From 364df36ac40b28f172f2bb0b821befeefd306246 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Mon, 8 Jul 2024 22:37:20 +0800 Subject: [PATCH 001/325] feat: plugin call dify --- api/.env.example | 3 + api/configs/feature/__init__.py | 14 +++++ api/controllers/inner_api/__init__.py | 2 +- api/controllers/inner_api/plugin/__init__.py | 1 + api/controllers/inner_api/plugin/plugin.py | 59 +++++++++++++++++++ api/controllers/inner_api/plugin/wraps.py | 47 +++++++++++++++ .../inner_api/workspace/workspace.py | 4 +- api/controllers/inner_api/wraps.py | 20 ++++++- api/services/plugin/plugin_invoke_service.py | 16 +++++ 9 files changed, 161 insertions(+), 5 deletions(-) create mode 100644 api/controllers/inner_api/plugin/__init__.py create mode 100644 api/controllers/inner_api/plugin/plugin.py create mode 100644 api/controllers/inner_api/plugin/wraps.py create mode 100644 api/services/plugin/plugin_invoke_service.py diff --git a/api/.env.example b/api/.env.example index 573c8bf90c11a8..bdea20c5ffd9b6 100644 --- a/api/.env.example +++ b/api/.env.example @@ -238,3 +238,6 @@ WORKFLOW_CALL_MAX_DEPTH=5 # App configuration APP_MAX_EXECUTION_TIME=1200 +# Plugin configuration +PLUGIN_INNER_API_URL=http://127.0.0.1:5002 +PLUGIN_INNER_API_KEY=lYkiYYT6owG+71oLerGzA7GXCgOT++6ovaezWAjpCjf+Sjc3ZtU+qUEi diff --git a/api/configs/feature/__init__.py b/api/configs/feature/__init__.py index bd0ef983c4c5bf..2012b56c6251d8 100644 --- a/api/configs/feature/__init__.py +++ b/api/configs/feature/__init__.py @@ -47,6 +47,19 @@ class CodeExecutionSandboxConfig(BaseSettings): default='dify-sandbox', ) +class PluginConfig(BaseSettings): + """ + Plugin configs + """ + PLUGIN_INNER_API_URL: str = Field( + description='Plugin inner API URL', + default='http://plugin:8194', + ) + + PLUGIN_INNER_API_KEY: str = Field( + description='Plugin inner API key', + default='dify-inner-api-key', + ) class EndpointConfig(BaseSettings): """ @@ -431,6 +444,7 @@ class FeatureConfig( AppExecutionConfig, BillingConfig, CodeExecutionSandboxConfig, + PluginConfig, DataSetConfig, EndpointConfig, FileAccessConfig, diff --git a/api/controllers/inner_api/__init__.py b/api/controllers/inner_api/__init__.py index ad49a649caab66..32770aa0de6851 100644 --- a/api/controllers/inner_api/__init__.py +++ b/api/controllers/inner_api/__init__.py @@ -5,5 +5,5 @@ bp = Blueprint('inner_api', __name__, url_prefix='/inner/api') api = ExternalApi(bp) +from .plugin import plugin from .workspace import workspace - diff --git a/api/controllers/inner_api/plugin/__init__.py b/api/controllers/inner_api/plugin/__init__.py new file mode 100644 index 00000000000000..fd1918e6b26fee --- /dev/null +++ b/api/controllers/inner_api/plugin/__init__.py @@ -0,0 +1 @@ +from .plugin import * \ No newline at end of file diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py new file mode 100644 index 00000000000000..6ce860b877498a --- /dev/null +++ b/api/controllers/inner_api/plugin/plugin.py @@ -0,0 +1,59 @@ + +from flask_restful import Resource, reqparse + +from controllers.console.setup import setup_required +from controllers.inner_api import api +from controllers.inner_api.plugin.wraps import get_tenant +from controllers.inner_api.wraps import plugin_inner_api_only +from libs.helper import compact_generate_response +from models.account import Tenant +from services.plugin.plugin_invoke_service import PluginInvokeService + + +class PluginInvokeModelApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + def post(self, user_id: str, tenant_model: Tenant): + parser = reqparse.RequestParser() + parser.add_argument('provider', type=dict, required=True, location='json') + parser.add_argument('model', type=dict, required=True, location='json') + parser.add_argument('parameters', type=dict, required=True, location='json') + + args = parser.parse_args() + + +class PluginInvokeToolApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + def post(self, user_id: str, tenant_model: Tenant): + parser = reqparse.RequestParser() + parser.add_argument('provider', type=dict, required=True, location='json') + parser.add_argument('tool', type=dict, required=True, location='json') + parser.add_argument('parameters', type=dict, required=True, location='json') + + args = parser.parse_args() + + response = PluginInvokeService.invoke_tool(user_id, tenant_model, + args['provider'], args['tool'], + args['parameters']) + return compact_generate_response(response) + + +class PluginInvokeNodeApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + def post(self, user_id: str, tenant_model: Tenant): + parser = reqparse.RequestParser() + args = parser.parse_args() + + return { + 'message': 'success' + } + + +api.add_resource(PluginInvokeModelApi, '/invoke/model') +api.add_resource(PluginInvokeToolApi, '/invoke/tool') +api.add_resource(PluginInvokeNodeApi, '/invoke/node') diff --git a/api/controllers/inner_api/plugin/wraps.py b/api/controllers/inner_api/plugin/wraps.py new file mode 100644 index 00000000000000..d604e84a9dcc5e --- /dev/null +++ b/api/controllers/inner_api/plugin/wraps.py @@ -0,0 +1,47 @@ +from collections.abc import Callable +from functools import wraps +from typing import Optional + +from flask_restful import reqparse + +from extensions.ext_database import db +from models.account import Tenant + + +def get_tenant(view: Optional[Callable] = None): + def decorator(view_func): + @wraps(view_func) + def decorated_view(*args, **kwargs): + # fetch json body + parser = reqparse.RequestParser() + parser.add_argument('tenant_id', type=str, required=True, location='json') + parser.add_argument('user_id', type=str, required=True, location='json') + + kwargs = parser.parse_args() + + user_id = kwargs.get('user_id') + tenant_id = kwargs.get('tenant_id') + + del kwargs['tenant_id'] + del kwargs['user_id'] + + try: + tenant_model = db.session.query(Tenant).filter( + Tenant.id == tenant_id, + ).first() + except Exception: + raise ValueError('tenant not found') + + if not tenant_model: + raise ValueError('tenant not found') + + kwargs['tenant_model'] = tenant_model + kwargs['user_id'] = user_id + + return view_func(*args, **kwargs) + return decorated_view + + if view is None: + return decorator + else: + return decorator(view) diff --git a/api/controllers/inner_api/workspace/workspace.py b/api/controllers/inner_api/workspace/workspace.py index 06610d89330837..791d37f8686ef2 100644 --- a/api/controllers/inner_api/workspace/workspace.py +++ b/api/controllers/inner_api/workspace/workspace.py @@ -2,7 +2,7 @@ from controllers.console.setup import setup_required from controllers.inner_api import api -from controllers.inner_api.wraps import inner_api_only +from controllers.inner_api.wraps import enterprise_inner_api_only from events.tenant_event import tenant_was_created from models.account import Account from services.account_service import TenantService @@ -11,7 +11,7 @@ class EnterpriseWorkspace(Resource): @setup_required - @inner_api_only + @enterprise_inner_api_only def post(self): parser = reqparse.RequestParser() parser.add_argument('name', type=str, required=True, location='json') diff --git a/api/controllers/inner_api/wraps.py b/api/controllers/inner_api/wraps.py index 07cd38bc8561e9..0793a67eec01a5 100644 --- a/api/controllers/inner_api/wraps.py +++ b/api/controllers/inner_api/wraps.py @@ -5,11 +5,12 @@ from flask import abort, current_app, request +from configs import dify_config from extensions.ext_database import db from models.model import EndUser -def inner_api_only(view): +def enterprise_inner_api_only(view): @wraps(view) def decorated(*args, **kwargs): if not current_app.config['INNER_API']: @@ -25,7 +26,7 @@ def decorated(*args, **kwargs): return decorated -def inner_api_user_auth(view): +def enterprise_inner_api_user_auth(view): @wraps(view) def decorated(*args, **kwargs): if not current_app.config['INNER_API']: @@ -59,3 +60,18 @@ def decorated(*args, **kwargs): return view(*args, **kwargs) return decorated + +def plugin_inner_api_only(view): + @wraps(view) + def decorated(*args, **kwargs): + if not dify_config.PLUGIN_INNER_API_KEY: + abort(404) + + # get header 'X-Inner-Api-Key' + inner_api_key = request.headers.get('X-Inner-Api-Key') + if not inner_api_key or inner_api_key != dify_config.PLUGIN_INNER_API_KEY: + abort(404) + + return view(*args, **kwargs) + + return decorated \ No newline at end of file diff --git a/api/services/plugin/plugin_invoke_service.py b/api/services/plugin/plugin_invoke_service.py new file mode 100644 index 00000000000000..131de1ec1a5a0a --- /dev/null +++ b/api/services/plugin/plugin_invoke_service.py @@ -0,0 +1,16 @@ +from collections.abc import Generator +from typing import Any + +from core.tools.entities.tool_entities import ToolInvokeMessage +from models.account import Tenant + + +class PluginInvokeService: + @classmethod + def invoke_tool(cls, user_id: str, tenant: Tenant, + tool_provider: str, tool_name: str, + tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage]: + """ + Invokes a tool with the given user ID and tool parameters. + """ + \ No newline at end of file From 563d81277b74fb6e87bbcdf5f81b6e3832112fdd Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 9 Jul 2024 15:37:56 +0800 Subject: [PATCH 002/325] refactor: tool response to generator --- api/controllers/inner_api/plugin/plugin.py | 2 + api/core/agent/entities.py | 6 +- .../plugin_tool_callback_handler.py | 5 ++ api/core/tools/tool/api_tool.py | 5 +- api/core/tools/tool/dataset_retriever_tool.py | 5 +- api/core/tools/tool/tool.py | 8 +-- api/core/tools/tool/workflow_tool.py | 12 ++-- api/core/tools/tool_engine.py | 66 +++++++++++++++---- api/core/tools/tool_manager.py | 50 ++++---------- api/core/tools/utils/configuration.py | 7 +- api/core/tools/utils/message_transformer.py | 41 ++++++------ api/core/workflow/nodes/tool/entities.py | 3 +- api/core/workflow/nodes/tool/tool_node.py | 2 +- api/services/plugin/plugin_invoke_service.py | 43 ++++++++++-- api/services/tools/tools_transform_service.py | 32 ++++++--- 15 files changed, 177 insertions(+), 110 deletions(-) create mode 100644 api/core/callback_handler/plugin_tool_callback_handler.py diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index 6ce860b877498a..95500ea9f375e9 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -21,6 +21,8 @@ def post(self, user_id: str, tenant_model: Tenant): parser.add_argument('parameters', type=dict, required=True, location='json') args = parser.parse_args() + + class PluginInvokeToolApi(Resource): diff --git a/api/core/agent/entities.py b/api/core/agent/entities.py index 5274224de5772c..189c925d828d1b 100644 --- a/api/core/agent/entities.py +++ b/api/core/agent/entities.py @@ -1,14 +1,16 @@ from enum import Enum -from typing import Any, Literal, Optional, Union +from typing import Any, Optional, Union from pydantic import BaseModel +from core.tools.entities.tool_entities import ToolProviderType + class AgentToolEntity(BaseModel): """ Agent Tool Entity. """ - provider_type: Literal["builtin", "api", "workflow"] + provider_type: ToolProviderType provider_id: str tool_name: str tool_parameters: dict[str, Any] = {} diff --git a/api/core/callback_handler/plugin_tool_callback_handler.py b/api/core/callback_handler/plugin_tool_callback_handler.py new file mode 100644 index 00000000000000..e9b9784014fe35 --- /dev/null +++ b/api/core/callback_handler/plugin_tool_callback_handler.py @@ -0,0 +1,5 @@ +from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler + + +class DifyPluginCallbackHandler(DifyAgentCallbackHandler): + """Callback Handler that prints to std out.""" \ No newline at end of file diff --git a/api/core/tools/tool/api_tool.py b/api/core/tools/tool/api_tool.py index c8b683f9ef14ac..1d600d5efc26e7 100644 --- a/api/core/tools/tool/api_tool.py +++ b/api/core/tools/tool/api_tool.py @@ -1,4 +1,5 @@ import json +from collections.abc import Generator from os import getenv from typing import Any from urllib.parse import urlencode @@ -269,7 +270,7 @@ def _convert_body_property_type(self, property: dict[str, Any], value: Any) -> A except ValueError as e: return value - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage, None, None]: """ invoke http request """ @@ -283,4 +284,4 @@ def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMe response = self.validate_and_parse_response(response) # assemble invoke message - return self.create_text_message(response) + yield self.create_text_message(response) diff --git a/api/core/tools/tool/dataset_retriever_tool.py b/api/core/tools/tool/dataset_retriever_tool.py index 1170e1b7a5f065..3e81d84c92a479 100644 --- a/api/core/tools/tool/dataset_retriever_tool.py +++ b/api/core/tools/tool/dataset_retriever_tool.py @@ -1,3 +1,4 @@ +from collections.abc import Generator from typing import Any from core.app.app_config.entities import DatasetRetrieveConfigEntity @@ -86,7 +87,7 @@ def get_runtime_parameters(self) -> list[ToolParameter]: def tool_provider_type(self) -> ToolProviderType: return ToolProviderType.DATASET_RETRIEVAL - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage, None, None]: """ invoke dataset retriever tool """ @@ -97,7 +98,7 @@ def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMe # invoke dataset retriever tool result = self.retrival_tool._run(query=query) - return self.create_text_message(text=result) + yield self.create_text_message(text=result) def validate_credentials(self, credentials: dict[str, Any], parameters: dict[str, Any]) -> None: """ diff --git a/api/core/tools/tool/tool.py b/api/core/tools/tool/tool.py index 04c09c7f5b8238..291cac5ee3f848 100644 --- a/api/core/tools/tool/tool.py +++ b/api/core/tools/tool/tool.py @@ -1,4 +1,5 @@ from abc import ABC, abstractmethod +from collections.abc import Generator from copy import deepcopy from enum import Enum from typing import Any, Optional, Union @@ -190,7 +191,7 @@ def list_default_image_variables(self) -> list[ToolRuntimeVariable]: return result - def invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> list[ToolInvokeMessage]: + def invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage]: # update tool_parameters if self.runtime.runtime_parameters: tool_parameters.update(self.runtime.runtime_parameters) @@ -203,9 +204,6 @@ def invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> list[ToolInvo tool_parameters=tool_parameters, ) - if not isinstance(result, list): - result = [result] - return result def _transform_tool_parameters_type(self, tool_parameters: dict[str, Any]) -> dict[str, Any]: @@ -221,7 +219,7 @@ def _transform_tool_parameters_type(self, tool_parameters: dict[str, Any]) -> di return result @abstractmethod - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage, None, None]: pass def validate_credentials(self, credentials: dict[str, Any], parameters: dict[str, Any]) -> None: diff --git a/api/core/tools/tool/workflow_tool.py b/api/core/tools/tool/workflow_tool.py index 071081303c3b2a..d0a9df64799776 100644 --- a/api/core/tools/tool/workflow_tool.py +++ b/api/core/tools/tool/workflow_tool.py @@ -1,5 +1,6 @@ import json import logging +from collections.abc import Generator from copy import deepcopy from typing import Any, Union @@ -34,7 +35,7 @@ def tool_provider_type(self) -> ToolProviderType: def _invoke( self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: + ) -> Generator[ToolInvokeMessage, None, None]: """ invoke the tool """ @@ -46,6 +47,7 @@ def _invoke( from core.app.apps.workflow.app_generator import WorkflowAppGenerator generator = WorkflowAppGenerator() + result = generator.generate( app_model=app, workflow=workflow, @@ -64,16 +66,12 @@ def _invoke( if data.get('error'): raise Exception(data.get('error')) - result = [] - outputs = data.get('outputs', {}) outputs, files = self._extract_files(outputs) for file in files: - result.append(self.create_file_var_message(file)) + yield self.create_file_var_message(file) - result.append(self.create_text_message(json.dumps(outputs, ensure_ascii=False))) - - return result + yield self.create_text_message(json.dumps(outputs, ensure_ascii=False)) def _get_user(self, user_id: str) -> Union[EndUser, Account]: """ diff --git a/api/core/tools/tool_engine.py b/api/core/tools/tool_engine.py index 7615368934bfe5..7d94eedc5fd9b4 100644 --- a/api/core/tools/tool_engine.py +++ b/api/core/tools/tool_engine.py @@ -1,4 +1,5 @@ import json +from collections.abc import Generator from copy import deepcopy from datetime import datetime, timezone from mimetypes import guess_type @@ -8,6 +9,7 @@ from core.app.entities.app_invoke_entities import InvokeFrom from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler +from core.callback_handler.plugin_tool_callback_handler import DifyPluginCallbackHandler from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler from core.file.file_obj import FileTransferMethod from core.ops.ops_trace_manager import TraceQueueManager @@ -64,16 +66,25 @@ def agent_invoke( tool_inputs=tool_parameters ) - meta, response = ToolEngine._invoke(tool, tool_parameters, user_id) - response = ToolFileMessageTransformer.transform_tool_invoke_messages( - messages=response, - user_id=user_id, - tenant_id=tenant_id, + messages = ToolEngine._invoke(tool, tool_parameters, user_id) + invocation_meta_dict = {'meta': None} + + def message_callback(invocation_meta_dict: dict, messages: Generator[ToolInvokeMessage, None, None]): + for message in messages: + if isinstance(message, ToolInvokeMeta): + invocation_meta_dict['meta'] = message + else: + yield message + + messages = ToolFileMessageTransformer.transform_tool_invoke_messages( + messages=message_callback(invocation_meta_dict, messages), + user_id=user_id, + tenant_id=tenant_id, conversation_id=message.conversation_id ) # extract binary data from tool invoke message - binary_files = ToolEngine._extract_tool_response_binary(response) + binary_files = ToolEngine._extract_tool_response_binary(messages) # create message file message_files = ToolEngine._create_message_files( tool_messages=binary_files, @@ -82,7 +93,9 @@ def agent_invoke( user_id=user_id ) - plain_text = ToolEngine._convert_tool_response_to_str(response) + plain_text = ToolEngine._convert_tool_response_to_str(messages) + + meta = invocation_meta_dict['meta'] # hit the callback handler agent_tool_callback.on_tool_end( @@ -127,7 +140,7 @@ def workflow_invoke(tool: Tool, tool_parameters: dict, user_id: str, workflow_id: str, workflow_tool_callback: DifyWorkflowCallbackHandler, workflow_call_depth: int, - ) -> list[ToolInvokeMessage]: + ) -> Generator[ToolInvokeMessage, None, None]: """ Workflow invokes the tool with the given arguments. """ @@ -154,10 +167,38 @@ def workflow_invoke(tool: Tool, tool_parameters: dict, except Exception as e: workflow_tool_callback.on_tool_error(e) raise e - + + @staticmethod + def plugin_invoke(tool: Tool, tool_parameters: dict, user_id: str, + callback: DifyPluginCallbackHandler + ) -> Generator[ToolInvokeMessage, None, None]: + """ + Plugin invokes the tool with the given arguments. + """ + try: + # hit the callback handler + callback.on_tool_start( + tool_name=tool.identity.name, + tool_inputs=tool_parameters + ) + + response = tool.invoke(user_id, tool_parameters) + + # hit the callback handler + callback.on_tool_end( + tool_name=tool.identity.name, + tool_inputs=tool_parameters, + tool_outputs=response, + ) + + return response + except Exception as e: + callback.on_tool_error(e) + raise e + @staticmethod def _invoke(tool: Tool, tool_parameters: dict, user_id: str) \ - -> tuple[ToolInvokeMeta, list[ToolInvokeMessage]]: + -> Generator[ToolInvokeMessage | ToolInvokeMeta, None, None]: """ Invoke the tool with the given arguments. """ @@ -170,16 +211,15 @@ def _invoke(tool: Tool, tool_parameters: dict, user_id: str) \ 'tool_icon': tool.identity.icon }) try: - response = tool.invoke(user_id, tool_parameters) + yield from tool.invoke(user_id, tool_parameters) except Exception as e: meta.error = str(e) raise ToolEngineInvokeError(meta) finally: ended_at = datetime.now(timezone.utc) meta.time_cost = (ended_at - started_at).total_seconds() + yield meta - return meta, response - @staticmethod def _convert_tool_response_to_str(tool_response: list[ToolInvokeMessage]) -> str: """ diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index e30a905cbcf309..5822841db747c9 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -18,6 +18,7 @@ ApiProviderAuthType, ToolInvokeFrom, ToolParameter, + ToolProviderType, ) from core.tools.errors import ToolProviderNotFoundError from core.tools.provider.api_tool_provider import ApiToolProviderController @@ -26,6 +27,7 @@ from core.tools.tool.api_tool import ApiTool from core.tools.tool.builtin_tool import BuiltinTool from core.tools.tool.tool import Tool +from core.tools.tool.workflow_tool import WorkflowTool from core.tools.tool_label_manager import ToolLabelManager from core.tools.utils.configuration import ( ToolConfigurationManager, @@ -78,37 +80,13 @@ def get_builtin_tool(cls, provider: str, tool_name: str) -> BuiltinTool: return tool @classmethod - def get_tool(cls, provider_type: str, provider_id: str, tool_name: str, tenant_id: str = None) \ - -> Union[BuiltinTool, ApiTool]: - """ - get the tool - - :param provider_type: the type of the provider - :param provider_name: the name of the provider - :param tool_name: the name of the tool - - :return: the tool - """ - if provider_type == 'builtin': - return cls.get_builtin_tool(provider_id, tool_name) - elif provider_type == 'api': - if tenant_id is None: - raise ValueError('tenant id is required for api provider') - api_provider, _ = cls.get_api_provider_controller(tenant_id, provider_id) - return api_provider.get_tool(tool_name) - elif provider_type == 'app': - raise NotImplementedError('app provider not implemented') - else: - raise ToolProviderNotFoundError(f'provider type {provider_type} not found') - - @classmethod - def get_tool_runtime(cls, provider_type: str, + def get_tool_runtime(cls, provider_type: ToolProviderType, provider_id: str, tool_name: str, tenant_id: str, invoke_from: InvokeFrom = InvokeFrom.DEBUGGER, tool_invoke_from: ToolInvokeFrom = ToolInvokeFrom.AGENT) \ - -> Union[BuiltinTool, ApiTool]: + -> Union[BuiltinTool, ApiTool, WorkflowTool]: """ get the tool runtime @@ -118,7 +96,7 @@ def get_tool_runtime(cls, provider_type: str, :return: the tool """ - if provider_type == 'builtin': + if provider_type == ToolProviderType.BUILT_IN: builtin_tool = cls.get_builtin_tool(provider_id, tool_name) # check if the builtin tool need credentials @@ -155,7 +133,7 @@ def get_tool_runtime(cls, provider_type: str, 'tool_invoke_from': tool_invoke_from, }) - elif provider_type == 'api': + elif provider_type == ToolProviderType.API: if tenant_id is None: raise ValueError('tenant id is required for api provider') @@ -171,7 +149,7 @@ def get_tool_runtime(cls, provider_type: str, 'invoke_from': invoke_from, 'tool_invoke_from': tool_invoke_from, }) - elif provider_type == 'workflow': + elif provider_type == ToolProviderType.WORKFLOW: workflow_provider = db.session.query(WorkflowToolProvider).filter( WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.id == provider_id @@ -190,10 +168,10 @@ def get_tool_runtime(cls, provider_type: str, 'invoke_from': invoke_from, 'tool_invoke_from': tool_invoke_from, }) - elif provider_type == 'app': + elif provider_type == ToolProviderType.APP: raise NotImplementedError('app provider not implemented') else: - raise ToolProviderNotFoundError(f'provider type {provider_type} not found') + raise ToolProviderNotFoundError(f'provider type {provider_type.value} not found') @classmethod def _init_runtime_parameter(cls, parameter_rule: ToolParameter, parameters: dict) -> Union[str, int, float, bool]: @@ -554,7 +532,7 @@ def user_get_api_provider(cls, provider: str, tenant_id: str) -> dict: }) @classmethod - def get_tool_icon(cls, tenant_id: str, provider_type: str, provider_id: str) -> Union[str, dict]: + def get_tool_icon(cls, tenant_id: str, provider_type: ToolProviderType, provider_id: str) -> Union[str, dict]: """ get the tool icon @@ -563,14 +541,12 @@ def get_tool_icon(cls, tenant_id: str, provider_type: str, provider_id: str) -> :param provider_id: the id of the provider :return: """ - provider_type = provider_type - provider_id = provider_id - if provider_type == 'builtin': + if provider_type == ToolProviderType.BUILT_IN: return (current_app.config.get("CONSOLE_API_URL") + "/console/api/workspaces/current/tool-provider/builtin/" + provider_id + "/icon") - elif provider_type == 'api': + elif provider_type == ToolProviderType.API: try: provider: ApiToolProvider = db.session.query(ApiToolProvider).filter( ApiToolProvider.tenant_id == tenant_id, @@ -582,7 +558,7 @@ def get_tool_icon(cls, tenant_id: str, provider_type: str, provider_id: str) -> "background": "#252525", "content": "\ud83d\ude01" } - elif provider_type == 'workflow': + elif provider_type == ToolProviderType.WORKFLOW: provider: WorkflowToolProvider = db.session.query(WorkflowToolProvider).filter( WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.id == provider_id diff --git a/api/core/tools/utils/configuration.py b/api/core/tools/utils/configuration.py index b213879e960b14..68b0cea24f97eb 100644 --- a/api/core/tools/utils/configuration.py +++ b/api/core/tools/utils/configuration.py @@ -9,6 +9,7 @@ from core.tools.entities.tool_entities import ( ToolParameter, ToolProviderCredentials, + ToolProviderType, ) from core.tools.provider.tool_provider import ToolProviderController from core.tools.tool.tool import Tool @@ -108,7 +109,7 @@ class ToolParameterConfigurationManager(BaseModel): tenant_id: str tool_runtime: Tool provider_name: str - provider_type: str + provider_type: ToolProviderType identity_id: str def _deep_copy(self, parameters: dict[str, Any]) -> dict[str, Any]: @@ -191,7 +192,7 @@ def decrypt_tool_parameters(self, parameters: dict[str, Any]) -> dict[str, Any]: """ cache = ToolParameterCache( tenant_id=self.tenant_id, - provider=f'{self.provider_type}.{self.provider_name}', + provider=f'{self.provider_type.value}.{self.provider_name}', tool_name=self.tool_runtime.identity.name, cache_type=ToolParameterCacheType.PARAMETER, identity_id=self.identity_id @@ -221,7 +222,7 @@ def decrypt_tool_parameters(self, parameters: dict[str, Any]) -> dict[str, Any]: def delete_tool_parameters_cache(self): cache = ToolParameterCache( tenant_id=self.tenant_id, - provider=f'{self.provider_type}.{self.provider_name}', + provider=f'{self.provider_type.value}.{self.provider_name}', tool_name=self.tool_runtime.identity.name, cache_type=ToolParameterCacheType.PARAMETER, identity_id=self.identity_id diff --git a/api/core/tools/utils/message_transformer.py b/api/core/tools/utils/message_transformer.py index ef9e5b67ae2ab6..770abc683c581c 100644 --- a/api/core/tools/utils/message_transformer.py +++ b/api/core/tools/utils/message_transformer.py @@ -1,4 +1,5 @@ import logging +from collections.abc import Generator from mimetypes import guess_extension from core.file.file_obj import FileTransferMethod, FileType, FileVar @@ -9,20 +10,18 @@ class ToolFileMessageTransformer: @classmethod - def transform_tool_invoke_messages(cls, messages: list[ToolInvokeMessage], + def transform_tool_invoke_messages(cls, messages: Generator[ToolInvokeMessage, None, None], user_id: str, tenant_id: str, - conversation_id: str) -> list[ToolInvokeMessage]: + conversation_id: str) -> Generator[ToolInvokeMessage, None, None]: """ Transform tool message and handle file download """ - result = [] - for message in messages: if message.type == ToolInvokeMessage.MessageType.TEXT: - result.append(message) + yield message elif message.type == ToolInvokeMessage.MessageType.LINK: - result.append(message) + yield message elif message.type == ToolInvokeMessage.MessageType.IMAGE: # try to download image try: @@ -35,20 +34,20 @@ def transform_tool_invoke_messages(cls, messages: list[ToolInvokeMessage], url = f'/files/tools/{file.id}{guess_extension(file.mimetype) or ".png"}' - result.append(ToolInvokeMessage( + yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.IMAGE_LINK, message=url, save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, - )) + ) except Exception as e: logger.exception(e) - result.append(ToolInvokeMessage( + yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.TEXT, message=f"Failed to download image: {message.message}, you can try to download it yourself.", meta=message.meta.copy() if message.meta is not None else {}, save_as=message.save_as, - )) + ) elif message.type == ToolInvokeMessage.MessageType.BLOB: # get mime type and save blob to storage mimetype = message.meta.get('mime_type', 'octet/stream') @@ -67,43 +66,41 @@ def transform_tool_invoke_messages(cls, messages: list[ToolInvokeMessage], # check if file is image if 'image' in mimetype: - result.append(ToolInvokeMessage( + yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.IMAGE_LINK, message=url, save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, - )) + ) else: - result.append(ToolInvokeMessage( + yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.LINK, message=url, save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, - )) + ) elif message.type == ToolInvokeMessage.MessageType.FILE_VAR: file_var: FileVar = message.meta.get('file_var') if file_var: if file_var.transfer_method == FileTransferMethod.TOOL_FILE: url = cls.get_tool_file_url(file_var.related_id, file_var.extension) if file_var.type == FileType.IMAGE: - result.append(ToolInvokeMessage( + yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.IMAGE_LINK, message=url, save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, - )) + ) else: - result.append(ToolInvokeMessage( + yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.LINK, message=url, save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, - )) + ) else: - result.append(message) - - return result + yield message @classmethod def get_tool_file_url(cls, tool_file_id: str, extension: str) -> str: - return f'/files/tools/{tool_file_id}{extension or ".bin"}' \ No newline at end of file + return f'/files/tools/{tool_file_id}{extension or ".bin"}' diff --git a/api/core/workflow/nodes/tool/entities.py b/api/core/workflow/nodes/tool/entities.py index 2e4743c483229f..bc9bfde4db4a0d 100644 --- a/api/core/workflow/nodes/tool/entities.py +++ b/api/core/workflow/nodes/tool/entities.py @@ -3,12 +3,13 @@ from pydantic import BaseModel, field_validator from pydantic_core.core_schema import ValidationInfo +from core.tools.entities.tool_entities import ToolProviderType from core.workflow.entities.base_node_data_entities import BaseNodeData class ToolEntity(BaseModel): provider_id: str - provider_type: Literal['builtin', 'api', 'workflow'] + provider_type: ToolProviderType provider_name: str # redundancy tool_name: str tool_label: str # redundancy diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index cddea03bf862ad..f77ccd9bd677b6 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -32,7 +32,7 @@ def _run(self, variable_pool: VariablePool) -> NodeRunResult: # fetch tool icon tool_info = { - 'provider_type': node_data.provider_type, + 'provider_type': node_data.provider_type.value, 'provider_id': node_data.provider_id } diff --git a/api/services/plugin/plugin_invoke_service.py b/api/services/plugin/plugin_invoke_service.py index 131de1ec1a5a0a..317b42a6e16f75 100644 --- a/api/services/plugin/plugin_invoke_service.py +++ b/api/services/plugin/plugin_invoke_service.py @@ -1,16 +1,49 @@ from collections.abc import Generator -from typing import Any +from typing import Any, Union -from core.tools.entities.tool_entities import ToolInvokeMessage +from core.app.entities.app_invoke_entities import InvokeFrom +from core.callback_handler.plugin_tool_callback_handler import DifyPluginCallbackHandler +from core.model_runtime.entities.model_entities import ModelType +from core.tools.entities.tool_entities import ToolInvokeMessage, ToolProviderType +from core.tools.tool_engine import ToolEngine +from core.tools.tool_manager import ToolManager +from core.tools.utils.message_transformer import ToolFileMessageTransformer +from core.workflow.entities.node_entities import NodeType from models.account import Tenant +from services.tools.tools_transform_service import ToolTransformService class PluginInvokeService: @classmethod - def invoke_tool(cls, user_id: str, tenant: Tenant, - tool_provider: str, tool_name: str, + def invoke_tool(cls, user_id: str, invoke_from: InvokeFrom, tenant: Tenant, + tool_provider_type: ToolProviderType, tool_provider: str, tool_name: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage]: """ Invokes a tool with the given user ID and tool parameters. """ - \ No newline at end of file + tool_runtime = ToolManager.get_tool_runtime(tool_provider_type, provider_id=tool_provider, + tool_name=tool_name, tenant_id=tenant.id, + invoke_from=invoke_from) + + response = ToolEngine.plugin_invoke(tool_runtime, + tool_parameters, + user_id, + callback=DifyPluginCallbackHandler()) + response = ToolFileMessageTransformer.transform_tool_invoke_messages(response) + return ToolTransformService.transform_messages_to_dict(response) + + @classmethod + def invoke_model(cls, user_id: str, tenant: Tenant, + model_provider: str, model_name: str, model_type: ModelType, + model_parameters: dict[str, Any]) -> Union[dict, Generator[ToolInvokeMessage]]: + """ + Invokes a model with the given user ID and model parameters. + """ + + @classmethod + def invoke_workflow_node(cls, user_id: str, tenant: Tenant, + node_type: NodeType, node_data: dict[str, Any], + inputs: dict[str, Any]) -> Generator[ToolInvokeMessage]: + """ + Invokes a workflow node with the given user ID and node parameters. + """ \ No newline at end of file diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index 5c777324689341..08023a4a92dfda 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -1,5 +1,6 @@ import json import logging +from collections.abc import Generator from typing import Optional, Union from flask import current_app @@ -9,6 +10,7 @@ from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( ApiProviderAuthType, + ToolInvokeMessage, ToolParameter, ToolProviderCredentials, ToolProviderType, @@ -24,8 +26,8 @@ logger = logging.getLogger(__name__) class ToolTransformService: - @staticmethod - def get_tool_provider_icon_url(provider_type: str, provider_name: str, icon: str) -> Union[str, dict]: + @classmethod + def get_tool_provider_icon_url(cls, provider_type: str, provider_name: str, icon: str) -> Union[str, dict]: """ get tool provider icon url """ @@ -45,8 +47,8 @@ def get_tool_provider_icon_url(provider_type: str, provider_name: str, icon: str return '' - @staticmethod - def repack_provider(provider: Union[dict, UserToolProvider]): + @classmethod + def repack_provider(cls, provider: Union[dict, UserToolProvider]): """ repack provider @@ -65,8 +67,9 @@ def repack_provider(provider: Union[dict, UserToolProvider]): icon=provider.icon ) - @staticmethod + @classmethod def builtin_provider_to_user_provider( + cls, provider_controller: BuiltinToolProviderController, db_provider: Optional[BuiltinToolProvider], decrypt_credentials: bool = True, @@ -126,8 +129,9 @@ def builtin_provider_to_user_provider( return result - @staticmethod + @classmethod def api_provider_to_controller( + cls, db_provider: ApiToolProvider, ) -> ApiToolProviderController: """ @@ -142,8 +146,9 @@ def api_provider_to_controller( return controller - @staticmethod + @classmethod def workflow_provider_to_controller( + cls, db_provider: WorkflowToolProvider ) -> WorkflowToolProviderController: """ @@ -179,8 +184,9 @@ def workflow_provider_to_user_provider( labels=labels or [] ) - @staticmethod + @classmethod def api_provider_to_user_provider( + cls, provider_controller: ApiToolProviderController, db_provider: ApiToolProvider, decrypt_credentials: bool = True, @@ -231,8 +237,9 @@ def api_provider_to_user_provider( return result - @staticmethod + @classmethod def tool_to_user_tool( + cls, tool: Union[ApiToolBundle, WorkflowTool, Tool], credentials: dict = None, tenant_id: str = None, @@ -287,4 +294,9 @@ def tool_to_user_tool( ), parameters=tool.parameters, labels=labels - ) \ No newline at end of file + ) + + @classmethod + def transform_messages_to_dict(cls, responses: Generator[ToolInvokeMessage, None, None]): + for response in responses: + yield response.model_dump() \ No newline at end of file From e1db77eec2fae8542c96e009647ae24d29ee74e7 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Mon, 15 Jul 2024 16:00:11 +0800 Subject: [PATCH 003/325] fix --- api/core/agent/entities.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/api/core/agent/entities.py b/api/core/agent/entities.py index 189c925d828d1b..776e40e9fee753 100644 --- a/api/core/agent/entities.py +++ b/api/core/agent/entities.py @@ -76,5 +76,5 @@ class Strategy(Enum): model: str strategy: Strategy prompt: Optional[AgentPromptEntity] = None - tools: list[AgentToolEntity] = None + tools: Optional[list[AgentToolEntity]] = None max_iteration: int = 5 From f29b44acd807734eba64dd8c6a6ffbcf4e2150c4 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Mon, 29 Jul 2024 16:40:04 +0800 Subject: [PATCH 004/325] feat: support plugin inner api --- api/controllers/inner_api/plugin/plugin.py | 73 ++++++--- api/controllers/inner_api/plugin/wraps.py | 25 +++ api/core/plugin/entities/request.py | 42 +++++ api/core/tools/entities/tool_entities.py | 13 +- api/core/tools/tool/tool.py | 175 ++++++++++----------- 5 files changed, 210 insertions(+), 118 deletions(-) create mode 100644 api/core/plugin/entities/request.py diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index 95500ea9f375e9..cc2a49a41fb050 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -1,34 +1,68 @@ - from flask_restful import Resource, reqparse from controllers.console.setup import setup_required from controllers.inner_api import api -from controllers.inner_api.plugin.wraps import get_tenant +from controllers.inner_api.plugin.wraps import get_tenant, plugin_data from controllers.inner_api.wraps import plugin_inner_api_only +from core.plugin.entities.request import RequestInvokeLLM, RequestInvokeModeration, RequestInvokeRerank, RequestInvokeSpeech2Text, RequestInvokeTTS, RequestInvokeTextEmbedding, RequestInvokeTool from libs.helper import compact_generate_response from models.account import Tenant from services.plugin.plugin_invoke_service import PluginInvokeService -class PluginInvokeModelApi(Resource): +class PluginInvokeLLMApi(Resource): @setup_required @plugin_inner_api_only @get_tenant - def post(self, user_id: str, tenant_model: Tenant): - parser = reqparse.RequestParser() - parser.add_argument('provider', type=dict, required=True, location='json') - parser.add_argument('model', type=dict, required=True, location='json') - parser.add_argument('parameters', type=dict, required=True, location='json') + @plugin_data(payload_type=RequestInvokeLLM) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeLLM): + pass - args = parser.parse_args() +class PluginInvokeTextEmbeddingApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + @plugin_data(payload_type=RequestInvokeTextEmbedding) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeTextEmbedding): + pass + +class PluginInvokeRerankApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + @plugin_data(payload_type=RequestInvokeRerank) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeRerank): + pass + +class PluginInvokeTTSApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + @plugin_data(payload_type=RequestInvokeTTS) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeTTS): + pass + +class PluginInvokeSpeech2TextApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + @plugin_data(payload_type=RequestInvokeSpeech2Text) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeSpeech2Text): + pass - - +class PluginInvokeModerationApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + @plugin_data(payload_type=RequestInvokeModeration) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeModeration): + pass class PluginInvokeToolApi(Resource): @setup_required @plugin_inner_api_only @get_tenant + @plugin_data(payload_type=RequestInvokeTool) def post(self, user_id: str, tenant_model: Tenant): parser = reqparse.RequestParser() parser.add_argument('provider', type=dict, required=True, location='json') @@ -37,9 +71,9 @@ def post(self, user_id: str, tenant_model: Tenant): args = parser.parse_args() - response = PluginInvokeService.invoke_tool(user_id, tenant_model, - args['provider'], args['tool'], - args['parameters']) + response = PluginInvokeService.invoke_tool( + user_id, tenant_model, args['provider'], args['tool'], args['parameters'] + ) return compact_generate_response(response) @@ -51,11 +85,14 @@ def post(self, user_id: str, tenant_model: Tenant): parser = reqparse.RequestParser() args = parser.parse_args() - return { - 'message': 'success' - } + return {'message': 'success'} -api.add_resource(PluginInvokeModelApi, '/invoke/model') +api.add_resource(PluginInvokeLLMApi, '/invoke/llm') +api.add_resource(PluginInvokeTextEmbeddingApi, '/invoke/text-embedding') +api.add_resource(PluginInvokeRerankApi, '/invoke/rerank') +api.add_resource(PluginInvokeTTSApi, '/invoke/tts') +api.add_resource(PluginInvokeSpeech2TextApi, '/invoke/speech2text') +api.add_resource(PluginInvokeModerationApi, '/invoke/moderation') api.add_resource(PluginInvokeToolApi, '/invoke/tool') api.add_resource(PluginInvokeNodeApi, '/invoke/node') diff --git a/api/controllers/inner_api/plugin/wraps.py b/api/controllers/inner_api/plugin/wraps.py index d604e84a9dcc5e..eb753218ff0b0b 100644 --- a/api/controllers/inner_api/plugin/wraps.py +++ b/api/controllers/inner_api/plugin/wraps.py @@ -2,7 +2,9 @@ from functools import wraps from typing import Optional +from flask import request from flask_restful import reqparse +from pydantic import BaseModel from extensions.ext_database import db from models.account import Tenant @@ -45,3 +47,26 @@ def decorated_view(*args, **kwargs): return decorator else: return decorator(view) + +def plugin_data(view: Optional[Callable] = None, *, payload_type: type[BaseModel]): + def decorator(view_func): + def decorated_view(*args, **kwargs): + try: + data = request.get_json() + except Exception: + raise ValueError('invalid json') + + try: + payload = payload_type(**data) + except Exception as e: + raise ValueError(f'invalid payload: {str(e)}') + + kwargs['payload'] = payload + return view_func(*args, **kwargs) + + return decorated_view + + if view is None: + return decorator + else: + return decorator(view) diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py new file mode 100644 index 00000000000000..62db6396a88e25 --- /dev/null +++ b/api/core/plugin/entities/request.py @@ -0,0 +1,42 @@ +from pydantic import BaseModel + + +class RequestInvokeTool(BaseModel): + """ + Request to invoke a tool + """ + +class RequestInvokeLLM(BaseModel): + """ + Request to invoke LLM + """ + +class RequestInvokeTextEmbedding(BaseModel): + """ + Request to invoke text embedding + """ + +class RequestInvokeRerank(BaseModel): + """ + Request to invoke rerank + """ + +class RequestInvokeTTS(BaseModel): + """ + Request to invoke TTS + """ + +class RequestInvokeSpeech2Text(BaseModel): + """ + Request to invoke speech2text + """ + +class RequestInvokeModeration(BaseModel): + """ + Request to invoke moderation + """ + +class RequestInvokeNode(BaseModel): + """ + Request to invoke node + """ \ No newline at end of file diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 569a1d3238f87f..5213f35a4b41c9 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -103,8 +103,8 @@ class MessageType(Enum): """ plain text, image url or link url """ - message: Union[str, bytes, dict] = None - meta: dict[str, Any] = None + message: Optional[Union[str, bytes, dict]] = None + meta: Optional[dict[str, Any]] = None save_as: str = '' class ToolInvokeMessageBinary(BaseModel): @@ -168,16 +168,19 @@ def get_simple_instance(cls, """ # convert options to ToolParameterOption if options: - options = [ToolParameterOption(value=option, label=I18nObject(en_US=option, zh_Hans=option)) for option in options] + option_objs = [ToolParameterOption(value=option, label=I18nObject(en_US=option, zh_Hans=option)) for option in options] + else: + option_objs = None return cls( name=name, label=I18nObject(en_US='', zh_Hans=''), + placeholder=None, human_description=I18nObject(en_US='', zh_Hans=''), type=type, form=cls.ToolParameterForm.LLM, llm_description=llm_description, required=required, - options=options, + options=option_objs, ) class ToolProviderIdentity(BaseModel): @@ -245,7 +248,7 @@ def to_dict(self) -> dict: 'default': self.default, 'options': self.options, 'help': self.help.to_dict() if self.help else None, - 'label': self.label.to_dict(), + 'label': self.label.to_dict() if self.label else None, 'url': self.url, 'placeholder': self.placeholder.to_dict() if self.placeholder else None, } diff --git a/api/core/tools/tool/tool.py b/api/core/tools/tool/tool.py index e679434bdebb5b..134016b28d17dc 100644 --- a/api/core/tools/tool/tool.py +++ b/api/core/tools/tool/tool.py @@ -40,8 +40,9 @@ def set_parameters(cls, v, validation_info: ValidationInfo) -> list[ToolParamete class Runtime(BaseModel): """ - Meta data of a tool call processing + Meta data of a tool call processing """ + def __init__(self, **data: Any): super().__init__(**data) if not self.runtime_parameters: @@ -65,10 +66,10 @@ class VARIABLE_KEY(Enum): def fork_tool_runtime(self, runtime: dict[str, Any]) -> 'Tool': """ - fork a new tool with meta data + fork a new tool with meta data - :param meta: the meta data of a tool call processing, tenant_id is required - :return: the new tool + :param meta: the meta data of a tool call processing, tenant_id is required + :return: the new tool """ return self.__class__( identity=self.identity.model_copy() if self.identity else None, @@ -76,82 +77,82 @@ def fork_tool_runtime(self, runtime: dict[str, Any]) -> 'Tool': description=self.description.model_copy() if self.description else None, runtime=Tool.Runtime(**runtime), ) - + @abstractmethod def tool_provider_type(self) -> ToolProviderType: """ - get the tool provider type + get the tool provider type - :return: the tool provider type + :return: the tool provider type """ - + def load_variables(self, variables: ToolRuntimeVariablePool): """ - load variables from database + load variables from database - :param conversation_id: the conversation id + :param conversation_id: the conversation id """ self.variables = variables def set_image_variable(self, variable_name: str, image_key: str) -> None: """ - set an image variable + set an image variable """ if not self.variables: return - + self.variables.set_file(self.identity.name, variable_name, image_key) def set_text_variable(self, variable_name: str, text: str) -> None: """ - set a text variable + set a text variable """ if not self.variables: return - + self.variables.set_text(self.identity.name, variable_name, text) - + def get_variable(self, name: Union[str, Enum]) -> Optional[ToolRuntimeVariable]: """ - get a variable + get a variable - :param name: the name of the variable - :return: the variable + :param name: the name of the variable + :return: the variable """ if not self.variables: return None - + if isinstance(name, Enum): name = name.value - + for variable in self.variables.pool: if variable.name == name: return variable - + return None def get_default_image_variable(self) -> Optional[ToolRuntimeVariable]: """ - get the default image variable + get the default image variable - :return: the image variable + :return: the image variable """ if not self.variables: return None - + return self.get_variable(self.VARIABLE_KEY.IMAGE) - + def get_variable_file(self, name: Union[str, Enum]) -> Optional[bytes]: """ - get a variable file + get a variable file - :param name: the name of the variable - :return: the variable file + :param name: the name of the variable + :return: the variable file """ variable = self.get_variable(name) if not variable: return None - + if not isinstance(variable, ToolRuntimeImageVariable): return None @@ -160,31 +161,31 @@ def get_variable_file(self, name: Union[str, Enum]) -> Optional[bytes]: file_binary = ToolFileManager.get_file_binary_by_message_file_id(message_file_id) if not file_binary: return None - + return file_binary[0] - + def list_variables(self) -> list[ToolRuntimeVariable]: """ - list all variables + list all variables - :return: the variables + :return: the variables """ if not self.variables: return [] - + return self.variables.pool - + def list_default_image_variables(self) -> list[ToolRuntimeVariable]: """ - list all image variables + list all image variables - :return: the image variables + :return: the image variables """ if not self.variables: return [] - + result = [] - + for variable in self.variables.pool: if variable.name.startswith(self.VARIABLE_KEY.IMAGE.value): result.append(variable) @@ -215,38 +216,40 @@ def _transform_tool_parameters_type(self, tool_parameters: Mapping[str, Any]) -> result = deepcopy(tool_parameters) for parameter in self.parameters or []: if parameter.name in tool_parameters: - result[parameter.name] = ToolParameterConverter.cast_parameter_by_type(tool_parameters[parameter.name], parameter.type) + result[parameter.name] = ToolParameterConverter.cast_parameter_by_type( + tool_parameters[parameter.name], parameter.type + ) return result @abstractmethod def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage, None, None]: pass - + def validate_credentials(self, credentials: dict[str, Any], parameters: dict[str, Any]) -> None: """ - validate the credentials + validate the credentials - :param credentials: the credentials - :param parameters: the parameters + :param credentials: the credentials + :param parameters: the parameters """ pass def get_runtime_parameters(self) -> list[ToolParameter]: """ - get the runtime parameters + get the runtime parameters - interface for developer to dynamic change the parameters of a tool depends on the variables pool + interface for developer to dynamic change the parameters of a tool depends on the variables pool - :return: the runtime parameters + :return: the runtime parameters """ return self.parameters or [] - + def get_all_runtime_parameters(self) -> list[ToolParameter]: """ - get all runtime parameters + get all runtime parameters - :return: all runtime parameters + :return: all runtime parameters """ parameters = self.parameters or [] parameters = parameters.copy() @@ -275,68 +278,50 @@ def get_all_runtime_parameters(self) -> list[ToolParameter]: parameters.append(parameter) return parameters - + def create_image_message(self, image: str, save_as: str = '') -> ToolInvokeMessage: """ - create an image message + create an image message - :param image: the url of the image - :return: the image message + :param image: the url of the image + :return: the image message """ - return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.IMAGE, - message=image, - save_as=save_as) - + return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.IMAGE, message=image, save_as=save_as) + def create_file_var_message(self, file_var: FileVar) -> ToolInvokeMessage: - return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.FILE_VAR, - message='', - meta={ - 'file_var': file_var - }, - save_as='') - + return ToolInvokeMessage( + type=ToolInvokeMessage.MessageType.FILE_VAR, message='', meta={'file_var': file_var}, save_as='' + ) + def create_link_message(self, link: str, save_as: str = '') -> ToolInvokeMessage: """ - create a link message + create a link message - :param link: the url of the link - :return: the link message + :param link: the url of the link + :return: the link message """ - return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.LINK, - message=link, - save_as=save_as) - + return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.LINK, message=link, save_as=save_as) + def create_text_message(self, text: str, save_as: str = '') -> ToolInvokeMessage: """ - create a text message + create a text message - :param text: the text - :return: the text message + :param text: the text + :return: the text message """ - return ToolInvokeMessage( - type=ToolInvokeMessage.MessageType.TEXT, - message=text, - save_as=save_as - ) - - def create_blob_message(self, blob: bytes, meta: dict = None, save_as: str = '') -> ToolInvokeMessage: + return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.TEXT, message=text, save_as=save_as) + + def create_blob_message(self, blob: bytes, meta: Optional[dict] = None, save_as: str = '') -> ToolInvokeMessage: """ - create a blob message + create a blob message - :param blob: the blob - :return: the blob message + :param blob: the blob + :return: the blob message """ - return ToolInvokeMessage( - type=ToolInvokeMessage.MessageType.BLOB, - message=blob, meta=meta, - save_as=save_as - ) + return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.BLOB, message=blob, meta=meta, save_as=save_as) def create_json_message(self, object: dict) -> ToolInvokeMessage: """ - create a json message + create a json message """ - return ToolInvokeMessage( - type=ToolInvokeMessage.MessageType.JSON, - message=object - ) + return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.JSON, message=object) From d52476c1c9fc22f15ded6dc52b8217b3a5491c12 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Mon, 29 Jul 2024 18:57:34 +0800 Subject: [PATCH 005/325] feat: support backwards invocation --- api/controllers/inner_api/plugin/plugin.py | 45 ++++++++---- .../app/features/rate_limiting/rate_limit.py | 4 +- api/core/tools/entities/tool_entities.py | 8 ++- api/libs/helper.py | 72 +++++++++---------- 4 files changed, 77 insertions(+), 52 deletions(-) diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index cc2a49a41fb050..b3ebf81bf6f7a0 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -1,10 +1,20 @@ +import time from flask_restful import Resource, reqparse from controllers.console.setup import setup_required from controllers.inner_api import api from controllers.inner_api.plugin.wraps import get_tenant, plugin_data from controllers.inner_api.wraps import plugin_inner_api_only -from core.plugin.entities.request import RequestInvokeLLM, RequestInvokeModeration, RequestInvokeRerank, RequestInvokeSpeech2Text, RequestInvokeTTS, RequestInvokeTextEmbedding, RequestInvokeTool +from core.plugin.entities.request import ( + RequestInvokeLLM, + RequestInvokeModeration, + RequestInvokeRerank, + RequestInvokeSpeech2Text, + RequestInvokeTextEmbedding, + RequestInvokeTool, + RequestInvokeTTS, +) +from core.tools.entities.tool_entities import ToolInvokeMessage from libs.helper import compact_generate_response from models.account import Tenant from services.plugin.plugin_invoke_service import PluginInvokeService @@ -18,6 +28,7 @@ class PluginInvokeLLMApi(Resource): def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeLLM): pass + class PluginInvokeTextEmbeddingApi(Resource): @setup_required @plugin_inner_api_only @@ -26,6 +37,7 @@ class PluginInvokeTextEmbeddingApi(Resource): def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeTextEmbedding): pass + class PluginInvokeRerankApi(Resource): @setup_required @plugin_inner_api_only @@ -34,6 +46,7 @@ class PluginInvokeRerankApi(Resource): def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeRerank): pass + class PluginInvokeTTSApi(Resource): @setup_required @plugin_inner_api_only @@ -42,6 +55,7 @@ class PluginInvokeTTSApi(Resource): def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeTTS): pass + class PluginInvokeSpeech2TextApi(Resource): @setup_required @plugin_inner_api_only @@ -50,6 +64,7 @@ class PluginInvokeSpeech2TextApi(Resource): def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeSpeech2Text): pass + class PluginInvokeModerationApi(Resource): @setup_required @plugin_inner_api_only @@ -58,23 +73,27 @@ class PluginInvokeModerationApi(Resource): def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeModeration): pass + class PluginInvokeToolApi(Resource): @setup_required @plugin_inner_api_only @get_tenant @plugin_data(payload_type=RequestInvokeTool) - def post(self, user_id: str, tenant_model: Tenant): - parser = reqparse.RequestParser() - parser.add_argument('provider', type=dict, required=True, location='json') - parser.add_argument('tool', type=dict, required=True, location='json') - parser.add_argument('parameters', type=dict, required=True, location='json') - - args = parser.parse_args() - - response = PluginInvokeService.invoke_tool( - user_id, tenant_model, args['provider'], args['tool'], args['parameters'] - ) - return compact_generate_response(response) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeTool): + def generator(): + for i in range(10): + time.sleep(0.1) + yield ( + ToolInvokeMessage( + type=ToolInvokeMessage.MessageType.TEXT, + message=ToolInvokeMessage.TextMessage(text='helloworld'), + ) + .model_dump_json() + .encode() + + b'\n\n' + ) + + return compact_generate_response(generator()) class PluginInvokeNodeApi(Resource): diff --git a/api/core/app/features/rate_limiting/rate_limit.py b/api/core/app/features/rate_limiting/rate_limit.py index f11e8021f0b1cc..570e3c003f3273 100644 --- a/api/core/app/features/rate_limiting/rate_limit.py +++ b/api/core/app/features/rate_limiting/rate_limit.py @@ -1,7 +1,7 @@ import logging import time import uuid -from collections.abc import Generator +from collections.abc import Callable, Generator from datetime import timedelta from typing import Optional, Union @@ -91,7 +91,7 @@ def generate(self, generator: Union[Generator, callable, dict], request_id: str) class RateLimitGenerator: - def __init__(self, rate_limit: RateLimit, generator: Union[Generator, callable], request_id: str): + def __init__(self, rate_limit: RateLimit, generator: Union[Generator, Callable[[], Generator]], request_id: str): self.rate_limit = rate_limit if callable(generator): self.generator = generator() diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 5213f35a4b41c9..1d39e7fb005d8d 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -90,6 +90,12 @@ def value_of(cls, value: str) -> 'ApiProviderAuthType': raise ValueError(f'invalid mode value {value}') class ToolInvokeMessage(BaseModel): + class TextMessage(BaseModel): + text: str + + class JsonMessage(BaseModel): + json_object: dict + class MessageType(Enum): TEXT = "text" IMAGE = "image" @@ -103,7 +109,7 @@ class MessageType(Enum): """ plain text, image url or link url """ - message: Optional[Union[str, bytes, dict]] = None + message: JsonMessage | TextMessage meta: Optional[dict[str, Any]] = None save_as: str = '' diff --git a/api/libs/helper.py b/api/libs/helper.py index 15cd65dd6a38ba..c169d6ba1744b6 100644 --- a/api/libs/helper.py +++ b/api/libs/helper.py @@ -36,8 +36,7 @@ def email(email): if re.match(pattern, email) is not None: return email - error = ('{email} is not a valid email.' - .format(email=email)) + error = '{email} is not a valid email.'.format(email=email) raise ValueError(error) @@ -49,10 +48,10 @@ def uuid_value(value): uuid_obj = uuid.UUID(value) return str(uuid_obj) except ValueError: - error = ('{value} is not a valid uuid.' - .format(value=value)) + error = '{value} is not a valid uuid.'.format(value=value) raise ValueError(error) + def alphanumeric(value: str): # check if the value is alphanumeric and underlined if re.match(r'^[a-zA-Z0-9_]+$', value): @@ -60,6 +59,7 @@ def alphanumeric(value: str): raise ValueError(f'{value} is not a valid alphanumeric value') + def timestamp_value(timestamp): try: int_timestamp = int(timestamp) @@ -67,13 +67,12 @@ def timestamp_value(timestamp): raise ValueError return int_timestamp except ValueError: - error = ('{timestamp} is not a valid timestamp.' - .format(timestamp=timestamp)) + error = '{timestamp} is not a valid timestamp.'.format(timestamp=timestamp) raise ValueError(error) class str_len: - """ Restrict input to an integer in a range (inclusive) """ + """Restrict input to an integer in a range (inclusive)""" def __init__(self, max_length, argument='argument'): self.max_length = max_length @@ -82,15 +81,17 @@ def __init__(self, max_length, argument='argument'): def __call__(self, value): length = len(value) if length > self.max_length: - error = ('Invalid {arg}: {val}. {arg} cannot exceed length {length}' - .format(arg=self.argument, val=value, length=self.max_length)) + error = 'Invalid {arg}: {val}. {arg} cannot exceed length {length}'.format( + arg=self.argument, val=value, length=self.max_length + ) raise ValueError(error) return value class float_range: - """ Restrict input to an float in a range (inclusive) """ + """Restrict input to an float in a range (inclusive)""" + def __init__(self, low, high, argument='argument'): self.low = low self.high = high @@ -99,8 +100,9 @@ def __init__(self, low, high, argument='argument'): def __call__(self, value): value = _get_float(value) if value < self.low or value > self.high: - error = ('Invalid {arg}: {val}. {arg} must be within the range {lo} - {hi}' - .format(arg=self.argument, val=value, lo=self.low, hi=self.high)) + error = 'Invalid {arg}: {val}. {arg} must be within the range {lo} - {hi}'.format( + arg=self.argument, val=value, lo=self.low, hi=self.high + ) raise ValueError(error) return value @@ -115,8 +117,9 @@ def __call__(self, value): try: datetime.strptime(value, self.format) except ValueError: - error = ('Invalid {arg}: {val}. {arg} must be conform to the format {format}' - .format(arg=self.argument, val=value, format=self.format)) + error = 'Invalid {arg}: {val}. {arg} must be conform to the format {format}'.format( + arg=self.argument, val=value, format=self.format + ) raise ValueError(error) return value @@ -128,18 +131,18 @@ def _get_float(value): except (TypeError, ValueError): raise ValueError('{} is not a valid float'.format(value)) + def timezone(timezone_string): if timezone_string and timezone_string in available_timezones(): return timezone_string - error = ('{timezone_string} is not a valid timezone.' - .format(timezone_string=timezone_string)) + error = '{timezone_string} is not a valid timezone.'.format(timezone_string=timezone_string) raise ValueError(error) def generate_string(n): letters_digits = string.ascii_letters + string.digits - result = "" + result = '' for i in range(n): result += random.choice(letters_digits) @@ -149,8 +152,8 @@ def generate_string(n): def get_remote_ip(request) -> str: if request.headers.get('CF-Connecting-IP'): return request.headers.get('Cf-Connecting-Ip') - elif request.headers.getlist("X-Forwarded-For"): - return request.headers.getlist("X-Forwarded-For")[0] + elif request.headers.getlist('X-Forwarded-For'): + return request.headers.getlist('X-Forwarded-For')[0] else: return request.remote_addr @@ -160,19 +163,24 @@ def generate_text_hash(text: str) -> str: return sha256(hash_text.encode()).hexdigest() -def compact_generate_response(response: Union[dict, RateLimitGenerator]) -> Response: +def compact_generate_response(response: Union[dict, Generator, RateLimitGenerator]) -> Response: if isinstance(response, dict): return Response(response=json.dumps(response), status=200, mimetype='application/json') else: + def generate() -> Generator: - yield from response + for data in response: + if isinstance(data, dict): + yield json.dumps(data).encode() + if isinstance(data, str): + yield data.encode() + else: + yield data - return Response(stream_with_context(generate()), status=200, - mimetype='text/event-stream') + return Response(stream_with_context(generate()), status=200, mimetype='text/event-stream') class TokenManager: - @classmethod def generate_token(cls, account: Account, token_type: str, additional_data: dict = None) -> str: old_token = cls._get_current_token_for_account(account.id, token_type) @@ -182,21 +190,13 @@ def generate_token(cls, account: Account, token_type: str, additional_data: dict cls.revoke_token(old_token, token_type) token = str(uuid.uuid4()) - token_data = { - 'account_id': account.id, - 'email': account.email, - 'token_type': token_type - } + token_data = {'account_id': account.id, 'email': account.email, 'token_type': token_type} if additional_data: token_data.update(additional_data) expiry_hours = current_app.config[f'{token_type.upper()}_TOKEN_EXPIRY_HOURS'] token_key = cls._get_token_key(token, token_type) - redis_client.setex( - token_key, - expiry_hours * 60 * 60, - json.dumps(token_data) - ) + redis_client.setex(token_key, expiry_hours * 60 * 60, json.dumps(token_data)) cls._set_current_token_for_account(account.id, token, token_type, expiry_hours) return token @@ -215,7 +215,7 @@ def get_token_data(cls, token: str, token_type: str) -> Optional[dict[str, Any]] key = cls._get_token_key(token, token_type) token_data_json = redis_client.get(key) if token_data_json is None: - logging.warning(f"{token_type} token {token} not found with key {key}") + logging.warning(f'{token_type} token {token} not found with key {key}') return None token_data = json.loads(token_data_json) return token_data @@ -243,7 +243,7 @@ def __init__(self, prefix: str, max_attempts: int, time_window: int): self.time_window = time_window def _get_key(self, email: str) -> str: - return f"{self.prefix}:{email}" + return f'{self.prefix}:{email}' def is_rate_limited(self, email: str) -> bool: key = self._get_key(email) From 31e8b134d14f492dbf256067db184f83e4eef24e Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Mon, 29 Jul 2024 22:08:14 +0800 Subject: [PATCH 006/325] feat: backwards invoke llm --- api/controllers/inner_api/plugin/plugin.py | 14 ++++- api/core/model_manager.py | 4 +- api/core/plugin/backwards_invocation/model.py | 49 +++++++++++++++ api/core/plugin/entities/request.py | 59 ++++++++++++++++++- 4 files changed, 119 insertions(+), 7 deletions(-) create mode 100644 api/core/plugin/backwards_invocation/model.py diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index b3ebf81bf6f7a0..3a76e007677d7e 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -1,10 +1,13 @@ import time +from collections.abc import Generator + from flask_restful import Resource, reqparse from controllers.console.setup import setup_required from controllers.inner_api import api from controllers.inner_api.plugin.wraps import get_tenant, plugin_data from controllers.inner_api.wraps import plugin_inner_api_only +from core.plugin.backwards_invocation.model import PluginBackwardsInvocation from core.plugin.entities.request import ( RequestInvokeLLM, RequestInvokeModeration, @@ -17,7 +20,6 @@ from core.tools.entities.tool_entities import ToolInvokeMessage from libs.helper import compact_generate_response from models.account import Tenant -from services.plugin.plugin_invoke_service import PluginInvokeService class PluginInvokeLLMApi(Resource): @@ -26,7 +28,15 @@ class PluginInvokeLLMApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeLLM) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeLLM): - pass + def generator(): + response = PluginBackwardsInvocation.invoke_llm(user_id, tenant_model, payload) + if isinstance(response, Generator): + for chunk in response: + yield chunk.model_dump_json().encode() + b'\n\n' + else: + yield response.model_dump_json().encode() + b'\n\n' + + return compact_generate_response(generator()) class PluginInvokeTextEmbeddingApi(Resource): diff --git a/api/core/model_manager.py b/api/core/model_manager.py index 8e99ad3dec040b..e46d1d35ee402e 100644 --- a/api/core/model_manager.py +++ b/api/core/model_manager.py @@ -7,7 +7,7 @@ from core.entities.provider_entities import ModelLoadBalancingConfiguration from core.errors.error import ProviderTokenNotInitError from core.model_runtime.callbacks.base_callback import Callback -from core.model_runtime.entities.llm_entities import LLMResult +from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool from core.model_runtime.entities.model_entities import ModelType from core.model_runtime.entities.rerank_entities import RerankResult @@ -103,7 +103,7 @@ def _get_load_balancing_manager(self, configuration: ProviderConfiguration, def invoke_llm(self, prompt_messages: list[PromptMessage], model_parameters: Optional[dict] = None, tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None, stream: bool = True, user: Optional[str] = None, callbacks: Optional[list[Callback]] = None) \ - -> Union[LLMResult, Generator]: + -> Union[LLMResult, Generator[LLMResultChunk, None, None]]: """ Invoke large language model diff --git a/api/core/plugin/backwards_invocation/model.py b/api/core/plugin/backwards_invocation/model.py new file mode 100644 index 00000000000000..b6da133119e2b1 --- /dev/null +++ b/api/core/plugin/backwards_invocation/model.py @@ -0,0 +1,49 @@ +from collections.abc import Generator + +from core.model_manager import ModelManager +from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk +from core.plugin.entities.request import RequestInvokeLLM +from core.workflow.nodes.llm.llm_node import LLMNode +from models.account import Tenant + + +class PluginBackwardsInvocation: + @classmethod + def invoke_llm( + cls, user_id: str, tenant: Tenant, payload: RequestInvokeLLM + ) -> Generator[LLMResultChunk, None, None] | LLMResult: + """ + invoke llm + """ + model_instance = ModelManager().get_model_instance( + tenant_id=tenant.id, + provider=payload.provider, + model_type=payload.model_type, + model=payload.model, + ) + + # invoke model + response = model_instance.invoke_llm( + prompt_messages=payload.prompt_messages, + model_parameters=payload.model_parameters, + tools=payload.tools, + stop=payload.stop, + stream=payload.stream or True, + user=user_id, + ) + + if isinstance(response, Generator): + + def handle() -> Generator[LLMResultChunk, None, None]: + for chunk in response: + if chunk.delta.usage: + LLMNode.deduct_llm_quota( + tenant_id=tenant.id, model_instance=model_instance, usage=chunk.delta.usage + ) + yield chunk + + return handle() + else: + if response.usage: + LLMNode.deduct_llm_quota(tenant_id=tenant.id, model_instance=model_instance, usage=response.usage) + return response diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 62db6396a88e25..bb08facf751b44 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -1,4 +1,17 @@ -from pydantic import BaseModel +from typing import Any, Optional + +from pydantic import BaseModel, Field, field_validator + +from core.model_runtime.entities.message_entities import ( + AssistantPromptMessage, + PromptMessage, + PromptMessageRole, + PromptMessageTool, + SystemPromptMessage, + ToolPromptMessage, + UserPromptMessage, +) +from core.model_runtime.entities.model_entities import ModelType class RequestInvokeTool(BaseModel): @@ -6,37 +19,77 @@ class RequestInvokeTool(BaseModel): Request to invoke a tool """ -class RequestInvokeLLM(BaseModel): + +class BaseRequestInvokeModel(BaseModel): + provider: str + model: str + model_type: ModelType + + +class RequestInvokeLLM(BaseRequestInvokeModel): """ Request to invoke LLM """ + model_type: ModelType = ModelType.LLM + mode: str + model_parameters: dict[str, Any] = Field(default_factory=dict) + prompt_messages: list[PromptMessage] + tools: Optional[list[PromptMessageTool]] = Field(default_factory=list) + stop: Optional[list[str]] = Field(default_factory=list) + stream: Optional[bool] = False + + @field_validator('prompt_messages', mode='before') + def convert_prompt_messages(cls, v): + if not isinstance(v, list): + raise ValueError('prompt_messages must be a list') + + for i in range(len(v)): + if v[i]['role'] == PromptMessageRole.USER.value: + v[i] = UserPromptMessage(**v[i]) + elif v[i]['role'] == PromptMessageRole.ASSISTANT.value: + v[i] = AssistantPromptMessage(**v[i]) + elif v[i]['role'] == PromptMessageRole.SYSTEM.value: + v[i] = SystemPromptMessage(**v[i]) + elif v[i]['role'] == PromptMessageRole.TOOL.value: + v[i] = ToolPromptMessage(**v[i]) + else: + v[i] = PromptMessage(**v[i]) + + return v + + class RequestInvokeTextEmbedding(BaseModel): """ Request to invoke text embedding """ + class RequestInvokeRerank(BaseModel): """ Request to invoke rerank """ + class RequestInvokeTTS(BaseModel): """ Request to invoke TTS """ + class RequestInvokeSpeech2Text(BaseModel): """ Request to invoke speech2text """ + class RequestInvokeModeration(BaseModel): """ Request to invoke moderation """ + class RequestInvokeNode(BaseModel): """ Request to invoke node - """ \ No newline at end of file + """ From 25b8a512bfba2934cdce9aa14de2011511d86666 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 12:55:00 +0800 Subject: [PATCH 007/325] feat: invoke app --- api/controllers/inner_api/plugin/plugin.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index 3a76e007677d7e..67a51fdb2ecd56 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -116,6 +116,15 @@ def post(self, user_id: str, tenant_model: Tenant): return {'message': 'success'} +class PluginInvokeAppApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + def post(self, user_id: str, tenant_model: Tenant): + parser = reqparse.RequestParser() + args = parser.parse_args() + + return {'message': 'success'} api.add_resource(PluginInvokeLLMApi, '/invoke/llm') api.add_resource(PluginInvokeTextEmbeddingApi, '/invoke/text-embedding') @@ -125,3 +134,4 @@ def post(self, user_id: str, tenant_model: Tenant): api.add_resource(PluginInvokeModerationApi, '/invoke/moderation') api.add_resource(PluginInvokeToolApi, '/invoke/tool') api.add_resource(PluginInvokeNodeApi, '/invoke/node') +api.add_resource(PluginInvokeAppApi, '/invoke/app') From c28998a6f0de33260837e1fbc4ec922f11e5abb3 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 13:42:31 +0800 Subject: [PATCH 008/325] refactor: tool message transformer --- api/core/tools/entities/tool_entities.py | 7 +++- api/core/tools/tool_file_manager.py | 10 ++--- api/core/tools/utils/message_transformer.py | 44 ++++++++++++++------- api/core/workflow/nodes/tool/tool_node.py | 4 +- api/models/tools.py | 18 +++++---- 5 files changed, 52 insertions(+), 31 deletions(-) diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 7d96db865237a2..c266db1cdbd1d8 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -96,6 +96,9 @@ class TextMessage(BaseModel): class JsonMessage(BaseModel): json_object: dict + class BlobMessage(BaseModel): + blob: bytes + class MessageType(Enum): TEXT = "text" IMAGE = "image" @@ -109,7 +112,7 @@ class MessageType(Enum): """ plain text, image url or link url """ - message: JsonMessage | TextMessage | None + message: JsonMessage | TextMessage | BlobMessage | None meta: dict[str, Any] | None = None save_as: str = '' @@ -321,7 +324,7 @@ def set_text(self, tool_name: str, name: str, value: str) -> None: self.pool.append(variable) - def set_file(self, tool_name: str, value: str, name: str = None) -> None: + def set_file(self, tool_name: str, value: str, name: Optional[str] = None) -> None: """ set an image variable diff --git a/api/core/tools/tool_file_manager.py b/api/core/tools/tool_file_manager.py index f9f7c7d78a7f28..078c58c662a5b7 100644 --- a/api/core/tools/tool_file_manager.py +++ b/api/core/tools/tool_file_manager.py @@ -80,8 +80,8 @@ def create_file_by_raw( def create_file_by_url( user_id: str, tenant_id: str, - conversation_id: str, file_url: str, + conversation_id: Optional[str] = None, ) -> ToolFile: """ create file @@ -131,7 +131,7 @@ def get_file_binary(id: str) -> Union[tuple[bytes, str], None]: :return: the binary of the file, mime type """ - tool_file: ToolFile = ( + tool_file: ToolFile | None = ( db.session.query(ToolFile) .filter( ToolFile.id == id, @@ -155,7 +155,7 @@ def get_file_binary_by_message_file_id(id: str) -> Union[tuple[bytes, str], None :return: the binary of the file, mime type """ - message_file: MessageFile = ( + message_file: MessageFile | None = ( db.session.query(MessageFile) .filter( MessageFile.id == id, @@ -173,7 +173,7 @@ def get_file_binary_by_message_file_id(id: str) -> Union[tuple[bytes, str], None tool_file_id = None - tool_file: ToolFile = ( + tool_file: ToolFile | None = ( db.session.query(ToolFile) .filter( ToolFile.id == tool_file_id, @@ -197,7 +197,7 @@ def get_file_generator_by_tool_file_id(tool_file_id: str) -> Union[tuple[Generat :return: the binary of the file, mime type """ - tool_file: ToolFile = ( + tool_file: ToolFile | None = ( db.session.query(ToolFile) .filter( ToolFile.id == tool_file_id, diff --git a/api/core/tools/utils/message_transformer.py b/api/core/tools/utils/message_transformer.py index d22b88e58cdf41..41a93a4f9541ad 100644 --- a/api/core/tools/utils/message_transformer.py +++ b/api/core/tools/utils/message_transformer.py @@ -1,8 +1,9 @@ import logging from collections.abc import Generator from mimetypes import guess_extension +from typing import Optional -from core.file.file_obj import FileTransferMethod, FileType +from core.file.file_obj import FileTransferMethod, FileType, FileVar from core.tools.entities.tool_entities import ToolInvokeMessage from core.tools.tool_file_manager import ToolFileManager @@ -13,7 +14,7 @@ class ToolFileMessageTransformer: def transform_tool_invoke_messages(cls, messages: Generator[ToolInvokeMessage, None, None], user_id: str, tenant_id: str, - conversation_id: str) -> Generator[ToolInvokeMessage, None, None]: + conversation_id: Optional[str] = None) -> Generator[ToolInvokeMessage, None, None]: """ Transform tool message and handle file download """ @@ -25,18 +26,23 @@ def transform_tool_invoke_messages(cls, messages: Generator[ToolInvokeMessage, N elif message.type == ToolInvokeMessage.MessageType.IMAGE: # try to download image try: + if not conversation_id: + raise + + assert isinstance(message.message, ToolInvokeMessage.TextMessage) + file = ToolFileManager.create_file_by_url( user_id=user_id, tenant_id=tenant_id, + file_url=message.message.text, conversation_id=conversation_id, - file_url=message.message ) url = f'/files/tools/{file.id}{guess_extension(file.mimetype) or ".png"}' yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.IMAGE_LINK, - message=url, + message=ToolInvokeMessage.TextMessage(text=url), save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, ) @@ -44,57 +50,67 @@ def transform_tool_invoke_messages(cls, messages: Generator[ToolInvokeMessage, N logger.exception(e) yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.TEXT, - message=f"Failed to download image: {message.message}, you can try to download it yourself.", + message=ToolInvokeMessage.TextMessage( + text=f"Failed to download image: {message.message}, you can try to download it yourself." + ), meta=message.meta.copy() if message.meta is not None else {}, save_as=message.save_as, ) elif message.type == ToolInvokeMessage.MessageType.BLOB: # get mime type and save blob to storage + assert message.meta + mimetype = message.meta.get('mime_type', 'octet/stream') # if message is str, encode it to bytes - if isinstance(message.message, str): - message.message = message.message.encode('utf-8') + + if not isinstance(message.message, ToolInvokeMessage.BlobMessage): + raise ValueError("unexpected message type") file = ToolFileManager.create_file_by_raw( user_id=user_id, tenant_id=tenant_id, conversation_id=conversation_id, - file_binary=message.message, + file_binary=message.message.blob, mimetype=mimetype ) - url = cls.get_tool_file_url(file.id, guess_extension(file.mimetype)) + extension = guess_extension(file.mimetype) or ".bin" + url = cls.get_tool_file_url(file.id, extension) # check if file is image if 'image' in mimetype: yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.IMAGE_LINK, - message=url, + message=ToolInvokeMessage.TextMessage(text=url), save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, ) else: yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.LINK, - message=url, + message=ToolInvokeMessage.TextMessage(text=url), save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, ) elif message.type == ToolInvokeMessage.MessageType.FILE_VAR: - file_var = message.meta.get('file_var') + assert message.meta + + file_var: FileVar | None = message.meta.get('file_var') if file_var: if file_var.transfer_method == FileTransferMethod.TOOL_FILE: + assert file_var.related_id and file_var.extension + url = cls.get_tool_file_url(file_var.related_id, file_var.extension) if file_var.type == FileType.IMAGE: yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.IMAGE_LINK, - message=url, + message=ToolInvokeMessage.TextMessage(text=url), save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, ) else: yield ToolInvokeMessage( type=ToolInvokeMessage.MessageType.LINK, - message=url, + message=ToolInvokeMessage.TextMessage(text=url), save_as=message.save_as, meta=message.meta.copy() if message.meta is not None else {}, ) diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index 52a4a216e0eaf5..0774fc4f3d12b2 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -1,4 +1,4 @@ -from collections.abc import Mapping, Sequence +from collections.abc import Generator, Mapping, Sequence from os import path from typing import Any, cast @@ -145,7 +145,7 @@ def _fetch_files(self, variable_pool: VariablePool) -> list[FileVar]: assert isinstance(variable, ArrayAnyVariable | ArrayAnySegment) return list(variable.value) if variable else [] - def _convert_tool_messages(self, messages: list[ToolInvokeMessage]): + def _convert_tool_messages(self, messages: Generator[ToolInvokeMessage, None, None]): """ Convert ToolInvokeMessages into tuple[plain_text, files] """ diff --git a/api/models/tools.py b/api/models/tools.py index 069dc5bad083c8..3ee246eeb33de5 100644 --- a/api/models/tools.py +++ b/api/models/tools.py @@ -1,6 +1,7 @@ import json from sqlalchemy import ForeignKey +from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle @@ -277,7 +278,7 @@ class ToolConversationVariables(db.Model): def variables(self) -> dict: return json.loads(self.variables_str) -class ToolFile(db.Model): +class ToolFile(DeclarativeBase): """ store the file created by agent """ @@ -288,16 +289,17 @@ class ToolFile(db.Model): db.Index('tool_file_conversation_id_idx', 'conversation_id'), ) - id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) + id: Mapped[str] = mapped_column(StringUUID, default=db.text('uuid_generate_v4()')) # conversation user id - user_id = db.Column(StringUUID, nullable=False) + user_id: Mapped[str] = mapped_column(StringUUID) # tenant id - tenant_id = db.Column(StringUUID, nullable=False) + tenant_id: Mapped[StringUUID] = mapped_column(StringUUID) # conversation id - conversation_id = db.Column(StringUUID, nullable=True) + conversation_id: Mapped[StringUUID] = mapped_column(nullable=True) # file key - file_key = db.Column(db.String(255), nullable=False) + file_key: Mapped[str] = mapped_column(db.String(255), nullable=False) # mime type - mimetype = db.Column(db.String(255), nullable=False) + mimetype: Mapped[str] = mapped_column(db.String(255), nullable=False) # original url - original_url = db.Column(db.String(2048), nullable=True) \ No newline at end of file + original_url: Mapped[str] = mapped_column(db.String(2048), nullable=True) + \ No newline at end of file From 531ffaec4fd94817f73f4bd172b4abbd95d9211f Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 13:56:48 +0800 Subject: [PATCH 009/325] fix: tool node --- api/core/workflow/nodes/tool/tool_node.py | 45 ++++++++++++++++------- 1 file changed, 32 insertions(+), 13 deletions(-) diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index 0774fc4f3d12b2..47498f4f5fde1f 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -128,8 +128,10 @@ def _generate_parameters( else: tool_input = node_data.tool_parameters[parameter_name] if tool_input.type == 'variable': - # TODO: check if the variable exists in the variable pool - parameter_value = variable_pool.get(tool_input.value).value + parameter_value_segment = variable_pool.get(tool_input.value) + if not parameter_value_segment: + raise Exception("input variable dose not exists") + parameter_value = parameter_value_segment.value else: segment_group = parser.convert_template( template=str(tool_input.value), @@ -163,7 +165,7 @@ def _convert_tool_messages(self, messages: Generator[ToolInvokeMessage, None, No return plain_text, files, json - def _extract_tool_response_binary(self, tool_response: list[ToolInvokeMessage]) -> list[FileVar]: + def _extract_tool_response_binary(self, tool_response: Generator[ToolInvokeMessage, None, None]) -> list[FileVar]: """ Extract tool response binary """ @@ -172,7 +174,10 @@ def _extract_tool_response_binary(self, tool_response: list[ToolInvokeMessage]) for response in tool_response: if response.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \ response.type == ToolInvokeMessage.MessageType.IMAGE: - url = response.message + assert isinstance(response.message, ToolInvokeMessage.TextMessage) + assert response.meta + + url = response.message.text ext = path.splitext(url)[1] mimetype = response.meta.get('mime_type', 'image/jpeg') filename = response.save_as or url.split('/')[-1] @@ -192,7 +197,10 @@ def _extract_tool_response_binary(self, tool_response: list[ToolInvokeMessage]) )) elif response.type == ToolInvokeMessage.MessageType.BLOB: # get tool file id - tool_file_id = response.message.split('/')[-1].split('.')[0] + assert isinstance(response.message, ToolInvokeMessage.TextMessage) + assert response.meta + + tool_file_id = response.message.text.split('/')[-1].split('.')[0] result.append(FileVar( tenant_id=self.tenant_id, type=FileType.IMAGE, @@ -207,18 +215,28 @@ def _extract_tool_response_binary(self, tool_response: list[ToolInvokeMessage]) return result - def _extract_tool_response_text(self, tool_response: list[ToolInvokeMessage]) -> str: + def _extract_tool_response_text(self, tool_response: Generator[ToolInvokeMessage]) -> str: """ Extract tool response text """ - return '\n'.join([ - f'{message.message}' if message.type == ToolInvokeMessage.MessageType.TEXT else - f'Link: {message.message}' if message.type == ToolInvokeMessage.MessageType.LINK else '' - for message in tool_response - ]) + result: list[str] = [] + for message in tool_response: + if message.type == ToolInvokeMessage.MessageType.TEXT: + assert isinstance(message.message, ToolInvokeMessage.TextMessage) + result.append(message.message.text) + elif message.type == ToolInvokeMessage.MessageType.LINK: + assert isinstance(message.message, ToolInvokeMessage.TextMessage) + result.append(f'Link: {message.message.text}') - def _extract_tool_response_json(self, tool_response: list[ToolInvokeMessage]) -> list[dict]: - return [message.message for message in tool_response if message.type == ToolInvokeMessage.MessageType.JSON] + return '\n'.join(result) + + def _extract_tool_response_json(self, tool_response: Generator[ToolInvokeMessage]) -> list[dict]: + result: list[dict] = [] + for message in tool_response: + if message.type == ToolInvokeMessage.MessageType.JSON: + assert isinstance(message, ToolInvokeMessage.JsonMessage) + result.append(message.json_object) + return result @classmethod def _extract_variable_selector_to_variable_mapping(cls, node_data: ToolNodeData) -> dict[str, list[str]]: @@ -231,6 +249,7 @@ def _extract_variable_selector_to_variable_mapping(cls, node_data: ToolNodeData) for parameter_name in node_data.tool_parameters: input = node_data.tool_parameters[parameter_name] if input.type == 'mixed': + assert isinstance(input.value, str) selectors = VariableTemplateParser(input.value).extract_variable_selectors() for selector in selectors: result[selector.variable] = selector.value_selector From c8b0160ea9afb9c93061b33ba74cbe269a09debc Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 14:06:10 +0800 Subject: [PATCH 010/325] fix: tool type --- api/core/tools/tool/tool.py | 32 +++++++++++++++++++------------- 1 file changed, 19 insertions(+), 13 deletions(-) diff --git a/api/core/tools/tool/tool.py b/api/core/tools/tool/tool.py index ae346759e2cb06..52513c13f9461a 100644 --- a/api/core/tools/tool/tool.py +++ b/api/core/tools/tool/tool.py @@ -4,7 +4,7 @@ from enum import Enum from typing import TYPE_CHECKING, Any, Optional, Union -from pydantic import BaseModel, ConfigDict, field_validator +from pydantic import BaseModel, ConfigDict, Field, field_validator from pydantic_core.core_schema import ValidationInfo from core.app.entities.app_invoke_entities import InvokeFrom @@ -27,8 +27,8 @@ class Tool(BaseModel, ABC): - identity: Optional[ToolIdentity] = None - parameters: Optional[list[ToolParameter]] = None + identity: ToolIdentity + parameters: list[ToolParameter] = Field(default_factory=list) description: Optional[ToolDescription] = None is_team_authorization: bool = False @@ -194,10 +194,8 @@ def list_default_image_variables(self) -> list[ToolRuntimeVariable]: return result - def invoke(self, user_id: str, tool_parameters: Mapping[str, Any]) -> Generator[ToolInvokeMessage]: - # update tool_parameters - # TODO: Fix type error. - if self.runtime.runtime_parameters: + def invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage]: + if self.runtime and self.runtime.runtime_parameters: tool_parameters.update(self.runtime.runtime_parameters) # try parse tool parameters into the correct type @@ -210,7 +208,7 @@ def invoke(self, user_id: str, tool_parameters: Mapping[str, Any]) -> Generator[ return result - def _transform_tool_parameters_type(self, tool_parameters: Mapping[str, Any]) -> dict[str, Any]: + def _transform_tool_parameters_type(self, tool_parameters: dict[str, Any]) -> dict[str, Any]: """ Transform tool parameters type """ @@ -289,7 +287,7 @@ def create_image_message(self, image: str, save_as: str = '') -> ToolInvokeMessa :return: the image message """ return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.IMAGE, - message=image, + message=ToolInvokeMessage.TextMessage(text=image), save_as=save_as) def create_file_var_message(self, file_var: "FileVar") -> ToolInvokeMessage: @@ -308,7 +306,7 @@ def create_link_message(self, link: str, save_as: str = '') -> ToolInvokeMessage :return: the link message """ return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.LINK, - message=link, + message=ToolInvokeMessage.TextMessage(text=link), save_as=save_as) def create_text_message(self, text: str, save_as: str = '') -> ToolInvokeMessage: @@ -320,7 +318,7 @@ def create_text_message(self, text: str, save_as: str = '') -> ToolInvokeMessage """ return ToolInvokeMessage( type=ToolInvokeMessage.MessageType.TEXT, - message=text, + message=ToolInvokeMessage.TextMessage(text=text), save_as=save_as ) @@ -331,10 +329,18 @@ def create_blob_message(self, blob: bytes, meta: Optional[dict] = None, save_as: :param blob: the blob :return: the blob message """ - return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.BLOB, message=blob, meta=meta, save_as=save_as) + return ToolInvokeMessage( + type=ToolInvokeMessage.MessageType.BLOB, + message=ToolInvokeMessage.BlobMessage(blob=blob), + meta=meta, + save_as=save_as + ) def create_json_message(self, object: dict) -> ToolInvokeMessage: """ create a json message """ - return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.JSON, message=object) + return ToolInvokeMessage( + type=ToolInvokeMessage.MessageType.JSON, + message=ToolInvokeMessage.JsonMessage(json_object=object) + ) From 4a8d3c54ca54b3e792ea86be0a3d148a8388bc9e Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 14:09:47 +0800 Subject: [PATCH 011/325] fix: workflow as tool type --- api/core/app/apps/workflow/app_generator.py | 24 ++++++++++++++++++++- api/core/tools/tool/tool.py | 2 +- api/core/tools/tool/workflow_tool.py | 4 +++- 3 files changed, 27 insertions(+), 3 deletions(-) diff --git a/api/core/app/apps/workflow/app_generator.py b/api/core/app/apps/workflow/app_generator.py index df40aec154a856..c5bf35edb607f1 100644 --- a/api/core/app/apps/workflow/app_generator.py +++ b/api/core/app/apps/workflow/app_generator.py @@ -4,7 +4,7 @@ import threading import uuid from collections.abc import Generator -from typing import Union +from typing import Literal, Union, overload from flask import Flask, current_app from pydantic import ValidationError @@ -32,6 +32,28 @@ class WorkflowAppGenerator(BaseAppGenerator): + @overload + def generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: Literal[True] = True, + call_depth: int = 0, + ) -> Generator[dict, None, None]: ... + + @overload + def generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: Literal[False] = False, + call_depth: int = 0, + ) -> dict: ... + def generate( self, app_model: App, workflow: Workflow, diff --git a/api/core/tools/tool/tool.py b/api/core/tools/tool/tool.py index 52513c13f9461a..68db0d5b2eaf4b 100644 --- a/api/core/tools/tool/tool.py +++ b/api/core/tools/tool/tool.py @@ -1,5 +1,5 @@ from abc import ABC, abstractmethod -from collections.abc import Generator, Mapping +from collections.abc import Generator from copy import deepcopy from enum import Enum from typing import TYPE_CHECKING, Any, Optional, Union diff --git a/api/core/tools/tool/workflow_tool.py b/api/core/tools/tool/workflow_tool.py index 4724c992d26e05..7a669a4fe4a465 100644 --- a/api/core/tools/tool/workflow_tool.py +++ b/api/core/tools/tool/workflow_tool.py @@ -48,6 +48,8 @@ def _invoke( from core.app.apps.workflow.app_generator import WorkflowAppGenerator generator = WorkflowAppGenerator() + assert self.runtime and self.runtime.invoke_from + result = generator.generate( app_model=app, workflow=workflow, @@ -154,7 +156,7 @@ def _transform_args(self, tool_parameters: dict) -> tuple[dict, list[dict]]: try: file_var_list = [FileVar(**f) for f in file] for file_var in file_var_list: - file_dict = { + file_dict: dict[str, Any] = { 'transfer_method': file_var.transfer_method.value, 'type': file_var.type.value, } From f47712beaedd264042d5ee06f1998c0ad0748420 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 14:18:00 +0800 Subject: [PATCH 012/325] feat: add type annatation --- .../app/apps/advanced_chat/app_generator.py | 22 ++++++++++++- api/core/app/apps/agent_chat/app_generator.py | 20 ++++++++++- api/core/app/apps/chat/app_generator.py | 20 ++++++++++- api/core/app/apps/completion/app_generator.py | 33 +++++++++++++++---- 4 files changed, 85 insertions(+), 10 deletions(-) diff --git a/api/core/app/apps/advanced_chat/app_generator.py b/api/core/app/apps/advanced_chat/app_generator.py index 5a1e5973cd46ea..80d2694fc9f482 100644 --- a/api/core/app/apps/advanced_chat/app_generator.py +++ b/api/core/app/apps/advanced_chat/app_generator.py @@ -4,7 +4,7 @@ import threading import uuid from collections.abc import Generator -from typing import Union +from typing import Any, Literal, Union, overload from flask import Flask, current_app from pydantic import ValidationError @@ -39,6 +39,26 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): + @overload + def generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: Literal[True] = True, + ) -> Generator[str, None, None]: ... + + @overload + def generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: Literal[False] = False, + ) -> dict: ... + def generate( self, app_model: App, workflow: Workflow, diff --git a/api/core/app/apps/agent_chat/app_generator.py b/api/core/app/apps/agent_chat/app_generator.py index 53780bdfb003b2..cf6d8292567afd 100644 --- a/api/core/app/apps/agent_chat/app_generator.py +++ b/api/core/app/apps/agent_chat/app_generator.py @@ -3,7 +3,7 @@ import threading import uuid from collections.abc import Generator -from typing import Any, Union +from typing import Any, Literal, Union, overload from flask import Flask, current_app from pydantic import ValidationError @@ -28,6 +28,24 @@ class AgentChatAppGenerator(MessageBasedAppGenerator): + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: Literal[True] = True, + ) -> Generator[dict, None, None]: ... + + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: Literal[False] = False, + ) -> dict: ... + def generate(self, app_model: App, user: Union[Account, EndUser], args: Any, diff --git a/api/core/app/apps/chat/app_generator.py b/api/core/app/apps/chat/app_generator.py index 5b896e28455340..bf4e6083b6bd3a 100644 --- a/api/core/app/apps/chat/app_generator.py +++ b/api/core/app/apps/chat/app_generator.py @@ -3,7 +3,7 @@ import threading import uuid from collections.abc import Generator -from typing import Any, Union +from typing import Any, Literal, Union, overload from flask import Flask, current_app from pydantic import ValidationError @@ -28,6 +28,24 @@ class ChatAppGenerator(MessageBasedAppGenerator): + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: Literal[True] = True, + ) -> Generator[dict, None, None]: ... + + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: Literal[False] = False, + ) -> dict: ... + def generate( self, app_model: App, user: Union[Account, EndUser], diff --git a/api/core/app/apps/completion/app_generator.py b/api/core/app/apps/completion/app_generator.py index c4e1caf65a9679..b14568480f1d6f 100644 --- a/api/core/app/apps/completion/app_generator.py +++ b/api/core/app/apps/completion/app_generator.py @@ -3,7 +3,7 @@ import threading import uuid from collections.abc import Generator -from typing import Any, Union +from typing import Any, Literal, Union, overload from flask import Flask, current_app from pydantic import ValidationError @@ -30,12 +30,31 @@ class CompletionAppGenerator(MessageBasedAppGenerator): - def generate(self, app_model: App, - user: Union[Account, EndUser], - args: Any, - invoke_from: InvokeFrom, - stream: bool = True) \ - -> Union[dict, Generator[dict, None, None]]: + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: Literal[True] = True, + ) -> Generator[dict, None, None]: ... + + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: Literal[False] = False, + ) -> dict: ... + + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: bool = True + ) -> Union[dict, Generator[dict, None, None]]: """ Generate App response. From 6ce02b07d3111fe63ebb0f7fcf1bc2392c3333c3 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 14:23:19 +0800 Subject: [PATCH 013/325] feat: add type annatation --- api/core/app/apps/advanced_chat/app_generator.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/api/core/app/apps/advanced_chat/app_generator.py b/api/core/app/apps/advanced_chat/app_generator.py index 80d2694fc9f482..e7c9ebe09749de 100644 --- a/api/core/app/apps/advanced_chat/app_generator.py +++ b/api/core/app/apps/advanced_chat/app_generator.py @@ -4,7 +4,7 @@ import threading import uuid from collections.abc import Generator -from typing import Any, Literal, Union, overload +from typing import Literal, Union, overload from flask import Flask, current_app from pydantic import ValidationError From ec711d094d002bdc3068f73002899b8a2422193c Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 19:49:57 +0800 Subject: [PATCH 014/325] refactor: enforce return object in app generator --- .../app/apps/advanced_chat/app_generator.py | 18 +++++-- .../generate_response_converter.py | 9 ++-- api/core/app/apps/agent_chat/app_generator.py | 13 ++++- .../agent_chat/generate_response_converter.py | 9 ++-- .../base_app_generate_response_converter.py | 18 ++----- api/core/app/apps/base_app_generator.py | 22 +++++++- api/core/app/apps/base_app_queue_manager.py | 4 +- api/core/app/apps/chat/app_generator.py | 13 ++++- .../apps/chat/generate_response_converter.py | 9 ++-- api/core/app/apps/completion/app_generator.py | 9 ++++ .../completion/generate_response_converter.py | 9 ++-- api/core/app/apps/workflow/app_generator.py | 19 +++++-- .../workflow/generate_response_converter.py | 9 ++-- api/services/app_generate_service.py | 50 ++++++++++++------- 14 files changed, 140 insertions(+), 71 deletions(-) diff --git a/api/core/app/apps/advanced_chat/app_generator.py b/api/core/app/apps/advanced_chat/app_generator.py index e7c9ebe09749de..6d654c2dc6aebb 100644 --- a/api/core/app/apps/advanced_chat/app_generator.py +++ b/api/core/app/apps/advanced_chat/app_generator.py @@ -4,7 +4,7 @@ import threading import uuid from collections.abc import Generator -from typing import Literal, Union, overload +from typing import Any, Literal, Union, overload from flask import Flask, current_app from pydantic import ValidationError @@ -47,7 +47,7 @@ def generate( args: dict, invoke_from: InvokeFrom, stream: Literal[True] = True, - ) -> Generator[str, None, None]: ... + ) -> Generator[dict | str, None, None]: ... @overload def generate( @@ -59,6 +59,16 @@ def generate( stream: Literal[False] = False, ) -> dict: ... + @overload + def generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: bool = True, + ) -> Union[dict[str, Any], Generator[dict | str, Any, None]]: ... + def generate( self, app_model: App, workflow: Workflow, @@ -152,7 +162,7 @@ def generate( def single_iteration_generate(self, app_model: App, workflow: Workflow, node_id: str, - user: Account, + user: Account | EndUser, args: dict, stream: bool = True): """ @@ -325,7 +335,7 @@ def _generate(self, *, user=user, stream=stream, ) - + return AdvancedChatAppGenerateResponseConverter.convert( response=response, invoke_from=invoke_from diff --git a/api/core/app/apps/advanced_chat/generate_response_converter.py b/api/core/app/apps/advanced_chat/generate_response_converter.py index ef579827b47c7e..2ddbd816e25cc0 100644 --- a/api/core/app/apps/advanced_chat/generate_response_converter.py +++ b/api/core/app/apps/advanced_chat/generate_response_converter.py @@ -1,4 +1,3 @@ -import json from collections.abc import Generator from typing import Any, cast @@ -56,7 +55,7 @@ def convert_blocking_simple_response(cls, blocking_response: AppBlockingResponse return response @classmethod - def convert_stream_full_response(cls, stream_response: Generator[AppStreamResponse, None, None]) -> Generator[str, Any, None]: + def convert_stream_full_response(cls, stream_response: Generator[AppStreamResponse, None, None]) -> Generator[dict | str, Any, None]: """ Convert stream full response. :param stream_response: stream response @@ -82,10 +81,10 @@ def convert_stream_full_response(cls, stream_response: Generator[AppStreamRespon response_chunk.update(data) else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk @classmethod - def convert_stream_simple_response(cls, stream_response: Generator[AppStreamResponse, None, None]) -> Generator[str, Any, None]: + def convert_stream_simple_response(cls, stream_response: Generator[AppStreamResponse, None, None]) -> Generator[dict | str, Any, None]: """ Convert stream simple response. :param stream_response: stream response @@ -119,4 +118,4 @@ def convert_stream_simple_response(cls, stream_response: Generator[AppStreamResp else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk diff --git a/api/core/app/apps/agent_chat/app_generator.py b/api/core/app/apps/agent_chat/app_generator.py index 29c7447290cd08..726e7ca65c542e 100644 --- a/api/core/app/apps/agent_chat/app_generator.py +++ b/api/core/app/apps/agent_chat/app_generator.py @@ -35,7 +35,7 @@ def generate( args: dict, invoke_from: InvokeFrom, stream: Literal[True] = True, - ) -> Generator[str, None, None]: ... + ) -> Generator[dict | str, None, None]: ... @overload def generate( @@ -46,12 +46,21 @@ def generate( stream: Literal[False] = False, ) -> dict: ... + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: bool = False, + ) -> dict | Generator[dict | str, None, None]: ... + def generate(self, app_model: App, user: Union[Account, EndUser], args: Any, invoke_from: InvokeFrom, stream: bool = True) \ - -> Union[dict, Generator[str, None, None]]: + -> Union[dict, Generator[dict | str, None, None]]: """ Generate App response. diff --git a/api/core/app/apps/agent_chat/generate_response_converter.py b/api/core/app/apps/agent_chat/generate_response_converter.py index 118d82c495f1fe..02aec27e393588 100644 --- a/api/core/app/apps/agent_chat/generate_response_converter.py +++ b/api/core/app/apps/agent_chat/generate_response_converter.py @@ -1,4 +1,3 @@ -import json from collections.abc import Generator from typing import cast @@ -52,7 +51,7 @@ def convert_blocking_simple_response(cls, blocking_response: ChatbotAppBlockingR @classmethod def convert_stream_full_response(cls, stream_response: Generator[ChatbotAppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: """ Convert stream full response. :param stream_response: stream response @@ -78,11 +77,11 @@ def convert_stream_full_response(cls, stream_response: Generator[ChatbotAppStrea response_chunk.update(data) else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk @classmethod def convert_stream_simple_response(cls, stream_response: Generator[ChatbotAppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: """ Convert stream simple response. :param stream_response: stream response @@ -114,4 +113,4 @@ def convert_stream_simple_response(cls, stream_response: Generator[ChatbotAppStr else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk diff --git a/api/core/app/apps/base_app_generate_response_converter.py b/api/core/app/apps/base_app_generate_response_converter.py index 1165314a7f2bd8..bd0d08cb7bf7fa 100644 --- a/api/core/app/apps/base_app_generate_response_converter.py +++ b/api/core/app/apps/base_app_generate_response_converter.py @@ -21,24 +21,16 @@ def convert(cls, response: Union[ if isinstance(response, AppBlockingResponse): return cls.convert_blocking_full_response(response) else: - def _generate_full_response() -> Generator[str, Any, None]: - for chunk in cls.convert_stream_full_response(response): - if chunk == 'ping': - yield f'event: {chunk}\n\n' - else: - yield f'data: {chunk}\n\n' + def _generate_full_response() -> Generator[dict | str, Any, None]: + yield from cls.convert_stream_simple_response(response) return _generate_full_response() else: if isinstance(response, AppBlockingResponse): return cls.convert_blocking_simple_response(response) else: - def _generate_simple_response() -> Generator[str, Any, None]: - for chunk in cls.convert_stream_simple_response(response): - if chunk == 'ping': - yield f'event: {chunk}\n\n' - else: - yield f'data: {chunk}\n\n' + def _generate_simple_response() -> Generator[dict | str, Any, None]: + yield from cls.convert_stream_simple_response(response) return _generate_simple_response() @@ -55,7 +47,7 @@ def convert_blocking_simple_response(cls, blocking_response: AppBlockingResponse @classmethod @abstractmethod def convert_stream_full_response(cls, stream_response: Generator[AppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: raise NotImplementedError @classmethod diff --git a/api/core/app/apps/base_app_generator.py b/api/core/app/apps/base_app_generator.py index 9e331dff4d64e2..7727519aef5a08 100644 --- a/api/core/app/apps/base_app_generator.py +++ b/api/core/app/apps/base_app_generator.py @@ -1,5 +1,6 @@ -from collections.abc import Mapping -from typing import Any, Optional +from collections.abc import Generator, Mapping +import json +from typing import Any, Optional, Union from core.app.app_config.entities import AppConfig, VariableEntity, VariableEntityType @@ -54,3 +55,20 @@ def _sanitize_value(self, value: Any) -> Any: if isinstance(value, str): return value.replace('\x00', '') return value + + @classmethod + def convert_to_event_stream(cls, generator: Union[dict, Generator[dict| str, None, None]]): + """ + Convert messages into event stream + """ + if isinstance(generator, dict): + return generator + else: + def gen(): + for message in generator: + if isinstance(message, dict): + yield f'data: {json.dumps(message)}\n\n' + else: + yield f'event: {message}\n\n' + + return gen() \ No newline at end of file diff --git a/api/core/app/apps/base_app_queue_manager.py b/api/core/app/apps/base_app_queue_manager.py index f929a979f129de..b45f57e9b6372d 100644 --- a/api/core/app/apps/base_app_queue_manager.py +++ b/api/core/app/apps/base_app_queue_manager.py @@ -3,7 +3,7 @@ from abc import abstractmethod from collections.abc import Generator from enum import Enum -from typing import Any +from typing import Any, Optional from sqlalchemy.orm import DeclarativeMeta @@ -118,7 +118,7 @@ def set_stop_flag(cls, task_id: str, invoke_from: InvokeFrom, user_id: str) -> N Set task stop flag :return: """ - result = redis_client.get(cls._generate_task_belong_cache_key(task_id)) + result: Optional[Any] = redis_client.get(cls._generate_task_belong_cache_key(task_id)) if result is None: return diff --git a/api/core/app/apps/chat/app_generator.py b/api/core/app/apps/chat/app_generator.py index ab15928b744b61..b784f42e7e319f 100644 --- a/api/core/app/apps/chat/app_generator.py +++ b/api/core/app/apps/chat/app_generator.py @@ -35,7 +35,7 @@ def generate( args: Any, invoke_from: InvokeFrom, stream: Literal[True] = True, - ) -> Generator[str, None, None]: ... + ) -> Generator[dict | str, None, None]: ... @overload def generate( @@ -46,13 +46,22 @@ def generate( stream: Literal[False] = False, ) -> dict: ... + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: bool = False, + ) -> Union[dict, Generator[dict | str, None, None]]: ... + def generate( self, app_model: App, user: Union[Account, EndUser], args: Any, invoke_from: InvokeFrom, stream: bool = True, - ) -> Union[dict, Generator[str, None, None]]: + ) -> Union[dict, Generator[dict | str, None, None]]: """ Generate App response. diff --git a/api/core/app/apps/chat/generate_response_converter.py b/api/core/app/apps/chat/generate_response_converter.py index 625e14c9c39712..0ae9926bb8b10a 100644 --- a/api/core/app/apps/chat/generate_response_converter.py +++ b/api/core/app/apps/chat/generate_response_converter.py @@ -1,4 +1,3 @@ -import json from collections.abc import Generator from typing import cast @@ -52,7 +51,7 @@ def convert_blocking_simple_response(cls, blocking_response: ChatbotAppBlockingR @classmethod def convert_stream_full_response(cls, stream_response: Generator[ChatbotAppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: """ Convert stream full response. :param stream_response: stream response @@ -78,11 +77,11 @@ def convert_stream_full_response(cls, stream_response: Generator[ChatbotAppStrea response_chunk.update(data) else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk @classmethod def convert_stream_simple_response(cls, stream_response: Generator[ChatbotAppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: """ Convert stream simple response. :param stream_response: stream response @@ -114,4 +113,4 @@ def convert_stream_simple_response(cls, stream_response: Generator[ChatbotAppStr else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk diff --git a/api/core/app/apps/completion/app_generator.py b/api/core/app/apps/completion/app_generator.py index c0b13b40fdb0d6..3ce4d3ccaa0630 100644 --- a/api/core/app/apps/completion/app_generator.py +++ b/api/core/app/apps/completion/app_generator.py @@ -48,6 +48,15 @@ def generate( stream: Literal[False] = False, ) -> dict: ... + @overload + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: bool = False, + ) -> dict | Generator[str, None, None]: ... + def generate(self, app_model: App, user: Union[Account, EndUser], args: Any, diff --git a/api/core/app/apps/completion/generate_response_converter.py b/api/core/app/apps/completion/generate_response_converter.py index 14db74dbd04b95..61bb03952fbec4 100644 --- a/api/core/app/apps/completion/generate_response_converter.py +++ b/api/core/app/apps/completion/generate_response_converter.py @@ -1,4 +1,3 @@ -import json from collections.abc import Generator from typing import cast @@ -51,7 +50,7 @@ def convert_blocking_simple_response(cls, blocking_response: CompletionAppBlocki @classmethod def convert_stream_full_response(cls, stream_response: Generator[CompletionAppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: """ Convert stream full response. :param stream_response: stream response @@ -76,11 +75,11 @@ def convert_stream_full_response(cls, stream_response: Generator[CompletionAppSt response_chunk.update(data) else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk @classmethod def convert_stream_simple_response(cls, stream_response: Generator[CompletionAppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: """ Convert stream simple response. :param stream_response: stream response @@ -111,4 +110,4 @@ def convert_stream_simple_response(cls, stream_response: Generator[CompletionApp else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk diff --git a/api/core/app/apps/workflow/app_generator.py b/api/core/app/apps/workflow/app_generator.py index 26bb6c0f4f70b8..f1e79ff3e36d37 100644 --- a/api/core/app/apps/workflow/app_generator.py +++ b/api/core/app/apps/workflow/app_generator.py @@ -40,7 +40,8 @@ def generate( args: dict, invoke_from: InvokeFrom, stream: Literal[True] = True, - ) -> Generator[str, None, None]: ... + call_depth: int = 0, + ) -> Generator[dict | str, None, None]: ... @overload def generate( @@ -50,8 +51,20 @@ def generate( args: dict, invoke_from: InvokeFrom, stream: Literal[False] = False, + call_depth: int = 0, ) -> dict: ... + @overload + def generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: bool = False, + call_depth: int = 0, + ) -> dict | Generator[dict | str, None, None]: ... + def generate( self, app_model: App, workflow: Workflow, @@ -127,7 +140,7 @@ def _generate( application_generate_entity: WorkflowAppGenerateEntity, invoke_from: InvokeFrom, stream: bool = True, - ) -> Union[dict, Generator[str, None, None]]: + ) -> Union[dict, Generator[str | dict, None, None]]: """ Generate App response. @@ -173,7 +186,7 @@ def _generate( def single_iteration_generate(self, app_model: App, workflow: Workflow, node_id: str, - user: Account, + user: Account | EndUser, args: dict, stream: bool = True): """ diff --git a/api/core/app/apps/workflow/generate_response_converter.py b/api/core/app/apps/workflow/generate_response_converter.py index 88bde58ba049ba..48f20d8dc1db90 100644 --- a/api/core/app/apps/workflow/generate_response_converter.py +++ b/api/core/app/apps/workflow/generate_response_converter.py @@ -1,4 +1,3 @@ -import json from collections.abc import Generator from typing import cast @@ -36,7 +35,7 @@ def convert_blocking_simple_response(cls, blocking_response: WorkflowAppBlocking @classmethod def convert_stream_full_response(cls, stream_response: Generator[WorkflowAppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: """ Convert stream full response. :param stream_response: stream response @@ -60,11 +59,11 @@ def convert_stream_full_response(cls, stream_response: Generator[WorkflowAppStre response_chunk.update(data) else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk @classmethod def convert_stream_simple_response(cls, stream_response: Generator[WorkflowAppStreamResponse, None, None]) \ - -> Generator[str, None, None]: + -> Generator[dict | str, None, None]: """ Convert stream simple response. :param stream_response: stream response @@ -90,4 +89,4 @@ def convert_stream_simple_response(cls, stream_response: Generator[WorkflowAppSt response_chunk.update(sub_stream_response.to_ignore_detail_dict()) else: response_chunk.update(sub_stream_response.to_dict()) - yield json.dumps(response_chunk) + yield response_chunk diff --git a/api/services/app_generate_service.py b/api/services/app_generate_service.py index 747505977fe282..fd7eeea48fa8be 100644 --- a/api/services/app_generate_service.py +++ b/api/services/app_generate_service.py @@ -42,48 +42,58 @@ def generate( request_id = rate_limit.enter(request_id) if app_model.mode == AppMode.COMPLETION.value: return rate_limit.generate( - CompletionAppGenerator().generate( - app_model=app_model, user=user, args=args, invoke_from=invoke_from, stream=streaming + CompletionAppGenerator.convert_to_event_stream( + CompletionAppGenerator().generate( + app_model=app_model, user=user, args=args, invoke_from=invoke_from, stream=streaming + ), ), request_id, ) elif app_model.mode == AppMode.AGENT_CHAT.value or app_model.is_agent: return rate_limit.generate( - AgentChatAppGenerator().generate( - app_model=app_model, user=user, args=args, invoke_from=invoke_from, stream=streaming + AgentChatAppGenerator.convert_to_event_stream( + AgentChatAppGenerator().generate( + app_model=app_model, user=user, args=args, invoke_from=invoke_from, stream=streaming + ), ), request_id, ) elif app_model.mode == AppMode.CHAT.value: return rate_limit.generate( - ChatAppGenerator().generate( - app_model=app_model, user=user, args=args, invoke_from=invoke_from, stream=streaming + ChatAppGenerator.convert_to_event_stream( + ChatAppGenerator().generate( + app_model=app_model, user=user, args=args, invoke_from=invoke_from, stream=streaming + ), ), request_id, ) elif app_model.mode == AppMode.ADVANCED_CHAT.value: workflow = cls._get_workflow(app_model, invoke_from) return rate_limit.generate( - AdvancedChatAppGenerator().generate( + AdvancedChatAppGenerator.convert_to_event_stream( + AdvancedChatAppGenerator().generate( app_model=app_model, workflow=workflow, user=user, args=args, invoke_from=invoke_from, stream=streaming, + ), ), request_id, ) elif app_model.mode == AppMode.WORKFLOW.value: workflow = cls._get_workflow(app_model, invoke_from) return rate_limit.generate( - WorkflowAppGenerator().generate( - app_model=app_model, - workflow=workflow, - user=user, - args=args, - invoke_from=invoke_from, - stream=streaming, + WorkflowAppGenerator.convert_to_event_stream( + WorkflowAppGenerator().generate( + app_model=app_model, + workflow=workflow, + user=user, + args=args, + invoke_from=invoke_from, + stream=streaming, + ), ), request_id, ) @@ -108,13 +118,17 @@ def generate_single_iteration( ): if app_model.mode == AppMode.ADVANCED_CHAT.value: workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER) - return AdvancedChatAppGenerator().single_iteration_generate( - app_model=app_model, workflow=workflow, node_id=node_id, user=user, args=args, stream=streaming + return AdvancedChatAppGenerator.convert_to_event_stream( + AdvancedChatAppGenerator().single_iteration_generate( + app_model=app_model, workflow=workflow, node_id=node_id, user=user, args=args, stream=streaming + ) ) elif app_model.mode == AppMode.WORKFLOW.value: workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER) - return WorkflowAppGenerator().single_iteration_generate( - app_model=app_model, workflow=workflow, node_id=node_id, user=user, args=args, stream=streaming + return AdvancedChatAppGenerator.convert_to_event_stream( + WorkflowAppGenerator().single_iteration_generate( + app_model=app_model, workflow=workflow, node_id=node_id, user=user, args=args, stream=streaming + ) ) else: raise ValueError(f"Invalid app mode {app_model.mode}") From 113ff27d07d6e35393bcb641f58bcb1acfafc51f Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 20:06:14 +0800 Subject: [PATCH 015/325] fix: types --- api/controllers/console/app/workflow.py | 43 ++++++++++++++++++++-- api/controllers/console/app/wraps.py | 2 +- api/controllers/inner_api/plugin/plugin.py | 4 +- api/core/app/apps/base_app_generator.py | 2 +- 4 files changed, 44 insertions(+), 7 deletions(-) diff --git a/api/controllers/console/app/workflow.py b/api/controllers/console/app/workflow.py index e44820f6345c48..20ec3ef021a507 100644 --- a/api/controllers/console/app/workflow.py +++ b/api/controllers/console/app/workflow.py @@ -20,6 +20,7 @@ from libs import helper from libs.helper import TimestampField, uuid_value from libs.login import current_user, login_required +from models.account import Account from models.model import App, AppMode from services.app_dsl_service import AppDslService from services.app_generate_service import AppGenerateService @@ -97,6 +98,9 @@ def post(self, app_model: App): else: abort(415) + if not isinstance(current_user, Account): + raise Forbidden() + workflow_service = WorkflowService() try: @@ -136,6 +140,9 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() parser = reqparse.RequestParser() parser.add_argument("data", type=str, required=True, nullable=False, location="json") @@ -160,6 +167,9 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() parser = reqparse.RequestParser() parser.add_argument("inputs", type=dict, location="json") @@ -197,6 +207,9 @@ def post(self, app_model: App, node_id: str): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() parser = reqparse.RequestParser() parser.add_argument("inputs", type=dict, location="json") @@ -231,6 +244,9 @@ def post(self, app_model: App, node_id: str): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() parser = reqparse.RequestParser() parser.add_argument("inputs", type=dict, location="json") @@ -265,6 +281,9 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() parser = reqparse.RequestParser() parser.add_argument("inputs", type=dict, required=True, nullable=False, location="json") @@ -315,14 +334,21 @@ def post(self, app_model: App, node_id: str): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() parser = reqparse.RequestParser() parser.add_argument("inputs", type=dict, required=True, nullable=False, location="json") args = parser.parse_args() + inputs = args.get("inputs") + if inputs == None: + raise ValueError("missing inputs") + workflow_service = WorkflowService() workflow_node_execution = workflow_service.run_draft_workflow_node( - app_model=app_model, node_id=node_id, user_inputs=args.get("inputs"), account=current_user + app_model=app_model, node_id=node_id, user_inputs=inputs, account=current_user ) return workflow_node_execution @@ -360,6 +386,9 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() workflow_service = WorkflowService() workflow = workflow_service.publish_workflow(app_model=app_model, account=current_user) @@ -397,15 +426,20 @@ def get(self, app_model: App, block_type: str): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() parser = reqparse.RequestParser() parser.add_argument("q", type=str, location="args") args = parser.parse_args() + q = args.get("q") + filters = None - if args.get("q"): + if q: try: - filters = json.loads(args.get("q")) + filters = json.loads(q) except json.JSONDecodeError: raise ValueError("Invalid filters") @@ -428,6 +462,9 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() + + if not isinstance(current_user, Account): + raise Forbidden() if request.data: parser = reqparse.RequestParser() diff --git a/api/controllers/console/app/wraps.py b/api/controllers/console/app/wraps.py index 5e0a4bc814633a..8a743d6be9f7da 100644 --- a/api/controllers/console/app/wraps.py +++ b/api/controllers/console/app/wraps.py @@ -8,7 +8,7 @@ from models.model import App, AppMode -def get_app_model(view: Optional[Callable] = None, *, mode: Union[AppMode, list[AppMode]] = None): +def get_app_model(view: Optional[Callable] = None, *, mode: Union[AppMode, list[AppMode], None] = None): def decorator(view_func): @wraps(view_func) def decorated_view(*args, **kwargs): diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index 67a51fdb2ecd56..d9b58e1e932657 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -7,7 +7,7 @@ from controllers.inner_api import api from controllers.inner_api.plugin.wraps import get_tenant, plugin_data from controllers.inner_api.wraps import plugin_inner_api_only -from core.plugin.backwards_invocation.model import PluginBackwardsInvocation +from core.plugin.backwards_invocation.model import PluginModelBackwardsInvocation from core.plugin.entities.request import ( RequestInvokeLLM, RequestInvokeModeration, @@ -29,7 +29,7 @@ class PluginInvokeLLMApi(Resource): @plugin_data(payload_type=RequestInvokeLLM) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeLLM): def generator(): - response = PluginBackwardsInvocation.invoke_llm(user_id, tenant_model, payload) + response = PluginModelBackwardsInvocation.invoke_llm(user_id, tenant_model, payload) if isinstance(response, Generator): for chunk in response: yield chunk.model_dump_json().encode() + b'\n\n' diff --git a/api/core/app/apps/base_app_generator.py b/api/core/app/apps/base_app_generator.py index 7727519aef5a08..4159670de4bbbf 100644 --- a/api/core/app/apps/base_app_generator.py +++ b/api/core/app/apps/base_app_generator.py @@ -1,5 +1,5 @@ -from collections.abc import Generator, Mapping import json +from collections.abc import Generator, Mapping from typing import Any, Optional, Union from core.app.app_config.entities import AppConfig, VariableEntity, VariableEntityType From 41ed2e0cc291543ee7338b14bf416c5bcfab7255 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 20:17:17 +0800 Subject: [PATCH 016/325] feat: backwards invoke app --- api/controllers/inner_api/plugin/plugin.py | 8 +- api/core/plugin/backwards_invocation/app.py | 141 ++++++++++++++++++ api/core/plugin/backwards_invocation/base.py | 20 +++ api/core/plugin/backwards_invocation/model.py | 5 +- api/core/plugin/entities/request.py | 14 +- api/libs/login.py | 3 +- api/models/tools.py | 9 +- 7 files changed, 187 insertions(+), 13 deletions(-) create mode 100644 api/core/plugin/backwards_invocation/app.py create mode 100644 api/core/plugin/backwards_invocation/base.py diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index d9b58e1e932657..dfe02b76351d23 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -1,5 +1,4 @@ import time -from collections.abc import Generator from flask_restful import Resource, reqparse @@ -30,15 +29,10 @@ class PluginInvokeLLMApi(Resource): def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeLLM): def generator(): response = PluginModelBackwardsInvocation.invoke_llm(user_id, tenant_model, payload) - if isinstance(response, Generator): - for chunk in response: - yield chunk.model_dump_json().encode() + b'\n\n' - else: - yield response.model_dump_json().encode() + b'\n\n' + return PluginModelBackwardsInvocation.convert_to_event_stream(response) return compact_generate_response(generator()) - class PluginInvokeTextEmbeddingApi(Resource): @setup_required @plugin_inner_api_only diff --git a/api/core/plugin/backwards_invocation/app.py b/api/core/plugin/backwards_invocation/app.py new file mode 100644 index 00000000000000..7304c637faf0f9 --- /dev/null +++ b/api/core/plugin/backwards_invocation/app.py @@ -0,0 +1,141 @@ +from collections.abc import Generator, Mapping +from typing import Literal, Union + +from core.app.apps.advanced_chat.app_generator import AdvancedChatAppGenerator +from core.app.apps.workflow.app_generator import WorkflowAppGenerator +from core.app.entities.app_invoke_entities import InvokeFrom +from core.plugin.backwards_invocation.base import BaseBackwardsInvocation +from extensions.ext_database import db +from models.account import Account +from models.model import App, AppMode, EndUser + + +class PluginAppBackwardsInvocation(BaseBackwardsInvocation): + @classmethod + def invoke_app( + cls, app_id: str, + user_id: str, + tenant_id: str, + query: str, + inputs: Mapping, + files: list[dict], + ) -> Generator[dict, None, None] | dict: + """ + invoke app + """ + app = cls._get_app(app_id, tenant_id) + if app.mode in [AppMode.ADVANCED_CHAT.value, AppMode.AGENT_CHAT.value, AppMode.CHAT.value]: + return cls.invoke_chat_app(app, user_id, tenant_id, query, inputs, files) + elif app.mode in [AppMode.WORKFLOW.value]: + return cls.invoke_workflow_app(app, user_id, tenant_id, inputs, files) + elif app.mode in [AppMode.COMPLETION]: + return cls.invoke_completion_app(app, user_id, tenant_id, inputs, files) + + raise ValueError("unexpected app type") + + @classmethod + def invoke_chat_app( + cls, + app: App, + user: Account | EndUser, + tenant_id: str, + conversation_id: str, + query: str, + stream: bool, + inputs: Mapping, + files: list[dict], + ) -> Generator[dict, None, None] | dict: + """ + invoke chat app + """ + if app.mode == AppMode.ADVANCED_CHAT.value: + workflow = app.workflow + if not workflow: + raise ValueError("unexpected app type") + + generator = AdvancedChatAppGenerator() + response = generator.generate( + app_model=app, + workflow=workflow, + user=user, + args={ + }, + invoke_from=InvokeFrom.SERVICE_API, + stream=stream + ) + + + + @classmethod + def invoke_workflow_app( + cls, + app: App, + user_id: str, + tenant_id: str, + inputs: Mapping, + files: list[dict], + ): + """ + invoke workflow app + """ + workflow = app.workflow + if not workflow: + raise ValueError("") + + generator = WorkflowAppGenerator() + + result = generator.generate( + app_model=app, + workflow=workflow, + user=cls._get_user(user_id), + args={ + 'inputs': tool_parameters, + 'files': files + }, + invoke_from=self.runtime.invoke_from, + stream=False, + call_depth=self.workflow_call_depth + 1, + ) + + @classmethod + def invoke_completion_app( + cls, + app: App, + user_id: str, + tenant_id: str, + inputs: Mapping, + files: list[dict], + ): + """ + invoke completion app + """ + + @classmethod + def _get_user(cls, user_id: str) -> Union[EndUser, Account]: + """ + get the user by user id + """ + + user = db.session.query(EndUser).filter(EndUser.id == user_id).first() + if not user: + user = db.session.query(Account).filter(Account.id == user_id).first() + + if not user: + raise ValueError('user not found') + + return user + + @classmethod + def _get_app(cls, app_id: str, tenant_id: str) -> App: + """ + get app + """ + app = db.session.query(App). \ + filter(App.id == app_id). \ + filter(App.tenant_id == tenant_id). \ + first() + + if not app: + raise ValueError("app not found") + + return app \ No newline at end of file diff --git a/api/core/plugin/backwards_invocation/base.py b/api/core/plugin/backwards_invocation/base.py new file mode 100644 index 00000000000000..28b691d9905398 --- /dev/null +++ b/api/core/plugin/backwards_invocation/base.py @@ -0,0 +1,20 @@ +import json +from collections.abc import Generator + +from pydantic import BaseModel + + +class BaseBackwardsInvocation: + @classmethod + def convert_to_event_stream(cls, response: Generator[BaseModel | dict, None, None] | BaseModel | dict): + if isinstance(response, Generator): + for chunk in response: + if isinstance(chunk, BaseModel): + yield chunk.model_dump_json().encode() + b'\n\n' + else: + yield json.dumps(chunk).encode() + b'\n\n' + else: + if isinstance(response, BaseModel): + yield response.model_dump_json().encode() + b'\n\n' + else: + yield json.dumps(response).encode() + b'\n\n' \ No newline at end of file diff --git a/api/core/plugin/backwards_invocation/model.py b/api/core/plugin/backwards_invocation/model.py index b6da133119e2b1..7904fd62340ccf 100644 --- a/api/core/plugin/backwards_invocation/model.py +++ b/api/core/plugin/backwards_invocation/model.py @@ -2,12 +2,13 @@ from core.model_manager import ModelManager from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk +from core.plugin.backwards_invocation.base import BaseBackwardsInvocation from core.plugin.entities.request import RequestInvokeLLM from core.workflow.nodes.llm.llm_node import LLMNode from models.account import Tenant -class PluginBackwardsInvocation: +class PluginModelBackwardsInvocation(BaseBackwardsInvocation): @classmethod def invoke_llm( cls, user_id: str, tenant: Tenant, payload: RequestInvokeLLM @@ -47,3 +48,5 @@ def handle() -> Generator[LLMResultChunk, None, None]: if response.usage: LLMNode.deduct_llm_quota(tenant_id=tenant.id, model_instance=model_instance, usage=response.usage) return response + + \ No newline at end of file diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index bb08facf751b44..d7781ba37558f0 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -1,4 +1,4 @@ -from typing import Any, Optional +from typing import Any, Literal, Optional from pydantic import BaseModel, Field, field_validator @@ -93,3 +93,15 @@ class RequestInvokeNode(BaseModel): """ Request to invoke node """ + +class RequestInvokeApp(BaseModel): + """ + Request to invoke app + """ + app_id: str + inputs: dict[str, Any] + query: Optional[str] = None + response_mode: Literal["blocking", "streaming"] + conversation_id: Optional[str] = None + user: Optional[str] = None + files: list[dict] = Field(default_factory=list) diff --git a/api/libs/login.py b/api/libs/login.py index 7f05eb8404a0ba..8431d967bd1ee9 100644 --- a/api/libs/login.py +++ b/api/libs/login.py @@ -9,6 +9,7 @@ from extensions.ext_database import db from models.account import Account, Tenant, TenantAccountJoin +from models.model import EndUser #: A proxy for the current user. If no user is logged in, this will be an #: anonymous user @@ -96,7 +97,7 @@ def decorated_view(*args, **kwargs): return decorated_view -def _get_user(): +def _get_user() -> EndUser | Account | None: if has_request_context(): if "_login_user" not in g: current_app.login_manager._load_user() diff --git a/api/models/tools.py b/api/models/tools.py index 3ee246eeb33de5..937481583ab799 100644 --- a/api/models/tools.py +++ b/api/models/tools.py @@ -278,7 +278,10 @@ class ToolConversationVariables(db.Model): def variables(self) -> dict: return json.loads(self.variables_str) -class ToolFile(DeclarativeBase): +class Base(DeclarativeBase): + pass + +class ToolFile(Base): """ store the file created by agent """ @@ -293,9 +296,9 @@ class ToolFile(DeclarativeBase): # conversation user id user_id: Mapped[str] = mapped_column(StringUUID) # tenant id - tenant_id: Mapped[StringUUID] = mapped_column(StringUUID) + tenant_id: Mapped[str] = mapped_column(StringUUID) # conversation id - conversation_id: Mapped[StringUUID] = mapped_column(nullable=True) + conversation_id: Mapped[str] = mapped_column(StringUUID, nullable=True) # file key file_key: Mapped[str] = mapped_column(db.String(255), nullable=False) # mime type From 12ea085e224cf2b487c66b30c7183885f9e5fe7d Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 20:50:36 +0800 Subject: [PATCH 017/325] feat: implement invoke app args --- api/controllers/inner_api/plugin/plugin.py | 29 ++++-- api/core/plugin/backwards_invocation/app.py | 96 +++++++++++++++----- api/core/plugin/backwards_invocation/base.py | 6 +- api/core/plugin/entities/request.py | 1 + api/services/plugin/plugin_invoke_service.py | 49 ---------- 5 files changed, 99 insertions(+), 82 deletions(-) delete mode 100644 api/services/plugin/plugin_invoke_service.py diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index dfe02b76351d23..c7886b5773397e 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -6,10 +6,13 @@ from controllers.inner_api import api from controllers.inner_api.plugin.wraps import get_tenant, plugin_data from controllers.inner_api.wraps import plugin_inner_api_only +from core.plugin.backwards_invocation.app import PluginAppBackwardsInvocation from core.plugin.backwards_invocation.model import PluginModelBackwardsInvocation from core.plugin.entities.request import ( + RequestInvokeApp, RequestInvokeLLM, RequestInvokeModeration, + RequestInvokeNode, RequestInvokeRerank, RequestInvokeSpeech2Text, RequestInvokeTextEmbedding, @@ -104,21 +107,33 @@ class PluginInvokeNodeApi(Resource): @setup_required @plugin_inner_api_only @get_tenant - def post(self, user_id: str, tenant_model: Tenant): - parser = reqparse.RequestParser() - args = parser.parse_args() - - return {'message': 'success'} + @plugin_data(payload_type=RequestInvokeNode) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeNode): + pass class PluginInvokeAppApi(Resource): @setup_required @plugin_inner_api_only @get_tenant - def post(self, user_id: str, tenant_model: Tenant): + @plugin_data(payload_type=RequestInvokeApp) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeApp): parser = reqparse.RequestParser() args = parser.parse_args() - return {'message': 'success'} + response = PluginAppBackwardsInvocation.invoke_app( + app_id=payload.app_id, + user_id=user_id, + tenant_id=tenant_model.id, + conversation_id=payload.conversation_id, + query=payload.query, + stream=payload.stream, + inputs=payload.inputs, + files=payload.files + ) + + return compact_generate_response( + PluginAppBackwardsInvocation.convert_to_event_stream(response) + ) api.add_resource(PluginInvokeLLMApi, '/invoke/llm') api.add_resource(PluginInvokeTextEmbeddingApi, '/invoke/text-embedding') diff --git a/api/core/plugin/backwards_invocation/app.py b/api/core/plugin/backwards_invocation/app.py index 7304c637faf0f9..d20e0535dc7a40 100644 --- a/api/core/plugin/backwards_invocation/app.py +++ b/api/core/plugin/backwards_invocation/app.py @@ -1,7 +1,10 @@ from collections.abc import Generator, Mapping -from typing import Literal, Union +from typing import Optional, Union from core.app.apps.advanced_chat.app_generator import AdvancedChatAppGenerator +from core.app.apps.agent_chat.app_generator import AgentChatAppGenerator +from core.app.apps.chat.app_generator import ChatAppGenerator +from core.app.apps.completion.app_generator import CompletionAppGenerator from core.app.apps.workflow.app_generator import WorkflowAppGenerator from core.app.entities.app_invoke_entities import InvokeFrom from core.plugin.backwards_invocation.base import BaseBackwardsInvocation @@ -16,20 +19,29 @@ def invoke_app( cls, app_id: str, user_id: str, tenant_id: str, - query: str, + conversation_id: Optional[str], + query: Optional[str], + stream: bool, inputs: Mapping, files: list[dict], - ) -> Generator[dict, None, None] | dict: + ) -> Generator[dict | str, None, None] | dict: """ invoke app """ app = cls._get_app(app_id, tenant_id) + user = cls._get_user(user_id) + + conversation_id = conversation_id or "" + if app.mode in [AppMode.ADVANCED_CHAT.value, AppMode.AGENT_CHAT.value, AppMode.CHAT.value]: - return cls.invoke_chat_app(app, user_id, tenant_id, query, inputs, files) + if not query: + raise ValueError("missing query") + + return cls.invoke_chat_app(app, user, conversation_id, query, stream, inputs, files) elif app.mode in [AppMode.WORKFLOW.value]: - return cls.invoke_workflow_app(app, user_id, tenant_id, inputs, files) + return cls.invoke_workflow_app(app, user, stream, inputs, files) elif app.mode in [AppMode.COMPLETION]: - return cls.invoke_completion_app(app, user_id, tenant_id, inputs, files) + return cls.invoke_completion_app(app, user, stream, inputs, files) raise ValueError("unexpected app type") @@ -38,13 +50,12 @@ def invoke_chat_app( cls, app: App, user: Account | EndUser, - tenant_id: str, conversation_id: str, query: str, stream: bool, inputs: Mapping, files: list[dict], - ) -> Generator[dict, None, None] | dict: + ) -> Generator[dict | str, None, None] | dict: """ invoke chat app """ @@ -53,25 +64,54 @@ def invoke_chat_app( if not workflow: raise ValueError("unexpected app type") - generator = AdvancedChatAppGenerator() - response = generator.generate( + return AdvancedChatAppGenerator().generate( app_model=app, workflow=workflow, user=user, args={ + "inputs": inputs, + "query": query, + "files": files, + "conversation_id": conversation_id, + }, + invoke_from=InvokeFrom.SERVICE_API, + stream=stream + ) + elif app.mode == AppMode.AGENT_CHAT.value: + return AgentChatAppGenerator().generate( + app_model=app, + user=user, + args={ + "inputs": inputs, + "query": query, + "files": files, + "conversation_id": conversation_id, + }, + invoke_from=InvokeFrom.SERVICE_API, + stream=stream + ) + elif app.mode == AppMode.CHAT.value: + return ChatAppGenerator().generate( + app_model=app, + user=user, + args={ + "inputs": inputs, + "query": query, + "files": files, + "conversation_id": conversation_id, }, invoke_from=InvokeFrom.SERVICE_API, stream=stream ) + else: + raise ValueError("unexpected app type") - - @classmethod def invoke_workflow_app( cls, app: App, - user_id: str, - tenant_id: str, + user: EndUser | Account, + stream: bool, inputs: Mapping, files: list[dict], ): @@ -82,33 +122,41 @@ def invoke_workflow_app( if not workflow: raise ValueError("") - generator = WorkflowAppGenerator() - - result = generator.generate( + return WorkflowAppGenerator().generate( app_model=app, workflow=workflow, - user=cls._get_user(user_id), + user=user, args={ - 'inputs': tool_parameters, + 'inputs': inputs, 'files': files }, - invoke_from=self.runtime.invoke_from, - stream=False, - call_depth=self.workflow_call_depth + 1, + invoke_from=InvokeFrom.SERVICE_API, + stream=stream, + call_depth=1, ) @classmethod def invoke_completion_app( cls, app: App, - user_id: str, - tenant_id: str, + user: EndUser | Account, + stream: bool, inputs: Mapping, files: list[dict], ): """ invoke completion app """ + return CompletionAppGenerator().generate( + app_model=app, + user=user, + args={ + 'inputs': inputs, + 'files': files + }, + invoke_from=InvokeFrom.SERVICE_API, + stream=stream, + ) @classmethod def _get_user(cls, user_id: str) -> Union[EndUser, Account]: diff --git a/api/core/plugin/backwards_invocation/base.py b/api/core/plugin/backwards_invocation/base.py index 28b691d9905398..065e7135949c2c 100644 --- a/api/core/plugin/backwards_invocation/base.py +++ b/api/core/plugin/backwards_invocation/base.py @@ -6,15 +6,17 @@ class BaseBackwardsInvocation: @classmethod - def convert_to_event_stream(cls, response: Generator[BaseModel | dict, None, None] | BaseModel | dict): + def convert_to_event_stream(cls, response: Generator[BaseModel | dict | str, None, None] | BaseModel | dict): if isinstance(response, Generator): for chunk in response: if isinstance(chunk, BaseModel): yield chunk.model_dump_json().encode() + b'\n\n' + if isinstance(chunk, str): + yield f"event: {chunk}\n\n".encode() else: yield json.dumps(chunk).encode() + b'\n\n' else: if isinstance(response, BaseModel): yield response.model_dump_json().encode() + b'\n\n' else: - yield json.dumps(response).encode() + b'\n\n' \ No newline at end of file + yield json.dumps(response).encode() + b'\n\n' diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index d7781ba37558f0..2a24beb0c80af1 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -105,3 +105,4 @@ class RequestInvokeApp(BaseModel): conversation_id: Optional[str] = None user: Optional[str] = None files: list[dict] = Field(default_factory=list) + stream: bool = Field(default=False) \ No newline at end of file diff --git a/api/services/plugin/plugin_invoke_service.py b/api/services/plugin/plugin_invoke_service.py deleted file mode 100644 index 317b42a6e16f75..00000000000000 --- a/api/services/plugin/plugin_invoke_service.py +++ /dev/null @@ -1,49 +0,0 @@ -from collections.abc import Generator -from typing import Any, Union - -from core.app.entities.app_invoke_entities import InvokeFrom -from core.callback_handler.plugin_tool_callback_handler import DifyPluginCallbackHandler -from core.model_runtime.entities.model_entities import ModelType -from core.tools.entities.tool_entities import ToolInvokeMessage, ToolProviderType -from core.tools.tool_engine import ToolEngine -from core.tools.tool_manager import ToolManager -from core.tools.utils.message_transformer import ToolFileMessageTransformer -from core.workflow.entities.node_entities import NodeType -from models.account import Tenant -from services.tools.tools_transform_service import ToolTransformService - - -class PluginInvokeService: - @classmethod - def invoke_tool(cls, user_id: str, invoke_from: InvokeFrom, tenant: Tenant, - tool_provider_type: ToolProviderType, tool_provider: str, tool_name: str, - tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage]: - """ - Invokes a tool with the given user ID and tool parameters. - """ - tool_runtime = ToolManager.get_tool_runtime(tool_provider_type, provider_id=tool_provider, - tool_name=tool_name, tenant_id=tenant.id, - invoke_from=invoke_from) - - response = ToolEngine.plugin_invoke(tool_runtime, - tool_parameters, - user_id, - callback=DifyPluginCallbackHandler()) - response = ToolFileMessageTransformer.transform_tool_invoke_messages(response) - return ToolTransformService.transform_messages_to_dict(response) - - @classmethod - def invoke_model(cls, user_id: str, tenant: Tenant, - model_provider: str, model_name: str, model_type: ModelType, - model_parameters: dict[str, Any]) -> Union[dict, Generator[ToolInvokeMessage]]: - """ - Invokes a model with the given user ID and model parameters. - """ - - @classmethod - def invoke_workflow_node(cls, user_id: str, tenant: Tenant, - node_type: NodeType, node_data: dict[str, Any], - inputs: dict[str, Any]) -> Generator[ToolInvokeMessage]: - """ - Invokes a workflow node with the given user ID and node parameters. - """ \ No newline at end of file From ece82b87bfa9a9b555af73c49884c9be870129b1 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 21:14:23 +0800 Subject: [PATCH 018/325] feat: invoke app --- api/controllers/inner_api/plugin/plugin.py | 7 ++----- api/core/plugin/backwards_invocation/base.py | 2 +- api/core/plugin/entities/request.py | 2 +- 3 files changed, 4 insertions(+), 7 deletions(-) diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index c7886b5773397e..1586d39b4178d7 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -1,6 +1,6 @@ import time -from flask_restful import Resource, reqparse +from flask_restful import Resource from controllers.console.setup import setup_required from controllers.inner_api import api @@ -117,16 +117,13 @@ class PluginInvokeAppApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeApp) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeApp): - parser = reqparse.RequestParser() - args = parser.parse_args() - response = PluginAppBackwardsInvocation.invoke_app( app_id=payload.app_id, user_id=user_id, tenant_id=tenant_model.id, conversation_id=payload.conversation_id, query=payload.query, - stream=payload.stream, + stream=payload.response_mode == 'streaming', inputs=payload.inputs, files=payload.files ) diff --git a/api/core/plugin/backwards_invocation/base.py b/api/core/plugin/backwards_invocation/base.py index 065e7135949c2c..7b699b4d6784f5 100644 --- a/api/core/plugin/backwards_invocation/base.py +++ b/api/core/plugin/backwards_invocation/base.py @@ -11,7 +11,7 @@ def convert_to_event_stream(cls, response: Generator[BaseModel | dict | str, Non for chunk in response: if isinstance(chunk, BaseModel): yield chunk.model_dump_json().encode() + b'\n\n' - if isinstance(chunk, str): + elif isinstance(chunk, str): yield f"event: {chunk}\n\n".encode() else: yield json.dumps(chunk).encode() + b'\n\n' diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 2a24beb0c80af1..fd22d1f057ebc7 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -105,4 +105,4 @@ class RequestInvokeApp(BaseModel): conversation_id: Optional[str] = None user: Optional[str] = None files: list[dict] = Field(default_factory=list) - stream: bool = Field(default=False) \ No newline at end of file + \ No newline at end of file From 50a5cfe56a1fd583e682964468a5779d934a23ab Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 29 Aug 2024 21:48:20 +0800 Subject: [PATCH 019/325] fix: endpoint using default user --- api/core/plugin/backwards_invocation/app.py | 17 ++++++++++++----- 1 file changed, 12 insertions(+), 5 deletions(-) diff --git a/api/core/plugin/backwards_invocation/app.py b/api/core/plugin/backwards_invocation/app.py index d20e0535dc7a40..b1e1065affce80 100644 --- a/api/core/plugin/backwards_invocation/app.py +++ b/api/core/plugin/backwards_invocation/app.py @@ -1,6 +1,7 @@ from collections.abc import Generator, Mapping from typing import Optional, Union +from controllers.service_api.wraps import create_or_update_end_user_for_user_id from core.app.apps.advanced_chat.app_generator import AdvancedChatAppGenerator from core.app.apps.agent_chat.app_generator import AgentChatAppGenerator from core.app.apps.chat.app_generator import ChatAppGenerator @@ -29,7 +30,10 @@ def invoke_app( invoke app """ app = cls._get_app(app_id, tenant_id) - user = cls._get_user(user_id) + if not user_id: + user = create_or_update_end_user_for_user_id(app) + else: + user = cls._get_user(user_id) conversation_id = conversation_id or "" @@ -178,10 +182,13 @@ def _get_app(cls, app_id: str, tenant_id: str) -> App: """ get app """ - app = db.session.query(App). \ - filter(App.id == app_id). \ - filter(App.tenant_id == tenant_id). \ - first() + try: + app = db.session.query(App). \ + filter(App.id == app_id). \ + filter(App.tenant_id == tenant_id). \ + first() + except Exception: + raise ValueError("app not found") if not app: raise ValueError("app not found") From 1fa3b9cfd8834e2f80ed2104498098acd189e059 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 30 Aug 2024 14:23:14 +0800 Subject: [PATCH 020/325] refactor tools --- api/controllers/inner_api/plugin/plugin.py | 9 ++ api/controllers/inner_api/wraps.py | 2 + api/core/app/entities/queue_entities.py | 2 +- api/core/entities/parameter_entities.py | 30 +++++ api/core/entities/provider_entities.py | 55 ++++++++- api/core/file/tool_file_parser.py | 7 +- api/core/plugin/entities/request.py | 14 ++- api/core/tools/entities/api_entities.py | 4 +- api/core/tools/entities/tool_entities.py | 71 ++--------- api/core/tools/provider/api_tool_provider.py | 18 +-- api/core/tools/provider/app_tool_provider.py | 115 ------------------ .../tools/provider/builtin_tool_provider.py | 92 ++------------ api/core/tools/provider/tool_provider.py | 113 +++-------------- .../tools/provider/workflow_tool_provider.py | 19 +-- api/core/tools/tool/tool.py | 2 +- api/core/tools/tool_manager.py | 89 ++++++++------ api/core/tools/utils/configuration.py | 8 +- .../utils/workflow_configuration_sync.py | 6 +- .../tools/api_tools_manage_service.py | 14 +-- api/services/tools/tools_transform_service.py | 4 +- 20 files changed, 239 insertions(+), 435 deletions(-) create mode 100644 api/core/entities/parameter_entities.py delete mode 100644 api/core/tools/provider/app_tool_provider.py diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index 1586d39b4178d7..c3911f31aeb56a 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -10,6 +10,7 @@ from core.plugin.backwards_invocation.model import PluginModelBackwardsInvocation from core.plugin.entities.request import ( RequestInvokeApp, + RequestInvokeEncrypt, RequestInvokeLLM, RequestInvokeModeration, RequestInvokeNode, @@ -132,6 +133,14 @@ def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeApp): PluginAppBackwardsInvocation.convert_to_event_stream(response) ) +class PluginInvokeEncryptApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + @plugin_data(payload_type=RequestInvokeEncrypt) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeEncrypt): + """""" + api.add_resource(PluginInvokeLLMApi, '/invoke/llm') api.add_resource(PluginInvokeTextEmbeddingApi, '/invoke/text-embedding') api.add_resource(PluginInvokeRerankApi, '/invoke/rerank') diff --git a/api/controllers/inner_api/wraps.py b/api/controllers/inner_api/wraps.py index 754b792d6193c1..235359a9bb0bb6 100644 --- a/api/controllers/inner_api/wraps.py +++ b/api/controllers/inner_api/wraps.py @@ -46,6 +46,8 @@ def decorated(*args, **kwargs): user_id = user_id.split(" ")[1] inner_api_key = request.headers.get("X-Inner-Api-Key") + if not inner_api_key: + raise ValueError("inner api key not found") data_to_sign = f"DIFY {user_id}" diff --git a/api/core/app/entities/queue_entities.py b/api/core/app/entities/queue_entities.py index 15348251f2de35..73476bef58a302 100644 --- a/api/core/app/entities/queue_entities.py +++ b/api/core/app/entities/queue_entities.py @@ -60,7 +60,7 @@ class QueueIterationStartEvent(AppQueueEvent): node_data: BaseNodeData node_run_index: int - inputs: dict = None + inputs: Optional[dict] = None predecessor_node_id: Optional[str] = None metadata: Optional[dict] = None diff --git a/api/core/entities/parameter_entities.py b/api/core/entities/parameter_entities.py new file mode 100644 index 00000000000000..cc402de7736a55 --- /dev/null +++ b/api/core/entities/parameter_entities.py @@ -0,0 +1,30 @@ +from enum import Enum + + +class CommonParameterType(Enum): + SECRET_INPUT = "secret-input" + TEXT_INPUT = "text-input" + SELECT = "select" + STRING = "string" + NUMBER = "number" + FILE = "file" + BOOLEAN = "boolean" + APP_SELECTOR = "app-selector" + MODEL_CONFIG = "model-config" + + +class AppSelectorScope(Enum): + ALL = "all" + CHAT = "chat" + WORKFLOW = "workflow" + COMPLETION = "completion" + + +class ModelConfigScope(Enum): + LLM = "llm" + TEXT_EMBEDDING = "text-embedding" + RERANK = "rerank" + TTS = "tts" + SPEECH2TEXT = "speech2text" + MODERATION = "moderation" + VISION = "vision" \ No newline at end of file diff --git a/api/core/entities/provider_entities.py b/api/core/entities/provider_entities.py index 0d5b0a1b2c6ba6..ae78d9ecf93b27 100644 --- a/api/core/entities/provider_entities.py +++ b/api/core/entities/provider_entities.py @@ -1,8 +1,10 @@ from enum import Enum -from typing import Optional +from typing import Optional, Union -from pydantic import BaseModel, ConfigDict +from pydantic import BaseModel, ConfigDict, Field +from core.entities.parameter_entities import AppSelectorScope, CommonParameterType, ModelConfigScope +from core.model_runtime.entities.common_entities import I18nObject from core.model_runtime.entities.model_entities import ModelType from models.provider import ProviderQuotaType @@ -100,3 +102,52 @@ class ModelSettings(BaseModel): # pydantic configs model_config = ConfigDict(protected_namespaces=()) + +class BasicProviderConfig(BaseModel): + """ + Base model class for common provider settings like credentials + """ + class Type(Enum): + SECRET_INPUT = CommonParameterType.SECRET_INPUT.value + TEXT_INPUT = CommonParameterType.TEXT_INPUT.value + SELECT = CommonParameterType.SELECT.value + BOOLEAN = CommonParameterType.BOOLEAN.value + APP_SELECTOR = CommonParameterType.APP_SELECTOR.value + MODEL_CONFIG = CommonParameterType.MODEL_CONFIG.value + + @classmethod + def value_of(cls, value: str) -> "ProviderConfig.Type": + """ + Get value of given mode. + + :param value: mode value + :return: mode + """ + for mode in cls: + if mode.value == value: + return mode + raise ValueError(f'invalid mode value {value}') + + @staticmethod + def default(value: str) -> str: + return "" + + type: Type = Field(..., description="The type of the credentials") + name: str = Field(..., description="The name of the credentials") + +class ProviderConfig(BasicProviderConfig): + """ + Model class for common provider settings like credentials + """ + class Option(BaseModel): + value: str = Field(..., description="The value of the option") + label: I18nObject = Field(..., description="The label of the option") + + scope: AppSelectorScope | ModelConfigScope | None + required: bool = False + default: Optional[Union[int, str]] = None + options: Optional[list[Option]] = None + label: Optional[I18nObject] = None + help: Optional[I18nObject] = None + url: Optional[str] = None + placeholder: Optional[I18nObject] = None diff --git a/api/core/file/tool_file_parser.py b/api/core/file/tool_file_parser.py index ea8605ac577e3a..98226e89c057f4 100644 --- a/api/core/file/tool_file_parser.py +++ b/api/core/file/tool_file_parser.py @@ -1,4 +1,9 @@ -tool_file_manager = { +from typing import TYPE_CHECKING, Any + +if TYPE_CHECKING: + from core.tools.tool_file_manager import ToolFileManager + +tool_file_manager: dict[str, Any] = { 'manager': None } diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index fd22d1f057ebc7..0533746815f0a0 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -1,7 +1,9 @@ +from collections.abc import Mapping from typing import Any, Literal, Optional from pydantic import BaseModel, Field, field_validator +from core.entities.provider_entities import BasicProviderConfig from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, PromptMessage, @@ -30,11 +32,10 @@ class RequestInvokeLLM(BaseRequestInvokeModel): """ Request to invoke LLM """ - model_type: ModelType = ModelType.LLM mode: str model_parameters: dict[str, Any] = Field(default_factory=dict) - prompt_messages: list[PromptMessage] + prompt_messages: list[PromptMessage] = Field(default_factory=list) tools: Optional[list[PromptMessageTool]] = Field(default_factory=list) stop: Optional[list[str]] = Field(default_factory=list) stream: Optional[bool] = False @@ -105,4 +106,11 @@ class RequestInvokeApp(BaseModel): conversation_id: Optional[str] = None user: Optional[str] = None files: list[dict] = Field(default_factory=list) - \ No newline at end of file + +class RequestInvokeEncrypt(BaseModel): + """ + Request to encryption + """ + opt: Literal["encrypt", "decrypt"] + data: dict = Field(default_factory=dict) + config: Mapping[str, BasicProviderConfig] = Field(default_factory=Mapping) diff --git a/api/core/tools/entities/api_entities.py b/api/core/tools/entities/api_entities.py index 2b01b8fd8e89c9..71db8d8b2dfc77 100644 --- a/api/core/tools/entities/api_entities.py +++ b/api/core/tools/entities/api_entities.py @@ -4,7 +4,7 @@ from core.model_runtime.utils.encoders import jsonable_encoder from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ToolProviderCredentials, ToolProviderType +from core.tools.entities.tool_entities import ProviderConfig, ToolProviderType from core.tools.tool.tool import ToolParameter @@ -62,4 +62,4 @@ def to_dict(self) -> dict: } class UserToolProviderCredentials(BaseModel): - credentials: dict[str, ToolProviderCredentials] \ No newline at end of file + credentials: dict[str, ProviderConfig] \ No newline at end of file diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index c266db1cdbd1d8..98efb92a0d9d73 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -3,6 +3,7 @@ from pydantic import BaseModel, Field, field_validator +from core.entities.parameter_entities import AppSelectorScope, CommonParameterType, ModelConfigScope from core.tools.entities.common_entities import I18nObject @@ -137,12 +138,12 @@ def transform_id_to_str(cls, value) -> str: class ToolParameter(BaseModel): class ToolParameterType(str, Enum): - STRING = "string" - NUMBER = "number" - BOOLEAN = "boolean" - SELECT = "select" - SECRET_INPUT = "secret-input" - FILE = "file" + STRING = CommonParameterType.STRING.value + NUMBER = CommonParameterType.NUMBER.value + BOOLEAN = CommonParameterType.BOOLEAN.value + SELECT = CommonParameterType.SELECT.value + SECRET_INPUT = CommonParameterType.SECRET_INPUT.value + FILE = CommonParameterType.FILE.value class ToolParameterForm(Enum): SCHEMA = "schema" # should be set while adding tool @@ -151,16 +152,17 @@ class ToolParameterForm(Enum): name: str = Field(..., description="The name of the parameter") label: I18nObject = Field(..., description="The label presented to the user") - human_description: Optional[I18nObject] = Field(None, description="The description presented to the user") - placeholder: Optional[I18nObject] = Field(None, description="The placeholder presented to the user") + human_description: Optional[I18nObject] = Field(default=None, description="The description presented to the user") + placeholder: Optional[I18nObject] = Field(default=None, description="The placeholder presented to the user") type: ToolParameterType = Field(..., description="The type of the parameter") + scope: AppSelectorScope | ModelConfigScope | None = None form: ToolParameterForm = Field(..., description="The form of the parameter, schema/form/llm") llm_description: Optional[str] = None required: Optional[bool] = False default: Optional[Union[float, int, str]] = None min: Optional[Union[float, int]] = None max: Optional[Union[float, int]] = None - options: Optional[list[ToolParameterOption]] = None + options: list[ToolParameterOption] = Field(default_factory=list) @classmethod def get_simple_instance(cls, @@ -211,57 +213,6 @@ class ToolIdentity(BaseModel): provider: str = Field(..., description="The provider of the tool") icon: Optional[str] = None -class ToolCredentialsOption(BaseModel): - value: str = Field(..., description="The value of the option") - label: I18nObject = Field(..., description="The label of the option") - -class ToolProviderCredentials(BaseModel): - class CredentialsType(Enum): - SECRET_INPUT = "secret-input" - TEXT_INPUT = "text-input" - SELECT = "select" - BOOLEAN = "boolean" - - @classmethod - def value_of(cls, value: str) -> "ToolProviderCredentials.CredentialsType": - """ - Get value of given mode. - - :param value: mode value - :return: mode - """ - for mode in cls: - if mode.value == value: - return mode - raise ValueError(f'invalid mode value {value}') - - @staticmethod - def default(value: str) -> str: - return "" - - name: str = Field(..., description="The name of the credentials") - type: CredentialsType = Field(..., description="The type of the credentials") - required: bool = False - default: Optional[Union[int, str]] = None - options: Optional[list[ToolCredentialsOption]] = None - label: Optional[I18nObject] = None - help: Optional[I18nObject] = None - url: Optional[str] = None - placeholder: Optional[I18nObject] = None - - def to_dict(self) -> dict: - return { - 'name': self.name, - 'type': self.type.value, - 'required': self.required, - 'default': self.default, - 'options': self.options, - 'help': self.help.to_dict() if self.help else None, - 'label': self.label.to_dict() if self.label else None, - 'url': self.url, - 'placeholder': self.placeholder.to_dict() if self.placeholder else None, - } - class ToolRuntimeVariableType(Enum): TEXT = "text" IMAGE = "image" diff --git a/api/core/tools/provider/api_tool_provider.py b/api/core/tools/provider/api_tool_provider.py index ae80ad2114cce0..fc7fcb675a7ad8 100644 --- a/api/core/tools/provider/api_tool_provider.py +++ b/api/core/tools/provider/api_tool_provider.py @@ -3,8 +3,8 @@ from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( ApiProviderAuthType, + ProviderConfig, ToolCredentialsOption, - ToolProviderCredentials, ToolProviderType, ) from core.tools.provider.tool_provider import ToolProviderController @@ -20,10 +20,10 @@ class ApiToolProviderController(ToolProviderController): @staticmethod def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> 'ApiToolProviderController': credentials_schema = { - 'auth_type': ToolProviderCredentials( + 'auth_type': ProviderConfig( name='auth_type', required=True, - type=ToolProviderCredentials.CredentialsType.SELECT, + type=ProviderConfig.Type.SELECT, options=[ ToolCredentialsOption(value='none', label=I18nObject(en_US='None', zh_Hans='无')), ToolCredentialsOption(value='api_key', label=I18nObject(en_US='api_key', zh_Hans='api_key')) @@ -38,30 +38,30 @@ def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> 'Ap if auth_type == ApiProviderAuthType.API_KEY: credentials_schema = { **credentials_schema, - 'api_key_header': ToolProviderCredentials( + 'api_key_header': ProviderConfig( name='api_key_header', required=False, default='api_key', - type=ToolProviderCredentials.CredentialsType.TEXT_INPUT, + type=ProviderConfig.Type.TEXT_INPUT, help=I18nObject( en_US='The header name of the api key', zh_Hans='携带 api key 的 header 名称' ) ), - 'api_key_value': ToolProviderCredentials( + 'api_key_value': ProviderConfig( name='api_key_value', required=True, - type=ToolProviderCredentials.CredentialsType.SECRET_INPUT, + type=ProviderConfig.Type.SECRET_INPUT, help=I18nObject( en_US='The api key', zh_Hans='api key的值' ) ), - 'api_key_header_prefix': ToolProviderCredentials( + 'api_key_header_prefix': ProviderConfig( name='api_key_header_prefix', required=False, default='basic', - type=ToolProviderCredentials.CredentialsType.SELECT, + type=ProviderConfig.Type.SELECT, help=I18nObject( en_US='The prefix of the api key header', zh_Hans='api key header 的前缀' diff --git a/api/core/tools/provider/app_tool_provider.py b/api/core/tools/provider/app_tool_provider.py deleted file mode 100644 index 2d472e0a93c866..00000000000000 --- a/api/core/tools/provider/app_tool_provider.py +++ /dev/null @@ -1,115 +0,0 @@ -import logging -from typing import Any - -from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ToolParameter, ToolParameterOption, ToolProviderType -from core.tools.provider.tool_provider import ToolProviderController -from core.tools.tool.tool import Tool -from extensions.ext_database import db -from models.model import App, AppModelConfig -from models.tools import PublishedAppTool - -logger = logging.getLogger(__name__) - -class AppToolProviderEntity(ToolProviderController): - @property - def provider_type(self) -> ToolProviderType: - return ToolProviderType.APP - - def _validate_credentials(self, tool_name: str, credentials: dict[str, Any]) -> None: - pass - - def validate_parameters(self, tool_name: str, tool_parameters: dict[str, Any]) -> None: - pass - - def get_tools(self, user_id: str) -> list[Tool]: - db_tools: list[PublishedAppTool] = db.session.query(PublishedAppTool).filter( - PublishedAppTool.user_id == user_id, - ).all() - - if not db_tools or len(db_tools) == 0: - return [] - - tools: list[Tool] = [] - - for db_tool in db_tools: - tool = { - 'identity': { - 'author': db_tool.author, - 'name': db_tool.tool_name, - 'label': { - 'en_US': db_tool.tool_name, - 'zh_Hans': db_tool.tool_name - }, - 'icon': '' - }, - 'description': { - 'human': { - 'en_US': db_tool.description_i18n.en_US, - 'zh_Hans': db_tool.description_i18n.zh_Hans - }, - 'llm': db_tool.llm_description - }, - 'parameters': [] - } - # get app from db - app: App = db_tool.app - - if not app: - logger.error(f"app {db_tool.app_id} not found") - continue - - app_model_config: AppModelConfig = app.app_model_config - user_input_form_list = app_model_config.user_input_form_list - for input_form in user_input_form_list: - # get type - form_type = input_form.keys()[0] - default = input_form[form_type]['default'] - required = input_form[form_type]['required'] - label = input_form[form_type]['label'] - variable_name = input_form[form_type]['variable_name'] - options = input_form[form_type].get('options', []) - if form_type == 'paragraph' or form_type == 'text-input': - tool['parameters'].append(ToolParameter( - name=variable_name, - label=I18nObject( - en_US=label, - zh_Hans=label - ), - human_description=I18nObject( - en_US=label, - zh_Hans=label - ), - llm_description=label, - form=ToolParameter.ToolParameterForm.FORM, - type=ToolParameter.ToolParameterType.STRING, - required=required, - default=default - )) - elif form_type == 'select': - tool['parameters'].append(ToolParameter( - name=variable_name, - label=I18nObject( - en_US=label, - zh_Hans=label - ), - human_description=I18nObject( - en_US=label, - zh_Hans=label - ), - llm_description=label, - form=ToolParameter.ToolParameterForm.FORM, - type=ToolParameter.ToolParameterType.SELECT, - required=required, - default=default, - options=[ToolParameterOption( - value=option, - label=I18nObject( - en_US=option, - zh_Hans=option - ) - ) for option in options] - )) - - tools.append(Tool(**tool)) - return tools \ No newline at end of file diff --git a/api/core/tools/provider/builtin_tool_provider.py b/api/core/tools/provider/builtin_tool_provider.py index bcf41c90edbfcd..7ad8a5468b131d 100644 --- a/api/core/tools/provider/builtin_tool_provider.py +++ b/api/core/tools/provider/builtin_tool_provider.py @@ -2,22 +2,23 @@ from os import listdir, path from typing import Any +from pydantic import Field + +from core.entities.provider_entities import ProviderConfig from core.helper.module_import_helper import load_single_subclass_from_source -from core.tools.entities.tool_entities import ToolParameter, ToolProviderCredentials, ToolProviderType +from core.tools.entities.tool_entities import ToolProviderType from core.tools.entities.values import ToolLabelEnum, default_tool_label_dict from core.tools.errors import ( - ToolNotFoundError, - ToolParameterValidationError, ToolProviderNotFoundError, ) from core.tools.provider.tool_provider import ToolProviderController from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.tool.tool import Tool -from core.tools.utils.tool_parameter_converter import ToolParameterConverter from core.tools.utils.yaml_utils import load_yaml_file class BuiltinToolProviderController(ToolProviderController): + tools: list[BuiltinTool] = Field(default_factory=list) + def __init__(self, **data: Any) -> None: if self.provider_type == ToolProviderType.API or self.provider_type == ToolProviderType.APP: super().__init__(**data) @@ -41,7 +42,7 @@ def __init__(self, **data: Any) -> None: 'credentials_schema': provider_yaml.get('credentials_for_provider', None), }) - def _get_builtin_tools(self) -> list[Tool]: + def _get_builtin_tools(self) -> list[BuiltinTool]: """ returns a list of tools that the provider can provide @@ -72,7 +73,7 @@ def _get_builtin_tools(self) -> list[Tool]: self.tools = tools return tools - def get_credentials_schema(self) -> dict[str, ToolProviderCredentials]: + def get_credentials_schema(self) -> dict[str, ProviderConfig]: """ returns the credentials schema of the provider @@ -83,7 +84,7 @@ def get_credentials_schema(self) -> dict[str, ToolProviderCredentials]: return self.credentials_schema.copy() - def get_tools(self) -> list[Tool]: + def get_tools(self) -> list[BuiltinTool]: """ returns a list of tools that the provider can provide @@ -91,24 +92,12 @@ def get_tools(self) -> list[Tool]: """ return self._get_builtin_tools() - def get_tool(self, tool_name: str) -> Tool: + def get_tool(self, tool_name: str) -> BuiltinTool | None: """ returns the tool that the provider can provide """ return next(filter(lambda x: x.identity.name == tool_name, self.get_tools()), None) - def get_parameters(self, tool_name: str) -> list[ToolParameter]: - """ - returns the parameters of the tool - - :param tool_name: the name of the tool, defined in `get_tools` - :return: list of parameters - """ - tool = next(filter(lambda x: x.identity.name == tool_name, self.get_tools()), None) - if tool is None: - raise ToolNotFoundError(f'tool {tool_name} not found') - return tool.parameters - @property def need_credentials(self) -> bool: """ @@ -143,67 +132,6 @@ def _get_tool_labels(self) -> list[ToolLabelEnum]: returns the labels of the provider """ return self.identity.tags or [] - - def validate_parameters(self, tool_id: int, tool_name: str, tool_parameters: dict[str, Any]) -> None: - """ - validate the parameters of the tool and set the default value if needed - - :param tool_name: the name of the tool, defined in `get_tools` - :param tool_parameters: the parameters of the tool - """ - tool_parameters_schema = self.get_parameters(tool_name) - - tool_parameters_need_to_validate: dict[str, ToolParameter] = {} - for parameter in tool_parameters_schema: - tool_parameters_need_to_validate[parameter.name] = parameter - - for parameter in tool_parameters: - if parameter not in tool_parameters_need_to_validate: - raise ToolParameterValidationError(f'parameter {parameter} not found in tool {tool_name}') - - # check type - parameter_schema = tool_parameters_need_to_validate[parameter] - if parameter_schema.type == ToolParameter.ToolParameterType.STRING: - if not isinstance(tool_parameters[parameter], str): - raise ToolParameterValidationError(f'parameter {parameter} should be string') - - elif parameter_schema.type == ToolParameter.ToolParameterType.NUMBER: - if not isinstance(tool_parameters[parameter], int | float): - raise ToolParameterValidationError(f'parameter {parameter} should be number') - - if parameter_schema.min is not None and tool_parameters[parameter] < parameter_schema.min: - raise ToolParameterValidationError(f'parameter {parameter} should be greater than {parameter_schema.min}') - - if parameter_schema.max is not None and tool_parameters[parameter] > parameter_schema.max: - raise ToolParameterValidationError(f'parameter {parameter} should be less than {parameter_schema.max}') - - elif parameter_schema.type == ToolParameter.ToolParameterType.BOOLEAN: - if not isinstance(tool_parameters[parameter], bool): - raise ToolParameterValidationError(f'parameter {parameter} should be boolean') - - elif parameter_schema.type == ToolParameter.ToolParameterType.SELECT: - if not isinstance(tool_parameters[parameter], str): - raise ToolParameterValidationError(f'parameter {parameter} should be string') - - options = parameter_schema.options - if not isinstance(options, list): - raise ToolParameterValidationError(f'parameter {parameter} options should be list') - - if tool_parameters[parameter] not in [x.value for x in options]: - raise ToolParameterValidationError(f'parameter {parameter} should be one of {options}') - - tool_parameters_need_to_validate.pop(parameter) - - for parameter in tool_parameters_need_to_validate: - parameter_schema = tool_parameters_need_to_validate[parameter] - if parameter_schema.required: - raise ToolParameterValidationError(f'parameter {parameter} is required') - - # the parameter is not set currently, set the default value if needed - if parameter_schema.default is not None: - default_value = ToolParameterConverter.cast_parameter_by_type(parameter_schema.default, - parameter_schema.type) - tool_parameters[parameter] = default_value def validate_credentials(self, credentials: dict[str, Any]) -> None: """ diff --git a/api/core/tools/provider/tool_provider.py b/api/core/tools/provider/tool_provider.py index ef1ace9c7c31e7..ac770a2a60125c 100644 --- a/api/core/tools/provider/tool_provider.py +++ b/api/core/tools/provider/tool_provider.py @@ -1,25 +1,23 @@ from abc import ABC, abstractmethod -from typing import Any, Optional +from typing import Any -from pydantic import BaseModel +from pydantic import BaseModel, Field +from core.entities.provider_entities import ProviderConfig from core.tools.entities.tool_entities import ( - ToolParameter, - ToolProviderCredentials, ToolProviderIdentity, ToolProviderType, ) -from core.tools.errors import ToolNotFoundError, ToolParameterValidationError, ToolProviderCredentialValidationError +from core.tools.errors import ToolProviderCredentialValidationError from core.tools.tool.tool import Tool -from core.tools.utils.tool_parameter_converter import ToolParameterConverter class ToolProviderController(BaseModel, ABC): - identity: Optional[ToolProviderIdentity] = None - tools: Optional[list[Tool]] = None - credentials_schema: Optional[dict[str, ToolProviderCredentials]] = None + identity: ToolProviderIdentity + tools: list[Tool] = Field(default_factory=list) + credentials_schema: dict[str, ProviderConfig] = Field(default_factory=dict) - def get_credentials_schema(self) -> dict[str, ToolProviderCredentials]: + def get_credentials_schema(self) -> dict[str, ProviderConfig]: """ returns the credentials schema of the provider @@ -27,15 +25,6 @@ def get_credentials_schema(self) -> dict[str, ToolProviderCredentials]: """ return self.credentials_schema.copy() - @abstractmethod - def get_tools(self) -> list[Tool]: - """ - returns a list of tools that the provider can provide - - :return: list of tools - """ - pass - @abstractmethod def get_tool(self, tool_name: str) -> Tool: """ @@ -45,18 +34,6 @@ def get_tool(self, tool_name: str) -> Tool: """ pass - def get_parameters(self, tool_name: str) -> list[ToolParameter]: - """ - returns the parameters of the tool - - :param tool_name: the name of the tool, defined in `get_tools` - :return: list of parameters - """ - tool = next(filter(lambda x: x.identity.name == tool_name, self.get_tools()), None) - if tool is None: - raise ToolNotFoundError(f'tool {tool_name} not found') - return tool.parameters - @property def provider_type(self) -> ToolProviderType: """ @@ -66,66 +43,6 @@ def provider_type(self) -> ToolProviderType: """ return ToolProviderType.BUILT_IN - def validate_parameters(self, tool_id: int, tool_name: str, tool_parameters: dict[str, Any]) -> None: - """ - validate the parameters of the tool and set the default value if needed - - :param tool_name: the name of the tool, defined in `get_tools` - :param tool_parameters: the parameters of the tool - """ - tool_parameters_schema = self.get_parameters(tool_name) - - tool_parameters_need_to_validate: dict[str, ToolParameter] = {} - for parameter in tool_parameters_schema: - tool_parameters_need_to_validate[parameter.name] = parameter - - for parameter in tool_parameters: - if parameter not in tool_parameters_need_to_validate: - raise ToolParameterValidationError(f'parameter {parameter} not found in tool {tool_name}') - - # check type - parameter_schema = tool_parameters_need_to_validate[parameter] - if parameter_schema.type == ToolParameter.ToolParameterType.STRING: - if not isinstance(tool_parameters[parameter], str): - raise ToolParameterValidationError(f'parameter {parameter} should be string') - - elif parameter_schema.type == ToolParameter.ToolParameterType.NUMBER: - if not isinstance(tool_parameters[parameter], int | float): - raise ToolParameterValidationError(f'parameter {parameter} should be number') - - if parameter_schema.min is not None and tool_parameters[parameter] < parameter_schema.min: - raise ToolParameterValidationError(f'parameter {parameter} should be greater than {parameter_schema.min}') - - if parameter_schema.max is not None and tool_parameters[parameter] > parameter_schema.max: - raise ToolParameterValidationError(f'parameter {parameter} should be less than {parameter_schema.max}') - - elif parameter_schema.type == ToolParameter.ToolParameterType.BOOLEAN: - if not isinstance(tool_parameters[parameter], bool): - raise ToolParameterValidationError(f'parameter {parameter} should be boolean') - - elif parameter_schema.type == ToolParameter.ToolParameterType.SELECT: - if not isinstance(tool_parameters[parameter], str): - raise ToolParameterValidationError(f'parameter {parameter} should be string') - - options = parameter_schema.options - if not isinstance(options, list): - raise ToolParameterValidationError(f'parameter {parameter} options should be list') - - if tool_parameters[parameter] not in [x.value for x in options]: - raise ToolParameterValidationError(f'parameter {parameter} should be one of {options}') - - tool_parameters_need_to_validate.pop(parameter) - - for parameter in tool_parameters_need_to_validate: - parameter_schema = tool_parameters_need_to_validate[parameter] - if parameter_schema.required: - raise ToolParameterValidationError(f'parameter {parameter} is required') - - # the parameter is not set currently, set the default value if needed - if parameter_schema.default is not None: - tool_parameters[parameter] = ToolParameterConverter.cast_parameter_by_type(parameter_schema.default, - parameter_schema.type) - def validate_credentials_format(self, credentials: dict[str, Any]) -> None: """ validate the format of the credentials of the provider and set the default value if needed @@ -136,7 +53,7 @@ def validate_credentials_format(self, credentials: dict[str, Any]) -> None: if credentials_schema is None: return - credentials_need_to_validate: dict[str, ToolProviderCredentials] = {} + credentials_need_to_validate: dict[str, ProviderConfig] = {} for credential_name in credentials_schema: credentials_need_to_validate[credential_name] = credentials_schema[credential_name] @@ -146,12 +63,12 @@ def validate_credentials_format(self, credentials: dict[str, Any]) -> None: # check type credential_schema = credentials_need_to_validate[credential_name] - if credential_schema == ToolProviderCredentials.CredentialsType.SECRET_INPUT or \ - credential_schema == ToolProviderCredentials.CredentialsType.TEXT_INPUT: + if credential_schema == ProviderConfig.Type.SECRET_INPUT or \ + credential_schema == ProviderConfig.Type.TEXT_INPUT: if not isinstance(credentials[credential_name], str): raise ToolProviderCredentialValidationError(f'credential {credential_name} should be string') - elif credential_schema.type == ToolProviderCredentials.CredentialsType.SELECT: + elif credential_schema.type == ProviderConfig.Type.SELECT: if not isinstance(credentials[credential_name], str): raise ToolProviderCredentialValidationError(f'credential {credential_name} should be string') @@ -173,9 +90,9 @@ def validate_credentials_format(self, credentials: dict[str, Any]) -> None: if credential_schema.default is not None: default_value = credential_schema.default # parse default value into the correct type - if credential_schema.type == ToolProviderCredentials.CredentialsType.SECRET_INPUT or \ - credential_schema.type == ToolProviderCredentials.CredentialsType.TEXT_INPUT or \ - credential_schema.type == ToolProviderCredentials.CredentialsType.SELECT: + if credential_schema.type == ProviderConfig.Type.SECRET_INPUT or \ + credential_schema.type == ProviderConfig.Type.TEXT_INPUT or \ + credential_schema.type == ProviderConfig.Type.SELECT: default_value = str(default_value) credentials[credential_name] = default_value diff --git a/api/core/tools/provider/workflow_tool_provider.py b/api/core/tools/provider/workflow_tool_provider.py index f14abac76777da..a84b7a36ed9e47 100644 --- a/api/core/tools/provider/workflow_tool_provider.py +++ b/api/core/tools/provider/workflow_tool_provider.py @@ -1,5 +1,8 @@ +from collections.abc import Mapping from typing import Optional +from pydantic import Field + from core.app.app_config.entities import VariableEntity, VariableEntityType from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager from core.tools.entities.common_entities import I18nObject @@ -28,6 +31,7 @@ class WorkflowToolProviderController(ToolProviderController): provider_id: str + tools: list[WorkflowTool] = Field(default_factory=list) @classmethod def from_db(cls, db_provider: WorkflowToolProvider) -> 'WorkflowToolProviderController': @@ -71,16 +75,17 @@ def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> :param app: the app :return: the tool """ - workflow: Workflow = db.session.query(Workflow).filter( + workflow: Workflow | None = db.session.query(Workflow).filter( Workflow.app_id == db_provider.app_id, Workflow.version == db_provider.version ).first() + if not workflow: raise ValueError('workflow not found') # fetch start node - graph: dict = workflow.graph_dict - features_dict: dict = workflow.features_dict + graph: Mapping = workflow.graph_dict + features_dict: Mapping = workflow.features_dict features = WorkflowAppConfigManager.convert_features( config_dict=features_dict, app_mode=AppMode.WORKFLOW @@ -89,7 +94,7 @@ def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> parameters = db_provider.parameter_configurations variables = WorkflowToolConfigurationUtils.get_workflow_graph_variables(graph) - def fetch_workflow_variable(variable_name: str) -> VariableEntity: + def fetch_workflow_variable(variable_name: str) -> VariableEntity | None: return next(filter(lambda x: x.variable == variable_name, variables), None) user = db_provider.user @@ -99,7 +104,7 @@ def fetch_workflow_variable(variable_name: str) -> VariableEntity: variable = fetch_workflow_variable(parameter.name) if variable: parameter_type = None - options = None + options = [] if variable.type not in VARIABLE_TO_PARAMETER_TYPE_MAPPING: raise ValueError(f'unsupported variable type {variable.type}') parameter_type = VARIABLE_TO_PARAMETER_TYPE_MAPPING[variable.type] @@ -185,7 +190,7 @@ def fetch_workflow_variable(variable_name: str) -> VariableEntity: label=db_provider.label ) - def get_tools(self, user_id: str, tenant_id: str) -> list[WorkflowTool]: + def get_tools(self, tenant_id: str) -> list[WorkflowTool]: """ fetch tools from database @@ -196,7 +201,7 @@ def get_tools(self, user_id: str, tenant_id: str) -> list[WorkflowTool]: if self.tools is not None: return self.tools - db_providers: WorkflowToolProvider = db.session.query(WorkflowToolProvider).filter( + db_providers: WorkflowToolProvider | None = db.session.query(WorkflowToolProvider).filter( WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.app_id == self.provider_id, ).first() diff --git a/api/core/tools/tool/tool.py b/api/core/tools/tool/tool.py index 68db0d5b2eaf4b..6005297118516a 100644 --- a/api/core/tools/tool/tool.py +++ b/api/core/tools/tool/tool.py @@ -55,7 +55,7 @@ def __init__(self, **data: Any): invoke_from: Optional[InvokeFrom] = None tool_invoke_from: Optional[ToolInvokeFrom] = None credentials: Optional[dict[str, Any]] = None - runtime_parameters: Optional[dict[str, Any]] = None + runtime_parameters: dict[str, Any] = Field(default_factory=dict) runtime: Optional[Runtime] = None variables: Optional[ToolRuntimeVariablePool] = None diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 06b6bb9f5285af..efc28020161603 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -4,7 +4,7 @@ from collections.abc import Generator from os import listdir, path from threading import Lock -from typing import Any, Union +from typing import Any, Union, cast from configs import dify_config from core.agent.entities import AgentToolEntity @@ -22,6 +22,7 @@ from core.tools.tool.api_tool import ApiTool from core.tools.tool.builtin_tool import BuiltinTool from core.tools.tool.tool import Tool +from core.tools.tool.workflow_tool import WorkflowTool from core.tools.tool_label_manager import ToolLabelManager from core.tools.utils.configuration import ToolConfigurationManager, ToolParameterConfigurationManager from core.tools.utils.tool_parameter_converter import ToolParameterConverter @@ -57,7 +58,7 @@ def get_builtin_provider(cls, provider: str) -> BuiltinToolProviderController: return cls._builtin_providers[provider] @classmethod - def get_builtin_tool(cls, provider: str, tool_name: str) -> BuiltinTool: + def get_builtin_tool(cls, provider: str, tool_name: str) -> BuiltinTool | None: """ get the builtin tool @@ -78,7 +79,7 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, tenant_id: str, invoke_from: InvokeFrom = InvokeFrom.DEBUGGER, tool_invoke_from: ToolInvokeFrom = ToolInvokeFrom.AGENT) \ - -> Union[BuiltinTool, ApiTool]: + -> Union[BuiltinTool, ApiTool, WorkflowTool]: """ get the tool runtime @@ -90,19 +91,21 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, """ if provider_type == ToolProviderType.BUILT_IN: builtin_tool = cls.get_builtin_tool(provider_id, tool_name) + if not builtin_tool: + raise ValueError(f"tool {tool_name} not found") # check if the builtin tool need credentials provider_controller = cls.get_builtin_provider(provider_id) if not provider_controller.need_credentials: - return builtin_tool.fork_tool_runtime(runtime={ + return cast(BuiltinTool, builtin_tool.fork_tool_runtime(runtime={ 'tenant_id': tenant_id, 'credentials': {}, 'invoke_from': invoke_from, 'tool_invoke_from': tool_invoke_from, - }) + })) # get credentials - builtin_provider: BuiltinToolProvider = db.session.query(BuiltinToolProvider).filter( + builtin_provider: BuiltinToolProvider | None = db.session.query(BuiltinToolProvider).filter( BuiltinToolProvider.tenant_id == tenant_id, BuiltinToolProvider.provider == provider_id, ).first() @@ -117,13 +120,13 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) - return builtin_tool.fork_tool_runtime(runtime={ + return cast(BuiltinTool, builtin_tool.fork_tool_runtime(runtime={ 'tenant_id': tenant_id, 'credentials': decrypted_credentials, 'runtime_parameters': {}, 'invoke_from': invoke_from, 'tool_invoke_from': tool_invoke_from, - }) + })) elif provider_type == ToolProviderType.API: if tenant_id is None: @@ -135,12 +138,12 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=api_provider) decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) - return api_provider.get_tool(tool_name).fork_tool_runtime(runtime={ + return cast(ApiTool, api_provider.get_tool(tool_name).fork_tool_runtime(runtime={ 'tenant_id': tenant_id, 'credentials': decrypted_credentials, 'invoke_from': invoke_from, 'tool_invoke_from': tool_invoke_from, - }) + })) elif provider_type == ToolProviderType.WORKFLOW: workflow_provider = db.session.query(WorkflowToolProvider).filter( WorkflowToolProvider.tenant_id == tenant_id, @@ -154,12 +157,12 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, db_provider=workflow_provider ) - return controller.get_tools(user_id=None, tenant_id=workflow_provider.tenant_id)[0].fork_tool_runtime(runtime={ + return cast(WorkflowTool, controller.get_tools(tenant_id=workflow_provider.tenant_id)[0].fork_tool_runtime(runtime={ 'tenant_id': tenant_id, 'credentials': {}, 'invoke_from': invoke_from, 'tool_invoke_from': tool_invoke_from, - }) + })) elif provider_type == ToolProviderType.APP: raise NotImplementedError('app provider not implemented') else: @@ -220,7 +223,10 @@ def get_agent_tool_runtime(cls, tenant_id: str, app_id: str, agent_tool: AgentTo identity_id=f'AGENT.{app_id}' ) runtime_parameters = encryption_manager.decrypt_tool_parameters(runtime_parameters) - + + if not tool_entity.runtime: + raise Exception("tool missing runtime") + tool_entity.runtime.runtime_parameters.update(runtime_parameters) return tool_entity @@ -258,6 +264,9 @@ def get_workflow_tool_runtime(cls, tenant_id: str, app_id: str, node_id: str, wo if runtime_parameters: runtime_parameters = encryption_manager.decrypt_tool_parameters(runtime_parameters) + if not tool_entity.runtime: + raise Exception("tool missing runtime") + tool_entity.runtime.runtime_parameters.update(runtime_parameters) return tool_entity @@ -304,20 +313,20 @@ def _list_builtin_providers(cls) -> Generator[BuiltinToolProviderController, Non """ list all the builtin providers """ - for provider in listdir(path.join(path.dirname(path.realpath(__file__)), 'provider', 'builtin')): - if provider.startswith('__'): + for provider_path in listdir(path.join(path.dirname(path.realpath(__file__)), 'provider', 'builtin')): + if provider_path.startswith('__'): continue - if path.isdir(path.join(path.dirname(path.realpath(__file__)), 'provider', 'builtin', provider)): - if provider.startswith('__'): + if path.isdir(path.join(path.dirname(path.realpath(__file__)), 'provider', 'builtin', provider_path)): + if provider_path.startswith('__'): continue # init provider try: provider_class = load_single_subclass_from_source( - module_name=f'core.tools.provider.builtin.{provider}.{provider}', + module_name=f'core.tools.provider.builtin.{provider_path}.{provider_path}', script_path=path.join(path.dirname(path.realpath(__file__)), - 'provider', 'builtin', provider, f'{provider}.py'), + 'provider', 'builtin', provider_path, f'{provider_path}.py'), parent_type=BuiltinToolProviderController) provider: BuiltinToolProviderController = provider_class() cls._builtin_providers[provider.identity.name] = provider @@ -387,8 +396,8 @@ def user_list_providers(cls, user_id: str, tenant_id: str, typ: UserToolProvider for provider in builtin_providers: # handle include, exclude if is_filtered( - include_set=dify_config.POSITION_TOOL_INCLUDES_SET, - exclude_set=dify_config.POSITION_TOOL_EXCLUDES_SET, + include_set=dify_config.POSITION_TOOL_INCLUDES_SET, # type: ignore + exclude_set=dify_config.POSITION_TOOL_EXCLUDES_SET, # type: ignore data=provider, name_func=lambda x: x.identity.name ): @@ -461,7 +470,7 @@ def get_api_provider_controller(cls, tenant_id: str, provider_id: str) -> tuple[ :return: the provider controller, the credentials """ - provider: ApiToolProvider = db.session.query(ApiToolProvider).filter( + provider: ApiToolProvider | None = db.session.query(ApiToolProvider).filter( ApiToolProvider.id == provider_id, ApiToolProvider.tenant_id == tenant_id, ).first() @@ -486,22 +495,22 @@ def user_get_api_provider(cls, provider: str, tenant_id: str) -> dict: """ get tool provider """ - provider: ApiToolProvider = db.session.query(ApiToolProvider).filter( + provider_obj: ApiToolProvider| None = db.session.query(ApiToolProvider).filter( ApiToolProvider.tenant_id == tenant_id, ApiToolProvider.name == provider, ).first() - if provider is None: + if provider_obj is None: raise ValueError(f'you have not added provider {provider}') try: - credentials = json.loads(provider.credentials_str) or {} + credentials = json.loads(provider_obj.credentials_str) or {} except: credentials = {} # package tool provider controller controller = ApiToolProviderController.from_db( - provider, ApiProviderAuthType.API_KEY if credentials['auth_type'] == 'api_key' else ApiProviderAuthType.NONE + provider_obj, ApiProviderAuthType.API_KEY if credentials['auth_type'] == 'api_key' else ApiProviderAuthType.NONE ) # init tool configuration tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=controller) @@ -510,7 +519,7 @@ def user_get_api_provider(cls, provider: str, tenant_id: str) -> dict: masked_credentials = tool_configuration.mask_tool_credentials(decrypted_credentials) try: - icon = json.loads(provider.icon) + icon = json.loads(provider_obj.icon) except: icon = { "background": "#252525", @@ -521,14 +530,14 @@ def user_get_api_provider(cls, provider: str, tenant_id: str) -> dict: labels = ToolLabelManager.get_tool_labels(controller) return jsonable_encoder({ - 'schema_type': provider.schema_type, - 'schema': provider.schema, - 'tools': provider.tools, + 'schema_type': provider_obj.schema_type, + 'schema': provider_obj.schema, + 'tools': provider_obj.tools, 'icon': icon, - 'description': provider.description, + 'description': provider_obj.description, 'credentials': masked_credentials, - 'privacy_policy': provider.privacy_policy, - 'custom_disclaimer': provider.custom_disclaimer, + 'privacy_policy': provider_obj.privacy_policy, + 'custom_disclaimer': provider_obj.custom_disclaimer, 'labels': labels, }) @@ -551,25 +560,29 @@ def get_tool_icon(cls, tenant_id: str, provider_type: ToolProviderType, provider + "/icon") elif provider_type == ToolProviderType.API: try: - provider: ApiToolProvider = db.session.query(ApiToolProvider).filter( + api_provider: ApiToolProvider | None = db.session.query(ApiToolProvider).filter( ApiToolProvider.tenant_id == tenant_id, ApiToolProvider.id == provider_id ).first() - return json.loads(provider.icon) + if not api_provider: + raise ValueError("api tool not found") + + return json.loads(api_provider.icon) except: return { "background": "#252525", "content": "\ud83d\ude01" } elif provider_type == ToolProviderType.WORKFLOW: - provider: WorkflowToolProvider = db.session.query(WorkflowToolProvider).filter( + workflow_provider: WorkflowToolProvider | None = db.session.query(WorkflowToolProvider).filter( WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.id == provider_id ).first() - if provider is None: + + if workflow_provider is None: raise ToolProviderNotFoundError(f'workflow provider {provider_id} not found') - return json.loads(provider.icon) + return json.loads(workflow_provider.icon) else: raise ValueError(f"provider type {provider_type} not found") diff --git a/api/core/tools/utils/configuration.py b/api/core/tools/utils/configuration.py index 68b0cea24f97eb..2fc0ba3bcd3192 100644 --- a/api/core/tools/utils/configuration.py +++ b/api/core/tools/utils/configuration.py @@ -7,8 +7,8 @@ from core.helper.tool_parameter_cache import ToolParameterCache, ToolParameterCacheType from core.helper.tool_provider_cache import ToolProviderCredentialsCache, ToolProviderCredentialsCacheType from core.tools.entities.tool_entities import ( + ProviderConfig, ToolParameter, - ToolProviderCredentials, ToolProviderType, ) from core.tools.provider.tool_provider import ToolProviderController @@ -36,7 +36,7 @@ def encrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str # get fields need to be decrypted fields = self.provider_controller.get_credentials_schema() for field_name, field in fields.items(): - if field.type == ToolProviderCredentials.CredentialsType.SECRET_INPUT: + if field.type == ProviderConfig.Type.SECRET_INPUT: if field_name in credentials: encrypted = encrypter.encrypt_token(self.tenant_id, credentials[field_name]) credentials[field_name] = encrypted @@ -54,7 +54,7 @@ def mask_tool_credentials(self, credentials: dict[str, Any]) -> dict[str, Any]: # get fields need to be decrypted fields = self.provider_controller.get_credentials_schema() for field_name, field in fields.items(): - if field.type == ToolProviderCredentials.CredentialsType.SECRET_INPUT: + if field.type == ProviderConfig.Type.SECRET_INPUT: if field_name in credentials: if len(credentials[field_name]) > 6: credentials[field_name] = \ @@ -84,7 +84,7 @@ def decrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str # get fields need to be decrypted fields = self.provider_controller.get_credentials_schema() for field_name, field in fields.items(): - if field.type == ToolProviderCredentials.CredentialsType.SECRET_INPUT: + if field.type == ProviderConfig.Type.SECRET_INPUT: if field_name in credentials: try: credentials[field_name] = encrypter.decrypt_token(self.tenant_id, credentials[field_name]) diff --git a/api/core/tools/utils/workflow_configuration_sync.py b/api/core/tools/utils/workflow_configuration_sync.py index ff5505bbbfb9f5..b8237fd043e277 100644 --- a/api/core/tools/utils/workflow_configuration_sync.py +++ b/api/core/tools/utils/workflow_configuration_sync.py @@ -1,3 +1,5 @@ +from collections.abc import Mapping + from core.app.app_config.entities import VariableEntity from core.tools.entities.tool_entities import WorkflowToolParameterConfiguration @@ -13,7 +15,7 @@ def check_parameter_configurations(cls, configurations: list[dict]): raise ValueError('invalid parameter configuration') @classmethod - def get_workflow_graph_variables(cls, graph: dict) -> list[VariableEntity]: + def get_workflow_graph_variables(cls, graph: Mapping) -> list[VariableEntity]: """ get workflow graph variables """ @@ -44,5 +46,3 @@ def check_is_synced(cls, for parameter in tool_configurations: if parameter.name not in variable_names: raise ValueError('parameter configuration mismatch, please republish the tool to update') - - return True \ No newline at end of file diff --git a/api/services/tools/api_tools_manage_service.py b/api/services/tools/api_tools_manage_service.py index 3ded9c0989b53c..d7538bd812878b 100644 --- a/api/services/tools/api_tools_manage_service.py +++ b/api/services/tools/api_tools_manage_service.py @@ -10,8 +10,8 @@ from core.tools.entities.tool_entities import ( ApiProviderAuthType, ApiProviderSchemaType, + ProviderConfig, ToolCredentialsOption, - ToolProviderCredentials, ) from core.tools.provider.api_tool_provider import ApiToolProviderController from core.tools.tool_label_manager import ToolLabelManager @@ -39,9 +39,9 @@ def parser_api_schema(schema: str) -> list[ApiToolBundle]: raise ValueError(f"invalid schema: {str(e)}") credentials_schema = [ - ToolProviderCredentials( + ProviderConfig( name="auth_type", - type=ToolProviderCredentials.CredentialsType.SELECT, + type=ProviderConfig.Type.SELECT, required=True, default="none", options=[ @@ -50,17 +50,17 @@ def parser_api_schema(schema: str) -> list[ApiToolBundle]: ], placeholder=I18nObject(en_US="Select auth type", zh_Hans="选择认证方式"), ), - ToolProviderCredentials( + ProviderConfig( name="api_key_header", - type=ToolProviderCredentials.CredentialsType.TEXT_INPUT, + type=ProviderConfig.Type.TEXT_INPUT, required=False, placeholder=I18nObject(en_US="Enter api key header", zh_Hans="输入 api key header，如：X-API-KEY"), default="api_key", help=I18nObject(en_US="HTTP header name for api key", zh_Hans="HTTP 头部字段名，用于传递 api key"), ), - ToolProviderCredentials( + ProviderConfig( name="api_key_value", - type=ToolProviderCredentials.CredentialsType.TEXT_INPUT, + type=ProviderConfig.Type.TEXT_INPUT, required=False, placeholder=I18nObject(en_US="Enter api key", zh_Hans="输入 api key"), default="", diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index d072203fbaf387..1848fb2a1343ce 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -8,8 +8,8 @@ from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( ApiProviderAuthType, + ProviderConfig, ToolParameter, - ToolProviderCredentials, ToolProviderType, ) from core.tools.provider.api_tool_provider import ApiToolProviderController @@ -92,7 +92,7 @@ def builtin_provider_to_user_provider( # get credentials schema schema = provider_controller.get_credentials_schema() for name, value in schema.items(): - result.masked_credentials[name] = ToolProviderCredentials.CredentialsType.default(value.type) + result.masked_credentials[name] = ProviderConfig.Type.default(value.type) # check if the provider need credentials if not provider_controller.need_credentials: From cf4e9f317e207a4f1d6fef71e4329d6c74134054 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 30 Aug 2024 15:55:10 +0800 Subject: [PATCH 021/325] refactor: tool models --- .../agent_tool_callback_handler.py | 4 +- api/core/tools/tool_engine.py | 59 ++++++++++--------- api/core/workflow/nodes/tool/tool_node.py | 6 +- api/models/base.py | 5 ++ api/models/model.py | 28 +++++---- api/models/tools.py | 6 +- 6 files changed, 60 insertions(+), 48 deletions(-) create mode 100644 api/models/base.py diff --git a/api/core/callback_handler/agent_tool_callback_handler.py b/api/core/callback_handler/agent_tool_callback_handler.py index 578996574739a8..4c246b230de5a1 100644 --- a/api/core/callback_handler/agent_tool_callback_handler.py +++ b/api/core/callback_handler/agent_tool_callback_handler.py @@ -1,5 +1,5 @@ import os -from collections.abc import Mapping, Sequence +from collections.abc import Iterable, Mapping from typing import Any, Optional, TextIO, Union from pydantic import BaseModel @@ -55,7 +55,7 @@ def on_tool_end( self, tool_name: str, tool_inputs: Mapping[str, Any], - tool_outputs: Sequence[ToolInvokeMessage], + tool_outputs: Iterable[ToolInvokeMessage] | str, message_id: Optional[str] = None, timer: Optional[Any] = None, trace_manager: Optional[TraceQueueManager] = None diff --git a/api/core/tools/tool_engine.py b/api/core/tools/tool_engine.py index 9397f22494880d..0fb44704983b72 100644 --- a/api/core/tools/tool_engine.py +++ b/api/core/tools/tool_engine.py @@ -1,9 +1,9 @@ import json -from collections.abc import Generator, Mapping +from collections.abc import Generator, Iterable from copy import deepcopy from datetime import datetime, timezone from mimetypes import guess_type -from typing import Any, Optional, Union +from typing import Any, Optional, Union, cast from yarl import URL @@ -40,7 +40,7 @@ def agent_invoke( user_id: str, tenant_id: str, message: Message, invoke_from: InvokeFrom, agent_tool_callback: DifyAgentCallbackHandler, trace_manager: Optional[TraceQueueManager] = None - ) -> tuple[str, list[tuple[MessageFile, bool]], ToolInvokeMeta]: + ) -> tuple[str, list[tuple[MessageFile, str]], ToolInvokeMeta]: """ Agent invokes the tool with the given arguments. """ @@ -67,9 +67,9 @@ def agent_invoke( ) messages = ToolEngine._invoke(tool, tool_parameters, user_id) - invocation_meta_dict = {'meta': None} + invocation_meta_dict: dict[str, ToolInvokeMeta] = {} - def message_callback(invocation_meta_dict: dict, messages: Generator[ToolInvokeMessage, None, None]): + def message_callback(invocation_meta_dict: dict, messages: Generator[ToolInvokeMessage | ToolInvokeMeta, None, None]): for message in messages: if isinstance(message, ToolInvokeMeta): invocation_meta_dict['meta'] = message @@ -136,7 +136,7 @@ def message_callback(invocation_meta_dict: dict, messages: Generator[ToolInvokeM return error_response, [], ToolInvokeMeta.error_instance(error_response) @staticmethod - def workflow_invoke(tool: Tool, tool_parameters: Mapping[str, Any], + def workflow_invoke(tool: Tool, tool_parameters: dict[str, Any], user_id: str, workflow_tool_callback: DifyWorkflowCallbackHandler, workflow_call_depth: int, @@ -156,6 +156,7 @@ def workflow_invoke(tool: Tool, tool_parameters: Mapping[str, Any], if tool.runtime and tool.runtime.runtime_parameters: tool_parameters = {**tool.runtime.runtime_parameters, **tool_parameters} + response = tool.invoke(user_id=user_id, tool_parameters=tool_parameters) # hit the callback handler @@ -204,6 +205,9 @@ def _invoke(tool: Tool, tool_parameters: dict, user_id: str) \ """ Invoke the tool with the given arguments. """ + if not tool.runtime: + raise ValueError("missing runtime in tool") + started_at = datetime.now(timezone.utc) meta = ToolInvokeMeta(time_cost=0.0, error=None, tool_config={ 'tool_name': tool.identity.name, @@ -223,42 +227,42 @@ def _invoke(tool: Tool, tool_parameters: dict, user_id: str) \ yield meta @staticmethod - def _convert_tool_response_to_str(tool_response: list[ToolInvokeMessage]) -> str: + def _convert_tool_response_to_str(tool_response: Generator[ToolInvokeMessage, None, None]) -> str: """ Handle tool response """ result = '' for response in tool_response: if response.type == ToolInvokeMessage.MessageType.TEXT: - result += response.message + result += cast(ToolInvokeMessage.TextMessage, response.message).text elif response.type == ToolInvokeMessage.MessageType.LINK: - result += f"result link: {response.message}. please tell user to check it." + result += f"result link: {cast(ToolInvokeMessage.TextMessage, response.message).text}. please tell user to check it." elif response.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \ response.type == ToolInvokeMessage.MessageType.IMAGE: result += "image has been created and sent to user already, you do not need to create it, just tell the user to check it now." elif response.type == ToolInvokeMessage.MessageType.JSON: - result += f"tool response: {json.dumps(response.message, ensure_ascii=False)}." + result += f"tool response: {json.dumps(cast(ToolInvokeMessage.JsonMessage, response.message).json_object, ensure_ascii=False)}." else: result += f"tool response: {response.message}." return result @staticmethod - def _extract_tool_response_binary(tool_response: list[ToolInvokeMessage]) -> list[ToolInvokeMessageBinary]: + def _extract_tool_response_binary(tool_response: Generator[ToolInvokeMessage, None, None]) -> Generator[ToolInvokeMessageBinary, None, None]: """ Extract tool response binary """ - result = [] - for response in tool_response: if response.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \ response.type == ToolInvokeMessage.MessageType.IMAGE: mimetype = None + if not response.meta: + raise ValueError("missing meta data") if response.meta.get('mime_type'): mimetype = response.meta.get('mime_type') else: try: - url = URL(response.message) + url = URL(cast(ToolInvokeMessage.TextMessage, response.message).text) extension = url.suffix guess_type_result, _ = guess_type(f'a{extension}') if guess_type_result: @@ -269,35 +273,36 @@ def _extract_tool_response_binary(tool_response: list[ToolInvokeMessage]) -> lis if not mimetype: mimetype = 'image/jpeg' - result.append(ToolInvokeMessageBinary( + yield ToolInvokeMessageBinary( mimetype=response.meta.get('mime_type', 'image/jpeg'), - url=response.message, + url=cast(ToolInvokeMessage.TextMessage, response.message).text, save_as=response.save_as, - )) + ) elif response.type == ToolInvokeMessage.MessageType.BLOB: - result.append(ToolInvokeMessageBinary( + if not response.meta: + raise ValueError("missing meta data") + + yield ToolInvokeMessageBinary( mimetype=response.meta.get('mime_type', 'octet/stream'), - url=response.message, + url=cast(ToolInvokeMessage.TextMessage, response.message).text, save_as=response.save_as, - )) + ) elif response.type == ToolInvokeMessage.MessageType.LINK: # check if there is a mime type in meta if response.meta and 'mime_type' in response.meta: - result.append(ToolInvokeMessageBinary( + yield ToolInvokeMessageBinary( mimetype=response.meta.get('mime_type', 'octet/stream') if response.meta else 'octet/stream', - url=response.message, + url=cast(ToolInvokeMessage.TextMessage, response.message).text, save_as=response.save_as, - )) - - return result + ) @staticmethod def _create_message_files( - tool_messages: list[ToolInvokeMessageBinary], + tool_messages: Iterable[ToolInvokeMessageBinary], agent_message: Message, invoke_from: InvokeFrom, user_id: str - ) -> list[tuple[Any, str]]: + ) -> list[tuple[MessageFile, str]]: """ Create message file diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index 47498f4f5fde1f..6ba7e7e09b01c4 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -1,4 +1,4 @@ -from collections.abc import Generator, Mapping, Sequence +from collections.abc import Generator, Sequence from os import path from typing import Any, cast @@ -100,7 +100,7 @@ def _generate_parameters( variable_pool: VariablePool, node_data: ToolNodeData, for_log: bool = False, - ) -> Mapping[str, Any]: + ) -> dict[str, Any]: """ Generate parameters based on the given tool parameters, variable pool, and node data. @@ -110,7 +110,7 @@ def _generate_parameters( node_data (ToolNodeData): The data associated with the tool node. Returns: - Mapping[str, Any]: A dictionary containing the generated parameters. + dict[str, Any]: A dictionary containing the generated parameters. """ tool_parameters_dictionary = {parameter.name: parameter for parameter in tool_parameters} diff --git a/api/models/base.py b/api/models/base.py new file mode 100644 index 00000000000000..1c2dcc40b94f8a --- /dev/null +++ b/api/models/base.py @@ -0,0 +1,5 @@ +from sqlalchemy.orm import DeclarativeBase + + +class Base(DeclarativeBase): + pass \ No newline at end of file diff --git a/api/models/model.py b/api/models/model.py index e2d1fcfc237a4d..298bfbda120e90 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -14,6 +14,7 @@ from core.file.upload_file_parser import UploadFileParser from extensions.ext_database import db from libs.helper import generate_string +from models.base import Base from .account import Account, Tenant from .types import StringUUID @@ -211,7 +212,7 @@ def tags(self): return tags if tags else [] -class AppModelConfig(db.Model): +class AppModelConfig(Base): __tablename__ = 'app_model_configs' __table_args__ = ( db.PrimaryKeyConstraint('id', name='app_model_config_pkey'), @@ -550,6 +551,9 @@ def model_config(self): else: app_model_config = db.session.query(AppModelConfig).filter( AppModelConfig.id == self.app_model_config_id).first() + + if not app_model_config: + raise ValueError("app config not found") model_config = app_model_config.to_dict() @@ -640,7 +644,7 @@ def in_debug_mode(self): return self.override_model_configs is not None -class Message(db.Model): +class Message(Base): __tablename__ = 'messages' __table_args__ = ( db.PrimaryKeyConstraint('id', name='message_pkey'), @@ -932,7 +936,7 @@ def from_account(self): return account -class MessageFile(db.Model): +class MessageFile(Base): __tablename__ = 'message_files' __table_args__ = ( db.PrimaryKeyConstraint('id', name='message_file_pkey'), @@ -940,15 +944,15 @@ class MessageFile(db.Model): db.Index('message_file_created_by_idx', 'created_by') ) - id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) - message_id = db.Column(StringUUID, nullable=False) - type = db.Column(db.String(255), nullable=False) - transfer_method = db.Column(db.String(255), nullable=False) - url = db.Column(db.Text, nullable=True) - belongs_to = db.Column(db.String(255), nullable=True) - upload_file_id = db.Column(StringUUID, nullable=True) - created_by_role = db.Column(db.String(255), nullable=False) - created_by = db.Column(StringUUID, nullable=False) + id: Mapped[str] = mapped_column(StringUUID, default=db.text('uuid_generate_v4()')) + message_id: Mapped[str] = mapped_column(StringUUID, nullable=False) + type: Mapped[str] = mapped_column(db.String(255), nullable=False) + transfer_method: Mapped[str] = mapped_column(db.String(255), nullable=False) + url: Mapped[str] = mapped_column(db.Text, nullable=True) + belongs_to: Mapped[str] = mapped_column(db.String(255), nullable=True) + upload_file_id: Mapped[str] = mapped_column(StringUUID, nullable=True) + created_by_role: Mapped[str] = mapped_column(db.String(255), nullable=False) + created_by: Mapped[str] = mapped_column(StringUUID, nullable=False) created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) diff --git a/api/models/tools.py b/api/models/tools.py index 937481583ab799..1e7421622aae08 100644 --- a/api/models/tools.py +++ b/api/models/tools.py @@ -1,12 +1,13 @@ import json from sqlalchemy import ForeignKey -from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column +from sqlalchemy.orm import Mapped, mapped_column from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ApiProviderSchemaType, WorkflowToolParameterConfiguration from extensions.ext_database import db +from models.base import Base from .model import Account, App, Tenant from .types import StringUUID @@ -277,9 +278,6 @@ class ToolConversationVariables(db.Model): @property def variables(self) -> dict: return json.loads(self.variables_str) - -class Base(DeclarativeBase): - pass class ToolFile(Base): """ From 886a1601152b5fd887f6e5777efd0bd37b88f84c Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 30 Aug 2024 18:11:38 +0800 Subject: [PATCH 022/325] fix: invoke tool streamingly --- api/core/entities/provider_entities.py | 4 +- api/core/helper/tool_provider_cache.py | 1 + api/core/tools/entities/api_entities.py | 11 ++-- api/core/tools/entities/tool_entities.py | 4 +- api/core/tools/provider/api_tool_provider.py | 25 +++++---- .../tools/provider/builtin_tool_provider.py | 2 +- api/core/tools/provider/tool_provider.py | 4 +- api/core/tools/tool/tool.py | 13 ++++- api/core/tools/tool_manager.py | 21 ++++++-- api/core/tools/utils/configuration.py | 24 +++++---- api/core/tools/utils/parser.py | 11 ++-- api/core/workflow/nodes/tool/tool_node.py | 17 +++--- api/models/model.py | 24 ++++----- api/models/tools.py | 6 +-- .../tools/api_tools_manage_service.py | 52 ++++++++++++------- api/services/tools/tools_transform_service.py | 22 +++++--- 16 files changed, 149 insertions(+), 92 deletions(-) diff --git a/api/core/entities/provider_entities.py b/api/core/entities/provider_entities.py index ae78d9ecf93b27..e0d1de151f143d 100644 --- a/api/core/entities/provider_entities.py +++ b/api/core/entities/provider_entities.py @@ -4,8 +4,8 @@ from pydantic import BaseModel, ConfigDict, Field from core.entities.parameter_entities import AppSelectorScope, CommonParameterType, ModelConfigScope -from core.model_runtime.entities.common_entities import I18nObject from core.model_runtime.entities.model_entities import ModelType +from core.tools.entities.common_entities import I18nObject from models.provider import ProviderQuotaType @@ -143,7 +143,7 @@ class Option(BaseModel): value: str = Field(..., description="The value of the option") label: I18nObject = Field(..., description="The label of the option") - scope: AppSelectorScope | ModelConfigScope | None + scope: AppSelectorScope | ModelConfigScope | None = None required: bool = False default: Optional[Union[int, str]] = None options: Optional[list[Option]] = None diff --git a/api/core/helper/tool_provider_cache.py b/api/core/helper/tool_provider_cache.py index 6c5d3b8fb6880c..2777367963bdae 100644 --- a/api/core/helper/tool_provider_cache.py +++ b/api/core/helper/tool_provider_cache.py @@ -8,6 +8,7 @@ class ToolProviderCredentialsCacheType(Enum): PROVIDER = "tool_provider" + ENDPOINT = "endpoint" class ToolProviderCredentialsCache: def __init__(self, tenant_id: str, identity_id: str, cache_type: ToolProviderCredentialsCacheType): diff --git a/api/core/tools/entities/api_entities.py b/api/core/tools/entities/api_entities.py index 71db8d8b2dfc77..2aaca3506009b2 100644 --- a/api/core/tools/entities/api_entities.py +++ b/api/core/tools/entities/api_entities.py @@ -1,10 +1,11 @@ from typing import Literal, Optional -from pydantic import BaseModel +from pydantic import BaseModel, Field +from core.entities.provider_entities import ProviderConfig from core.model_runtime.utils.encoders import jsonable_encoder from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ProviderConfig, ToolProviderType +from core.tools.entities.tool_entities import ToolProviderType from core.tools.tool.tool import ToolParameter @@ -14,7 +15,7 @@ class UserTool(BaseModel): label: I18nObject # label description: I18nObject parameters: Optional[list[ToolParameter]] = None - labels: list[str] = None + labels: list[str] = Field(default_factory=list) UserToolProviderTypeLiteral = Optional[Literal[ 'builtin', 'api', 'workflow' @@ -32,8 +33,8 @@ class UserToolProvider(BaseModel): original_credentials: Optional[dict] = None is_team_authorization: bool = False allow_delete: bool = True - tools: list[UserTool] = None - labels: list[str] = None + tools: list[UserTool] = Field(default_factory=list) + labels: list[str] = Field(default_factory=list) def to_dict(self) -> dict: # ------------- diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 98efb92a0d9d73..4b0961fb0999c9 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -25,7 +25,7 @@ class ToolLabelEnum(Enum): UTILITIES = 'utilities' OTHER = 'other' -class ToolProviderType(Enum): +class ToolProviderType(str, Enum): """ Enum class for tool provider """ @@ -181,7 +181,7 @@ def get_simple_instance(cls, if options: option_objs = [ToolParameterOption(value=option, label=I18nObject(en_US=option, zh_Hans=option)) for option in options] else: - option_objs = None + option_objs = [] return cls( name=name, label=I18nObject(en_US='', zh_Hans=''), diff --git a/api/core/tools/provider/api_tool_provider.py b/api/core/tools/provider/api_tool_provider.py index fc7fcb675a7ad8..880ddc4955b917 100644 --- a/api/core/tools/provider/api_tool_provider.py +++ b/api/core/tools/provider/api_tool_provider.py @@ -1,21 +1,23 @@ +from pydantic import Field + +from core.entities.provider_entities import ProviderConfig from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( ApiProviderAuthType, - ProviderConfig, - ToolCredentialsOption, ToolProviderType, ) from core.tools.provider.tool_provider import ToolProviderController from core.tools.tool.api_tool import ApiTool -from core.tools.tool.tool import Tool from extensions.ext_database import db from models.tools import ApiToolProvider class ApiToolProviderController(ToolProviderController): provider_id: str + tenant_id: str + tools: list[ApiTool] = Field(default_factory=list) @staticmethod def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> 'ApiToolProviderController': @@ -25,8 +27,8 @@ def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> 'Ap required=True, type=ProviderConfig.Type.SELECT, options=[ - ToolCredentialsOption(value='none', label=I18nObject(en_US='None', zh_Hans='无')), - ToolCredentialsOption(value='api_key', label=I18nObject(en_US='api_key', zh_Hans='api_key')) + ProviderConfig.Option(value='none', label=I18nObject(en_US='None', zh_Hans='无')), + ProviderConfig.Option(value='api_key', label=I18nObject(en_US='api_key', zh_Hans='api_key')) ], default='none', help=I18nObject( @@ -67,9 +69,9 @@ def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> 'Ap zh_Hans='api key header 的前缀' ), options=[ - ToolCredentialsOption(value='basic', label=I18nObject(en_US='Basic', zh_Hans='Basic')), - ToolCredentialsOption(value='bearer', label=I18nObject(en_US='Bearer', zh_Hans='Bearer')), - ToolCredentialsOption(value='custom', label=I18nObject(en_US='Custom', zh_Hans='Custom')) + ProviderConfig.Option(value='basic', label=I18nObject(en_US='Basic', zh_Hans='Basic')), + ProviderConfig.Option(value='bearer', label=I18nObject(en_US='Bearer', zh_Hans='Bearer')), + ProviderConfig.Option(value='custom', label=I18nObject(en_US='Custom', zh_Hans='Custom')) ] ) } @@ -96,6 +98,7 @@ def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> 'Ap }, 'credentials_schema': credentials_schema, 'provider_id': db_provider.id or '', + 'tenant_id': db_provider.tenant_id or '', }) @property @@ -142,7 +145,7 @@ def load_bundled_tools(self, tools: list[ApiToolBundle]) -> list[ApiTool]: return self.tools - def get_tools(self, user_id: str, tenant_id: str) -> list[ApiTool]: + def get_tools(self, tenant_id: str) -> list[ApiTool]: """ fetch tools from database @@ -153,7 +156,7 @@ def get_tools(self, user_id: str, tenant_id: str) -> list[ApiTool]: if self.tools is not None: return self.tools - tools: list[Tool] = [] + tools: list[ApiTool] = [] # get tenant api providers db_providers: list[ApiToolProvider] = db.session.query(ApiToolProvider).filter( @@ -179,7 +182,7 @@ def get_tool(self, tool_name: str) -> ApiTool: :return: the tool """ if self.tools is None: - self.get_tools() + self.get_tools(self.tenant_id) for tool in self.tools: if tool.identity.name == tool_name: diff --git a/api/core/tools/provider/builtin_tool_provider.py b/api/core/tools/provider/builtin_tool_provider.py index 7ad8a5468b131d..8dd543b00a539e 100644 --- a/api/core/tools/provider/builtin_tool_provider.py +++ b/api/core/tools/provider/builtin_tool_provider.py @@ -39,7 +39,7 @@ def __init__(self, **data: Any) -> None: super().__init__(**{ 'identity': provider_yaml['identity'], - 'credentials_schema': provider_yaml.get('credentials_for_provider', None), + 'credentials_schema': provider_yaml.get('credentials_for_provider', {}) or {}, }) def _get_builtin_tools(self) -> list[BuiltinTool]: diff --git a/api/core/tools/provider/tool_provider.py b/api/core/tools/provider/tool_provider.py index ac770a2a60125c..057f3060ed0f34 100644 --- a/api/core/tools/provider/tool_provider.py +++ b/api/core/tools/provider/tool_provider.py @@ -1,7 +1,7 @@ from abc import ABC, abstractmethod from typing import Any -from pydantic import BaseModel, Field +from pydantic import BaseModel, ConfigDict, Field from core.entities.provider_entities import ProviderConfig from core.tools.entities.tool_entities import ( @@ -17,6 +17,8 @@ class ToolProviderController(BaseModel, ABC): tools: list[Tool] = Field(default_factory=list) credentials_schema: dict[str, ProviderConfig] = Field(default_factory=dict) + model_config = ConfigDict(validate_assignment=True) + def get_credentials_schema(self) -> dict[str, ProviderConfig]: """ returns the credentials schema of the provider diff --git a/api/core/tools/tool/tool.py b/api/core/tools/tool/tool.py index 6005297118516a..6f21afdb357fd5 100644 --- a/api/core/tools/tool/tool.py +++ b/api/core/tools/tool/tool.py @@ -206,7 +206,16 @@ def invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[Too tool_parameters=tool_parameters, ) - return result + if isinstance(result, ToolInvokeMessage): + def single_generator(): + yield result + return single_generator() + elif isinstance(result, list): + def generator(): + yield from result + return generator() + else: + return result def _transform_tool_parameters_type(self, tool_parameters: dict[str, Any]) -> dict[str, Any]: """ @@ -223,7 +232,7 @@ def _transform_tool_parameters_type(self, tool_parameters: dict[str, Any]) -> di return result @abstractmethod - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage, None, None]: + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage] | Generator[ToolInvokeMessage, None, None]: pass def validate_credentials(self, credentials: dict[str, Any], parameters: dict[str, Any]) -> None: diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index efc28020161603..56e97252f9478a 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -116,7 +116,12 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, # decrypt the credentials credentials = builtin_provider.credentials controller = cls.get_builtin_provider(provider_id) - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=controller) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=controller.get_credentials_schema(), + provider_type=controller.provider_type.value, + provider_identity=controller.identity.name + ) decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) @@ -135,7 +140,12 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, api_provider, credentials = cls.get_api_provider_controller(tenant_id, provider_id) # decrypt the credentials - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=api_provider) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=api_provider.get_credentials_schema(), + provider_type=api_provider.provider_type.value, + provider_identity=api_provider.identity.name + ) decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) return cast(ApiTool, api_provider.get_tool(tool_name).fork_tool_runtime(runtime={ @@ -513,7 +523,12 @@ def user_get_api_provider(cls, provider: str, tenant_id: str) -> dict: provider_obj, ApiProviderAuthType.API_KEY if credentials['auth_type'] == 'api_key' else ApiProviderAuthType.NONE ) # init tool configuration - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=controller) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=controller.get_credentials_schema(), + provider_type=controller.provider_type.value, + provider_identity=controller.identity.name + ) decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) masked_credentials = tool_configuration.mask_tool_credentials(decrypted_credentials) diff --git a/api/core/tools/utils/configuration.py b/api/core/tools/utils/configuration.py index 2fc0ba3bcd3192..5b65ce443f0fcc 100644 --- a/api/core/tools/utils/configuration.py +++ b/api/core/tools/utils/configuration.py @@ -1,23 +1,25 @@ +from collections.abc import Mapping from copy import deepcopy from typing import Any from pydantic import BaseModel +from core.entities.provider_entities import BasicProviderConfig from core.helper import encrypter from core.helper.tool_parameter_cache import ToolParameterCache, ToolParameterCacheType from core.helper.tool_provider_cache import ToolProviderCredentialsCache, ToolProviderCredentialsCacheType from core.tools.entities.tool_entities import ( - ProviderConfig, ToolParameter, ToolProviderType, ) -from core.tools.provider.tool_provider import ToolProviderController from core.tools.tool.tool import Tool class ToolConfigurationManager(BaseModel): tenant_id: str - provider_controller: ToolProviderController + config: Mapping[str, BasicProviderConfig] + provider_type: str + provider_identity: str def _deep_copy(self, credentials: dict[str, str]) -> dict[str, str]: """ @@ -34,9 +36,9 @@ def encrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str credentials = self._deep_copy(credentials) # get fields need to be decrypted - fields = self.provider_controller.get_credentials_schema() + fields = self.config for field_name, field in fields.items(): - if field.type == ProviderConfig.Type.SECRET_INPUT: + if field.type == BasicProviderConfig.Type.SECRET_INPUT: if field_name in credentials: encrypted = encrypter.encrypt_token(self.tenant_id, credentials[field_name]) credentials[field_name] = encrypted @@ -52,9 +54,9 @@ def mask_tool_credentials(self, credentials: dict[str, Any]) -> dict[str, Any]: credentials = self._deep_copy(credentials) # get fields need to be decrypted - fields = self.provider_controller.get_credentials_schema() + fields = self.config for field_name, field in fields.items(): - if field.type == ProviderConfig.Type.SECRET_INPUT: + if field.type == BasicProviderConfig.Type.SECRET_INPUT: if field_name in credentials: if len(credentials[field_name]) > 6: credentials[field_name] = \ @@ -74,7 +76,7 @@ def decrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str """ cache = ToolProviderCredentialsCache( tenant_id=self.tenant_id, - identity_id=f'{self.provider_controller.provider_type.value}.{self.provider_controller.identity.name}', + identity_id=f'{self.provider_type}.{self.provider_identity}', cache_type=ToolProviderCredentialsCacheType.PROVIDER ) cached_credentials = cache.get() @@ -82,9 +84,9 @@ def decrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str return cached_credentials credentials = self._deep_copy(credentials) # get fields need to be decrypted - fields = self.provider_controller.get_credentials_schema() + fields = self.config for field_name, field in fields.items(): - if field.type == ProviderConfig.Type.SECRET_INPUT: + if field.type == BasicProviderConfig.Type.SECRET_INPUT: if field_name in credentials: try: credentials[field_name] = encrypter.decrypt_token(self.tenant_id, credentials[field_name]) @@ -97,7 +99,7 @@ def decrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str def delete_tool_credentials_cache(self): cache = ToolProviderCredentialsCache( tenant_id=self.tenant_id, - identity_id=f'{self.provider_controller.provider_type.value}.{self.provider_controller.identity.name}', + identity_id=f'{self.provider_type}.{self.provider_identity}', cache_type=ToolProviderCredentialsCacheType.PROVIDER ) cache.delete() diff --git a/api/core/tools/utils/parser.py b/api/core/tools/utils/parser.py index f711f7c9f3c2e8..882e276afe37a7 100644 --- a/api/core/tools/utils/parser.py +++ b/api/core/tools/utils/parser.py @@ -16,7 +16,7 @@ class ApiBasedToolSchemaParser: @staticmethod - def parse_openapi_to_tool_bundle(openapi: dict, extra_info: dict = None, warning: dict = None) -> list[ApiToolBundle]: + def parse_openapi_to_tool_bundle(openapi: dict, extra_info: dict | None = None, warning: dict | None = None) -> list[ApiToolBundle]: warning = warning if warning is not None else {} extra_info = extra_info if extra_info is not None else {} @@ -173,7 +173,7 @@ def _get_tool_parameter_type(parameter: dict) -> ToolParameter.ToolParameterType return ToolParameter.ToolParameterType.STRING @staticmethod - def parse_openapi_yaml_to_tool_bundle(yaml: str, extra_info: dict = None, warning: dict = None) -> list[ApiToolBundle]: + def parse_openapi_yaml_to_tool_bundle(yaml: str, extra_info: dict | None = None, warning: dict | None = None) -> list[ApiToolBundle]: """ parse openapi yaml to tool bundle @@ -189,7 +189,8 @@ def parse_openapi_yaml_to_tool_bundle(yaml: str, extra_info: dict = None, warnin return ApiBasedToolSchemaParser.parse_openapi_to_tool_bundle(openapi, extra_info=extra_info, warning=warning) @staticmethod - def parse_swagger_to_openapi(swagger: dict, extra_info: dict = None, warning: dict = None) -> dict: + def parse_swagger_to_openapi(swagger: dict, extra_info: dict | None = None, warning: dict | None = None) -> dict: + warning = warning or {} """ parse swagger to openapi @@ -255,7 +256,7 @@ def parse_swagger_to_openapi(swagger: dict, extra_info: dict = None, warning: di return openapi @staticmethod - def parse_openai_plugin_json_to_tool_bundle(json: str, extra_info: dict = None, warning: dict = None) -> list[ApiToolBundle]: + def parse_openai_plugin_json_to_tool_bundle(json: str, extra_info: dict | None = None, warning: dict | None = None) -> list[ApiToolBundle]: """ parse openapi plugin yaml to tool bundle @@ -287,7 +288,7 @@ def parse_openai_plugin_json_to_tool_bundle(json: str, extra_info: dict = None, return ApiBasedToolSchemaParser.parse_openapi_yaml_to_tool_bundle(response.text, extra_info=extra_info, warning=warning) @staticmethod - def auto_parse_to_tool_bundle(content: str, extra_info: dict = None, warning: dict = None) -> tuple[list[ApiToolBundle], str]: + def auto_parse_to_tool_bundle(content: str, extra_info: dict | None = None, warning: dict | None = None) -> tuple[list[ApiToolBundle], str]: """ auto parse to tool bundle diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index 6ba7e7e09b01c4..2d01bad1f468ac 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -1,6 +1,6 @@ from collections.abc import Generator, Sequence from os import path -from typing import Any, cast +from typing import Any, Iterable, cast from core.app.segments import ArrayAnySegment, ArrayAnyVariable, parser from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler @@ -158,14 +158,17 @@ def _convert_tool_messages(self, messages: Generator[ToolInvokeMessage, None, No tenant_id=self.tenant_id, conversation_id=None, ) + + result = list(messages) + # extract plain text and files - files = self._extract_tool_response_binary(messages) - plain_text = self._extract_tool_response_text(messages) - json = self._extract_tool_response_json(messages) + files = self._extract_tool_response_binary(result) + plain_text = self._extract_tool_response_text(result) + json = self._extract_tool_response_json(result) return plain_text, files, json - def _extract_tool_response_binary(self, tool_response: Generator[ToolInvokeMessage, None, None]) -> list[FileVar]: + def _extract_tool_response_binary(self, tool_response: Iterable[ToolInvokeMessage]) -> list[FileVar]: """ Extract tool response binary """ @@ -215,7 +218,7 @@ def _extract_tool_response_binary(self, tool_response: Generator[ToolInvokeMessa return result - def _extract_tool_response_text(self, tool_response: Generator[ToolInvokeMessage]) -> str: + def _extract_tool_response_text(self, tool_response: Iterable[ToolInvokeMessage]) -> str: """ Extract tool response text """ @@ -230,7 +233,7 @@ def _extract_tool_response_text(self, tool_response: Generator[ToolInvokeMessage return '\n'.join(result) - def _extract_tool_response_json(self, tool_response: Generator[ToolInvokeMessage]) -> list[dict]: + def _extract_tool_response_json(self, tool_response: Iterable[ToolInvokeMessage]) -> list[dict]: result: list[dict] = [] for message in tool_response: if message.type == ToolInvokeMessage.MessageType.JSON: diff --git a/api/models/model.py b/api/models/model.py index 298bfbda120e90..74ba4a7fd56ba7 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -7,7 +7,7 @@ from flask import request from flask_login import UserMixin from sqlalchemy import Float, func, text -from sqlalchemy.orm import Mapped, mapped_column +from sqlalchemy.orm import Mapped, mapped_column, relationship from configs import dify_config from core.file.tool_file_parser import ToolFileParser @@ -495,14 +495,14 @@ def tenant(self): return tenant -class Conversation(db.Model): +class Conversation(Base): __tablename__ = 'conversations' __table_args__ = ( db.PrimaryKeyConstraint('id', name='conversation_pkey'), db.Index('conversation_app_from_user_idx', 'app_id', 'from_source', 'from_end_user_id') ) - id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) + id: Mapped[str] = mapped_column(StringUUID, server_default=db.text('uuid_generate_v4()')) app_id = db.Column(StringUUID, nullable=False) app_model_config_id = db.Column(StringUUID, nullable=True) model_provider = db.Column(db.String(255), nullable=True) @@ -526,8 +526,8 @@ class Conversation(db.Model): created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) - messages = db.relationship("Message", backref="conversation", lazy='select', passive_deletes="all") - message_annotations = db.relationship("MessageAnnotation", backref="conversation", lazy='select', passive_deletes="all") + messages: Mapped[list["Message"]] = relationship("Message", backref="conversation", lazy='select', passive_deletes="all") + message_annotations: Mapped[list["MessageAnnotation"]] = relationship("MessageAnnotation", backref="conversation", lazy='select', passive_deletes="all") is_deleted = db.Column(db.Boolean, nullable=False, server_default=db.text('false')) @@ -660,10 +660,10 @@ class Message(Base): model_provider = db.Column(db.String(255), nullable=True) model_id = db.Column(db.String(255), nullable=True) override_model_configs = db.Column(db.Text) - conversation_id = db.Column(StringUUID, db.ForeignKey('conversations.id'), nullable=False) - inputs = db.Column(db.JSON) - query = db.Column(db.Text, nullable=False) - message = db.Column(db.JSON, nullable=False) + conversation_id: Mapped[str] = mapped_column(StringUUID, db.ForeignKey('conversations.id'), nullable=False) + inputs: Mapped[str] = mapped_column(db.JSON) + query: Mapped[str] = mapped_column(db.Text, nullable=False) + message: Mapped[str] = mapped_column(db.JSON, nullable=False) message_tokens = db.Column(db.Integer, nullable=False, server_default=db.text('0')) message_unit_price = db.Column(db.Numeric(10, 4), nullable=False) message_price_unit = db.Column(db.Numeric(10, 7), nullable=False, server_default=db.text('0.001')) @@ -944,7 +944,7 @@ class MessageFile(Base): db.Index('message_file_created_by_idx', 'created_by') ) - id: Mapped[str] = mapped_column(StringUUID, default=db.text('uuid_generate_v4()')) + id: Mapped[str] = mapped_column(StringUUID, server_default=db.text('uuid_generate_v4()')) message_id: Mapped[str] = mapped_column(StringUUID, nullable=False) type: Mapped[str] = mapped_column(db.String(255), nullable=False) transfer_method: Mapped[str] = mapped_column(db.String(255), nullable=False) @@ -956,7 +956,7 @@ class MessageFile(Base): created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) -class MessageAnnotation(db.Model): +class MessageAnnotation(Base): __tablename__ = 'message_annotations' __table_args__ = ( db.PrimaryKeyConstraint('id', name='message_annotation_pkey'), @@ -967,7 +967,7 @@ class MessageAnnotation(db.Model): id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) app_id = db.Column(StringUUID, nullable=False) - conversation_id = db.Column(StringUUID, db.ForeignKey('conversations.id'), nullable=True) + conversation_id: Mapped[str] = mapped_column(StringUUID, db.ForeignKey('conversations.id'), nullable=True) message_id = db.Column(StringUUID, nullable=True) question = db.Column(db.Text, nullable=True) content = db.Column(db.Text, nullable=False) diff --git a/api/models/tools.py b/api/models/tools.py index 1e7421622aae08..a87dfad0797934 100644 --- a/api/models/tools.py +++ b/api/models/tools.py @@ -77,10 +77,10 @@ def description_i18n(self) -> I18nObject: return I18nObject(**json.loads(self.description)) @property - def app(self) -> App: + def app(self) -> App | None: return db.session.query(App).filter(App.id == self.app_id).first() -class ApiToolProvider(db.Model): +class ApiToolProvider(Base): """ The table stores the api providers. """ @@ -290,7 +290,7 @@ class ToolFile(Base): db.Index('tool_file_conversation_id_idx', 'conversation_id'), ) - id: Mapped[str] = mapped_column(StringUUID, default=db.text('uuid_generate_v4()')) + id: Mapped[str] = mapped_column(StringUUID, server_default=db.text('uuid_generate_v4()')) # conversation user id user_id: Mapped[str] = mapped_column(StringUUID) # tenant id diff --git a/api/services/tools/api_tools_manage_service.py b/api/services/tools/api_tools_manage_service.py index d7538bd812878b..bfb9827ce268b9 100644 --- a/api/services/tools/api_tools_manage_service.py +++ b/api/services/tools/api_tools_manage_service.py @@ -3,6 +3,7 @@ from httpx import get +from core.entities.provider_entities import ProviderConfig from core.model_runtime.utils.encoders import jsonable_encoder from core.tools.entities.api_entities import UserTool, UserToolProvider from core.tools.entities.common_entities import I18nObject @@ -10,8 +11,6 @@ from core.tools.entities.tool_entities import ( ApiProviderAuthType, ApiProviderSchemaType, - ProviderConfig, - ToolCredentialsOption, ) from core.tools.provider.api_tool_provider import ApiToolProviderController from core.tools.tool_label_manager import ToolLabelManager @@ -45,8 +44,8 @@ def parser_api_schema(schema: str) -> list[ApiToolBundle]: required=True, default="none", options=[ - ToolCredentialsOption(value="none", label=I18nObject(en_US="None", zh_Hans="无")), - ToolCredentialsOption(value="api_key", label=I18nObject(en_US="Api Key", zh_Hans="Api Key")), + ProviderConfig.Option(value="none", label=I18nObject(en_US="None", zh_Hans="无")), + ProviderConfig.Option(value="api_key", label=I18nObject(en_US="Api Key", zh_Hans="Api Key")), ], placeholder=I18nObject(en_US="Select auth type", zh_Hans="选择认证方式"), ), @@ -79,15 +78,14 @@ def parser_api_schema(schema: str) -> list[ApiToolBundle]: raise ValueError(f"invalid schema: {str(e)}") @staticmethod - def convert_schema_to_tool_bundles(schema: str, extra_info: dict = None) -> list[ApiToolBundle]: + def convert_schema_to_tool_bundles(schema: str, extra_info: dict | None = None) -> tuple[list[ApiToolBundle], str]: """ convert schema to tool bundles :return: the list of tool bundles, description """ try: - tool_bundles = ApiBasedToolSchemaParser.auto_parse_to_tool_bundle(schema, extra_info=extra_info) - return tool_bundles + return ApiBasedToolSchemaParser.auto_parse_to_tool_bundle(schema, extra_info=extra_info) except Exception as e: raise ValueError(f"invalid schema: {str(e)}") @@ -111,7 +109,7 @@ def create_api_tool_provider( raise ValueError(f"invalid schema type {schema}") # check if the provider exists - provider: ApiToolProvider = ( + provider: ApiToolProvider | None = ( db.session.query(ApiToolProvider) .filter( ApiToolProvider.tenant_id == tenant_id, @@ -158,7 +156,13 @@ def create_api_tool_provider( provider_controller.load_bundled_tools(tool_bundles) # encrypt credentials - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=provider_controller) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name + ) + encrypted_credentials = tool_configuration.encrypt_tool_credentials(credentials) db_provider.credentials_str = json.dumps(encrypted_credentials) @@ -195,21 +199,21 @@ def get_api_tool_provider_remote_schema(user_id: str, tenant_id: str, url: str): return {"schema": schema} @staticmethod - def list_api_tool_provider_tools(user_id: str, tenant_id: str, provider: str) -> list[UserTool]: + def list_api_tool_provider_tools(user_id: str, tenant_id: str, provider_name: str) -> list[UserTool]: """ list api tool provider tools """ - provider: ApiToolProvider = ( + provider: ApiToolProvider | None = ( db.session.query(ApiToolProvider) .filter( ApiToolProvider.tenant_id == tenant_id, - ApiToolProvider.name == provider, + ApiToolProvider.name == provider_name, ) .first() ) if provider is None: - raise ValueError(f"you have not added provider {provider}") + raise ValueError(f"you have not added provider {provider_name}") controller = ToolTransformService.api_provider_to_controller(db_provider=provider) labels = ToolLabelManager.get_tool_labels(controller) @@ -243,7 +247,7 @@ def update_api_tool_provider( raise ValueError(f"invalid schema type {schema}") # check if the provider exists - provider: ApiToolProvider = ( + provider: ApiToolProvider | None = ( db.session.query(ApiToolProvider) .filter( ApiToolProvider.tenant_id == tenant_id, @@ -282,7 +286,12 @@ def update_api_tool_provider( provider_controller.load_bundled_tools(tool_bundles) # get original credentials if exists - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=provider_controller) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name + ) original_credentials = tool_configuration.decrypt_tool_credentials(provider.credentials) masked_credentials = tool_configuration.mask_tool_credentials(original_credentials) @@ -310,7 +319,7 @@ def delete_api_tool_provider(user_id: str, tenant_id: str, provider_name: str): """ delete tool provider """ - provider: ApiToolProvider = ( + provider: ApiToolProvider | None = ( db.session.query(ApiToolProvider) .filter( ApiToolProvider.tenant_id == tenant_id, @@ -360,7 +369,7 @@ def test_api_tool_preview( if tool_bundle is None: raise ValueError(f"invalid tool name {tool_name}") - db_provider: ApiToolProvider = ( + db_provider: ApiToolProvider | None = ( db.session.query(ApiToolProvider) .filter( ApiToolProvider.tenant_id == tenant_id, @@ -396,7 +405,12 @@ def test_api_tool_preview( # decrypt credentials if db_provider.id: - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=provider_controller) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name + ) decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) # check if the credential has changed, save the original credential masked_credentials = tool_configuration.mask_tool_credentials(decrypted_credentials) @@ -444,7 +458,7 @@ def list_api_tools(user_id: str, tenant_id: str) -> list[UserToolProvider]: # add icon ToolTransformService.repack_provider(user_provider) - tools = provider_controller.get_tools(user_id=user_id, tenant_id=tenant_id) + tools = provider_controller.get_tools(tenant_id=tenant_id) for tool in tools: user_provider.tools.append( diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index 1848fb2a1343ce..513a4219660b75 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -3,12 +3,12 @@ from typing import Optional, Union from configs import dify_config +from core.entities.provider_entities import ProviderConfig from core.tools.entities.api_entities import UserTool, UserToolProvider from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( ApiProviderAuthType, - ProviderConfig, ToolParameter, ToolProviderType, ) @@ -106,7 +106,10 @@ def builtin_provider_to_user_provider( # init tool configuration tool_configuration = ToolConfigurationManager( - tenant_id=db_provider.tenant_id, provider_controller=provider_controller + tenant_id=db_provider.tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name ) # decrypt the credentials and mask the credentials decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials=credentials) @@ -143,7 +146,7 @@ def workflow_provider_to_controller(db_provider: WorkflowToolProvider) -> Workfl @staticmethod def workflow_provider_to_user_provider( - provider_controller: WorkflowToolProviderController, labels: list[str] = None + provider_controller: WorkflowToolProviderController, labels: list[str] | None = None ): """ convert provider controller to user provider @@ -174,7 +177,7 @@ def api_provider_to_user_provider( provider_controller: ApiToolProviderController, db_provider: ApiToolProvider, decrypt_credentials: bool = True, - labels: list[str] = None, + labels: list[str] | None = None, ) -> UserToolProvider: """ convert provider controller to user provider @@ -209,7 +212,10 @@ def api_provider_to_user_provider( if decrypt_credentials: # init tool configuration tool_configuration = ToolConfigurationManager( - tenant_id=db_provider.tenant_id, provider_controller=provider_controller + tenant_id=db_provider.tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name ) # decrypt the credentials and mask the credentials @@ -223,9 +229,9 @@ def api_provider_to_user_provider( @staticmethod def tool_to_user_tool( tool: Union[ApiToolBundle, WorkflowTool, Tool], - credentials: dict = None, - tenant_id: str = None, - labels: list[str] = None, + credentials: dict | None = None, + tenant_id: str | None = None, + labels: list[str] | None = None, ) -> UserTool: """ convert tool to user tool From 46ba16fe901bd826d5de7d1a2c85056d99e67bf1 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 30 Aug 2024 18:21:03 +0800 Subject: [PATCH 023/325] fix: reformatter --- api/core/workflow/nodes/tool/tool_node.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index 2d01bad1f468ac..ba0f67e1e2bed0 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -1,6 +1,6 @@ -from collections.abc import Generator, Sequence +from collections.abc import Generator, Iterable, Sequence from os import path -from typing import Any, Iterable, cast +from typing import Any, cast from core.app.segments import ArrayAnySegment, ArrayAnyVariable, parser from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler From 279dee485db13767da34d1f0d552eb8b388541fb Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 30 Aug 2024 21:10:19 +0800 Subject: [PATCH 024/325] feat: type --- api/core/entities/provider_entities.py | 4 - api/core/tools/entities/api_entities.py | 2 +- .../tools/provider/workflow_tool_provider.py | 6 +- api/models/tools.py | 108 ++++++------------ .../tools/builtin_tools_manage_service.py | 49 +++++--- api/services/tools/tools_transform_service.py | 24 ++-- .../tools/workflow_tools_manage_service.py | 75 ++++++------ 7 files changed, 121 insertions(+), 147 deletions(-) diff --git a/api/core/entities/provider_entities.py b/api/core/entities/provider_entities.py index e0d1de151f143d..6c616d1aadfa8d 100644 --- a/api/core/entities/provider_entities.py +++ b/api/core/entities/provider_entities.py @@ -128,10 +128,6 @@ def value_of(cls, value: str) -> "ProviderConfig.Type": return mode raise ValueError(f'invalid mode value {value}') - @staticmethod - def default(value: str) -> str: - return "" - type: Type = Field(..., description="The type of the credentials") name: str = Field(..., description="The name of the credentials") diff --git a/api/core/tools/entities/api_entities.py b/api/core/tools/entities/api_entities.py index 2aaca3506009b2..3f0e7285af1667 100644 --- a/api/core/tools/entities/api_entities.py +++ b/api/core/tools/entities/api_entities.py @@ -26,7 +26,7 @@ class UserToolProvider(BaseModel): author: str name: str # identifier description: I18nObject - icon: str + icon: str | dict label: I18nObject # label type: ToolProviderType masked_credentials: Optional[dict] = None diff --git a/api/core/tools/provider/workflow_tool_provider.py b/api/core/tools/provider/workflow_tool_provider.py index a84b7a36ed9e47..19bf3d9a86adf4 100644 --- a/api/core/tools/provider/workflow_tool_provider.py +++ b/api/core/tools/provider/workflow_tool_provider.py @@ -208,8 +208,12 @@ def get_tools(self, tenant_id: str) -> list[WorkflowTool]: if not db_providers: return [] + + app = db_providers.app + if not app: + raise ValueError("can not read app of workflow") - self.tools = [self._get_db_provider_tool(db_providers, db_providers.app)] + self.tools = [self._get_db_provider_tool(db_providers, app)] return self.tools diff --git a/api/models/tools.py b/api/models/tools.py index a87dfad0797934..47b89bfe0afef3 100644 --- a/api/models/tools.py +++ b/api/models/tools.py @@ -1,4 +1,5 @@ import json +from datetime import datetime from sqlalchemy import ForeignKey from sqlalchemy.orm import Mapped, mapped_column @@ -13,7 +14,7 @@ from .types import StringUUID -class BuiltinToolProvider(db.Model): +class BuiltinToolProvider(Base): """ This table stores the tool provider information for built-in tools for each tenant. """ @@ -25,61 +26,22 @@ class BuiltinToolProvider(db.Model): ) # id of the tool provider - id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) + id: Mapped[str] = mapped_column(StringUUID, server_default=db.text('uuid_generate_v4()')) # id of the tenant - tenant_id = db.Column(StringUUID, nullable=True) + tenant_id: Mapped[str] = mapped_column(StringUUID, nullable=True) # who created this tool provider - user_id = db.Column(StringUUID, nullable=False) + user_id: Mapped[str] = mapped_column(StringUUID, nullable=False) # name of the tool provider - provider = db.Column(db.String(40), nullable=False) + provider: Mapped[str] = mapped_column(db.String(40), nullable=False) # credential of the tool provider - encrypted_credentials = db.Column(db.Text, nullable=True) - created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) - updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) + encrypted_credentials: Mapped[str] = mapped_column(db.Text, nullable=True) + created_at: Mapped[datetime] = mapped_column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) + updated_at: Mapped[datetime] = mapped_column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) @property def credentials(self) -> dict: return json.loads(self.encrypted_credentials) -class PublishedAppTool(db.Model): - """ - The table stores the apps published as a tool for each person. - """ - __tablename__ = 'tool_published_apps' - __table_args__ = ( - db.PrimaryKeyConstraint('id', name='published_app_tool_pkey'), - db.UniqueConstraint('app_id', 'user_id', name='unique_published_app_tool') - ) - - # id of the tool provider - id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) - # id of the app - app_id = db.Column(StringUUID, ForeignKey('apps.id'), nullable=False) - # who published this tool - user_id = db.Column(StringUUID, nullable=False) - # description of the tool, stored in i18n format, for human - description = db.Column(db.Text, nullable=False) - # llm_description of the tool, for LLM - llm_description = db.Column(db.Text, nullable=False) - # query description, query will be seem as a parameter of the tool, to describe this parameter to llm, we need this field - query_description = db.Column(db.Text, nullable=False) - # query name, the name of the query parameter - query_name = db.Column(db.String(40), nullable=False) - # name of the tool provider - tool_name = db.Column(db.String(40), nullable=False) - # author - author = db.Column(db.String(40), nullable=False) - created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) - updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) - - @property - def description_i18n(self) -> I18nObject: - return I18nObject(**json.loads(self.description)) - - @property - def app(self) -> App | None: - return db.session.query(App).filter(App.id == self.app_id).first() - class ApiToolProvider(Base): """ The table stores the api providers. @@ -129,14 +91,14 @@ def credentials(self) -> dict: return json.loads(self.credentials_str) @property - def user(self) -> Account: + def user(self) -> Account | None: return db.session.query(Account).filter(Account.id == self.user_id).first() @property - def tenant(self) -> Tenant: + def tenant(self) -> Tenant | None: return db.session.query(Tenant).filter(Tenant.id == self.tenant_id).first() -class ToolLabelBinding(db.Model): +class ToolLabelBinding(Base): """ The table stores the labels for tools. """ @@ -146,15 +108,15 @@ class ToolLabelBinding(db.Model): db.UniqueConstraint('tool_id', 'label_name', name='unique_tool_label_bind'), ) - id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) + id: Mapped[str] = mapped_column(StringUUID, server_default=db.text('uuid_generate_v4()')) # tool id - tool_id = db.Column(db.String(64), nullable=False) + tool_id: Mapped[str] = mapped_column(db.String(64), nullable=False) # tool type - tool_type = db.Column(db.String(40), nullable=False) + tool_type: Mapped[str] = mapped_column(db.String(40), nullable=False) # label name - label_name = db.Column(db.String(40), nullable=False) + label_name: Mapped[str] = mapped_column(db.String(40), nullable=False) -class WorkflowToolProvider(db.Model): +class WorkflowToolProvider(Base): """ The table stores the workflow providers. """ @@ -165,41 +127,37 @@ class WorkflowToolProvider(db.Model): db.UniqueConstraint('tenant_id', 'app_id', name='unique_workflow_tool_provider_app_id'), ) - id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) + id: Mapped[str] = mapped_column(StringUUID, server_default=db.text('uuid_generate_v4()')) # name of the workflow provider - name = db.Column(db.String(40), nullable=False) + name: Mapped[str] = mapped_column(db.String(40), nullable=False) # label of the workflow provider - label = db.Column(db.String(255), nullable=False, server_default='') + label: Mapped[str] = mapped_column(db.String(255), nullable=False, server_default='') # icon - icon = db.Column(db.String(255), nullable=False) + icon: Mapped[str] = mapped_column(db.String(255), nullable=False) # app id of the workflow provider - app_id = db.Column(StringUUID, nullable=False) + app_id: Mapped[str] = mapped_column(StringUUID, nullable=False) # version of the workflow provider - version = db.Column(db.String(255), nullable=False, server_default='') + version: Mapped[str] = mapped_column(db.String(255), nullable=False, server_default='') # who created this tool - user_id = db.Column(StringUUID, nullable=False) + user_id: Mapped[str] = mapped_column(StringUUID, nullable=False) # tenant id - tenant_id = db.Column(StringUUID, nullable=False) + tenant_id: Mapped[str] = mapped_column(StringUUID, nullable=False) # description of the provider - description = db.Column(db.Text, nullable=False) + description: Mapped[str] = mapped_column(db.Text, nullable=False) # parameter configuration - parameter_configuration = db.Column(db.Text, nullable=False, server_default='[]') + parameter_configuration: Mapped[str] = mapped_column(db.Text, nullable=False, server_default='[]') # privacy policy - privacy_policy = db.Column(db.String(255), nullable=True, server_default='') + privacy_policy: Mapped[str] = mapped_column(db.String(255), nullable=True, server_default='') - created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) - updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) + created_at: Mapped[datetime] = mapped_column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) + updated_at: Mapped[datetime] = mapped_column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) @property - def schema_type(self) -> ApiProviderSchemaType: - return ApiProviderSchemaType.value_of(self.schema_type_str) - - @property - def user(self) -> Account: + def user(self) -> Account | None: return db.session.query(Account).filter(Account.id == self.user_id).first() @property - def tenant(self) -> Tenant: + def tenant(self) -> Tenant | None: return db.session.query(Tenant).filter(Tenant.id == self.tenant_id).first() @property @@ -210,7 +168,7 @@ def parameter_configurations(self) -> list[WorkflowToolParameterConfiguration]: ] @property - def app(self) -> App: + def app(self) -> App | None: return db.session.query(App).filter(App.id == self.app_id).first() class ToolModelInvoke(db.Model): diff --git a/api/services/tools/builtin_tools_manage_service.py b/api/services/tools/builtin_tools_manage_service.py index dc8cebb587a2d8..8bc93e7ea3be0f 100644 --- a/api/services/tools/builtin_tools_manage_service.py +++ b/api/services/tools/builtin_tools_manage_service.py @@ -28,10 +28,13 @@ def list_builtin_tool_provider_tools(user_id: str, tenant_id: str, provider: str tools = provider_controller.get_tools() tool_provider_configurations = ToolConfigurationManager( - tenant_id=tenant_id, provider_controller=provider_controller + tenant_id=tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name, ) # check if user has added the provider - builtin_provider: BuiltinToolProvider = ( + builtin_provider: BuiltinToolProvider | None = ( db.session.query(BuiltinToolProvider) .filter( BuiltinToolProvider.tenant_id == tenant_id, @@ -75,7 +78,7 @@ def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st update builtin tool provider """ # get if the provider exists - provider: BuiltinToolProvider = ( + provider: BuiltinToolProvider | None = ( db.session.query(BuiltinToolProvider) .filter( BuiltinToolProvider.tenant_id == tenant_id, @@ -89,7 +92,13 @@ def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st provider_controller = ToolManager.get_builtin_provider(provider_name) if not provider_controller.need_credentials: raise ValueError(f"provider {provider_name} does not need credentials") - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=provider_controller) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name, + ) + # get original credentials if exists if provider is not None: original_credentials = tool_configuration.decrypt_tool_credentials(provider.credentials) @@ -132,7 +141,7 @@ def get_builtin_tool_provider_credentials(user_id: str, tenant_id: str, provider """ get builtin tool provider credentials """ - provider: BuiltinToolProvider = ( + provider_obj: BuiltinToolProvider | None = ( db.session.query(BuiltinToolProvider) .filter( BuiltinToolProvider.tenant_id == tenant_id, @@ -141,12 +150,17 @@ def get_builtin_tool_provider_credentials(user_id: str, tenant_id: str, provider .first() ) - if provider is None: + if provider_obj is None: return {} - provider_controller = ToolManager.get_builtin_provider(provider.provider) - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=provider_controller) - credentials = tool_configuration.decrypt_tool_credentials(provider.credentials) + provider_controller = ToolManager.get_builtin_provider(provider_obj.provider) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name, + ) + credentials = tool_configuration.decrypt_tool_credentials(provider_obj.credentials) credentials = tool_configuration.mask_tool_credentials(credentials) return credentials @@ -155,7 +169,7 @@ def delete_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st """ delete tool provider """ - provider: BuiltinToolProvider = ( + provider_obj: BuiltinToolProvider | None = ( db.session.query(BuiltinToolProvider) .filter( BuiltinToolProvider.tenant_id == tenant_id, @@ -164,15 +178,20 @@ def delete_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st .first() ) - if provider is None: + if provider_obj is None: raise ValueError(f"you have not added provider {provider_name}") - db.session.delete(provider) + db.session.delete(provider_obj) db.session.commit() # delete cache provider_controller = ToolManager.get_builtin_provider(provider_name) - tool_configuration = ToolConfigurationManager(tenant_id=tenant_id, provider_controller=provider_controller) + tool_configuration = ToolConfigurationManager( + tenant_id=tenant_id, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.identity.name, + ) tool_configuration.delete_tool_credentials_cache() return {"result": "success"} @@ -212,8 +231,8 @@ def list_builtin_tools(user_id: str, tenant_id: str) -> list[UserToolProvider]: try: # handle include, exclude if is_filtered( - include_set=dify_config.POSITION_TOOL_INCLUDES_SET, - exclude_set=dify_config.POSITION_TOOL_EXCLUDES_SET, + include_set=dify_config.POSITION_TOOL_INCLUDES_SET, # type: ignore + exclude_set=dify_config.POSITION_TOOL_EXCLUDES_SET, # type: ignore data=provider_controller, name_func=lambda x: x.identity.name, ): diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index 513a4219660b75..8b4076a418a102 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -1,6 +1,6 @@ import json import logging -from typing import Optional, Union +from typing import Literal, Optional, Union, overload from configs import dify_config from core.entities.provider_entities import ProviderConfig @@ -25,7 +25,7 @@ class ToolTransformService: @classmethod - def get_tool_provider_icon_url(cls, provider_type: str, provider_name: str, icon: str) -> Union[str, dict]: + def get_tool_provider_icon_url(cls, provider_type: str, provider_name: str, icon: str | dict) -> Union[str, dict]: """ get tool provider icon url """ @@ -35,7 +35,9 @@ def get_tool_provider_icon_url(cls, provider_type: str, provider_name: str, icon return url_prefix + "builtin/" + provider_name + "/icon" elif provider_type in [ToolProviderType.API.value, ToolProviderType.WORKFLOW.value]: try: - return json.loads(icon) + if isinstance(icon, str): + return json.loads(icon) + return icon except: return {"background": "#252525", "content": "\ud83d\ude01"} @@ -92,7 +94,8 @@ def builtin_provider_to_user_provider( # get credentials schema schema = provider_controller.get_credentials_schema() for name, value in schema.items(): - result.masked_credentials[name] = ProviderConfig.Type.default(value.type) + if result.masked_credentials: + result.masked_credentials[name] = "" # check if the provider need credentials if not provider_controller.need_credentials: @@ -184,9 +187,14 @@ def api_provider_to_user_provider( """ username = "Anonymous" try: - username = db_provider.user.name + user = db_provider.user + if not user: + raise ValueError("user not found") + + username = user.name except Exception as e: logger.error(f"failed to get user name for api provider {db_provider.id}: {str(e)}") + # add provider into providers credentials = db_provider.credentials result = UserToolProvider( @@ -266,9 +274,9 @@ def tool_to_user_tool( author=tool.identity.author, name=tool.identity.name, label=tool.identity.label, - description=tool.description.human, + description=tool.description.human if tool.description else I18nObject(en_US=''), parameters=current_parameters, - labels=labels, + labels=labels or [], ) if isinstance(tool, ApiToolBundle): return UserTool( @@ -277,5 +285,5 @@ def tool_to_user_tool( label=I18nObject(en_US=tool.operation_id, zh_Hans=tool.operation_id), description=I18nObject(en_US=tool.summary or "", zh_Hans=tool.summary or ""), parameters=tool.parameters, - labels=labels, + labels=labels or [], ) diff --git a/api/services/tools/workflow_tools_manage_service.py b/api/services/tools/workflow_tools_manage_service.py index 3830e75339eebc..9586e743d08a2d 100644 --- a/api/services/tools/workflow_tools_manage_service.py +++ b/api/services/tools/workflow_tools_manage_service.py @@ -4,7 +4,7 @@ from sqlalchemy import or_ from core.model_runtime.utils.encoders import jsonable_encoder -from core.tools.entities.api_entities import UserToolProvider +from core.tools.entities.api_entities import UserTool, UserToolProvider from core.tools.provider.workflow_tool_provider import WorkflowToolProviderController from core.tools.tool_label_manager import ToolLabelManager from core.tools.utils.workflow_configuration_sync import WorkflowToolConfigurationUtils @@ -32,7 +32,7 @@ def create_workflow_tool( description: str, parameters: list[dict], privacy_policy: str = "", - labels: list[str] = None, + labels: list[str] | None = None, ) -> dict: """ Create a workflow tool. @@ -62,12 +62,12 @@ def create_workflow_tool( if existing_workflow_tool_provider is not None: raise ValueError(f"Tool with name {name} or app_id {workflow_app_id} already exists") - app: App = db.session.query(App).filter(App.id == workflow_app_id, App.tenant_id == tenant_id).first() + app: App | None = db.session.query(App).filter(App.id == workflow_app_id, App.tenant_id == tenant_id).first() if app is None: raise ValueError(f"App {workflow_app_id} not found") - workflow: Workflow = app.workflow + workflow: Workflow | None = app.workflow if workflow is None: raise ValueError(f"Workflow not found for app {workflow_app_id}") @@ -106,7 +106,7 @@ def update_workflow_tool( description: str, parameters: list[dict], privacy_policy: str = "", - labels: list[str] = None, + labels: list[str] | None = None, ) -> dict: """ Update a workflow tool. @@ -138,7 +138,7 @@ def update_workflow_tool( if existing_workflow_tool_provider is not None: raise ValueError(f"Tool with name {name} already exists") - workflow_tool_provider: WorkflowToolProvider = ( + workflow_tool_provider: WorkflowToolProvider | None = ( db.session.query(WorkflowToolProvider) .filter(WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.id == workflow_tool_id) .first() @@ -147,14 +147,14 @@ def update_workflow_tool( if workflow_tool_provider is None: raise ValueError(f"Tool {workflow_tool_id} not found") - app: App = ( + app: App | None = ( db.session.query(App).filter(App.id == workflow_tool_provider.app_id, App.tenant_id == tenant_id).first() ) if app is None: raise ValueError(f"App {workflow_tool_provider.app_id} not found") - workflow: Workflow = app.workflow + workflow: Workflow | None = app.workflow if workflow is None: raise ValueError(f"Workflow not found for app {workflow_tool_provider.app_id}") @@ -243,36 +243,12 @@ def get_workflow_tool_by_tool_id(cls, user_id: str, tenant_id: str, workflow_too :param workflow_app_id: the workflow app id :return: the tool """ - db_tool: WorkflowToolProvider = ( + db_tool: WorkflowToolProvider | None = ( db.session.query(WorkflowToolProvider) .filter(WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.id == workflow_tool_id) .first() ) - - if db_tool is None: - raise ValueError(f"Tool {workflow_tool_id} not found") - - workflow_app: App = db.session.query(App).filter(App.id == db_tool.app_id, App.tenant_id == tenant_id).first() - - if workflow_app is None: - raise ValueError(f"App {db_tool.app_id} not found") - - tool = ToolTransformService.workflow_provider_to_controller(db_tool) - - return { - "name": db_tool.name, - "label": db_tool.label, - "workflow_tool_id": db_tool.id, - "workflow_app_id": db_tool.app_id, - "icon": json.loads(db_tool.icon), - "description": db_tool.description, - "parameters": jsonable_encoder(db_tool.parameter_configurations), - "tool": ToolTransformService.tool_to_user_tool( - tool.get_tools(user_id, tenant_id)[0], labels=ToolLabelManager.get_tool_labels(tool) - ), - "synced": workflow_app.workflow.version == db_tool.version, - "privacy_policy": db_tool.privacy_policy, - } + return cls._get_workflow_tool(db_tool) @classmethod def get_workflow_tool_by_app_id(cls, user_id: str, tenant_id: str, workflow_app_id: str) -> dict: @@ -283,19 +259,31 @@ def get_workflow_tool_by_app_id(cls, user_id: str, tenant_id: str, workflow_app_ :param workflow_app_id: the workflow app id :return: the tool """ - db_tool: WorkflowToolProvider = ( + db_tool: WorkflowToolProvider | None = ( db.session.query(WorkflowToolProvider) .filter(WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.app_id == workflow_app_id) .first() ) - + return cls._get_workflow_tool(db_tool) + + @classmethod + def _get_workflow_tool(cls, db_tool: WorkflowToolProvider | None): + """ + Get a workflow tool. + :db_tool: the database tool + :return: the tool + """ if db_tool is None: - raise ValueError(f"Tool {workflow_app_id} not found") + raise ValueError("Tool not found") - workflow_app: App = db.session.query(App).filter(App.id == db_tool.app_id, App.tenant_id == tenant_id).first() + workflow_app: App | None = db.session.query(App).filter(App.id == db_tool.app_id, App.tenant_id == db_tool.tenant_id).first() if workflow_app is None: raise ValueError(f"App {db_tool.app_id} not found") + + workflow = workflow_app.workflow + if not workflow: + raise ValueError("Workflow not found") tool = ToolTransformService.workflow_provider_to_controller(db_tool) @@ -308,14 +296,14 @@ def get_workflow_tool_by_app_id(cls, user_id: str, tenant_id: str, workflow_app_ "description": db_tool.description, "parameters": jsonable_encoder(db_tool.parameter_configurations), "tool": ToolTransformService.tool_to_user_tool( - tool.get_tools(user_id, tenant_id)[0], labels=ToolLabelManager.get_tool_labels(tool) + tool.get_tools(db_tool.tenant_id)[0], labels=ToolLabelManager.get_tool_labels(tool) ), - "synced": workflow_app.workflow.version == db_tool.version, + "synced": workflow.version == db_tool.version, "privacy_policy": db_tool.privacy_policy, } @classmethod - def list_single_workflow_tools(cls, user_id: str, tenant_id: str, workflow_tool_id: str) -> list[dict]: + def list_single_workflow_tools(cls, user_id: str, tenant_id: str, workflow_tool_id: str) -> list[UserTool]: """ List workflow tool provider tools. :param user_id: the user id @@ -323,7 +311,7 @@ def list_single_workflow_tools(cls, user_id: str, tenant_id: str, workflow_tool_ :param workflow_app_id: the workflow app id :return: the list of tools """ - db_tool: WorkflowToolProvider = ( + db_tool: WorkflowToolProvider | None = ( db.session.query(WorkflowToolProvider) .filter(WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.id == workflow_tool_id) .first() @@ -336,6 +324,7 @@ def list_single_workflow_tools(cls, user_id: str, tenant_id: str, workflow_tool_ return [ ToolTransformService.tool_to_user_tool( - tool.get_tools(user_id, tenant_id)[0], labels=ToolLabelManager.get_tool_labels(tool) + tool=tool.get_tools(db_tool.tenant_id)[0], + labels=ToolLabelManager.get_tool_labels(tool) ) ] From 60e75dc748c1173e1ae65ef03fc70faa380b9208 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 30 Aug 2024 21:11:39 +0800 Subject: [PATCH 025/325] fix: linter --- api/models/tools.py | 2 -- api/services/tools/tools_transform_service.py | 3 +-- 2 files changed, 1 insertion(+), 4 deletions(-) diff --git a/api/models/tools.py b/api/models/tools.py index 47b89bfe0afef3..27d1001740c1a6 100644 --- a/api/models/tools.py +++ b/api/models/tools.py @@ -1,10 +1,8 @@ import json from datetime import datetime -from sqlalchemy import ForeignKey from sqlalchemy.orm import Mapped, mapped_column -from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ApiProviderSchemaType, WorkflowToolParameterConfiguration from extensions.ext_database import db diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index 8b4076a418a102..56e579a27b8eb6 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -1,9 +1,8 @@ import json import logging -from typing import Literal, Optional, Union, overload +from typing import Optional, Union from configs import dify_config -from core.entities.provider_entities import ProviderConfig from core.tools.entities.api_entities import UserTool, UserToolProvider from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle From de01ca8d550c3daa8107131a2d354fc317d0dc89 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 30 Aug 2024 21:25:58 +0800 Subject: [PATCH 026/325] feat: inner api encrypt --- api/controllers/inner_api/plugin/plugin.py | 7 ++- api/core/plugin/encrypt/__init__.py | 22 ++++++++ api/core/plugin/entities/request.py | 4 +- api/core/tools/tool_manager.py | 14 ++--- api/core/tools/utils/configuration.py | 52 +++++++++---------- .../tools/api_tools_manage_service.py | 16 +++--- .../tools/builtin_tools_manage_service.py | 18 +++---- api/services/tools/tools_transform_service.py | 14 ++--- 8 files changed, 88 insertions(+), 59 deletions(-) create mode 100644 api/core/plugin/encrypt/__init__.py diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index c3911f31aeb56a..70a74e73e7868f 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -8,6 +8,7 @@ from controllers.inner_api.wraps import plugin_inner_api_only from core.plugin.backwards_invocation.app import PluginAppBackwardsInvocation from core.plugin.backwards_invocation.model import PluginModelBackwardsInvocation +from core.plugin.encrypt import PluginEncrypter from core.plugin.entities.request import ( RequestInvokeApp, RequestInvokeEncrypt, @@ -139,7 +140,10 @@ class PluginInvokeEncryptApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeEncrypt) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeEncrypt): - """""" + """ + encrypt or decrypt data + """ + return PluginEncrypter.invoke_encrypt(tenant_model, payload) api.add_resource(PluginInvokeLLMApi, '/invoke/llm') api.add_resource(PluginInvokeTextEmbeddingApi, '/invoke/text-embedding') @@ -150,3 +154,4 @@ def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeEncrypt api.add_resource(PluginInvokeToolApi, '/invoke/tool') api.add_resource(PluginInvokeNodeApi, '/invoke/node') api.add_resource(PluginInvokeAppApi, '/invoke/app') +api.add_resource(PluginInvokeEncryptApi, '/invoke/encrypt') diff --git a/api/core/plugin/encrypt/__init__.py b/api/core/plugin/encrypt/__init__.py new file mode 100644 index 00000000000000..5315780fce1222 --- /dev/null +++ b/api/core/plugin/encrypt/__init__.py @@ -0,0 +1,22 @@ +from collections.abc import Mapping +from typing import Any + +from core.plugin.entities.request import RequestInvokeEncrypt +from core.tools.utils.configuration import ProviderConfigEncrypter +from models.account import Tenant + + +class PluginEncrypter: + @classmethod + def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> Mapping[str, Any]: + encrypter = ProviderConfigEncrypter( + tenant_id=tenant.id, + config=payload.data, + provider_type=payload.type, + provider_identity=payload.identity, + ) + + if payload.opt == "encrypt": + return encrypter.encrypt(payload.data) + else: + return encrypter.decrypt(payload.data) \ No newline at end of file diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 0533746815f0a0..9911ec9d85b4b5 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -112,5 +112,7 @@ class RequestInvokeEncrypt(BaseModel): Request to encryption """ opt: Literal["encrypt", "decrypt"] + type: Literal["endpoint"] + identity: str data: dict = Field(default_factory=dict) - config: Mapping[str, BasicProviderConfig] = Field(default_factory=Mapping) + config: Mapping[str, BasicProviderConfig] = Field(default_factory=Mapping) \ No newline at end of file diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 56e97252f9478a..26b8c755802871 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -24,7 +24,7 @@ from core.tools.tool.tool import Tool from core.tools.tool.workflow_tool import WorkflowTool from core.tools.tool_label_manager import ToolLabelManager -from core.tools.utils.configuration import ToolConfigurationManager, ToolParameterConfigurationManager +from core.tools.utils.configuration import ProviderConfigEncrypter, ToolParameterConfigurationManager from core.tools.utils.tool_parameter_converter import ToolParameterConverter from core.workflow.nodes.tool.entities import ToolEntity from extensions.ext_database import db @@ -116,14 +116,14 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, # decrypt the credentials credentials = builtin_provider.credentials controller = cls.get_builtin_provider(provider_id) - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=controller.get_credentials_schema(), provider_type=controller.provider_type.value, provider_identity=controller.identity.name ) - decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) + decrypted_credentials = tool_configuration.decrypt(credentials) return cast(BuiltinTool, builtin_tool.fork_tool_runtime(runtime={ 'tenant_id': tenant_id, @@ -140,13 +140,13 @@ def get_tool_runtime(cls, provider_type: ToolProviderType, api_provider, credentials = cls.get_api_provider_controller(tenant_id, provider_id) # decrypt the credentials - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=api_provider.get_credentials_schema(), provider_type=api_provider.provider_type.value, provider_identity=api_provider.identity.name ) - decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) + decrypted_credentials = tool_configuration.decrypt(credentials) return cast(ApiTool, api_provider.get_tool(tool_name).fork_tool_runtime(runtime={ 'tenant_id': tenant_id, @@ -523,14 +523,14 @@ def user_get_api_provider(cls, provider: str, tenant_id: str) -> dict: provider_obj, ApiProviderAuthType.API_KEY if credentials['auth_type'] == 'api_key' else ApiProviderAuthType.NONE ) # init tool configuration - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=controller.get_credentials_schema(), provider_type=controller.provider_type.value, provider_identity=controller.identity.name ) - decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) + decrypted_credentials = tool_configuration.decrypt(credentials) masked_credentials = tool_configuration.mask_tool_credentials(decrypted_credentials) try: diff --git a/api/core/tools/utils/configuration.py b/api/core/tools/utils/configuration.py index 5b65ce443f0fcc..2f4414c114b91e 100644 --- a/api/core/tools/utils/configuration.py +++ b/api/core/tools/utils/configuration.py @@ -15,60 +15,60 @@ from core.tools.tool.tool import Tool -class ToolConfigurationManager(BaseModel): +class ProviderConfigEncrypter(BaseModel): tenant_id: str config: Mapping[str, BasicProviderConfig] provider_type: str provider_identity: str - def _deep_copy(self, credentials: dict[str, str]) -> dict[str, str]: + def _deep_copy(self, data: dict[str, str]) -> dict[str, str]: """ - deep copy credentials + deep copy data """ - return deepcopy(credentials) + return deepcopy(data) - def encrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str]: + def encrypt(self, data: dict[str, str]) -> Mapping[str, str]: """ encrypt tool credentials with tenant id return a deep copy of credentials with encrypted values """ - credentials = self._deep_copy(credentials) + data = self._deep_copy(data) # get fields need to be decrypted fields = self.config for field_name, field in fields.items(): if field.type == BasicProviderConfig.Type.SECRET_INPUT: - if field_name in credentials: - encrypted = encrypter.encrypt_token(self.tenant_id, credentials[field_name]) - credentials[field_name] = encrypted + if field_name in data: + encrypted = encrypter.encrypt_token(self.tenant_id, data[field_name]) + data[field_name] = encrypted - return credentials + return data - def mask_tool_credentials(self, credentials: dict[str, Any]) -> dict[str, Any]: + def mask_tool_credentials(self, data: dict[str, Any]) -> Mapping[str, Any]: """ mask tool credentials return a deep copy of credentials with masked values """ - credentials = self._deep_copy(credentials) + data = self._deep_copy(data) # get fields need to be decrypted fields = self.config for field_name, field in fields.items(): if field.type == BasicProviderConfig.Type.SECRET_INPUT: - if field_name in credentials: - if len(credentials[field_name]) > 6: - credentials[field_name] = \ - credentials[field_name][:2] + \ - '*' * (len(credentials[field_name]) - 4) + \ - credentials[field_name][-2:] + if field_name in data: + if len(data[field_name]) > 6: + data[field_name] = \ + data[field_name][:2] + \ + '*' * (len(data[field_name]) - 4) + \ + data[field_name][-2:] else: - credentials[field_name] = '*' * len(credentials[field_name]) + data[field_name] = '*' * len(data[field_name]) - return credentials + return data - def decrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str]: + def decrypt(self, data: dict[str, str]) -> Mapping[str, str]: """ decrypt tool credentials with tenant id @@ -82,19 +82,19 @@ def decrypt_tool_credentials(self, credentials: dict[str, str]) -> dict[str, str cached_credentials = cache.get() if cached_credentials: return cached_credentials - credentials = self._deep_copy(credentials) + data = self._deep_copy(data) # get fields need to be decrypted fields = self.config for field_name, field in fields.items(): if field.type == BasicProviderConfig.Type.SECRET_INPUT: - if field_name in credentials: + if field_name in data: try: - credentials[field_name] = encrypter.decrypt_token(self.tenant_id, credentials[field_name]) + data[field_name] = encrypter.decrypt_token(self.tenant_id, data[field_name]) except: pass - cache.set(credentials) - return credentials + cache.set(data) + return data def delete_tool_credentials_cache(self): cache = ToolProviderCredentialsCache( diff --git a/api/services/tools/api_tools_manage_service.py b/api/services/tools/api_tools_manage_service.py index bfb9827ce268b9..3e6e62a415c5ef 100644 --- a/api/services/tools/api_tools_manage_service.py +++ b/api/services/tools/api_tools_manage_service.py @@ -15,7 +15,7 @@ from core.tools.provider.api_tool_provider import ApiToolProviderController from core.tools.tool_label_manager import ToolLabelManager from core.tools.tool_manager import ToolManager -from core.tools.utils.configuration import ToolConfigurationManager +from core.tools.utils.configuration import ProviderConfigEncrypter from core.tools.utils.parser import ApiBasedToolSchemaParser from extensions.ext_database import db from models.tools import ApiToolProvider @@ -156,14 +156,14 @@ def create_api_tool_provider( provider_controller.load_bundled_tools(tool_bundles) # encrypt credentials - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, provider_identity=provider_controller.identity.name ) - encrypted_credentials = tool_configuration.encrypt_tool_credentials(credentials) + encrypted_credentials = tool_configuration.encrypt(credentials) db_provider.credentials_str = json.dumps(encrypted_credentials) db.session.add(db_provider) @@ -286,21 +286,21 @@ def update_api_tool_provider( provider_controller.load_bundled_tools(tool_bundles) # get original credentials if exists - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, provider_identity=provider_controller.identity.name ) - original_credentials = tool_configuration.decrypt_tool_credentials(provider.credentials) + original_credentials = tool_configuration.decrypt(provider.credentials) masked_credentials = tool_configuration.mask_tool_credentials(original_credentials) # check if the credential has changed, save the original credential for name, value in credentials.items(): if name in masked_credentials and value == masked_credentials[name]: credentials[name] = original_credentials[name] - credentials = tool_configuration.encrypt_tool_credentials(credentials) + credentials = tool_configuration.encrypt(credentials) provider.credentials_str = json.dumps(credentials) db.session.add(provider) @@ -405,13 +405,13 @@ def test_api_tool_preview( # decrypt credentials if db_provider.id: - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, provider_identity=provider_controller.identity.name ) - decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials) + decrypted_credentials = tool_configuration.decrypt(credentials) # check if the credential has changed, save the original credential masked_credentials = tool_configuration.mask_tool_credentials(decrypted_credentials) for name, value in credentials.items(): diff --git a/api/services/tools/builtin_tools_manage_service.py b/api/services/tools/builtin_tools_manage_service.py index 8bc93e7ea3be0f..e202eeb15b896e 100644 --- a/api/services/tools/builtin_tools_manage_service.py +++ b/api/services/tools/builtin_tools_manage_service.py @@ -10,7 +10,7 @@ from core.tools.provider.tool_provider import ToolProviderController from core.tools.tool_label_manager import ToolLabelManager from core.tools.tool_manager import ToolManager -from core.tools.utils.configuration import ToolConfigurationManager +from core.tools.utils.configuration import ProviderConfigEncrypter from extensions.ext_database import db from models.tools import BuiltinToolProvider from services.tools.tools_transform_service import ToolTransformService @@ -27,7 +27,7 @@ def list_builtin_tool_provider_tools(user_id: str, tenant_id: str, provider: str provider_controller: ToolProviderController = ToolManager.get_builtin_provider(provider) tools = provider_controller.get_tools() - tool_provider_configurations = ToolConfigurationManager( + tool_provider_configurations = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, @@ -47,7 +47,7 @@ def list_builtin_tool_provider_tools(user_id: str, tenant_id: str, provider: str if builtin_provider is not None: # get credentials credentials = builtin_provider.credentials - credentials = tool_provider_configurations.decrypt_tool_credentials(credentials) + credentials = tool_provider_configurations.decrypt(credentials) result = [] for tool in tools: @@ -92,7 +92,7 @@ def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st provider_controller = ToolManager.get_builtin_provider(provider_name) if not provider_controller.need_credentials: raise ValueError(f"provider {provider_name} does not need credentials") - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, @@ -101,7 +101,7 @@ def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st # get original credentials if exists if provider is not None: - original_credentials = tool_configuration.decrypt_tool_credentials(provider.credentials) + original_credentials = tool_configuration.decrypt(provider.credentials) masked_credentials = tool_configuration.mask_tool_credentials(original_credentials) # check if the credential has changed, save the original credential for name, value in credentials.items(): @@ -110,7 +110,7 @@ def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st # validate credentials provider_controller.validate_credentials(credentials) # encrypt credentials - credentials = tool_configuration.encrypt_tool_credentials(credentials) + credentials = tool_configuration.encrypt(credentials) except (ToolProviderNotFoundError, ToolNotFoundError, ToolProviderCredentialValidationError) as e: raise ValueError(str(e)) @@ -154,13 +154,13 @@ def get_builtin_tool_provider_credentials(user_id: str, tenant_id: str, provider return {} provider_controller = ToolManager.get_builtin_provider(provider_obj.provider) - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, provider_identity=provider_controller.identity.name, ) - credentials = tool_configuration.decrypt_tool_credentials(provider_obj.credentials) + credentials = tool_configuration.decrypt(provider_obj.credentials) credentials = tool_configuration.mask_tool_credentials(credentials) return credentials @@ -186,7 +186,7 @@ def delete_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st # delete cache provider_controller = ToolManager.get_builtin_provider(provider_name) - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index 56e579a27b8eb6..1e069c704bd1b6 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -16,7 +16,7 @@ from core.tools.provider.workflow_tool_provider import WorkflowToolProviderController from core.tools.tool.tool import Tool from core.tools.tool.workflow_tool import WorkflowTool -from core.tools.utils.configuration import ToolConfigurationManager +from core.tools.utils.configuration import ProviderConfigEncrypter from models.tools import ApiToolProvider, BuiltinToolProvider, WorkflowToolProvider logger = logging.getLogger(__name__) @@ -107,15 +107,15 @@ def builtin_provider_to_user_provider( credentials = db_provider.credentials # init tool configuration - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=db_provider.tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, provider_identity=provider_controller.identity.name ) # decrypt the credentials and mask the credentials - decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials=credentials) - masked_credentials = tool_configuration.mask_tool_credentials(credentials=decrypted_credentials) + decrypted_credentials = tool_configuration.decrypt(data=credentials) + masked_credentials = tool_configuration.mask_tool_credentials(data=decrypted_credentials) result.masked_credentials = masked_credentials result.original_credentials = decrypted_credentials @@ -218,7 +218,7 @@ def api_provider_to_user_provider( if decrypt_credentials: # init tool configuration - tool_configuration = ToolConfigurationManager( + tool_configuration = ProviderConfigEncrypter( tenant_id=db_provider.tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, @@ -226,8 +226,8 @@ def api_provider_to_user_provider( ) # decrypt the credentials and mask the credentials - decrypted_credentials = tool_configuration.decrypt_tool_credentials(credentials=credentials) - masked_credentials = tool_configuration.mask_tool_credentials(credentials=decrypted_credentials) + decrypted_credentials = tool_configuration.decrypt(data=credentials) + masked_credentials = tool_configuration.mask_tool_credentials(data=decrypted_credentials) result.masked_credentials = masked_credentials From b7c5abc5dd8871e38b42843cb749c70af899a59e Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 30 Aug 2024 23:29:04 +0800 Subject: [PATCH 027/325] reformatter --- api/core/plugin/encrypt/__init__.py | 2 +- api/core/plugin/entities/request.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/api/core/plugin/encrypt/__init__.py b/api/core/plugin/encrypt/__init__.py index 5315780fce1222..614ce81d20c196 100644 --- a/api/core/plugin/encrypt/__init__.py +++ b/api/core/plugin/encrypt/__init__.py @@ -12,7 +12,7 @@ def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> Mappin encrypter = ProviderConfigEncrypter( tenant_id=tenant.id, config=payload.data, - provider_type=payload.type, + provider_type=payload.namespace, provider_identity=payload.identity, ) diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 9911ec9d85b4b5..78414e2aa59bc8 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -112,7 +112,7 @@ class RequestInvokeEncrypt(BaseModel): Request to encryption """ opt: Literal["encrypt", "decrypt"] - type: Literal["endpoint"] + namespace: Literal["endpoint"] identity: str data: dict = Field(default_factory=dict) config: Mapping[str, BasicProviderConfig] = Field(default_factory=Mapping) \ No newline at end of file From cf73374c1bc1509e1bbb75d8354a45f81a255620 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 10 Sep 2024 17:16:55 +0800 Subject: [PATCH 028/325] refactor: stream output --- api/core/workflow/nodes/tool/tool_node.py | 199 ++++++++++++---------- 1 file changed, 107 insertions(+), 92 deletions(-) diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index bb4649eaa4cb8f..3865695c71c448 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -1,6 +1,7 @@ -from collections.abc import Generator, Iterable, Sequence +from collections.abc import Generator, Iterable, Mapping, Sequence from os import path -from typing import Any, Mapping, cast +from typing import Any, cast +from urllib import response from core.app.segments import ArrayAnySegment, ArrayAnyVariable, parser from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler @@ -13,6 +14,7 @@ from core.workflow.entities.variable_pool import VariablePool from core.workflow.enums import SystemVariableKey from core.workflow.nodes.base_node import BaseNode +from core.workflow.nodes.event import RunCompletedEvent, RunEvent, RunStreamChunkEvent from core.workflow.nodes.tool.entities import ToolNodeData from core.workflow.utils.variable_template_parser import VariableTemplateParser from models import WorkflowNodeExecutionStatus @@ -26,7 +28,7 @@ class ToolNode(BaseNode): _node_data_cls = ToolNodeData _node_type = NodeType.TOOL - def _run(self) -> NodeRunResult: + def _run(self) -> Generator[RunEvent]: """ Run the tool node """ @@ -45,22 +47,34 @@ def _run(self) -> NodeRunResult: self.tenant_id, self.app_id, self.node_id, node_data, self.invoke_from ) except Exception as e: - return NodeRunResult( - status=WorkflowNodeExecutionStatus.FAILED, - inputs={}, - metadata={ - NodeRunMetadataKey.TOOL_INFO: tool_info - }, - error=f'Failed to get tool runtime: {str(e)}' + yield RunCompletedEvent( + run_result=NodeRunResult( + status=WorkflowNodeExecutionStatus.FAILED, + inputs={}, + metadata={ + NodeRunMetadataKey.TOOL_INFO: tool_info + }, + error=f'Failed to get tool runtime: {str(e)}' + ) ) + return # get parameters tool_parameters = tool_runtime.get_runtime_parameters() or [] - parameters = self._generate_parameters(tool_parameters=tool_parameters, variable_pool=self.graph_runtime_state.variable_pool, node_data=node_data) - parameters_for_log = self._generate_parameters(tool_parameters=tool_parameters, variable_pool=self.graph_runtime_state.variable_pool, node_data=node_data, for_log=True) + parameters = self._generate_parameters( + tool_parameters=tool_parameters, + variable_pool=self.graph_runtime_state.variable_pool, + node_data=node_data + ) + parameters_for_log = self._generate_parameters( + tool_parameters=tool_parameters, + variable_pool=self.graph_runtime_state.variable_pool, + node_data=node_data, + for_log=True + ) try: - messages = ToolEngine.workflow_invoke( + message_stream = ToolEngine.workflow_invoke( tool=tool_runtime, tool_parameters=parameters, user_id=self.user_id, @@ -69,30 +83,33 @@ def _run(self) -> NodeRunResult: thread_pool_id=self.thread_pool_id, ) except Exception as e: - return NodeRunResult( - status=WorkflowNodeExecutionStatus.FAILED, - inputs=parameters_for_log, - metadata={ - NodeRunMetadataKey.TOOL_INFO: tool_info - }, - error=f'Failed to invoke tool: {str(e)}', + yield RunCompletedEvent( + run_result=NodeRunResult( + status=WorkflowNodeExecutionStatus.FAILED, + inputs=parameters_for_log, + metadata={ + NodeRunMetadataKey.TOOL_INFO: tool_info + }, + error=f'Failed to invoke tool: {str(e)}', + ) ) + return # convert tool messages - plain_text, files, json = self._convert_tool_messages(messages) - - return NodeRunResult( - status=WorkflowNodeExecutionStatus.SUCCEEDED, - outputs={ - 'text': plain_text, - 'files': files, - 'json': json - }, - metadata={ - NodeRunMetadataKey.TOOL_INFO: tool_info - }, - inputs=parameters_for_log - ) + yield from self._transform_message(message_stream, tool_info, parameters_for_log) + + # return NodeRunResult( + # status=WorkflowNodeExecutionStatus.SUCCEEDED, + # outputs={ + # 'text': plain_text, + # 'files': files, + # 'json': json + # }, + # metadata={ + # NodeRunMetadataKey.TOOL_INFO: tool_info + # }, + # inputs=parameters_for_log + # ) def _generate_parameters( self, @@ -148,48 +165,40 @@ def _fetch_files(self, variable_pool: VariablePool) -> list[FileVar]: assert isinstance(variable, ArrayAnyVariable | ArrayAnySegment) return list(variable.value) if variable else [] - def _convert_tool_messages(self, messages: Generator[ToolInvokeMessage, None, None]): + def _transform_message(self, + messages: Generator[ToolInvokeMessage, None, None], + tool_info: Mapping[str, Any], + parameters_for_log: dict[str, Any]) -> Generator[RunEvent, None, None]: """ Convert ToolInvokeMessages into tuple[plain_text, files] """ # transform message and handle file storage - messages = ToolFileMessageTransformer.transform_tool_invoke_messages( + message_stream = ToolFileMessageTransformer.transform_tool_invoke_messages( messages=messages, user_id=self.user_id, tenant_id=self.tenant_id, conversation_id=None, ) - result = list(messages) - - # extract plain text and files - files = self._extract_tool_response_binary(result) - plain_text = self._extract_tool_response_text(result) - json = self._extract_tool_response_json(result) - - return plain_text, files, json - - def _extract_tool_response_binary(self, tool_response: Iterable[ToolInvokeMessage]) -> list[FileVar]: - """ - Extract tool response binary - """ - result = [] + files: list[FileVar] = [] + text = "" + json: list[dict] = [] - for response in tool_response: - if response.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \ - response.type == ToolInvokeMessage.MessageType.IMAGE: - assert isinstance(response.message, ToolInvokeMessage.TextMessage) - assert response.meta + for message in message_stream: + if message.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \ + message.type == ToolInvokeMessage.MessageType.IMAGE: + assert isinstance(message.message, ToolInvokeMessage.TextMessage) + assert message.meta - url = response.message.text + url = message.message.text ext = path.splitext(url)[1] - mimetype = response.meta.get('mime_type', 'image/jpeg') - filename = response.save_as or url.split('/')[-1] - transfer_method = response.meta.get('transfer_method', FileTransferMethod.TOOL_FILE) + mimetype = message.meta.get('mime_type', 'image/jpeg') + filename = message.save_as or url.split('/')[-1] + transfer_method = message.meta.get('transfer_method', FileTransferMethod.TOOL_FILE) # get tool file id tool_file_id = url.split('/')[-1].split('.')[0] - result.append(FileVar( + files.append(FileVar( tenant_id=self.tenant_id, type=FileType.IMAGE, transfer_method=transfer_method, @@ -199,48 +208,54 @@ def _extract_tool_response_binary(self, tool_response: Iterable[ToolInvokeMessag extension=ext, mime_type=mimetype, )) - elif response.type == ToolInvokeMessage.MessageType.BLOB: + elif message.type == ToolInvokeMessage.MessageType.BLOB: # get tool file id - assert isinstance(response.message, ToolInvokeMessage.TextMessage) - assert response.meta + assert isinstance(message.message, ToolInvokeMessage.TextMessage) + assert message.meta - tool_file_id = response.message.text.split('/')[-1].split('.')[0] - result.append(FileVar( + tool_file_id = message.message.text.split('/')[-1].split('.')[0] + files.append(FileVar( tenant_id=self.tenant_id, type=FileType.IMAGE, transfer_method=FileTransferMethod.TOOL_FILE, related_id=tool_file_id, - filename=response.save_as, - extension=path.splitext(response.save_as)[1], - mime_type=response.meta.get('mime_type', 'application/octet-stream'), + filename=message.save_as, + extension=path.splitext(message.save_as)[1], + mime_type=message.meta.get('mime_type', 'application/octet-stream'), )) - elif response.type == ToolInvokeMessage.MessageType.LINK: - pass # TODO: - - return result - - def _extract_tool_response_text(self, tool_response: Iterable[ToolInvokeMessage]) -> str: - """ - Extract tool response text - """ - result: list[str] = [] - for message in tool_response: - if message.type == ToolInvokeMessage.MessageType.TEXT: + elif message.type == ToolInvokeMessage.MessageType.TEXT: assert isinstance(message.message, ToolInvokeMessage.TextMessage) - result.append(message.message.text) + text += message.message.text + '\n' + yield RunStreamChunkEvent( + chunk_content=message.message.text, + from_variable_selector=[self.node_id, 'text'] + ) + elif message.type == ToolInvokeMessage.MessageType.JSON: + assert isinstance(message, ToolInvokeMessage.JsonMessage) + json.append(message.json_object) elif message.type == ToolInvokeMessage.MessageType.LINK: assert isinstance(message.message, ToolInvokeMessage.TextMessage) - result.append(f'Link: {message.message.text}') - - return '\n'.join(result) - - def _extract_tool_response_json(self, tool_response: Iterable[ToolInvokeMessage]) -> list[dict]: - result: list[dict] = [] - for message in tool_response: - if message.type == ToolInvokeMessage.MessageType.JSON: - assert isinstance(message, ToolInvokeMessage.JsonMessage) - result.append(message.json_object) - return result + stream_text = f'Link: {message.message.text}\n' + text += stream_text + yield RunStreamChunkEvent( + chunk_content=stream_text, + from_variable_selector=[self.node_id, 'text'] + ) + + yield RunCompletedEvent( + run_result=NodeRunResult( + status=WorkflowNodeExecutionStatus.SUCCEEDED, + outputs={ + 'text': text, + 'files': files, + 'json': json + }, + metadata={ + NodeRunMetadataKey.TOOL_INFO: tool_info + }, + inputs=parameters_for_log + ) + ) @classmethod def _extract_variable_selector_to_variable_mapping( From 70c001436e4513c38523537e334820d8089d0e7b Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 10 Sep 2024 18:13:33 +0800 Subject: [PATCH 029/325] support variable --- api/core/tools/entities/tool_entities.py | 44 +++++++++++++++++++++-- api/core/workflow/nodes/tool/tool_node.py | 38 +++++++++++--------- 2 files changed, 64 insertions(+), 18 deletions(-) diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 4b0961fb0999c9..ef96207fa73ee0 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -1,7 +1,8 @@ +import base64 from enum import Enum from typing import Any, Optional, Union, cast -from pydantic import BaseModel, Field, field_validator +from pydantic import BaseModel, Field, field_serializer, field_validator from core.entities.parameter_entities import AppSelectorScope, CommonParameterType, ModelConfigScope from core.tools.entities.common_entities import I18nObject @@ -100,6 +101,26 @@ class JsonMessage(BaseModel): class BlobMessage(BaseModel): blob: bytes + class VariableMessage(BaseModel): + variable_name: str = Field(..., description="The name of the variable") + variable_value: str = Field(..., description="The value of the variable") + stream: bool = Field(default=False, description="Whether the variable is streamed") + + @field_validator("variable_value", mode="before") + def transform_variable_value(cls, value, values) -> Any: + """ + Only basic types and lists are allowed. + """ + if not isinstance(value, dict | list | str | int | float | bool): + raise ValueError("Only basic types and lists are allowed.") + + # if stream is true, the value must be a string + if values.get('stream'): + if not isinstance(value, str): + raise ValueError("When 'stream' is True, 'variable_value' must be a string.") + + return value + class MessageType(Enum): TEXT = "text" IMAGE = "image" @@ -108,15 +129,34 @@ class MessageType(Enum): JSON = "json" IMAGE_LINK = "image_link" FILE_VAR = "file_var" + VARIABLE = "variable" type: MessageType = MessageType.TEXT """ plain text, image url or link url """ - message: JsonMessage | TextMessage | BlobMessage | None + message: JsonMessage | TextMessage | BlobMessage | VariableMessage | None meta: dict[str, Any] | None = None save_as: str = '' + @field_validator('message', mode='before') + @classmethod + def decode_blob_message(cls, v): + if isinstance(v, dict) and 'blob' in v: + try: + v['blob'] = base64.b64decode(v['blob']) + except Exception: + pass + return v + + @field_serializer('message') + def serialize_message(self, v): + if isinstance(v, self.BlobMessage): + return { + 'blob': base64.b64encode(v.blob).decode('utf-8') + } + return v + class ToolInvokeMessageBinary(BaseModel): mimetype: str = Field(..., description="The mimetype of the binary") url: str = Field(..., description="The url of the binary") diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index 3865695c71c448..1f32c7b8bd10c1 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -1,7 +1,6 @@ -from collections.abc import Generator, Iterable, Mapping, Sequence +from collections.abc import Generator, Mapping, Sequence from os import path from typing import Any, cast -from urllib import response from core.app.segments import ArrayAnySegment, ArrayAnyVariable, parser from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler @@ -98,19 +97,6 @@ def _run(self) -> Generator[RunEvent]: # convert tool messages yield from self._transform_message(message_stream, tool_info, parameters_for_log) - # return NodeRunResult( - # status=WorkflowNodeExecutionStatus.SUCCEEDED, - # outputs={ - # 'text': plain_text, - # 'files': files, - # 'json': json - # }, - # metadata={ - # NodeRunMetadataKey.TOOL_INFO: tool_info - # }, - # inputs=parameters_for_log - # ) - def _generate_parameters( self, *, @@ -183,6 +169,8 @@ def _transform_message(self, files: list[FileVar] = [] text = "" json: list[dict] = [] + + variables: dict[str, Any] = {} for message in message_stream: if message.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \ @@ -241,6 +229,23 @@ def _transform_message(self, chunk_content=stream_text, from_variable_selector=[self.node_id, 'text'] ) + elif message.type == ToolInvokeMessage.MessageType.VARIABLE: + assert isinstance(message.message, ToolInvokeMessage.VariableMessage) + variable_name = message.message.variable_name + variable_value = message.message.variable_value + if message.message.stream: + if not isinstance(variable_value, str): + raise ValueError("When 'stream' is True, 'variable_value' must be a string.") + if variable_name not in variables: + variables[variable_name] = "" + variables[variable_name] += variable_value + + yield RunStreamChunkEvent( + chunk_content=variable_value, + from_variable_selector=[self.node_id, variable_name] + ) + else: + variables[variable_name] = variable_value yield RunCompletedEvent( run_result=NodeRunResult( @@ -248,7 +253,8 @@ def _transform_message(self, outputs={ 'text': text, 'files': files, - 'json': json + 'json': json, + **variables }, metadata={ NodeRunMetadataKey.TOOL_INFO: tool_info From 87c746f6bbc66b2a7ae12d117c77d52b9838d305 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Sat, 14 Sep 2024 01:26:22 +0800 Subject: [PATCH 030/325] tmp --- api/core/tools/entities/tool_entities.py | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index ef96207fa73ee0..2f25898f4e94eb 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -120,6 +120,15 @@ def transform_variable_value(cls, value, values) -> Any: raise ValueError("When 'stream' is True, 'variable_value' must be a string.") return value + + @field_validator("variable_name", mode="before") + def transform_variable_name(cls, value) -> str: + """ + The variable name must be a string. + """ + if value in ["json", "text", "files"]: + raise ValueError(f"The variable name '{value}' is reserved.") + return value class MessageType(Enum): TEXT = "text" From c472ea6c67e43e1d4001b5aef0edab85d8d2af55 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 19 Sep 2024 18:02:24 +0800 Subject: [PATCH 031/325] fix: pydantic --- api/core/plugin/entities/request.py | 3 ++- api/core/tools/entities/tool_entities.py | 6 ++++-- api/core/tools/tool_engine.py | 5 ++--- 3 files changed, 8 insertions(+), 6 deletions(-) diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 627b3352251493..2e87b76636ca2d 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -42,7 +42,8 @@ class RequestInvokeLLM(BaseRequestInvokeModel): stream: Optional[bool] = False @field_validator("prompt_messages", mode="before") - def convert_prompt_messages(self, v): + @classmethod + def convert_prompt_messages(cls, v): if not isinstance(v, list): raise ValueError("prompt_messages must be a list") diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index b764ac62ecaf7b..d8383539bbaed7 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -114,7 +114,8 @@ class VariableMessage(BaseModel): stream: bool = Field(default=False, description="Whether the variable is streamed") @field_validator("variable_value", mode="before") - def transform_variable_value(self, value, values) -> Any: + @classmethod + def transform_variable_value(cls, value, values) -> Any: """ Only basic types and lists are allowed. """ @@ -129,7 +130,8 @@ def transform_variable_value(self, value, values) -> Any: return value @field_validator("variable_name", mode="before") - def transform_variable_name(self, value) -> str: + @classmethod + def transform_variable_name(cls, value) -> str: """ The variable name must be a string. """ diff --git a/api/core/tools/tool_engine.py b/api/core/tools/tool_engine.py index 8a4be51d285cfb..469eea67a6920d 100644 --- a/api/core/tools/tool_engine.py +++ b/api/core/tools/tool_engine.py @@ -245,9 +245,8 @@ def _convert_tool_response_to_str(tool_response: Generator[ToolInvokeMessage, No + "you do not need to create it, just tell the user to check it now." ) elif response.type == ToolInvokeMessage.MessageType.JSON: - result += f"tool response: { - json.dumps(cast(ToolInvokeMessage.JsonMessage, response.message).json_object, ensure_ascii=False) - }." + text = json.dumps(cast(ToolInvokeMessage.JsonMessage, response.message).json_object, ensure_ascii=False) + result += f"tool response: {text}." else: result += f"tool response: {response.message}." From 661392eaef8cec4171258dedcbe884be80f02db8 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 20 Sep 2024 02:25:14 +0800 Subject: [PATCH 032/325] refactor: tool --- api/core/agent/base_agent_runner.py | 4 +- api/core/agent/cot_agent_runner.py | 2 +- api/core/rag/retrieval/dataset_retrieval.py | 10 +- api/core/tools/{tool => __base}/tool.py | 0 .../{provider => __base}/tool_provider.py | 2 +- api/core/tools/builtin_tool/_position.yaml | 3 + .../provider.py} | 13 +- .../providers}/__init__.py | 0 .../providers}/_positions.py | 0 .../providers}/code/_assets/icon.svg | 0 .../providers}/code/code.py | 2 +- .../providers}/code/code.yaml | 0 .../providers}/code/tools/simple_code.py | 2 +- .../providers}/code/tools/simple_code.yaml | 0 .../providers}/qrcode/_assets/icon.svg | 0 .../providers}/qrcode/qrcode.py | 4 +- .../providers}/qrcode/qrcode.yaml | 0 .../qrcode/tools/qrcode_generator.py | 2 +- .../qrcode/tools/qrcode_generator.yaml | 0 .../providers}/time/_assets/icon.svg | 0 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api/core/tools/provider/builtin/youtube/_assets/icon.svg delete mode 100644 api/core/tools/provider/builtin/youtube/tools/videos.py delete mode 100644 api/core/tools/provider/builtin/youtube/tools/videos.yaml delete mode 100644 api/core/tools/provider/builtin/youtube/youtube.py delete mode 100644 api/core/tools/provider/builtin/youtube/youtube.yaml rename api/core/tools/{tool => utils}/dataset_retriever/dataset_multi_retriever_tool.py (98%) rename api/core/tools/{tool => utils}/dataset_retriever/dataset_retriever_base_tool.py (100%) rename api/core/tools/{tool => utils}/dataset_retriever/dataset_retriever_tool.py (100%) rename api/core/tools/{tool => utils}/dataset_retriever_tool.py (96%) create mode 100644 api/core/tools/workflow_as_tool/provider.py rename api/core/tools/{tool/workflow_tool.py => workflow_as_tool/tool.py} (99%) rename api/core/tools/{provider => workflow_as_tool}/workflow_tool_provider.py (98%) diff --git a/api/core/agent/base_agent_runner.py b/api/core/agent/base_agent_runner.py index d09a9956a4a591..55fd8825de6909 100644 --- a/api/core/agent/base_agent_runner.py +++ b/api/core/agent/base_agent_runner.py @@ -32,13 +32,13 @@ from core.model_runtime.entities.model_entities import ModelFeature from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel from core.model_runtime.utils.encoders import jsonable_encoder +from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ( ToolParameter, ToolRuntimeVariablePool, ) -from core.tools.tool.dataset_retriever_tool import DatasetRetrieverTool -from core.tools.tool.tool import Tool from core.tools.tool_manager import ToolManager +from core.tools.utils.dataset_retriever_tool import DatasetRetrieverTool from core.tools.utils.tool_parameter_converter import ToolParameterConverter from extensions.ext_database import db from models.model import Conversation, Message, MessageAgentThought diff --git a/api/core/agent/cot_agent_runner.py b/api/core/agent/cot_agent_runner.py index ebe04bf26000f1..0d74b1e5ebe933 100644 --- a/api/core/agent/cot_agent_runner.py +++ b/api/core/agent/cot_agent_runner.py @@ -17,8 +17,8 @@ ) from core.ops.ops_trace_manager import TraceQueueManager from core.prompt.agent_history_prompt_transform import AgentHistoryPromptTransform +from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ToolInvokeMeta -from core.tools.tool.tool import Tool from core.tools.tool_engine import ToolEngine from models.model import Message diff --git a/api/core/rag/retrieval/dataset_retrieval.py b/api/core/rag/retrieval/dataset_retrieval.py index 286ecd4c036841..05f6fe6e269c8e 100644 --- a/api/core/rag/retrieval/dataset_retrieval.py +++ b/api/core/rag/retrieval/dataset_retrieval.py @@ -24,9 +24,7 @@ from core.rag.retrieval.retrieval_methods import RetrievalMethod from core.rag.retrieval.router.multi_dataset_function_call_router import FunctionCallMultiDatasetRouter from core.rag.retrieval.router.multi_dataset_react_route import ReactMultiDatasetRouter -from core.tools.tool.dataset_retriever.dataset_multi_retriever_tool import DatasetMultiRetrieverTool -from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool -from core.tools.tool.dataset_retriever.dataset_retriever_tool import DatasetRetrieverTool +from core.tools.utils.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool from extensions.ext_database import db from models.dataset import Dataset, DatasetQuery, DocumentSegment from models.dataset import Document as DatasetDocument @@ -371,7 +369,7 @@ def _on_retrieval_end( db.session.commit() # get tracing instance - trace_manager: TraceQueueManager = ( + trace_manager: TraceQueueManager | None = ( self.application_generate_entity.trace_manager if self.application_generate_entity else None ) if trace_manager: @@ -494,7 +492,8 @@ def to_dataset_retriever_tool( score_threshold_enabled = retrieval_model_config.get("score_threshold_enabled") if score_threshold_enabled: score_threshold = retrieval_model_config.get("score_threshold") - + + from core.tools.utils.dataset_retriever.dataset_retriever_tool import DatasetRetrieverTool tool = DatasetRetrieverTool.from_dataset( dataset=dataset, top_k=top_k, @@ -506,6 +505,7 @@ def to_dataset_retriever_tool( tools.append(tool) elif retrieve_config.retrieve_strategy == DatasetRetrieveConfigEntity.RetrieveStrategy.MULTIPLE: + from core.tools.utils.dataset_retriever.dataset_multi_retriever_tool import DatasetMultiRetrieverTool tool = DatasetMultiRetrieverTool.from_dataset( dataset_ids=[dataset.id for dataset in available_datasets], tenant_id=tenant_id, diff --git a/api/core/tools/tool/tool.py b/api/core/tools/__base/tool.py similarity index 100% rename from api/core/tools/tool/tool.py rename to api/core/tools/__base/tool.py diff --git a/api/core/tools/provider/tool_provider.py b/api/core/tools/__base/tool_provider.py similarity index 99% rename from api/core/tools/provider/tool_provider.py rename to api/core/tools/__base/tool_provider.py index f07af649ad055d..7960ed5f84d5dc 100644 --- a/api/core/tools/provider/tool_provider.py +++ b/api/core/tools/__base/tool_provider.py @@ -4,12 +4,12 @@ from pydantic import BaseModel, ConfigDict, Field from core.entities.provider_entities import ProviderConfig +from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ( ToolProviderIdentity, ToolProviderType, ) from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.tool.tool import Tool class ToolProviderController(BaseModel, ABC): diff --git a/api/core/tools/builtin_tool/_position.yaml b/api/core/tools/builtin_tool/_position.yaml new file mode 100644 index 00000000000000..b5875e20759163 --- /dev/null +++ b/api/core/tools/builtin_tool/_position.yaml @@ -0,0 +1,3 @@ +- code +- time +- qrcode diff --git a/api/core/tools/provider/builtin_tool_provider.py b/api/core/tools/builtin_tool/provider.py similarity index 92% rename from api/core/tools/provider/builtin_tool_provider.py rename to api/core/tools/builtin_tool/provider.py index 2a966d3999adde..7d1775b7f561fa 100644 --- a/api/core/tools/provider/builtin_tool_provider.py +++ b/api/core/tools/builtin_tool/provider.py @@ -6,13 +6,13 @@ from core.entities.provider_entities import ProviderConfig from core.helper.module_import_helper import load_single_subclass_from_source +from core.tools.__base.tool_provider import ToolProviderController +from core.tools.builtin_tool.tool import BuiltinTool from core.tools.entities.tool_entities import ToolProviderType from core.tools.entities.values import ToolLabelEnum, default_tool_label_dict from core.tools.errors import ( ToolProviderNotFoundError, ) -from core.tools.provider.tool_provider import ToolProviderController -from core.tools.tool.builtin_tool import BuiltinTool from core.tools.utils.yaml_utils import load_yaml_file @@ -26,7 +26,7 @@ def __init__(self, **data: Any) -> None: # load provider yaml provider = self.__class__.__module__.split(".")[-1] - yaml_path = path.join(path.dirname(path.realpath(__file__)), "builtin", provider, f"{provider}.yaml") + yaml_path = path.join(path.dirname(path.realpath(__file__)), "providers", provider, f"{provider}.yaml") try: provider_yaml = load_yaml_file(yaml_path, ignore_error=False) except Exception as e: @@ -52,7 +52,7 @@ def _get_builtin_tools(self) -> list[BuiltinTool]: return self.tools provider = self.identity.name - tool_path = path.join(path.dirname(path.realpath(__file__)), "builtin", provider, "tools") + tool_path = path.join(path.dirname(path.realpath(__file__)), "providers", provider, "tools") # get all the yaml files in the tool path tool_files = list(filter(lambda x: x.endswith(".yaml") and not x.startswith("__"), listdir(tool_path))) tools = [] @@ -63,9 +63,10 @@ def _get_builtin_tools(self) -> list[BuiltinTool]: # get tool class, import the module assistant_tool_class = load_single_subclass_from_source( - module_name=f"core.tools.provider.builtin.{provider}.tools.{tool_name}", + module_name=f"core.tools.builtin_tool.providers.{provider}.tools.{tool_name}", script_path=path.join( - path.dirname(path.realpath(__file__)), "builtin", provider, "tools", f"{tool_name}.py" + path.dirname(path.realpath(__file__)), + "builtin_tool", "providers", provider, "tools", f"{tool_name}.py" ), parent_type=BuiltinTool, ) diff --git a/api/core/tools/provider/builtin/__init__.py b/api/core/tools/builtin_tool/providers/__init__.py similarity index 100% rename from api/core/tools/provider/builtin/__init__.py rename to api/core/tools/builtin_tool/providers/__init__.py diff --git a/api/core/tools/provider/builtin/_positions.py b/api/core/tools/builtin_tool/providers/_positions.py similarity index 100% rename from api/core/tools/provider/builtin/_positions.py rename to api/core/tools/builtin_tool/providers/_positions.py diff --git a/api/core/tools/provider/builtin/code/_assets/icon.svg b/api/core/tools/builtin_tool/providers/code/_assets/icon.svg similarity index 100% rename from api/core/tools/provider/builtin/code/_assets/icon.svg rename to api/core/tools/builtin_tool/providers/code/_assets/icon.svg diff --git a/api/core/tools/provider/builtin/code/code.py b/api/core/tools/builtin_tool/providers/code/code.py similarity index 66% rename from api/core/tools/provider/builtin/code/code.py rename to api/core/tools/builtin_tool/providers/code/code.py index 211417c9a431ed..53210e9c439cb6 100644 --- a/api/core/tools/provider/builtin/code/code.py +++ b/api/core/tools/builtin_tool/providers/code/code.py @@ -1,6 +1,6 @@ from typing import Any -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController +from core.tools.builtin_tool.provider import BuiltinToolProviderController class CodeToolProvider(BuiltinToolProviderController): diff --git a/api/core/tools/provider/builtin/code/code.yaml b/api/core/tools/builtin_tool/providers/code/code.yaml similarity index 100% rename from api/core/tools/provider/builtin/code/code.yaml rename to api/core/tools/builtin_tool/providers/code/code.yaml diff --git a/api/core/tools/provider/builtin/code/tools/simple_code.py b/api/core/tools/builtin_tool/providers/code/tools/simple_code.py similarity index 93% rename from api/core/tools/provider/builtin/code/tools/simple_code.py rename to api/core/tools/builtin_tool/providers/code/tools/simple_code.py index 632c9fc7f1451b..14ff1969ff2b4d 100644 --- a/api/core/tools/provider/builtin/code/tools/simple_code.py +++ b/api/core/tools/builtin_tool/providers/code/tools/simple_code.py @@ -1,8 +1,8 @@ from typing import Any from core.helper.code_executor.code_executor import CodeExecutor, CodeLanguage +from core.tools.builtin_tool.tool import BuiltinTool from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool class SimpleCode(BuiltinTool): diff --git a/api/core/tools/provider/builtin/code/tools/simple_code.yaml b/api/core/tools/builtin_tool/providers/code/tools/simple_code.yaml similarity index 100% rename from api/core/tools/provider/builtin/code/tools/simple_code.yaml rename to api/core/tools/builtin_tool/providers/code/tools/simple_code.yaml diff --git a/api/core/tools/provider/builtin/qrcode/_assets/icon.svg b/api/core/tools/builtin_tool/providers/qrcode/_assets/icon.svg similarity index 100% rename from api/core/tools/provider/builtin/qrcode/_assets/icon.svg rename to api/core/tools/builtin_tool/providers/qrcode/_assets/icon.svg diff --git a/api/core/tools/provider/builtin/qrcode/qrcode.py b/api/core/tools/builtin_tool/providers/qrcode/qrcode.py similarity index 71% rename from api/core/tools/provider/builtin/qrcode/qrcode.py rename to api/core/tools/builtin_tool/providers/qrcode/qrcode.py index 8466b9a26b42b6..542ee7b63e9e09 100644 --- a/api/core/tools/provider/builtin/qrcode/qrcode.py +++ b/api/core/tools/builtin_tool/providers/qrcode/qrcode.py @@ -1,8 +1,8 @@ from typing import Any +from core.tools.builtin_tool.provider import BuiltinToolProviderController +from core.tools.builtin_tool.providers.qrcode.tools.qrcode_generator import QRCodeGeneratorTool from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.qrcode.tools.qrcode_generator import QRCodeGeneratorTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController class QRCodeProvider(BuiltinToolProviderController): diff --git a/api/core/tools/provider/builtin/qrcode/qrcode.yaml b/api/core/tools/builtin_tool/providers/qrcode/qrcode.yaml similarity index 100% rename from api/core/tools/provider/builtin/qrcode/qrcode.yaml rename to api/core/tools/builtin_tool/providers/qrcode/qrcode.yaml diff --git a/api/core/tools/provider/builtin/qrcode/tools/qrcode_generator.py b/api/core/tools/builtin_tool/providers/qrcode/tools/qrcode_generator.py similarity index 97% rename from api/core/tools/provider/builtin/qrcode/tools/qrcode_generator.py rename to api/core/tools/builtin_tool/providers/qrcode/tools/qrcode_generator.py index d8ca20bde6ffc9..081ad30231f88e 100644 --- a/api/core/tools/provider/builtin/qrcode/tools/qrcode_generator.py +++ b/api/core/tools/builtin_tool/providers/qrcode/tools/qrcode_generator.py @@ -7,8 +7,8 @@ from qrcode.image.pure import PyPNGImage from qrcode.main import QRCode +from core.tools.builtin_tool.tool import BuiltinTool from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool class QRCodeGeneratorTool(BuiltinTool): diff --git a/api/core/tools/provider/builtin/qrcode/tools/qrcode_generator.yaml b/api/core/tools/builtin_tool/providers/qrcode/tools/qrcode_generator.yaml similarity index 100% rename from api/core/tools/provider/builtin/qrcode/tools/qrcode_generator.yaml rename to api/core/tools/builtin_tool/providers/qrcode/tools/qrcode_generator.yaml diff --git a/api/core/tools/provider/builtin/time/_assets/icon.svg b/api/core/tools/builtin_tool/providers/time/_assets/icon.svg similarity index 100% rename from api/core/tools/provider/builtin/time/_assets/icon.svg rename to api/core/tools/builtin_tool/providers/time/_assets/icon.svg diff --git a/api/core/tools/provider/builtin/time/time.py b/api/core/tools/builtin_tool/providers/time/time.py similarity index 73% rename from api/core/tools/provider/builtin/time/time.py rename to api/core/tools/builtin_tool/providers/time/time.py index e4df8d616cba38..234ca9d9d6389b 100644 --- a/api/core/tools/provider/builtin/time/time.py +++ b/api/core/tools/builtin_tool/providers/time/time.py @@ -1,8 +1,8 @@ from typing import Any +from core.tools.builtin_tool.provider import BuiltinToolProviderController +from core.tools.builtin_tool.providers.time.tools.current_time import CurrentTimeTool from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.time.tools.current_time import CurrentTimeTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController class WikiPediaProvider(BuiltinToolProviderController): diff --git a/api/core/tools/provider/builtin/time/time.yaml b/api/core/tools/builtin_tool/providers/time/time.yaml similarity index 100% rename from api/core/tools/provider/builtin/time/time.yaml rename to api/core/tools/builtin_tool/providers/time/time.yaml diff --git a/api/core/tools/provider/builtin/time/tools/current_time.py b/api/core/tools/builtin_tool/providers/time/tools/current_time.py similarity index 94% rename from api/core/tools/provider/builtin/time/tools/current_time.py rename to api/core/tools/builtin_tool/providers/time/tools/current_time.py index cc38739c16f04b..a403c4929651e0 100644 --- a/api/core/tools/provider/builtin/time/tools/current_time.py +++ b/api/core/tools/builtin_tool/providers/time/tools/current_time.py @@ -3,8 +3,8 @@ from pytz import timezone as pytz_timezone +from core.tools.builtin_tool.tool import BuiltinTool from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool class CurrentTimeTool(BuiltinTool): diff --git a/api/core/tools/provider/builtin/time/tools/current_time.yaml b/api/core/tools/builtin_tool/providers/time/tools/current_time.yaml similarity index 100% rename from api/core/tools/provider/builtin/time/tools/current_time.yaml rename to api/core/tools/builtin_tool/providers/time/tools/current_time.yaml diff --git a/api/core/tools/provider/builtin/time/tools/weekday.py b/api/core/tools/builtin_tool/providers/time/tools/weekday.py similarity index 91% rename from api/core/tools/provider/builtin/time/tools/weekday.py rename to api/core/tools/builtin_tool/providers/time/tools/weekday.py index b327e54e171048..570ab624133d2d 100644 --- a/api/core/tools/provider/builtin/time/tools/weekday.py +++ b/api/core/tools/builtin_tool/providers/time/tools/weekday.py @@ -2,8 +2,8 @@ from datetime import datetime from typing import Any, Union +from core.tools.builtin_tool.tool import BuiltinTool from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool class WeekdayTool(BuiltinTool): @@ -17,6 +17,8 @@ def _invoke( """ year = tool_parameters.get("year") month = tool_parameters.get("month") + if month is None: + raise ValueError("Month is required") day = tool_parameters.get("day") date_obj = self.convert_datetime(year, month, day) diff --git a/api/core/tools/provider/builtin/time/tools/weekday.yaml b/api/core/tools/builtin_tool/providers/time/tools/weekday.yaml similarity index 100% rename from api/core/tools/provider/builtin/time/tools/weekday.yaml rename to api/core/tools/builtin_tool/providers/time/tools/weekday.yaml diff --git a/api/core/tools/tool/builtin_tool.py b/api/core/tools/builtin_tool/tool.py similarity index 96% rename from api/core/tools/tool/builtin_tool.py rename to api/core/tools/builtin_tool/tool.py index 8edaf7c0e6a5f5..243d99dee3f36c 100644 --- a/api/core/tools/tool/builtin_tool.py +++ b/api/core/tools/builtin_tool/tool.py @@ -1,7 +1,7 @@ from core.model_runtime.entities.llm_entities import LLMResult from core.model_runtime.entities.message_entities import PromptMessage, SystemPromptMessage, UserPromptMessage +from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ToolProviderType -from core.tools.tool.tool import Tool from core.tools.utils.model_invocation_utils import ModelInvocationUtils from core.tools.utils.web_reader_tool import get_url @@ -32,7 +32,7 @@ def invoke_model(self, user_id: str, prompt_messages: list[PromptMessage], stop: # invoke model return ModelInvocationUtils.invoke( user_id=user_id, - tenant_id=self.runtime.tenant_id, + tenant_id=self.runtime.tenant_id or "", tool_type="builtin", tool_name=self.identity.name, prompt_messages=prompt_messages, @@ -124,7 +124,7 @@ def summarize(content: str) -> str: return result - def get_url(self, url: str, user_agent: str = None) -> str: + def get_url(self, url: str, user_agent: str | None = None) -> str: """ get url """ diff --git a/api/core/tools/provider/api_tool_provider.py b/api/core/tools/custom_tool/provider.py similarity index 97% rename from api/core/tools/provider/api_tool_provider.py rename to api/core/tools/custom_tool/provider.py index 307cc0a0d957e6..7ebaa6c5c6fc29 100644 --- a/api/core/tools/provider/api_tool_provider.py +++ b/api/core/tools/custom_tool/provider.py @@ -1,14 +1,14 @@ from pydantic import Field from core.entities.provider_entities import ProviderConfig +from core.tools.__base.tool_provider import ToolProviderController +from core.tools.custom_tool.tool import ApiTool from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( ApiProviderAuthType, ToolProviderType, ) -from core.tools.provider.tool_provider import ToolProviderController -from core.tools.tool.api_tool import ApiTool from extensions.ext_database import db from models.tools import ApiToolProvider @@ -67,7 +67,8 @@ def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> "Ap else: raise ValueError(f"invalid auth type {auth_type}") - user_name = db_provider.user.name if db_provider.user_id else "" + user = db_provider.user + user_name = user.name if user else "" return ApiToolProviderController( **{ diff --git a/api/core/tools/tool/api_tool.py b/api/core/tools/custom_tool/tool.py similarity index 96% rename from api/core/tools/tool/api_tool.py rename to api/core/tools/custom_tool/tool.py index 87f2514ce2a514..9a728bb684b664 100644 --- a/api/core/tools/tool/api_tool.py +++ b/api/core/tools/custom_tool/tool.py @@ -7,10 +7,10 @@ import httpx from core.helper import ssrf_proxy +from core.tools.__base.tool import Tool from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ToolInvokeMessage, ToolProviderType from core.tools.errors import ToolInvokeError, ToolParameterValidationError, ToolProviderCredentialValidationError -from core.tools.tool.tool import Tool API_TOOL_DEFAULT_TIMEOUT = ( int(getenv("API_TOOL_DEFAULT_CONNECT_TIMEOUT", "10")), @@ -33,10 +33,10 @@ def fork_tool_runtime(self, runtime: dict[str, Any]) -> "Tool": :return: the new tool """ return self.__class__( - identity=self.identity.model_copy() if self.identity else None, - parameters=self.parameters.copy() if self.parameters else None, + identity=self.identity.model_copy(), + parameters=self.parameters.copy() if self.parameters else [], description=self.description.model_copy() if self.description else None, - api_bundle=self.api_bundle.model_copy() if self.api_bundle else None, + api_bundle=self.api_bundle.model_copy(), runtime=Tool.Runtime(**runtime), ) @@ -60,6 +60,9 @@ def tool_provider_type(self) -> ToolProviderType: return ToolProviderType.API def assembling_request(self, parameters: dict[str, Any]) -> dict[str, Any]: + if self.runtime == None: + raise ToolProviderCredentialValidationError("runtime not initialized") + headers = {} credentials = self.runtime.credentials or {} @@ -88,7 +91,7 @@ def assembling_request(self, parameters: dict[str, Any]) -> dict[str, Any]: headers[api_key_header] = credentials["api_key_value"] - needed_parameters = [parameter for parameter in self.api_bundle.parameters if parameter.required] + needed_parameters = [parameter for parameter in (self.api_bundle.parameters or []) if parameter.required] for parameter in needed_parameters: if parameter.required and parameter.name not in parameters: raise ToolParameterValidationError(f"Missing required parameter {parameter.name}") @@ -204,7 +207,7 @@ def do_http_request( ) return response else: - raise ValueError(f"Invalid http method {self.method}") + raise ValueError(f"Invalid http method {method}") def _convert_body_property_any_of( self, property: dict[str, Any], value: Any, any_of: list[dict[str, Any]], max_recursive=10 diff --git a/api/core/tools/entities/api_entities.py b/api/core/tools/entities/api_entities.py index ae84338cdc6958..b3a98b4a6dcf79 100644 --- a/api/core/tools/entities/api_entities.py +++ b/api/core/tools/entities/api_entities.py @@ -4,9 +4,9 @@ from core.entities.provider_entities import ProviderConfig from core.model_runtime.utils.encoders import jsonable_encoder +from core.tools.__base.tool import ToolParameter from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ToolProviderType -from core.tools.tool.tool import ToolParameter class UserTool(BaseModel): diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index d8383539bbaed7..cc84f6eaada186 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -32,6 +32,7 @@ class ToolProviderType(str, Enum): Enum class for tool provider """ + PLUGIN = "plugin" BUILT_IN = "builtin" WORKFLOW = "workflow" API = "api" diff --git a/api/core/tools/plugin_tool/plugin_tool_provider.py b/api/core/tools/plugin_tool/plugin_tool_provider.py new file mode 100644 index 00000000000000..47a78ee3183fda --- /dev/null +++ b/api/core/tools/plugin_tool/plugin_tool_provider.py @@ -0,0 +1,30 @@ + + +from core.entities.provider_entities import ProviderConfig +from core.tools.__base.tool import Tool +from core.tools.__base.tool_provider import ToolProviderController +from core.tools.entities.tool_entities import ToolProviderType + + +class PluginToolProvider(ToolProviderController): + @property + def provider_type(self) -> ToolProviderType: + """ + returns the type of the provider + + :return: type of the provider + """ + return ToolProviderType.PLUGIN + + def get_tool(self, tool_name: str) -> Tool: + """ + return tool with given name + """ + return super().get_tool(tool_name) + + def get_credentials_schema(self) -> dict[str, ProviderConfig]: + """ + get credentials schema + """ + return super().get_credentials_schema() + \ No newline at end of file diff --git a/api/core/tools/provider/_position.yaml b/api/core/tools/provider/_position.yaml deleted file mode 100644 index 40c3356116770b..00000000000000 --- a/api/core/tools/provider/_position.yaml +++ /dev/null @@ -1,38 +0,0 @@ -- google -- bing -- perplexity -- duckduckgo -- searchapi -- serper -- searxng -- dalle -- azuredalle -- stability -- wikipedia -- nominatim -- yahoo -- alphavantage -- arxiv -- pubmed -- stablediffusion -- webscraper -- jina -- aippt -- youtube -- code -- wolframalpha -- maths -- github -- chart -- time -- vectorizer -- gaode -- wecom -- qrcode -- dingtalk -- feishu -- feishu_base -- feishu_document -- feishu_message -- slack -- tianditu diff --git a/api/core/tools/provider/app_tool_provider.py b/api/core/tools/provider/app_tool_provider.py deleted file mode 100644 index 09f328cd1fe65f..00000000000000 --- a/api/core/tools/provider/app_tool_provider.py +++ /dev/null @@ -1,103 +0,0 @@ -import logging -from typing import Any - -from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ToolParameter, ToolParameterOption, ToolProviderType -from core.tools.provider.tool_provider import ToolProviderController -from core.tools.tool.tool import Tool -from extensions.ext_database import db -from models.model import App, AppModelConfig -from models.tools import PublishedAppTool - -logger = logging.getLogger(__name__) - - -class AppToolProviderEntity(ToolProviderController): - @property - def provider_type(self) -> ToolProviderType: - return ToolProviderType.APP - - def _validate_credentials(self, tool_name: str, credentials: dict[str, Any]) -> None: - pass - - def validate_parameters(self, tool_name: str, tool_parameters: dict[str, Any]) -> None: - pass - - def get_tools(self, user_id: str) -> list[Tool]: - db_tools: list[PublishedAppTool] = ( - db.session.query(PublishedAppTool) - .filter( - PublishedAppTool.user_id == user_id, - ) - .all() - ) - - if not db_tools or len(db_tools) == 0: - return [] - - tools: list[Tool] = [] - - for db_tool in db_tools: - tool = { - "identity": { - "author": db_tool.author, - "name": db_tool.tool_name, - "label": {"en_US": db_tool.tool_name, "zh_Hans": db_tool.tool_name}, - "icon": "", - }, - "description": { - "human": {"en_US": db_tool.description_i18n.en_US, "zh_Hans": db_tool.description_i18n.zh_Hans}, - "llm": db_tool.llm_description, - }, - "parameters": [], - } - # get app from db - app: App = db_tool.app - - if not app: - logger.error(f"app {db_tool.app_id} not found") - continue - - app_model_config: AppModelConfig = app.app_model_config - user_input_form_list = app_model_config.user_input_form_list - for input_form in user_input_form_list: - # get type - form_type = input_form.keys()[0] - default = input_form[form_type]["default"] - required = input_form[form_type]["required"] - label = input_form[form_type]["label"] - variable_name = input_form[form_type]["variable_name"] - options = input_form[form_type].get("options", []) - if form_type in {"paragraph", "text-input"}: - tool["parameters"].append( - ToolParameter( - name=variable_name, - label=I18nObject(en_US=label, zh_Hans=label), - human_description=I18nObject(en_US=label, zh_Hans=label), - llm_description=label, - form=ToolParameter.ToolParameterForm.FORM, - type=ToolParameter.ToolParameterType.STRING, - required=required, - default=default, - ) - ) - elif form_type == "select": - tool["parameters"].append( - ToolParameter( - name=variable_name, - label=I18nObject(en_US=label, zh_Hans=label), - human_description=I18nObject(en_US=label, zh_Hans=label), - llm_description=label, - form=ToolParameter.ToolParameterForm.FORM, - type=ToolParameter.ToolParameterType.SELECT, - required=required, - default=default, - options=[ - ToolParameterOption(value=option, label=I18nObject(en_US=option, zh_Hans=option)) - for option in options - ], - ) - ) - - tools.append(Tool(**tool)) - return tools diff --git a/api/core/tools/provider/builtin/aippt/_assets/icon.png b/api/core/tools/provider/builtin/aippt/_assets/icon.png deleted file mode 100644 index b70618b4878984f88dd1991a64cc69bc0afeaaa8..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1961 zcmV;a2UhrrP)}be?ilJh^tl7C04E7Km3nmuE)r9#}WA}rRl?ISYbedqU*T|WL)~Yw( zP?|Jh;?dp!(3&jVCkLS8&FUWaO>-bs*(NZtmjFC017KdFu(8U=ed`$sqx}y-6ABrr zGa%WqqYeovwib-*3jm<3Sy=1}AX(UyH4hD|O7k_sW`b#b2>_H$wBI7k-Ykyv)Bg@RW?`53 zId_Ix99W&^*D=E&>{#Uh$ZKx=*zkGdPc-Ec?Ia`?YN2WsA!HC$`4%v&A^=eCiYRQE zoUwc-%#sj55az4wR$5L9E#_ z=Ibgu5R0WoKwAXhQ@Y+9rz$%xH=AKC&=vvsHs8KV7_&`o+_#rQTLchHs$qqc`HJ;@ zG@7{*0R*53vF?$a@%*LNr{d7Id;rZ61Rz9d^C&~*2c!THJ{#KViZxv)a9`M34I#F_ 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b/api/core/tools/provider/builtin/aippt/aippt.py deleted file mode 100644 index e0cbbd2992a515..00000000000000 --- a/api/core/tools/provider/builtin/aippt/aippt.py +++ /dev/null @@ -1,11 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.aippt.tools.aippt import AIPPTGenerateTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class AIPPTProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - AIPPTGenerateTool._get_api_token(credentials, user_id="__dify_system__") - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/aippt/aippt.yaml b/api/core/tools/provider/builtin/aippt/aippt.yaml deleted file mode 100644 index 9b1b45d0f21a73..00000000000000 --- a/api/core/tools/provider/builtin/aippt/aippt.yaml +++ /dev/null @@ -1,45 +0,0 @@ -identity: - author: Dify - name: aippt - label: - en_US: AIPPT - zh_Hans: AIPPT - description: - en_US: AI-generated PPT with one click, input your content topic, and let AI serve you one-stop - zh_Hans: AI一键生成PPT，输入你的内容主题，让AI为你一站式服务到底 - icon: icon.png - tags: - - productivity - - design -credentials_for_provider: - aippt_access_key: - type: secret-input - required: true - label: - en_US: AIPPT API key - zh_Hans: AIPPT API key - pt_BR: AIPPT API key - help: - en_US: Please input your AIPPT API key - zh_Hans: 请输入你的 AIPPT API key - pt_BR: Please input your AIPPT API key - placeholder: - en_US: Please input your AIPPT API key - zh_Hans: 请输入你的 AIPPT API key - pt_BR: Please input your AIPPT API key - url: https://www.aippt.cn - aippt_secret_key: - type: secret-input - required: true - label: - en_US: AIPPT Secret key - zh_Hans: AIPPT Secret key - pt_BR: AIPPT Secret key - help: - en_US: Please input your AIPPT Secret key - zh_Hans: 请输入你的 AIPPT Secret key - pt_BR: Please input your AIPPT Secret key - placeholder: - en_US: Please input your AIPPT Secret key - zh_Hans: 请输入你的 AIPPT Secret key - pt_BR: Please input your AIPPT Secret key diff --git a/api/core/tools/provider/builtin/aippt/tools/aippt.py b/api/core/tools/provider/builtin/aippt/tools/aippt.py deleted file mode 100644 index dd9371f70d63f5..00000000000000 --- a/api/core/tools/provider/builtin/aippt/tools/aippt.py +++ /dev/null @@ -1,498 +0,0 @@ -from base64 import b64encode -from hashlib import sha1 -from hmac import new as hmac_new -from json import loads as json_loads -from threading import Lock -from time import sleep, time -from typing import Any, Optional - -from httpx import get, post -from requests import get as requests_get -from yarl import URL - -from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter, ToolParameterOption -from core.tools.tool.builtin_tool import BuiltinTool - - -class AIPPTGenerateTool(BuiltinTool): - """ - A tool for generating a ppt - """ - - _api_base_url = URL("https://co.aippt.cn/api") - _api_token_cache = {} - _api_token_cache_lock: Optional[Lock] = None - _style_cache = {} - _style_cache_lock: Optional[Lock] = None - - _task = {} - _task_type_map = { - "auto": 1, - "markdown": 7, - } - - def __init__(self, **kwargs: Any): - super().__init__(**kwargs) - self._api_token_cache_lock = Lock() - self._style_cache_lock = Lock() - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: - """ - Invokes the AIPPT generate tool with the given user ID and tool parameters. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Any]): The parameters for the tool - - Returns: - ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation, - which can be a single message or a list of messages. - """ - title = tool_parameters.get("title", "") - if not title: - return self.create_text_message("Please provide a title for the ppt") - - model = tool_parameters.get("model", "aippt") - if not model: - return self.create_text_message("Please provide a model for the ppt") - - outline = tool_parameters.get("outline", "") - - # create task - task_id = self._create_task( - type=self._task_type_map["auto" if not outline else "markdown"], - title=title, - content=outline, - user_id=user_id, - ) - - # get suit - color = tool_parameters.get("color") - style = tool_parameters.get("style") - - if color == "__default__": - color_id = "" - else: - color_id = int(color.split("-")[1]) - - if style == "__default__": - style_id = "" - else: - style_id = int(style.split("-")[1]) - - suit_id = self._get_suit(style_id=style_id, colour_id=color_id) - - # generate outline - if not outline: - self._generate_outline(task_id=task_id, model=model, user_id=user_id) - - # generate content - self._generate_content(task_id=task_id, model=model, user_id=user_id) - - # generate ppt - _, ppt_url = self._generate_ppt(task_id=task_id, suit_id=suit_id, user_id=user_id) - - return self.create_text_message( - """the ppt has been created successfully,""" - f"""the ppt url is {ppt_url}""" - """please give the ppt url to user and direct user to download it.""" - ) - - def _create_task(self, type: int, title: str, content: str, user_id: str) -> str: - """ - Create a task - - :param type: the task type - :param title: the task title - :param content: the task content - - :return: the task ID - """ - headers = { - "x-channel": "", - "x-api-key": self.runtime.credentials["aippt_access_key"], - "x-token": self._get_api_token(credentials=self.runtime.credentials, user_id=user_id), - } - response = post( - str(self._api_base_url / "ai" / "chat" / "v2" / "task"), - headers=headers, - files={"type": ("", str(type)), "title": ("", title), "content": ("", content)}, - ) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - - response = response.json() - if response.get("code") != 0: - raise Exception(f'Failed to create task: {response.get("msg")}') - - return response.get("data", {}).get("id") - - def _generate_outline(self, task_id: str, model: str, user_id: str) -> str: - api_url = ( - self._api_base_url / "ai" / "chat" / "outline" - if model == "aippt" - else self._api_base_url / "ai" / "chat" / "wx" / "outline" - ) - api_url %= {"task_id": task_id} - - headers = { - "x-channel": "", - "x-api-key": self.runtime.credentials["aippt_access_key"], - "x-token": self._get_api_token(credentials=self.runtime.credentials, user_id=user_id), - } - - response = requests_get(url=api_url, headers=headers, stream=True, timeout=(10, 60)) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - - outline = "" - for chunk in response.iter_lines(delimiter=b"\n\n"): - if not chunk: - continue - - event = "" - lines = chunk.decode("utf-8").split("\n") - for line in lines: - if line.startswith("event:"): - event = line[6:] - elif line.startswith("data:"): - data = line[5:] - if event == "message": - try: - data = json_loads(data) - outline += data.get("content", "") - except Exception as e: - pass - elif event == "close": - break - elif event in {"error", "filter"}: - raise Exception(f"Failed to generate outline: {data}") - - return outline - - def _generate_content(self, task_id: str, model: str, user_id: str) -> str: - api_url = ( - self._api_base_url / "ai" / "chat" / "content" - if model == "aippt" - else self._api_base_url / "ai" / "chat" / "wx" / "content" - ) - api_url %= {"task_id": task_id} - - headers = { - "x-channel": "", - "x-api-key": self.runtime.credentials["aippt_access_key"], - "x-token": self._get_api_token(credentials=self.runtime.credentials, user_id=user_id), - } - - response = requests_get(url=api_url, headers=headers, stream=True, timeout=(10, 60)) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - - if model == "aippt": - content = "" - for chunk in response.iter_lines(delimiter=b"\n\n"): - if not chunk: - continue - - event = "" - lines = chunk.decode("utf-8").split("\n") - for line in lines: - if line.startswith("event:"): - event = line[6:] - elif line.startswith("data:"): - data = line[5:] - if event == "message": - try: - data = json_loads(data) - content += data.get("content", "") - except Exception as e: - pass - elif event == "close": - break - elif event in {"error", "filter"}: - raise Exception(f"Failed to generate content: {data}") - - return content - elif model == "wenxin": - response = response.json() - if response.get("code") != 0: - raise Exception(f'Failed to generate content: {response.get("msg")}') - - return response.get("data", "") - - return "" - - def _generate_ppt(self, task_id: str, suit_id: int, user_id) -> tuple[str, str]: - """ - Generate a ppt - - :param task_id: the task ID - :param suit_id: the suit ID - :return: the cover url of the ppt and the ppt url - """ - headers = { - "x-channel": "", - "x-api-key": self.runtime.credentials["aippt_access_key"], - "x-token": self._get_api_token(credentials=self.runtime.credentials, user_id=user_id), - } - - response = post( - str(self._api_base_url / "design" / "v2" / "save"), - headers=headers, - data={"task_id": task_id, "template_id": suit_id}, - ) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - - response = response.json() - if response.get("code") != 0: - raise Exception(f'Failed to generate ppt: {response.get("msg")}') - - id = response.get("data", {}).get("id") - cover_url = response.get("data", {}).get("cover_url") - - response = post( - str(self._api_base_url / "download" / "export" / "file"), - headers=headers, - data={"id": id, "format": "ppt", "files_to_zip": False, "edit": True}, - ) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - - response = response.json() - if response.get("code") != 0: - raise Exception(f'Failed to generate ppt: {response.get("msg")}') - - export_code = response.get("data") - if not export_code: - raise Exception("Failed to generate ppt, the export code is empty") - - current_iteration = 0 - while current_iteration < 50: - # get ppt url - response = post( - str(self._api_base_url / "download" / "export" / "file" / "result"), - headers=headers, - data={"task_key": export_code}, - ) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - - response = response.json() - if response.get("code") != 0: - raise Exception(f'Failed to generate ppt: {response.get("msg")}') - - if response.get("msg") == "导出中": - current_iteration += 1 - sleep(2) - continue - - ppt_url = response.get("data", []) - if len(ppt_url) == 0: - raise Exception("Failed to generate ppt, the ppt url is empty") - - return cover_url, ppt_url[0] - - raise Exception("Failed to generate ppt, the export is timeout") - - @classmethod - def _get_api_token(cls, credentials: dict[str, str], user_id: str) -> str: - """ - Get API token - - :param credentials: the credentials - :return: the API token - """ - access_key = credentials["aippt_access_key"] - secret_key = credentials["aippt_secret_key"] - - cache_key = f"{access_key}#@#{user_id}" - - with cls._api_token_cache_lock: - # clear expired tokens - now = time() - for key in list(cls._api_token_cache.keys()): - if cls._api_token_cache[key]["expire"] < now: - del cls._api_token_cache[key] - - if cache_key in cls._api_token_cache: - return cls._api_token_cache[cache_key]["token"] - - # get token - headers = { - "x-api-key": access_key, - "x-timestamp": str(int(now)), - "x-signature": cls._calculate_sign(access_key, secret_key, int(now)), - } - - param = {"uid": user_id, "channel": ""} - - response = get(str(cls._api_base_url / "grant" / "token"), params=param, headers=headers) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - response = response.json() - if response.get("code") != 0: - raise Exception(f'Failed to connect to aippt: {response.get("msg")}') - - token = response.get("data", {}).get("token") - expire = response.get("data", {}).get("time_expire") - - with cls._api_token_cache_lock: - cls._api_token_cache[cache_key] = {"token": token, "expire": now + expire} - - return token - - @classmethod - def _calculate_sign(cls, access_key: str, secret_key: str, timestamp: int) -> str: - return b64encode( - hmac_new( - key=secret_key.encode("utf-8"), msg=f"GET@/api/grant/token/@{timestamp}".encode(), digestmod=sha1 - ).digest() - ).decode("utf-8") - - @classmethod - def _get_styles(cls, credentials: dict[str, str], user_id: str) -> tuple[list[dict], list[dict]]: - """ - Get styles - """ - - # check cache - with cls._style_cache_lock: - # clear expired styles - now = time() - for key in list(cls._style_cache.keys()): - if cls._style_cache[key]["expire"] < now: - del cls._style_cache[key] - - key = f'{credentials["aippt_access_key"]}#@#{user_id}' - if key in cls._style_cache: - return cls._style_cache[key]["colors"], cls._style_cache[key]["styles"] - - headers = { - "x-channel": "", - "x-api-key": credentials["aippt_access_key"], - "x-token": cls._get_api_token(credentials=credentials, user_id=user_id), - } - response = get(str(cls._api_base_url / "template_component" / "suit" / "select"), headers=headers) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - - response = response.json() - - if response.get("code") != 0: - raise Exception(f'Failed to connect to aippt: {response.get("msg")}') - - colors = [ - { - "id": f'id-{item.get("id")}', - "name": item.get("name"), - "en_name": item.get("en_name", item.get("name")), - } - for item in response.get("data", {}).get("colour") or [] - ] - styles = [ - { - "id": f'id-{item.get("id")}', - "name": item.get("title"), - } - for item in response.get("data", {}).get("suit_style") or [] - ] - - with cls._style_cache_lock: - cls._style_cache[key] = {"colors": colors, "styles": styles, "expire": now + 60 * 60} - - return colors, styles - - def get_styles(self, user_id: str) -> tuple[list[dict], list[dict]]: - """ - Get styles - - :param credentials: the credentials - :return: Tuple[list[dict[id, color]], list[dict[id, style]] - """ - if not self.runtime.credentials.get("aippt_access_key") or not self.runtime.credentials.get("aippt_secret_key"): - raise Exception("Please provide aippt credentials") - - return self._get_styles(credentials=self.runtime.credentials, user_id=user_id) - - def _get_suit(self, style_id: int, colour_id: int) -> int: - """ - Get suit - """ - headers = { - "x-channel": "", - "x-api-key": self.runtime.credentials["aippt_access_key"], - "x-token": self._get_api_token(credentials=self.runtime.credentials, user_id="__dify_system__"), - } - response = get( - str(self._api_base_url / "template_component" / "suit" / "search"), - headers=headers, - params={"style_id": style_id, "colour_id": colour_id, "page": 1, "page_size": 1}, - ) - - if response.status_code != 200: - raise Exception(f"Failed to connect to aippt: {response.text}") - - response = response.json() - - if response.get("code") != 0: - raise Exception(f'Failed to connect to aippt: {response.get("msg")}') - - if len(response.get("data", {}).get("list") or []) > 0: - return response.get("data", {}).get("list")[0].get("id") - - raise Exception("Failed to get suit, the suit does not exist, please check the style and color") - - def get_runtime_parameters(self) -> list[ToolParameter]: - """ - Get runtime parameters - - Override this method to add runtime parameters to the tool. - """ - try: - colors, styles = self.get_styles(user_id="__dify_system__") - except Exception as e: - colors, styles = ( - [{"id": "-1", "name": "__default__", "en_name": "__default__"}], - [{"id": "-1", "name": "__default__", "en_name": "__default__"}], - ) - - return [ - ToolParameter( - name="color", - label=I18nObject(zh_Hans="颜色", en_US="Color"), - human_description=I18nObject(zh_Hans="颜色", en_US="Color"), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - required=False, - default=colors[0]["id"], - options=[ - ToolParameterOption( - value=color["id"], label=I18nObject(zh_Hans=color["name"], en_US=color["en_name"]) - ) - for color in colors - ], - ), - ToolParameter( - name="style", - label=I18nObject(zh_Hans="风格", en_US="Style"), - human_description=I18nObject(zh_Hans="风格", en_US="Style"), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - required=False, - default=styles[0]["id"], - options=[ - ToolParameterOption(value=style["id"], label=I18nObject(zh_Hans=style["name"], en_US=style["name"])) - for style in styles - ], - ), - ] diff --git a/api/core/tools/provider/builtin/aippt/tools/aippt.yaml b/api/core/tools/provider/builtin/aippt/tools/aippt.yaml deleted file mode 100644 index d35798ad66106e..00000000000000 --- a/api/core/tools/provider/builtin/aippt/tools/aippt.yaml +++ /dev/null @@ -1,54 +0,0 @@ -identity: - name: aippt - author: Dify - label: - en_US: AIPPT - zh_Hans: AIPPT -description: - human: - en_US: AI-generated PPT with one click, input your content topic, and let AI serve you one-stop - zh_Hans: AI一键生成PPT，输入你的内容主题，让AI为你一站式服务到底 - llm: A tool used to generate PPT with AI, input your content topic, and let AI generate PPT for you. -parameters: - - name: title - type: string - required: true - label: - en_US: Title - zh_Hans: 标题 - human_description: - en_US: The title of the PPT. - zh_Hans: PPT的标题。 - llm_description: The title of the PPT, which will be used to generate the PPT outline. - form: llm - - name: outline - type: string - required: false - label: - en_US: Outline - zh_Hans: 大纲 - human_description: - en_US: The outline of the PPT - zh_Hans: PPT的大纲 - llm_description: The outline of the PPT, which will be used to generate the PPT content. provide it if you have. - form: llm - - name: llm - type: select - required: true - label: - en_US: LLM model - zh_Hans: 生成大纲的LLM - options: - - value: aippt - label: - en_US: AIPPT default model - zh_Hans: AIPPT默认模型 - - value: wenxin - label: - en_US: Wenxin ErnieBot - zh_Hans: 文心一言 - default: aippt - human_description: - en_US: The LLM model used for generating PPT outline. - zh_Hans: 用于生成PPT大纲的LLM模型。 - form: form diff --git a/api/core/tools/provider/builtin/alphavantage/_assets/icon.svg b/api/core/tools/provider/builtin/alphavantage/_assets/icon.svg deleted file mode 100644 index 785432943bc148..00000000000000 --- a/api/core/tools/provider/builtin/alphavantage/_assets/icon.svg +++ /dev/null @@ -1,7 +0,0 @@ - - - 形状结合 - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/alphavantage/alphavantage.py b/api/core/tools/provider/builtin/alphavantage/alphavantage.py deleted file mode 100644 index a84630e5aa990a..00000000000000 --- a/api/core/tools/provider/builtin/alphavantage/alphavantage.py +++ /dev/null @@ -1,22 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.alphavantage.tools.query_stock import QueryStockTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class AlphaVantageProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - QueryStockTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "code": "AAPL", # Apple Inc. - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/alphavantage/alphavantage.yaml b/api/core/tools/provider/builtin/alphavantage/alphavantage.yaml deleted file mode 100644 index 710510cfd8ed4a..00000000000000 --- a/api/core/tools/provider/builtin/alphavantage/alphavantage.yaml +++ /dev/null @@ -1,31 +0,0 @@ -identity: - author: zhuhao - name: alphavantage - label: - en_US: AlphaVantage - zh_Hans: AlphaVantage - pt_BR: AlphaVantage - description: - en_US: AlphaVantage is an online platform that provides financial market data and APIs, making it convenient for individual investors and developers to access stock quotes, technical indicators, and stock analysis. - zh_Hans: AlphaVantage是一个在线平台，它提供金融市场数据和API，便于个人投资者和开发者获取股票报价、技术指标和股票分析。 - pt_BR: AlphaVantage is an online platform that provides financial market data and APIs, making it convenient for individual investors and developers to access stock quotes, technical indicators, and stock analysis. - icon: icon.svg - tags: - - finance -credentials_for_provider: - api_key: - type: secret-input - required: true - label: - en_US: AlphaVantage API key - zh_Hans: AlphaVantage API key - pt_BR: AlphaVantage API key - placeholder: - en_US: Please input your AlphaVantage API key - zh_Hans: 请输入你的 AlphaVantage API key - pt_BR: Please input your AlphaVantage API key - help: - en_US: Get your AlphaVantage API key from AlphaVantage - zh_Hans: 从 AlphaVantage 获取您的 AlphaVantage API key - pt_BR: Get your AlphaVantage API key from AlphaVantage - url: https://www.alphavantage.co/support/#api-key diff --git a/api/core/tools/provider/builtin/alphavantage/tools/query_stock.py b/api/core/tools/provider/builtin/alphavantage/tools/query_stock.py deleted file mode 100644 index d06611acd05d1d..00000000000000 --- a/api/core/tools/provider/builtin/alphavantage/tools/query_stock.py +++ /dev/null @@ -1,48 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -ALPHAVANTAGE_API_URL = "https://www.alphavantage.co/query" - - -class QueryStockTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - stock_code = tool_parameters.get("code", "") - if not stock_code: - return self.create_text_message("Please tell me your stock code") - - if "api_key" not in self.runtime.credentials or not self.runtime.credentials.get("api_key"): - return self.create_text_message("Alpha Vantage API key is required.") - - params = { - "function": "TIME_SERIES_DAILY", - "symbol": stock_code, - "outputsize": "compact", - "datatype": "json", - "apikey": self.runtime.credentials["api_key"], - } - response = requests.get(url=ALPHAVANTAGE_API_URL, params=params) - response.raise_for_status() - result = self._handle_response(response.json()) - return self.create_json_message(result) - - def _handle_response(self, response: dict[str, Any]) -> dict[str, Any]: - result = response.get("Time Series (Daily)", {}) - if not result: - return {} - stock_result = {} - for k, v in result.items(): - stock_result[k] = {} - stock_result[k]["open"] = v.get("1. open") - stock_result[k]["high"] = v.get("2. high") - stock_result[k]["low"] = v.get("3. low") - stock_result[k]["close"] = v.get("4. close") - stock_result[k]["volume"] = v.get("5. volume") - return stock_result diff --git a/api/core/tools/provider/builtin/alphavantage/tools/query_stock.yaml b/api/core/tools/provider/builtin/alphavantage/tools/query_stock.yaml deleted file mode 100644 index d89f34e373f9fa..00000000000000 --- a/api/core/tools/provider/builtin/alphavantage/tools/query_stock.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: query_stock - author: zhuhao - label: - en_US: query_stock - zh_Hans: query_stock - pt_BR: query_stock -description: - human: - en_US: Retrieve information such as daily opening price, daily highest price, daily lowest price, daily closing price, and daily trading volume for a specified stock symbol. - zh_Hans: 获取指定股票代码的每日开盘价、每日最高价、每日最低价、每日收盘价和每日交易量等信息。 - pt_BR: Retrieve information such as daily opening price, daily highest price, daily lowest price, daily closing price, and daily trading volume for a specified stock symbol - llm: Retrieve information such as daily opening price, daily highest price, daily lowest price, daily closing price, and daily trading volume for a specified stock symbol -parameters: - - name: code - type: string - required: true - label: - en_US: stock code - zh_Hans: 股票代码 - pt_BR: stock code - human_description: - en_US: stock code - zh_Hans: 股票代码 - pt_BR: stock code - llm_description: stock code for query from alphavantage - form: llm diff --git a/api/core/tools/provider/builtin/arxiv/_assets/icon.svg b/api/core/tools/provider/builtin/arxiv/_assets/icon.svg deleted file mode 100644 index 0e60f635739993..00000000000000 --- a/api/core/tools/provider/builtin/arxiv/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/arxiv/arxiv.py b/api/core/tools/provider/builtin/arxiv/arxiv.py deleted file mode 100644 index ebb2d1a8c47be9..00000000000000 --- a/api/core/tools/provider/builtin/arxiv/arxiv.py +++ /dev/null @@ -1,20 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.arxiv.tools.arxiv_search import ArxivSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class ArxivProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - ArxivSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "query": "John Doe", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/arxiv/arxiv.yaml b/api/core/tools/provider/builtin/arxiv/arxiv.yaml deleted file mode 100644 index d26993b3364ea1..00000000000000 --- a/api/core/tools/provider/builtin/arxiv/arxiv.yaml +++ /dev/null @@ -1,12 +0,0 @@ -identity: - author: Yash Parmar - name: arxiv - label: - en_US: ArXiv - zh_Hans: ArXiv - description: - en_US: Access to a vast repository of scientific papers and articles in various fields of research. - zh_Hans: 访问各个研究领域大量科学论文和文章的存储库。 - icon: icon.svg - tags: - - search diff --git a/api/core/tools/provider/builtin/arxiv/tools/arxiv_search.py b/api/core/tools/provider/builtin/arxiv/tools/arxiv_search.py deleted file mode 100644 index 2d65ba2d6f4389..00000000000000 --- a/api/core/tools/provider/builtin/arxiv/tools/arxiv_search.py +++ /dev/null @@ -1,119 +0,0 @@ -import logging -from typing import Any, Optional - -import arxiv -from pydantic import BaseModel, Field - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -logger = logging.getLogger(__name__) - - -class ArxivAPIWrapper(BaseModel): - """Wrapper around ArxivAPI. - - To use, you should have the ``arxiv`` python package installed. - https://lukasschwab.me/arxiv.py/index.html - This wrapper will use the Arxiv API to conduct searches and - fetch document summaries. By default, it will return the document summaries - of the top-k results. - It limits the Document content by doc_content_chars_max. - Set doc_content_chars_max=None if you don't want to limit the content size. - - Args: - top_k_results: number of the top-scored document used for the arxiv tool - ARXIV_MAX_QUERY_LENGTH: the cut limit on the query used for the arxiv tool. - load_max_docs: a limit to the number of loaded documents - load_all_available_meta: - if True: the `metadata` of the loaded Documents contains all available - meta info (see https://lukasschwab.me/arxiv.py/index.html#Result), - if False: the `metadata` contains only the published date, title, - authors and summary. - doc_content_chars_max: an optional cut limit for the length of a document's - content - - Example: - .. code-block:: python - - arxiv = ArxivAPIWrapper( - top_k_results = 3, - ARXIV_MAX_QUERY_LENGTH = 300, - load_max_docs = 3, - load_all_available_meta = False, - doc_content_chars_max = 40000 - ) - arxiv.run("tree of thought llm) - """ - - arxiv_search: type[arxiv.Search] = arxiv.Search #: :meta private: - arxiv_http_error: tuple[type[Exception]] = (arxiv.ArxivError, arxiv.UnexpectedEmptyPageError, arxiv.HTTPError) - top_k_results: int = 3 - ARXIV_MAX_QUERY_LENGTH: int = 300 - load_max_docs: int = 100 - load_all_available_meta: bool = False - doc_content_chars_max: Optional[int] = 4000 - - def run(self, query: str) -> str: - """ - Performs an arxiv search and A single string - with the publish date, title, authors, and summary - for each article separated by two newlines. - - If an error occurs or no documents found, error text - is returned instead. Wrapper for - https://lukasschwab.me/arxiv.py/index.html#Search - - Args: - query: a plaintext search query - """ - try: - results = self.arxiv_search( # type: ignore - query[: self.ARXIV_MAX_QUERY_LENGTH], max_results=self.top_k_results - ).results() - except arxiv_http_error as ex: - return f"Arxiv exception: {ex}" - docs = [ - f"Published: {result.updated.date()}\n" - f"Title: {result.title}\n" - f"Authors: {', '.join(a.name for a in result.authors)}\n" - f"Summary: {result.summary}" - for result in results - ] - if docs: - return "\n\n".join(docs)[: self.doc_content_chars_max] - else: - return "No good Arxiv Result was found" - - -class ArxivSearchInput(BaseModel): - query: str = Field(..., description="Search query.") - - -class ArxivSearchTool(BuiltinTool): - """ - A tool for searching articles on Arxiv. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: - """ - Invokes the Arxiv search tool with the given user ID and tool parameters. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Any]): The parameters for the tool, including the 'query' parameter. - - Returns: - ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation, - which can be a single message or a list of messages. - """ - query = tool_parameters.get("query", "") - - if not query: - return self.create_text_message("Please input query") - - arxiv = ArxivAPIWrapper() - - response = arxiv.run(query) - - return self.create_text_message(self.summary(user_id=user_id, content=response)) diff --git a/api/core/tools/provider/builtin/arxiv/tools/arxiv_search.yaml b/api/core/tools/provider/builtin/arxiv/tools/arxiv_search.yaml deleted file mode 100644 index 7439a48658c6a0..00000000000000 --- a/api/core/tools/provider/builtin/arxiv/tools/arxiv_search.yaml +++ /dev/null @@ -1,23 +0,0 @@ -identity: - name: arxiv_search - author: Yash Parmar - label: - en_US: Arxiv Search - zh_Hans: Arxiv 搜索 -description: - human: - en_US: A tool for searching scientific papers and articles from the Arxiv repository. Input can be an Arxiv ID or an author's name. - zh_Hans: 一个用于从Arxiv存储库搜索科学论文和文章的工具。 输入可以是Arxiv ID或作者姓名。 - llm: A tool for searching scientific papers and articles from the Arxiv repository. Input can be an Arxiv ID or an author's name. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询字符串 - human_description: - en_US: The Arxiv ID or author's name used for searching. - zh_Hans: 用于搜索的Arxiv ID或作者姓名。 - llm_description: The Arxiv ID or author's name used for searching. - form: llm diff --git a/api/core/tools/provider/builtin/aws/_assets/icon.svg b/api/core/tools/provider/builtin/aws/_assets/icon.svg deleted file mode 100644 index ecfcfc08d4eeff..00000000000000 --- a/api/core/tools/provider/builtin/aws/_assets/icon.svg +++ /dev/null @@ -1,9 +0,0 @@ - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/aws/aws.py b/api/core/tools/provider/builtin/aws/aws.py deleted file mode 100644 index f81b5dbd27d17c..00000000000000 --- a/api/core/tools/provider/builtin/aws/aws.py +++ /dev/null @@ -1,24 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.aws.tools.sagemaker_text_rerank import SageMakerReRankTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class SageMakerProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - SageMakerReRankTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "sagemaker_endpoint": "", - "query": "misaka mikoto", - "candidate_texts": "hello$$$hello world", - "topk": 5, - "aws_region": "", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/aws/aws.yaml b/api/core/tools/provider/builtin/aws/aws.yaml deleted file mode 100644 index 847c6824a53df6..00000000000000 --- a/api/core/tools/provider/builtin/aws/aws.yaml +++ /dev/null @@ -1,15 +0,0 @@ -identity: - author: AWS - name: aws - label: - en_US: AWS - zh_Hans: 亚马逊云科技 - pt_BR: AWS - description: - en_US: Services on AWS. - zh_Hans: 亚马逊云科技的各类服务 - pt_BR: Services on AWS. - icon: icon.svg - tags: - - search -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/aws/tools/apply_guardrail.py b/api/core/tools/provider/builtin/aws/tools/apply_guardrail.py deleted file mode 100644 index a04f5c0fe9f1af..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/apply_guardrail.py +++ /dev/null @@ -1,90 +0,0 @@ -import json -import logging -from typing import Any, Union - -import boto3 -from botocore.exceptions import BotoCoreError -from pydantic import BaseModel, Field - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -logging.basicConfig(level=logging.INFO) -logger = logging.getLogger(__name__) - - -class GuardrailParameters(BaseModel): - guardrail_id: str = Field(..., description="The identifier of the guardrail") - guardrail_version: str = Field(..., description="The version of the guardrail") - source: str = Field(..., description="The source of the content") - text: str = Field(..., description="The text to apply the guardrail to") - aws_region: str = Field(..., description="AWS region for the Bedrock client") - - -class ApplyGuardrailTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the ApplyGuardrail tool - """ - try: - # Validate and parse input parameters - params = GuardrailParameters(**tool_parameters) - - # Initialize AWS client - bedrock_client = boto3.client("bedrock-runtime", region_name=params.aws_region) - - # Apply guardrail - response = bedrock_client.apply_guardrail( - guardrailIdentifier=params.guardrail_id, - guardrailVersion=params.guardrail_version, - source=params.source, - content=[{"text": {"text": params.text}}], - ) - - logger.info(f"Raw response from AWS: {json.dumps(response, indent=2)}") - - # Check for empty response - if not response: - return self.create_text_message(text="Received empty response from AWS Bedrock.") - - # Process the result - action = response.get("action", "No action specified") - outputs = response.get("outputs", []) - output = outputs[0].get("text", "No output received") if outputs else "No output received" - assessments = response.get("assessments", []) - - # Format assessments - formatted_assessments = [] - for assessment in assessments: - for policy_type, policy_data in assessment.items(): - if isinstance(policy_data, dict) and "topics" in policy_data: - for topic in policy_data["topics"]: - formatted_assessments.append( - f"Policy: {policy_type}, Topic: {topic['name']}, Type: {topic['type']}," - f" Action: {topic['action']}" - ) - else: - formatted_assessments.append(f"Policy: {policy_type}, Data: {policy_data}") - - result = f"Action: {action}\n " - result += f"Output: {output}\n " - if formatted_assessments: - result += "Assessments:\n " + "\n ".join(formatted_assessments) + "\n " - # result += f"Full response: {json.dumps(response, indent=2, ensure_ascii=False)}" - - return self.create_text_message(text=result) - - except BotoCoreError as e: - error_message = f"AWS service error: {str(e)}" - logger.error(error_message, exc_info=True) - return self.create_text_message(text=error_message) - except json.JSONDecodeError as e: - error_message = f"JSON parsing error: {str(e)}" - logger.error(error_message, exc_info=True) - return self.create_text_message(text=error_message) - except Exception as e: - error_message = f"An unexpected error occurred: {str(e)}" - logger.error(error_message, exc_info=True) - return self.create_text_message(text=error_message) diff --git a/api/core/tools/provider/builtin/aws/tools/apply_guardrail.yaml b/api/core/tools/provider/builtin/aws/tools/apply_guardrail.yaml deleted file mode 100644 index 66044e4ea84fe1..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/apply_guardrail.yaml +++ /dev/null @@ -1,67 +0,0 @@ -identity: - name: apply_guardrail - author: AWS - label: - en_US: Content Moderation Guardrails - zh_Hans: 内容审查护栏 -description: - human: - en_US: Content Moderation Guardrails utilizes the ApplyGuardrail API, a feature of Guardrails for Amazon Bedrock. This API is capable of evaluating input prompts and model responses for all Foundation Models (FMs), including those on Amazon Bedrock, custom FMs, and third-party FMs. By implementing this functionality, organizations can achieve centralized governance across all their generative AI applications, thereby enhancing control and consistency in content moderation. - zh_Hans: 内容审查护栏采用 Guardrails for Amazon Bedrock 功能中的 ApplyGuardrail API 。ApplyGuardrail 可以评估所有基础模型(FMs)的输入提示和模型响应，包括 Amazon Bedrock 上的 FMs、自定义 FMs 和第三方 FMs。通过实施这一功能, 组织可以在所有生成式 AI 应用程序中实现集中化的治理，从而增强内容审核的控制力和一致性。 - llm: Content Moderation Guardrails utilizes the ApplyGuardrail API, a feature of Guardrails for Amazon Bedrock. This API is capable of evaluating input prompts and model responses for all Foundation Models (FMs), including those on Amazon Bedrock, custom FMs, and third-party FMs. By implementing this functionality, organizations can achieve centralized governance across all their generative AI applications, thereby enhancing control and consistency in content moderation. -parameters: - - name: guardrail_id - type: string - required: true - label: - en_US: Guardrail ID - zh_Hans: Guardrail ID - human_description: - en_US: Please enter the ID of the Guardrail that has already been created on Amazon Bedrock, for example 'qk5nk0e4b77b'. - zh_Hans: 请输入已经在 Amazon Bedrock 上创建好的 Guardrail ID, 例如 'qk5nk0e4b77b'. - llm_description: Please enter the ID of the Guardrail that has already been created on Amazon Bedrock, for example 'qk5nk0e4b77b'. - form: form - - name: guardrail_version - type: string - required: true - label: - en_US: Guardrail Version Number - zh_Hans: Guardrail 版本号码 - human_description: - en_US: Please enter the published version of the Guardrail ID that has already been created on Amazon Bedrock. This is typically a version number, such as 2. - zh_Hans: 请输入已经在Amazon Bedrock 上创建好的Guardrail ID发布的版本, 通常使用版本号, 例如2. - llm_description: Please enter the published version of the Guardrail ID that has already been created on Amazon Bedrock. This is typically a version number, such as 2. - form: form - - name: source - type: string - required: true - label: - en_US: Content Source (INPUT or OUTPUT) - zh_Hans: 内容来源 (INPUT or OUTPUT) - human_description: - en_US: The source of data used in the request to apply the guardrail. Valid Values "INPUT | OUTPUT" - zh_Hans: 用于应用护栏的请求中所使用的数据来源。有效值为 "INPUT | OUTPUT" - llm_description: The source of data used in the request to apply the guardrail. Valid Values "INPUT | OUTPUT" - form: form - - name: text - type: string - required: true - label: - en_US: Content to be reviewed - zh_Hans: 待审查内容 - human_description: - en_US: The content used for requesting guardrail review, which can be either user input or LLM output. - zh_Hans: 用于请求护栏审查的内容，可以是用户输入或 LLM 输出。 - llm_description: The content used for requesting guardrail review, which can be either user input or LLM output. - form: llm - - name: aws_region - type: string - required: true - label: - en_US: AWS Region - zh_Hans: AWS 区域 - human_description: - en_US: Please enter the AWS region for the Bedrock client, for example 'us-east-1'. - zh_Hans: 请输入 Bedrock 客户端的 AWS 区域，例如 'us-east-1'。 - llm_description: Please enter the AWS region for the Bedrock client, for example 'us-east-1'. - form: form diff --git a/api/core/tools/provider/builtin/aws/tools/lambda_translate_utils.py b/api/core/tools/provider/builtin/aws/tools/lambda_translate_utils.py deleted file mode 100644 index 48755753ace7c1..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/lambda_translate_utils.py +++ /dev/null @@ -1,91 +0,0 @@ -import json -from typing import Any, Union - -import boto3 - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class LambdaTranslateUtilsTool(BuiltinTool): - lambda_client: Any = None - - def _invoke_lambda(self, text_content, src_lang, dest_lang, model_id, dictionary_name, request_type, lambda_name): - msg = { - "src_content": text_content, - "src_lang": src_lang, - "dest_lang": dest_lang, - "dictionary_id": dictionary_name, - "request_type": request_type, - "model_id": model_id, - } - - invoke_response = self.lambda_client.invoke( - FunctionName=lambda_name, InvocationType="RequestResponse", Payload=json.dumps(msg) - ) - response_body = invoke_response["Payload"] - - response_str = response_body.read().decode("unicode_escape") - - return response_str - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - line = 0 - try: - if not self.lambda_client: - aws_region = tool_parameters.get("aws_region") - if aws_region: - self.lambda_client = boto3.client("lambda", region_name=aws_region) - else: - self.lambda_client = boto3.client("lambda") - - line = 1 - text_content = tool_parameters.get("text_content", "") - if not text_content: - return self.create_text_message("Please input text_content") - - line = 2 - src_lang = tool_parameters.get("src_lang", "") - if not src_lang: - return self.create_text_message("Please input src_lang") - - line = 3 - dest_lang = tool_parameters.get("dest_lang", "") - if not dest_lang: - return self.create_text_message("Please input dest_lang") - - line = 4 - lambda_name = tool_parameters.get("lambda_name", "") - if not lambda_name: - return self.create_text_message("Please input lambda_name") - - line = 5 - request_type = tool_parameters.get("request_type", "") - if not request_type: - return self.create_text_message("Please input request_type") - - line = 6 - model_id = tool_parameters.get("model_id", "") - if not model_id: - return self.create_text_message("Please input model_id") - - line = 7 - dictionary_name = tool_parameters.get("dictionary_name", "") - if not dictionary_name: - return self.create_text_message("Please input dictionary_name") - - result = self._invoke_lambda( - text_content, src_lang, dest_lang, model_id, dictionary_name, request_type, lambda_name - ) - - return self.create_text_message(text=result) - - except Exception as e: - return self.create_text_message(f"Exception {str(e)}, line : {line}") diff --git a/api/core/tools/provider/builtin/aws/tools/lambda_translate_utils.yaml b/api/core/tools/provider/builtin/aws/tools/lambda_translate_utils.yaml deleted file mode 100644 index 3bb133c7ec8d16..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/lambda_translate_utils.yaml +++ /dev/null @@ -1,134 +0,0 @@ -identity: - name: lambda_translate_utils - author: AWS - label: - en_US: TranslateTool - zh_Hans: 翻译工具 - pt_BR: TranslateTool - icon: icon.svg -description: - human: - en_US: A util tools for LLM translation, extra deployment is needed on AWS. Please refer Github Repo - https://github.com/ybalbert001/dynamodb-rag - zh_Hans: 大语言模型翻译工具(专词映射获取)，需要在AWS上进行额外部署，可参考Github Repo - https://github.com/ybalbert001/dynamodb-rag - pt_BR: A util tools for LLM translation, specific Lambda Function deployment is needed on AWS. Please refer Github Repo - https://github.com/ybalbert001/dynamodb-rag - llm: A util tools for translation. -parameters: - - name: text_content - type: string - required: true - label: - en_US: source content for translation - zh_Hans: 待翻译原文 - pt_BR: source content for translation - human_description: - en_US: source content for translation - zh_Hans: 待翻译原文 - pt_BR: source content for translation - llm_description: source content for translation - form: llm - - name: src_lang - type: string - required: true - label: - en_US: source language code - zh_Hans: 原文语言代号 - pt_BR: source language code - human_description: - en_US: source language code - zh_Hans: 原文语言代号 - pt_BR: source language code - llm_description: source language code - form: llm - - name: dest_lang - type: string - required: true - label: - en_US: target language code - zh_Hans: 目标语言代号 - pt_BR: target language code - human_description: - en_US: target language code - zh_Hans: 目标语言代号 - pt_BR: target language code - llm_description: target language code - form: llm - - name: aws_region - type: string - required: false - label: - en_US: region of Lambda - zh_Hans: Lambda 所在的region - pt_BR: region of Lambda - human_description: - en_US: region of Lambda - zh_Hans: Lambda 所在的region - pt_BR: region of Lambda - llm_description: region of Lambda - form: form - - name: model_id - type: string - required: false - default: anthropic.claude-3-sonnet-20240229-v1:0 - label: - en_US: LLM model_id in bedrock - zh_Hans: bedrock上的大语言模型model_id - pt_BR: LLM model_id in bedrock - human_description: - en_US: LLM model_id in bedrock - zh_Hans: bedrock上的大语言模型model_id - pt_BR: LLM model_id in bedrock - llm_description: LLM model_id in bedrock - form: form - - name: dictionary_name - type: string - required: false - label: - en_US: dictionary name for term mapping - zh_Hans: 专词映射表名称 - pt_BR: dictionary name for term mapping - human_description: - en_US: dictionary name for term mapping - zh_Hans: 专词映射表名称 - pt_BR: dictionary name for term mapping - llm_description: dictionary name for term mapping - form: form - - name: request_type - type: select - required: false - label: - en_US: request type - zh_Hans: 请求类型 - pt_BR: request type - human_description: - en_US: request type - zh_Hans: 请求类型 - pt_BR: request type - default: term_mapping - options: - - value: term_mapping - label: - en_US: term_mapping - zh_Hans: 专词映射 - - value: segment_only - label: - en_US: segment_only - zh_Hans: 仅切词 - - value: translate - label: - en_US: translate - zh_Hans: 翻译内容 - form: form - - name: lambda_name - type: string - default: "translate_tool" - required: true - label: - en_US: AWS Lambda for term mapping retrieval - zh_Hans: 专词召回映射 - AWS Lambda - pt_BR: lambda name for term mapping retrieval - human_description: - en_US: AWS Lambda for term mapping retrieval - zh_Hans: 专词召回映射 - AWS Lambda - pt_BR: AWS Lambda for term mapping retrieval - llm_description: AWS Lambda for term mapping retrieval - form: form diff --git a/api/core/tools/provider/builtin/aws/tools/lambda_yaml_to_json.py b/api/core/tools/provider/builtin/aws/tools/lambda_yaml_to_json.py deleted file mode 100644 index f43f3b6fe05694..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/lambda_yaml_to_json.py +++ /dev/null @@ -1,70 +0,0 @@ -import json -import logging -from typing import Any, Union - -import boto3 - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -logging.basicConfig(level=logging.INFO) -logger = logging.getLogger(__name__) - -console_handler = logging.StreamHandler() -logger.addHandler(console_handler) - - -class LambdaYamlToJsonTool(BuiltinTool): - lambda_client: Any = None - - def _invoke_lambda(self, lambda_name: str, yaml_content: str) -> str: - msg = {"body": yaml_content} - logger.info(json.dumps(msg)) - - invoke_response = self.lambda_client.invoke( - FunctionName=lambda_name, InvocationType="RequestResponse", Payload=json.dumps(msg) - ) - response_body = invoke_response["Payload"] - - response_str = response_body.read().decode("utf-8") - resp_json = json.loads(response_str) - - logger.info(resp_json) - if resp_json["statusCode"] != 200: - raise Exception(f"Invalid status code: {response_str}") - - return resp_json["body"] - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - try: - if not self.lambda_client: - aws_region = tool_parameters.get("aws_region") # todo: move aws_region out, and update client region - if aws_region: - self.lambda_client = boto3.client("lambda", region_name=aws_region) - else: - self.lambda_client = boto3.client("lambda") - - yaml_content = tool_parameters.get("yaml_content", "") - if not yaml_content: - return self.create_text_message("Please input yaml_content") - - lambda_name = tool_parameters.get("lambda_name", "") - if not lambda_name: - return self.create_text_message("Please input lambda_name") - logger.debug(f"{json.dumps(tool_parameters, indent=2, ensure_ascii=False)}") - - result = self._invoke_lambda(lambda_name, yaml_content) - logger.debug(result) - - return self.create_text_message(result) - except Exception as e: - return self.create_text_message(f"Exception: {str(e)}") - - console_handler.flush() diff --git a/api/core/tools/provider/builtin/aws/tools/lambda_yaml_to_json.yaml b/api/core/tools/provider/builtin/aws/tools/lambda_yaml_to_json.yaml deleted file mode 100644 index 919c285348df83..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/lambda_yaml_to_json.yaml +++ /dev/null @@ -1,53 +0,0 @@ -identity: - name: lambda_yaml_to_json - author: AWS - label: - en_US: LambdaYamlToJson - zh_Hans: LambdaYamlToJson - pt_BR: LambdaYamlToJson - icon: icon.svg -description: - human: - en_US: A tool to convert yaml to json using AWS Lambda. - zh_Hans: 将 YAML 转为 JSON 的工具（通过AWS Lambda）。 - pt_BR: A tool to convert yaml to json using AWS Lambda. - llm: A tool to convert yaml to json. -parameters: - - name: yaml_content - type: string - required: true - label: - en_US: YAML content to convert for - zh_Hans: YAML 内容 - pt_BR: YAML content to convert for - human_description: - en_US: YAML content to convert for - zh_Hans: YAML 内容 - pt_BR: YAML content to convert for - llm_description: YAML content to convert for - form: llm - - name: aws_region - type: string - required: false - label: - en_US: region of lambda - zh_Hans: Lambda 所在的region - pt_BR: region of lambda - human_description: - en_US: region of lambda - zh_Hans: Lambda 所在的region - pt_BR: region of lambda - llm_description: region of lambda - form: form - - name: lambda_name - type: string - required: false - label: - en_US: name of lambda - zh_Hans: Lambda 名称 - pt_BR: name of lambda - human_description: - en_US: name of lambda - zh_Hans: Lambda 名称 - pt_BR: name of lambda - form: form diff --git a/api/core/tools/provider/builtin/aws/tools/sagemaker_text_rerank.py b/api/core/tools/provider/builtin/aws/tools/sagemaker_text_rerank.py deleted file mode 100644 index bffcd058b509bf..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/sagemaker_text_rerank.py +++ /dev/null @@ -1,81 +0,0 @@ -import json -import operator -from typing import Any, Union - -import boto3 - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class SageMakerReRankTool(BuiltinTool): - sagemaker_client: Any = None - sagemaker_endpoint: str = None - topk: int = None - - def _sagemaker_rerank(self, query_input: str, docs: list[str], rerank_endpoint: str): - inputs = [query_input] * len(docs) - response_model = self.sagemaker_client.invoke_endpoint( - EndpointName=rerank_endpoint, - Body=json.dumps({"inputs": inputs, "docs": docs}), - ContentType="application/json", - ) - json_str = response_model["Body"].read().decode("utf8") - json_obj = json.loads(json_str) - scores = json_obj["scores"] - return scores if isinstance(scores, list) else [scores] - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - line = 0 - try: - if not self.sagemaker_client: - aws_region = tool_parameters.get("aws_region") - if aws_region: - self.sagemaker_client = boto3.client("sagemaker-runtime", region_name=aws_region) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime") - - line = 1 - if not self.sagemaker_endpoint: - self.sagemaker_endpoint = tool_parameters.get("sagemaker_endpoint") - - line = 2 - if not self.topk: - self.topk = tool_parameters.get("topk", 5) - - line = 3 - query = tool_parameters.get("query", "") - if not query: - return self.create_text_message("Please input query") - - line = 4 - candidate_texts = tool_parameters.get("candidate_texts") - if not candidate_texts: - return self.create_text_message("Please input candidate_texts") - - line = 5 - candidate_docs = json.loads(candidate_texts) - docs = [item.get("content") for item in candidate_docs] - - line = 6 - scores = self._sagemaker_rerank(query_input=query, docs=docs, rerank_endpoint=self.sagemaker_endpoint) - - line = 7 - for idx in range(len(candidate_docs)): - candidate_docs[idx]["score"] = scores[idx] - - line = 8 - sorted_candidate_docs = sorted(candidate_docs, key=operator.itemgetter("score"), reverse=True) - - line = 9 - return [self.create_json_message(res) for res in sorted_candidate_docs[: self.topk]] - - except Exception as e: - return self.create_text_message(f"Exception {str(e)}, line : {line}") diff --git a/api/core/tools/provider/builtin/aws/tools/sagemaker_text_rerank.yaml b/api/core/tools/provider/builtin/aws/tools/sagemaker_text_rerank.yaml deleted file mode 100644 index d1dfdb9f84a858..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/sagemaker_text_rerank.yaml +++ /dev/null @@ -1,82 +0,0 @@ -identity: - name: sagemaker_text_rerank - author: AWS - label: - en_US: SagemakerRerank - zh_Hans: Sagemaker重排序 - pt_BR: SagemakerRerank - icon: icon.svg -description: - human: - en_US: A tool for performing text similarity ranking. You can find deploy notebook on Github Repo - https://github.com/aws-samples/dify-aws-tool - zh_Hans: Sagemaker重排序工具, 请参考 Github Repo - https://github.com/aws-samples/dify-aws-tool上的部署脚本 - pt_BR: A tool for performing text similarity ranking. - llm: A tool for performing text similarity ranking. You can find deploy notebook on Github Repo - https://github.com/aws-samples/dify-aws-tool -parameters: - - name: sagemaker_endpoint - type: string - required: true - label: - en_US: sagemaker endpoint for reranking - zh_Hans: 重排序的SageMaker 端点 - pt_BR: sagemaker endpoint for reranking - human_description: - en_US: sagemaker endpoint for reranking - zh_Hans: 重排序的SageMaker 端点 - pt_BR: sagemaker endpoint for reranking - llm_description: sagemaker endpoint for reranking - form: form - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - pt_BR: Query string - human_description: - en_US: key words for searching - zh_Hans: 查询关键词 - pt_BR: key words for searching - llm_description: key words for searching - form: llm - - name: candidate_texts - type: string - required: true - label: - en_US: text candidates - zh_Hans: 候选文本 - pt_BR: text candidates - human_description: - en_US: searched candidates by query - zh_Hans: 查询文本搜到候选文本 - pt_BR: searched candidates by query - llm_description: searched candidates by query - form: llm - - name: topk - type: number - required: false - form: form - label: - en_US: Limit for results count - zh_Hans: 返回个数限制 - pt_BR: Limit for results count - human_description: - en_US: Limit for results count - zh_Hans: 返回个数限制 - pt_BR: Limit for results count - min: 1 - max: 10 - default: 5 - - name: aws_region - type: string - required: false - label: - en_US: region of sagemaker endpoint - zh_Hans: SageMaker 端点所在的region - pt_BR: region of sagemaker endpoint - human_description: - en_US: region of sagemaker endpoint - zh_Hans: SageMaker 端点所在的region - pt_BR: region of sagemaker endpoint - llm_description: region of sagemaker endpoint - form: form diff --git a/api/core/tools/provider/builtin/aws/tools/sagemaker_tts.py b/api/core/tools/provider/builtin/aws/tools/sagemaker_tts.py deleted file mode 100644 index bceeaab7453d94..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/sagemaker_tts.py +++ /dev/null @@ -1,101 +0,0 @@ -import json -from enum import Enum -from typing import Any, Union - -import boto3 - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class TTSModelType(Enum): - PresetVoice = "PresetVoice" - CloneVoice = "CloneVoice" - CloneVoice_CrossLingual = "CloneVoice_CrossLingual" - InstructVoice = "InstructVoice" - - -class SageMakerTTSTool(BuiltinTool): - sagemaker_client: Any = None - sagemaker_endpoint: str = None - s3_client: Any = None - comprehend_client: Any = None - - def _detect_lang_code(self, content: str, map_dict: dict = None): - map_dict = {"zh": "<|zh|>", "en": "<|en|>", "ja": "<|jp|>", "zh-TW": "<|yue|>", "ko": "<|ko|>"} - - response = self.comprehend_client.detect_dominant_language(Text=content) - language_code = response["Languages"][0]["LanguageCode"] - return map_dict.get(language_code, "<|zh|>") - - def _build_tts_payload( - self, - model_type: str, - content_text: str, - model_role: str, - prompt_text: str, - prompt_audio: str, - instruct_text: str, - ): - if model_type == TTSModelType.PresetVoice.value and model_role: - return {"tts_text": content_text, "role": model_role} - if model_type == TTSModelType.CloneVoice.value and prompt_text and prompt_audio: - return {"tts_text": content_text, "prompt_text": prompt_text, "prompt_audio": prompt_audio} - if model_type == TTSModelType.CloneVoice_CrossLingual.value and prompt_audio: - lang_tag = self._detect_lang_code(content_text) - return {"tts_text": f"{content_text}", "prompt_audio": prompt_audio, "lang_tag": lang_tag} - if model_type == TTSModelType.InstructVoice.value and instruct_text and model_role: - return {"tts_text": content_text, "role": model_role, "instruct_text": instruct_text} - - raise RuntimeError(f"Invalid params for {model_type}") - - def _invoke_sagemaker(self, payload: dict, endpoint: str): - response_model = self.sagemaker_client.invoke_endpoint( - EndpointName=endpoint, - Body=json.dumps(payload), - ContentType="application/json", - ) - json_str = response_model["Body"].read().decode("utf8") - json_obj = json.loads(json_str) - return json_obj - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - try: - if not self.sagemaker_client: - aws_region = tool_parameters.get("aws_region") - if aws_region: - self.sagemaker_client = boto3.client("sagemaker-runtime", region_name=aws_region) - self.s3_client = boto3.client("s3", region_name=aws_region) - self.comprehend_client = boto3.client("comprehend", region_name=aws_region) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime") - self.s3_client = boto3.client("s3") - self.comprehend_client = boto3.client("comprehend") - - if not self.sagemaker_endpoint: - self.sagemaker_endpoint = tool_parameters.get("sagemaker_endpoint") - - tts_text = tool_parameters.get("tts_text") - tts_infer_type = tool_parameters.get("tts_infer_type") - - voice = tool_parameters.get("voice") - mock_voice_audio = tool_parameters.get("mock_voice_audio") - mock_voice_text = tool_parameters.get("mock_voice_text") - voice_instruct_prompt = tool_parameters.get("voice_instruct_prompt") - payload = self._build_tts_payload( - tts_infer_type, tts_text, voice, mock_voice_text, mock_voice_audio, voice_instruct_prompt - ) - - result = self._invoke_sagemaker(payload, self.sagemaker_endpoint) - - return self.create_text_message(text=result["s3_presign_url"]) - - except Exception as e: - return self.create_text_message(f"Exception {str(e)}") diff --git a/api/core/tools/provider/builtin/aws/tools/sagemaker_tts.yaml b/api/core/tools/provider/builtin/aws/tools/sagemaker_tts.yaml deleted file mode 100644 index a6a61dd4aa519a..00000000000000 --- a/api/core/tools/provider/builtin/aws/tools/sagemaker_tts.yaml +++ /dev/null @@ -1,149 +0,0 @@ -identity: - name: sagemaker_tts - author: AWS - label: - en_US: SagemakerTTS - zh_Hans: Sagemaker语音合成 - pt_BR: SagemakerTTS - icon: icon.svg -description: - human: - en_US: A tool for Speech synthesis - https://github.com/aws-samples/dify-aws-tool - zh_Hans: Sagemaker语音合成工具, 请参考 Github Repo - https://github.com/aws-samples/dify-aws-tool上的部署脚本 - pt_BR: A tool for Speech synthesis. - llm: A tool for Speech synthesis. You can find deploy notebook on Github Repo - https://github.com/aws-samples/dify-aws-tool -parameters: - - name: sagemaker_endpoint - type: string - required: true - label: - en_US: sagemaker endpoint for tts - zh_Hans: 语音生成的SageMaker端点 - pt_BR: sagemaker endpoint for tts - human_description: - en_US: sagemaker endpoint for tts - zh_Hans: 语音生成的SageMaker端点 - pt_BR: sagemaker endpoint for tts - llm_description: sagemaker endpoint for tts - form: form - - name: tts_text - type: string - required: true - label: - en_US: tts text - zh_Hans: 语音合成原文 - pt_BR: tts text - human_description: - en_US: tts text - zh_Hans: 语音合成原文 - pt_BR: tts text - llm_description: tts text - form: llm - - name: tts_infer_type - type: select - required: false - label: - en_US: tts infer type - zh_Hans: 合成方式 - pt_BR: tts infer type - human_description: - en_US: tts infer type - zh_Hans: 合成方式 - pt_BR: tts infer type - llm_description: tts infer type - options: - - value: PresetVoice - label: - en_US: preset voice - zh_Hans: 预置音色 - - value: CloneVoice - label: - en_US: clone voice - zh_Hans: 克隆音色 - - value: CloneVoice_CrossLingual - label: - en_US: clone crossLingual voice - zh_Hans: 克隆音色(跨语言) - - value: InstructVoice - label: - en_US: instruct voice - zh_Hans: 指令音色 - form: form - - name: voice - type: select - required: false - label: - en_US: preset voice - zh_Hans: 预置音色 - pt_BR: preset voice - human_description: - en_US: preset voice - zh_Hans: 预置音色 - pt_BR: preset voice - llm_description: preset voice - options: - - value: 中文男 - label: - en_US: zh-cn male - zh_Hans: 中文男 - - value: 中文女 - label: - en_US: zh-cn female - zh_Hans: 中文女 - - value: 粤语女 - label: - en_US: zh-TW female - zh_Hans: 粤语女 - form: form - - name: mock_voice_audio - type: string - required: false - label: - en_US: clone voice link - zh_Hans: 克隆音频链接 - pt_BR: clone voice link - human_description: - en_US: clone voice link - zh_Hans: 克隆音频链接 - pt_BR: clone voice link - llm_description: clone voice link - form: llm - - name: mock_voice_text - type: string - required: false - label: - en_US: text of clone voice - zh_Hans: 克隆音频对应文本 - pt_BR: text of clone voice - human_description: - en_US: text of clone voice - zh_Hans: 克隆音频对应文本 - pt_BR: text of clone voice - llm_description: text of clone voice - form: llm - - name: voice_instruct_prompt - type: string - required: false - label: - en_US: instruct prompt for voice - zh_Hans: 音色指令文本 - pt_BR: instruct prompt for voice - human_description: - en_US: instruct prompt for voice - zh_Hans: 音色指令文本 - pt_BR: instruct prompt for voice - llm_description: instruct prompt for voice - form: llm - - name: aws_region - type: string - required: false - label: - en_US: region of sagemaker endpoint - zh_Hans: SageMaker 端点所在的region - pt_BR: region of sagemaker endpoint - human_description: - en_US: region of sagemaker endpoint - zh_Hans: SageMaker 端点所在的region - pt_BR: region of sagemaker endpoint - llm_description: region of sagemaker endpoint - form: form diff --git 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zLbLl~y|3xZ+!bMg6KDlstQ`LsE9X=luT3oo@8PO!kr2$F`M9(SmF!M}3q9+M(QZGza1tD^~URw_}>9N{yIVrkE?$L1_rA~fBJj@+yLKv_wW9rP(M8W`NyY!ec<^Y z|K}I~Kvv)vX9&E0+fu-s{gfSU2&RlktAWKR0)x6wP7E;9BUs{+3G;onJ6VJ_f>hsWl||9hMM725xjz?DB}_FMuS zz4!lY+0(T@=mQKcUHE$}kVx0Y|F13k?;rn$r2m)9u|yi-xN978M1mmTQ<7JcD|uiX F_&;rM#gPC2 diff --git a/api/core/tools/provider/builtin/azuredalle/azuredalle.py b/api/core/tools/provider/builtin/azuredalle/azuredalle.py deleted file mode 100644 index 1fab0d03a28ff3..00000000000000 --- a/api/core/tools/provider/builtin/azuredalle/azuredalle.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.azuredalle.tools.dalle3 import DallE3Tool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class AzureDALLEProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - DallE3Tool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={"prompt": "cute girl, blue eyes, white hair, anime style", "size": "square", "n": 1}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/azuredalle/azuredalle.yaml b/api/core/tools/provider/builtin/azuredalle/azuredalle.yaml deleted file mode 100644 index 4353e0c4862f61..00000000000000 --- a/api/core/tools/provider/builtin/azuredalle/azuredalle.yaml +++ /dev/null @@ -1,76 +0,0 @@ -identity: - author: Leslie - name: azuredalle - label: - en_US: Azure DALL-E - zh_Hans: Azure DALL-E 绘画 - pt_BR: Azure DALL-E - description: - en_US: Azure DALL-E art - zh_Hans: Azure DALL-E 绘画 - pt_BR: Azure DALL-E art - icon: icon.png - tags: - - image - - productivity -credentials_for_provider: - azure_openai_api_key: - type: secret-input - required: true - label: - en_US: API key - zh_Hans: 密钥 - pt_BR: API key - help: - en_US: Please input your Azure OpenAI API key - zh_Hans: 请输入你的 Azure OpenAI API key - pt_BR: Introduza a sua chave de API OpenAI do Azure - placeholder: - en_US: Please input your Azure OpenAI API key - zh_Hans: 请输入你的 Azure OpenAI API key - pt_BR: Introduza a sua chave de API OpenAI do Azure - azure_openai_api_model_name: - type: text-input - required: true - label: - en_US: Deployment Name - zh_Hans: 部署名称 - pt_BR: Nome da Implantação - help: - en_US: Please input the name of your Azure Openai DALL-E API deployment - zh_Hans: 请输入你的 Azure Openai DALL-E API 部署名称 - pt_BR: Insira o nome da implantação da API DALL-E do Azure Openai - placeholder: - en_US: Please input the name of your Azure Openai DALL-E API deployment - zh_Hans: 请输入你的 Azure Openai DALL-E API 部署名称 - pt_BR: Insira o nome da implantação da API DALL-E do Azure Openai - azure_openai_base_url: - type: text-input - required: true - label: - en_US: API Endpoint URL - zh_Hans: API 域名 - pt_BR: API Endpoint URL - help: - en_US: Please input your Azure OpenAI Endpoint URL, e.g. https://xxx.openai.azure.com/ - zh_Hans: 请输入你的 Azure OpenAI API域名，例如：https://xxx.openai.azure.com/ - pt_BR: Introduza a URL do Azure OpenAI Endpoint, e.g. https://xxx.openai.azure.com/ - placeholder: - en_US: Please input your Azure OpenAI Endpoint URL, e.g. https://xxx.openai.azure.com/ - zh_Hans: 请输入你的 Azure OpenAI API域名，例如：https://xxx.openai.azure.com/ - pt_BR: Introduza a URL do Azure OpenAI Endpoint, e.g. https://xxx.openai.azure.com/ - azure_openai_api_version: - type: text-input - required: true - label: - en_US: API Version - zh_Hans: API 版本 - pt_BR: API Version - help: - en_US: Please input your Azure OpenAI API Version,e.g. 2023-12-01-preview - zh_Hans: 请输入你的 Azure OpenAI API 版本，例如：2023-12-01-preview - pt_BR: Introduza a versão da API OpenAI do Azure,e.g. 2023-12-01-preview - placeholder: - en_US: Please input your Azure OpenAI API Version,e.g. 2023-12-01-preview - zh_Hans: 请输入你的 Azure OpenAI API 版本，例如：2023-12-01-preview - pt_BR: Introduza a versão da API OpenAI do Azure,e.g. 2023-12-01-preview diff --git a/api/core/tools/provider/builtin/azuredalle/tools/dalle3.py b/api/core/tools/provider/builtin/azuredalle/tools/dalle3.py deleted file mode 100644 index cfa3cfb092803a..00000000000000 --- a/api/core/tools/provider/builtin/azuredalle/tools/dalle3.py +++ /dev/null @@ -1,83 +0,0 @@ -import random -from base64 import b64decode -from typing import Any, Union - -from openai import AzureOpenAI - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DallE3Tool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - client = AzureOpenAI( - api_version=self.runtime.credentials["azure_openai_api_version"], - azure_endpoint=self.runtime.credentials["azure_openai_base_url"], - api_key=self.runtime.credentials["azure_openai_api_key"], - ) - - SIZE_MAPPING = { - "square": "1024x1024", - "vertical": "1024x1792", - "horizontal": "1792x1024", - } - - # prompt - prompt = tool_parameters.get("prompt", "") - if not prompt: - return self.create_text_message("Please input prompt") - # get size - size = SIZE_MAPPING[tool_parameters.get("size", "square")] - # get n - n = tool_parameters.get("n", 1) - # get quality - quality = tool_parameters.get("quality", "standard") - if quality not in {"standard", "hd"}: - return self.create_text_message("Invalid quality") - # get style - style = tool_parameters.get("style", "vivid") - if style not in {"natural", "vivid"}: - return self.create_text_message("Invalid style") - # set extra body - seed_id = tool_parameters.get("seed_id", self._generate_random_id(8)) - extra_body = {"seed": seed_id} - - # call openapi dalle3 - model = self.runtime.credentials["azure_openai_api_model_name"] - response = client.images.generate( - prompt=prompt, - model=model, - size=size, - n=n, - extra_body=extra_body, - style=style, - quality=quality, - response_format="b64_json", - ) - - result = [] - - for image in response.data: - result.append( - self.create_blob_message( - blob=b64decode(image.b64_json), - meta={"mime_type": "image/png"}, - save_as=self.VariableKey.IMAGE.value, - ) - ) - result.append(self.create_text_message(f"\nGenerate image source to Seed ID: {seed_id}")) - - return result - - @staticmethod - def _generate_random_id(length=8): - characters = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789" - random_id = "".join(random.choices(characters, k=length)) - return random_id diff --git a/api/core/tools/provider/builtin/azuredalle/tools/dalle3.yaml b/api/core/tools/provider/builtin/azuredalle/tools/dalle3.yaml deleted file mode 100644 index e256748e8f7188..00000000000000 --- a/api/core/tools/provider/builtin/azuredalle/tools/dalle3.yaml +++ /dev/null @@ -1,136 +0,0 @@ -identity: - name: azure_dalle3 - author: Leslie - label: - en_US: Azure DALL-E 3 - zh_Hans: Azure DALL-E 3 绘画 - pt_BR: Azure DALL-E 3 - description: - en_US: DALL-E 3 is a powerful drawing tool that can draw the image you want based on your prompt, compared to DallE 2, DallE 3 has stronger drawing ability, but it will consume more resources - zh_Hans: DALL-E 3 是一个强大的绘画工具，它可以根据您的提示词绘制出您想要的图像，相比于DallE 2， DallE 3拥有更强的绘画能力，但会消耗更多的资源 - pt_BR: DALL-E 3 é uma poderosa ferramenta de desenho que pode desenhar a imagem que você deseja com base em seu prompt, em comparação com DallE 2, DallE 3 tem uma capacidade de desenho mais forte, mas consumirá mais recursos -description: - human: - en_US: DALL-E is a text to image tool - zh_Hans: DALL-E 是一个文本到图像的工具 - pt_BR: DALL-E é uma ferramenta de texto para imagem - llm: DALL-E is a tool used to generate images from text -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: Image prompt, you can check the official documentation of DallE 3 - zh_Hans: 图像提示词，您可以查看 DallE 3 的官方文档 - pt_BR: Imagem prompt, você pode verificar a documentação oficial do DallE 3 - llm_description: Image prompt of DallE 3, you should describe the image you want to generate as a list of words as possible as detailed - form: llm - - name: seed_id - type: string - required: false - label: - en_US: Seed ID - zh_Hans: 种子ID - pt_BR: ID da semente - human_description: - en_US: Image generation seed ID to ensure consistency of series generated images - zh_Hans: 图像生成种子ID，确保系列生成图像的一致性 - pt_BR: ID de semente de geração de imagem para garantir a consistência das imagens geradas em série - llm_description: If the user requests image consistency, extract the seed ID from the user's question or context.The seed id consists of an 8-bit string containing uppercase and lowercase letters and numbers - form: llm - - name: size - type: select - required: true - human_description: - en_US: selecting the image size - zh_Hans: 选择图像大小 - pt_BR: seleccionar o tamanho da imagem - label: - en_US: Image size - zh_Hans: 图像大小 - pt_BR: Tamanho da imagem - form: form - options: - - value: square - label: - en_US: Squre(1024x1024) - zh_Hans: 方(1024x1024) - pt_BR: Squire(1024x1024) - - value: vertical - label: - en_US: Vertical(1024x1792) - zh_Hans: 竖屏(1024x1792) - pt_BR: Vertical(1024x1792) - - value: horizontal - label: - en_US: Horizontal(1792x1024) - zh_Hans: 横屏(1792x1024) - pt_BR: Horizontal(1792x1024) - default: square - - name: n - type: number - required: true - human_description: - en_US: selecting the number of images - zh_Hans: 选择图像数量 - pt_BR: seleccionar o número de imagens - label: - en_US: Number of images - zh_Hans: 图像数量 - pt_BR: Número de imagens - form: form - min: 1 - max: 1 - default: 1 - - name: quality - type: select - required: true - human_description: - en_US: selecting the image quality - zh_Hans: 选择图像质量 - pt_BR: seleccionar a qualidade da imagem - label: - en_US: Image quality - zh_Hans: 图像质量 - pt_BR: Qualidade da imagem - form: form - options: - - value: standard - label: - en_US: Standard - zh_Hans: 标准 - pt_BR: Normal - - value: hd - label: - en_US: HD - zh_Hans: 高清 - pt_BR: HD - default: standard - - name: style - type: select - required: true - human_description: - en_US: selecting the image style - zh_Hans: 选择图像风格 - pt_BR: seleccionar o estilo da imagem - label: - en_US: Image style - zh_Hans: 图像风格 - pt_BR: Estilo da imagem - form: form - options: - - value: vivid - label: - en_US: Vivid - zh_Hans: 生动 - pt_BR: Vívido - - value: natural - label: - en_US: Natural - zh_Hans: 自然 - pt_BR: Natural - default: vivid diff --git a/api/core/tools/provider/builtin/bing/_assets/icon.svg b/api/core/tools/provider/builtin/bing/_assets/icon.svg deleted file mode 100644 index a94de7971d35b7..00000000000000 --- a/api/core/tools/provider/builtin/bing/_assets/icon.svg +++ /dev/null @@ -1,40 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/bing/bing.py b/api/core/tools/provider/builtin/bing/bing.py deleted file mode 100644 index c71128be4a784f..00000000000000 --- a/api/core/tools/provider/builtin/bing/bing.py +++ /dev/null @@ -1,23 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.bing.tools.bing_web_search import BingSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class BingProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - BingSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).validate_credentials( - credentials=credentials, - tool_parameters={ - "query": "test", - "result_type": "link", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/bing/bing.yaml b/api/core/tools/provider/builtin/bing/bing.yaml deleted file mode 100644 index 1ab17d5294b37c..00000000000000 --- a/api/core/tools/provider/builtin/bing/bing.yaml +++ /dev/null @@ -1,107 +0,0 @@ -identity: - author: Dify - name: bing - label: - en_US: Bing - zh_Hans: Bing - pt_BR: Bing - description: - en_US: Bing Search - zh_Hans: Bing 搜索 - pt_BR: Bing Search - icon: icon.svg - tags: - - search -credentials_for_provider: - subscription_key: - type: secret-input - required: true - label: - en_US: Bing subscription key - zh_Hans: Bing subscription key - pt_BR: Bing subscription key - placeholder: - en_US: Please input your Bing subscription key - zh_Hans: 请输入你的 Bing subscription key - pt_BR: Please input your Bing subscription key - help: - en_US: Get your Bing subscription key from Bing - zh_Hans: 从 Bing 获取您的 Bing subscription key - pt_BR: Get your Bing subscription key from Bing - url: https://www.microsoft.com/cognitive-services/en-us/bing-web-search-api - server_url: - type: text-input - required: false - label: - en_US: Bing endpoint - zh_Hans: Bing endpoint - pt_BR: Bing endpoint - placeholder: - en_US: Please input your Bing endpoint - zh_Hans: 请输入你的 Bing 端点 - pt_BR: Please input your Bing endpoint - help: - en_US: An endpoint is like "https://api.bing.microsoft.com/v7.0/search" - zh_Hans: 例如 "https://api.bing.microsoft.com/v7.0/search" - pt_BR: An endpoint is like "https://api.bing.microsoft.com/v7.0/search" - default: https://api.bing.microsoft.com/v7.0/search - allow_entities: - type: boolean - required: false - label: - en_US: Allow Entities Search - zh_Hans: 支持实体搜索 - pt_BR: Allow Entities Search - help: - en_US: Does your subscription plan allow entity search - zh_Hans: 您的订阅计划是否支持实体搜索 - pt_BR: Does your subscription plan allow entity search - default: true - allow_web_pages: - type: boolean - required: false - label: - en_US: Allow Web Pages Search - zh_Hans: 支持网页搜索 - pt_BR: Allow Web Pages Search - help: - en_US: Does your subscription plan allow web pages search - zh_Hans: 您的订阅计划是否支持网页搜索 - pt_BR: Does your subscription plan allow web pages search - default: true - allow_computation: - type: boolean - required: false - label: - en_US: Allow Computation Search - zh_Hans: 支持计算搜索 - pt_BR: Allow Computation Search - help: - en_US: Does your subscription plan allow computation search - zh_Hans: 您的订阅计划是否支持计算搜索 - pt_BR: Does your subscription plan allow computation search - default: false - allow_news: - type: boolean - required: false - label: - en_US: Allow News Search - zh_Hans: 支持新闻搜索 - pt_BR: Allow News Search - help: - en_US: Does your subscription plan allow news search - zh_Hans: 您的订阅计划是否支持新闻搜索 - pt_BR: Does your subscription plan allow news search - default: false - allow_related_searches: - type: boolean - required: false - label: - en_US: Allow Related Searches - zh_Hans: 支持相关搜索 - pt_BR: Allow Related Searches - help: - en_US: Does your subscription plan allow related searches - zh_Hans: 您的订阅计划是否支持相关搜索 - pt_BR: Does your subscription plan allow related searches - default: false diff --git a/api/core/tools/provider/builtin/bing/tools/bing_web_search.py b/api/core/tools/provider/builtin/bing/tools/bing_web_search.py deleted file mode 100644 index 8bed2c556cf879..00000000000000 --- a/api/core/tools/provider/builtin/bing/tools/bing_web_search.py +++ /dev/null @@ -1,202 +0,0 @@ -from typing import Any, Union -from urllib.parse import quote - -from requests import get - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class BingSearchTool(BuiltinTool): - url: str = "https://api.bing.microsoft.com/v7.0/search" - - def _invoke_bing( - self, - user_id: str, - server_url: str, - subscription_key: str, - query: str, - limit: int, - result_type: str, - market: str, - lang: str, - filters: list[str], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke bing search - """ - market_code = f"{lang}-{market}" - accept_language = f"{lang},{market_code};q=0.9" - headers = {"Ocp-Apim-Subscription-Key": subscription_key, "Accept-Language": accept_language} - - query = quote(query) - server_url = f'{server_url}?q={query}&mkt={market_code}&count={limit}&responseFilter={",".join(filters)}' - response = get(server_url, headers=headers) - - if response.status_code != 200: - raise Exception(f"Error {response.status_code}: {response.text}") - - response = response.json() - search_results = response["webPages"]["value"][:limit] if "webPages" in response else [] - related_searches = response["relatedSearches"]["value"] if "relatedSearches" in response else [] - entities = response["entities"]["value"] if "entities" in response else [] - news = response["news"]["value"] if "news" in response else [] - computation = response["computation"]["value"] if "computation" in response else None - - if result_type == "link": - results = [] - if search_results: - for result in search_results: - url = f': {result["url"]}' if "url" in result else "" - results.append(self.create_text_message(text=f'{result["name"]}{url}')) - - if entities: - for entity in entities: - url = f': {entity["url"]}' if "url" in entity else "" - results.append(self.create_text_message(text=f'{entity.get("name", "")}{url}')) - - if news: - for news_item in news: - url = f': {news_item["url"]}' if "url" in news_item else "" - results.append(self.create_text_message(text=f'{news_item.get("name", "")}{url}')) - - if related_searches: - for related in related_searches: - url = f': {related["displayText"]}' if "displayText" in related else "" - results.append(self.create_text_message(text=f'{related.get("displayText", "")}{url}')) - - return results - else: - # construct text - text = "" - if search_results: - for i, result in enumerate(search_results): - text += f'{i + 1}: {result.get("name", "")} - {result.get("snippet", "")}\n' - - if computation and "expression" in computation and "value" in computation: - text += "\nComputation:\n" - text += f'{computation["expression"]} = {computation["value"]}\n' - - if entities: - text += "\nEntities:\n" - for entity in entities: - url = f'- {entity["url"]}' if "url" in entity else "" - text += f'{entity.get("name", "")}{url}\n' - - if news: - text += "\nNews:\n" - for news_item in news: - url = f'- {news_item["url"]}' if "url" in news_item else "" - text += f'{news_item.get("name", "")}{url}\n' - - if related_searches: - text += "\n\nRelated Searches:\n" - for related in related_searches: - url = f'- {related["webSearchUrl"]}' if "webSearchUrl" in related else "" - text += f'{related.get("displayText", "")}{url}\n' - - return self.create_text_message(text=self.summary(user_id=user_id, content=text)) - - def validate_credentials(self, credentials: dict[str, Any], tool_parameters: dict[str, Any]) -> None: - key = credentials.get("subscription_key") - if not key: - raise Exception("subscription_key is required") - - server_url = credentials.get("server_url") - if not server_url: - server_url = self.url - - query = tool_parameters.get("query") - if not query: - raise Exception("query is required") - - limit = min(tool_parameters.get("limit", 5), 10) - result_type = tool_parameters.get("result_type", "text") or "text" - - market = tool_parameters.get("market", "US") - lang = tool_parameters.get("language", "en") - filter = [] - - if credentials.get("allow_entities", False): - filter.append("Entities") - - if credentials.get("allow_computation", False): - filter.append("Computation") - - if credentials.get("allow_news", False): - filter.append("News") - - if credentials.get("allow_related_searches", False): - filter.append("RelatedSearches") - - if credentials.get("allow_web_pages", False): - filter.append("WebPages") - - if not filter: - raise Exception("At least one filter is required") - - self._invoke_bing( - user_id="test", - server_url=server_url, - subscription_key=key, - query=query, - limit=limit, - result_type=result_type, - market=market, - lang=lang, - filters=filter, - ) - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - - key = self.runtime.credentials.get("subscription_key", None) - if not key: - raise Exception("subscription_key is required") - - server_url = self.runtime.credentials.get("server_url", None) - if not server_url: - server_url = self.url - - query = tool_parameters.get("query") - if not query: - raise Exception("query is required") - - limit = min(tool_parameters.get("limit", 5), 10) - result_type = tool_parameters.get("result_type", "text") or "text" - - market = tool_parameters.get("market", "US") - lang = tool_parameters.get("language", "en") - filter = [] - - if tool_parameters.get("enable_computation", False): - filter.append("Computation") - if tool_parameters.get("enable_entities", False): - filter.append("Entities") - if tool_parameters.get("enable_news", False): - filter.append("News") - if tool_parameters.get("enable_related_search", False): - filter.append("RelatedSearches") - if tool_parameters.get("enable_webpages", False): - filter.append("WebPages") - - if not filter: - raise Exception("At least one filter is required") - - return self._invoke_bing( - user_id=user_id, - server_url=server_url, - subscription_key=key, - query=query, - limit=limit, - result_type=result_type, - market=market, - lang=lang, - filters=filter, - ) diff --git a/api/core/tools/provider/builtin/bing/tools/bing_web_search.yaml b/api/core/tools/provider/builtin/bing/tools/bing_web_search.yaml deleted file mode 100644 index a3f60bb09b6509..00000000000000 --- a/api/core/tools/provider/builtin/bing/tools/bing_web_search.yaml +++ /dev/null @@ -1,584 +0,0 @@ -identity: - name: bing_web_search - author: Dify - label: - en_US: BingWebSearch - zh_Hans: 必应网页搜索 - pt_BR: BingWebSearch -description: - human: - en_US: A tool for performing a Bing SERP search and extracting snippets and webpages.Input should be a search query. - zh_Hans: 一个用于执行 Bing SERP 搜索并提取片段和网页的工具。输入应该是一个搜索查询。 - pt_BR: A tool for performing a Bing SERP search and extracting snippets and webpages.Input should be a search query. - llm: A tool for performing a Bing SERP search and extracting snippets and webpages.Input should be a search query. -parameters: - - name: query - type: string - required: true - form: llm - label: - en_US: Query string - zh_Hans: 查询语句 - pt_BR: Query string - human_description: - en_US: used for searching - zh_Hans: 用于搜索网页内容 - pt_BR: used for searching - llm_description: key words for searching - - name: enable_computation - type: boolean - required: false - form: form - label: - en_US: Enable computation - zh_Hans: 启用计算 - pt_BR: Enable computation - human_description: - en_US: enable computation - zh_Hans: 启用计算 - pt_BR: enable computation - default: false - - name: enable_entities - type: boolean - required: false - form: form - label: - en_US: Enable entities - zh_Hans: 启用实体搜索 - pt_BR: Enable entities - human_description: - en_US: enable entities - zh_Hans: 启用实体搜索 - pt_BR: enable entities - default: true - - name: enable_news - type: boolean - required: false - form: form - label: - en_US: Enable news - zh_Hans: 启用新闻搜索 - pt_BR: Enable news - human_description: - en_US: enable news - zh_Hans: 启用新闻搜索 - pt_BR: enable news - default: false - - name: enable_related_search - type: boolean - required: false - form: form - label: - en_US: Enable related search - zh_Hans: 启用相关搜索 - pt_BR: Enable related search - human_description: - en_US: enable related search - zh_Hans: 启用相关搜索 - pt_BR: enable related search - default: false - - name: enable_webpages - type: boolean - required: false - form: form - label: - en_US: Enable webpages search - zh_Hans: 启用网页搜索 - pt_BR: Enable webpages search - human_description: - en_US: enable webpages search - zh_Hans: 启用网页搜索 - pt_BR: enable webpages search - default: true - - name: limit - type: number - required: true - form: form - label: - en_US: Limit for results length - zh_Hans: 返回长度限制 - pt_BR: Limit for results length - human_description: - en_US: limit the number of results - zh_Hans: 限制返回结果的数量 - pt_BR: limit the number of results - min: 1 - max: 10 - default: 5 - - name: result_type - type: select - required: true - label: - en_US: result type - zh_Hans: 结果类型 - pt_BR: result type - human_description: - en_US: return a list of links or texts - zh_Hans: 返回一个连接列表还是纯文本内容 - pt_BR: return a list of links or texts - default: text - options: - - value: link - label: - en_US: Link - zh_Hans: 链接 - pt_BR: Link - - value: text - label: - en_US: Text - zh_Hans: 文本 - pt_BR: Text - form: form - - name: market - type: select - label: - en_US: Market - zh_Hans: 市场 - pt_BR: Market - human_description: - en_US: market takes responsibility for the region - zh_Hans: 市场决定了搜索结果的地区 - pt_BR: market takes responsibility for the region - required: false - form: form - default: US - options: - - value: AR - label: - en_US: Argentina - zh_Hans: 阿根廷 - pt_BR: Argentina - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: AT - label: - en_US: Austria - zh_Hans: 奥地利 - pt_BR: Austria - - value: BE - label: - en_US: Belgium - zh_Hans: 比利时 - pt_BR: Belgium - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: CL - label: - en_US: Chile - zh_Hans: 智利 - pt_BR: Chile - - value: CO - label: - en_US: Colombia - zh_Hans: 哥伦比亚 - pt_BR: Colombia - - value: CN - label: - en_US: China - zh_Hans: 中国 - pt_BR: China - - value: CZ - label: - en_US: Czech Republic - zh_Hans: 捷克共和国 - pt_BR: Czech Republic - - value: DK - label: - en_US: Denmark - zh_Hans: 丹麦 - pt_BR: Denmark - - value: FI - label: - en_US: Finland - zh_Hans: 芬兰 - pt_BR: Finland - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: HK - label: - en_US: Hong Kong - zh_Hans: 香港 - pt_BR: Hong Kong - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: ID - label: - en_US: Indonesia - zh_Hans: 印度尼西亚 - pt_BR: Indonesia - - value: IT - label: - en_US: Italy - zh_Hans: 意大利 - pt_BR: Italy - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: MY - label: - en_US: Malaysia - zh_Hans: 马来西亚 - pt_BR: Malaysia - - value: MX - label: - en_US: Mexico - zh_Hans: 墨西哥 - pt_BR: Mexico - - value: NL - label: - en_US: Netherlands - zh_Hans: 荷兰 - pt_BR: Netherlands - - value: NZ - label: - en_US: New Zealand - zh_Hans: 新西兰 - pt_BR: New Zealand - - value: 'NO' - label: - en_US: Norway - zh_Hans: 挪威 - pt_BR: Norway - - value: PH - label: - en_US: Philippines - zh_Hans: 菲律宾 - pt_BR: Philippines - - value: PL - label: - en_US: Poland - zh_Hans: 波兰 - pt_BR: Poland - - value: PT - label: - en_US: Portugal - zh_Hans: 葡萄牙 - pt_BR: Portugal - - value: RU - label: - en_US: Russia - zh_Hans: 俄罗斯 - pt_BR: Russia - - value: SA - label: - en_US: Saudi Arabia - zh_Hans: 沙特阿拉伯 - pt_BR: Saudi Arabia - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: ZA - label: - en_US: South Africa - zh_Hans: 南非 - pt_BR: South Africa - - value: ES - label: - en_US: Spain - zh_Hans: 西班牙 - pt_BR: Spain - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - value: CH - label: - en_US: Switzerland - zh_Hans: 瑞士 - pt_BR: Switzerland - - value: TW - label: - en_US: Taiwan - zh_Hans: 台湾 - pt_BR: Taiwan - - value: TH - label: - en_US: Thailand - zh_Hans: 泰国 - pt_BR: Thailand - - value: TR - label: - en_US: Turkey - zh_Hans: 土耳其 - pt_BR: Turkey - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - name: language - type: select - label: - en_US: Language - zh_Hans: 语言 - pt_BR: Language - human_description: - en_US: language takes responsibility for the language of the search result - zh_Hans: 语言决定了搜索结果的语言 - pt_BR: language takes responsibility for the language of the search result - required: false - default: en - form: form - options: - - value: ar - label: - en_US: Arabic - zh_Hans: 阿拉伯语 - pt_BR: Arabic - - value: bg - label: - en_US: Bulgarian - zh_Hans: 保加利亚语 - pt_BR: Bulgarian - - value: ca - label: - en_US: Catalan - zh_Hans: 加泰罗尼亚语 - pt_BR: Catalan - - value: zh-hans - label: - en_US: Chinese (Simplified) - zh_Hans: 中文（简体） - pt_BR: Chinese (Simplified) - - value: zh-hant - label: - en_US: Chinese (Traditional) - zh_Hans: 中文（繁体） - pt_BR: Chinese (Traditional) - - value: cs - label: - en_US: Czech - zh_Hans: 捷克语 - pt_BR: Czech - - value: da - label: - en_US: Danish - zh_Hans: 丹麦语 - pt_BR: Danish - - value: nl - label: - en_US: Dutch - zh_Hans: 荷兰语 - pt_BR: Dutch - - value: en - label: - en_US: English - zh_Hans: 英语 - pt_BR: English - - value: et - label: - en_US: Estonian - zh_Hans: 爱沙尼亚语 - pt_BR: Estonian - - value: fi - label: - en_US: Finnish - zh_Hans: 芬兰语 - pt_BR: Finnish - - value: fr - label: - en_US: French - zh_Hans: 法语 - pt_BR: French - - value: de - label: - en_US: German - zh_Hans: 德语 - pt_BR: German - - value: el - label: - en_US: Greek - zh_Hans: 希腊语 - pt_BR: Greek - - value: he - label: - en_US: Hebrew - zh_Hans: 希伯来语 - pt_BR: Hebrew - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - pt_BR: Hindi - - value: hu - label: - en_US: Hungarian - zh_Hans: 匈牙利语 - pt_BR: Hungarian - - value: id - label: - en_US: Indonesian - zh_Hans: 印尼语 - pt_BR: Indonesian - - value: it - label: - en_US: Italian - zh_Hans: 意大利语 - pt_BR: Italian - - value: jp - label: - en_US: Japanese - zh_Hans: 日语 - pt_BR: Japanese - - value: kn - label: - en_US: Kannada - zh_Hans: 卡纳达语 - pt_BR: Kannada - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - pt_BR: Korean - - value: lv - label: - en_US: Latvian - zh_Hans: 拉脱维亚语 - pt_BR: Latvian - - value: lt - label: - en_US: Lithuanian - zh_Hans: 立陶宛语 - pt_BR: Lithuanian - - value: ms - label: - en_US: Malay - zh_Hans: 马来语 - pt_BR: Malay - - value: ml - label: - en_US: Malayalam - zh_Hans: 马拉雅拉姆语 - pt_BR: Malayalam - - value: mr - label: - en_US: Marathi - zh_Hans: 马拉地语 - pt_BR: Marathi - - value: nb - label: - en_US: Norwegian - zh_Hans: 挪威语 - pt_BR: Norwegian - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - pt_BR: Polish - - value: pt-br - label: - en_US: Portuguese (Brazil) - zh_Hans: 葡萄牙语（巴西） - pt_BR: Portuguese (Brazil) - - value: pt-pt - label: - en_US: Portuguese (Portugal) - zh_Hans: 葡萄牙语（葡萄牙） - pt_BR: Portuguese (Portugal) - - value: pa - label: - en_US: Punjabi - zh_Hans: 旁遮普语 - pt_BR: Punjabi - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - pt_BR: Romanian - - value: ru - label: - en_US: Russian - zh_Hans: 俄语 - pt_BR: Russian - - value: sr - label: - en_US: Serbian - zh_Hans: 塞尔维亚语 - pt_BR: Serbian - - value: sk - label: - en_US: Slovak - zh_Hans: 斯洛伐克语 - pt_BR: Slovak - - value: sl - label: - en_US: Slovenian - zh_Hans: 斯洛文尼亚语 - pt_BR: Slovenian - - value: es - label: - en_US: Spanish - zh_Hans: 西班牙语 - pt_BR: Spanish - - value: sv - label: - en_US: Swedish - zh_Hans: 瑞典语 - pt_BR: Swedish - - value: ta - label: - en_US: Tamil - zh_Hans: 泰米尔语 - pt_BR: Tamil - - value: te - label: - en_US: Telugu - zh_Hans: 泰卢固语 - pt_BR: Telugu - - value: th - label: - en_US: Thai - zh_Hans: 泰语 - pt_BR: Thai - - value: tr - label: - en_US: Turkish - zh_Hans: 土耳其语 - pt_BR: Turkish - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - pt_BR: Ukrainian - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 - pt_BR: Vietnamese diff --git a/api/core/tools/provider/builtin/brave/_assets/icon.svg b/api/core/tools/provider/builtin/brave/_assets/icon.svg deleted file mode 100644 index d059f7c5161e98..00000000000000 --- a/api/core/tools/provider/builtin/brave/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/brave/brave.py b/api/core/tools/provider/builtin/brave/brave.py deleted file mode 100644 index c24ee67334083b..00000000000000 --- a/api/core/tools/provider/builtin/brave/brave.py +++ /dev/null @@ -1,22 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.brave.tools.brave_search import BraveSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class BraveProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - BraveSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "query": "Sachin Tendulkar", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/brave/brave.yaml b/api/core/tools/provider/builtin/brave/brave.yaml deleted file mode 100644 index 2b0dcc0188caf8..00000000000000 --- a/api/core/tools/provider/builtin/brave/brave.yaml +++ /dev/null @@ -1,39 +0,0 @@ -identity: - author: Yash Parmar - name: brave - label: - en_US: Brave - zh_Hans: Brave - pt_BR: Brave - description: - en_US: Brave - zh_Hans: Brave - pt_BR: Brave - icon: icon.svg - tags: - - search -credentials_for_provider: - brave_search_api_key: - type: secret-input - required: true - label: - en_US: Brave Search API key - zh_Hans: Brave Search API key - pt_BR: Brave Search API key - placeholder: - en_US: Please input your Brave Search API key - zh_Hans: 请输入你的 Brave Search API key - pt_BR: Please input your Brave Search API key - help: - en_US: Get your Brave Search API key from Brave - zh_Hans: 从 Brave 获取您的 Brave Search API key - pt_BR: Get your Brave Search API key from Brave - url: https://brave.com/search/api/ - base_url: - type: text-input - required: false - label: - en_US: Brave server's Base URL - zh_Hans: Brave服务器的API URL - placeholder: - en_US: https://api.search.brave.com/res/v1/web/search diff --git a/api/core/tools/provider/builtin/brave/tools/brave_search.py b/api/core/tools/provider/builtin/brave/tools/brave_search.py deleted file mode 100644 index c34362ae52ecac..00000000000000 --- a/api/core/tools/provider/builtin/brave/tools/brave_search.py +++ /dev/null @@ -1,138 +0,0 @@ -import json -from typing import Any, Optional - -import requests -from pydantic import BaseModel, Field - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -BRAVE_BASE_URL = "https://api.search.brave.com/res/v1/web/search" - - -class BraveSearchWrapper(BaseModel): - """Wrapper around the Brave search engine.""" - - api_key: str - """The API key to use for the Brave search engine.""" - search_kwargs: dict = Field(default_factory=dict) - """Additional keyword arguments to pass to the search request.""" - base_url: str = BRAVE_BASE_URL - """The base URL for the Brave search engine.""" - ensure_ascii: bool = True - """Ensure the JSON output is ASCII encoded.""" - - def run(self, query: str) -> str: - """Query the Brave search engine and return the results as a JSON string. - - Args: - query: The query to search for. - - Returns: The results as a JSON string. - - """ - web_search_results = self._search_request(query=query) - final_results = [ - { - "title": item.get("title"), - "link": item.get("url"), - "snippet": item.get("description"), - } - for item in web_search_results - ] - return json.dumps(final_results, ensure_ascii=self.ensure_ascii) - - def _search_request(self, query: str) -> list[dict]: - headers = { - "X-Subscription-Token": self.api_key, - "Accept": "application/json", - } - req = requests.PreparedRequest() - params = {**self.search_kwargs, **{"q": query}} - req.prepare_url(self.base_url, params) - if req.url is None: - raise ValueError("prepared url is None, this should not happen") - - response = requests.get(req.url, headers=headers) - if not response.ok: - raise Exception(f"HTTP error {response.status_code}") - - return response.json().get("web", {}).get("results", []) - - -class BraveSearch(BaseModel): - """Tool that queries the BraveSearch.""" - - name: str = "brave_search" - description: str = ( - "a search engine. " - "useful for when you need to answer questions about current events." - " input should be a search query." - ) - search_wrapper: BraveSearchWrapper - - @classmethod - def from_api_key( - cls, api_key: str, base_url: str, search_kwargs: Optional[dict] = None, ensure_ascii: bool = True, **kwargs: Any - ) -> "BraveSearch": - """Create a tool from an api key. - - Args: - api_key: The api key to use. - search_kwargs: Any additional kwargs to pass to the search wrapper. - **kwargs: Any additional kwargs to pass to the tool. - - Returns: - A tool. - """ - wrapper = BraveSearchWrapper( - api_key=api_key, base_url=base_url, search_kwargs=search_kwargs or {}, ensure_ascii=ensure_ascii - ) - return cls(search_wrapper=wrapper, **kwargs) - - def _run( - self, - query: str, - ) -> str: - """Use the tool.""" - return self.search_wrapper.run(query) - - -class BraveSearchTool(BuiltinTool): - """ - Tool for performing a search using Brave search engine. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: - """ - Invoke the Brave search tool. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Any]): The parameters for the tool invocation. - - Returns: - ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation. - """ - query = tool_parameters.get("query", "") - count = tool_parameters.get("count", 3) - api_key = self.runtime.credentials["brave_search_api_key"] - base_url = self.runtime.credentials.get("base_url", BRAVE_BASE_URL) - ensure_ascii = tool_parameters.get("ensure_ascii", True) - - if len(base_url) == 0: - base_url = BRAVE_BASE_URL - - if not query: - return self.create_text_message("Please input query") - - tool = BraveSearch.from_api_key( - api_key=api_key, base_url=base_url, search_kwargs={"count": count}, ensure_ascii=ensure_ascii - ) - - results = tool._run(query) - - if not results: - return self.create_text_message(f"No results found for '{query}' in Tavily") - else: - return self.create_text_message(text=results) diff --git a/api/core/tools/provider/builtin/brave/tools/brave_search.yaml b/api/core/tools/provider/builtin/brave/tools/brave_search.yaml deleted file mode 100644 index 5222a375f84cee..00000000000000 --- a/api/core/tools/provider/builtin/brave/tools/brave_search.yaml +++ /dev/null @@ -1,53 +0,0 @@ -identity: - name: brave_search - author: Yash Parmar - label: - en_US: BraveSearch - zh_Hans: BraveSearch - pt_BR: BraveSearch -description: - human: - en_US: BraveSearch is a privacy-focused search engine that leverages its own index to deliver unbiased, independent, and fast search results. It's designed to respect user privacy by not tracking searches or personal information, making it a secure choice for those concerned about online privacy. - zh_Hans: BraveSearch 是一个注重隐私的搜索引擎，它利用自己的索引来提供公正、独立和快速的搜索结果。它旨在通过不跟踪搜索或个人信息来尊重用户隐私，为那些关注在线隐私的用户提供了一个安全的选择。 - pt_BR: BraveSearch é um mecanismo de busca focado na privacidade que utiliza seu próprio índice para entregar resultados de busca imparciais, independentes e rápidos. Ele é projetado para respeitar a privacidade do usuário, não rastreando buscas ou informações pessoais, tornando-se uma escolha segura para aqueles preocupados com a privacidade online. - llm: BraveSearch is a privacy-centric search engine utilizing its unique index to offer unbiased, independent, and swift search results. It aims to protect user privacy by avoiding the tracking of search activities or personal data, presenting a secure option for users mindful of their online privacy. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - pt_BR: Query string - human_description: - en_US: The text input used for initiating searches on the web, focusing on delivering relevant and accurate results without compromising user privacy. - zh_Hans: 用于在网上启动搜索的文本输入，专注于提供相关且准确的结果，同时不妨碍用户隐私。 - pt_BR: A entrada de texto usada para iniciar pesquisas na web, focada em entregar resultados relevantes e precisos sem comprometer a privacidade do usuário. - llm_description: Keywords or phrases entered to perform searches, aimed at providing relevant and precise results while ensuring the privacy of the user is maintained. - form: llm - - name: count - type: number - required: false - default: 3 - label: - en_US: Result count - zh_Hans: 结果数量 - pt_BR: Contagem de resultados - human_description: - en_US: The number of search results to return, allowing users to control the breadth of their search output. - zh_Hans: 要返回的搜索结果数量，允许用户控制他们搜索输出的广度。 - pt_BR: O número de resultados de pesquisa a serem retornados, permitindo que os usuários controlem a amplitude de sua saída de pesquisa. - llm_description: Specifies the amount of search results to be displayed, offering users the ability to adjust the scope of their search findings. - form: llm - - name: ensure_ascii - type: boolean - default: true - label: - en_US: Ensure ASCII - zh_Hans: 确保 ASCII - pt_BR: Ensure ASCII - human_description: - en_US: Ensure the JSON output is ASCII encoded - zh_Hans: 确保输出的 JSON 是 ASCII 编码 - pt_BR: Ensure the JSON output is ASCII encoded - form: form diff --git a/api/core/tools/provider/builtin/chart/_assets/icon.png b/api/core/tools/provider/builtin/chart/_assets/icon.png deleted file mode 100644 index 878e56a0512c31735cc94480cef9b8fa5dfcc7fd..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1363 zcmV-Z1+4msP)@~0drDELIAGL9O(c600d`2O+f$vv5yPZ%b}MY?$!^0(ngoeR2q9r8kU$C`L_-DtfaD*9CP;uHKKjH23JN5$ zO@wH&siIUi)k2y$o9xEPdgkUHCytc)wtdgs8}0i@QMBXn%<6sS+!@~)?;!#J0I*+C zG$-9||Ip68MmGxRXie)it!i!3`Vj30lo~1>4b1ym5?c5a+MP{ zE+hQKUK))%WlB{&I^(BTW)yh0pLXB!!n1Fb!iGKEuKAGJZ{Je`(>f_^a3UNDA)+ z$CYCQE!I$tE=K{)v zarWn1)+G28KI2qC*)aH@4GF%5&o~n>YZ!}4@G*SGiGX>-m{)?Y;WL#BSTu}TCHNdZ zQ>g%3VU(5Nd-zPEUf+CYOXN3_2xGF%kIgopPv0ivTljzezWP|^l~jP#kyum-J|Fp0 z#05wX19=i8_GcSW0acB`WhD3*J|iZe>Jwm|1Yg5v!~`69Wx4V(I88!-u;*>~jMyEq zm6hbCt2h#Q+h@MpesnWO@@|$5#46zGwa1?%sCpRS;C&CD5vzddqa1uB4u=t4`sZ$` z@LSCq9eHgz^Yz<1nlAl4B3o3wzc`{d z9PjQ4x0=P%%FUL&d%{)kFAg3}bPNPI1_B%d0gizH$3TE%AiyyY;1~#S3S3V5l#RJ_iM#q0RGKU-i3ats7G z1_B%d0gizH$3TE%AiyyY;1~#SjM!Afx!-n37d%jQ{=&`^`#xJ#_9Z>=04HD41KB`; zV^aQfv6`zP87M$ujHpOaXi@;6{{?FhA2~o_W26bEhIEWfKJNLBi}z zGBeo~^%O=!X927>bY^%%d% None: - try: - LinearChartTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "data": "1,3,5,7,9,2,4,6,8,10", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/chart/chart.yaml b/api/core/tools/provider/builtin/chart/chart.yaml deleted file mode 100644 index ad0d9a6cd688cf..00000000000000 --- a/api/core/tools/provider/builtin/chart/chart.yaml +++ /dev/null @@ -1,17 +0,0 @@ -identity: - author: Dify - name: chart - label: - en_US: ChartGenerator - zh_Hans: 图表生成 - pt_BR: Gerador de gráficos - description: - en_US: Chart Generator is a tool for generating statistical charts like bar chart, line chart, pie chart, etc. - zh_Hans: 图表生成是一个用于生成可视化图表的工具，你可以通过它来生成柱状图、折线图、饼图等各类图表 - pt_BR: O Gerador de gráficos é uma ferramenta para gerar gráficos estatísticos como gráfico de barras, gráfico de linhas, gráfico de pizza, etc. - icon: icon.png - tags: - - design - - productivity - - utilities -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/chart/tools/bar.py b/api/core/tools/provider/builtin/chart/tools/bar.py deleted file mode 100644 index 3a47c0cfc0d47f..00000000000000 --- a/api/core/tools/provider/builtin/chart/tools/bar.py +++ /dev/null @@ -1,48 +0,0 @@ -import io -from typing import Any, Union - -import matplotlib.pyplot as plt - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class BarChartTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - data = tool_parameters.get("data", "") - if not data: - return self.create_text_message("Please input data") - data = data.split(";") - - # if all data is int, convert to int - if all(i.isdigit() for i in data): - data = [int(i) for i in data] - else: - data = [float(i) for i in data] - - axis = tool_parameters.get("x_axis") or None - if axis: - axis = axis.split(";") - if len(axis) != len(data): - axis = None - - flg, ax = plt.subplots(figsize=(10, 8)) - - if axis: - axis = [label[:10] + "..." if len(label) > 10 else label for label in axis] - ax.set_xticklabels(axis, rotation=45, ha="right") - ax.bar(axis, data) - else: - ax.bar(range(len(data)), data) - - buf = io.BytesIO() - flg.savefig(buf, format="png") - buf.seek(0) - plt.close(flg) - - return [ - self.create_text_message("the bar chart is saved as an image."), - self.create_blob_message(blob=buf.read(), meta={"mime_type": "image/png"}), - ] diff --git a/api/core/tools/provider/builtin/chart/tools/bar.yaml b/api/core/tools/provider/builtin/chart/tools/bar.yaml deleted file mode 100644 index ee7405f6810efa..00000000000000 --- a/api/core/tools/provider/builtin/chart/tools/bar.yaml +++ /dev/null @@ -1,41 +0,0 @@ -identity: - name: bar_chart - author: Dify - label: - en_US: Bar Chart - zh_Hans: 柱状图 - pt_BR: Gráfico de barras - icon: icon.svg -description: - human: - en_US: Bar chart - zh_Hans: 柱状图 - pt_BR: Gráfico de barras - llm: generate a bar chart with input data -parameters: - - name: data - type: string - required: true - label: - en_US: data - zh_Hans: 数据 - pt_BR: dados - human_description: - en_US: data for generating chart, each number should be separated by ";" - zh_Hans: 用于生成柱状图的数据，每个数字之间用 ";" 分隔 - pt_BR: dados para gerar gráfico de barras, cada número deve ser separado por ";" - llm_description: data for generating bar chart, data should be a string contains a list of numbers like "1;2;3;4;5" - form: llm - - name: x_axis - type: string - required: false - label: - en_US: X Axis - zh_Hans: x 轴 - pt_BR: Eixo X - human_description: - en_US: X axis for chart, each text should be separated by ";" - zh_Hans: 柱状图的 x 轴，每个文本之间用 ";" 分隔 - pt_BR: Eixo X para gráfico de barras, cada texto deve ser separado por ";" - llm_description: x axis for bar chart, x axis should be a string contains a list of texts like "a;b;c;1;2" in order to match the data - form: llm diff --git a/api/core/tools/provider/builtin/chart/tools/line.py b/api/core/tools/provider/builtin/chart/tools/line.py deleted file mode 100644 index 39e8caac7ef609..00000000000000 --- a/api/core/tools/provider/builtin/chart/tools/line.py +++ /dev/null @@ -1,50 +0,0 @@ -import io -from typing import Any, Union - -import matplotlib.pyplot as plt - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class LinearChartTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - data = tool_parameters.get("data", "") - if not data: - return self.create_text_message("Please input data") - data = data.split(";") - - axis = tool_parameters.get("x_axis") or None - if axis: - axis = axis.split(";") - if len(axis) != len(data): - axis = None - - # if all data is int, convert to int - if all(i.isdigit() for i in data): - data = [int(i) for i in data] - else: - data = [float(i) for i in data] - - flg, ax = plt.subplots(figsize=(10, 8)) - - if axis: - axis = [label[:10] + "..." if len(label) > 10 else label for label in axis] - ax.set_xticklabels(axis, rotation=45, ha="right") - ax.plot(axis, data) - else: - ax.plot(data) - - buf = io.BytesIO() - flg.savefig(buf, format="png") - buf.seek(0) - plt.close(flg) - - return [ - self.create_text_message("the linear chart is saved as an image."), - self.create_blob_message(blob=buf.read(), meta={"mime_type": "image/png"}), - ] diff --git a/api/core/tools/provider/builtin/chart/tools/line.yaml b/api/core/tools/provider/builtin/chart/tools/line.yaml deleted file mode 100644 index 35ebe3b68bddb3..00000000000000 --- a/api/core/tools/provider/builtin/chart/tools/line.yaml +++ /dev/null @@ -1,41 +0,0 @@ -identity: - name: line_chart - author: Dify - label: - en_US: Linear Chart - zh_Hans: 线性图表 - pt_BR: Gráfico linear - icon: icon.svg -description: - human: - en_US: linear chart - zh_Hans: 线性图表 - pt_BR: Gráfico linear - llm: generate a linear chart with input data -parameters: - - name: data - type: string - required: true - label: - en_US: data - zh_Hans: 数据 - pt_BR: dados - human_description: - en_US: data for generating chart, each number should be separated by ";" - zh_Hans: 用于生成线性图表的数据，每个数字之间用 ";" 分隔 - pt_BR: dados para gerar gráfico linear, cada número deve ser separado por ";" - llm_description: data for generating linear chart, data should be a string contains a list of numbers like "1;2;3;4;5" - form: llm - - name: x_axis - type: string - required: false - label: - en_US: X Axis - zh_Hans: x 轴 - pt_BR: Eixo X - human_description: - en_US: X axis for chart, each text should be separated by ";" - zh_Hans: 线性图表的 x 轴，每个文本之间用 ";" 分隔 - pt_BR: Eixo X para gráfico linear, cada texto deve ser separado por ";" - llm_description: x axis for linear chart, x axis should be a string contains a list of texts like "a;b;c;1;2" in order to match the data - form: llm diff --git a/api/core/tools/provider/builtin/chart/tools/pie.py b/api/core/tools/provider/builtin/chart/tools/pie.py deleted file mode 100644 index 2c3b8a733eac9a..00000000000000 --- a/api/core/tools/provider/builtin/chart/tools/pie.py +++ /dev/null @@ -1,48 +0,0 @@ -import io -from typing import Any, Union - -import matplotlib.pyplot as plt - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class PieChartTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - data = tool_parameters.get("data", "") - if not data: - return self.create_text_message("Please input data") - data = data.split(";") - categories = tool_parameters.get("categories") or None - - # if all data is int, convert to int - if all(i.isdigit() for i in data): - data = [int(i) for i in data] - else: - data = [float(i) for i in data] - - flg, ax = plt.subplots() - - if categories: - categories = categories.split(";") - if len(categories) != len(data): - categories = None - - if categories: - ax.pie(data, labels=categories) - else: - ax.pie(data) - - buf = io.BytesIO() - flg.savefig(buf, format="png") - buf.seek(0) - plt.close(flg) - - return [ - self.create_text_message("the pie chart is saved as an image."), - self.create_blob_message(blob=buf.read(), meta={"mime_type": "image/png"}), - ] diff --git a/api/core/tools/provider/builtin/chart/tools/pie.yaml b/api/core/tools/provider/builtin/chart/tools/pie.yaml deleted file mode 100644 index 541715cb7d86dd..00000000000000 --- a/api/core/tools/provider/builtin/chart/tools/pie.yaml +++ /dev/null @@ -1,41 +0,0 @@ -identity: - name: pie_chart - author: Dify - label: - en_US: Pie Chart - zh_Hans: 饼图 - pt_BR: Gráfico de pizza - icon: icon.svg -description: - human: - en_US: Pie chart - zh_Hans: 饼图 - pt_BR: Gráfico de pizza - llm: generate a pie chart with input data -parameters: - - name: data - type: string - required: true - label: - en_US: data - zh_Hans: 数据 - pt_BR: dados - human_description: - en_US: data for generating chart, each number should be separated by ";" - zh_Hans: 用于生成饼图的数据，每个数字之间用 ";" 分隔 - pt_BR: dados para gerar gráfico de pizza, cada número deve ser separado por ";" - llm_description: data for generating pie chart, data should be a string contains a list of numbers like "1;2;3;4;5" - form: llm - - name: categories - type: string - required: true - label: - en_US: Categories - zh_Hans: 分类 - pt_BR: Categorias - human_description: - en_US: Categories for chart, each category should be separated by ";" - zh_Hans: 饼图的分类，每个分类之间用 ";" 分隔 - pt_BR: Categorias para gráfico de pizza, cada categoria deve ser separada por ";" - llm_description: categories for pie chart, categories should be a string contains a list of texts like "a;b;c;1;2" in order to match the data, each category should be split by ";" 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a/api/core/tools/provider/builtin/cogview/cogview.yaml b/api/core/tools/provider/builtin/cogview/cogview.yaml deleted file mode 100644 index 374b0e98d9122c..00000000000000 --- a/api/core/tools/provider/builtin/cogview/cogview.yaml +++ /dev/null @@ -1,61 +0,0 @@ -identity: - author: Waffle - name: cogview - label: - en_US: CogView - zh_Hans: CogView 绘画 - pt_BR: CogView - description: - en_US: CogView art - zh_Hans: CogView 绘画 - pt_BR: CogView art - icon: icon.png - tags: - - image - - productivity -credentials_for_provider: - zhipuai_api_key: - type: secret-input - required: true - label: - en_US: ZhipuAI API key - zh_Hans: ZhipuAI API key - pt_BR: ZhipuAI API key - help: - en_US: Please input your ZhipuAI API key - zh_Hans: 请输入你的 ZhipuAI API key - pt_BR: Please input your ZhipuAI API key - placeholder: - en_US: Please input your ZhipuAI API key - zh_Hans: 请输入你的 ZhipuAI API key - pt_BR: Please input your ZhipuAI API key - zhipuai_organizaion_id: - type: text-input - required: false - label: - en_US: ZhipuAI organization ID - zh_Hans: ZhipuAI organization ID - pt_BR: ZhipuAI organization ID - help: - en_US: Please input your ZhipuAI organization ID - zh_Hans: 请输入你的 ZhipuAI organization ID - pt_BR: Please input your ZhipuAI organization ID - placeholder: - en_US: Please input your ZhipuAI organization ID - zh_Hans: 请输入你的 ZhipuAI organization ID - pt_BR: Please input your ZhipuAI organization ID - zhipuai_base_url: - type: text-input - required: false - label: - en_US: ZhipuAI base URL - zh_Hans: ZhipuAI base URL - pt_BR: ZhipuAI base URL - help: - en_US: Please input your ZhipuAI base URL - zh_Hans: 请输入你的 ZhipuAI base URL - pt_BR: Please input your ZhipuAI base URL - placeholder: - en_US: Please input your ZhipuAI base URL - zh_Hans: 请输入你的 ZhipuAI base URL - pt_BR: Please input your ZhipuAI base URL diff --git a/api/core/tools/provider/builtin/cogview/tools/cogview3.py b/api/core/tools/provider/builtin/cogview/tools/cogview3.py deleted file mode 100644 index 9039708588df16..00000000000000 --- a/api/core/tools/provider/builtin/cogview/tools/cogview3.py +++ /dev/null @@ -1,72 +0,0 @@ -import random -from typing import Any, Union - -from core.model_runtime.model_providers.zhipuai.zhipuai_sdk._client import ZhipuAI -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class CogView3Tool(BuiltinTool): - """CogView3 Tool""" - - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke CogView3 tool - """ - client = ZhipuAI( - base_url=self.runtime.credentials["zhipuai_base_url"], - api_key=self.runtime.credentials["zhipuai_api_key"], - ) - size_mapping = { - "square": "1024x1024", - "vertical": "1024x1792", - "horizontal": "1792x1024", - } - # prompt - prompt = tool_parameters.get("prompt", "") - if not prompt: - return self.create_text_message("Please input prompt") - # get size - size = size_mapping[tool_parameters.get("size", "square")] - # get n - n = tool_parameters.get("n", 1) - # get quality - quality = tool_parameters.get("quality", "standard") - if quality not in {"standard", "hd"}: - return self.create_text_message("Invalid quality") - # get style - style = tool_parameters.get("style", "vivid") - if style not in {"natural", "vivid"}: - return self.create_text_message("Invalid style") - # set extra body - seed_id = tool_parameters.get("seed_id", self._generate_random_id(8)) - extra_body = {"seed": seed_id} - response = client.images.generations( - prompt=prompt, - model="cogview-3", - size=size, - n=n, - extra_body=extra_body, - style=style, - quality=quality, - response_format="b64_json", - ) - result = [] - for image in response.data: - result.append(self.create_image_message(image=image.url)) - result.append( - self.create_json_message( - { - "url": image.url, - } - ) - ) - return result - - @staticmethod - def _generate_random_id(length=8): - characters = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789" - random_id = "".join(random.choices(characters, k=length)) - return random_id diff --git a/api/core/tools/provider/builtin/cogview/tools/cogview3.yaml b/api/core/tools/provider/builtin/cogview/tools/cogview3.yaml deleted file mode 100644 index 1de3f599b6ac02..00000000000000 --- a/api/core/tools/provider/builtin/cogview/tools/cogview3.yaml +++ /dev/null @@ -1,123 +0,0 @@ -identity: - name: cogview3 - author: Waffle - label: - en_US: CogView 3 - zh_Hans: CogView 3 绘画 - pt_BR: CogView 3 - description: - en_US: CogView 3 is a powerful drawing tool that can draw the image you want based on your prompt - zh_Hans: CogView 3 是一个强大的绘画工具，它可以根据您的提示词绘制出您想要的图像 - pt_BR: CogView 3 is a powerful drawing tool that can draw the image you want based on your prompt -description: - human: - en_US: CogView 3 is a text to image tool - zh_Hans: CogView 3 是一个文本到图像的工具 - pt_BR: CogView 3 is a text to image tool - llm: CogView 3 is a tool used to generate images from text -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: Image prompt, you can check the official documentation of CogView 3 - zh_Hans: 图像提示词，您可以查看 CogView 3 的官方文档 - pt_BR: Image prompt, you can check the official documentation of CogView 3 - llm_description: Image prompt of CogView 3, you should describe the image you want to generate as a list of words as possible as detailed - form: llm - - name: size - type: select - required: true - human_description: - en_US: selecting the image size - zh_Hans: 选择图像大小 - pt_BR: selecting the image size - label: - en_US: Image size - zh_Hans: 图像大小 - pt_BR: Image size - form: form - options: - - value: square - label: - en_US: Squre(1024x1024) - zh_Hans: 方(1024x1024) - pt_BR: Squre(1024x1024) - - value: vertical - label: - en_US: Vertical(1024x1792) - zh_Hans: 竖屏(1024x1792) - pt_BR: Vertical(1024x1792) - - value: horizontal - label: - en_US: Horizontal(1792x1024) - zh_Hans: 横屏(1792x1024) - pt_BR: Horizontal(1792x1024) - default: square - - name: n - type: number - required: true - human_description: - en_US: selecting the number of images - zh_Hans: 选择图像数量 - pt_BR: selecting the number of images - label: - en_US: Number of images - zh_Hans: 图像数量 - pt_BR: Number of images - form: form - min: 1 - max: 1 - default: 1 - - name: quality - type: select - required: true - human_description: - en_US: selecting the image quality - zh_Hans: 选择图像质量 - pt_BR: selecting the image quality - label: - en_US: Image quality - zh_Hans: 图像质量 - pt_BR: Image quality - form: form - options: - - value: standard - label: - en_US: Standard - zh_Hans: 标准 - pt_BR: Standard - - value: hd - label: - en_US: HD - zh_Hans: 高清 - pt_BR: HD - default: standard - - name: style - type: select - required: true - human_description: - en_US: selecting the image style - zh_Hans: 选择图像风格 - pt_BR: selecting the image style - label: - en_US: Image style - 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zNO#a624n@em!g>s9>Zbis0%1F4PQV}>0U-hHrS96QZ*iZ?c@78n6D#%aF)D;uKe<@ zP^G1TQjRHV?(lX#dWT@?YLfQ~_PV40(`G#^2Vf;S_wcgUj2Vmit7VNRK<85Gl(V8j zijRys6KZ9cjx!*Q+_K|~1Z76I9orU*u@ENJLC>F!2y=qq5N6R0avs`Yp^1RN%j|an zI$7Uxt>Zo_0myifwKwM`!3aBHg%d73_76yCW~Kk>C@vFBk=S6+0x5P|yycf7F>iE& zB@XzW6%L5Gnc2KuL{-SI8eygN=XZ6r-6sV%aV~6VWy5P2iDFbJ*u``He?qZ}1Qg0K zfR>r7W5R)TF|OvbtfId^kVz{4+fv;=7%JQtPA~9(QvUCU z9gM;M^zVN+rjq{8GlLf(x550^E%<-$qymBu`u|%1%`E!=|Iwc;qEZu9;U(X}UB(a) NvXV*?HDZQ={|9+=nRoyI diff --git a/api/core/tools/provider/builtin/comfyui/comfyui.py b/api/core/tools/provider/builtin/comfyui/comfyui.py deleted file mode 100644 index 7013a0b93c8dcb..00000000000000 --- a/api/core/tools/provider/builtin/comfyui/comfyui.py +++ /dev/null @@ -1,17 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.comfyui.tools.comfyui_stable_diffusion import ComfyuiStableDiffusionTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class ComfyUIProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - ComfyuiStableDiffusionTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).validate_models() - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/comfyui/comfyui.yaml b/api/core/tools/provider/builtin/comfyui/comfyui.yaml deleted file mode 100644 index 066fd853082817..00000000000000 --- a/api/core/tools/provider/builtin/comfyui/comfyui.yaml +++ /dev/null @@ -1,42 +0,0 @@ -identity: - author: Qun - name: comfyui - label: - en_US: ComfyUI - zh_Hans: ComfyUI - pt_BR: ComfyUI - description: - en_US: ComfyUI is a tool for generating images which can be deployed locally. - zh_Hans: ComfyUI 是一个可以在本地部署的图片生成的工具。 - pt_BR: ComfyUI is a tool for generating images which can be deployed locally. - icon: icon.png - tags: - - image -credentials_for_provider: - base_url: - type: text-input - required: true - label: - en_US: Base URL - zh_Hans: ComfyUI服务器的Base URL - pt_BR: Base URL - placeholder: - en_US: Please input your ComfyUI server's Base URL - zh_Hans: 请输入你的 ComfyUI 服务器的 Base URL - pt_BR: Please input your ComfyUI server's Base URL - model: - type: text-input - required: true - label: - en_US: Model with suffix - zh_Hans: 模型, 需要带后缀 - pt_BR: Model with suffix - placeholder: - en_US: Please input your model - zh_Hans: 请输入你的模型名称 - pt_BR: Please input your model - help: - en_US: The checkpoint name of the ComfyUI server, e.g. xxx.safetensors - zh_Hans: ComfyUI服务器的模型名称, 比如 xxx.safetensors - pt_BR: The checkpoint name of the ComfyUI server, e.g. xxx.safetensors - url: https://docs.dify.ai/tutorials/tool-configuration/comfyui diff --git a/api/core/tools/provider/builtin/comfyui/tools/comfyui_stable_diffusion.py b/api/core/tools/provider/builtin/comfyui/tools/comfyui_stable_diffusion.py deleted file mode 100644 index 81fc8cc9851a7e..00000000000000 --- a/api/core/tools/provider/builtin/comfyui/tools/comfyui_stable_diffusion.py +++ /dev/null @@ -1,475 +0,0 @@ -import json -import os -import random -import uuid -from copy import deepcopy -from enum import Enum -from typing import Any, Union - -import websocket -from httpx import get, post -from yarl import URL - -from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter, ToolParameterOption -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.tool.builtin_tool import BuiltinTool - -SD_TXT2IMG_OPTIONS = {} -LORA_NODE = { - "inputs": {"lora_name": "", "strength_model": 1, "strength_clip": 1, "model": ["11", 0], "clip": ["11", 1]}, - "class_type": "LoraLoader", - "_meta": {"title": "Load LoRA"}, -} -FluxGuidanceNode = { - "inputs": {"guidance": 3.5, "conditioning": ["6", 0]}, - "class_type": "FluxGuidance", - "_meta": {"title": "FluxGuidance"}, -} - - -class ModelType(Enum): - SD15 = 1 - SDXL = 2 - SD3 = 3 - FLUX = 4 - - -class ComfyuiStableDiffusionTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - # base url - base_url = self.runtime.credentials.get("base_url", "") - if not base_url: - return self.create_text_message("Please input base_url") - - if tool_parameters.get("model"): - self.runtime.credentials["model"] = tool_parameters["model"] - - model = self.runtime.credentials.get("model", None) - if not model: - return self.create_text_message("Please input model") - - # prompt - prompt = tool_parameters.get("prompt", "") - if not prompt: - return self.create_text_message("Please input prompt") - - # get negative prompt - negative_prompt = tool_parameters.get("negative_prompt", "") - - # get size - width = tool_parameters.get("width", 1024) - height = tool_parameters.get("height", 1024) - - # get steps - steps = tool_parameters.get("steps", 1) - - # get sampler_name - sampler_name = tool_parameters.get("sampler_name", "euler") - - # scheduler - scheduler = tool_parameters.get("scheduler", "normal") - - # get cfg - cfg = tool_parameters.get("cfg", 7.0) - - # get model type - model_type = tool_parameters.get("model_type", ModelType.SD15.name) - - # get lora - # supports up to 3 loras - lora_list = [] - lora_strength_list = [] - if tool_parameters.get("lora_1"): - lora_list.append(tool_parameters["lora_1"]) - lora_strength_list.append(tool_parameters.get("lora_strength_1", 1)) - if tool_parameters.get("lora_2"): - lora_list.append(tool_parameters["lora_2"]) - lora_strength_list.append(tool_parameters.get("lora_strength_2", 1)) - if tool_parameters.get("lora_3"): - lora_list.append(tool_parameters["lora_3"]) - lora_strength_list.append(tool_parameters.get("lora_strength_3", 1)) - - return self.text2img( - base_url=base_url, - model=model, - model_type=model_type, - prompt=prompt, - negative_prompt=negative_prompt, - width=width, - height=height, - steps=steps, - sampler_name=sampler_name, - scheduler=scheduler, - cfg=cfg, - lora_list=lora_list, - lora_strength_list=lora_strength_list, - ) - - def get_checkpoints(self) -> list[str]: - """ - get checkpoints - """ - try: - base_url = self.runtime.credentials.get("base_url", None) - if not base_url: - return [] - api_url = str(URL(base_url) / "models" / "checkpoints") - response = get(url=api_url, timeout=(2, 10)) - if response.status_code != 200: - return [] - else: - return response.json() - except Exception as e: - return [] - - def get_loras(self) -> list[str]: - """ - get loras - """ - try: - base_url = self.runtime.credentials.get("base_url", None) - if not base_url: - return [] - api_url = str(URL(base_url) / "models" / "loras") - response = get(url=api_url, timeout=(2, 10)) - if response.status_code != 200: - return [] - else: - return response.json() - except Exception as e: - return [] - - def get_sample_methods(self) -> tuple[list[str], list[str]]: - """ - get sample method - """ - try: - base_url = self.runtime.credentials.get("base_url", None) - if not base_url: - return [], [] - api_url = str(URL(base_url) / "object_info" / "KSampler") - response = get(url=api_url, timeout=(2, 10)) - if response.status_code != 200: - return [], [] - else: - data = response.json()["KSampler"]["input"]["required"] - return data["sampler_name"][0], data["scheduler"][0] - except Exception as e: - return [], [] - - def validate_models(self) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - validate models - """ - try: - base_url = self.runtime.credentials.get("base_url", None) - if not base_url: - raise ToolProviderCredentialValidationError("Please input base_url") - model = self.runtime.credentials.get("model", None) - if not model: - raise ToolProviderCredentialValidationError("Please input model") - - api_url = str(URL(base_url) / "models" / "checkpoints") - response = get(url=api_url, timeout=(2, 10)) - if response.status_code != 200: - raise ToolProviderCredentialValidationError("Failed to get models") - else: - models = response.json() - if len([d for d in models if d == model]) > 0: - return self.create_text_message(json.dumps(models)) - else: - raise ToolProviderCredentialValidationError(f"model {model} does not exist") - except Exception as e: - raise ToolProviderCredentialValidationError(f"Failed to get models, {e}") - - def get_history(self, base_url, prompt_id): - """ - get history - """ - url = str(URL(base_url) / "history") - respond = get(url, params={"prompt_id": prompt_id}, timeout=(2, 10)) - return respond.json() - - def download_image(self, base_url, filename, subfolder, folder_type): - """ - download image - """ - url = str(URL(base_url) / "view") - response = get(url, params={"filename": filename, "subfolder": subfolder, "type": folder_type}, timeout=(2, 10)) - return response.content - - def queue_prompt_image(self, base_url, client_id, prompt): - """ - send prompt task and rotate - """ - # initiate task execution - url = str(URL(base_url) / "prompt") - respond = post(url, data=json.dumps({"client_id": client_id, "prompt": prompt}), timeout=(2, 10)) - prompt_id = respond.json()["prompt_id"] - - ws = websocket.WebSocket() - if "https" in base_url: - ws_url = base_url.replace("https", "ws") - else: - ws_url = base_url.replace("http", "ws") - ws.connect(str(URL(f"{ws_url}") / "ws") + f"?clientId={client_id}", timeout=120) - - # websocket rotate execution status - output_images = {} - while True: - out = ws.recv() - if isinstance(out, str): - message = json.loads(out) - if message["type"] == "executing": - data = message["data"] - if data["node"] is None and data["prompt_id"] == prompt_id: - break # Execution is done - elif message["type"] == "status": - data = message["data"] - if data["status"]["exec_info"]["queue_remaining"] == 0 and data.get("sid"): - break # Execution is done - else: - continue # previews are binary data - - # download image when execution finished - history = self.get_history(base_url, prompt_id)[prompt_id] - for o in history["outputs"]: - for node_id in history["outputs"]: - node_output = history["outputs"][node_id] - if "images" in node_output: - images_output = [] - for image in node_output["images"]: - image_data = self.download_image(base_url, image["filename"], image["subfolder"], image["type"]) - images_output.append(image_data) - output_images[node_id] = images_output - - ws.close() - - return output_images - - def text2img( - self, - base_url: str, - model: str, - model_type: str, - prompt: str, - negative_prompt: str, - width: int, - height: int, - steps: int, - sampler_name: str, - scheduler: str, - cfg: float, - lora_list: list, - lora_strength_list: list, - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - generate image - """ - if not SD_TXT2IMG_OPTIONS: - current_dir = os.path.dirname(os.path.realpath(__file__)) - with open(os.path.join(current_dir, "txt2img.json")) as file: - SD_TXT2IMG_OPTIONS.update(json.load(file)) - - draw_options = deepcopy(SD_TXT2IMG_OPTIONS) - draw_options["3"]["inputs"]["steps"] = steps - draw_options["3"]["inputs"]["sampler_name"] = sampler_name - draw_options["3"]["inputs"]["scheduler"] = scheduler - draw_options["3"]["inputs"]["cfg"] = cfg - # generate different image when using same prompt next time - draw_options["3"]["inputs"]["seed"] = random.randint(0, 100000000) - draw_options["4"]["inputs"]["ckpt_name"] = model - draw_options["5"]["inputs"]["width"] = width - draw_options["5"]["inputs"]["height"] = height - draw_options["6"]["inputs"]["text"] = prompt - draw_options["7"]["inputs"]["text"] = negative_prompt - # if the model is SD3 or FLUX series, the Latent class should be corresponding to SD3 Latent - if model_type in {ModelType.SD3.name, ModelType.FLUX.name}: - draw_options["5"]["class_type"] = "EmptySD3LatentImage" - - if lora_list: - # last Lora node link to KSampler node - draw_options["3"]["inputs"]["model"][0] = "10" - # last Lora node link to positive and negative Clip node - draw_options["6"]["inputs"]["clip"][0] = "10" - draw_options["7"]["inputs"]["clip"][0] = "10" - # every Lora node link to next Lora node, and Checkpoints node link to first Lora node - for i, (lora, strength) in enumerate(zip(lora_list, lora_strength_list), 10): - if i - 10 == len(lora_list) - 1: - next_node_id = "4" - else: - next_node_id = str(i + 1) - lora_node = deepcopy(LORA_NODE) - lora_node["inputs"]["lora_name"] = lora - lora_node["inputs"]["strength_model"] = strength - lora_node["inputs"]["strength_clip"] = strength - lora_node["inputs"]["model"][0] = next_node_id - lora_node["inputs"]["clip"][0] = next_node_id - draw_options[str(i)] = lora_node - - # FLUX need to add FluxGuidance Node - if model_type == ModelType.FLUX.name: - last_node_id = str(10 + len(lora_list)) - draw_options[last_node_id] = deepcopy(FluxGuidanceNode) - draw_options[last_node_id]["inputs"]["conditioning"][0] = "6" - draw_options["3"]["inputs"]["positive"][0] = last_node_id - - try: - client_id = str(uuid.uuid4()) - result = self.queue_prompt_image(base_url, client_id, prompt=draw_options) - - # get first image - image = b"" - for node in result: - for img in result[node]: - if img: - image = img - break - - return self.create_blob_message( - blob=image, meta={"mime_type": "image/png"}, save_as=self.VARIABLE_KEY.IMAGE.value - ) - - except Exception as e: - return self.create_text_message(f"Failed to generate image: {str(e)}") - - def get_runtime_parameters(self) -> list[ToolParameter]: - parameters = [ - ToolParameter( - name="prompt", - label=I18nObject(en_US="Prompt", zh_Hans="Prompt"), - human_description=I18nObject( - en_US="Image prompt, you can check the official documentation of Stable Diffusion", - zh_Hans="图像提示词，您可以查看 Stable Diffusion 的官方文档", - ), - type=ToolParameter.ToolParameterType.STRING, - form=ToolParameter.ToolParameterForm.LLM, - llm_description="Image prompt of Stable Diffusion, you should describe the image " - "you want to generate as a list of words as possible as detailed, " - "the prompt must be written in English.", - required=True, - ), - ] - if self.runtime.credentials: - try: - models = self.get_checkpoints() - if len(models) != 0: - parameters.append( - ToolParameter( - name="model", - label=I18nObject(en_US="Model", zh_Hans="Model"), - human_description=I18nObject( - en_US="Model of Stable Diffusion or FLUX, " - "you can check the official documentation of Stable Diffusion or FLUX", - zh_Hans="Stable Diffusion 或者 FLUX 的模型，您可以查看 Stable Diffusion 的官方文档", - ), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - llm_description="Model of Stable Diffusion or FLUX, " - "you can check the official documentation of Stable Diffusion or FLUX", - required=True, - default=models[0], - options=[ - ToolParameterOption(value=i, label=I18nObject(en_US=i, zh_Hans=i)) for i in models - ], - ) - ) - loras = self.get_loras() - if len(loras) != 0: - for n in range(1, 4): - parameters.append( - ToolParameter( - name=f"lora_{n}", - label=I18nObject(en_US=f"Lora {n}", zh_Hans=f"Lora {n}"), - human_description=I18nObject( - en_US="Lora of Stable Diffusion, " - "you can check the official documentation of Stable Diffusion", - zh_Hans="Stable Diffusion 的 Lora 模型，您可以查看 Stable Diffusion 的官方文档", - ), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - llm_description="Lora of Stable Diffusion, " - "you can check the official documentation of " - "Stable Diffusion", - required=False, - options=[ - ToolParameterOption(value=i, label=I18nObject(en_US=i, zh_Hans=i)) for i in loras - ], - ) - ) - sample_methods, schedulers = self.get_sample_methods() - if len(sample_methods) != 0: - parameters.append( - ToolParameter( - name="sampler_name", - label=I18nObject(en_US="Sampling method", zh_Hans="Sampling method"), - human_description=I18nObject( - en_US="Sampling method of Stable Diffusion, " - "you can check the official documentation of Stable Diffusion", - zh_Hans="Stable Diffusion 的Sampling method，您可以查看 Stable Diffusion 的官方文档", - ), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - llm_description="Sampling method of Stable Diffusion, " - "you can check the official documentation of Stable Diffusion", - required=True, - default=sample_methods[0], - options=[ - ToolParameterOption(value=i, label=I18nObject(en_US=i, zh_Hans=i)) - for i in sample_methods - ], - ) - ) - if len(schedulers) != 0: - parameters.append( - ToolParameter( - name="scheduler", - label=I18nObject(en_US="Scheduler", zh_Hans="Scheduler"), - human_description=I18nObject( - en_US="Scheduler of Stable Diffusion, " - "you can check the official documentation of Stable Diffusion", - zh_Hans="Stable Diffusion 的Scheduler，您可以查看 Stable Diffusion 的官方文档", - ), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - llm_description="Scheduler of Stable Diffusion, " - "you can check the official documentation of Stable Diffusion", - required=True, - default=schedulers[0], - options=[ - ToolParameterOption(value=i, label=I18nObject(en_US=i, zh_Hans=i)) for i in schedulers - ], - ) - ) - parameters.append( - ToolParameter( - name="model_type", - label=I18nObject(en_US="Model Type", zh_Hans="Model Type"), - human_description=I18nObject( - en_US="Model Type of Stable Diffusion or Flux, " - "you can check the official documentation of Stable Diffusion or Flux", - zh_Hans="Stable Diffusion 或 FLUX 的模型类型，" - "您可以查看 Stable Diffusion 或 Flux 的官方文档", - ), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - llm_description="Model Type of Stable Diffusion or Flux, " - "you can check the official documentation of Stable Diffusion or Flux", - required=True, - default=ModelType.SD15.name, - options=[ - ToolParameterOption(value=i, label=I18nObject(en_US=i, zh_Hans=i)) - for i in ModelType.__members__ - ], - ) - ) - except: - pass - - return parameters diff --git a/api/core/tools/provider/builtin/comfyui/tools/comfyui_stable_diffusion.yaml b/api/core/tools/provider/builtin/comfyui/tools/comfyui_stable_diffusion.yaml deleted file mode 100644 index 4f4a6942b3bac4..00000000000000 --- a/api/core/tools/provider/builtin/comfyui/tools/comfyui_stable_diffusion.yaml +++ /dev/null @@ -1,212 +0,0 @@ -identity: - name: txt2img workflow - author: Qun - label: - en_US: Txt2Img Workflow - zh_Hans: Txt2Img Workflow - pt_BR: Txt2Img Workflow -description: - human: - en_US: a pre-defined comfyui workflow that can use one model and up to 3 loras to generate images. Support SD1.5, SDXL, SD3 and FLUX which contain text encoders/clip, but does not support models that requires a triple clip loader. - zh_Hans: 一个预定义的 ComfyUI 工作流，可以使用一个模型和最多3个loras来生成图像。支持包含文本编码器/clip的SD1.5、SDXL、SD3和FLUX，但不支持需要clip加载器的模型。 - pt_BR: a pre-defined comfyui workflow that can use one model and up to 3 loras to generate images. Support SD1.5, SDXL, SD3 and FLUX which contain text encoders/clip, but does not support models that requires a triple clip loader. - llm: draw the image you want based on your prompt. -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: Image prompt, you can check the official documentation of Stable Diffusion or FLUX - zh_Hans: 图像提示词，您可以查看 Stable Diffusion 或者 FLUX 的官方文档 - pt_BR: Image prompt, you can check the official documentation of Stable Diffusion or FLUX - llm_description: Image prompt of Stable Diffusion, you should describe the image you want to generate as a list of words as possible as detailed, the prompt must be written in English. - form: llm - - name: model - type: string - required: true - label: - en_US: Model Name - zh_Hans: 模型名称 - pt_BR: Model Name - human_description: - en_US: Model Name - zh_Hans: 模型名称 - pt_BR: Model Name - form: form - - name: model_type - type: string - required: true - label: - en_US: Model Type - zh_Hans: 模型类型 - pt_BR: Model Type - human_description: - en_US: Model Type - zh_Hans: 模型类型 - pt_BR: Model Type - form: form - - name: lora_1 - type: string - required: false - label: - en_US: Lora 1 - zh_Hans: Lora 1 - pt_BR: Lora 1 - human_description: - en_US: Lora 1 - zh_Hans: Lora 1 - pt_BR: Lora 1 - form: form - - name: lora_strength_1 - type: number - required: false - label: - en_US: Lora Strength 1 - zh_Hans: Lora Strength 1 - pt_BR: Lora Strength 1 - human_description: - en_US: Lora Strength 1 - zh_Hans: Lora模型的权重 - pt_BR: Lora Strength 1 - form: form - - name: steps - type: number - required: false - label: - en_US: Steps - zh_Hans: Steps - pt_BR: Steps - human_description: - en_US: Steps - zh_Hans: Steps - pt_BR: Steps - form: form - default: 20 - - name: width - type: number - required: false - label: - en_US: Width - zh_Hans: Width - pt_BR: Width - human_description: - en_US: Width - zh_Hans: Width - pt_BR: Width - form: form - default: 1024 - - name: height - type: number - required: false - label: - en_US: Height - zh_Hans: Height - pt_BR: Height - human_description: - en_US: Height - zh_Hans: Height - pt_BR: Height - form: form - default: 1024 - - name: negative_prompt - type: string - required: false - label: - en_US: Negative prompt - zh_Hans: Negative prompt - pt_BR: Negative prompt - human_description: - en_US: Negative prompt - zh_Hans: Negative prompt - pt_BR: Negative prompt - form: form - default: bad art, ugly, deformed, watermark, duplicated, discontinuous lines - - name: cfg - type: number - required: false - label: - en_US: CFG Scale - zh_Hans: CFG Scale - pt_BR: CFG Scale - human_description: - en_US: CFG Scale - zh_Hans: 提示词相关性(CFG Scale) - pt_BR: CFG Scale - form: form - default: 7.0 - - name: sampler_name - type: string - required: false - label: - en_US: Sampling method - zh_Hans: Sampling method - pt_BR: Sampling method - human_description: - en_US: Sampling method - zh_Hans: Sampling method - pt_BR: Sampling method - form: form - - name: scheduler - type: string - required: false - label: - en_US: Scheduler - zh_Hans: Scheduler - pt_BR: Scheduler - human_description: - en_US: Scheduler - zh_Hans: Scheduler - pt_BR: Scheduler - form: form - - name: lora_2 - type: string - required: false - label: - en_US: Lora 2 - zh_Hans: Lora 2 - pt_BR: Lora 2 - human_description: - en_US: Lora 2 - zh_Hans: Lora 2 - pt_BR: Lora 2 - form: form - - name: lora_strength_2 - type: number - required: false - label: - en_US: Lora Strength 2 - zh_Hans: Lora Strength 2 - pt_BR: Lora Strength 2 - human_description: - en_US: Lora Strength 2 - zh_Hans: Lora模型的权重 - pt_BR: Lora Strength 2 - form: form - - name: lora_3 - type: string - required: false - label: - en_US: Lora 3 - zh_Hans: Lora 3 - pt_BR: Lora 3 - human_description: - en_US: Lora 3 - zh_Hans: Lora 3 - pt_BR: Lora 3 - form: form - - name: lora_strength_3 - type: number - required: false - label: - en_US: Lora Strength 3 - zh_Hans: Lora Strength 3 - pt_BR: Lora Strength 3 - human_description: - en_US: Lora Strength 3 - zh_Hans: Lora模型的权重 - pt_BR: Lora Strength 3 - form: form diff --git a/api/core/tools/provider/builtin/comfyui/tools/txt2img.json b/api/core/tools/provider/builtin/comfyui/tools/txt2img.json deleted file mode 100644 index 8ea869ff106c38..00000000000000 --- a/api/core/tools/provider/builtin/comfyui/tools/txt2img.json +++ /dev/null @@ -1,107 +0,0 @@ -{ - "3": { - "inputs": { - "seed": 156680208700286, - "steps": 20, - "cfg": 8, - "sampler_name": "euler", - "scheduler": "normal", - "denoise": 1, - "model": [ - "4", - 0 - ], - "positive": [ - "6", - 0 - ], - "negative": [ - "7", - 0 - ], - "latent_image": [ - "5", - 0 - ] - }, - "class_type": "KSampler", - "_meta": { - "title": "KSampler" - } - }, - "4": { - "inputs": { - "ckpt_name": "3dAnimationDiffusion_v10.safetensors" - }, - "class_type": "CheckpointLoaderSimple", - "_meta": { - "title": "Load Checkpoint" - } - }, - "5": { - "inputs": { - "width": 512, - "height": 512, - "batch_size": 1 - }, - "class_type": "EmptyLatentImage", - "_meta": { - "title": "Empty Latent Image" - } - }, - "6": { - "inputs": { - "text": "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,", - "clip": [ - "4", - 1 - ] - }, - "class_type": "CLIPTextEncode", - "_meta": { - "title": "CLIP Text Encode (Prompt)" - } - }, - "7": { - "inputs": { - "text": "text, watermark", - "clip": [ - "4", - 1 - ] - }, - "class_type": "CLIPTextEncode", - "_meta": { - "title": "CLIP Text Encode (Prompt)" - } - }, - "8": { - "inputs": { - "samples": [ - "3", - 0 - ], - "vae": [ - "4", - 2 - ] - }, - "class_type": "VAEDecode", - "_meta": { - "title": "VAE Decode" - } - }, - "9": { - "inputs": { - "filename_prefix": "ComfyUI", - "images": [ - "8", - 0 - ] - }, - "class_type": "SaveImage", - "_meta": { - "title": "Save Image" - } - } -} \ No newline at end of file diff --git a/api/core/tools/provider/builtin/crossref/_assets/icon.svg b/api/core/tools/provider/builtin/crossref/_assets/icon.svg deleted file mode 100644 index aa629de7cb1660..00000000000000 --- a/api/core/tools/provider/builtin/crossref/_assets/icon.svg +++ /dev/null @@ -1,49 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/api/core/tools/provider/builtin/crossref/crossref.py b/api/core/tools/provider/builtin/crossref/crossref.py deleted file mode 100644 index 8ba3c1b48ae6d7..00000000000000 --- a/api/core/tools/provider/builtin/crossref/crossref.py +++ /dev/null @@ -1,20 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.crossref.tools.query_doi import CrossRefQueryDOITool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class CrossRefProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - CrossRefQueryDOITool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "doi": "10.1007/s00894-022-05373-8", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/crossref/crossref.yaml b/api/core/tools/provider/builtin/crossref/crossref.yaml deleted file mode 100644 index da67fbec3a480b..00000000000000 --- a/api/core/tools/provider/builtin/crossref/crossref.yaml +++ /dev/null @@ -1,29 +0,0 @@ -identity: - author: Sakura4036 - name: crossref - label: - en_US: CrossRef - zh_Hans: CrossRef - description: - en_US: Crossref is a cross-publisher reference linking registration query system using DOI technology created in 2000. Crossref establishes cross-database links between the reference list and citation full text of papers, making it very convenient for readers to access the full text of papers. - zh_Hans: Crossref是于2000年创建的使用DOI技术的跨出版商参考文献链接注册查询系统。Crossref建立了在论文的参考文献列表和引文全文之间的跨数据库链接，使得读者能够非常便捷地获取文献全文。 - icon: icon.svg - tags: - - search -credentials_for_provider: - mailto: - type: text-input - required: true - label: - en_US: email address - zh_Hans: email地址 - pt_BR: email address - placeholder: - en_US: Please input your email address - zh_Hans: 请输入你的email地址 - pt_BR: Please input your email address - help: - en_US: According to the requirements of Crossref, an email address is required - zh_Hans: 根据Crossref的要求，需要提供一个邮箱地址 - pt_BR: According to the requirements of Crossref, an email address is required - url: https://api.crossref.org/swagger-ui/index.html diff --git a/api/core/tools/provider/builtin/crossref/tools/query_doi.py b/api/core/tools/provider/builtin/crossref/tools/query_doi.py deleted file mode 100644 index 746139dd69d27b..00000000000000 --- a/api/core/tools/provider/builtin/crossref/tools/query_doi.py +++ /dev/null @@ -1,28 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.errors import ToolParameterValidationError -from core.tools.tool.builtin_tool import BuiltinTool - - -class CrossRefQueryDOITool(BuiltinTool): - """ - Tool for querying the metadata of a publication using its DOI. - """ - - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - doi = tool_parameters.get("doi") - if not doi: - raise ToolParameterValidationError("doi is required.") - # doc: https://github.com/CrossRef/rest-api-doc - url = f"https://api.crossref.org/works/{doi}" - response = requests.get(url) - response.raise_for_status() - response = response.json() - message = response.get("message", {}) - - return self.create_json_message(message) diff --git a/api/core/tools/provider/builtin/crossref/tools/query_doi.yaml b/api/core/tools/provider/builtin/crossref/tools/query_doi.yaml deleted file mode 100644 index 9c16da25edf2b3..00000000000000 --- a/api/core/tools/provider/builtin/crossref/tools/query_doi.yaml +++ /dev/null @@ -1,23 +0,0 @@ -identity: - name: crossref_query_doi - author: Sakura4036 - label: - en_US: CrossRef Query DOI - zh_Hans: CrossRef DOI 查询 - pt_BR: CrossRef Query DOI -description: - human: - en_US: A tool for searching literature information using CrossRef by DOI. - zh_Hans: 一个使用CrossRef通过DOI获取文献信息的工具。 - pt_BR: A tool for searching literature information using CrossRef by DOI. - llm: A tool for searching literature information using CrossRef by DOI. -parameters: - - name: doi - type: string - required: true - label: - en_US: DOI - zh_Hans: DOI - pt_BR: DOI - llm_description: DOI for searching in CrossRef - form: llm diff --git a/api/core/tools/provider/builtin/crossref/tools/query_title.py b/api/core/tools/provider/builtin/crossref/tools/query_title.py deleted file mode 100644 index e2452381832938..00000000000000 --- a/api/core/tools/provider/builtin/crossref/tools/query_title.py +++ /dev/null @@ -1,143 +0,0 @@ -import time -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -def convert_time_str_to_seconds(time_str: str) -> int: - """ - Convert a time string to seconds. - example: 1s -> 1, 1m30s -> 90, 1h30m -> 5400, 1h30m30s -> 5430 - """ - time_str = time_str.lower().strip().replace(" ", "") - seconds = 0 - if "h" in time_str: - hours, time_str = time_str.split("h") - seconds += int(hours) * 3600 - if "m" in time_str: - minutes, time_str = time_str.split("m") - seconds += int(minutes) * 60 - if "s" in time_str: - seconds += int(time_str.replace("s", "")) - return seconds - - -class CrossRefQueryTitleAPI: - """ - Tool for querying the metadata of a publication using its title. - Crossref API doc: https://github.com/CrossRef/rest-api-doc - """ - - query_url_template: str = "https://api.crossref.org/works?query.bibliographic={query}&rows={rows}&offset={offset}&sort={sort}&order={order}&mailto={mailto}" - rate_limit: int = 50 - rate_interval: float = 1 - max_limit: int = 1000 - - def __init__(self, mailto: str): - self.mailto = mailto - - def _query( - self, - query: str, - rows: int = 5, - offset: int = 0, - sort: str = "relevance", - order: str = "desc", - fuzzy_query: bool = False, - ) -> list[dict]: - """ - Query the metadata of a publication using its title. - :param query: the title of the publication - :param rows: the number of results to return - :param sort: the sort field - :param order: the sort order - :param fuzzy_query: whether to return all items that match the query - """ - url = self.query_url_template.format( - query=query, rows=rows, offset=offset, sort=sort, order=order, mailto=self.mailto - ) - response = requests.get(url) - response.raise_for_status() - rate_limit = int(response.headers["x-ratelimit-limit"]) - # convert time string to seconds - rate_interval = convert_time_str_to_seconds(response.headers["x-ratelimit-interval"]) - - self.rate_limit = rate_limit - self.rate_interval = rate_interval - - response = response.json() - if response["status"] != "ok": - return [] - - message = response["message"] - if fuzzy_query: - # fuzzy query return all items - return message["items"] - else: - for paper in message["items"]: - title = paper["title"][0] - if title.lower() != query.lower(): - continue - return [paper] - return [] - - def query( - self, query: str, rows: int = 5, sort: str = "relevance", order: str = "desc", fuzzy_query: bool = False - ) -> list[dict]: - """ - Query the metadata of a publication using its title. - :param query: the title of the publication - :param rows: the number of results to return - :param sort: the sort field - :param order: the sort order - :param fuzzy_query: whether to return all items that match the query - """ - rows = min(rows, self.max_limit) - if rows > self.rate_limit: - # query multiple times - query_times = rows // self.rate_limit + 1 - results = [] - - for i in range(query_times): - result = self._query( - query, - rows=self.rate_limit, - offset=i * self.rate_limit, - sort=sort, - order=order, - fuzzy_query=fuzzy_query, - ) - if fuzzy_query: - results.extend(result) - else: - # fuzzy_query=False, only one result - if result: - return result - time.sleep(self.rate_interval) - return results - else: - # query once - return self._query(query, rows, sort=sort, order=order, fuzzy_query=fuzzy_query) - - -class CrossRefQueryTitleTool(BuiltinTool): - """ - Tool for querying the metadata of a publication using its title. - """ - - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - query = tool_parameters.get("query") - fuzzy_query = tool_parameters.get("fuzzy_query", False) - rows = tool_parameters.get("rows", 3) - sort = tool_parameters.get("sort", "relevance") - order = tool_parameters.get("order", "desc") - mailto = self.runtime.credentials["mailto"] - - result = CrossRefQueryTitleAPI(mailto).query(query, rows, sort, order, fuzzy_query) - - return [self.create_json_message(r) for r in result] diff --git a/api/core/tools/provider/builtin/crossref/tools/query_title.yaml b/api/core/tools/provider/builtin/crossref/tools/query_title.yaml deleted file mode 100644 index 5579c77f5293d3..00000000000000 --- a/api/core/tools/provider/builtin/crossref/tools/query_title.yaml +++ /dev/null @@ -1,105 +0,0 @@ -identity: - name: crossref_query_title - author: Sakura4036 - label: - en_US: CrossRef Title Query - zh_Hans: CrossRef 标题查询 - pt_BR: CrossRef Title Query -description: - human: - en_US: A tool for querying literature information using CrossRef by title. - zh_Hans: 一个使用CrossRef通过标题搜索文献信息的工具。 - pt_BR: A tool for querying literature information using CrossRef by title. - llm: A tool for querying literature information using CrossRef by title. -parameters: - - name: query - type: string - required: true - label: - en_US: 标题 - zh_Hans: 查询语句 - pt_BR: 标题 - human_description: - en_US: Query bibliographic information, useful for citation look up. Includes titles, authors, ISSNs and publication years - zh_Hans: 用于搜索文献信息，有助于查找引用。包括标题，作者，ISSN和出版年份 - pt_BR: Query bibliographic information, useful for citation look up. Includes titles, authors, ISSNs and publication years - llm_description: key words for querying in Web of Science - form: llm - - name: fuzzy_query - type: boolean - default: false - label: - en_US: Whether to fuzzy search - zh_Hans: 是否模糊搜索 - pt_BR: Whether to fuzzy search - human_description: - en_US: used for selecting the query type, fuzzy query returns more results, precise query returns 1 or none - zh_Hans: 用于选择搜索类型，模糊搜索返回更多结果，精确搜索返回1条结果或无 - pt_BR: used for selecting the query type, fuzzy query returns more results, precise query returns 1 or none - form: form - - name: limit - type: number - required: false - label: - en_US: max query number - zh_Hans: 最大搜索数 - pt_BR: max query number - human_description: - en_US: max query number(fuzzy search returns the maximum number of results or precise search the maximum number of matches) - zh_Hans: 最大搜索数(模糊搜索返回的最大结果数或精确搜索最大匹配数) - pt_BR: max query number(fuzzy search returns the maximum number of results or precise search the maximum number of matches) - form: llm - default: 50 - - name: sort - type: select - required: true - options: - - value: relevance - label: - en_US: relevance - zh_Hans: 相关性 - pt_BR: relevance - - value: published - label: - en_US: publication date - zh_Hans: 出版日期 - pt_BR: publication date - - value: references-count - label: - en_US: references-count - zh_Hans: 引用次数 - pt_BR: references-count - default: relevance - label: - en_US: sorting field - zh_Hans: 排序字段 - pt_BR: sorting field - human_description: - en_US: Sorting of query results - zh_Hans: 检索结果的排序字段 - pt_BR: Sorting of query results - form: form - - name: order - type: select - required: true - options: - - value: desc - label: - en_US: descending - zh_Hans: 降序 - pt_BR: descending - - value: asc - label: - en_US: ascending - zh_Hans: 升序 - pt_BR: ascending - default: desc - label: - en_US: Order - zh_Hans: 排序 - pt_BR: Order - human_description: - en_US: Order of query results - zh_Hans: 检索结果的排序方式 - pt_BR: Order of query results - form: form 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z_5{VNTCD^dhQww Z*92R|Jvv!ULn#2aG*q;eEB~_y`X9!4)eHat diff --git a/api/core/tools/provider/builtin/dalle/dalle.py b/api/core/tools/provider/builtin/dalle/dalle.py deleted file mode 100644 index 5bd16e49e85e29..00000000000000 --- a/api/core/tools/provider/builtin/dalle/dalle.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.dalle.tools.dalle2 import DallE2Tool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class DALLEProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - DallE2Tool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={"prompt": "cute girl, blue eyes, white hair, anime style", "size": "small", "n": 1}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/dalle/dalle.yaml b/api/core/tools/provider/builtin/dalle/dalle.yaml deleted file mode 100644 index 37cf93c28aae58..00000000000000 --- a/api/core/tools/provider/builtin/dalle/dalle.yaml +++ /dev/null @@ -1,61 +0,0 @@ -identity: - author: Dify - name: dalle - label: - en_US: DALL-E - zh_Hans: DALL-E 绘画 - pt_BR: DALL-E - description: - en_US: DALL-E art - zh_Hans: DALL-E 绘画 - pt_BR: DALL-E art - icon: icon.png - tags: - - image - - productivity -credentials_for_provider: - openai_api_key: - type: secret-input - required: true - label: - en_US: OpenAI API key - zh_Hans: OpenAI API key - pt_BR: OpenAI API key - help: - en_US: Please input your OpenAI API key - zh_Hans: 请输入你的 OpenAI API key - pt_BR: Please input your OpenAI API key - placeholder: - en_US: Please input your OpenAI API key - zh_Hans: 请输入你的 OpenAI API key - pt_BR: Please input your OpenAI API key - openai_organization_id: - type: text-input - required: false - label: - en_US: OpenAI organization ID - zh_Hans: OpenAI organization ID - pt_BR: OpenAI organization ID - help: - en_US: Please input your OpenAI organization ID - zh_Hans: 请输入你的 OpenAI organization ID - pt_BR: Please input your OpenAI organization ID - placeholder: - en_US: Please input your OpenAI organization ID - zh_Hans: 请输入你的 OpenAI organization ID - pt_BR: Please input your OpenAI organization ID - openai_base_url: - type: text-input - required: false - label: - en_US: OpenAI base URL - zh_Hans: OpenAI base URL - pt_BR: OpenAI base URL - help: - en_US: Please input your OpenAI base URL - zh_Hans: 请输入你的 OpenAI base URL - pt_BR: Please input your OpenAI base URL - placeholder: - en_US: Please input your OpenAI base URL - zh_Hans: 请输入你的 OpenAI base URL - pt_BR: Please input your OpenAI base URL diff --git a/api/core/tools/provider/builtin/dalle/tools/dalle2.py b/api/core/tools/provider/builtin/dalle/tools/dalle2.py deleted file mode 100644 index fbd7397292155e..00000000000000 --- a/api/core/tools/provider/builtin/dalle/tools/dalle2.py +++ /dev/null @@ -1,66 +0,0 @@ -from base64 import b64decode -from typing import Any, Union - -from openai import OpenAI -from yarl import URL - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DallE2Tool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - openai_organization = self.runtime.credentials.get("openai_organization_id", None) - if not openai_organization: - openai_organization = None - openai_base_url = self.runtime.credentials.get("openai_base_url", None) - if not openai_base_url: - openai_base_url = None - else: - openai_base_url = str(URL(openai_base_url) / "v1") - - client = OpenAI( - api_key=self.runtime.credentials["openai_api_key"], - base_url=openai_base_url, - organization=openai_organization, - ) - - SIZE_MAPPING = { - "small": "256x256", - "medium": "512x512", - "large": "1024x1024", - } - - # prompt - prompt = tool_parameters.get("prompt", "") - if not prompt: - return self.create_text_message("Please input prompt") - - # get size - size = SIZE_MAPPING[tool_parameters.get("size", "large")] - - # get n - n = tool_parameters.get("n", 1) - - # call openapi dalle2 - response = client.images.generate(prompt=prompt, model="dall-e-2", size=size, n=n, response_format="b64_json") - - result = [] - - for image in response.data: - result.append( - self.create_blob_message( - blob=b64decode(image.b64_json), - meta={"mime_type": "image/png"}, - save_as=self.VariableKey.IMAGE.value, - ) - ) - - return result diff --git a/api/core/tools/provider/builtin/dalle/tools/dalle2.yaml b/api/core/tools/provider/builtin/dalle/tools/dalle2.yaml deleted file mode 100644 index e43e5df8cddd9b..00000000000000 --- a/api/core/tools/provider/builtin/dalle/tools/dalle2.yaml +++ /dev/null @@ -1,74 +0,0 @@ -identity: - name: dalle2 - author: Dify - label: - en_US: DALL-E 2 - zh_Hans: DALL-E 2 绘画 - description: - en_US: DALL-E 2 is a powerful drawing tool that can draw the image you want based on your prompt - zh_Hans: DALL-E 2 是一个强大的绘画工具，它可以根据您的提示词绘制出您想要的图像 - pt_BR: DALL-E 2 is a powerful drawing tool that can draw the image you want based on your prompt -description: - human: - en_US: DALL-E is a text to image tool - zh_Hans: DALL-E 是一个文本到图像的工具 - pt_BR: DALL-E is a text to image tool - llm: DALL-E is a tool used to generate images from text -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: Image prompt, you can check the official documentation of DallE 2 - zh_Hans: 图像提示词，您可以查看 DallE 2 的官方文档 - pt_BR: Image prompt, you can check the official documentation of DallE 2 - llm_description: Image prompt of DallE 2, you should describe the image you want to generate as a list of words as possible as detailed - form: llm - - name: size - type: select - required: true - human_description: - en_US: used for selecting the image size - zh_Hans: 用于选择图像大小 - pt_BR: used for selecting the image size - label: - en_US: Image size - zh_Hans: 图像大小 - pt_BR: Image size - form: form - options: - - value: small - label: - en_US: Small(256x256) - zh_Hans: 小(256x256) - pt_BR: Small(256x256) - - value: medium - label: - en_US: Medium(512x512) - zh_Hans: 中(512x512) - pt_BR: Medium(512x512) - - value: large - label: - en_US: Large(1024x1024) - zh_Hans: 大(1024x1024) - pt_BR: Large(1024x1024) - default: large - - name: n - type: number - required: true - human_description: - en_US: used for selecting the number of images - zh_Hans: 用于选择图像数量 - pt_BR: used for selecting the number of images - label: - en_US: Number of images - zh_Hans: 图像数量 - pt_BR: Number of images - form: form - default: 1 - min: 1 - max: 10 diff --git a/api/core/tools/provider/builtin/dalle/tools/dalle3.py b/api/core/tools/provider/builtin/dalle/tools/dalle3.py deleted file mode 100644 index a8c647d71e69e0..00000000000000 --- a/api/core/tools/provider/builtin/dalle/tools/dalle3.py +++ /dev/null @@ -1,115 +0,0 @@ -import base64 -import random -from typing import Any, Union - -from openai import OpenAI -from yarl import URL - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DallE3Tool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - openai_organization = self.runtime.credentials.get("openai_organization_id", None) - if not openai_organization: - openai_organization = None - openai_base_url = self.runtime.credentials.get("openai_base_url", None) - if not openai_base_url: - openai_base_url = None - else: - openai_base_url = str(URL(openai_base_url) / "v1") - - client = OpenAI( - api_key=self.runtime.credentials["openai_api_key"], - base_url=openai_base_url, - organization=openai_organization, - ) - - SIZE_MAPPING = { - "square": "1024x1024", - "vertical": "1024x1792", - "horizontal": "1792x1024", - } - - # prompt - prompt = tool_parameters.get("prompt", "") - if not prompt: - return self.create_text_message("Please input prompt") - # get size - size = SIZE_MAPPING[tool_parameters.get("size", "square")] - # get n - n = tool_parameters.get("n", 1) - # get quality - quality = tool_parameters.get("quality", "standard") - if quality not in {"standard", "hd"}: - return self.create_text_message("Invalid quality") - # get style - style = tool_parameters.get("style", "vivid") - if style not in {"natural", "vivid"}: - return self.create_text_message("Invalid style") - - # call openapi dalle3 - response = client.images.generate( - prompt=prompt, model="dall-e-3", size=size, n=n, style=style, quality=quality, response_format="b64_json" - ) - - result = [] - - for image in response.data: - mime_type, blob_image = DallE3Tool._decode_image(image.b64_json) - blob_message = self.create_blob_message( - blob=blob_image, meta={"mime_type": mime_type}, save_as=self.VariableKey.IMAGE.value - ) - result.append(blob_message) - return result - - @staticmethod - def _decode_image(base64_image: str) -> tuple[str, bytes]: - """ - Decode a base64 encoded image. If the image is not prefixed with a MIME type, - it assumes 'image/png' as the default. - - :param base64_image: Base64 encoded image string - :return: A tuple containing the MIME type and the decoded image bytes - """ - if DallE3Tool._is_plain_base64(base64_image): - return "image/png", base64.b64decode(base64_image) - else: - return DallE3Tool._extract_mime_and_data(base64_image) - - @staticmethod - def _is_plain_base64(encoded_str: str) -> bool: - """ - Check if the given encoded string is plain base64 without a MIME type prefix. - - :param encoded_str: Base64 encoded image string - :return: True if the string is plain base64, False otherwise - """ - return not encoded_str.startswith("data:image") - - @staticmethod - def _extract_mime_and_data(encoded_str: str) -> tuple[str, bytes]: - """ - Extract MIME type and image data from a base64 encoded string with a MIME type prefix. - - :param encoded_str: Base64 encoded image string with MIME type prefix - :return: A tuple containing the MIME type and the decoded image bytes - """ - mime_type = encoded_str.split(";")[0].split(":")[1] - image_data_base64 = encoded_str.split(",")[1] - decoded_data = base64.b64decode(image_data_base64) - return mime_type, decoded_data - - @staticmethod - def _generate_random_id(length=8): - characters = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789" - random_id = "".join(random.choices(characters, k=length)) - return random_id diff --git a/api/core/tools/provider/builtin/dalle/tools/dalle3.yaml b/api/core/tools/provider/builtin/dalle/tools/dalle3.yaml deleted file mode 100644 index 0cea8af761e1e5..00000000000000 --- a/api/core/tools/provider/builtin/dalle/tools/dalle3.yaml +++ /dev/null @@ -1,123 +0,0 @@ -identity: - name: dalle3 - author: Dify - label: - en_US: DALL-E 3 - zh_Hans: DALL-E 3 绘画 - pt_BR: DALL-E 3 - description: - en_US: DALL-E 3 is a powerful drawing tool that can draw the image you want based on your prompt, compared to DallE 2, DallE 3 has stronger drawing ability, but it will consume more resources - zh_Hans: DALL-E 3 是一个强大的绘画工具，它可以根据您的提示词绘制出您想要的图像，相比于DallE 2， DallE 3拥有更强的绘画能力，但会消耗更多的资源 - pt_BR: DALL-E 3 is a powerful drawing tool that can draw the image you want based on your prompt, compared to DallE 2, DallE 3 has stronger drawing ability, but it will consume more resources -description: - human: - en_US: DALL-E is a text to image tool - zh_Hans: DALL-E 是一个文本到图像的工具 - pt_BR: DALL-E is a text to image tool - llm: DALL-E is a tool used to generate images from text -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: Image prompt, you can check the official documentation of DallE 3 - zh_Hans: 图像提示词，您可以查看 DallE 3 的官方文档 - pt_BR: Image prompt, you can check the official documentation of DallE 3 - llm_description: Image prompt of DallE 3, you should describe the image you want to generate as a list of words as possible as detailed - form: llm - - name: size - type: select - required: true - human_description: - en_US: selecting the image size - zh_Hans: 选择图像大小 - pt_BR: selecting the image size - label: - en_US: Image size - zh_Hans: 图像大小 - pt_BR: Image size - form: form - options: - - value: square - label: - en_US: Squre(1024x1024) - zh_Hans: 方(1024x1024) - pt_BR: Squre(1024x1024) - - value: vertical - label: - en_US: Vertical(1024x1792) - zh_Hans: 竖屏(1024x1792) - pt_BR: Vertical(1024x1792) - - value: horizontal - label: - en_US: Horizontal(1792x1024) - zh_Hans: 横屏(1792x1024) - pt_BR: Horizontal(1792x1024) - default: square - - name: n - type: number - required: true - human_description: - en_US: selecting the number of images - zh_Hans: 选择图像数量 - pt_BR: selecting the number of images - label: - en_US: Number of images - zh_Hans: 图像数量 - pt_BR: Number of images - form: form - min: 1 - max: 1 - default: 1 - - name: quality - type: select - required: true - human_description: - en_US: selecting the image quality - zh_Hans: 选择图像质量 - pt_BR: selecting the image quality - label: - en_US: Image quality - zh_Hans: 图像质量 - pt_BR: Image quality - form: form - options: - - value: standard - label: - en_US: Standard - zh_Hans: 标准 - pt_BR: Standard - - value: hd - label: - en_US: HD - zh_Hans: 高清 - pt_BR: HD - default: standard - - name: style - type: select - required: true - human_description: - en_US: selecting the image style - zh_Hans: 选择图像风格 - pt_BR: selecting the image style - label: - en_US: Image style - zh_Hans: 图像风格 - pt_BR: Image style - form: form - options: - - value: vivid - label: - en_US: Vivid - zh_Hans: 生动 - pt_BR: Vivid - - value: natural - label: - en_US: Natural - zh_Hans: 自然 - pt_BR: Natural - default: vivid diff --git a/api/core/tools/provider/builtin/devdocs/_assets/icon.svg b/api/core/tools/provider/builtin/devdocs/_assets/icon.svg deleted file mode 100644 index c7a19fabfb18bf..00000000000000 --- a/api/core/tools/provider/builtin/devdocs/_assets/icon.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/devdocs/devdocs.py b/api/core/tools/provider/builtin/devdocs/devdocs.py deleted file mode 100644 index 446c1e548935c0..00000000000000 --- a/api/core/tools/provider/builtin/devdocs/devdocs.py +++ /dev/null @@ -1,21 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.devdocs.tools.searchDevDocs import SearchDevDocsTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class DevDocsProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - SearchDevDocsTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "doc": "python~3.12", - "topic": "library/code", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/devdocs/devdocs.yaml b/api/core/tools/provider/builtin/devdocs/devdocs.yaml deleted file mode 100644 index 7552f5a4973f7e..00000000000000 --- a/api/core/tools/provider/builtin/devdocs/devdocs.yaml +++ /dev/null @@ -1,13 +0,0 @@ -identity: - author: Richards Tu - name: devdocs - label: - en_US: DevDocs - zh_Hans: DevDocs - description: - en_US: Get official developer documentations on DevDocs. - zh_Hans: 从DevDocs获取官方开发者文档。 - icon: icon.svg - tags: - - search - - productivity diff --git a/api/core/tools/provider/builtin/devdocs/tools/searchDevDocs.py b/api/core/tools/provider/builtin/devdocs/tools/searchDevDocs.py deleted file mode 100644 index 57cf6d7a308dba..00000000000000 --- a/api/core/tools/provider/builtin/devdocs/tools/searchDevDocs.py +++ /dev/null @@ -1,47 +0,0 @@ -from typing import Any, Union - -import requests -from pydantic import BaseModel, Field - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class SearchDevDocsInput(BaseModel): - doc: str = Field(..., description="The name of the documentation.") - topic: str = Field(..., description="The path of the section/topic.") - - -class SearchDevDocsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invokes the DevDocs search tool with the given user ID and tool parameters. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Any]): The parameters for the tool, including 'doc' and 'topic'. - - Returns: - ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation, - which can be a single message or a list of messages. - """ - doc = tool_parameters.get("doc", "") - topic = tool_parameters.get("topic", "") - - if not doc: - return self.create_text_message("Please provide the documentation name.") - if not topic: - return self.create_text_message("Please provide the topic path.") - - url = f"https://documents.devdocs.io/{doc}/{topic}.html" - response = requests.get(url) - - if response.status_code == 200: - content = response.text - return self.create_text_message(self.summary(user_id=user_id, content=content)) - else: - return self.create_text_message( - f"Failed to retrieve the documentation. Status code: {response.status_code}" - ) diff --git a/api/core/tools/provider/builtin/devdocs/tools/searchDevDocs.yaml b/api/core/tools/provider/builtin/devdocs/tools/searchDevDocs.yaml deleted file mode 100644 index 2476db9da42d60..00000000000000 --- a/api/core/tools/provider/builtin/devdocs/tools/searchDevDocs.yaml +++ /dev/null @@ -1,34 +0,0 @@ -identity: - name: searchDevDocs - author: Richards Tu - label: - en_US: Search Developer Docs - zh_Hans: 搜索开发者文档 -description: - human: - en_US: A tools for searching for a specific topic and path in DevDocs based on the provided documentation name and topic. Don't for get to add some shots in the system prompt; for example, the documentation name should be like \"vuex~4\", \"css\", or \"python~3.12\", while the topic should be like \"guide/actions\" for Vuex 4, \"display-box\" for CSS, or \"library/code\" for Python 3.12. - zh_Hans: 一个用于根据提供的文档名称和主题，在DevDocs中搜索特定主题和路径的工具。不要忘记在系统提示词中添加一些示例；例如，文档名称应该是\"vuex~4\"、\"css\"或\"python~3.12\"，而主题应该是\"guide/actions\"用于Vuex 4，\"display-box\"用于CSS，或\"library/code\"用于Python 3.12。 - llm: A tools for searching for specific developer documentation in DevDocs based on the provided documentation name and topic. -parameters: - - name: doc - type: string - required: true - label: - en_US: Documentation name - zh_Hans: 文档名称 - human_description: - en_US: The name of the documentation. - zh_Hans: 文档名称。 - llm_description: The name of the documentation, such as \"vuex~4\", \"css\", or \"python~3.12\". The exact value should be identified by the user. - form: llm - - name: topic - type: string - required: true - label: - en_US: Topic name - zh_Hans: 主题名称 - human_description: - en_US: The path of the section/topic. - zh_Hans: 文档主题的路径。 - llm_description: The path of the section/topic, such as \"guide/actions\" for Vuex 4, \"display-box\" for CSS, or \"library/code\" for Python 3.12. - form: llm diff --git a/api/core/tools/provider/builtin/did/_assets/icon.svg b/api/core/tools/provider/builtin/did/_assets/icon.svg deleted file mode 100644 index c477d7cb71dea2..00000000000000 --- a/api/core/tools/provider/builtin/did/_assets/icon.svg +++ /dev/null @@ -1,14 +0,0 @@ - - - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/did/did.py b/api/core/tools/provider/builtin/did/did.py deleted file mode 100644 index 5af78794f625b7..00000000000000 --- a/api/core/tools/provider/builtin/did/did.py +++ /dev/null @@ -1,18 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.did.tools.talks import TalksTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class DIDProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - # Example validation using the D-ID talks tool - TalksTool().fork_tool_runtime(runtime={"credentials": credentials}).invoke( - user_id="", - tool_parameters={ - "source_url": "https://www.d-id.com/wp-content/uploads/2023/11/Hero-image-1.png", - "text_input": "Hello, welcome to use D-ID tool in Dify", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/did/did.yaml b/api/core/tools/provider/builtin/did/did.yaml deleted file mode 100644 index a70b71812e4648..00000000000000 --- a/api/core/tools/provider/builtin/did/did.yaml +++ /dev/null @@ -1,28 +0,0 @@ -identity: - author: Matri Qi - name: did - label: - en_US: D-ID - description: - en_US: D-ID is a tool enabling the creation of high-quality, custom videos of Digital Humans from a single image. - icon: icon.svg - tags: - - videos -credentials_for_provider: - did_api_key: - type: secret-input - required: true - label: - en_US: D-ID API Key - placeholder: - en_US: Please input your D-ID API key - help: - en_US: Get your D-ID API key from your D-ID account settings. - url: https://studio.d-id.com/account-settings - base_url: - type: text-input - required: false - label: - en_US: D-ID server's Base URL - placeholder: - en_US: https://api.d-id.com diff --git a/api/core/tools/provider/builtin/did/did_appx.py b/api/core/tools/provider/builtin/did/did_appx.py deleted file mode 100644 index c68878630d67b0..00000000000000 --- a/api/core/tools/provider/builtin/did/did_appx.py +++ /dev/null @@ -1,87 +0,0 @@ -import logging -import time -from collections.abc import Mapping -from typing import Any - -import requests -from requests.exceptions import HTTPError - -logger = logging.getLogger(__name__) - - -class DIDApp: - def __init__(self, api_key: str | None = None, base_url: str | None = None): - self.api_key = api_key - self.base_url = base_url or "https://api.d-id.com" - if not self.api_key: - raise ValueError("API key is required") - - def _prepare_headers(self, idempotency_key: str | None = None): - headers = {"Content-Type": "application/json", "Authorization": f"Basic {self.api_key}"} - if idempotency_key: - headers["Idempotency-Key"] = idempotency_key - return headers - - def _request( - self, - method: str, - url: str, - data: Mapping[str, Any] | None = None, - headers: Mapping[str, str] | None = None, - retries: int = 3, - backoff_factor: float = 0.3, - ) -> Mapping[str, Any] | None: - for i in range(retries): - try: - response = requests.request(method, url, json=data, headers=headers) - response.raise_for_status() - return response.json() - except requests.exceptions.RequestException as e: - if i < retries - 1 and isinstance(e, HTTPError) and e.response.status_code >= 500: - time.sleep(backoff_factor * (2**i)) - else: - raise - return None - - def talks(self, wait: bool = True, poll_interval: int = 5, idempotency_key: str | None = None, **kwargs): - endpoint = f"{self.base_url}/talks" - headers = self._prepare_headers(idempotency_key) - data = kwargs["params"] - logger.debug(f"Send request to {endpoint=} body={data}") - response = self._request("POST", endpoint, data, headers) - if response is None: - raise HTTPError("Failed to initiate D-ID talks after multiple retries") - id: str = response["id"] - if wait: - return self._monitor_job_status(id=id, target="talks", poll_interval=poll_interval) - return id - - def animations(self, wait: bool = True, poll_interval: int = 5, idempotency_key: str | None = None, **kwargs): - endpoint = f"{self.base_url}/animations" - headers = self._prepare_headers(idempotency_key) - data = kwargs["params"] - logger.debug(f"Send request to {endpoint=} body={data}") - response = self._request("POST", endpoint, data, headers) - if response is None: - raise HTTPError("Failed to initiate D-ID talks after multiple retries") - id: str = response["id"] - if wait: - return self._monitor_job_status(target="animations", id=id, poll_interval=poll_interval) - return id - - def check_did_status(self, target: str, id: str): - endpoint = f"{self.base_url}/{target}/{id}" - headers = self._prepare_headers() - response = self._request("GET", endpoint, headers=headers) - if response is None: - raise HTTPError(f"Failed to check status for talks {id} after multiple retries") - return response - - def _monitor_job_status(self, target: str, id: str, poll_interval: int): - while True: - status = self.check_did_status(target=target, id=id) - if status["status"] == "done": - return status - elif status["status"] == "error" or status["status"] == "rejected": - raise HTTPError(f'Talks {id} failed: {status["status"]} {status.get("error", {}).get("description")}') - time.sleep(poll_interval) diff --git a/api/core/tools/provider/builtin/did/tools/animations.py b/api/core/tools/provider/builtin/did/tools/animations.py deleted file mode 100644 index bc9d17e40d2878..00000000000000 --- a/api/core/tools/provider/builtin/did/tools/animations.py +++ /dev/null @@ -1,49 +0,0 @@ -import json -from typing import Any, Union - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.did.did_appx import DIDApp -from core.tools.tool.builtin_tool import BuiltinTool - - -class AnimationsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - app = DIDApp(api_key=self.runtime.credentials["did_api_key"], base_url=self.runtime.credentials["base_url"]) - - driver_expressions_str = tool_parameters.get("driver_expressions") - driver_expressions = json.loads(driver_expressions_str) if driver_expressions_str else None - - config = { - "stitch": tool_parameters.get("stitch", True), - "mute": tool_parameters.get("mute"), - "result_format": tool_parameters.get("result_format") or "mp4", - } - config = {k: v for k, v in config.items() if v is not None and v != ""} - - options = { - "source_url": tool_parameters["source_url"], - "driver_url": tool_parameters.get("driver_url"), - "config": config, - } - options = {k: v for k, v in options.items() if v is not None and v != ""} - - if not options.get("source_url"): - raise ValueError("Source URL is required") - - if config.get("logo_url"): - if not config.get("logo_x"): - raise ValueError("Logo X position is required when logo URL is provided") - if not config.get("logo_y"): - raise ValueError("Logo Y position is required when logo URL is provided") - - animations_result = app.animations(params=options, wait=True) - - if not isinstance(animations_result, str): - animations_result = json.dumps(animations_result, ensure_ascii=False, indent=4) - - if not animations_result: - return self.create_text_message("D-ID animations request failed.") - - return self.create_text_message(animations_result) diff --git a/api/core/tools/provider/builtin/did/tools/animations.yaml b/api/core/tools/provider/builtin/did/tools/animations.yaml deleted file mode 100644 index 2a2036c7b2a88f..00000000000000 --- a/api/core/tools/provider/builtin/did/tools/animations.yaml +++ /dev/null @@ -1,86 +0,0 @@ -identity: - name: animations - author: Matri Qi - label: - en_US: Animations -description: - human: - en_US: Animations enables to create videos matching head movements, expressions, emotions, and voice from a driver video and image. - llm: Animations enables to create videos matching head movements, expressions, emotions, and voice from a driver video and image. -parameters: - - name: source_url - type: string - required: true - label: - en_US: source url - human_description: - en_US: The URL of the source image to be animated by the driver video, or a selection from the list of provided studio actors. - llm_description: The URL of the source image to be animated by the driver video, or a selection from the list of provided studio actors. - form: llm - - name: driver_url - type: string - required: false - label: - en_US: driver url - human_description: - en_US: The URL of the driver video to drive the animation, or a provided driver name from D-ID. - form: form - - name: mute - type: boolean - required: false - label: - en_US: mute - human_description: - en_US: Mutes the driver sound in the animated video result, defaults to true - form: form - - name: stitch - type: boolean - required: false - label: - en_US: stitch - human_description: - en_US: If enabled, the driver video will be stitched with the animationing head video. - form: form - - name: logo_url - type: string - required: false - label: - en_US: logo url - human_description: - en_US: The URL of the logo image to be added to the animation video. - form: form - - name: logo_x - type: number - required: false - label: - en_US: logo position x - human_description: - en_US: The x position of the logo image in the animation video. It's required when logo url is provided. - form: form - - name: logo_y - type: number - required: false - label: - en_US: logo position y - human_description: - en_US: The y position of the logo image in the animation video. It's required when logo url is provided. - form: form - - name: result_format - type: string - default: mp4 - required: false - label: - en_US: result format - human_description: - en_US: The format of the result video. - form: form - options: - - value: mp4 - label: - en_US: mp4 - - value: gif - label: - en_US: gif - - value: mov - label: - en_US: mov diff --git a/api/core/tools/provider/builtin/did/tools/talks.py b/api/core/tools/provider/builtin/did/tools/talks.py deleted file mode 100644 index d6f0c7ff179793..00000000000000 --- a/api/core/tools/provider/builtin/did/tools/talks.py +++ /dev/null @@ -1,65 +0,0 @@ -import json -from typing import Any, Union - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.did.did_appx import DIDApp -from core.tools.tool.builtin_tool import BuiltinTool - - -class TalksTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - app = DIDApp(api_key=self.runtime.credentials["did_api_key"], base_url=self.runtime.credentials["base_url"]) - - driver_expressions_str = tool_parameters.get("driver_expressions") - driver_expressions = json.loads(driver_expressions_str) if driver_expressions_str else None - - script = { - "type": tool_parameters.get("script_type") or "text", - "input": tool_parameters.get("text_input"), - "audio_url": tool_parameters.get("audio_url"), - "reduce_noise": tool_parameters.get("audio_reduce_noise", False), - } - script = {k: v for k, v in script.items() if v is not None and v != ""} - config = { - "stitch": tool_parameters.get("stitch", True), - "sharpen": tool_parameters.get("sharpen"), - "fluent": tool_parameters.get("fluent"), - "result_format": tool_parameters.get("result_format") or "mp4", - "pad_audio": tool_parameters.get("pad_audio"), - "driver_expressions": driver_expressions, - } - config = {k: v for k, v in config.items() if v is not None and v != ""} - - options = { - "source_url": tool_parameters["source_url"], - "driver_url": tool_parameters.get("driver_url"), - "script": script, - "config": config, - } - options = {k: v for k, v in options.items() if v is not None and v != ""} - - if not options.get("source_url"): - raise ValueError("Source URL is required") - - if script.get("type") == "audio": - script.pop("input", None) - if not script.get("audio_url"): - raise ValueError("Audio URL is required for audio script type") - - if script.get("type") == "text": - script.pop("audio_url", None) - script.pop("reduce_noise", None) - if not script.get("input"): - raise ValueError("Text input is required for text script type") - - talks_result = app.talks(params=options, wait=True) - - if not isinstance(talks_result, str): - talks_result = json.dumps(talks_result, ensure_ascii=False, indent=4) - - if not talks_result: - return self.create_text_message("D-ID talks request failed.") - - return self.create_text_message(talks_result) diff --git a/api/core/tools/provider/builtin/did/tools/talks.yaml b/api/core/tools/provider/builtin/did/tools/talks.yaml deleted file mode 100644 index 88d430512923e4..00000000000000 --- a/api/core/tools/provider/builtin/did/tools/talks.yaml +++ /dev/null @@ -1,126 +0,0 @@ -identity: - name: talks - author: Matri Qi - label: - en_US: Talks -description: - human: - en_US: Talks enables the creation of realistic talking head videos from text or audio inputs. - llm: Talks enables the creation of realistic talking head videos from text or audio inputs. -parameters: - - name: source_url - type: string - required: true - label: - en_US: source url - human_description: - en_US: The URL of the source image to be animated by the driver video, or a selection from the list of provided studio actors. - llm_description: The URL of the source image to be animated by the driver video, or a selection from the list of provided studio actors. - form: llm - - name: driver_url - type: string - required: false - label: - en_US: driver url - human_description: - en_US: The URL of the driver video to drive the talk, or a provided driver name from D-ID. - form: form - - name: script_type - type: string - required: false - label: - en_US: script type - human_description: - en_US: The type of the script. - form: form - options: - - value: text - label: - en_US: text - - value: audio - label: - en_US: audio - - name: text_input - type: string - required: false - label: - en_US: text input - human_description: - en_US: The text input to be spoken by the talking head. Required when script type is text. - form: form - - name: audio_url - type: string - required: false - label: - en_US: audio url - human_description: - en_US: The URL of the audio file to be spoken by the talking head. Required when script type is audio. - form: form - - name: audio_reduce_noise - type: boolean - required: false - label: - en_US: audio reduce noise - human_description: - en_US: If enabled, the audio will be processed to reduce noise before being spoken by the talking head. It only works when script type is audio. - form: form - - name: stitch - type: boolean - required: false - label: - en_US: stitch - human_description: - en_US: If enabled, the driver video will be stitched with the talking head video. - form: form - - name: sharpen - type: boolean - required: false - label: - en_US: sharpen - human_description: - en_US: If enabled, the talking head video will be sharpened. - form: form - - name: result_format - type: string - required: false - label: - en_US: result format - human_description: - en_US: The format of the result video. - form: form - options: - - value: mp4 - label: - en_US: mp4 - - value: gif - label: - en_US: gif - - value: mov - label: - en_US: mov - - name: fluent - type: boolean - required: false - label: - en_US: fluent - human_description: - en_US: Interpolate between the last & first frames of the driver video When used together with pad_audio can create a seamless transition between videos of the same driver - form: form - - name: pad_audio - type: number - required: false - label: - en_US: pad audio - human_description: - en_US: Pad the audio with silence at the end (given in seconds) Will increase the video duration & the credits it consumes - form: form - min: 1 - max: 60 - - name: driver_expressions - type: string - required: false - label: - en_US: driver expressions - human_description: - en_US: timed expressions for animation. It should be an JSON array style string. Take D-ID documentation(https://docs.d-id.com/reference/createtalk) for more information. - form: form diff --git a/api/core/tools/provider/builtin/dingtalk/_assets/icon.svg b/api/core/tools/provider/builtin/dingtalk/_assets/icon.svg deleted file mode 100644 index b60653b7a59409..00000000000000 --- a/api/core/tools/provider/builtin/dingtalk/_assets/icon.svg +++ /dev/null @@ -1,7 +0,0 @@ - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/dingtalk/dingtalk.py b/api/core/tools/provider/builtin/dingtalk/dingtalk.py deleted file mode 100644 index be1d5e099c2246..00000000000000 --- a/api/core/tools/provider/builtin/dingtalk/dingtalk.py +++ /dev/null @@ -1,8 +0,0 @@ -from core.tools.provider.builtin.dingtalk.tools.dingtalk_group_bot import DingTalkGroupBotTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class DingTalkProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - DingTalkGroupBotTool() - pass diff --git a/api/core/tools/provider/builtin/dingtalk/dingtalk.yaml b/api/core/tools/provider/builtin/dingtalk/dingtalk.yaml deleted file mode 100644 index c922c140a8badc..00000000000000 --- a/api/core/tools/provider/builtin/dingtalk/dingtalk.yaml +++ /dev/null @@ -1,16 +0,0 @@ -identity: - author: Bowen Liang - name: dingtalk - label: - en_US: DingTalk - zh_Hans: 钉钉 - pt_BR: DingTalk - description: - en_US: DingTalk group robot - zh_Hans: 钉钉群机器人 - pt_BR: DingTalk group robot - icon: icon.svg - tags: - - social - - productivity -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/dingtalk/tools/dingtalk_group_bot.py b/api/core/tools/provider/builtin/dingtalk/tools/dingtalk_group_bot.py deleted file mode 100644 index f33ad5be59b403..00000000000000 --- a/api/core/tools/provider/builtin/dingtalk/tools/dingtalk_group_bot.py +++ /dev/null @@ -1,89 +0,0 @@ -import base64 -import hashlib -import hmac -import logging -import time -import urllib.parse -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DingTalkGroupBotTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - Dingtalk custom group robot API docs: - https://open.dingtalk.com/document/orgapp/custom-robot-access - """ - content = tool_parameters.get("content") - if not content: - return self.create_text_message("Invalid parameter content") - - access_token = tool_parameters.get("access_token") - if not access_token: - return self.create_text_message( - "Invalid parameter access_token. " - "Regarding information about security details," - "please refer to the DingTalk docs:" - "https://open.dingtalk.com/document/robots/customize-robot-security-settings" - ) - - sign_secret = tool_parameters.get("sign_secret") - if not sign_secret: - return self.create_text_message( - "Invalid parameter sign_secret. " - "Regarding information about security details," - "please refer to the DingTalk docs:" - "https://open.dingtalk.com/document/robots/customize-robot-security-settings" - ) - - msgtype = "text" - api_url = "https://oapi.dingtalk.com/robot/send" - headers = { - "Content-Type": "application/json", - } - params = { - "access_token": access_token, - } - - self._apply_security_mechanism(params, sign_secret) - - payload = { - "msgtype": msgtype, - "text": { - "content": content, - }, - } - - try: - res = httpx.post(api_url, headers=headers, params=params, json=payload) - if res.is_success: - return self.create_text_message("Text message sent successfully") - else: - return self.create_text_message( - f"Failed to send the text message, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to send message to group chat bot. {}".format(e)) - - @staticmethod - def _apply_security_mechanism(params: dict[str, Any], sign_secret: str): - try: - timestamp = str(round(time.time() * 1000)) - secret_enc = sign_secret.encode("utf-8") - string_to_sign = f"{timestamp}\n{sign_secret}" - string_to_sign_enc = string_to_sign.encode("utf-8") - hmac_code = hmac.new(secret_enc, string_to_sign_enc, digestmod=hashlib.sha256).digest() - sign = urllib.parse.quote_plus(base64.b64encode(hmac_code)) - - params["timestamp"] = timestamp - params["sign"] = sign - except Exception: - msg = "Failed to apply security mechanism to the request." - logging.exception(msg) diff --git a/api/core/tools/provider/builtin/dingtalk/tools/dingtalk_group_bot.yaml b/api/core/tools/provider/builtin/dingtalk/tools/dingtalk_group_bot.yaml deleted file mode 100644 index dc8a90b7193903..00000000000000 --- a/api/core/tools/provider/builtin/dingtalk/tools/dingtalk_group_bot.yaml +++ /dev/null @@ -1,52 +0,0 @@ -identity: - name: dingtalk_group_bot - author: Bowen Liang - label: - en_US: Send Group Message - zh_Hans: 发送群消息 - pt_BR: Send Group Message - icon: icon.svg -description: - human: - en_US: Sending a group message on DingTalk via the webhook of group bot - zh_Hans: 通过钉钉的群机器人webhook发送群消息 - pt_BR: Sending a group message on DingTalk via the webhook of group bot - llm: A tool for sending messages to a chat group on DingTalk(钉钉) . -parameters: - - name: access_token - type: secret-input - required: true - label: - en_US: access token - zh_Hans: access token - pt_BR: access token - human_description: - en_US: access_token in the group robot webhook - zh_Hans: 群自定义机器人webhook中access_token字段的值 - pt_BR: access_token in the group robot webhook - form: form - - name: sign_secret - type: secret-input - required: true - label: - en_US: secret key for signing - zh_Hans: 加签秘钥 - pt_BR: secret key for signing - human_description: - en_US: secret key for signing - zh_Hans: 加签秘钥 - pt_BR: secret key for signing - form: form - - name: content - type: string - required: true - label: - en_US: content - zh_Hans: 消息内容 - pt_BR: content - human_description: - en_US: Content to sent to the group. - zh_Hans: 群消息文本 - pt_BR: Content to sent to the group. - llm_description: Content of the message - form: llm diff --git a/api/core/tools/provider/builtin/duckduckgo/_assets/icon.svg b/api/core/tools/provider/builtin/duckduckgo/_assets/icon.svg deleted file mode 100644 index a816a6b49ebb78..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/duckduckgo/duckduckgo.py b/api/core/tools/provider/builtin/duckduckgo/duckduckgo.py deleted file mode 100644 index 8269167127b8e5..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/duckduckgo.py +++ /dev/null @@ -1,20 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.duckduckgo.tools.ddgo_search import DuckDuckGoSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class DuckDuckGoProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - DuckDuckGoSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "query": "John Doe", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/duckduckgo/duckduckgo.yaml b/api/core/tools/provider/builtin/duckduckgo/duckduckgo.yaml deleted file mode 100644 index f3faa060455772..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/duckduckgo.yaml +++ /dev/null @@ -1,12 +0,0 @@ -identity: - author: Yash Parmar - name: duckduckgo - label: - en_US: DuckDuckGo - zh_Hans: DuckDuckGo - description: - en_US: A privacy-focused search engine. - zh_Hans: 一个注重隐私的搜索引擎。 - icon: icon.svg - tags: - - search diff --git a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_ai.py b/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_ai.py deleted file mode 100644 index 8bdd638f4a01d1..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_ai.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from duckduckgo_search import DDGS - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DuckDuckGoAITool(BuiltinTool): - """ - Tool for performing a search using DuckDuckGo search engine. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - query_dict = { - "keywords": tool_parameters.get("query"), - "model": tool_parameters.get("model"), - } - response = DDGS().chat(**query_dict) - return self.create_text_message(text=response) diff --git a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_ai.yaml b/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_ai.yaml deleted file mode 100644 index 21cbae6bd3e002..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_ai.yaml +++ /dev/null @@ -1,47 +0,0 @@ -identity: - name: ddgo_ai - author: hjlarry - label: - en_US: DuckDuckGo AI Chat - zh_Hans: DuckDuckGo AI聊天 -description: - human: - en_US: Use the anonymous private chat provided by DuckDuckGo. - zh_Hans: 使用DuckDuckGo提供的匿名私密聊天。 - llm: Use the anonymous private chat provided by DuckDuckGo. -parameters: - - name: query - type: string - required: true - label: - en_US: Chat Content - zh_Hans: 聊天内容 - human_description: - en_US: The chat content. - zh_Hans: 要聊天的内容。 - llm_description: Key words for chat - form: llm - - name: model - type: select - required: true - options: - - value: gpt-4o-mini - label: - en_US: GPT-4o-mini - - value: claude-3-haiku - label: - en_US: Claude 3 - - value: llama-3-70b - label: - en_US: Llama 3 - - value: mixtral-8x7b - label: - en_US: Mixtral - default: gpt-3.5 - label: - en_US: Choose Model - zh_Hans: 选择模型 - human_description: - en_US: used to select the model for AI chat. - zh_Hans: 用于选择使用AI聊天的模型 - form: form diff --git a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_img.py b/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_img.py deleted file mode 100644 index 396570248ae785..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_img.py +++ /dev/null @@ -1,30 +0,0 @@ -from typing import Any - -from duckduckgo_search import DDGS - -from core.file.file_obj import FileTransferMethod -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DuckDuckGoImageSearchTool(BuiltinTool): - """ - Tool for performing an image search using DuckDuckGo search engine. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> list[ToolInvokeMessage]: - query_dict = { - "keywords": tool_parameters.get("query"), - "timelimit": tool_parameters.get("timelimit"), - "size": tool_parameters.get("size"), - "max_results": tool_parameters.get("max_results"), - } - response = DDGS().images(**query_dict) - result = [] - for res in response: - res["transfer_method"] = FileTransferMethod.REMOTE_URL - msg = ToolInvokeMessage( - type=ToolInvokeMessage.MessageType.IMAGE_LINK, message=res.get("image"), save_as="", meta=res - ) - result.append(msg) - return result diff --git a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_img.yaml b/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_img.yaml deleted file mode 100644 index 168cface224e40..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_img.yaml +++ /dev/null @@ -1,88 +0,0 @@ -identity: - name: ddgo_img - author: hjlarry - label: - en_US: DuckDuckGo Image Search - zh_Hans: DuckDuckGo 图片搜索 -description: - human: - en_US: Perform image searches on DuckDuckGo and get results. - zh_Hans: 在 DuckDuckGo 上进行图片搜索并获取结果。 - llm: Perform image searches on DuckDuckGo and get results. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - human_description: - en_US: The search query. - zh_Hans: 搜索查询语句。 - llm_description: Key words for searching - form: llm - - name: max_results - type: number - required: true - default: 3 - label: - en_US: Max results - zh_Hans: 最大结果数量 - human_description: - en_US: The max results. - zh_Hans: 最大结果数量 - form: form - - name: timelimit - type: select - required: false - options: - - value: Day - label: - en_US: current day - zh_Hans: 当天 - - value: Week - label: - en_US: current week - zh_Hans: 本周 - - value: Month - label: - en_US: current month - zh_Hans: 当月 - - value: Year - label: - en_US: current year - zh_Hans: 今年 - label: - en_US: Result time limit - zh_Hans: 结果时间限制 - human_description: - en_US: Use when querying results within a specific time range only. - zh_Hans: 只查询一定时间范围内的结果时使用 - form: form - - name: size - type: select - required: false - options: - - value: Small - label: - en_US: small - zh_Hans: 小 - - value: Medium - label: - en_US: medium - zh_Hans: 中 - - value: Large - label: - en_US: large - zh_Hans: 大 - - value: Wallpaper - label: - en_US: xl - zh_Hans: 超大 - label: - en_US: image size - zh_Hans: 图片大小 - human_description: - en_US: The size of the image to be searched. - zh_Hans: 要搜索的图片的大小 - form: form diff --git a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_search.py b/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_search.py deleted file mode 100644 index cbd65d2e7756e0..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_search.py +++ /dev/null @@ -1,45 +0,0 @@ -from typing import Any - -from duckduckgo_search import DDGS - -from core.model_runtime.entities.message_entities import SystemPromptMessage -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -SUMMARY_PROMPT = """ -User's query: -{query} - -Here is the search engine result: -{content} - -Please summarize the result in a few sentences. -""" - - -class DuckDuckGoSearchTool(BuiltinTool): - """ - Tool for performing a search using DuckDuckGo search engine. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: - query = tool_parameters.get("query") - max_results = tool_parameters.get("max_results", 5) - require_summary = tool_parameters.get("require_summary", False) - response = DDGS().text(query, max_results=max_results) - if require_summary: - results = "\n".join([res.get("body") for res in response]) - results = self.summary_results(user_id=user_id, content=results, query=query) - return self.create_text_message(text=results) - return [self.create_json_message(res) for res in response] - - def summary_results(self, user_id: str, content: str, query: str) -> str: - prompt = SUMMARY_PROMPT.format(query=query, content=content) - summary = self.invoke_model( - user_id=user_id, - prompt_messages=[ - SystemPromptMessage(content=prompt), - ], - stop=[], - ) - return summary.message.content diff --git a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_search.yaml b/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_search.yaml deleted file mode 100644 index 333c0cb093dbd2..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_search.yaml +++ /dev/null @@ -1,41 +0,0 @@ -identity: - name: ddgo_search - author: Yash Parmar - label: - en_US: DuckDuckGo Search - zh_Hans: DuckDuckGo 搜索 -description: - human: - en_US: Perform searches on DuckDuckGo and get results. - zh_Hans: 在 DuckDuckGo 上进行搜索并获取结果。 - llm: Perform searches on DuckDuckGo and get results. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - human_description: - en_US: The search query. - zh_Hans: 搜索查询语句。 - llm_description: Key words for searching - form: llm - - name: max_results - type: number - required: true - default: 5 - label: - en_US: Max results - zh_Hans: 最大结果数量 - form: form - - name: require_summary - type: boolean - default: false - label: - en_US: Require Summary - zh_Hans: 是否总结 - human_description: - en_US: Whether to pass the search results to llm for summarization. - zh_Hans: 是否需要将搜索结果传给大模型总结 - form: form diff --git a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_translate.py b/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_translate.py deleted file mode 100644 index 396ce21b183afc..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_translate.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from duckduckgo_search import DDGS - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DuckDuckGoTranslateTool(BuiltinTool): - """ - Tool for performing a search using DuckDuckGo search engine. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - query_dict = { - "keywords": tool_parameters.get("query"), - "to": tool_parameters.get("translate_to"), - } - response = DDGS().translate(**query_dict)[0].get("translated", "Unable to translate!") - return self.create_text_message(text=response) diff --git a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_translate.yaml b/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_translate.yaml deleted file mode 100644 index 78b5d0b02275b2..00000000000000 --- a/api/core/tools/provider/builtin/duckduckgo/tools/ddgo_translate.yaml +++ /dev/null @@ -1,51 +0,0 @@ -identity: - name: ddgo_translate - author: hjlarry - label: - en_US: DuckDuckGo Translate - zh_Hans: DuckDuckGo 翻译 -description: - human: - en_US: Use DuckDuckGo's translation feature. - zh_Hans: 使用DuckDuckGo的翻译功能。 - llm: Use DuckDuckGo's translation feature. -parameters: - - name: query - type: string - required: true - label: - en_US: Translate Content - zh_Hans: 翻译内容 - human_description: - en_US: The translate content. - zh_Hans: 要翻译的内容。 - llm_description: Key words for translate - form: llm - - name: translate_to - type: select - required: true - options: - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: zh-Hans - label: - en_US: Simplified Chinese - zh_Hans: 简体中文 - - value: zh-Hant - label: - en_US: Traditional Chinese - zh_Hans: 繁体中文 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - default: en - label: - en_US: Choose Language - zh_Hans: 选择语言 - human_description: - en_US: select the language to translate. - zh_Hans: 选择要翻译的语言 - form: form diff --git a/api/core/tools/provider/builtin/feishu/_assets/icon.svg b/api/core/tools/provider/builtin/feishu/_assets/icon.svg deleted file mode 100644 index bf3c202abf3ff6..00000000000000 --- a/api/core/tools/provider/builtin/feishu/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - diff --git a/api/core/tools/provider/builtin/feishu/feishu.py b/api/core/tools/provider/builtin/feishu/feishu.py deleted file mode 100644 index 72a9333619988d..00000000000000 --- a/api/core/tools/provider/builtin/feishu/feishu.py +++ /dev/null @@ -1,7 +0,0 @@ -from core.tools.provider.builtin.feishu.tools.feishu_group_bot import FeishuGroupBotTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class FeishuProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - FeishuGroupBotTool() diff --git a/api/core/tools/provider/builtin/feishu/feishu.yaml b/api/core/tools/provider/builtin/feishu/feishu.yaml deleted file mode 100644 index a029c7edb8853b..00000000000000 --- a/api/core/tools/provider/builtin/feishu/feishu.yaml +++ /dev/null @@ -1,16 +0,0 @@ -identity: - author: Arkii Sun - name: feishu - label: - en_US: Feishu - zh_Hans: 飞书 - pt_BR: Feishu - description: - en_US: Feishu group bot - zh_Hans: 飞书群机器人 - pt_BR: Feishu group bot - icon: icon.svg - tags: - - social - - productivity -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/feishu/tools/feishu_group_bot.py b/api/core/tools/provider/builtin/feishu/tools/feishu_group_bot.py deleted file mode 100644 index e82da8ca534b96..00000000000000 --- a/api/core/tools/provider/builtin/feishu/tools/feishu_group_bot.py +++ /dev/null @@ -1,51 +0,0 @@ -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.utils.uuid_utils import is_valid_uuid - - -class FeishuGroupBotTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - API document: https://open.feishu.cn/document/client-docs/bot-v3/add-custom-bot - """ - - url = "https://open.feishu.cn/open-apis/bot/v2/hook" - - content = tool_parameters.get("content", "") - if not content: - return self.create_text_message("Invalid parameter content") - - hook_key = tool_parameters.get("hook_key", "") - if not is_valid_uuid(hook_key): - return self.create_text_message(f"Invalid parameter hook_key ${hook_key}, not a valid UUID") - - msg_type = "text" - api_url = f"{url}/{hook_key}" - headers = { - "Content-Type": "application/json", - } - params = {} - payload = { - "msg_type": msg_type, - "content": { - "text": content, - }, - } - - try: - res = httpx.post(api_url, headers=headers, params=params, json=payload) - if res.is_success: - return self.create_text_message("Text message sent successfully") - else: - return self.create_text_message( - f"Failed to send the text message, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to send message to group chat bot. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu/tools/feishu_group_bot.yaml b/api/core/tools/provider/builtin/feishu/tools/feishu_group_bot.yaml deleted file mode 100644 index 6c3f084e4dafe3..00000000000000 --- a/api/core/tools/provider/builtin/feishu/tools/feishu_group_bot.yaml +++ /dev/null @@ -1,40 +0,0 @@ -identity: - name: feishu_group_bot - author: Arkii Sun - label: - en_US: Send Group Message - zh_Hans: 发送群消息 - pt_BR: Send Group Message - icon: icon.png -description: - human: - en_US: Sending a group message on Feishu via the webhook of group bot - zh_Hans: 通过飞书的群机器人webhook发送群消息 - pt_BR: Sending a group message on Feishu via the webhook of group bot - llm: A tool for sending messages to a chat group on Feishu(飞书) . -parameters: - - name: hook_key - type: secret-input - required: true - label: - en_US: Feishu Group bot webhook key - zh_Hans: 群机器人webhook的key - pt_BR: Feishu Group bot webhook key - human_description: - en_US: Feishu Group bot webhook key - zh_Hans: 群机器人webhook的key - pt_BR: Feishu Group bot webhook key - form: form - - name: content - type: string - required: true - label: - en_US: content - zh_Hans: 消息内容 - pt_BR: content - human_description: - en_US: Content to sent to the group. - zh_Hans: 群消息文本 - pt_BR: Content to sent to the group. - llm_description: Content of the message - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/_assets/icon.svg b/api/core/tools/provider/builtin/feishu_base/_assets/icon.svg deleted file mode 100644 index 2663a0f59ee6a4..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/_assets/icon.svg +++ /dev/null @@ -1,47 +0,0 @@ - - - - diff --git a/api/core/tools/provider/builtin/feishu_base/feishu_base.py b/api/core/tools/provider/builtin/feishu_base/feishu_base.py deleted file mode 100644 index 04056af53b5f95..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/feishu_base.py +++ /dev/null @@ -1,8 +0,0 @@ -from core.tools.provider.builtin.feishu_base.tools.get_tenant_access_token import GetTenantAccessTokenTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class FeishuBaseProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - GetTenantAccessTokenTool() - pass diff --git a/api/core/tools/provider/builtin/feishu_base/feishu_base.yaml b/api/core/tools/provider/builtin/feishu_base/feishu_base.yaml deleted file mode 100644 index f3dcbb6136b3a3..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/feishu_base.yaml +++ /dev/null @@ -1,14 +0,0 @@ -identity: - author: Doug Lea - name: feishu_base - label: - en_US: Feishu Base - zh_Hans: 飞书多维表格 - description: - en_US: Feishu Base - zh_Hans: 飞书多维表格 - icon: icon.svg - tags: - - social - - productivity -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/feishu_base/tools/add_base_record.py b/api/core/tools/provider/builtin/feishu_base/tools/add_base_record.py deleted file mode 100644 index 4a605fbffeef0b..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/add_base_record.py +++ /dev/null @@ -1,56 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class AddBaseRecordTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - table_id = tool_parameters.get("table_id", "") - if not table_id: - return self.create_text_message("Invalid parameter table_id") - - fields = tool_parameters.get("fields", "") - if not fields: - return self.create_text_message("Invalid parameter fields") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - params = {} - payload = {"fields": json.loads(fields)} - - try: - res = httpx.post( - url.format(app_token=app_token, table_id=table_id), - headers=headers, - params=params, - json=payload, - timeout=30, - ) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to add base record, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to add base record. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/add_base_record.yaml b/api/core/tools/provider/builtin/feishu_base/tools/add_base_record.yaml deleted file mode 100644 index 3ce0154efd69dc..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/add_base_record.yaml +++ /dev/null @@ -1,66 +0,0 @@ -identity: - name: add_base_record - author: Doug Lea - label: - en_US: Add Base Record - zh_Hans: 在多维表格数据表中新增一条记录 -description: - human: - en_US: Add Base Record - zh_Hans: | - 在多维表格数据表中新增一条记录，详细请参考：https://open.larkoffice.com/document/server-docs/docs/bitable-v1/app-table-record/create - llm: Add a new record in the multidimensional table data table. -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm - - - name: table_id - type: string - required: true - label: - en_US: table_id - zh_Hans: 多维表格的数据表 - human_description: - en_US: bitable table id - zh_Hans: 多维表格数据表的唯一标识符 table_id - llm_description: bitable table id - form: llm - - - name: fields - type: string - required: true - label: - en_US: fields - zh_Hans: 数据表的列字段内容 - human_description: - en_US: The fields of the Base data table are the columns of the data table. - zh_Hans: | - 要增加一行多维表格记录，字段结构拼接如下：{"多行文本":"多行文本内容","单选":"选项1","多选":["选项1","选项2"],"复选框":true,"人员":[{"id":"ou_2910013f1e6456f16a0ce75ede950a0a"}],"群组":[{"id":"oc_cd07f55f14d6f4a4f1b51504e7e97f48"}],"电话号码":"13026162666"} - 当前接口支持的字段类型为：多行文本、单选、条码、多选、日期、人员、附件、复选框、超链接、数字、单向关联、双向关联、电话号码、地理位置。 - 不同类型字段的数据结构请参考数据结构概述：https://open.larkoffice.com/document/server-docs/docs/bitable-v1/bitable-structure - llm_description: | - 要增加一行多维表格记录，字段结构拼接如下：{"多行文本":"多行文本内容","单选":"选项1","多选":["选项1","选项2"],"复选框":true,"人员":[{"id":"ou_2910013f1e6456f16a0ce75ede950a0a"}],"群组":[{"id":"oc_cd07f55f14d6f4a4f1b51504e7e97f48"}],"电话号码":"13026162666"} - 当前接口支持的字段类型为：多行文本、单选、条码、多选、日期、人员、附件、复选框、超链接、数字、单向关联、双向关联、电话号码、地理位置。 - 不同类型字段的数据结构请参考数据结构概述：https://open.larkoffice.com/document/server-docs/docs/bitable-v1/bitable-structure - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/create_base.py b/api/core/tools/provider/builtin/feishu_base/tools/create_base.py deleted file mode 100644 index 6b755e2007d7d6..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/create_base.py +++ /dev/null @@ -1,41 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class CreateBaseTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - name = tool_parameters.get("name", "") - folder_token = tool_parameters.get("folder_token", "") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - params = {} - payload = {"name": name, "folder_token": folder_token} - - try: - res = httpx.post(url, headers=headers, params=params, json=payload, timeout=30) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to create base, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to create base. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/create_base.yaml b/api/core/tools/provider/builtin/feishu_base/tools/create_base.yaml deleted file mode 100644 index 76c76a916d4951..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/create_base.yaml +++ /dev/null @@ -1,47 +0,0 @@ -identity: - name: create_base - author: Doug Lea - label: - en_US: Create Base - zh_Hans: 创建多维表格 -description: - human: - en_US: Create base - zh_Hans: 在指定目录下创建多维表格 - llm: A tool for create a multidimensional table in the specified directory. -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: name - type: string - required: false - label: - en_US: name - zh_Hans: name - human_description: - en_US: Base App Name - zh_Hans: 多维表格App名字 - llm_description: Base App Name - form: llm - - - name: folder_token - type: string - required: false - label: - en_US: folder_token - zh_Hans: 多维表格App归属文件夹 - human_description: - en_US: Base App home folder. The default is empty, indicating that Base will be created in the cloud space root directory. - zh_Hans: 多维表格App归属文件夹。默认为空，表示多维表格将被创建在云空间根目录。 - llm_description: Base App home folder. The default is empty, indicating that Base will be created in the cloud space root directory. - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/create_base_table.py b/api/core/tools/provider/builtin/feishu_base/tools/create_base_table.py deleted file mode 100644 index b05d700113880b..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/create_base_table.py +++ /dev/null @@ -1,48 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class CreateBaseTableTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - name = tool_parameters.get("name", "") - - fields = tool_parameters.get("fields", "") - if not fields: - return self.create_text_message("Invalid parameter fields") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - params = {} - payload = {"table": {"name": name, "fields": json.loads(fields)}} - - try: - res = httpx.post(url.format(app_token=app_token), headers=headers, params=params, json=payload, timeout=30) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to create base table, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to create base table. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/create_base_table.yaml b/api/core/tools/provider/builtin/feishu_base/tools/create_base_table.yaml deleted file mode 100644 index 48c46bec14f448..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/create_base_table.yaml +++ /dev/null @@ -1,106 +0,0 @@ -identity: - name: create_base_table - author: Doug Lea - label: - en_US: Create Base Table - zh_Hans: 多维表格新增一个数据表 -description: - human: - en_US: Create base table - zh_Hans: | - 多维表格新增一个数据表，详细请参考：https://open.larkoffice.com/document/server-docs/docs/bitable-v1/app-table/create - llm: A tool for add a new data table to the multidimensional table. -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm - - - name: name - type: string - required: false - label: - en_US: name - zh_Hans: name - human_description: - en_US: Multidimensional table data table name - zh_Hans: 多维表格数据表名称 - llm_description: Multidimensional table data table name - form: llm - - - name: fields - type: string - required: true - label: - en_US: fields - zh_Hans: fields - human_description: - en_US: Initial fields of the data table - zh_Hans: | - 数据表的初始字段，格式为：[{"field_name":"多行文本","type":1},{"field_name":"数字","type":2},{"field_name":"单选","type":3},{"field_name":"多选","type":4},{"field_name":"日期","type":5}]。 - field_name：字段名； - type: 字段类型；可选值有 - 1：多行文本 - 2：数字 - 3：单选 - 4：多选 - 5：日期 - 7：复选框 - 11：人员 - 13：电话号码 - 15：超链接 - 17：附件 - 18：单向关联 - 20：公式 - 21：双向关联 - 22：地理位置 - 23：群组 - 1001：创建时间 - 1002：最后更新时间 - 1003：创建人 - 1004：修改人 - 1005：自动编号 - llm_description: | - 数据表的初始字段，格式为：[{"field_name":"多行文本","type":1},{"field_name":"数字","type":2},{"field_name":"单选","type":3},{"field_name":"多选","type":4},{"field_name":"日期","type":5}]。 - field_name：字段名； - type: 字段类型；可选值有 - 1：多行文本 - 2：数字 - 3：单选 - 4：多选 - 5：日期 - 7：复选框 - 11：人员 - 13：电话号码 - 15：超链接 - 17：附件 - 18：单向关联 - 20：公式 - 21：双向关联 - 22：地理位置 - 23：群组 - 1001：创建时间 - 1002：最后更新时间 - 1003：创建人 - 1004：修改人 - 1005：自动编号 - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/delete_base_records.py b/api/core/tools/provider/builtin/feishu_base/tools/delete_base_records.py deleted file mode 100644 index 862eb2171b9269..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/delete_base_records.py +++ /dev/null @@ -1,56 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DeleteBaseRecordsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records/batch_delete" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - table_id = tool_parameters.get("table_id", "") - if not table_id: - return self.create_text_message("Invalid parameter table_id") - - record_ids = tool_parameters.get("record_ids", "") - if not record_ids: - return self.create_text_message("Invalid parameter record_ids") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - params = {} - payload = {"records": json.loads(record_ids)} - - try: - res = httpx.post( - url.format(app_token=app_token, table_id=table_id), - headers=headers, - params=params, - json=payload, - timeout=30, - ) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to delete base records, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to delete base records. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/delete_base_records.yaml b/api/core/tools/provider/builtin/feishu_base/tools/delete_base_records.yaml deleted file mode 100644 index 595b2870298af9..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/delete_base_records.yaml +++ /dev/null @@ -1,60 +0,0 @@ -identity: - name: delete_base_records - author: Doug Lea - label: - en_US: Delete Base Records - zh_Hans: 在多维表格数据表中删除多条记录 -description: - human: - en_US: Delete base records - zh_Hans: | - 该接口用于删除多维表格数据表中的多条记录，单次调用中最多删除 500 条记录。 - llm: A tool for delete multiple records in a multidimensional table data table, up to 500 records can be deleted in a single call. -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm - - - name: table_id - type: string - required: true - label: - en_US: table_id - zh_Hans: 多维表格的数据表 - human_description: - en_US: bitable table id - zh_Hans: 多维表格数据表的唯一标识符 table_id - llm_description: bitable table id - form: llm - - - name: record_ids - type: string - required: true - label: - en_US: record_ids - zh_Hans: record_ids - human_description: - en_US: A list of multiple record IDs to be deleted, for example ["recwNXzPQv","recpCsf4ME"] - zh_Hans: 待删除的多条记录id列表，示例为 ["recwNXzPQv","recpCsf4ME"] - llm_description: A list of multiple record IDs to be deleted, for example ["recwNXzPQv","recpCsf4ME"] - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/delete_base_tables.py b/api/core/tools/provider/builtin/feishu_base/tools/delete_base_tables.py deleted file mode 100644 index f5121863035313..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/delete_base_tables.py +++ /dev/null @@ -1,46 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DeleteBaseTablesTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/batch_delete" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - table_ids = tool_parameters.get("table_ids", "") - if not table_ids: - return self.create_text_message("Invalid parameter table_ids") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - params = {} - payload = {"table_ids": json.loads(table_ids)} - - try: - res = httpx.post(url.format(app_token=app_token), headers=headers, params=params, json=payload, timeout=30) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to delete base tables, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to delete base tables. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/delete_base_tables.yaml b/api/core/tools/provider/builtin/feishu_base/tools/delete_base_tables.yaml deleted file mode 100644 index 5d72814363d86f..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/delete_base_tables.yaml +++ /dev/null @@ -1,48 +0,0 @@ -identity: - name: delete_base_tables - author: Doug Lea - label: - en_US: Delete Base Tables - zh_Hans: 删除多维表格中的数据表 -description: - human: - en_US: Delete base tables - zh_Hans: | - 删除多维表格中的数据表 - llm: A tool for deleting a data table in a multidimensional table -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm - - - name: table_ids - type: string - required: true - label: - en_US: table_ids - zh_Hans: table_ids - human_description: - en_US: The ID list of the data tables to be deleted. Currently, a maximum of 50 data tables can be deleted at a time. The example is ["tbl1TkhyTWDkSoZ3","tblsRc9GRRXKqhvW"] - zh_Hans: 待删除数据表的id列表，当前一次操作最多支持50个数据表，示例为 ["tbl1TkhyTWDkSoZ3","tblsRc9GRRXKqhvW"] - llm_description: The ID list of the data tables to be deleted. Currently, a maximum of 50 data tables can be deleted at a time. The example is ["tbl1TkhyTWDkSoZ3","tblsRc9GRRXKqhvW"] - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/get_base_info.py b/api/core/tools/provider/builtin/feishu_base/tools/get_base_info.py deleted file mode 100644 index f664bbeed08693..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/get_base_info.py +++ /dev/null @@ -1,39 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetBaseInfoTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - try: - res = httpx.get(url.format(app_token=app_token), headers=headers, timeout=30) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to get base info, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to get base info. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/get_base_info.yaml b/api/core/tools/provider/builtin/feishu_base/tools/get_base_info.yaml deleted file mode 100644 index de0868901834ee..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/get_base_info.yaml +++ /dev/null @@ -1,54 +0,0 @@ -identity: - name: get_base_info - author: Doug Lea - label: - en_US: Get Base Info - zh_Hans: 获取多维表格元数据 -description: - human: - en_US: Get base info - zh_Hans: | - 获取多维表格元数据，响应体如下: - { - "code": 0, - "msg": "success", - "data": { - "app": { - "app_token": "appbcbWCzen6D8dezhoCH2RpMAh", - "name": "mybase", - "revision": 1, - "is_advanced": false, - "time_zone": "Asia/Beijing" - } - } - } - app_token: 多维表格的 app_token; - name: 多维表格的名字; - revision: 多维表格的版本号; - is_advanced: 多维表格是否开启了高级权限。取值包括：(true-表示开启了高级权限，false-表示关闭了高级权限); - time_zone: 文档时区; - llm: A tool to get Base Metadata, imported parameter is Unique Device Identifier app_token of Base, app_token is required. -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/get_tenant_access_token.py b/api/core/tools/provider/builtin/feishu_base/tools/get_tenant_access_token.py deleted file mode 100644 index 2ea61d0068237b..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/get_tenant_access_token.py +++ /dev/null @@ -1,48 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetTenantAccessTokenTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal" - - app_id = tool_parameters.get("app_id", "") - if not app_id: - return self.create_text_message("Invalid parameter app_id") - - app_secret = tool_parameters.get("app_secret", "") - if not app_secret: - return self.create_text_message("Invalid parameter app_secret") - - headers = { - "Content-Type": "application/json", - } - params = {} - payload = {"app_id": app_id, "app_secret": app_secret} - - """ - { - "code": 0, - "msg": "ok", - "tenant_access_token": "t-caecc734c2e3328a62489fe0648c4b98779515d3", - "expire": 7200 - } - """ - try: - res = httpx.post(url, headers=headers, params=params, json=payload, timeout=30) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to get tenant access token, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to get tenant access token. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/get_tenant_access_token.yaml b/api/core/tools/provider/builtin/feishu_base/tools/get_tenant_access_token.yaml deleted file mode 100644 index 88acc27e06eca1..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/get_tenant_access_token.yaml +++ /dev/null @@ -1,39 +0,0 @@ -identity: - name: get_tenant_access_token - author: Doug Lea - label: - en_US: Get Tenant Access Token - zh_Hans: 获取飞书自建应用的 tenant_access_token -description: - human: - en_US: Get tenant access token - zh_Hans: | - 获取飞书自建应用的 tenant_access_token，响应体示例: - {"code":0,"msg":"ok","tenant_access_token":"t-caecc734c2e3328a62489fe0648c4b98779515d3","expire":7200} - tenant_access_token: 租户访问凭证; - expire: tenant_access_token 的过期时间，单位为秒; - llm: A tool for obtaining a tenant access token. The input parameters must include app_id and app_secret. -parameters: - - name: app_id - type: string - required: true - label: - en_US: app_id - zh_Hans: 应用唯一标识 - human_description: - en_US: app_id is the unique identifier of the Lark Open Platform application - zh_Hans: app_id 是飞书开放平台应用的唯一标识 - llm_description: app_id is the unique identifier of the Lark Open Platform application - form: llm - - - name: app_secret - type: secret-input - required: true - label: - en_US: app_secret - zh_Hans: 应用秘钥 - human_description: - en_US: app_secret is the secret key of the application - zh_Hans: app_secret 是应用的秘钥 - llm_description: app_secret is the secret key of the application - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/list_base_records.py b/api/core/tools/provider/builtin/feishu_base/tools/list_base_records.py deleted file mode 100644 index e579d02f6967e7..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/list_base_records.py +++ /dev/null @@ -1,65 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class ListBaseRecordsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records/search" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - table_id = tool_parameters.get("table_id", "") - if not table_id: - return self.create_text_message("Invalid parameter table_id") - - page_token = tool_parameters.get("page_token", "") - page_size = tool_parameters.get("page_size", "") - sort_condition = tool_parameters.get("sort_condition", "") - filter_condition = tool_parameters.get("filter_condition", "") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - params = { - "page_token": page_token, - "page_size": page_size, - } - - payload = {"automatic_fields": True} - if sort_condition: - payload["sort"] = json.loads(sort_condition) - if filter_condition: - payload["filter"] = json.loads(filter_condition) - - try: - res = httpx.post( - url.format(app_token=app_token, table_id=table_id), - headers=headers, - params=params, - json=payload, - timeout=30, - ) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to list base records, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to list base records. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/list_base_records.yaml b/api/core/tools/provider/builtin/feishu_base/tools/list_base_records.yaml deleted file mode 100644 index 8647c880a60024..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/list_base_records.yaml +++ /dev/null @@ -1,108 +0,0 @@ -identity: - name: list_base_records - author: Doug Lea - label: - en_US: List Base Records - zh_Hans: 查询多维表格数据表中的现有记录 -description: - human: - en_US: List base records - zh_Hans: | - 查询多维表格数据表中的现有记录，单次最多查询 500 行记录，支持分页获取。 - llm: Query existing records in a multidimensional table data table. A maximum of 500 rows of records can be queried at a time, and paging retrieval is supported. -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm - - - name: table_id - type: string - required: true - label: - en_US: table_id - zh_Hans: 多维表格的数据表 - human_description: - en_US: bitable table id - zh_Hans: 多维表格数据表的唯一标识符 table_id - llm_description: bitable table id - form: llm - - - name: page_token - type: string - required: false - label: - en_US: page_token - zh_Hans: 分页标记 - human_description: - en_US: Pagination mark. If it is not filled in the first request, it means to traverse from the beginning. - zh_Hans: 分页标记，第一次请求不填，表示从头开始遍历。 - llm_description: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 - form: llm - - - name: page_size - type: number - required: false - default: 20 - label: - en_US: page_size - zh_Hans: 分页大小 - human_description: - en_US: paging size - zh_Hans: 分页大小，默认值为 20，最大值为 100。 - llm_description: The default value of paging size is 20 and the maximum value is 100. - form: llm - - - name: sort_condition - type: string - required: false - label: - en_US: sort_condition - zh_Hans: 排序条件 - human_description: - en_US: sort condition - zh_Hans: | - 排序条件，格式为：[{"field_name":"多行文本","desc":true}]。 - field_name: 字段名称； - desc: 是否倒序排序; - llm_description: | - Sorting conditions, the format is: [{"field_name":"multi-line text","desc":true}]. - form: llm - - - name: filter_condition - type: string - required: false - label: - en_US: filter_condition - zh_Hans: 筛选条件 - human_description: - en_US: filter condition - zh_Hans: | - 筛选条件，格式为：{"conjunction":"and","conditions":[{"field_name":"字段1","operator":"is","value":["文本内容"]}]}。 - conjunction：条件逻辑连接词； - conditions：筛选条件集合； - field_name：筛选条件的左值，值为字段的名称； - operator：条件运算符； - value：目标值； - llm_description: | - The format of the filter condition is: {"conjunction":"and","conditions":[{"field_name":"Field 1","operator":"is","value":["text content"]}]}. - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/list_base_tables.py b/api/core/tools/provider/builtin/feishu_base/tools/list_base_tables.py deleted file mode 100644 index 4ec9a476bc8832..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/list_base_tables.py +++ /dev/null @@ -1,47 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class ListBaseTablesTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - page_token = tool_parameters.get("page_token", "") - page_size = tool_parameters.get("page_size", "") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - params = { - "page_token": page_token, - "page_size": page_size, - } - - try: - res = httpx.get(url.format(app_token=app_token), headers=headers, params=params, timeout=30) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to list base tables, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to list base tables. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/list_base_tables.yaml b/api/core/tools/provider/builtin/feishu_base/tools/list_base_tables.yaml deleted file mode 100644 index 9887124a28823a..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/list_base_tables.yaml +++ /dev/null @@ -1,65 +0,0 @@ -identity: - name: list_base_tables - author: Doug Lea - label: - en_US: List Base Tables - zh_Hans: 根据 app_token 获取多维表格下的所有数据表 -description: - human: - en_US: List base tables - zh_Hans: | - 根据 app_token 获取多维表格下的所有数据表 - llm: A tool for getting all data tables under a multidimensional table based on app_token. -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm - - - name: page_token - type: string - required: false - label: - en_US: page_token - zh_Hans: 分页标记 - human_description: - en_US: Pagination mark. If it is not filled in the first request, it means to traverse from the beginning. - zh_Hans: 分页标记，第一次请求不填，表示从头开始遍历。 - llm_description: | - Pagination token. If it is not filled in the first request, it means to start traversal from the beginning. - If there are more items in the pagination query result, a new page_token will be returned at the same time. - The page_token can be used to obtain the query result in the next traversal. - 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 - form: llm - - - name: page_size - type: number - required: false - default: 20 - label: - en_US: page_size - zh_Hans: 分页大小 - human_description: - en_US: paging size - zh_Hans: 分页大小，默认值为 20，最大值为 100。 - llm_description: The default value of paging size is 20 and the maximum value is 100. - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/read_base_record.py b/api/core/tools/provider/builtin/feishu_base/tools/read_base_record.py deleted file mode 100644 index fb818f838073fa..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/read_base_record.py +++ /dev/null @@ -1,49 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class ReadBaseRecordTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records/{record_id}" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - table_id = tool_parameters.get("table_id", "") - if not table_id: - return self.create_text_message("Invalid parameter table_id") - - record_id = tool_parameters.get("record_id", "") - if not record_id: - return self.create_text_message("Invalid parameter record_id") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - try: - res = httpx.get( - url.format(app_token=app_token, table_id=table_id, record_id=record_id), headers=headers, timeout=30 - ) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to read base record, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to read base record. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/read_base_record.yaml b/api/core/tools/provider/builtin/feishu_base/tools/read_base_record.yaml deleted file mode 100644 index 400e9a1021f2db..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/read_base_record.yaml +++ /dev/null @@ -1,60 +0,0 @@ -identity: - name: read_base_record - author: Doug Lea - label: - en_US: Read Base Record - zh_Hans: 根据 record_id 的值检索多维表格数据表的记录 -description: - human: - en_US: Read base record - zh_Hans: | - 根据 record_id 的值检索多维表格数据表的记录 - llm: Retrieve records from a multidimensional table based on the value of record_id -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm - - - name: table_id - type: string - required: true - label: - en_US: table_id - zh_Hans: 多维表格的数据表 - human_description: - en_US: bitable table id - zh_Hans: 多维表格数据表的唯一标识符 table_id - llm_description: bitable table id - form: llm - - - name: record_id - type: string - required: true - label: - en_US: record_id - zh_Hans: 单条记录的 id - human_description: - en_US: The id of a single record - zh_Hans: 单条记录的 id - llm_description: The id of a single record - form: llm diff --git a/api/core/tools/provider/builtin/feishu_base/tools/update_base_record.py b/api/core/tools/provider/builtin/feishu_base/tools/update_base_record.py deleted file mode 100644 index 6d7e33f3ffef7c..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/update_base_record.py +++ /dev/null @@ -1,60 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class UpdateBaseRecordTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - url = "https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records/{record_id}" - - access_token = tool_parameters.get("Authorization", "") - if not access_token: - return self.create_text_message("Invalid parameter access_token") - - app_token = tool_parameters.get("app_token", "") - if not app_token: - return self.create_text_message("Invalid parameter app_token") - - table_id = tool_parameters.get("table_id", "") - if not table_id: - return self.create_text_message("Invalid parameter table_id") - - record_id = tool_parameters.get("record_id", "") - if not record_id: - return self.create_text_message("Invalid parameter record_id") - - fields = tool_parameters.get("fields", "") - if not fields: - return self.create_text_message("Invalid parameter fields") - - headers = { - "Content-Type": "application/json", - "Authorization": f"Bearer {access_token}", - } - - params = {} - payload = {"fields": json.loads(fields)} - - try: - res = httpx.put( - url.format(app_token=app_token, table_id=table_id, record_id=record_id), - headers=headers, - params=params, - json=payload, - timeout=30, - ) - res_json = res.json() - if res.is_success: - return self.create_text_message(text=json.dumps(res_json)) - else: - return self.create_text_message( - f"Failed to update base record, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to update base record. {}".format(e)) diff --git a/api/core/tools/provider/builtin/feishu_base/tools/update_base_record.yaml b/api/core/tools/provider/builtin/feishu_base/tools/update_base_record.yaml deleted file mode 100644 index 788798c4b3b40e..00000000000000 --- a/api/core/tools/provider/builtin/feishu_base/tools/update_base_record.yaml +++ /dev/null @@ -1,78 +0,0 @@ -identity: - name: update_base_record - author: Doug Lea - label: - en_US: Update Base Record - zh_Hans: 更新多维表格数据表中的一条记录 -description: - human: - en_US: Update base record - zh_Hans: | - 更新多维表格数据表中的一条记录，详细请参考：https://open.larkoffice.com/document/server-docs/docs/bitable-v1/app-table-record/update - llm: Update a record in a multidimensional table data table -parameters: - - name: Authorization - type: string - required: true - label: - en_US: token - zh_Hans: 凭证 - human_description: - en_US: API access token parameter, tenant_access_token or user_access_token - zh_Hans: API 的访问凭证参数，tenant_access_token 或 user_access_token - llm_description: API access token parameter, tenant_access_token or user_access_token - form: llm - - - name: app_token - type: string - required: true - label: - en_US: app_token - zh_Hans: 多维表格 - human_description: - en_US: bitable app token - zh_Hans: 多维表格的唯一标识符 app_token - llm_description: bitable app token - form: llm - - - name: table_id - type: string - required: true - label: - en_US: table_id - zh_Hans: 多维表格的数据表 - human_description: - en_US: bitable table id - zh_Hans: 多维表格数据表的唯一标识符 table_id - llm_description: bitable table id - form: llm - - - name: record_id - type: string - required: true - label: - en_US: record_id - zh_Hans: 单条记录的 id - human_description: - en_US: The id of a single record - zh_Hans: 单条记录的 id - llm_description: The id of a single record - form: llm - - - name: fields - type: string - required: true - label: - en_US: fields - zh_Hans: 数据表的列字段内容 - human_description: - en_US: The fields of a multidimensional table data table, that is, the columns of the data table. - zh_Hans: | - 要更新一行多维表格记录，字段结构拼接如下：{"多行文本":"多行文本内容","单选":"选项1","多选":["选项1","选项2"],"复选框":true,"人员":[{"id":"ou_2910013f1e6456f16a0ce75ede950a0a"}],"群组":[{"id":"oc_cd07f55f14d6f4a4f1b51504e7e97f48"}],"电话号码":"13026162666"} - 当前接口支持的字段类型为：多行文本、单选、条码、多选、日期、人员、附件、复选框、超链接、数字、单向关联、双向关联、电话号码、地理位置。 - 不同类型字段的数据结构请参考数据结构概述：https://open.larkoffice.com/document/server-docs/docs/bitable-v1/bitable-structure - llm_description: | - 要更新一行多维表格记录，字段结构拼接如下：{"多行文本":"多行文本内容","单选":"选项1","多选":["选项1","选项2"],"复选框":true,"人员":[{"id":"ou_2910013f1e6456f16a0ce75ede950a0a"}],"群组":[{"id":"oc_cd07f55f14d6f4a4f1b51504e7e97f48"}],"电话号码":"13026162666"} - 当前接口支持的字段类型为：多行文本、单选、条码、多选、日期、人员、附件、复选框、超链接、数字、单向关联、双向关联、电话号码、地理位置。 - 不同类型字段的数据结构请参考数据结构概述：https://open.larkoffice.com/document/server-docs/docs/bitable-v1/bitable-structure - form: llm diff --git a/api/core/tools/provider/builtin/feishu_document/_assets/icon.svg b/api/core/tools/provider/builtin/feishu_document/_assets/icon.svg deleted file mode 100644 index 5a0a6416b3db32..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/_assets/icon.svg +++ /dev/null @@ -1,9 +0,0 @@ - - - - - - - - - diff --git a/api/core/tools/provider/builtin/feishu_document/feishu_document.py b/api/core/tools/provider/builtin/feishu_document/feishu_document.py deleted file mode 100644 index b0a1e393eb8116..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/feishu_document.py +++ /dev/null @@ -1,15 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController -from core.tools.utils.feishu_api_utils import FeishuRequest - - -class FeishuDocumentProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - app_id = credentials.get("app_id") - app_secret = credentials.get("app_secret") - if not app_id or not app_secret: - raise ToolProviderCredentialValidationError("app_id and app_secret is required") - try: - assert FeishuRequest(app_id, app_secret).tenant_access_token is not None - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/feishu_document/feishu_document.yaml b/api/core/tools/provider/builtin/feishu_document/feishu_document.yaml deleted file mode 100644 index 8eaa6b27049c6b..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/feishu_document.yaml +++ /dev/null @@ -1,34 +0,0 @@ -identity: - author: Doug Lea - name: feishu_document - label: - en_US: Lark Cloud Document - zh_Hans: 飞书云文档 - description: - en_US: Lark Cloud Document - zh_Hans: 飞书云文档 - icon: icon.svg - tags: - - social - - productivity -credentials_for_provider: - app_id: - type: text-input - required: true - label: - en_US: APP ID - placeholder: - en_US: Please input your feishu app id - zh_Hans: 请输入你的飞书 app id - help: - en_US: Get your app_id and app_secret from Feishu - zh_Hans: 从飞书获取您的 app_id 和 app_secret - url: https://open.feishu.cn - app_secret: - type: secret-input - required: true - label: - en_US: APP Secret - placeholder: - en_US: Please input your app secret - zh_Hans: 请输入你的飞书 app secret diff --git a/api/core/tools/provider/builtin/feishu_document/tools/create_document.py b/api/core/tools/provider/builtin/feishu_document/tools/create_document.py deleted file mode 100644 index 090a0828e89bbf..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/tools/create_document.py +++ /dev/null @@ -1,19 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.utils.feishu_api_utils import FeishuRequest - - -class CreateDocumentTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - app_id = self.runtime.credentials.get("app_id") - app_secret = self.runtime.credentials.get("app_secret") - client = FeishuRequest(app_id, app_secret) - - title = tool_parameters.get("title") - content = tool_parameters.get("content") - folder_token = tool_parameters.get("folder_token") - - res = client.create_document(title, content, folder_token) - return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_document/tools/create_document.yaml b/api/core/tools/provider/builtin/feishu_document/tools/create_document.yaml deleted file mode 100644 index ddf2729f0e4b5c..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/tools/create_document.yaml +++ /dev/null @@ -1,47 +0,0 @@ -identity: - name: create_document - author: Doug Lea - label: - en_US: Create Lark document - zh_Hans: 创建飞书文档 -description: - human: - en_US: Create Lark document - zh_Hans: 创建飞书文档，支持创建空文档和带内容的文档，支持 markdown 语法创建。 - llm: A tool for creating Feishu documents. -parameters: - - name: title - type: string - required: false - label: - en_US: Document title - zh_Hans: 文档标题 - human_description: - en_US: Document title, only supports plain text content. - zh_Hans: 文档标题，只支持纯文本内容。 - llm_description: 文档标题，只支持纯文本内容，可以为空。 - form: llm - - - name: content - type: string - required: false - label: - en_US: Document content - zh_Hans: 文档内容 - human_description: - en_US: Document content, supports markdown syntax, can be empty. - zh_Hans: 文档内容，支持 markdown 语法，可以为空。 - llm_description: 文档内容，支持 markdown 语法，可以为空。 - form: llm - - - name: folder_token - type: string - required: false - label: - en_US: folder_token - zh_Hans: 文档所在文件夹的 Token - human_description: - en_US: The token of the folder where the document is located. If it is not passed or is empty, it means the root directory. - zh_Hans: 文档所在文件夹的 Token，不传或传空表示根目录。 - llm_description: 文档所在文件夹的 Token，不传或传空表示根目录。 - form: llm diff --git a/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.py b/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.py deleted file mode 100644 index c94a5f70ed7e34..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.py +++ /dev/null @@ -1,19 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.utils.feishu_api_utils import FeishuRequest - - -class GetDocumentRawContentTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - app_id = self.runtime.credentials.get("app_id") - app_secret = self.runtime.credentials.get("app_secret") - client = FeishuRequest(app_id, app_secret) - - document_id = tool_parameters.get("document_id") - mode = tool_parameters.get("mode") - lang = tool_parameters.get("lang", 0) - - res = client.get_document_content(document_id, mode, lang) - return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.yaml b/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.yaml deleted file mode 100644 index 51eda73a60095c..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/tools/get_document_content.yaml +++ /dev/null @@ -1,49 +0,0 @@ -identity: - name: get_document_content - author: Doug Lea - label: - en_US: Get Document Content - zh_Hans: 获取飞书云文档的内容 -description: - human: - en_US: Get document content - zh_Hans: 获取飞书云文档的内容 - llm: A tool for retrieving content from Feishu cloud documents. -parameters: - - name: document_id - type: string - required: true - label: - en_US: document_id - zh_Hans: 飞书文档的唯一标识 - human_description: - en_US: Unique identifier for a Feishu document. You can also input the document's URL. - zh_Hans: 飞书文档的唯一标识，支持输入文档的 URL。 - llm_description: 飞书文档的唯一标识，支持输入文档的 URL。 - form: llm - - - name: mode - type: string - required: false - label: - en_US: mode - zh_Hans: 文档返回格式 - human_description: - en_US: Format of the document return, optional values are text, markdown, can be empty, default is markdown. - zh_Hans: 文档返回格式，可选值有 text、markdown，可以为空，默认值为 markdown。 - llm_description: 文档返回格式，可选值有 text、markdown，可以为空，默认值为 markdown。 - form: llm - - - name: lang - type: number - required: false - default: 0 - label: - en_US: lang - zh_Hans: 指定@用户的语言 - human_description: - en_US: | - Specifies the language for MentionUser, optional values are [0, 1]. 0: User's default name, 1: User's English name, default is 0. - zh_Hans: 指定返回的 MentionUser，即 @用户 的语言，可选值有 [0,1]。0：该用户的默认名称，1：该用户的英文名称，默认值为 0。 - llm_description: 指定返回的 MentionUser，即 @用户 的语言，可选值有 [0,1]。0：该用户的默认名称，1：该用户的英文名称，默认值为 0。 - form: llm diff --git a/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.py b/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.py deleted file mode 100644 index 572a7abf284193..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.py +++ /dev/null @@ -1,19 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.utils.feishu_api_utils import FeishuRequest - - -class ListDocumentBlockTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - app_id = self.runtime.credentials.get("app_id") - app_secret = self.runtime.credentials.get("app_secret") - client = FeishuRequest(app_id, app_secret) - - document_id = tool_parameters.get("document_id") - page_size = tool_parameters.get("page_size", 500) - page_token = tool_parameters.get("page_token", "") - - res = client.list_document_blocks(document_id, page_token, page_size) - return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.yaml b/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.yaml deleted file mode 100644 index 019ac983906ff1..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/tools/list_document_blocks.yaml +++ /dev/null @@ -1,74 +0,0 @@ -identity: - name: list_document_blocks - author: Doug Lea - label: - en_US: List Document Blocks - zh_Hans: 获取飞书文档所有块 -description: - human: - en_US: List document blocks - zh_Hans: 获取飞书文档所有块的富文本内容并分页返回 - llm: A tool to get all blocks of Feishu documents -parameters: - - name: document_id - type: string - required: true - label: - en_US: document_id - zh_Hans: 飞书文档的唯一标识 - human_description: - en_US: Unique identifier for a Feishu document. You can also input the document's URL. - zh_Hans: 飞书文档的唯一标识，支持输入文档的 URL。 - llm_description: 飞书文档的唯一标识，支持输入文档的 URL。 - form: llm - - - name: user_id_type - type: select - required: false - options: - - value: open_id - label: - en_US: open_id - zh_Hans: open_id - - value: union_id - label: - en_US: union_id - zh_Hans: union_id - - value: user_id - label: - en_US: user_id - zh_Hans: user_id - default: "open_id" - label: - en_US: user_id_type - zh_Hans: 用户 ID 类型 - human_description: - en_US: User ID type, optional values are open_id, union_id, user_id, with a default value of open_id. - zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 - llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id，默认值为 open_id。 - form: llm - - - name: page_size - type: number - required: false - default: "500" - label: - en_US: page_size - zh_Hans: 分页大小 - human_description: - en_US: Paging size, the default and maximum value is 500. - zh_Hans: 分页大小, 默认值和最大值为 500。 - llm_description: 分页大小, 表示一次请求最多返回多少条数据，默认值和最大值为 500。 - form: llm - - - name: page_token - type: string - required: false - label: - en_US: page_token - zh_Hans: 分页标记 - human_description: - en_US: Pagination token used to navigate through query results, allowing retrieval of additional items in subsequent requests. - zh_Hans: 分页标记，用于分页查询结果，以便下次遍历时获取更多项。 - llm_description: 分页标记，第一次请求不填，表示从头开始遍历；分页查询结果还有更多项时会同时返回新的 page_token，下次遍历可采用该 page_token 获取查询结果。 - form: llm diff --git a/api/core/tools/provider/builtin/feishu_document/tools/write_document.py b/api/core/tools/provider/builtin/feishu_document/tools/write_document.py deleted file mode 100644 index 6061250e48e136..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/tools/write_document.py +++ /dev/null @@ -1,19 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.utils.feishu_api_utils import FeishuRequest - - -class CreateDocumentTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - app_id = self.runtime.credentials.get("app_id") - app_secret = self.runtime.credentials.get("app_secret") - client = FeishuRequest(app_id, app_secret) - - document_id = tool_parameters.get("document_id") - content = tool_parameters.get("content") - position = tool_parameters.get("position") - - res = client.write_document(document_id, content, position) - return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_document/tools/write_document.yaml b/api/core/tools/provider/builtin/feishu_document/tools/write_document.yaml deleted file mode 100644 index 4282e3dcf3977f..00000000000000 --- a/api/core/tools/provider/builtin/feishu_document/tools/write_document.yaml +++ /dev/null @@ -1,59 +0,0 @@ -identity: - name: write_document - author: Doug Lea - label: - en_US: Write Document - zh_Hans: 在飞书文档中新增内容 -description: - human: - en_US: Adding new content to Lark documents - zh_Hans: 在飞书文档中新增内容 - llm: A tool for adding new content to Lark documents. -parameters: - - name: document_id - type: string - required: true - label: - en_US: document_id - zh_Hans: 飞书文档的唯一标识 - human_description: - en_US: Unique identifier for a Feishu document. You can also input the document's URL. - zh_Hans: 飞书文档的唯一标识，支持输入文档的 URL。 - llm_description: 飞书文档的唯一标识，支持输入文档的 URL。 - form: llm - - - name: content - type: string - required: true - label: - en_US: Plain text or Markdown content - zh_Hans: 纯文本或 Markdown 内容 - human_description: - en_US: Plain text or Markdown content. Note that embedded tables in the document should not have merged cells. - zh_Hans: 纯文本或 Markdown 内容。注意文档的内嵌套表格不允许有单元格合并。 - llm_description: 纯文本或 Markdown 内容，注意文档的内嵌套表格不允许有单元格合并。 - form: llm - - - name: position - type: string - required: false - label: - en_US: position - zh_Hans: 添加位置 - human_description: - en_US: | - Enumeration values: start or end. Use 'start' to add content at the beginning of the document, and 'end' to add content at the end. The default value is 'end'. - zh_Hans: 枚举值：start 或 end。使用 'start' 在文档开头添加内容，使用 'end' 在文档结尾添加内容，默认值为 'end'。 - llm_description: | - 枚举值 start、end，start: 在文档开头添加内容；end: 在文档结尾添加内容，默认值为 end。 - form: llm - options: - - value: start - label: - en_US: start - zh_Hans: 在文档开头添加内容 - - value: end - label: - en_US: end - zh_Hans: 在文档结尾添加内容 - default: start diff --git a/api/core/tools/provider/builtin/feishu_message/_assets/icon.svg b/api/core/tools/provider/builtin/feishu_message/_assets/icon.svg deleted file mode 100644 index 222a1571f9bbbb..00000000000000 --- a/api/core/tools/provider/builtin/feishu_message/_assets/icon.svg +++ /dev/null @@ -1,19 +0,0 @@ - - - - diff --git a/api/core/tools/provider/builtin/feishu_message/feishu_message.py b/api/core/tools/provider/builtin/feishu_message/feishu_message.py deleted file mode 100644 index 7b3adb9293750b..00000000000000 --- a/api/core/tools/provider/builtin/feishu_message/feishu_message.py +++ /dev/null @@ -1,15 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController -from core.tools.utils.feishu_api_utils import FeishuRequest - - -class FeishuMessageProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - app_id = credentials.get("app_id") - app_secret = credentials.get("app_secret") - if not app_id or not app_secret: - raise ToolProviderCredentialValidationError("app_id and app_secret is required") - try: - assert FeishuRequest(app_id, app_secret).tenant_access_token is not None - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/feishu_message/feishu_message.yaml b/api/core/tools/provider/builtin/feishu_message/feishu_message.yaml deleted file mode 100644 index 1bd8953dddcb24..00000000000000 --- a/api/core/tools/provider/builtin/feishu_message/feishu_message.yaml +++ /dev/null @@ -1,34 +0,0 @@ -identity: - author: Doug Lea - name: feishu_message - label: - en_US: Lark Message - zh_Hans: 飞书消息 - description: - en_US: Lark Message - zh_Hans: 飞书消息 - icon: icon.svg - tags: - - social - - productivity -credentials_for_provider: - app_id: - type: text-input - required: true - label: - en_US: APP ID - placeholder: - en_US: Please input your feishu app id - zh_Hans: 请输入你的飞书 app id - help: - en_US: Get your app_id and app_secret from Feishu - zh_Hans: 从飞书获取您的 app_id 和 app_secret - url: https://open.feishu.cn - app_secret: - type: secret-input - required: true - label: - en_US: APP Secret - placeholder: - en_US: Please input your app secret - zh_Hans: 请输入你的飞书 app secret diff --git a/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.py b/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.py deleted file mode 100644 index 1dd315d0e293a0..00000000000000 --- a/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.utils.feishu_api_utils import FeishuRequest - - -class SendBotMessageTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - app_id = self.runtime.credentials.get("app_id") - app_secret = self.runtime.credentials.get("app_secret") - client = FeishuRequest(app_id, app_secret) - - receive_id_type = tool_parameters.get("receive_id_type") - receive_id = tool_parameters.get("receive_id") - msg_type = tool_parameters.get("msg_type") - content = tool_parameters.get("content") - - res = client.send_bot_message(receive_id_type, receive_id, msg_type, content) - return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.yaml b/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.yaml deleted file mode 100644 index 6e398b18ab3aee..00000000000000 --- a/api/core/tools/provider/builtin/feishu_message/tools/send_bot_message.yaml +++ /dev/null @@ -1,91 +0,0 @@ -identity: - name: send_bot_message - author: Doug Lea - label: - en_US: Send Bot Message - zh_Hans: 发送飞书应用消息 -description: - human: - en_US: Send bot message - zh_Hans: 发送飞书应用消息 - llm: A tool for sending Feishu application messages. -parameters: - - name: receive_id_type - type: select - required: true - options: - - value: open_id - label: - en_US: open id - zh_Hans: open id - - value: union_id - label: - en_US: union id - zh_Hans: union id - - value: user_id - label: - en_US: user id - zh_Hans: user id - - value: email - label: - en_US: email - zh_Hans: email - - value: chat_id - label: - en_US: chat id - zh_Hans: chat id - label: - en_US: User ID Type - zh_Hans: 用户 ID 类型 - human_description: - en_US: User ID Type - zh_Hans: 用户 ID 类型，可选值有 open_id、union_id、user_id、email、chat_id。 - llm_description: 用户 ID 类型，可选值有 open_id、union_id、user_id、email、chat_id。 - form: llm - - - name: receive_id - type: string - required: true - label: - en_US: Receive Id - zh_Hans: 消息接收者的 ID - human_description: - en_US: The ID of the message receiver. The ID type should correspond to the query parameter receive_id_type. - zh_Hans: 消息接收者的 ID，ID 类型应与查询参数 receive_id_type 对应。 - llm_description: 消息接收者的 ID，ID 类型应与查询参数 receive_id_type 对应。 - form: llm - - - name: msg_type - type: string - required: true - options: - - value: text - label: - en_US: text - zh_Hans: 文本 - - value: interactive - label: - en_US: message card - zh_Hans: 消息卡片 - label: - en_US: Message type - zh_Hans: 消息类型 - human_description: - en_US: Message type, optional values are, text (text), interactive (message card). - zh_Hans: 消息类型，可选值有：text(文本)、interactive(消息卡片)。 - llm_description: 消息类型，可选值有：text(文本)、interactive(消息卡片)。 - form: llm - - - name: content - type: string - required: true - label: - en_US: Message content - zh_Hans: 消息内容 - human_description: - en_US: Message content - zh_Hans: | - 消息内容，JSON 结构序列化后的字符串。不同 msg_type 对应不同内容， - 具体格式说明参考：https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json - llm_description: 消息内容，JSON 结构序列化后的字符串。不同 msg_type 对应不同内容。 - form: llm diff --git a/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.py b/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.py deleted file mode 100644 index 44e70e0a15b64d..00000000000000 --- a/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.py +++ /dev/null @@ -1,19 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.utils.feishu_api_utils import FeishuRequest - - -class SendWebhookMessageTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - app_id = self.runtime.credentials.get("app_id") - app_secret = self.runtime.credentials.get("app_secret") - client = FeishuRequest(app_id, app_secret) - - webhook = tool_parameters.get("webhook") - msg_type = tool_parameters.get("msg_type") - content = tool_parameters.get("content") - - res = client.send_webhook_message(webhook, msg_type, content) - return self.create_json_message(res) diff --git a/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.yaml b/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.yaml deleted file mode 100644 index 8b39ce4874d506..00000000000000 --- a/api/core/tools/provider/builtin/feishu_message/tools/send_webhook_message.yaml +++ /dev/null @@ -1,58 +0,0 @@ -identity: - name: send_webhook_message - author: Doug Lea - label: - en_US: Send Webhook Message - zh_Hans: 使用自定义机器人发送飞书消息 -description: - human: - en_US: Send webhook message - zh_Hans: 使用自定义机器人发送飞书消息 - llm: A tool for sending Lark messages using a custom robot. -parameters: - - name: webhook - type: string - required: true - label: - en_US: webhook - zh_Hans: webhook 的地址 - human_description: - en_US: The address of the webhook - zh_Hans: webhook 的地址 - llm_description: webhook 的地址 - form: llm - - - name: msg_type - type: string - required: true - options: - - value: text - label: - en_US: text - zh_Hans: 文本 - - value: interactive - label: - en_US: message card - zh_Hans: 消息卡片 - label: - en_US: Message type - zh_Hans: 消息类型 - human_description: - en_US: Message type, optional values are, text (text), interactive (message card). - zh_Hans: 消息类型，可选值有：text(文本)、interactive(消息卡片)。 - llm_description: 消息类型，可选值有：text(文本)、interactive(消息卡片)。 - form: llm - - - name: content - type: string - required: true - label: - en_US: Message content - zh_Hans: 消息内容 - human_description: - en_US: Message content - zh_Hans: | - 消息内容，JSON 结构序列化后的字符串。不同 msg_type 对应不同内容， - 具体格式说明参考：https://open.larkoffice.com/document/server-docs/im-v1/message-content-description/create_json - llm_description: 消息内容，JSON 结构序列化后的字符串。不同 msg_type 对应不同内容。 - form: llm diff --git a/api/core/tools/provider/builtin/firecrawl/_assets/icon.svg b/api/core/tools/provider/builtin/firecrawl/_assets/icon.svg deleted file mode 100644 index e1e5f54117b1be..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/_assets/icon.svg +++ /dev/null @@ -1,3 +0,0 @@ - - 🔥 - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/firecrawl/firecrawl.py b/api/core/tools/provider/builtin/firecrawl/firecrawl.py deleted file mode 100644 index 01455d7206f185..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/firecrawl.py +++ /dev/null @@ -1,14 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.firecrawl.tools.scrape import ScrapeTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class FirecrawlProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - # Example validation using the ScrapeTool, only scraping title for minimize content - ScrapeTool().fork_tool_runtime(runtime={"credentials": credentials}).invoke( - user_id="", tool_parameters={"url": "https://google.com", "onlyIncludeTags": "title"} - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/firecrawl/firecrawl.yaml b/api/core/tools/provider/builtin/firecrawl/firecrawl.yaml deleted file mode 100644 index a48b9d9f541eb3..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/firecrawl.yaml +++ /dev/null @@ -1,35 +0,0 @@ -identity: - author: Richards Tu - name: firecrawl - label: - en_US: Firecrawl - zh_CN: Firecrawl - description: - en_US: Firecrawl API integration for web crawling and scraping. - zh_Hans: Firecrawl API 集成，用于网页爬取和数据抓取。 - icon: icon.svg - tags: - - search - - utilities -credentials_for_provider: - firecrawl_api_key: - type: secret-input - required: true - label: - en_US: Firecrawl API Key - zh_Hans: Firecrawl API 密钥 - placeholder: - en_US: Please input your Firecrawl API key - zh_Hans: 请输入您的 Firecrawl API 密钥，如果是自托管版本，可以随意填写密钥 - help: - en_US: Get your Firecrawl API key from your Firecrawl account settings.If you are using a self-hosted version, you may enter any key at your convenience. - zh_Hans: 从您的 Firecrawl 账户设置中获取 Firecrawl API 密钥。如果是自托管版本，可以随意填写密钥。 - url: https://www.firecrawl.dev/account - base_url: - type: text-input - required: false - label: - en_US: Firecrawl server's Base URL - zh_Hans: Firecrawl服务器的API URL - placeholder: - en_US: https://api.firecrawl.dev diff --git a/api/core/tools/provider/builtin/firecrawl/firecrawl_appx.py b/api/core/tools/provider/builtin/firecrawl/firecrawl_appx.py deleted file mode 100644 index d9fb6f04bcfa75..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/firecrawl_appx.py +++ /dev/null @@ -1,122 +0,0 @@ -import json -import logging -import time -from collections.abc import Mapping -from typing import Any - -import requests -from requests.exceptions import HTTPError - -logger = logging.getLogger(__name__) - - -class FirecrawlApp: - def __init__(self, api_key: str | None = None, base_url: str | None = None): - self.api_key = api_key - self.base_url = base_url or "https://api.firecrawl.dev" - if not self.api_key: - raise ValueError("API key is required") - - def _prepare_headers(self, idempotency_key: str | None = None): - headers = {"Content-Type": "application/json", "Authorization": f"Bearer {self.api_key}"} - if idempotency_key: - headers["Idempotency-Key"] = idempotency_key - return headers - - def _request( - self, - method: str, - url: str, - data: Mapping[str, Any] | None = None, - headers: Mapping[str, str] | None = None, - retries: int = 3, - backoff_factor: float = 0.3, - ) -> Mapping[str, Any] | None: - if not headers: - headers = self._prepare_headers() - for i in range(retries): - try: - response = requests.request(method, url, json=data, headers=headers) - return response.json() - except requests.exceptions.RequestException: - if i < retries - 1: - time.sleep(backoff_factor * (2**i)) - else: - raise - return None - - def scrape_url(self, url: str, **kwargs): - endpoint = f"{self.base_url}/v1/scrape" - data = {"url": url, **kwargs} - logger.debug(f"Sent request to {endpoint=} body={data}") - response = self._request("POST", endpoint, data) - if response is None: - raise HTTPError("Failed to scrape URL after multiple retries") - return response - - def map(self, url: str, **kwargs): - endpoint = f"{self.base_url}/v1/map" - data = {"url": url, **kwargs} - logger.debug(f"Sent request to {endpoint=} body={data}") - response = self._request("POST", endpoint, data) - if response is None: - raise HTTPError("Failed to perform map after multiple retries") - return response - - def crawl_url( - self, url: str, wait: bool = True, poll_interval: int = 5, idempotency_key: str | None = None, **kwargs - ): - endpoint = f"{self.base_url}/v1/crawl" - headers = self._prepare_headers(idempotency_key) - data = {"url": url, **kwargs} - logger.debug(f"Sent request to {endpoint=} body={data}") - response = self._request("POST", endpoint, data, headers) - if response is None: - raise HTTPError("Failed to initiate crawl after multiple retries") - elif response.get("success") == False: - raise HTTPError(f'Failed to crawl: {response.get("error")}') - job_id: str = response["id"] - if wait: - return self._monitor_job_status(job_id=job_id, poll_interval=poll_interval) - return response - - def check_crawl_status(self, job_id: str): - endpoint = f"{self.base_url}/v1/crawl/{job_id}" - response = self._request("GET", endpoint) - if response is None: - raise HTTPError(f"Failed to check status for job {job_id} after multiple retries") - return response - - def cancel_crawl_job(self, job_id: str): - endpoint = f"{self.base_url}/v1/crawl/{job_id}" - response = self._request("DELETE", endpoint) - if response is None: - raise HTTPError(f"Failed to cancel job {job_id} after multiple retries") - return response - - def _monitor_job_status(self, job_id: str, poll_interval: int): - while True: - status = self.check_crawl_status(job_id) - if status["status"] == "completed": - return status - elif status["status"] == "failed": - raise HTTPError(f'Job {job_id} failed: {status["error"]}') - time.sleep(poll_interval) - - -def get_array_params(tool_parameters: dict[str, Any], key): - param = tool_parameters.get(key) - if param: - return param.split(",") - - -def get_json_params(tool_parameters: dict[str, Any], key): - param = tool_parameters.get(key) - if param: - try: - # support both single quotes and double quotes - param = param.replace("'", '"') - param = json.loads(param) - except Exception: - raise ValueError(f"Invalid {key} format.") - return param diff --git a/api/core/tools/provider/builtin/firecrawl/tools/crawl.py b/api/core/tools/provider/builtin/firecrawl/tools/crawl.py deleted file mode 100644 index 9675b8eb913351..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/tools/crawl.py +++ /dev/null @@ -1,45 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.firecrawl.firecrawl_appx import FirecrawlApp, get_array_params, get_json_params -from core.tools.tool.builtin_tool import BuiltinTool - - -class CrawlTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - """ - the api doc: - https://docs.firecrawl.dev/api-reference/endpoint/crawl - """ - app = FirecrawlApp( - api_key=self.runtime.credentials["firecrawl_api_key"], base_url=self.runtime.credentials["base_url"] - ) - - scrapeOptions = {} - payload = {} - - wait_for_results = tool_parameters.get("wait_for_results", True) - - payload["excludePaths"] = get_array_params(tool_parameters, "excludePaths") - payload["includePaths"] = get_array_params(tool_parameters, "includePaths") - payload["maxDepth"] = tool_parameters.get("maxDepth") - payload["ignoreSitemap"] = tool_parameters.get("ignoreSitemap", False) - payload["limit"] = tool_parameters.get("limit", 5) - payload["allowBackwardLinks"] = tool_parameters.get("allowBackwardLinks", False) - payload["allowExternalLinks"] = tool_parameters.get("allowExternalLinks", False) - payload["webhook"] = tool_parameters.get("webhook") - - scrapeOptions["formats"] = get_array_params(tool_parameters, "formats") - scrapeOptions["headers"] = get_json_params(tool_parameters, "headers") - scrapeOptions["includeTags"] = get_array_params(tool_parameters, "includeTags") - scrapeOptions["excludeTags"] = get_array_params(tool_parameters, "excludeTags") - scrapeOptions["onlyMainContent"] = tool_parameters.get("onlyMainContent", False) - scrapeOptions["waitFor"] = tool_parameters.get("waitFor", 0) - scrapeOptions = {k: v for k, v in scrapeOptions.items() if v not in {None, ""}} - payload["scrapeOptions"] = scrapeOptions or None - - payload = {k: v for k, v in payload.items() if v not in {None, ""}} - - crawl_result = app.crawl_url(url=tool_parameters["url"], wait=wait_for_results, **payload) - - return self.create_json_message(crawl_result) diff --git a/api/core/tools/provider/builtin/firecrawl/tools/crawl.yaml b/api/core/tools/provider/builtin/firecrawl/tools/crawl.yaml deleted file mode 100644 index 0d7dbcac20ea16..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/tools/crawl.yaml +++ /dev/null @@ -1,200 +0,0 @@ -identity: - name: crawl - author: Richards Tu - label: - en_US: Crawl - zh_Hans: 深度爬取 -description: - human: - en_US: Recursively search through a urls subdomains, and gather the content. - zh_Hans: 递归爬取一个网址的子域名，并收集内容。 - llm: This tool initiates a web crawl to extract data from a specified URL. It allows configuring crawler options such as including or excluding URL patterns, generating alt text for images using LLMs (paid plan required), limiting the maximum number of pages to crawl, and returning only the main content of the page. The tool can return either a list of crawled documents or a list of URLs based on the provided options. -parameters: - - name: url - type: string - required: true - label: - en_US: Start URL - zh_Hans: 起始URL - human_description: - en_US: The base URL to start crawling from. - zh_Hans: 要爬取网站的起始URL。 - llm_description: The URL of the website that needs to be crawled. This is a required parameter. - form: llm - - name: wait_for_results - type: boolean - default: true - label: - en_US: Wait For Results - zh_Hans: 等待爬取结果 - human_description: - en_US: If you choose not to wait, it will directly return a job ID. You can use this job ID to check the crawling results or cancel the crawling task, which is usually very useful for a large-scale crawling task. - zh_Hans: 如果选择不等待，则会直接返回一个job_id，可以通过job_id查询爬取结果或取消爬取任务，这通常对于一个大型爬取任务来说非常有用。 - form: form -############## Payload ####################### - - name: excludePaths - type: string - label: - en_US: URL patterns to exclude - zh_Hans: 要排除的URL模式 - placeholder: - en_US: Use commas to separate multiple tags - zh_Hans: 多个标签时使用半角逗号分隔 - human_description: - en_US: | - Pages matching these patterns will be skipped. Example: blog/*, about/* - zh_Hans: 匹配这些模式的页面将被跳过。示例：blog/*, about/* - form: form - - name: includePaths - type: string - required: false - label: - en_US: URL patterns to include - zh_Hans: 要包含的URL模式 - placeholder: - en_US: Use commas to separate multiple tags - zh_Hans: 多个标签时使用半角逗号分隔 - human_description: - en_US: | - Only pages matching these patterns will be crawled. Example: blog/*, about/* - zh_Hans: 只有与这些模式匹配的页面才会被爬取。示例：blog/*, about/* - form: form - - name: maxDepth - type: number - label: - en_US: Maximum crawl depth - zh_Hans: 爬取深度 - human_description: - en_US: Maximum depth to crawl relative to the entered URL. A maxDepth of 0 scrapes only the entered URL. A maxDepth of 1 scrapes the entered URL and all pages one level deep. A maxDepth of 2 scrapes the entered URL and all pages up to two levels deep. Higher values follow the same pattern. - zh_Hans: 相对于输入的URL，爬取的最大深度。maxDepth为0时，仅抓取输入的URL。maxDepth为1时，抓取输入的URL以及所有一级深层页面。maxDepth为2时，抓取输入的URL以及所有两级深层页面。更高值遵循相同模式。 - form: form - min: 0 - default: 2 - - name: ignoreSitemap - type: boolean - default: true - label: - en_US: ignore Sitemap - zh_Hans: 忽略站点地图 - human_description: - en_US: Ignore the website sitemap when crawling. - zh_Hans: 爬取时忽略网站站点地图。 - form: form - - name: limit - type: number - required: false - label: - en_US: Maximum pages to crawl - zh_Hans: 最大爬取页面数 - human_description: - en_US: Specify the maximum number of pages to crawl. The crawler will stop after reaching this limit. - zh_Hans: 指定要爬取的最大页面数。爬虫将在达到此限制后停止。 - form: form - min: 1 - default: 5 - - name: allowBackwardLinks - type: boolean - default: false - label: - en_US: allow Backward Crawling - zh_Hans: 允许向后爬取 - human_description: - en_US: Enables the crawler to navigate from a specific URL to previously linked pages. For instance, from 'example.com/product/123' back to 'example.com/product' - zh_Hans: 使爬虫能够从特定URL导航到之前链接的页面。例如，从'example.com/product/123'返回到'example.com/product' - form: form - - name: allowExternalLinks - type: boolean - default: false - label: - en_US: allow External Content Links - zh_Hans: 允许爬取外链 - human_description: - en_US: Allows the crawler to follow links to external websites. - zh_Hans: - form: form - - name: webhook - type: string - label: - en_US: webhook - human_description: - en_US: | - The URL to send the webhook to. This will trigger for crawl started (crawl.started) ,every page crawled (crawl.page) and when the crawl is completed (crawl.completed or crawl.failed). The response will be the same as the /scrape endpoint. - zh_Hans: 发送Webhook的URL。这将在开始爬取（crawl.started）、每爬取一个页面（crawl.page）以及爬取完成（crawl.completed或crawl.failed）时触发。响应将与/scrape端点相同。 - form: form -############## Scrape Options ####################### - - name: formats - type: string - label: - en_US: Formats - zh_Hans: 结果的格式 - placeholder: - en_US: Use commas to separate multiple tags - zh_Hans: 多个标签时使用半角逗号分隔 - human_description: - en_US: | - Formats to include in the output. Available options: markdown, html, rawHtml, links, screenshot - zh_Hans: | - 输出中应包含的格式。可以填入: markdown, html, rawHtml, links, screenshot - form: form - - name: headers - type: string - label: - en_US: headers - zh_Hans: 请求头 - human_description: - en_US: | - Headers to send with the request. Can be used to send cookies, user-agent, etc. Example: {"cookies": "testcookies"} - zh_Hans: | - 随请求发送的头部。可以用来发送cookies、用户代理等。示例：{"cookies": "testcookies"} - placeholder: - en_US: Please enter an object that can be serialized in JSON - zh_Hans: 请输入可以json序列化的对象 - form: form - - name: includeTags - type: string - label: - en_US: Include Tags - zh_Hans: 仅抓取这些标签 - placeholder: - en_US: Use commas to separate multiple tags - zh_Hans: 多个标签时使用半角逗号分隔 - human_description: - en_US: | - Only include tags, classes and ids from the page in the final output. Use comma separated values. Example: script, .ad, #footer - zh_Hans: | - 仅在最终输出中包含HTML页面的这些标签，可以通过标签名、类或ID来设定，使用逗号分隔值。示例：script, .ad, #footer - form: form - - name: excludeTags - type: string - label: - en_US: Exclude Tags - zh_Hans: 要移除这些标签 - human_description: - en_US: | - Tags, classes and ids to remove from the page. Use comma separated values. Example: script, .ad, #footer - zh_Hans: | - 要在最终输出中移除HTML页面的这些标签，可以通过标签名、类或ID来设定，使用逗号分隔值。示例：script, .ad, #footer - placeholder: - en_US: Use commas to separate multiple tags - zh_Hans: 多个标签时使用半角逗号分隔 - form: form - - name: onlyMainContent - type: boolean - default: false - label: - en_US: only Main Content - zh_Hans: 仅抓取主要内容 - human_description: - en_US: Only return the main content of the page excluding headers, navs, footers, etc. - zh_Hans: 只返回页面的主要内容，不包括头部、导航栏、尾部等。 - form: form - - name: waitFor - type: number - min: 0 - label: - en_US: wait For - zh_Hans: 等待时间 - human_description: - en_US: Wait x amount of milliseconds for the page to load to fetch content. - zh_Hans: 等待x毫秒以使页面加载并获取内容。 - form: form diff --git a/api/core/tools/provider/builtin/firecrawl/tools/crawl_job.py b/api/core/tools/provider/builtin/firecrawl/tools/crawl_job.py deleted file mode 100644 index 0d2486c7ca4426..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/tools/crawl_job.py +++ /dev/null @@ -1,21 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.firecrawl.firecrawl_appx import FirecrawlApp -from core.tools.tool.builtin_tool import BuiltinTool - - -class CrawlJobTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - app = FirecrawlApp( - api_key=self.runtime.credentials["firecrawl_api_key"], base_url=self.runtime.credentials["base_url"] - ) - operation = tool_parameters.get("operation", "get") - if operation == "get": - result = app.check_crawl_status(job_id=tool_parameters["job_id"]) - elif operation == "cancel": - result = app.cancel_crawl_job(job_id=tool_parameters["job_id"]) - else: - raise ValueError(f"Invalid operation: {operation}") - - return self.create_json_message(result) diff --git a/api/core/tools/provider/builtin/firecrawl/tools/crawl_job.yaml b/api/core/tools/provider/builtin/firecrawl/tools/crawl_job.yaml deleted file mode 100644 index 78008e4ad4d8a6..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/tools/crawl_job.yaml +++ /dev/null @@ -1,37 +0,0 @@ -identity: - name: crawl_job - author: hjlarry - label: - en_US: Crawl Job - zh_Hans: 爬取任务处理 -description: - human: - en_US: Retrieve the scraping results based on the job ID, or cancel the scraping task. - zh_Hans: 根据爬取任务ID获取爬取结果，或者取消爬取任务 - llm: Retrieve the scraping results based on the job ID, or cancel the scraping task. -parameters: - - name: job_id - type: string - required: true - label: - en_US: Job ID - human_description: - en_US: Set wait_for_results to false in the Crawl tool can get the job ID. - zh_Hans: 在深度爬取工具中将等待爬取结果设置为否可以获取Job ID。 - llm_description: Set wait_for_results to false in the Crawl tool can get the job ID. - form: llm - - name: operation - type: select - required: true - options: - - value: get - label: - en_US: get crawl status - - value: cancel - label: - en_US: cancel crawl job - label: - en_US: operation - zh_Hans: 操作 - llm_description: choose the operation to perform. `get` is for getting the crawl status, `cancel` is for cancelling the crawl job. - form: llm diff --git a/api/core/tools/provider/builtin/firecrawl/tools/map.py b/api/core/tools/provider/builtin/firecrawl/tools/map.py deleted file mode 100644 index bdfb5faeb8e2c9..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/tools/map.py +++ /dev/null @@ -1,25 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.firecrawl.firecrawl_appx import FirecrawlApp -from core.tools.tool.builtin_tool import BuiltinTool - - -class MapTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage: - """ - the api doc: - https://docs.firecrawl.dev/api-reference/endpoint/map - """ - app = FirecrawlApp( - api_key=self.runtime.credentials["firecrawl_api_key"], base_url=self.runtime.credentials["base_url"] - ) - payload = {} - payload["search"] = tool_parameters.get("search") - payload["ignoreSitemap"] = tool_parameters.get("ignoreSitemap", True) - payload["includeSubdomains"] = tool_parameters.get("includeSubdomains", False) - payload["limit"] = tool_parameters.get("limit", 5000) - - map_result = app.map(url=tool_parameters["url"], **payload) - - return self.create_json_message(map_result) diff --git a/api/core/tools/provider/builtin/firecrawl/tools/map.yaml b/api/core/tools/provider/builtin/firecrawl/tools/map.yaml deleted file mode 100644 index 9913756983370a..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/tools/map.yaml +++ /dev/null @@ -1,59 +0,0 @@ -identity: - name: map - author: hjlarry - label: - en_US: Map - zh_Hans: 地图式快爬 -description: - human: - en_US: Input a website and get all the urls on the website - extremly fast - zh_Hans: 输入一个网站，快速获取网站上的所有网址。 - llm: Input a website and get all the urls on the website - extremly fast -parameters: - - name: url - type: string - required: true - label: - en_US: Start URL - zh_Hans: 起始URL - human_description: - en_US: The base URL to start crawling from. - zh_Hans: 要爬取网站的起始URL。 - llm_description: The URL of the website that needs to be crawled. This is a required parameter. - form: llm - - name: search - type: string - label: - en_US: search - zh_Hans: 搜索查询 - human_description: - en_US: Search query to use for mapping. During the Alpha phase, the 'smart' part of the search functionality is limited to 100 search results. However, if map finds more results, there is no limit applied. - zh_Hans: 用于映射的搜索查询。在Alpha阶段，搜索功能的“智能”部分限制为最多100个搜索结果。然而，如果地图找到了更多结果，则不施加任何限制。 - llm_description: Search query to use for mapping. During the Alpha phase, the 'smart' part of the search functionality is limited to 100 search results. However, if map finds more results, there is no limit applied. - form: llm -############## Page Options ####################### - - name: ignoreSitemap - type: boolean - default: true - label: - en_US: ignore Sitemap - zh_Hans: 忽略站点地图 - human_description: - en_US: Ignore the website sitemap when crawling. - zh_Hans: 爬取时忽略网站站点地图。 - form: form - - name: includeSubdomains - type: boolean - default: false - label: - en_US: include Subdomains - zh_Hans: 包含子域名 - form: form - - name: limit - type: number - min: 0 - default: 5000 - label: - en_US: Maximum results - zh_Hans: 最大结果数量 - form: form diff --git a/api/core/tools/provider/builtin/firecrawl/tools/scrape.py b/api/core/tools/provider/builtin/firecrawl/tools/scrape.py deleted file mode 100644 index 538b4a1fcbf056..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/tools/scrape.py +++ /dev/null @@ -1,39 +0,0 @@ -from typing import Any - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.firecrawl.firecrawl_appx import FirecrawlApp, get_array_params, get_json_params -from core.tools.tool.builtin_tool import BuiltinTool - - -class ScrapeTool(BuiltinTool): - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> list[ToolInvokeMessage]: - """ - the api doc: - https://docs.firecrawl.dev/api-reference/endpoint/scrape - """ - app = FirecrawlApp( - api_key=self.runtime.credentials["firecrawl_api_key"], base_url=self.runtime.credentials["base_url"] - ) - - payload = {} - extract = {} - - payload["formats"] = get_array_params(tool_parameters, "formats") - payload["onlyMainContent"] = tool_parameters.get("onlyMainContent", True) - payload["includeTags"] = get_array_params(tool_parameters, "includeTags") - payload["excludeTags"] = get_array_params(tool_parameters, "excludeTags") - payload["headers"] = get_json_params(tool_parameters, "headers") - payload["waitFor"] = tool_parameters.get("waitFor", 0) - payload["timeout"] = tool_parameters.get("timeout", 30000) - - extract["schema"] = get_json_params(tool_parameters, "schema") - extract["systemPrompt"] = tool_parameters.get("systemPrompt") - extract["prompt"] = tool_parameters.get("prompt") - extract = {k: v for k, v in extract.items() if v not in {None, ""}} - payload["extract"] = extract or None - - payload = {k: v for k, v in payload.items() if v not in {None, ""}} - - crawl_result = app.scrape_url(url=tool_parameters["url"], **payload) - markdown_result = crawl_result.get("data", {}).get("markdown", "") - return [self.create_text_message(markdown_result), self.create_json_message(crawl_result)] diff --git a/api/core/tools/provider/builtin/firecrawl/tools/scrape.yaml b/api/core/tools/provider/builtin/firecrawl/tools/scrape.yaml deleted file mode 100644 index 8f1f1348a459ca..00000000000000 --- a/api/core/tools/provider/builtin/firecrawl/tools/scrape.yaml +++ /dev/null @@ -1,152 +0,0 @@ -identity: - name: scrape - author: ahasasjeb - label: - en_US: Scrape - zh_Hans: 单页面抓取 -description: - human: - en_US: Turn any url into clean data. - zh_Hans: 将任何网址转换为干净的数据。 - llm: This tool is designed to scrape URL and output the content in Markdown format. -parameters: - - name: url - type: string - required: true - label: - en_US: URL to scrape - zh_Hans: 要抓取的URL - human_description: - en_US: The URL of the website to scrape and extract data from. - zh_Hans: 要抓取并提取数据的网站URL。 - llm_description: The URL of the website that needs to be crawled. This is a required parameter. - form: llm -############## Payload ####################### - - name: formats - type: string - label: - en_US: Formats - zh_Hans: 结果的格式 - placeholder: - en_US: Use commas to separate multiple tags - zh_Hans: 多个标签时使用半角逗号分隔 - human_description: - en_US: | - Formats to include in the output. Available options: markdown, html, rawHtml, links, screenshot, extract, screenshot@fullPage - zh_Hans: | - 输出中应包含的格式。可以填入: markdown, html, rawHtml, links, screenshot, extract, screenshot@fullPage - form: form - - name: onlyMainContent - type: boolean - default: false - label: - en_US: only Main Content - zh_Hans: 仅抓取主要内容 - human_description: - en_US: Only return the main content of the page excluding headers, navs, footers, etc. - zh_Hans: 只返回页面的主要内容，不包括头部、导航栏、尾部等。 - form: form - - name: includeTags - type: string - label: - en_US: Include Tags - zh_Hans: 仅抓取这些标签 - placeholder: - en_US: Use commas to separate multiple tags - zh_Hans: 多个标签时使用半角逗号分隔 - human_description: - en_US: | - Only include tags, classes and ids from the page in the final output. Use comma separated values. Example: script, .ad, #footer - zh_Hans: | - 仅在最终输出中包含HTML页面的这些标签，可以通过标签名、类或ID来设定，使用逗号分隔值。示例：script, .ad, #footer - form: form - - name: excludeTags - type: string - label: - en_US: Exclude Tags - zh_Hans: 要移除这些标签 - human_description: - en_US: | - Tags, classes and ids to remove from the page. Use comma separated values. Example: script, .ad, #footer - zh_Hans: | - 要在最终输出中移除HTML页面的这些标签，可以通过标签名、类或ID来设定，使用逗号分隔值。示例：script, .ad, #footer - placeholder: - en_US: Use commas to separate multiple tags - zh_Hans: 多个标签时使用半角逗号分隔 - form: form - - name: headers - type: string - label: - en_US: headers - zh_Hans: 请求头 - human_description: - en_US: | - Headers to send with the request. Can be used to send cookies, user-agent, etc. Example: {"cookies": "testcookies"} - zh_Hans: | - 随请求发送的头部。可以用来发送cookies、用户代理等。示例：{"cookies": "testcookies"} - placeholder: - en_US: Please enter an object that can be serialized in JSON - zh_Hans: 请输入可以json序列化的对象 - form: form - - name: waitFor - type: number - min: 0 - default: 0 - label: - en_US: wait For - zh_Hans: 等待时间 - human_description: - en_US: Wait x amount of milliseconds for the page to load to fetch content. - zh_Hans: 等待x毫秒以使页面加载并获取内容。 - form: form - - name: timeout - type: number - min: 0 - default: 30000 - label: - en_US: Timeout - human_description: - en_US: Timeout in milliseconds for the request. - zh_Hans: 请求的超时时间（以毫秒为单位）。 - form: form -############## Extractor Options ####################### - - name: schema - type: string - label: - en_US: Extractor Schema - zh_Hans: 提取时的结构 - placeholder: - en_US: Please enter an object that can be serialized in JSON - zh_Hans: 请输入可以json序列化的对象 - human_description: - en_US: | - The schema for the data to be extracted. Example: { - "type": "object", - "properties": {"company_mission": {"type": "string"}}, - "required": ["company_mission"] - } - zh_Hans: | - 使用该结构去提取，示例：{ - "type": "object", - "properties": {"company_mission": {"type": "string"}}, - "required": ["company_mission"] - } - form: form - - name: systemPrompt - type: string - label: - en_US: Extractor System Prompt - zh_Hans: 提取时的系统提示词 - human_description: - en_US: The system prompt to use for the extraction. - zh_Hans: 用于提取的系统提示。 - form: form - - name: prompt - type: string - label: - en_US: Extractor Prompt - zh_Hans: 提取时的提示词 - human_description: - en_US: The prompt to use for the extraction without a schema. - zh_Hans: 用于无schema时提取的提示词 - form: form diff --git a/api/core/tools/provider/builtin/gaode/_assets/icon.svg b/api/core/tools/provider/builtin/gaode/_assets/icon.svg deleted file mode 100644 index 0f5729e17aea8d..00000000000000 --- a/api/core/tools/provider/builtin/gaode/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/gaode/gaode.py b/api/core/tools/provider/builtin/gaode/gaode.py deleted file mode 100644 index 49a8e537fb9070..00000000000000 --- a/api/core/tools/provider/builtin/gaode/gaode.py +++ /dev/null @@ -1,28 +0,0 @@ -import urllib.parse - -import requests - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class GaodeProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - if "api_key" not in credentials or not credentials.get("api_key"): - raise ToolProviderCredentialValidationError("Gaode API key is required.") - - try: - response = requests.get( - url="https://restapi.amap.com/v3/geocode/geo?address={address}&key={apikey}".format( - address=urllib.parse.quote("广东省广州市天河区广州塔"), apikey=credentials.get("api_key") - ) - ) - if response.status_code == 200 and (response.json()).get("info") == "OK": - pass - else: - raise ToolProviderCredentialValidationError((response.json()).get("info")) - except Exception as e: - raise ToolProviderCredentialValidationError("Gaode API Key is invalid. {}".format(e)) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/gaode/gaode.yaml b/api/core/tools/provider/builtin/gaode/gaode.yaml deleted file mode 100644 index 2eb3b161a29915..00000000000000 --- a/api/core/tools/provider/builtin/gaode/gaode.yaml +++ /dev/null @@ -1,34 +0,0 @@ -identity: - author: CharlieWei - name: gaode - label: - en_US: Autonavi - zh_Hans: 高德 - pt_BR: Autonavi - description: - en_US: Autonavi Open Platform service toolkit. - zh_Hans: 高德开放平台服务工具包。 - pt_BR: Kit de ferramentas de serviço Autonavi Open Platform. - icon: icon.svg - tags: - - utilities - - productivity - - travel - - weather -credentials_for_provider: - api_key: - type: secret-input - required: true - label: - en_US: API Key - zh_Hans: API Key - pt_BR: Fogo a chave - placeholder: - en_US: Please enter your Autonavi API Key - zh_Hans: 请输入你的高德开放平台 API Key - pt_BR: Insira sua chave de API Autonavi - help: - en_US: Get your API Key from Autonavi - zh_Hans: 从高德获取您的 API Key - pt_BR: Obtenha sua chave de API do Autonavi - url: https://console.amap.com/dev/key/app diff --git a/api/core/tools/provider/builtin/gaode/tools/gaode_weather.py b/api/core/tools/provider/builtin/gaode/tools/gaode_weather.py deleted file mode 100644 index ea06e2ce611cbc..00000000000000 --- a/api/core/tools/provider/builtin/gaode/tools/gaode_weather.py +++ /dev/null @@ -1,64 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GaodeRepositoriesTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - city = tool_parameters.get("city", "") - if not city: - return self.create_text_message("Please tell me your city") - - if "api_key" not in self.runtime.credentials or not self.runtime.credentials.get("api_key"): - return self.create_text_message("Gaode API key is required.") - - try: - s = requests.session() - api_domain = "https://restapi.amap.com/v3" - city_response = s.request( - method="GET", - headers={"Content-Type": "application/json; charset=utf-8"}, - url="{url}/config/district?keywords={keywords}&subdistrict=0&extensions=base&key={apikey}".format( - url=api_domain, keywords=city, apikey=self.runtime.credentials.get("api_key") - ), - ) - City_data = city_response.json() - if city_response.status_code == 200 and City_data.get("info") == "OK": - if len(City_data.get("districts")) > 0: - CityCode = City_data["districts"][0]["adcode"] - weatherInfo_response = s.request( - method="GET", - url="{url}/weather/weatherInfo?city={citycode}&extensions=all&key={apikey}&output=json" - "".format(url=api_domain, citycode=CityCode, apikey=self.runtime.credentials.get("api_key")), - ) - weatherInfo_data = weatherInfo_response.json() - if weatherInfo_response.status_code == 200 and weatherInfo_data.get("info") == "OK": - contents = [] - if len(weatherInfo_data.get("forecasts")) > 0: - for item in weatherInfo_data["forecasts"][0]["casts"]: - content = {} - content["date"] = item.get("date") - content["week"] = item.get("week") - content["dayweather"] = item.get("dayweather") - content["daytemp_float"] = item.get("daytemp_float") - content["daywind"] = item.get("daywind") - content["nightweather"] = item.get("nightweather") - content["nighttemp_float"] = item.get("nighttemp_float") - contents.append(content) - s.close() - return self.create_text_message( - self.summary(user_id=user_id, content=json.dumps(contents, ensure_ascii=False)) - ) - s.close() - return self.create_text_message(f"No weather information for {city} was found.") - except Exception as e: - return self.create_text_message("Gaode API Key and Api Version is invalid. {}".format(e)) diff --git a/api/core/tools/provider/builtin/gaode/tools/gaode_weather.yaml b/api/core/tools/provider/builtin/gaode/tools/gaode_weather.yaml deleted file mode 100644 index e41851e188edee..00000000000000 --- a/api/core/tools/provider/builtin/gaode/tools/gaode_weather.yaml +++ /dev/null @@ -1,28 +0,0 @@ -identity: - name: gaode_weather - author: CharlieWei - label: - en_US: Weather Forecast - zh_Hans: 天气预报 - pt_BR: Previsão do tempo - icon: icon.svg -description: - human: - en_US: Weather forecast inquiry - zh_Hans: 天气预报查询。 - pt_BR: Inquérito sobre previsão meteorológica. - llm: A tool when you want to ask about the weather or weather-related question. -parameters: - - name: city - type: string - required: true - label: - en_US: city - zh_Hans: 城市 - pt_BR: cidade - human_description: - en_US: Target city for weather forecast query. - zh_Hans: 天气预报查询的目标城市。 - pt_BR: Cidade de destino para consulta de previsão do tempo. - llm_description: If you don't know you can extract the city name from the question or you can reply：Please tell me your city. You have to extract the Chinese city name from the question. - form: llm diff --git a/api/core/tools/provider/builtin/getimgai/_assets/icon.svg b/api/core/tools/provider/builtin/getimgai/_assets/icon.svg deleted file mode 100644 index 6b2513386da458..00000000000000 --- a/api/core/tools/provider/builtin/getimgai/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/getimgai/getimgai.py b/api/core/tools/provider/builtin/getimgai/getimgai.py deleted file mode 100644 index bbd07d120fd0ea..00000000000000 --- a/api/core/tools/provider/builtin/getimgai/getimgai.py +++ /dev/null @@ -1,19 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.getimgai.tools.text2image import Text2ImageTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class GetImgAIProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - # Example validation using the text2image tool - Text2ImageTool().fork_tool_runtime(runtime={"credentials": credentials}).invoke( - user_id="", - tool_parameters={ - "prompt": "A fire egg", - "response_format": "url", - "style": "photorealism", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/getimgai/getimgai.yaml b/api/core/tools/provider/builtin/getimgai/getimgai.yaml deleted file mode 100644 index c9db0a9e22a6c4..00000000000000 --- a/api/core/tools/provider/builtin/getimgai/getimgai.yaml +++ /dev/null @@ -1,29 +0,0 @@ -identity: - author: Matri Qi - name: getimgai - label: - en_US: getimg.ai - zh_CN: getimg.ai - description: - en_US: GetImg API integration for image generation and scraping. - icon: icon.svg - tags: - - image -credentials_for_provider: - getimg_api_key: - type: secret-input - required: true - label: - en_US: getimg.ai API Key - placeholder: - en_US: Please input your getimg.ai API key - help: - en_US: Get your getimg.ai API key from your getimg.ai account settings. If you are using a self-hosted version, you may enter any key at your convenience. - url: https://dashboard.getimg.ai/api-keys - base_url: - type: text-input - required: false - label: - en_US: getimg.ai server's Base URL - placeholder: - en_US: https://api.getimg.ai/v1 diff --git a/api/core/tools/provider/builtin/getimgai/getimgai_appx.py b/api/core/tools/provider/builtin/getimgai/getimgai_appx.py deleted file mode 100644 index 0e95a5f654505f..00000000000000 --- a/api/core/tools/provider/builtin/getimgai/getimgai_appx.py +++ /dev/null @@ -1,55 +0,0 @@ -import logging -import time -from collections.abc import Mapping -from typing import Any - -import requests -from requests.exceptions import HTTPError - -logger = logging.getLogger(__name__) - - -class GetImgAIApp: - def __init__(self, api_key: str | None = None, base_url: str | None = None): - self.api_key = api_key - self.base_url = base_url or "https://api.getimg.ai/v1" - if not self.api_key: - raise ValueError("API key is required") - - def _prepare_headers(self): - headers = {"Content-Type": "application/json", "Authorization": f"Bearer {self.api_key}"} - return headers - - def _request( - self, - method: str, - url: str, - data: Mapping[str, Any] | None = None, - headers: Mapping[str, str] | None = None, - retries: int = 3, - backoff_factor: float = 0.3, - ) -> Mapping[str, Any] | None: - for i in range(retries): - try: - response = requests.request(method, url, json=data, headers=headers) - response.raise_for_status() - return response.json() - except requests.exceptions.RequestException as e: - if i < retries - 1 and isinstance(e, HTTPError) and e.response.status_code >= 500: - time.sleep(backoff_factor * (2**i)) - else: - raise - return None - - def text2image(self, mode: str, **kwargs): - data = kwargs["params"] - if not data.get("prompt"): - raise ValueError("Prompt is required") - - endpoint = f"{self.base_url}/{mode}/text-to-image" - headers = self._prepare_headers() - logger.debug(f"Send request to {endpoint=} body={data}") - response = self._request("POST", endpoint, data, headers) - if response is None: - raise HTTPError("Failed to initiate getimg.ai after multiple retries") - return response diff --git a/api/core/tools/provider/builtin/getimgai/tools/text2image.py b/api/core/tools/provider/builtin/getimgai/tools/text2image.py deleted file mode 100644 index c556749552c8ef..00000000000000 --- a/api/core/tools/provider/builtin/getimgai/tools/text2image.py +++ /dev/null @@ -1,39 +0,0 @@ -import json -from typing import Any, Union - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.getimgai.getimgai_appx import GetImgAIApp -from core.tools.tool.builtin_tool import BuiltinTool - - -class Text2ImageTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - app = GetImgAIApp( - api_key=self.runtime.credentials["getimg_api_key"], base_url=self.runtime.credentials["base_url"] - ) - - options = { - "style": tool_parameters.get("style"), - "prompt": tool_parameters.get("prompt"), - "aspect_ratio": tool_parameters.get("aspect_ratio"), - "output_format": tool_parameters.get("output_format", "jpeg"), - "response_format": tool_parameters.get("response_format", "url"), - "width": tool_parameters.get("width"), - "height": tool_parameters.get("height"), - "steps": tool_parameters.get("steps"), - "negative_prompt": tool_parameters.get("negative_prompt"), - "prompt_2": tool_parameters.get("prompt_2"), - } - options = {k: v for k, v in options.items() if v} - - text2image_result = app.text2image(mode=tool_parameters.get("mode", "essential-v2"), params=options, wait=True) - - if not isinstance(text2image_result, str): - text2image_result = json.dumps(text2image_result, ensure_ascii=False, indent=4) - - if not text2image_result: - return self.create_text_message("getimg.ai request failed.") - - return self.create_text_message(text2image_result) diff --git a/api/core/tools/provider/builtin/getimgai/tools/text2image.yaml b/api/core/tools/provider/builtin/getimgai/tools/text2image.yaml deleted file mode 100644 index d972186f56d6a6..00000000000000 --- a/api/core/tools/provider/builtin/getimgai/tools/text2image.yaml +++ /dev/null @@ -1,167 +0,0 @@ -identity: - name: text2image - author: Matri Qi - label: - en_US: text2image - icon: icon.svg -description: - human: - en_US: Generate image via getimg.ai. - llm: This tool is used to generate image from prompt or image via https://getimg.ai. -parameters: - - name: prompt - type: string - required: true - label: - en_US: prompt - human_description: - en_US: The text prompt used to generate the image. The getimg.aier will generate an image based on this prompt. - llm_description: this prompt text will be used to generate image. - form: llm - - name: mode - type: select - required: false - label: - en_US: mode - human_description: - en_US: The getimg.ai mode to use. The mode determines the endpoint used to generate the image. - form: form - options: - - value: "essential-v2" - label: - en_US: essential-v2 - - value: stable-diffusion-xl - label: - en_US: stable-diffusion-xl - - value: stable-diffusion - label: - en_US: stable-diffusion - - value: latent-consistency - label: - en_US: latent-consistency - - name: style - type: select - required: false - label: - en_US: style - human_description: - en_US: The style preset to use. The style preset guides the generation towards a particular style. It's just efficient for `Essential V2` mode. - form: form - options: - - value: photorealism - label: - en_US: photorealism - - value: anime - label: - en_US: anime - - value: art - label: - en_US: art - - name: aspect_ratio - type: select - required: false - label: - en_US: "aspect ratio" - human_description: - en_US: The aspect ratio of the generated image. It's just efficient for `Essential V2` mode. - form: form - options: - - value: "1:1" - label: - en_US: "1:1" - - value: "4:5" - label: - en_US: "4:5" - - value: "5:4" - label: - en_US: "5:4" - - value: "2:3" - label: - en_US: "2:3" - - value: "3:2" - label: - en_US: "3:2" - - value: "4:7" - label: - en_US: "4:7" - - value: "7:4" - label: - en_US: "7:4" - - name: output_format - type: select - required: false - label: - en_US: "output format" - human_description: - en_US: The file format of the generated image. - form: form - options: - - value: jpeg - label: - en_US: jpeg - - value: png - label: - en_US: png - - name: response_format - type: select - required: false - label: - en_US: "response format" - human_description: - en_US: The format in which the generated images are returned. Must be one of url or b64. URLs are only valid for 1 hour after the image has been generated. - form: form - options: - - value: url - label: - en_US: url - - value: b64 - label: - en_US: b64 - - name: model - type: string - required: false - label: - en_US: model - human_description: - en_US: Model ID supported by this pipeline and family. It's just efficient for `Stable Diffusion XL`, `Stable Diffusion`, `Latent Consistency` mode. - form: form - - name: negative_prompt - type: string - required: false - label: - en_US: negative prompt - human_description: - en_US: Text input that will not guide the image generation. It's just efficient for `Stable Diffusion XL`, `Stable Diffusion`, `Latent Consistency` mode. - form: form - - name: prompt_2 - type: string - required: false - label: - en_US: prompt2 - human_description: - en_US: Prompt sent to second tokenizer and text encoder. If not defined, prompt is used in both text-encoders. It's just efficient for `Stable Diffusion XL` mode. - form: form - - name: width - type: number - required: false - label: - en_US: width - human_description: - en_US: he width of the generated image in pixels. Width needs to be multiple of 64. - form: form - - name: height - type: number - required: false - label: - en_US: height - human_description: - en_US: he height of the generated image in pixels. Height needs to be multiple of 64. - form: form - - name: steps - type: number - required: false - label: - en_US: steps - human_description: - en_US: The number of denoising steps. More steps usually can produce higher quality images, but take more time to generate. It's just efficient for `Stable Diffusion XL`, `Stable Diffusion`, `Latent Consistency` mode. - form: form diff --git a/api/core/tools/provider/builtin/github/_assets/icon.svg b/api/core/tools/provider/builtin/github/_assets/icon.svg deleted file mode 100644 index d56adb2c2f9955..00000000000000 --- a/api/core/tools/provider/builtin/github/_assets/icon.svg +++ /dev/null @@ -1,17 +0,0 @@ - - - github [#142] - Created with Sketch. - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/github/github.py b/api/core/tools/provider/builtin/github/github.py deleted file mode 100644 index 87a34ac3e806ea..00000000000000 --- a/api/core/tools/provider/builtin/github/github.py +++ /dev/null @@ -1,32 +0,0 @@ -import requests - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class GithubProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - if "access_tokens" not in credentials or not credentials.get("access_tokens"): - raise ToolProviderCredentialValidationError("Github API Access Tokens is required.") - if "api_version" not in credentials or not credentials.get("api_version"): - api_version = "2022-11-28" - else: - api_version = credentials.get("api_version") - - try: - headers = { - "Content-Type": "application/vnd.github+json", - "Authorization": f"Bearer {credentials.get('access_tokens')}", - "X-GitHub-Api-Version": api_version, - } - - response = requests.get( - url="https://api.github.com/search/users?q={account}".format(account="charli117"), headers=headers - ) - if response.status_code != 200: - raise ToolProviderCredentialValidationError((response.json()).get("message")) - except Exception as e: - raise ToolProviderCredentialValidationError("Github API Key and Api Version is invalid. {}".format(e)) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/github/github.yaml b/api/core/tools/provider/builtin/github/github.yaml deleted file mode 100644 index c3d85fc3f69cf7..00000000000000 --- a/api/core/tools/provider/builtin/github/github.yaml +++ /dev/null @@ -1,48 +0,0 @@ -identity: - author: CharlieWei - name: github - label: - en_US: Github - zh_Hans: Github - pt_BR: Github - description: - en_US: GitHub is an online software source code hosting service. - zh_Hans: GitHub是一个在线软件源代码托管服务平台。 - pt_BR: GitHub é uma plataforma online para serviços de hospedagem de código fonte de software. - icon: icon.svg - tags: - - utilities -credentials_for_provider: - access_tokens: - type: secret-input - required: true - label: - en_US: Access Tokens - zh_Hans: Access Tokens - pt_BR: Tokens de acesso - placeholder: - en_US: Please input your Github Access Tokens - zh_Hans: 请输入你的 Github Access Tokens - pt_BR: Insira seus Tokens de Acesso do Github - help: - en_US: Get your Access Tokens from Github - zh_Hans: 从 Github 获取您的 Access Tokens - pt_BR: Obtenha sua chave da API do Google no Google - url: https://github.com/settings/tokens?type=beta - api_version: - type: text-input - required: false - default: '2022-11-28' - label: - en_US: API Version - zh_Hans: API Version - pt_BR: Versão da API - placeholder: - en_US: Please input your Github API Version - zh_Hans: 请输入你的 Github API Version - pt_BR: Insira sua versão da API do Github - help: - en_US: Get your API Version from Github - zh_Hans: 从 Github 获取您的 API Version - pt_BR: Obtenha sua versão da API do Github - url: https://docs.github.com/en/rest/about-the-rest-api/api-versions?apiVersion=2022-11-28 diff --git a/api/core/tools/provider/builtin/github/tools/github_repositories.py b/api/core/tools/provider/builtin/github/tools/github_repositories.py deleted file mode 100644 index 32f9922e651785..00000000000000 --- a/api/core/tools/provider/builtin/github/tools/github_repositories.py +++ /dev/null @@ -1,70 +0,0 @@ -import json -from datetime import datetime -from typing import Any, Union -from urllib.parse import quote - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GithubRepositoriesTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - top_n = tool_parameters.get("top_n", 5) - query = tool_parameters.get("query", "") - if not query: - return self.create_text_message("Please input symbol") - - if "access_tokens" not in self.runtime.credentials or not self.runtime.credentials.get("access_tokens"): - return self.create_text_message("Github API Access Tokens is required.") - if "api_version" not in self.runtime.credentials or not self.runtime.credentials.get("api_version"): - api_version = "2022-11-28" - else: - api_version = self.runtime.credentials.get("api_version") - - try: - headers = { - "Content-Type": "application/vnd.github+json", - "Authorization": f"Bearer {self.runtime.credentials.get('access_tokens')}", - "X-GitHub-Api-Version": api_version, - } - s = requests.session() - api_domain = "https://api.github.com" - response = s.request( - method="GET", - headers=headers, - url=f"{api_domain}/search/repositories?q={quote(query)}&sort=stars&per_page={top_n}&order=desc", - ) - response_data = response.json() - if response.status_code == 200 and isinstance(response_data.get("items"), list): - contents = [] - if len(response_data.get("items")) > 0: - for item in response_data.get("items"): - content = {} - updated_at_object = datetime.strptime(item["updated_at"], "%Y-%m-%dT%H:%M:%SZ") - content["owner"] = item["owner"]["login"] - content["name"] = item["name"] - content["description"] = ( - item["description"][:100] + "..." if len(item["description"]) > 100 else item["description"] - ) - content["url"] = item["html_url"] - content["star"] = item["watchers"] - content["forks"] = item["forks"] - content["updated"] = updated_at_object.strftime("%Y-%m-%d") - contents.append(content) - s.close() - return self.create_text_message( - self.summary(user_id=user_id, content=json.dumps(contents, ensure_ascii=False)) - ) - else: - return self.create_text_message(f"No items related to {query} were found.") - else: - return self.create_text_message((response.json()).get("message")) - except Exception as e: - return self.create_text_message("Github API Key and Api Version is invalid. {}".format(e)) diff --git a/api/core/tools/provider/builtin/github/tools/github_repositories.yaml b/api/core/tools/provider/builtin/github/tools/github_repositories.yaml deleted file mode 100644 index c170aee797fe4d..00000000000000 --- a/api/core/tools/provider/builtin/github/tools/github_repositories.yaml +++ /dev/null @@ -1,42 +0,0 @@ -identity: - name: github_repositories - author: CharlieWei - label: - en_US: Search Repositories - zh_Hans: 仓库搜索 - pt_BR: Pesquisar Repositórios - icon: icon.svg -description: - human: - en_US: Search the Github repository to retrieve the open source projects you need - zh_Hans: 搜索Github仓库，检索你需要的开源项目。 - pt_BR: Pesquise o repositório do Github para recuperar os projetos de código aberto necessários. - llm: A tool when you wants to search for popular warehouses or open source projects for any keyword. format query condition like "keywords+language:js", language can be other dev languages. -parameters: - - name: query - type: string - required: true - label: - en_US: query - zh_Hans: 关键字 - pt_BR: consulta - human_description: - en_US: You want to find the project development language, keywords, For example. Find 10 Python developed PDF document parsing projects. - zh_Hans: 你想要找的项目开发语言、关键字，如：找10个Python开发的PDF文档解析项目。 - pt_BR: Você deseja encontrar a linguagem de desenvolvimento do projeto, palavras-chave, Por exemplo. Encontre 10 projetos de análise de documentos PDF desenvolvidos em Python. - llm_description: The query of you want to search, format query condition like "keywords+language:js", language can be other dev languages. - form: llm - - name: top_n - type: number - default: 5 - required: true - label: - en_US: Top N - zh_Hans: Top N - pt_BR: Topo N - human_description: - en_US: Number of records returned by sorting based on stars. 5 is returned by default. - zh_Hans: 基于stars排序返回的记录数, 默认返回5条。 - pt_BR: Número de registros retornados por classificação com base em estrelas. 5 é retornado por padrão. - llm_description: Extract the first N records from the returned result. - form: llm diff --git a/api/core/tools/provider/builtin/gitlab/_assets/gitlab.svg b/api/core/tools/provider/builtin/gitlab/_assets/gitlab.svg deleted file mode 100644 index 07734077d5d300..00000000000000 --- a/api/core/tools/provider/builtin/gitlab/_assets/gitlab.svg +++ /dev/null @@ -1,2 +0,0 @@ - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/gitlab/gitlab.py b/api/core/tools/provider/builtin/gitlab/gitlab.py deleted file mode 100644 index 9bd4a0bd52ea64..00000000000000 --- a/api/core/tools/provider/builtin/gitlab/gitlab.py +++ /dev/null @@ -1,32 +0,0 @@ -from typing import Any - -import requests - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class GitlabProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - if "access_tokens" not in credentials or not credentials.get("access_tokens"): - raise ToolProviderCredentialValidationError("Gitlab Access Tokens is required.") - - if "site_url" not in credentials or not credentials.get("site_url"): - site_url = "https://gitlab.com" - else: - site_url = credentials.get("site_url") - - try: - headers = { - "Content-Type": "application/vnd.text+json", - "Authorization": f"Bearer {credentials.get('access_tokens')}", - } - - response = requests.get(url=f"{site_url}/api/v4/user", headers=headers) - if response.status_code != 200: - raise ToolProviderCredentialValidationError((response.json()).get("message")) - except Exception as e: - raise ToolProviderCredentialValidationError("Gitlab Access Tokens is invalid. {}".format(e)) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/gitlab/gitlab.yaml b/api/core/tools/provider/builtin/gitlab/gitlab.yaml deleted file mode 100644 index 22d7ebf73ac2aa..00000000000000 --- a/api/core/tools/provider/builtin/gitlab/gitlab.yaml +++ /dev/null @@ -1,38 +0,0 @@ -identity: - author: Leo.Wang - name: gitlab - label: - en_US: GitLab - zh_Hans: GitLab - description: - en_US: GitLab plugin, API v4 only. - zh_Hans: 用于获取GitLab内容的插件，目前仅支持 API v4。 - icon: gitlab.svg -credentials_for_provider: - access_tokens: - type: secret-input - required: true - label: - en_US: GitLab access token - zh_Hans: GitLab access token - placeholder: - en_US: Please input your GitLab access token - zh_Hans: 请输入你的 GitLab access token - help: - en_US: Get your GitLab access token from GitLab - zh_Hans: 从 GitLab 获取您的 access token - url: https://docs.gitlab.com/16.9/ee/api/oauth2.html - site_url: - type: text-input - required: false - default: 'https://gitlab.com' - label: - en_US: GitLab site url - zh_Hans: GitLab site url - placeholder: - en_US: Please input your GitLab site url - zh_Hans: 请输入你的 GitLab site url - help: - en_US: Find your GitLab url - zh_Hans: 找到你的 GitLab url - url: https://gitlab.com/help diff --git a/api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.py b/api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.py deleted file mode 100644 index 45ab15f437e19a..00000000000000 --- a/api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.py +++ /dev/null @@ -1,142 +0,0 @@ -import json -import urllib.parse -from datetime import datetime, timedelta -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GitlabCommitsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - project = tool_parameters.get("project", "") - repository = tool_parameters.get("repository", "") - employee = tool_parameters.get("employee", "") - start_time = tool_parameters.get("start_time", "") - end_time = tool_parameters.get("end_time", "") - change_type = tool_parameters.get("change_type", "all") - - if not project and not repository: - return self.create_text_message("Either project or repository is required") - - if not start_time: - start_time = (datetime.utcnow() - timedelta(days=1)).isoformat() - if not end_time: - end_time = datetime.utcnow().isoformat() - - access_token = self.runtime.credentials.get("access_tokens") - site_url = self.runtime.credentials.get("site_url") - - if "access_tokens" not in self.runtime.credentials or not self.runtime.credentials.get("access_tokens"): - return self.create_text_message("Gitlab API Access Tokens is required.") - if "site_url" not in self.runtime.credentials or not self.runtime.credentials.get("site_url"): - site_url = "https://gitlab.com" - - # Get commit content - if repository: - result = self.fetch_commits( - site_url, access_token, repository, employee, start_time, end_time, change_type, is_repository=True - ) - else: - result = self.fetch_commits( - site_url, access_token, project, employee, start_time, end_time, change_type, is_repository=False - ) - - return [self.create_json_message(item) for item in result] - - def fetch_commits( - self, - site_url: str, - access_token: str, - identifier: str, - employee: str, - start_time: str, - end_time: str, - change_type: str, - is_repository: bool, - ) -> list[dict[str, Any]]: - domain = site_url - headers = {"PRIVATE-TOKEN": access_token} - results = [] - - try: - if is_repository: - # URL encode the repository path - encoded_identifier = urllib.parse.quote(identifier, safe="") - commits_url = f"{domain}/api/v4/projects/{encoded_identifier}/repository/commits" - else: - # Get all projects - url = f"{domain}/api/v4/projects" - response = requests.get(url, headers=headers) - response.raise_for_status() - projects = response.json() - - filtered_projects = [p for p in projects if identifier == "*" or p["name"] == identifier] - - for project in filtered_projects: - project_id = project["id"] - project_name = project["name"] - print(f"Project: {project_name}") - - commits_url = f"{domain}/api/v4/projects/{project_id}/repository/commits" - - params = {"since": start_time, "until": end_time} - if employee: - params["author"] = employee - - commits_response = requests.get(commits_url, headers=headers, params=params) - commits_response.raise_for_status() - commits = commits_response.json() - - for commit in commits: - commit_sha = commit["id"] - author_name = commit["author_name"] - - if is_repository: - diff_url = f"{domain}/api/v4/projects/{encoded_identifier}/repository/commits/{commit_sha}/diff" - else: - diff_url = f"{domain}/api/v4/projects/{project_id}/repository/commits/{commit_sha}/diff" - - diff_response = requests.get(diff_url, headers=headers) - diff_response.raise_for_status() - diffs = diff_response.json() - - for diff in diffs: - # Calculate code lines of changes - added_lines = diff["diff"].count("\n+") - removed_lines = diff["diff"].count("\n-") - total_changes = added_lines + removed_lines - - if change_type == "new": - if added_lines > 1: - final_code = "".join( - [ - line[1:] - for line in diff["diff"].split("\n") - if line.startswith("+") and not line.startswith("+++") - ] - ) - results.append({"commit_sha": commit_sha, "author_name": author_name, "diff": final_code}) - else: - if total_changes > 1: - final_code = "".join( - [ - line[1:] - for line in diff["diff"].split("\n") - if (line.startswith("+") or line.startswith("-")) - and not line.startswith("+++") - and not line.startswith("---") - ] - ) - final_code_escaped = json.dumps(final_code)[1:-1] # Escape the final code - results.append( - {"commit_sha": commit_sha, "author_name": author_name, "diff": final_code_escaped} - ) - except requests.RequestException as e: - print(f"Error fetching data from GitLab: {e}") - - return results diff --git a/api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.yaml b/api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.yaml deleted file mode 100644 index 669378ac97c89a..00000000000000 --- a/api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.yaml +++ /dev/null @@ -1,88 +0,0 @@ -identity: - name: gitlab_commits - author: Leo.Wang - label: - en_US: GitLab Commits - zh_Hans: GitLab 提交内容查询 -description: - human: - en_US: A tool for query GitLab commits, Input should be a exists username or project. - zh_Hans: 一个用于查询 GitLab 代码提交内容的工具，输入的内容应该是一个已存在的用户名或者项目名。 - llm: A tool for query GitLab commits, Input should be a exists username or project. -parameters: - - name: username - type: string - required: false - label: - en_US: username - zh_Hans: 员工用户名 - human_description: - en_US: username - zh_Hans: 员工用户名 - llm_description: User name for GitLab - form: llm - - name: repository - type: string - required: false - label: - en_US: repository - zh_Hans: 仓库路径 - human_description: - en_US: repository - zh_Hans: 仓库路径，以namespace/project_name的形式。 - llm_description: Repository path for GitLab, like namespace/project_name. - form: llm - - name: project - type: string - required: false - label: - en_US: project - zh_Hans: 项目名 - human_description: - en_US: project - zh_Hans: 项目名 - llm_description: project for GitLab - form: llm - - name: start_time - type: string - required: false - label: - en_US: start_time - zh_Hans: 开始时间 - human_description: - en_US: start_time - zh_Hans: 开始时间 - llm_description: Start time for GitLab - form: llm - - name: end_time - type: string - required: false - label: - en_US: end_time - zh_Hans: 结束时间 - human_description: - en_US: end_time - zh_Hans: 结束时间 - llm_description: End time for GitLab - form: llm - - name: change_type - type: select - required: false - options: - - value: all - label: - en_US: all - zh_Hans: 所有 - - value: new - label: - en_US: new - zh_Hans: 新增 - default: all - label: - en_US: change_type - zh_Hans: 变更类型 - human_description: - en_US: change_type - zh_Hans: 变更类型 - llm_description: Content change type for GitLab - form: llm diff --git a/api/core/tools/provider/builtin/gitlab/tools/gitlab_files.py b/api/core/tools/provider/builtin/gitlab/tools/gitlab_files.py deleted file mode 100644 index 1e77f3c6dfc678..00000000000000 --- a/api/core/tools/provider/builtin/gitlab/tools/gitlab_files.py +++ /dev/null @@ -1,103 +0,0 @@ -import urllib.parse -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GitlabFilesTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - project = tool_parameters.get("project", "") - repository = tool_parameters.get("repository", "") - branch = tool_parameters.get("branch", "") - path = tool_parameters.get("path", "") - - if not project and not repository: - return self.create_text_message("Either project or repository is required") - if not branch: - return self.create_text_message("Branch is required") - if not path: - return self.create_text_message("Path is required") - - access_token = self.runtime.credentials.get("access_tokens") - site_url = self.runtime.credentials.get("site_url") - - if "access_tokens" not in self.runtime.credentials or not self.runtime.credentials.get("access_tokens"): - return self.create_text_message("Gitlab API Access Tokens is required.") - if "site_url" not in self.runtime.credentials or not self.runtime.credentials.get("site_url"): - site_url = "https://gitlab.com" - - # Get file content - if repository: - result = self.fetch_files(site_url, access_token, repository, branch, path, is_repository=True) - else: - result = self.fetch_files(site_url, access_token, project, branch, path, is_repository=False) - - return [self.create_json_message(item) for item in result] - - def fetch_files( - self, site_url: str, access_token: str, identifier: str, branch: str, path: str, is_repository: bool - ) -> list[dict[str, Any]]: - domain = site_url - headers = {"PRIVATE-TOKEN": access_token} - results = [] - - try: - if is_repository: - # URL encode the repository path - encoded_identifier = urllib.parse.quote(identifier, safe="") - tree_url = f"{domain}/api/v4/projects/{encoded_identifier}/repository/tree?path={path}&ref={branch}" - else: - # Get project ID from project name - project_id = self.get_project_id(site_url, access_token, identifier) - if not project_id: - return self.create_text_message(f"Project '{identifier}' not found.") - tree_url = f"{domain}/api/v4/projects/{project_id}/repository/tree?path={path}&ref={branch}" - - response = requests.get(tree_url, headers=headers) - response.raise_for_status() - items = response.json() - - for item in items: - item_path = item["path"] - if item["type"] == "tree": # It's a directory - results.extend( - self.fetch_files(site_url, access_token, identifier, branch, item_path, is_repository) - ) - else: # It's a file - if is_repository: - file_url = ( - f"{domain}/api/v4/projects/{encoded_identifier}/repository/files" - f"/{item_path}/raw?ref={branch}" - ) - else: - file_url = ( - f"{domain}/api/v4/projects/{project_id}/repository/files/{item_path}/raw?ref={branch}" - ) - - file_response = requests.get(file_url, headers=headers) - file_response.raise_for_status() - file_content = file_response.text - results.append({"path": item_path, "branch": branch, "content": file_content}) - except requests.RequestException as e: - print(f"Error fetching data from GitLab: {e}") - - return results - - def get_project_id(self, site_url: str, access_token: str, project_name: str) -> Union[str, None]: - headers = {"PRIVATE-TOKEN": access_token} - try: - url = f"{site_url}/api/v4/projects?search={project_name}" - response = requests.get(url, headers=headers) - response.raise_for_status() - projects = response.json() - for project in projects: - if project["name"] == project_name: - return project["id"] - except requests.RequestException as e: - print(f"Error fetching project ID from GitLab: {e}") - return None diff --git a/api/core/tools/provider/builtin/gitlab/tools/gitlab_files.yaml b/api/core/tools/provider/builtin/gitlab/tools/gitlab_files.yaml deleted file mode 100644 index 4c733673f15254..00000000000000 --- a/api/core/tools/provider/builtin/gitlab/tools/gitlab_files.yaml +++ /dev/null @@ -1,56 +0,0 @@ -identity: - name: gitlab_files - author: Leo.Wang - label: - en_US: GitLab Files - zh_Hans: GitLab 文件获取 -description: - human: - en_US: A tool for query GitLab files, Input should be branch and a exists file or directory path. - zh_Hans: 一个用于查询 GitLab 文件的工具，输入的内容应该是分支和一个已存在文件或者文件夹路径。 - llm: A tool for query GitLab files, Input should be a exists file or directory path. -parameters: - - name: repository - type: string - required: false - label: - en_US: repository - zh_Hans: 仓库路径 - human_description: - en_US: repository - zh_Hans: 仓库路径，以namespace/project_name的形式。 - llm_description: Repository path for GitLab, like namespace/project_name. - form: llm - - name: project - type: string - required: false - label: - en_US: project - zh_Hans: 项目 - human_description: - en_US: project - zh_Hans: 项目 - llm_description: Project for GitLab - form: llm - - name: branch - type: string - required: true - label: - en_US: branch - zh_Hans: 分支 - human_description: - en_US: branch - zh_Hans: 分支 - llm_description: Branch for GitLab - form: llm - - name: path - type: string - required: true - label: - en_US: path - zh_Hans: 文件路径 - human_description: - en_US: path - zh_Hans: 文件路径 - llm_description: File path for GitLab - form: llm diff --git a/api/core/tools/provider/builtin/google/_assets/icon.svg b/api/core/tools/provider/builtin/google/_assets/icon.svg deleted file mode 100644 index bebbf52d3a23a4..00000000000000 --- a/api/core/tools/provider/builtin/google/_assets/icon.svg +++ /dev/null @@ -1,6 +0,0 @@ - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/google/google.py b/api/core/tools/provider/builtin/google/google.py deleted file mode 100644 index 6b5395f9d3e5b8..00000000000000 --- a/api/core/tools/provider/builtin/google/google.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.google.tools.google_search import GoogleSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class GoogleProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - GoogleSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={"query": "test", "result_type": "link"}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/google/google.yaml b/api/core/tools/provider/builtin/google/google.yaml deleted file mode 100644 index afb4d5b2145ba6..00000000000000 --- a/api/core/tools/provider/builtin/google/google.yaml +++ /dev/null @@ -1,31 +0,0 @@ -identity: - author: Dify - name: google - label: - en_US: Google - zh_Hans: Google - pt_BR: Google - description: - en_US: Google - zh_Hans: GoogleSearch - pt_BR: Google - icon: icon.svg - tags: - - search -credentials_for_provider: - serpapi_api_key: - type: secret-input - required: true - label: - en_US: SerpApi API key - zh_Hans: SerpApi API key - pt_BR: SerpApi API key - placeholder: - en_US: Please input your SerpApi API key - zh_Hans: 请输入你的 SerpApi API key - pt_BR: Please input your SerpApi API key - help: - en_US: Get your SerpApi API key from SerpApi - zh_Hans: 从 SerpApi 获取您的 SerpApi API key - pt_BR: Get your SerpApi API key from SerpApi - url: https://serpapi.com/manage-api-key diff --git a/api/core/tools/provider/builtin/google/tools/google_search.py b/api/core/tools/provider/builtin/google/tools/google_search.py deleted file mode 100644 index a9f65925d86f94..00000000000000 --- a/api/core/tools/provider/builtin/google/tools/google_search.py +++ /dev/null @@ -1,40 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -SERP_API_URL = "https://serpapi.com/search" - - -class GoogleSearchTool(BuiltinTool): - def _parse_response(self, response: dict) -> dict: - result = {} - if "knowledge_graph" in response: - result["title"] = response["knowledge_graph"].get("title", "") - result["description"] = response["knowledge_graph"].get("description", "") - if "organic_results" in response: - result["organic_results"] = [ - {"title": item.get("title", ""), "link": item.get("link", ""), "snippet": item.get("snippet", "")} - for item in response["organic_results"] - ] - return result - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - params = { - "api_key": self.runtime.credentials["serpapi_api_key"], - "q": tool_parameters["query"], - "engine": "google", - "google_domain": "google.com", - "gl": "us", - "hl": "en", - } - response = requests.get(url=SERP_API_URL, params=params) - response.raise_for_status() - valuable_res = self._parse_response(response.json()) - return self.create_json_message(valuable_res) diff --git a/api/core/tools/provider/builtin/google/tools/google_search.yaml b/api/core/tools/provider/builtin/google/tools/google_search.yaml deleted file mode 100644 index 72db3839eb022a..00000000000000 --- a/api/core/tools/provider/builtin/google/tools/google_search.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: google_search - author: Dify - label: - en_US: GoogleSearch - zh_Hans: 谷歌搜索 - pt_BR: GoogleSearch -description: - human: - en_US: A tool for performing a Google SERP search and extracting snippets and webpages.Input should be a search query. - zh_Hans: 一个用于执行 Google SERP 搜索并提取片段和网页的工具。输入应该是一个搜索查询。 - pt_BR: A tool for performing a Google SERP search and extracting snippets and webpages.Input should be a search query. - llm: A tool for performing a Google SERP search and extracting snippets and webpages.Input should be a search query. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - pt_BR: Query string - human_description: - en_US: used for searching - zh_Hans: 用于搜索网页内容 - pt_BR: used for searching - llm_description: key words for searching - form: llm diff --git a/api/core/tools/provider/builtin/google_translate/_assets/icon.svg b/api/core/tools/provider/builtin/google_translate/_assets/icon.svg deleted file mode 100644 index de69a9c5e58316..00000000000000 --- a/api/core/tools/provider/builtin/google_translate/_assets/icon.svg +++ /dev/null @@ -1,18 +0,0 @@ - - - - - - - - - - - - - - - - - - diff --git a/api/core/tools/provider/builtin/google_translate/google_translate.py b/api/core/tools/provider/builtin/google_translate/google_translate.py deleted file mode 100644 index ea53aa4eeb906f..00000000000000 --- a/api/core/tools/provider/builtin/google_translate/google_translate.py +++ /dev/null @@ -1,13 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.google_translate.tools.translate import GoogleTranslate -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class JsonExtractProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - GoogleTranslate().invoke(user_id="", tool_parameters={"content": "这是一段测试文本", "dest": "en"}) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/google_translate/google_translate.yaml b/api/core/tools/provider/builtin/google_translate/google_translate.yaml deleted file mode 100644 index 8bc821a3d5e9fa..00000000000000 --- a/api/core/tools/provider/builtin/google_translate/google_translate.yaml +++ /dev/null @@ -1,12 +0,0 @@ -identity: - author: Ron Liu - name: google_translate - label: - en_US: Google Translate - zh_Hans: 谷歌翻译 - description: - en_US: Translate text using Google - zh_Hans: 使用 Google 进行翻译 - icon: icon.svg - tags: - - utilities diff --git a/api/core/tools/provider/builtin/google_translate/tools/translate.py b/api/core/tools/provider/builtin/google_translate/tools/translate.py deleted file mode 100644 index ea3f2077d5d485..00000000000000 --- a/api/core/tools/provider/builtin/google_translate/tools/translate.py +++ /dev/null @@ -1,47 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GoogleTranslate(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - content = tool_parameters.get("content", "") - if not content: - return self.create_text_message("Invalid parameter content") - - dest = tool_parameters.get("dest", "") - if not dest: - return self.create_text_message("Invalid parameter destination language") - - try: - result = self._translate(content, dest) - return self.create_text_message(str(result)) - except Exception: - return self.create_text_message("Translation service error, please check the network") - - def _translate(self, content: str, dest: str) -> str: - try: - url = "https://translate.googleapis.com/translate_a/single" - params = {"client": "gtx", "sl": "auto", "tl": dest, "dt": "t", "q": content} - - headers = { - "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)" - " Chrome/91.0.4472.124 Safari/537.36" - } - - response_json = requests.get(url, params=params, headers=headers).json() - result = response_json[0] - translated_text = "".join([item[0] for item in result if item[0]]) - return str(translated_text) - except Exception as e: - return str(e) diff --git a/api/core/tools/provider/builtin/google_translate/tools/translate.yaml b/api/core/tools/provider/builtin/google_translate/tools/translate.yaml deleted file mode 100644 index a4189cd7439ad7..00000000000000 --- a/api/core/tools/provider/builtin/google_translate/tools/translate.yaml +++ /dev/null @@ -1,215 +0,0 @@ -identity: - name: translate - author: Ron Liu - label: - en_US: Translate - zh_Hans: 翻译 -description: - human: - en_US: A tool for Google Translate - zh_Hans: Google 翻译 - llm: A tool for Google Translate -parameters: - - name: content - type: string - required: true - label: - en_US: Text content - zh_Hans: 文本内容 - human_description: - en_US: Text content - zh_Hans: 需要翻译的文本内容 - llm_description: Text content - form: llm - - name: dest - type: select - required: true - label: - en_US: destination language - zh_Hans: 目标语言 - human_description: - en_US: The destination language you want to translate. - zh_Hans: 你想翻译的目标语言 - default: en - form: form - options: - - value: ar - label: - en_US: Arabic - zh_Hans: 阿拉伯语 - - value: bg - label: - en_US: Bulgarian - zh_Hans: 保加利亚语 - - value: ca - label: - en_US: Catalan - zh_Hans: 加泰罗尼亚语 - - value: zh-cn - label: - en_US: Chinese (Simplified) - zh_Hans: 中文（简体） - - value: zh-tw - label: - en_US: Chinese (Traditional) - zh_Hans: 中文（繁体） - - value: cs - label: - en_US: Czech - zh_Hans: 捷克语 - - value: da - label: - en_US: Danish - zh_Hans: 丹麦语 - - value: nl - label: - en_US: Dutch - zh_Hans: 荷兰语 - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: et - label: - en_US: Estonian - zh_Hans: 爱沙尼亚语 - - value: fi - label: - en_US: Finnish - zh_Hans: 芬兰语 - - value: fr - label: - en_US: French - zh_Hans: 法语 - - value: de - label: - en_US: German - zh_Hans: 德语 - - value: el - label: - en_US: Greek - zh_Hans: 希腊语 - - value: iw - label: - en_US: Hebrew - zh_Hans: 希伯来语 - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - - value: hu - label: - en_US: Hungarian - zh_Hans: 匈牙利语 - - value: id - label: - en_US: Indonesian - zh_Hans: 印尼语 - - value: it - label: - en_US: Italian - zh_Hans: 意大利语 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - - value: kn - label: - en_US: Kannada - zh_Hans: 卡纳达语 - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - - value: lv - label: - en_US: Latvian - zh_Hans: 拉脱维亚语 - - value: lt - label: - en_US: Lithuanian - zh_Hans: 立陶宛语 - - value: my - label: - en_US: Malay - zh_Hans: 马来语 - - value: ml - label: - en_US: Malayalam - zh_Hans: 马拉雅拉姆语 - - value: mr - label: - en_US: Marathi - zh_Hans: 马拉地语 - - value: "no" - label: - en_US: Norwegian - zh_Hans: 挪威语 - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - - value: pt-br - label: - en_US: Portuguese (Brazil) - zh_Hans: 葡萄牙语（巴西） - - value: pt-pt - label: - en_US: Portuguese (Portugal) - zh_Hans: 葡萄牙语（葡萄牙） - - value: pa - label: - en_US: Punjabi - zh_Hans: 旁遮普语 - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - - value: ru - label: - en_US: Russian - zh_Hans: 俄语 - - value: sr - label: - en_US: Serbian - zh_Hans: 塞尔维亚语 - - value: sk - label: - en_US: Slovak - zh_Hans: 斯洛伐克语 - - value: sl - label: - en_US: Slovenian - zh_Hans: 斯洛文尼亚语 - - value: es - label: - en_US: Spanish - zh_Hans: 西班牙语 - - value: sv - label: - en_US: Swedish - zh_Hans: 瑞典语 - - value: ta - label: - en_US: Tamil - zh_Hans: 泰米尔语 - - value: te - label: - en_US: Telugu - zh_Hans: 泰卢固语 - - value: th - label: - en_US: Thai - zh_Hans: 泰语 - - value: tr - label: - en_US: Turkish - zh_Hans: 土耳其语 - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 diff --git a/api/core/tools/provider/builtin/hap/_assets/icon.svg b/api/core/tools/provider/builtin/hap/_assets/icon.svg deleted file mode 100644 index 0fa6f0886fdfdb..00000000000000 --- a/api/core/tools/provider/builtin/hap/_assets/icon.svg +++ /dev/null @@ -1,16 +0,0 @@ - - - - - - - - - - - - - - - - diff --git a/api/core/tools/provider/builtin/hap/hap.py b/api/core/tools/provider/builtin/hap/hap.py deleted file mode 100644 index cbdf9504659568..00000000000000 --- a/api/core/tools/provider/builtin/hap/hap.py +++ /dev/null @@ -1,8 +0,0 @@ -from typing import Any - -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class HapProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - pass diff --git a/api/core/tools/provider/builtin/hap/hap.yaml b/api/core/tools/provider/builtin/hap/hap.yaml deleted file mode 100644 index 25b473cf9dd211..00000000000000 --- a/api/core/tools/provider/builtin/hap/hap.yaml +++ /dev/null @@ -1,15 +0,0 @@ -identity: - author: Mingdao - name: hap - label: - en_US: HAP - zh_Hans: HAP - pt_BR: HAP - description: - en_US: "Hyper application platform that is particularly friendly to AI" - zh_Hans: "对 AI 特别友好的超级应用平台" - pt_BR: "Plataforma de aplicação hiper que é particularmente amigável à IA" - icon: icon.svg - tags: - - productivity -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/hap/tools/add_worksheet_record.py b/api/core/tools/provider/builtin/hap/tools/add_worksheet_record.py deleted file mode 100644 index 597adc91db9768..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/add_worksheet_record.py +++ /dev/null @@ -1,52 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class AddWorksheetRecordTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - appkey = tool_parameters.get("appkey", "") - if not appkey: - return self.create_text_message("Invalid parameter App Key") - sign = tool_parameters.get("sign", "") - if not sign: - return self.create_text_message("Invalid parameter Sign") - worksheet_id = tool_parameters.get("worksheet_id", "") - if not worksheet_id: - return self.create_text_message("Invalid parameter Worksheet ID") - record_data = tool_parameters.get("record_data", "") - if not record_data: - return self.create_text_message("Invalid parameter Record Row Data") - - host = tool_parameters.get("host", "") - if not host: - host = "https://api.mingdao.com" - elif not host.startswith(("http://", "https://")): - return self.create_text_message("Invalid parameter Host Address") - else: - host = f"{host.removesuffix('/')}/api" - - url = f"{host}/v2/open/worksheet/addRow" - headers = {"Content-Type": "application/json"} - payload = {"appKey": appkey, "sign": sign, "worksheetId": worksheet_id} - - try: - payload["controls"] = json.loads(record_data) - res = httpx.post(url, headers=headers, json=payload, timeout=60) - res.raise_for_status() - res_json = res.json() - if res_json.get("error_code") != 1: - return self.create_text_message(f"Failed to add the new record. {res_json['error_msg']}") - return self.create_text_message(f"New record added successfully. The record ID is {res_json['data']}.") - except httpx.RequestError as e: - return self.create_text_message(f"Failed to add the new record, request error: {e}") - except json.JSONDecodeError as e: - return self.create_text_message(f"Failed to parse JSON response: {e}") - except Exception as e: - return self.create_text_message(f"Failed to add the new record, unexpected error: {e}") diff --git a/api/core/tools/provider/builtin/hap/tools/add_worksheet_record.yaml b/api/core/tools/provider/builtin/hap/tools/add_worksheet_record.yaml deleted file mode 100644 index add7742cd74db1..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/add_worksheet_record.yaml +++ /dev/null @@ -1,78 +0,0 @@ -identity: - name: add_worksheet_record - author: Ryan Tian - label: - en_US: Add Worksheet Record - zh_Hans: 新增一条工作表记录 -description: - human: - en_US: Adds a new record to the specified worksheet - zh_Hans: 向指定的工作表新增一条记录数据 - llm: A tool to append a new data entry into a specified worksheet. -parameters: - - name: appkey - type: secret-input - required: true - label: - en_US: App Key - zh_Hans: App Key - human_description: - en_US: The AppKey parameter for the HAP application, typically found in the application's API documentation. - zh_Hans: HAP 应用的 AppKey 参数，可以从应用 API 文档中查找到 - llm_description: the AppKey parameter for the HAP application - form: form - - - name: sign - type: secret-input - required: true - label: - en_US: Sign - zh_Hans: Sign - human_description: - en_US: The Sign parameter for the HAP application - zh_Hans: HAP 应用的 Sign 参数 - llm_description: the Sign parameter for the HAP application - form: form - - - name: worksheet_id - type: string - required: true - label: - en_US: Worksheet ID - zh_Hans: 工作表 ID - human_description: - en_US: The ID of the specified worksheet - zh_Hans: 要获取字段信息的工作表 ID - llm_description: The ID of the specified worksheet which to get the fields information. - form: llm - - - name: record_data - type: string - required: true - label: - en_US: Record Row Data - zh_Hans: 记录数据 - human_description: - en_US: The fields with data of the specified record - zh_Hans: 要新增的记录数据，JSON 对象数组格式。数组元素属性：controlId-字段ID，value-字段值 - llm_description: | - The fields with data of the specified record which to be created. It is in the format of an array of JSON objects, and the structure is defined as follows: - ``` - type RowData = { - controlId: string; // Field ID to be updated - value: string; // Field value to be updated - }[]; - ``` - form: llm - - - name: host - type: string - required: false - label: - en_US: Host Address - zh_Hans: 服务器地址 - human_description: - en_US: The address for the privately deployed HAP server. - zh_Hans: 私有部署 HAP 服务器地址，公有云无需填写 - llm_description: the address for the privately deployed HAP server. - form: form diff --git a/api/core/tools/provider/builtin/hap/tools/delete_worksheet_record.py b/api/core/tools/provider/builtin/hap/tools/delete_worksheet_record.py deleted file mode 100644 index 5d42af4c490598..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/delete_worksheet_record.py +++ /dev/null @@ -1,48 +0,0 @@ -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DeleteWorksheetRecordTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - appkey = tool_parameters.get("appkey", "") - if not appkey: - return self.create_text_message("Invalid parameter App Key") - sign = tool_parameters.get("sign", "") - if not sign: - return self.create_text_message("Invalid parameter Sign") - worksheet_id = tool_parameters.get("worksheet_id", "") - if not worksheet_id: - return self.create_text_message("Invalid parameter Worksheet ID") - row_id = tool_parameters.get("row_id", "") - if not row_id: - return self.create_text_message("Invalid parameter Record Row ID") - - host = tool_parameters.get("host", "") - if not host: - host = "https://api.mingdao.com" - elif not host.startswith(("http://", "https://")): - return self.create_text_message("Invalid parameter Host Address") - else: - host = f"{host.removesuffix('/')}/api" - - url = f"{host}/v2/open/worksheet/deleteRow" - headers = {"Content-Type": "application/json"} - payload = {"appKey": appkey, "sign": sign, "worksheetId": worksheet_id, "rowId": row_id} - - try: - res = httpx.post(url, headers=headers, json=payload, timeout=30) - res.raise_for_status() - res_json = res.json() - if res_json.get("error_code") != 1: - return self.create_text_message(f"Failed to delete the record. {res_json['error_msg']}") - return self.create_text_message("Successfully deleted the record.") - except httpx.RequestError as e: - return self.create_text_message(f"Failed to delete the record, request error: {e}") - except Exception as e: - return self.create_text_message(f"Failed to delete the record, unexpected error: {e}") diff --git a/api/core/tools/provider/builtin/hap/tools/delete_worksheet_record.yaml b/api/core/tools/provider/builtin/hap/tools/delete_worksheet_record.yaml deleted file mode 100644 index 7c0c2a6439003f..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/delete_worksheet_record.yaml +++ /dev/null @@ -1,71 +0,0 @@ -identity: - name: delete_worksheet_record - author: Ryan Tian - label: - en_US: Delete Worksheet Record - zh_Hans: 删除指定的一条工作表记录 -description: - human: - en_US: Deletes a single record from a worksheet based on the specified record row ID - zh_Hans: 根据指定的记录ID删除一条工作表记录数据 - llm: A tool to remove a particular record from a worksheet by specifying its unique record identifier. -parameters: - - name: appkey - type: secret-input - required: true - label: - en_US: App Key - zh_Hans: App Key - human_description: - en_US: The AppKey parameter for the HAP application, typically found in the application's API documentation. - zh_Hans: HAP 应用的 AppKey 参数，可以从应用 API 文档中查找到 - llm_description: the AppKey parameter for the HAP application - form: form - - - name: sign - type: secret-input - required: true - label: - en_US: Sign - zh_Hans: Sign - human_description: - en_US: The Sign parameter for the HAP application - zh_Hans: HAP 应用的 Sign 参数 - llm_description: the Sign parameter for the HAP application - form: form - - - name: worksheet_id - type: string - required: true - label: - en_US: Worksheet ID - zh_Hans: 工作表 ID - human_description: - en_US: The ID of the specified worksheet - zh_Hans: 要获取字段信息的工作表 ID - llm_description: The ID of the specified worksheet which to get the fields information. - form: llm - - - name: row_id - type: string - required: true - label: - en_US: Record Row ID - zh_Hans: 记录 ID - human_description: - en_US: The row ID of the specified record - zh_Hans: 要删除的记录 ID - llm_description: The row ID of the specified record which to be deleted. - form: llm - - - name: host - type: string - required: false - label: - en_US: Host Address - zh_Hans: 服务器地址 - human_description: - en_US: The address for the privately deployed HAP server. - zh_Hans: 私有部署 HAP 服务器地址，公有云无需填写 - llm_description: the address for the privately deployed HAP server. - form: form diff --git a/api/core/tools/provider/builtin/hap/tools/get_worksheet_fields.py b/api/core/tools/provider/builtin/hap/tools/get_worksheet_fields.py deleted file mode 100644 index 6887b8b4e99df6..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/get_worksheet_fields.py +++ /dev/null @@ -1,152 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetWorksheetFieldsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - appkey = tool_parameters.get("appkey", "") - if not appkey: - return self.create_text_message("Invalid parameter App Key") - sign = tool_parameters.get("sign", "") - if not sign: - return self.create_text_message("Invalid parameter Sign") - worksheet_id = tool_parameters.get("worksheet_id", "") - if not worksheet_id: - return self.create_text_message("Invalid parameter Worksheet ID") - - host = tool_parameters.get("host", "") - if not host: - host = "https://api.mingdao.com" - elif not host.startswith(("http://", "https://")): - return self.create_text_message("Invalid parameter Host Address") - else: - host = f"{host.removesuffix('/')}/api" - - url = f"{host}/v2/open/worksheet/getWorksheetInfo" - headers = {"Content-Type": "application/json"} - payload = {"appKey": appkey, "sign": sign, "worksheetId": worksheet_id} - - try: - res = httpx.post(url, headers=headers, json=payload, timeout=60) - res.raise_for_status() - res_json = res.json() - if res_json.get("error_code") != 1: - return self.create_text_message(f"Failed to get the worksheet information. {res_json['error_msg']}") - - fields_json, fields_table = self.get_controls(res_json["data"]["controls"]) - result_type = tool_parameters.get("result_type", "table") - return self.create_text_message( - text=json.dumps(fields_json, ensure_ascii=False) if result_type == "json" else fields_table - ) - except httpx.RequestError as e: - return self.create_text_message(f"Failed to get the worksheet information, request error: {e}") - except json.JSONDecodeError as e: - return self.create_text_message(f"Failed to parse JSON response: {e}") - except Exception as e: - return self.create_text_message(f"Failed to get the worksheet information, unexpected error: {e}") - - def get_field_type_by_id(self, field_type_id: int) -> str: - field_type_map = { - 2: "Text", - 3: "Text-Phone", - 4: "Text-Phone", - 5: "Text-Email", - 6: "Number", - 7: "Text", - 8: "Number", - 9: "Option-Single Choice", - 10: "Option-Multiple Choices", - 11: "Option-Single Choice", - 15: "Date", - 16: "Date", - 24: "Option-Region", - 25: "Text", - 26: "Option-Member", - 27: "Option-Department", - 28: "Number", - 29: "Option-Linked Record", - 30: "Unknown Type", - 31: "Number", - 32: "Text", - 33: "Text", - 35: "Option-Linked Record", - 36: "Number-Yes1/No0", - 37: "Number", - 38: "Date", - 40: "Location", - 41: "Text", - 46: "Time", - 48: "Option-Organizational Role", - 50: "Text", - 51: "Query Record", - } - return field_type_map.get(field_type_id, "") - - def get_controls(self, controls: list) -> dict: - fields = [] - fields_list = ["|fieldId|fieldName|fieldType|fieldTypeId|description|options|", "|" + "---|" * 6] - for control in controls: - if control["type"] in self._get_ignore_types(): - continue - field_type_id = control["type"] - field_type = self.get_field_type_by_id(control["type"]) - if field_type_id == 30: - source_type = control["sourceControl"]["type"] - if source_type in self._get_ignore_types(): - continue - else: - field_type_id = source_type - field_type = self.get_field_type_by_id(source_type) - field = { - "id": control["controlId"], - "name": control["controlName"], - "type": field_type, - "typeId": field_type_id, - "description": control["remark"].replace("\n", " ").replace("\t", " "), - "options": self._extract_options(control), - } - fields.append(field) - fields_list.append( - f"|{field['id']}|{field['name']}|{field['type']}|{field['typeId']}|{field['description']}" - f"|{field['options'] or ''}|" - ) - - fields.append( - { - "id": "ctime", - "name": "Created Time", - "type": self.get_field_type_by_id(16), - "typeId": 16, - "description": "", - "options": [], - } - ) - fields_list.append("|ctime|Created Time|Date|16|||") - return fields, "\n".join(fields_list) - - def _extract_options(self, control: dict) -> list: - options = [] - if control["type"] in {9, 10, 11}: - options.extend([{"key": opt["key"], "value": opt["value"]} for opt in control.get("options", [])]) - elif control["type"] in {28, 36}: - itemnames = control["advancedSetting"].get("itemnames") - if itemnames and itemnames.startswith("[{"): - try: - options = json.loads(itemnames) - except json.JSONDecodeError: - pass - elif control["type"] == 30: - source_type = control["sourceControl"]["type"] - if source_type not in self._get_ignore_types(): - options.extend([{"key": opt["key"], "value": opt["value"]} for opt in control.get("options", [])]) - return options - - def _get_ignore_types(self): - return {14, 21, 22, 34, 42, 43, 45, 47, 49, 10010} diff --git a/api/core/tools/provider/builtin/hap/tools/get_worksheet_fields.yaml b/api/core/tools/provider/builtin/hap/tools/get_worksheet_fields.yaml deleted file mode 100644 index f0d4973e8549f7..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/get_worksheet_fields.yaml +++ /dev/null @@ -1,80 +0,0 @@ -identity: - name: get_worksheet_fields - author: Ryan Tian - label: - en_US: Get Worksheet Fields - zh_Hans: 获取工作表字段结构 -description: - human: - en_US: Get fields information of the worksheet - zh_Hans: 获取指定工作表的所有字段结构信息 - llm: A tool to get fields information of the specific worksheet. -parameters: - - name: appkey - type: secret-input - required: true - label: - en_US: App Key - zh_Hans: App Key - human_description: - en_US: The AppKey parameter for the HAP application, typically found in the application's API documentation. - zh_Hans: HAP 应用的 AppKey 参数，可以从应用 API 文档中查找到 - llm_description: the AppKey parameter for the HAP application - form: form - - - name: sign - type: secret-input - required: true - label: - en_US: Sign - zh_Hans: Sign - human_description: - en_US: The Sign parameter for the HAP application - zh_Hans: HAP 应用的 Sign 参数 - llm_description: the Sign parameter for the HAP application - form: form - - - name: worksheet_id - type: string - required: true - label: - en_US: Worksheet ID - zh_Hans: 工作表 ID - human_description: - en_US: The ID of the specified worksheet - zh_Hans: 要获取字段信息的工作表 ID - llm_description: The ID of the specified worksheet which to get the fields information. - form: llm - - - name: host - type: string - required: false - label: - en_US: Host Address - zh_Hans: 服务器地址 - human_description: - en_US: The address for the privately deployed HAP server. - zh_Hans: 私有部署 HAP 服务器地址，公有云无需填写 - llm_description: the address for the privately deployed HAP server. - form: form - - - name: result_type - type: select - required: true - options: - - value: table - label: - en_US: table text - zh_Hans: 表格文本 - - value: json - label: - en_US: json text - zh_Hans: JSON文本 - default: table - label: - en_US: Result type - zh_Hans: 结果类型 - human_description: - en_US: used for selecting the result type, table styled text or json text - zh_Hans: 用于选择结果类型，使用表格格式文本还是JSON格式文本 - form: form diff --git a/api/core/tools/provider/builtin/hap/tools/get_worksheet_pivot_data.py b/api/core/tools/provider/builtin/hap/tools/get_worksheet_pivot_data.py deleted file mode 100644 index 26d7116869b6d9..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/get_worksheet_pivot_data.py +++ /dev/null @@ -1,137 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetWorksheetPivotDataTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - appkey = tool_parameters.get("appkey", "") - if not appkey: - return self.create_text_message("Invalid parameter App Key") - sign = tool_parameters.get("sign", "") - if not sign: - return self.create_text_message("Invalid parameter Sign") - worksheet_id = tool_parameters.get("worksheet_id", "") - if not worksheet_id: - return self.create_text_message("Invalid parameter Worksheet ID") - x_column_fields = tool_parameters.get("x_column_fields", "") - if not x_column_fields or not x_column_fields.startswith("["): - return self.create_text_message("Invalid parameter Column Fields") - y_row_fields = tool_parameters.get("y_row_fields", "") - if y_row_fields and not y_row_fields.strip().startswith("["): - return self.create_text_message("Invalid parameter Row Fields") - elif not y_row_fields: - y_row_fields = "[]" - value_fields = tool_parameters.get("value_fields", "") - if not value_fields or not value_fields.strip().startswith("["): - return self.create_text_message("Invalid parameter Value Fields") - - host = tool_parameters.get("host", "") - if not host: - host = "https://api.mingdao.com" - elif not host.startswith(("http://", "https://")): - return self.create_text_message("Invalid parameter Host Address") - else: - host = f"{host.removesuffix('/')}/api" - - url = f"{host}/report/getPivotData" - headers = {"Content-Type": "application/json"} - payload = {"appKey": appkey, "sign": sign, "worksheetId": worksheet_id, "options": {"showTotal": True}} - - try: - x_column_fields = json.loads(x_column_fields) - payload["columns"] = x_column_fields - y_row_fields = json.loads(y_row_fields) - if y_row_fields: - payload["rows"] = y_row_fields - value_fields = json.loads(value_fields) - payload["values"] = value_fields - sort_fields = tool_parameters.get("sort_fields", "") - if not sort_fields: - sort_fields = "[]" - sort_fields = json.loads(sort_fields) - if sort_fields: - payload["options"]["sort"] = sort_fields - res = httpx.post(url, headers=headers, json=payload, timeout=60) - res.raise_for_status() - res_json = res.json() - if res_json.get("status") != 1: - return self.create_text_message(f"Failed to get the worksheet pivot data. {res_json['msg']}") - - pivot_json = self.generate_pivot_json(res_json["data"]) - pivot_table = self.generate_pivot_table(res_json["data"]) - result_type = tool_parameters.get("result_type", "") - text = pivot_table if result_type == "table" else json.dumps(pivot_json, ensure_ascii=False) - return self.create_text_message(text) - except httpx.RequestError as e: - return self.create_text_message(f"Failed to get the worksheet pivot data, request error: {e}") - except json.JSONDecodeError as e: - return self.create_text_message(f"Failed to parse JSON response: {e}") - except Exception as e: - return self.create_text_message(f"Failed to get the worksheet pivot data, unexpected error: {e}") - - def generate_pivot_table(self, data: dict[str, Any]) -> str: - columns = data["metadata"]["columns"] - rows = data["metadata"]["rows"] - values = data["metadata"]["values"] - - rows_data = data["data"] - - header = ( - ([row["displayName"] for row in rows] if rows else []) - + [column["displayName"] for column in columns] - + [value["displayName"] for value in values] - ) - line = (["---"] * len(rows) if rows else []) + ["---"] * len(columns) + ["--:"] * len(values) - - table = [header, line] - for row in rows_data: - row_data = [self.replace_pipe(row["rows"][r["controlId"]]) for r in rows] if rows else [] - row_data.extend([self.replace_pipe(row["columns"][column["controlId"]]) for column in columns]) - row_data.extend([self.replace_pipe(str(row["values"][value["controlId"]])) for value in values]) - table.append(row_data) - - return "\n".join([("|" + "|".join(row) + "|") for row in table]) - - def replace_pipe(self, text: str) -> str: - return text.replace("|", "▏").replace("\n", " ") - - def generate_pivot_json(self, data: dict[str, Any]) -> dict: - fields = { - "x-axis": [ - {"fieldId": column["controlId"], "fieldName": column["displayName"]} - for column in data["metadata"]["columns"] - ], - "y-axis": [ - {"fieldId": row["controlId"], "fieldName": row["displayName"]} for row in data["metadata"]["rows"] - ] - if data["metadata"]["rows"] - else [], - "values": [ - {"fieldId": value["controlId"], "fieldName": value["displayName"]} - for value in data["metadata"]["values"] - ], - } - # fields = ([ - # {"fieldId": row["controlId"], "fieldName": row["displayName"]} - # for row in data["metadata"]["rows"] - # ] if data["metadata"]["rows"] else []) + [ - # {"fieldId": column["controlId"], "fieldName": column["displayName"]} - # for column in data["metadata"]["columns"] - # ] + [ - # {"fieldId": value["controlId"], "fieldName": value["displayName"]} - # for value in data["metadata"]["values"] - # ] - rows = [] - for row in data["data"]: - row_data = row["rows"] or {} - row_data.update(row["columns"]) - row_data.update(row["values"]) - rows.append(row_data) - return {"fields": fields, "rows": rows, "summary": data["metadata"]["totalRow"]} diff --git a/api/core/tools/provider/builtin/hap/tools/get_worksheet_pivot_data.yaml b/api/core/tools/provider/builtin/hap/tools/get_worksheet_pivot_data.yaml deleted file mode 100644 index cf8c57b26208a9..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/get_worksheet_pivot_data.yaml +++ /dev/null @@ -1,248 +0,0 @@ -identity: - name: get_worksheet_pivot_data - author: Ryan Tian - label: - en_US: Get Worksheet Pivot Data - zh_Hans: 获取工作表统计透视数据 -description: - human: - en_US: Retrieve statistical pivot table data from a specified worksheet - zh_Hans: 从指定的工作表中检索统计透视表数据 - llm: A tool for extracting statistical pivot table data from a specific worksheet, providing summarized information for analysis and reporting purposes. -parameters: - - name: appkey - type: secret-input - required: true - label: - en_US: App Key - zh_Hans: App Key - human_description: - en_US: The AppKey parameter for the HAP application, typically found in the application's API documentation. - zh_Hans: HAP 应用的 AppKey 参数，可以从应用 API 文档中查找到 - llm_description: the AppKey parameter for the HAP application - form: form - - - name: sign - type: secret-input - required: true - label: - en_US: Sign - zh_Hans: Sign - human_description: - en_US: The Sign parameter for the HAP application - zh_Hans: HAP 应用的 Sign 参数 - llm_description: the Sign parameter for the HAP application - form: form - - - name: worksheet_id - type: string - required: true - label: - en_US: Worksheet ID - zh_Hans: 工作表 ID - human_description: - en_US: The ID of the specified worksheet - zh_Hans: 要获取字段信息的工作表 ID - llm_description: The ID of the specified worksheet which to get the fields information. - form: llm - - - name: x_column_fields - type: string - required: true - label: - en_US: Columns (X-axis) - zh_Hans: 统计列字段（X轴） - human_description: - en_US: The column fields that make up the pivot table's X-axis groups or other dimensions for the X-axis in pivot charts - zh_Hans: 组成透视表的统计列或者统计图表的X轴分组及X轴其它维度。JSON 对象数组格式，数组元素属性：controlId-列ID，displayName-显示名称，particleSize(可选)-字段类型是日期或者地区时，通过此参数设置统计维度（日期时间：1-日，2-周，3-月；地区：1-全国，2-省，3-市） - llm_description: | - This parameter allows you to specify the columns that make up the pivot table's X-axis groups or other dimensions for the X-axis in pivot charts. It is formatted as a JSON array, with its structure defined as follows: - ``` - type XColumnFields = { // X-axis or column object array - controlId: string; // fieldId - displayName: string; // displayName - particleSize?: number; // field type is date or area, set the statistical dimension (date time: 1-day, 2-week, 3-month; area: 1-nation, 2-province, 3-city) - }[]; - ``` - form: llm - - - name: y_row_fields - type: string - required: false - label: - en_US: Rows (Y-axis) - zh_Hans: 统计行字段（Y轴） - human_description: - en_US: The row fields that make up the pivot table's Y-axis groups or other dimensions for the Y-axis in pivot charts - zh_Hans: 组成透视表的统计行或者统计图表的Y轴分组及Y轴其它维度。JSON 对象数组格式，数组元素属性：controlId-列ID，displayName-显示名称，particleSize(可选)-字段类型是日期或者地区时，通过此参数设置统计维度（日期时间：1-日，2-周，3-月；地区：1-全国，2-省，3-市） - llm_description: | - This parameter allows you to specify the rows that make up the pivot table's Y-axis groups or other dimensions for the Y-axis in pivot charts. It is formatted as a JSON array, with its structure defined as follows: - ``` - type YRowFields = { // Y-axis or row object array - controlId: string; // fieldId - displayName: string; // displayName - particleSize?: number; // field type is date or area, set the statistical dimension (date time: 1-day, 2-week, 3-month; area: 1-nation, 2-province, 3-city) - }[]; - ``` - form: llm - - - name: value_fields - type: string - required: true - label: - en_US: Aggregated Values - zh_Hans: 统计值字段 - human_description: - en_US: The aggregated value fields in the pivot table - zh_Hans: 透视表中经过聚合计算后的统计值字段。JSON 对象数组格式，数组元素属性：controlId-列ID，displayName-显示名称，aggregation-聚合方式（SUM,AVG,MIN,MAX,COUNT） - llm_description: | - This parameter allows you to specify the aggregated value fields in the pivot table. It is formatted as a JSON array, with its structure defined as follows: - ``` - type ValueFields = { // aggregated value object array - controlId: string; // fieldId - displayName: string; // displayName - aggregation: string; // aggregation method, e.g.: SUM, AVG, MIN, MAX, COUNT - }[]; - ``` - form: llm - - - name: filters - type: string - required: false - label: - en_US: Filter Set - zh_Hans: 筛选器组合 - human_description: - en_US: A combination of filters applied to query records, formatted as a JSON array. See the application's API documentation for details on its structure and usage. - zh_Hans: 查询记录的筛选条件组合，格式为 JSON 数组，可以从应用 API 文档中了解参数结构详情 - llm_description: | - This parameter allows you to specify a set of conditions that records must meet to be included in the result set. It is formatted as a JSON array, with its structure defined as follows: - ``` - type Filters = { // filter object array - controlId: string; // fieldId - dataType: number; // fieldTypeId - spliceType: number; // condition concatenation method, 1: And, 2: Or - filterType: number; // expression type, refer to the for enumerable values - values?: string[]; // values in the condition, for option-type fields, multiple values can be passed - value?: string; // value in the condition, a single value can be passed according to the field type - dateRange?: number; // date range, mandatory when filterType is 17 or 18, refer to the for enumerable values - minValue?: string; // minimum value for custom range - maxValue?: string; // maximum value for custom range - isAsc?: boolean; // ascending order, false: descending, true: ascending - }[]; - ``` - For option-type fields, if this option field has `options`, then you need to get the corresponding `key` value from the `options` in the current field information via `value`, and pass it into `values` in array format. Do not use the `options` value of other fields as input conditions. - - ### FilterTypeEnum Reference - ``` - Enum Value, Enum Character, Description - 1, Like, Contains - 2, Eq, Is (Equal) - 3, Start, Starts With - 4, End, Ends With - 5, NotLike, Does Not Contain - 6, Ne, Is Not (Not Equal) - 7, IsEmpty, Empty - 8, HasValue, Not Empty - 11, Between, Within Range - 12, NotBetween, Outside Range - 13, Gt, Greater Than - 14, Gte, Greater Than or Equal To - 15, Lt, Less Than - 16, Lte, Less Than or Equal To - 17, DateEnum, Date Is - 18, NotDateEnum, Date Is Not - 21, MySelf, Owned by Me - 22, UnRead, Unread - 23, Sub, Owned by Subordinate - 24, RCEq, Associated Field Is - 25, RCNe, Associated Field Is Not - 26, ArrEq, Array Equals - 27, ArrNe, Array Does Not Equal - 31, DateBetween, Date Within Range (can only be used with minValue and maxValue) - 32, DateNotBetween, Date Not Within Range (can only be used with minValue and maxValue) - 33, DateGt, Date Later Than - 34, DateGte, Date Later Than or Equal To - 35, DateLt, Date Earlier Than - 36, DateLte, Date Earlier Than or Equal To - ``` - - ### DateRangeEnum Reference - ``` - Enum Value, Enum Character, Description - 1, Today, Today - 2, Yesterday, Yesterday - 3, Tomorrow, Tomorrow - 4, ThisWeek, This Week - 5, LastWeek, Last Week - 6, NextWeek, Next Week - 7, ThisMonth, This Month - 8, LastMonth, Last Month - 9, NextMonth, Next Month - 12, ThisQuarter, This Quarter - 13, LastQuarter, Last Quarter - 14, NextQuarter, Next Quarter - 15, ThisYear, This Year - 16, LastYear, Last Year - 17, NextYear, Next Year - 18, Customize, Custom - 21, Last7Day, Past 7 Days - 22, Last14Day, Past 14 Days - 23, Last30Day, Past 30 Days - 31, Next7Day, Next 7 Days - 32, Next14Day, Next 14 Days - 33, Next33Day, Next 33 Days - ``` - form: llm - - - name: sort_fields - type: string - required: false - label: - en_US: Sort Fields - zh_Hans: 排序字段 - human_description: - en_US: The fields to used for sorting - zh_Hans: 用于确定排序的字段，不超过3个 - llm_description: | - This optional parameter specifies the unique identifier of the fields that will be used to sort the results. It is in the format of an array of JSON objects, and its structure is defined as follows: - ``` - type SortByFields = { - controlId: string; // Field ID used for sorting - isAsc: boolean; // Sorting direction, true indicates ascending order, false indicates descending order - }[]; - ``` - form: llm - - - name: host - type: string - required: false - label: - en_US: Host Address - zh_Hans: 服务器地址 - human_description: - en_US: The address for the privately deployed HAP server. - zh_Hans: 私有部署 HAP 服务器地址，公有云无需填写 - llm_description: the address for the privately deployed HAP server. - form: form - - - name: result_type - type: select - required: true - options: - - value: table - label: - en_US: table text - zh_Hans: 表格文本 - - value: json - label: - en_US: json text - zh_Hans: JSON文本 - default: table - label: - en_US: Result type - zh_Hans: 结果类型 - human_description: - en_US: used for selecting the result type, table styled text or json text - zh_Hans: 用于选择结果类型，使用表格格式文本还是JSON格式文本 - form: form diff --git a/api/core/tools/provider/builtin/hap/tools/list_worksheet_records.py b/api/core/tools/provider/builtin/hap/tools/list_worksheet_records.py deleted file mode 100644 index d6ac3688b7794a..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/list_worksheet_records.py +++ /dev/null @@ -1,231 +0,0 @@ -import json -import re -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class ListWorksheetRecordsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - appkey = tool_parameters.get("appkey", "") - if not appkey: - return self.create_text_message("Invalid parameter App Key") - - sign = tool_parameters.get("sign", "") - if not sign: - return self.create_text_message("Invalid parameter Sign") - - worksheet_id = tool_parameters.get("worksheet_id", "") - if not worksheet_id: - return self.create_text_message("Invalid parameter Worksheet ID") - - host = tool_parameters.get("host", "") - if not host: - host = "https://api.mingdao.com" - elif not (host.startswith("http://") or host.startswith("https://")): - return self.create_text_message("Invalid parameter Host Address") - else: - host = f"{host.removesuffix('/')}/api" - - url_fields = f"{host}/v2/open/worksheet/getWorksheetInfo" - headers = {"Content-Type": "application/json"} - payload = {"appKey": appkey, "sign": sign, "worksheetId": worksheet_id} - - field_ids = tool_parameters.get("field_ids", "") - - try: - res = httpx.post(url_fields, headers=headers, json=payload, timeout=30) - res_json = res.json() - if res.is_success: - if res_json["error_code"] != 1: - return self.create_text_message( - "Failed to get the worksheet information. {}".format(res_json["error_msg"]) - ) - else: - worksheet_name = res_json["data"]["name"] - fields, schema, table_header = self.get_schema(res_json["data"]["controls"], field_ids) - else: - return self.create_text_message( - f"Failed to get the worksheet information, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message( - "Failed to get the worksheet information, something went wrong: {}".format(e) - ) - - if field_ids: - payload["controls"] = [v.strip() for v in field_ids.split(",")] if field_ids else [] - filters = tool_parameters.get("filters", "") - if filters: - payload["filters"] = json.loads(filters) - sort_id = tool_parameters.get("sort_id", "") - sort_is_asc = tool_parameters.get("sort_is_asc", False) - if sort_id: - payload["sortId"] = sort_id - payload["isAsc"] = sort_is_asc - limit = tool_parameters.get("limit", 50) - payload["pageSize"] = limit - page_index = tool_parameters.get("page_index", 1) - payload["pageIndex"] = page_index - payload["useControlId"] = True - payload["listType"] = 1 - - url = f"{host}/v2/open/worksheet/getFilterRows" - try: - res = httpx.post(url, headers=headers, json=payload, timeout=90) - res_json = res.json() - if res.is_success: - if res_json["error_code"] != 1: - return self.create_text_message("Failed to get the records. {}".format(res_json["error_msg"])) - else: - result = { - "fields": fields, - "rows": [], - "total": res_json.get("data", {}).get("total"), - "payload": { - key: payload[key] - for key in [ - "worksheetId", - "controls", - "filters", - "sortId", - "isAsc", - "pageSize", - "pageIndex", - ] - if key in payload - }, - } - rows = res_json.get("data", {}).get("rows", []) - result_type = tool_parameters.get("result_type", "") - if not result_type: - result_type = "table" - if result_type == "json": - for row in rows: - result["rows"].append(self.get_row_field_value(row, schema)) - return self.create_text_message(json.dumps(result, ensure_ascii=False)) - else: - result_text = f"Found {result['total']} rows in worksheet \"{worksheet_name}\"." - if result["total"] > 0: - result_text += ( - f" The following are {min(limit, result['total'])}" - f" pieces of data presented in a table format:\n\n{table_header}" - ) - for row in rows: - result_values = [] - for f in fields: - result_values.append( - self.handle_value_type(row[f["fieldId"]], schema[f["fieldId"]]) - ) - result_text += "\n|" + "|".join(result_values) + "|" - return self.create_text_message(result_text) - else: - return self.create_text_message( - f"Failed to get the records, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to get the records, something went wrong: {}".format(e)) - - def get_row_field_value(self, row: dict, schema: dict): - row_value = {"rowid": row["rowid"]} - for field in schema: - row_value[field] = self.handle_value_type(row[field], schema[field]) - return row_value - - def get_schema(self, controls: list, fieldids: str): - allow_fields = {v.strip() for v in fieldids.split(",")} if fieldids else set() - fields = [] - schema = {} - field_names = [] - for control in controls: - control_type_id = self.get_real_type_id(control) - if (control_type_id in self._get_ignore_types()) or ( - allow_fields and control["controlId"] not in allow_fields - ): - continue - else: - fields.append({"fieldId": control["controlId"], "fieldName": control["controlName"]}) - schema[control["controlId"]] = {"typeId": control_type_id, "options": self.set_option(control)} - field_names.append(control["controlName"]) - if not allow_fields or ("ctime" in allow_fields): - fields.append({"fieldId": "ctime", "fieldName": "Created Time"}) - schema["ctime"] = {"typeId": 16, "options": {}} - field_names.append("Created Time") - fields.append({"fieldId": "rowid", "fieldName": "Record Row ID"}) - schema["rowid"] = {"typeId": 2, "options": {}} - field_names.append("Record Row ID") - return fields, schema, "|" + "|".join(field_names) + "|\n|" + "---|" * len(field_names) - - def get_real_type_id(self, control: dict) -> int: - return control["sourceControlType"] if control["type"] == 30 else control["type"] - - def set_option(self, control: dict) -> dict: - options = {} - if control.get("options"): - options = {option["key"]: option["value"] for option in control["options"]} - elif control.get("advancedSetting", {}).get("itemnames"): - try: - itemnames = json.loads(control["advancedSetting"]["itemnames"]) - options = {item["key"]: item["value"] for item in itemnames} - except json.JSONDecodeError: - pass - return options - - def _get_ignore_types(self): - return {14, 21, 22, 34, 42, 43, 45, 47, 49, 10010} - - def handle_value_type(self, value, field): - type_id = field.get("typeId") - if type_id == 10: - value = value if isinstance(value, str) else "、".join(value) - elif type_id in {28, 36}: - value = field.get("options", {}).get(value, value) - elif type_id in {26, 27, 48, 14}: - value = self.process_value(value) - elif type_id in {35, 29}: - value = self.parse_cascade_or_associated(field, value) - elif type_id == 40: - value = self.parse_location(value) - return self.rich_text_to_plain_text(value) if value else "" - - def process_value(self, value): - if isinstance(value, str): - if value.startswith('[{"accountId"'): - value = json.loads(value) - value = ", ".join([item["fullname"] for item in value]) - elif value.startswith('[{"departmentId"'): - value = json.loads(value) - value = "、".join([item["departmentName"] for item in value]) - elif value.startswith('[{"organizeId"'): - value = json.loads(value) - value = "、".join([item["organizeName"] for item in value]) - elif value.startswith('[{"file_id"') or value == "[]": - value = "" - elif hasattr(value, "accountId"): - value = value["fullname"] - return value - - def parse_cascade_or_associated(self, field, value): - if (field["typeId"] == 35 and value.startswith("[")) or (field["typeId"] == 29 and value.startswith("[{")): - value = json.loads(value) - value = value[0]["name"] if len(value) > 0 else "" - else: - value = "" - return value - - def parse_location(self, value): - if len(value) > 10: - parsed_value = json.loads(value) - value = parsed_value.get("address", "") - else: - value = "" - return value - - def rich_text_to_plain_text(self, rich_text): - text = re.sub(r"<[^>]+>", "", rich_text) if "<" in rich_text else rich_text - return text.replace("|", "▏").replace("\n", " ") diff --git a/api/core/tools/provider/builtin/hap/tools/list_worksheet_records.yaml b/api/core/tools/provider/builtin/hap/tools/list_worksheet_records.yaml deleted file mode 100644 index 3c37746b921d05..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/list_worksheet_records.yaml +++ /dev/null @@ -1,226 +0,0 @@ -identity: - name: list_worksheet_records - author: Ryan Tian - label: - en_US: List Worksheet Records - zh_Hans: 查询工作表记录数据 -description: - human: - en_US: List records from the worksheet - zh_Hans: 查询工作表的记录列表数据，一次最多1000行，可分页获取 - llm: A tool to retrieve record data from the specific worksheet. -parameters: - - name: appkey - type: secret-input - required: true - label: - en_US: App Key - zh_Hans: App Key - human_description: - en_US: The AppKey parameter for the HAP application, typically found in the application's API documentation. - zh_Hans: HAP 应用的 AppKey 参数，可以从应用 API 文档中查找到 - llm_description: the AppKey parameter for the HAP application - form: form - - - name: sign - type: secret-input - required: true - label: - en_US: Sign - zh_Hans: Sign - human_description: - en_US: The Sign parameter for the HAP application - zh_Hans: HAP 应用的 Sign 参数 - llm_description: the Sign parameter for the HAP application - form: form - - - name: worksheet_id - type: string - required: true - label: - en_US: Worksheet ID - zh_Hans: 工作表 ID - human_description: - en_US: The ID of the worksheet from which to retrieve record data - zh_Hans: 要获取记录数据的工作表 ID - llm_description: This parameter specifies the ID of the worksheet where the records are stored. - form: llm - - - name: field_ids - type: string - required: false - label: - en_US: Field IDs - zh_Hans: 字段 ID 列表 - human_description: - en_US: A comma-separated list of field IDs whose data to retrieve. If not provided, all fields' data will be fetched - zh_Hans: 要获取记录数据的字段 ID，多个 ID 间用英文逗号隔开，不传此参数则将获取所有字段的数据 - llm_description: This optional parameter lets you specify a comma-separated list of field IDs. Unless the user explicitly requests to output the specified field in the question, this parameter should usually be omitted. If this parameter is omitted, the API will return data for all fields by default. When provided, only the data associated with these fields will be included in the response. - form: llm - - - name: filters - type: string - required: false - label: - en_US: Filter Set - zh_Hans: 筛选器组合 - human_description: - en_US: A combination of filters applied to query records, formatted as a JSON array. See the application's API documentation for details on its structure and usage. - zh_Hans: 查询记录的筛选条件组合，格式为 JSON 数组，可以从应用 API 文档中了解参数结构详情 - llm_description: | - This parameter allows you to specify a set of conditions that records must meet to be included in the result set. It is formatted as a JSON array, with its structure defined as follows: - ``` - type Filters = { // filter object array - controlId: string; // fieldId - dataType: number; // fieldTypeId - spliceType: number; // condition concatenation method, 1: And, 2: Or - filterType: number; // expression type, refer to the for enumerable values - values?: string[]; // values in the condition, for option-type fields, multiple values can be passed - value?: string; // value in the condition, a single value can be passed according to the field type - dateRange?: number; // date range, mandatory when filterType is 17 or 18, refer to the for enumerable values - minValue?: string; // minimum value for custom range - maxValue?: string; // maximum value for custom range - isAsc?: boolean; // ascending order, false: descending, true: ascending - }[]; - ``` - For option-type fields, if this option field has `options`, then you need to get the corresponding `key` value from the `options` in the current field information via `value`, and pass it into `values` in array format. Do not use the `options` value of other fields as input conditions. - - ### FilterTypeEnum Reference - ``` - Enum Value, Enum Character, Description - 1, Like, Contains(Include) - 2, Eq, Is (Equal) - 3, Start, Starts With - 4, End, Ends With - 5, NotLike, Does Not Contain(Not Include) - 6, Ne, Is Not (Not Equal) - 7, IsEmpty, Empty - 8, HasValue, Not Empty - 11, Between, Within Range(Belong to) - 12, NotBetween, Outside Range(Not belong to) - 13, Gt, Greater Than - 14, Gte, Greater Than or Equal To - 15, Lt, Less Than - 16, Lte, Less Than or Equal To - 17, DateEnum, Date Is - 18, NotDateEnum, Date Is Not - 24, RCEq, Associated Field Is - 25, RCNe, Associated Field Is Not - 26, ArrEq, Array Equals - 27, ArrNe, Array Does Not Equal - 31, DateBetween, Date Within Range (can only be used with minValue and maxValue) - 32, DateNotBetween, Date Not Within Range (can only be used with minValue and maxValue) - 33, DateGt, Date Later Than - 34, DateGte, Date Later Than or Equal To - 35, DateLt, Date Earlier Than - 36, DateLte, Date Earlier Than or Equal To - ``` - - ### DateRangeEnum Reference - ``` - Enum Value, Enum Character, Description - 1, Today, Today - 2, Yesterday, Yesterday - 3, Tomorrow, Tomorrow - 4, ThisWeek, This Week - 5, LastWeek, Last Week - 6, NextWeek, Next Week - 7, ThisMonth, This Month - 8, LastMonth, Last Month - 9, NextMonth, Next Month - 12, ThisQuarter, This Quarter - 13, LastQuarter, Last Quarter - 14, NextQuarter, Next Quarter - 15, ThisYear, This Year - 16, LastYear, Last Year - 17, NextYear, Next Year - 18, Customize, Custom - 21, Last7Day, Past 7 Days - 22, Last14Day, Past 14 Days - 23, Last30Day, Past 30 Days - 31, Next7Day, Next 7 Days - 32, Next14Day, Next 14 Days - 33, Next33Day, Next 33 Days - ``` - form: llm - - - name: sort_id - type: string - required: false - label: - en_US: Sort Field ID - zh_Hans: 排序字段 ID - human_description: - en_US: The ID of the field used for sorting - zh_Hans: 用以排序的字段 ID - llm_description: This optional parameter specifies the unique identifier of the field that will be used to sort the results. It should be set to the ID of an existing field within your data structure. - form: llm - - - name: sort_is_asc - type: boolean - required: false - label: - en_US: Ascending Order - zh_Hans: 是否升序排列 - human_description: - en_US: Determines whether the sorting is in ascending (true) or descending (false) order - zh_Hans: 排序字段的排序方式：true-升序，false-降序 - llm_description: This optional parameter controls the direction of the sort. If set to true, the results will be sorted in ascending order; if false, they will be sorted in descending order. - form: llm - - - name: limit - type: number - required: false - label: - en_US: Record Limit - zh_Hans: 记录数量限制 - human_description: - en_US: The maximum number of records to retrieve - zh_Hans: 要获取的记录数量限制条数 - llm_description: This optional parameter allows you to specify the maximum number of records that should be returned in the result set. When retrieving paginated record data, this parameter indicates the number of rows to fetch per page, and must be used in conjunction with the `page_index` parameter. - form: llm - - - name: page_index - type: number - required: false - label: - en_US: Page Index - zh_Hans: 页码 - human_description: - en_US: The page number when paginating through a list of records - zh_Hans: 分页读取记录列表时的页码 - llm_description: This parameter is used when you need to paginate through a large set of records. The default value is 1, which refers to the first page. When it is used, the meaning of the `limit` parameter becomes the number of records per page. - form: llm - - - name: host - type: string - required: false - label: - en_US: Host Address - zh_Hans: 服务器地址 - human_description: - en_US: The address for the privately deployed HAP server. - zh_Hans: 私有部署 HAP 服务器地址，公有云无需填写 - llm_description: the address for the privately deployed HAP server. - form: form - - - name: result_type - type: select - required: true - options: - - value: table - label: - en_US: table text - zh_Hans: 表格文本 - - value: json - label: - en_US: json text - zh_Hans: JSON文本 - default: table - label: - en_US: Result type - zh_Hans: 结果类型 - human_description: - en_US: used for selecting the result type, table styled text or json text - zh_Hans: 用于选择结果类型，使用表格格式文本还是JSON格式文本 - form: form diff --git a/api/core/tools/provider/builtin/hap/tools/list_worksheets.py b/api/core/tools/provider/builtin/hap/tools/list_worksheets.py deleted file mode 100644 index 4e852c0028497c..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/list_worksheets.py +++ /dev/null @@ -1,83 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class ListWorksheetsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - appkey = tool_parameters.get("appkey", "") - if not appkey: - return self.create_text_message("Invalid parameter App Key") - sign = tool_parameters.get("sign", "") - if not sign: - return self.create_text_message("Invalid parameter Sign") - - host = tool_parameters.get("host", "") - if not host: - host = "https://api.mingdao.com" - elif not (host.startswith("http://") or host.startswith("https://")): - return self.create_text_message("Invalid parameter Host Address") - else: - host = f"{host.removesuffix('/')}/api" - url = f"{host}/v1/open/app/get" - - result_type = tool_parameters.get("result_type", "") - if not result_type: - result_type = "table" - - headers = {"Content-Type": "application/json"} - params = { - "appKey": appkey, - "sign": sign, - } - try: - res = httpx.get(url, headers=headers, params=params, timeout=30) - res_json = res.json() - if res.is_success: - if res_json["error_code"] != 1: - return self.create_text_message( - "Failed to access the application. {}".format(res_json["error_msg"]) - ) - else: - if result_type == "json": - worksheets = [] - for section in res_json["data"]["sections"]: - worksheets.extend(self._extract_worksheets(section, result_type)) - return self.create_text_message(text=json.dumps(worksheets, ensure_ascii=False)) - else: - worksheets = "|worksheetId|worksheetName|description|\n|---|---|---|" - for section in res_json["data"]["sections"]: - worksheets += self._extract_worksheets(section, result_type) - return self.create_text_message(worksheets) - - else: - return self.create_text_message( - f"Failed to list worksheets, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to list worksheets, something went wrong: {}".format(e)) - - def _extract_worksheets(self, section, type): - items = [] - tables = "" - for item in section.get("items", []): - if item.get("type") == 0 and ("notes" not in item or item.get("notes") != "NO"): - if type == "json": - filtered_item = {"id": item["id"], "name": item["name"], "notes": item.get("notes", "")} - items.append(filtered_item) - else: - tables += f"\n|{item['id']}|{item['name']}|{item.get('notes', '')}|" - - for child_section in section.get("childSections", []): - if type == "json": - items.extend(self._extract_worksheets(child_section, "json")) - else: - tables += self._extract_worksheets(child_section, "table") - - return items if type == "json" else tables diff --git a/api/core/tools/provider/builtin/hap/tools/list_worksheets.yaml b/api/core/tools/provider/builtin/hap/tools/list_worksheets.yaml deleted file mode 100644 index 935b72a89564cd..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/list_worksheets.yaml +++ /dev/null @@ -1,68 +0,0 @@ -identity: - name: list_worksheets - author: Ryan Tian - label: - en_US: List Worksheets - zh_Hans: 获取应用下所有工作表 -description: - human: - en_US: List worksheets within an application - zh_Hans: 获取应用下的所有工作表和说明信息 - llm: A tool to list worksheets info within an application, imported parameter is AppKey and Sign of the application. -parameters: - - name: appkey - type: secret-input - required: true - label: - en_US: App Key - zh_Hans: App Key - human_description: - en_US: The AppKey parameter for the HAP application, typically found in the application's API documentation. - zh_Hans: HAP 应用的 AppKey 参数，可以从应用 API 文档中查找到 - llm_description: the AppKey parameter for the HAP application - form: form - - - name: sign - type: secret-input - required: true - label: - en_US: Sign - zh_Hans: Sign - human_description: - en_US: The Sign parameter for the HAP application - zh_Hans: HAP 应用的 Sign 参数 - llm_description: the Sign parameter for the HAP application - form: form - - - name: host - type: string - required: false - label: - en_US: Host Address - zh_Hans: 服务器地址 - human_description: - en_US: The address for the privately deployed HAP server. - zh_Hans: 私有部署 HAP 服务器地址，公有云无需填写 - llm_description: the address for the privately deployed HAP server. - form: form - - - name: result_type - type: select - required: true - options: - - value: table - label: - en_US: table text - zh_Hans: 表格文本 - - value: json - label: - en_US: json text - zh_Hans: JSON文本 - default: table - label: - en_US: Result type - zh_Hans: 结果类型 - human_description: - en_US: used for selecting the result type, table styled text or json text - zh_Hans: 用于选择结果类型，使用表格格式文本还是JSON格式文本 - form: form diff --git a/api/core/tools/provider/builtin/hap/tools/update_worksheet_record.py b/api/core/tools/provider/builtin/hap/tools/update_worksheet_record.py deleted file mode 100644 index 971f3d37f6dfbf..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/update_worksheet_record.py +++ /dev/null @@ -1,55 +0,0 @@ -import json -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class UpdateWorksheetRecordTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - appkey = tool_parameters.get("appkey", "") - if not appkey: - return self.create_text_message("Invalid parameter App Key") - sign = tool_parameters.get("sign", "") - if not sign: - return self.create_text_message("Invalid parameter Sign") - worksheet_id = tool_parameters.get("worksheet_id", "") - if not worksheet_id: - return self.create_text_message("Invalid parameter Worksheet ID") - row_id = tool_parameters.get("row_id", "") - if not row_id: - return self.create_text_message("Invalid parameter Record Row ID") - record_data = tool_parameters.get("record_data", "") - if not record_data: - return self.create_text_message("Invalid parameter Record Row Data") - - host = tool_parameters.get("host", "") - if not host: - host = "https://api.mingdao.com" - elif not host.startswith(("http://", "https://")): - return self.create_text_message("Invalid parameter Host Address") - else: - host = f"{host.removesuffix('/')}/api" - - url = f"{host}/v2/open/worksheet/editRow" - headers = {"Content-Type": "application/json"} - payload = {"appKey": appkey, "sign": sign, "worksheetId": worksheet_id, "rowId": row_id} - - try: - payload["controls"] = json.loads(record_data) - res = httpx.post(url, headers=headers, json=payload, timeout=60) - res.raise_for_status() - res_json = res.json() - if res_json.get("error_code") != 1: - return self.create_text_message(f"Failed to update the record. {res_json['error_msg']}") - return self.create_text_message("Record updated successfully.") - except httpx.RequestError as e: - return self.create_text_message(f"Failed to update the record, request error: {e}") - except json.JSONDecodeError as e: - return self.create_text_message(f"Failed to parse JSON response: {e}") - except Exception as e: - return self.create_text_message(f"Failed to update the record, unexpected error: {e}") diff --git a/api/core/tools/provider/builtin/hap/tools/update_worksheet_record.yaml b/api/core/tools/provider/builtin/hap/tools/update_worksheet_record.yaml deleted file mode 100644 index fe1f8f671a4e2f..00000000000000 --- a/api/core/tools/provider/builtin/hap/tools/update_worksheet_record.yaml +++ /dev/null @@ -1,90 +0,0 @@ -identity: - name: update_worksheet_record - author: Ryan Tian - label: - en_US: Update Worksheet Record - zh_Hans: 更新指定的一条工作表记录 -description: - human: - en_US: Updates a single record in a worksheet based on the specified record row ID - zh_Hans: 根据指定的记录ID更新一条工作表记录数据 - llm: A tool to modify existing information within a particular record of a worksheet by referencing its unique identifier. -parameters: - - name: appkey - type: secret-input - required: true - label: - en_US: App Key - zh_Hans: App Key - human_description: - en_US: The AppKey parameter for the HAP application, typically found in the application's API documentation. - zh_Hans: HAP 应用的 AppKey 参数，可以从应用 API 文档中查找到 - llm_description: the AppKey parameter for the HAP application - form: form - - - name: sign - type: secret-input - required: true - label: - en_US: Sign - zh_Hans: Sign - human_description: - en_US: The Sign parameter for the HAP application - zh_Hans: HAP 应用的 Sign 参数 - llm_description: the Sign parameter for the HAP application - form: form - - - name: worksheet_id - type: string - required: true - label: - en_US: Worksheet ID - zh_Hans: 工作表 ID - human_description: - en_US: The ID of the specified worksheet - zh_Hans: 要获取字段信息的工作表 ID - llm_description: The ID of the specified worksheet which to get the fields information. - form: llm - - - name: row_id - type: string - required: true - label: - en_US: Record Row ID - zh_Hans: 记录 ID - human_description: - en_US: The row ID of the specified record - zh_Hans: 要更新的记录 ID - llm_description: The row ID of the specified record which to be updated. - form: llm - - - name: record_data - type: string - required: true - label: - en_US: Record Row Data - zh_Hans: 记录数据 - human_description: - en_US: The fields with data of the specified record - zh_Hans: 要更新的记录数据，JSON 对象数组格式。数组元素属性：controlId-字段ID，value-字段值 - llm_description: | - The fields with data of the specified record which to be updated. It is in the format of an array of JSON objects, and the structure is defined as follows: - ``` - type RowData = { - controlId: string; // Field ID to be updated - value: string; // Field value to be updated - }[]; - ``` - form: llm - - - name: host - type: string - required: false - label: - en_US: Host Address - zh_Hans: 服务器地址 - human_description: - en_US: The address for the privately deployed HAP server. - zh_Hans: 私有部署 HAP 服务器地址，公有云无需填写 - llm_description: the address for the privately deployed HAP server. - form: form diff --git a/api/core/tools/provider/builtin/jina/_assets/icon.svg b/api/core/tools/provider/builtin/jina/_assets/icon.svg deleted file mode 100644 index 2e1b00fa52e43c..00000000000000 --- a/api/core/tools/provider/builtin/jina/_assets/icon.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - diff --git a/api/core/tools/provider/builtin/jina/jina.py b/api/core/tools/provider/builtin/jina/jina.py deleted file mode 100644 index 154e15db016dd1..00000000000000 --- a/api/core/tools/provider/builtin/jina/jina.py +++ /dev/null @@ -1,38 +0,0 @@ -import json -from typing import Any - -from core.tools.entities.values import ToolLabelEnum -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.jina.tools.jina_reader import JinaReaderTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class GoogleProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - if credentials["api_key"] is None: - credentials["api_key"] = "" - else: - result = ( - JinaReaderTool() - .fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ) - .invoke( - user_id="", - tool_parameters={ - "url": "https://example.com", - }, - )[0] - ) - - message = json.loads(result.message) - if message["code"] != 200: - raise ToolProviderCredentialValidationError(message["message"]) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) - - def _get_tool_labels(self) -> list[ToolLabelEnum]: - return [ToolLabelEnum.SEARCH, ToolLabelEnum.PRODUCTIVITY] diff --git a/api/core/tools/provider/builtin/jina/jina.yaml b/api/core/tools/provider/builtin/jina/jina.yaml deleted file mode 100644 index 06f23382d92a3a..00000000000000 --- a/api/core/tools/provider/builtin/jina/jina.yaml +++ /dev/null @@ -1,32 +0,0 @@ -identity: - author: Dify - name: jina - label: - en_US: Jina - zh_Hans: Jina - pt_BR: Jina - description: - en_US: Convert any URL to an LLM-friendly input or perform searches on the web for grounding information. Experience improved output for your agent and RAG systems at no cost. - zh_Hans: 将任何URL转换为LLM易读的输入或在网页上搜索引擎上搜索引擎。 - pt_BR: Converte qualquer URL em uma entrada LLm-fácil de ler ou realize pesquisas na web para obter informação de grounding. Tenha uma experiência melhor para seu agente e sistemas RAG sem custo. - icon: icon.svg - tags: - - search - - productivity -credentials_for_provider: - api_key: - type: secret-input - required: false - label: - en_US: API Key (leave empty if you don't have one) - zh_Hans: API 密钥（可留空） - pt_BR: Chave API (deixe vazio se você não tiver uma) - placeholder: - en_US: Please enter your Jina API key - zh_Hans: 请输入你的 Jina API 密钥 - pt_BR: Por favor, insira sua chave de API do Jina - help: - en_US: Get your Jina API key from Jina (optional, but you can get a higher rate) - zh_Hans: 从 Jina 获取您的 Jina API 密钥（非必须，能得到更高的速率） - pt_BR: Obtenha sua chave de API do Jina na Jina (opcional, mas você pode obter uma taxa mais alta) - url: https://jina.ai diff --git a/api/core/tools/provider/builtin/jina/tools/jina_reader.py b/api/core/tools/provider/builtin/jina/tools/jina_reader.py deleted file mode 100644 index 0dd55c65291783..00000000000000 --- a/api/core/tools/provider/builtin/jina/tools/jina_reader.py +++ /dev/null @@ -1,74 +0,0 @@ -import json -from typing import Any, Union - -from yarl import URL - -from core.helper import ssrf_proxy -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class JinaReaderTool(BuiltinTool): - _jina_reader_endpoint = "https://r.jina.ai/" - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - url = tool_parameters["url"] - - headers = {"Accept": "application/json"} - - if "api_key" in self.runtime.credentials and self.runtime.credentials.get("api_key"): - headers["Authorization"] = "Bearer " + self.runtime.credentials.get("api_key") - - request_params = tool_parameters.get("request_params") - if request_params is not None and request_params != "": - try: - request_params = json.loads(request_params) - if not isinstance(request_params, dict): - raise ValueError("request_params must be a JSON object") - except (json.JSONDecodeError, ValueError) as e: - raise ValueError(f"Invalid request_params: {e}") - - target_selector = tool_parameters.get("target_selector") - if target_selector is not None and target_selector != "": - headers["X-Target-Selector"] = target_selector - - wait_for_selector = tool_parameters.get("wait_for_selector") - if wait_for_selector is not None and wait_for_selector != "": - headers["X-Wait-For-Selector"] = wait_for_selector - - if tool_parameters.get("image_caption", False): - headers["X-With-Generated-Alt"] = "true" - - if tool_parameters.get("gather_all_links_at_the_end", False): - headers["X-With-Links-Summary"] = "true" - - if tool_parameters.get("gather_all_images_at_the_end", False): - headers["X-With-Images-Summary"] = "true" - - proxy_server = tool_parameters.get("proxy_server") - if proxy_server is not None and proxy_server != "": - headers["X-Proxy-Url"] = proxy_server - - if tool_parameters.get("no_cache", False): - headers["X-No-Cache"] = "true" - - max_retries = tool_parameters.get("max_retries", 3) - response = ssrf_proxy.get( - str(URL(self._jina_reader_endpoint + url)), - headers=headers, - params=request_params, - timeout=(10, 60), - max_retries=max_retries, - ) - - if tool_parameters.get("summary", False): - return self.create_text_message(self.summary(user_id, response.text)) - - return self.create_text_message(response.text) diff --git a/api/core/tools/provider/builtin/jina/tools/jina_reader.yaml b/api/core/tools/provider/builtin/jina/tools/jina_reader.yaml deleted file mode 100644 index 58ad6d8694222d..00000000000000 --- a/api/core/tools/provider/builtin/jina/tools/jina_reader.yaml +++ /dev/null @@ -1,166 +0,0 @@ -identity: - name: jina_reader - author: Dify - label: - en_US: JinaReader - zh_Hans: JinaReader - pt_BR: JinaReader -description: - human: - en_US: Convert any URL to an LLM-friendly input. Experience improved output for your agent and RAG systems at no cost. - zh_Hans: 将任何 URL 转换为 LLM 友好的输入。无需付费即可体验为您的 Agent 和 RAG 系统提供的改进输出。 - pt_BR: Converta qualquer URL em uma entrada amigável ao LLM. Experimente uma saída aprimorada para seus sistemas de agente e RAG sem custo. - llm: A tool for scraping webpages. Input should be a URL. -parameters: - - name: url - type: string - required: true - label: - en_US: URL - zh_Hans: 网页链接 - pt_BR: URL - human_description: - en_US: used for linking to webpages - zh_Hans: 用于链接到网页 - pt_BR: used for linking to webpages - llm_description: url for scraping - form: llm - - name: request_params - type: string - required: false - label: - en_US: Request params - zh_Hans: 请求参数 - pt_BR: Request params - human_description: - en_US: | - request parameters, format: {"key1": "value1", "key2": "value2"} - zh_Hans: | - 请求参数，格式：{"key1": "value1", "key2": "value2"} - pt_BR: | - request parameters, format: {"key1": "value1", "key2": "value2"} - llm_description: request parameters - form: llm - - name: target_selector - type: string - required: false - label: - en_US: Target selector - zh_Hans: 目标选择器 - pt_BR: Seletor de destino - human_description: - en_US: css selector for scraping specific elements - zh_Hans: css 选择器用于抓取特定元素 - pt_BR: css selector for scraping specific elements - llm_description: css selector of the target element to scrape - form: form - - name: wait_for_selector - type: string - required: false - label: - en_US: Wait for selector - zh_Hans: 等待选择器 - pt_BR: Aguardar por seletor - human_description: - en_US: css selector for waiting for specific elements - zh_Hans: css 选择器用于等待特定元素 - pt_BR: css selector for waiting for specific elements - llm_description: css selector of the target element to wait for - form: form - - name: image_caption - type: boolean - required: false - default: false - label: - en_US: Image caption - zh_Hans: 图片说明 - pt_BR: Legenda da imagem - human_description: - en_US: "Captions all images at the specified URL, adding 'Image [idx]: [caption]' as an alt tag for those without one. This allows downstream LLMs to interact with the images in activities such as reasoning and summarizing." - zh_Hans: "为指定 URL 上的所有图像添加标题，为没有标题的图像添加“Image [idx]: [caption]”作为 alt 标签。这允许下游 LLM 在推理和总结等活动中与图像进行交互。" - pt_BR: "Captions all images at the specified URL, adding 'Image [idx]: [caption]' as an alt tag for those without one. This allows downstream LLMs to interact with the images in activities such as reasoning and summarizing." - llm_description: Captions all images at the specified URL - form: form - - name: gather_all_links_at_the_end - type: boolean - required: false - default: false - label: - en_US: Gather all links at the end - zh_Hans: 将所有链接集中到最后 - pt_BR: Coletar todos os links ao final - human_description: - en_US: A "Buttons & Links" section will be created at the end. This helps the downstream LLMs or web agents navigating the page or take further actions. - zh_Hans: 最后会创建一个“按钮和链接”部分。这可以帮助下游 LLM 或 Web 代理浏览页面或采取进一步的行动。 - pt_BR: A "Buttons & Links" section will be created at the end. This helps the downstream LLMs or web agents navigating the page or take further actions. - llm_description: Gather all links at the end - form: form - - name: gather_all_images_at_the_end - type: boolean - required: false - default: false - label: - en_US: Gather all images at the end - zh_Hans: 将所有图片集中到最后 - pt_BR: Coletar todas as imagens ao final - human_description: - en_US: An "Images" section will be created at the end. This gives the downstream LLMs an overview of all visuals on the page, which may improve reasoning. - zh_Hans: 最后会创建一个“图像”部分。这可以让下游的 LLM 概览页面上的所有视觉效果，从而提高推理能力。 - pt_BR: An "Images" section will be created at the end. This gives the downstream LLMs an overview of all visuals on the page, which may improve reasoning. - llm_description: Gather all images at the end - form: form - - name: proxy_server - type: string - required: false - label: - en_US: Proxy server - zh_Hans: 代理服务器 - pt_BR: Servidor de proxy - human_description: - en_US: Use proxy to access URLs - zh_Hans: 利用代理访问 URL - pt_BR: Use proxy to access URLs - llm_description: Use proxy to access URLs - form: form - - name: no_cache - type: boolean - required: false - default: false - label: - en_US: Bypass the Cache - zh_Hans: 绕过缓存 - pt_BR: Ignorar o cache - human_description: - en_US: Bypass the Cache - zh_Hans: 是否绕过缓存 - pt_BR: Ignorar o cache - llm_description: bypass the cache - form: form - - name: summary - type: boolean - required: false - default: false - label: - en_US: Enable summary - zh_Hans: 是否启用摘要 - pt_BR: Habilitar resumo - human_description: - en_US: Enable summary for the output - zh_Hans: 为输出启用摘要 - pt_BR: Habilitar resumo para a saída - llm_description: enable summary - form: form - - name: max_retries - type: number - required: false - default: 3 - label: - en_US: Retry - zh_Hans: 重试 - pt_BR: Repetir - human_description: - en_US: Number of times to retry the request if it fails - zh_Hans: 请求失败时重试的次数 - pt_BR: Número de vezes para repetir a solicitação se falhar - llm_description: Number of times to retry the request if it fails - form: form diff --git a/api/core/tools/provider/builtin/jina/tools/jina_search.py b/api/core/tools/provider/builtin/jina/tools/jina_search.py deleted file mode 100644 index 30af6de7831e59..00000000000000 --- a/api/core/tools/provider/builtin/jina/tools/jina_search.py +++ /dev/null @@ -1,46 +0,0 @@ -from typing import Any, Union - -from yarl import URL - -from core.helper import ssrf_proxy -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class JinaSearchTool(BuiltinTool): - _jina_search_endpoint = "https://s.jina.ai/" - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - query = tool_parameters["query"] - - headers = {"Accept": "application/json"} - - if "api_key" in self.runtime.credentials and self.runtime.credentials.get("api_key"): - headers["Authorization"] = "Bearer " + self.runtime.credentials.get("api_key") - - if tool_parameters.get("image_caption", False): - headers["X-With-Generated-Alt"] = "true" - - if tool_parameters.get("gather_all_links_at_the_end", False): - headers["X-With-Links-Summary"] = "true" - - if tool_parameters.get("gather_all_images_at_the_end", False): - headers["X-With-Images-Summary"] = "true" - - proxy_server = tool_parameters.get("proxy_server") - if proxy_server is not None and proxy_server != "": - headers["X-Proxy-Url"] = proxy_server - - if tool_parameters.get("no_cache", False): - headers["X-No-Cache"] = "true" - - max_retries = tool_parameters.get("max_retries", 3) - response = ssrf_proxy.get( - str(URL(self._jina_search_endpoint + query)), headers=headers, timeout=(10, 60), max_retries=max_retries - ) - - return self.create_text_message(response.text) diff --git a/api/core/tools/provider/builtin/jina/tools/jina_search.yaml b/api/core/tools/provider/builtin/jina/tools/jina_search.yaml deleted file mode 100644 index 2bc70e1be1934d..00000000000000 --- a/api/core/tools/provider/builtin/jina/tools/jina_search.yaml +++ /dev/null @@ -1,107 +0,0 @@ -identity: - name: jina_search - author: Dify - label: - en_US: JinaSearch - zh_Hans: JinaSearch - pt_BR: JinaSearch -description: - human: - en_US: Search on the web and get the top 5 results. Useful for grounding using information from the web. - zh_Hans: 在网络上搜索返回前 5 个结果。 - llm: A tool for searching results on the web for grounding. Input should be a simple question. -parameters: - - name: query - type: string - required: true - label: - en_US: Question (Query) - zh_Hans: 信息查询 - human_description: - en_US: used to find information on the web - zh_Hans: 在网络上搜索信息 - llm_description: simple question to ask on the web - form: llm - - name: image_caption - type: boolean - required: false - default: false - label: - en_US: Image caption - zh_Hans: 图片说明 - pt_BR: Legenda da imagem - human_description: - en_US: "Captions all images at the specified URL, adding 'Image [idx]: [caption]' as an alt tag for those without one. This allows downstream LLMs to interact with the images in activities such as reasoning and summarizing." - zh_Hans: "为指定 URL 上的所有图像添加标题，为没有标题的图像添加“Image [idx]: [caption]”作为 alt 标签。这允许下游 LLM 在推理和总结等活动中与图像进行交互。" - pt_BR: "Captions all images at the specified URL, adding 'Image [idx]: [caption]' as an alt tag for those without one. This allows downstream LLMs to interact with the images in activities such as reasoning and summarizing." - llm_description: Captions all images at the specified URL - form: form - - name: gather_all_links_at_the_end - type: boolean - required: false - default: false - label: - en_US: Gather all links at the end - zh_Hans: 将所有链接集中到最后 - pt_BR: Coletar todos os links ao final - human_description: - en_US: A "Buttons & Links" section will be created at the end. This helps the downstream LLMs or web agents navigating the page or take further actions. - zh_Hans: 最后会创建一个“按钮和链接”部分。这可以帮助下游 LLM 或 Web 代理浏览页面或采取进一步的行动。 - pt_BR: A "Buttons & Links" section will be created at the end. This helps the downstream LLMs or web agents navigating the page or take further actions. - llm_description: Gather all links at the end - form: form - - name: gather_all_images_at_the_end - type: boolean - required: false - default: false - label: - en_US: Gather all images at the end - zh_Hans: 将所有图片集中到最后 - pt_BR: Coletar todas as imagens ao final - human_description: - en_US: An "Images" section will be created at the end. This gives the downstream LLMs an overview of all visuals on the page, which may improve reasoning. - zh_Hans: 最后会创建一个“图像”部分。这可以让下游的 LLM 概览页面上的所有视觉效果，从而提高推理能力。 - pt_BR: An "Images" section will be created at the end. This gives the downstream LLMs an overview of all visuals on the page, which may improve reasoning. - llm_description: Gather all images at the end - form: form - - name: proxy_server - type: string - required: false - label: - en_US: Proxy server - zh_Hans: 代理服务器 - pt_BR: Servidor de proxy - human_description: - en_US: Use proxy to access URLs - zh_Hans: 利用代理访问 URL - pt_BR: Use proxy to access URLs - llm_description: Use proxy to access URLs - form: form - - name: no_cache - type: boolean - required: false - default: false - label: - en_US: Bypass the Cache - zh_Hans: 绕过缓存 - pt_BR: Ignorar o cache - human_description: - en_US: Bypass the Cache - zh_Hans: 是否绕过缓存 - pt_BR: Ignorar o cache - llm_description: bypass the cache - form: form - - name: max_retries - type: number - required: false - default: 3 - label: - en_US: Retry - zh_Hans: 重试 - pt_BR: Repetir - human_description: - en_US: Number of times to retry the request if it fails - zh_Hans: 请求失败时重试的次数 - pt_BR: Número de vezes para repetir a solicitação se falhar - llm_description: Number of times to retry the request if it fails - form: form diff --git a/api/core/tools/provider/builtin/jina/tools/jina_tokenizer.py b/api/core/tools/provider/builtin/jina/tools/jina_tokenizer.py deleted file mode 100644 index 06dabcc9c2a74e..00000000000000 --- a/api/core/tools/provider/builtin/jina/tools/jina_tokenizer.py +++ /dev/null @@ -1,39 +0,0 @@ -from typing import Any - -from core.helper import ssrf_proxy -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class JinaTokenizerTool(BuiltinTool): - _jina_tokenizer_endpoint = "https://tokenize.jina.ai/" - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> ToolInvokeMessage: - content = tool_parameters["content"] - body = {"content": content} - - headers = {"Content-Type": "application/json"} - - if "api_key" in self.runtime.credentials and self.runtime.credentials.get("api_key"): - headers["Authorization"] = "Bearer " + self.runtime.credentials.get("api_key") - - if tool_parameters.get("return_chunks", False): - body["return_chunks"] = True - - if tool_parameters.get("return_tokens", False): - body["return_tokens"] = True - - if tokenizer := tool_parameters.get("tokenizer"): - body["tokenizer"] = tokenizer - - response = ssrf_proxy.post( - self._jina_tokenizer_endpoint, - headers=headers, - json=body, - ) - - return self.create_json_message(response.json()) diff --git a/api/core/tools/provider/builtin/jina/tools/jina_tokenizer.yaml b/api/core/tools/provider/builtin/jina/tools/jina_tokenizer.yaml deleted file mode 100644 index 62a5c7e7bacd75..00000000000000 --- a/api/core/tools/provider/builtin/jina/tools/jina_tokenizer.yaml +++ /dev/null @@ -1,70 +0,0 @@ -identity: - name: jina_tokenizer - author: hjlarry - label: - en_US: JinaTokenizer -description: - human: - en_US: Free API to tokenize text and segment long text into chunks. - zh_Hans: 免费的API可以将文本tokenize，也可以将长文本分割成多个部分。 - llm: Free API to tokenize text and segment long text into chunks. -parameters: - - name: content - type: string - required: true - label: - en_US: Content - zh_Hans: 内容 - llm_description: the content which need to tokenize or segment - form: llm - - name: return_tokens - type: boolean - required: false - label: - en_US: Return the tokens - zh_Hans: 是否返回tokens - human_description: - en_US: Return the tokens and their corresponding ids in the response. - zh_Hans: 返回tokens及其对应的ids。 - form: form - - name: return_chunks - type: boolean - label: - en_US: Return the chunks - zh_Hans: 是否分块 - human_description: - en_US: Chunking the input into semantically meaningful segments while handling a wide variety of text types and edge cases based on common structural cues. - zh_Hans: 将输入分块为具有语义意义的片段，同时根据常见的结构线索处理各种文本类型和边缘情况。 - form: form - - name: tokenizer - type: select - options: - - value: cl100k_base - label: - en_US: cl100k_base - - value: o200k_base - label: - en_US: o200k_base - - value: p50k_base - label: - en_US: p50k_base - - value: r50k_base - label: - en_US: r50k_base - - value: p50k_edit - label: - en_US: p50k_edit - - value: gpt2 - label: - en_US: gpt2 - label: - en_US: Tokenizer - human_description: - en_US: | - · cl100k_base --- gpt-4, gpt-3.5-turbo, gpt-3.5 - · o200k_base --- gpt-4o, gpt-4o-mini - · p50k_base --- text-davinci-003, text-davinci-002 - · r50k_base --- text-davinci-001, text-curie-001 - · p50k_edit --- text-davinci-edit-001, code-davinci-edit-001 - · gpt2 --- gpt-2 - form: form diff --git a/api/core/tools/provider/builtin/json_process/_assets/icon.svg b/api/core/tools/provider/builtin/json_process/_assets/icon.svg deleted file mode 100644 index b123983836962a..00000000000000 --- a/api/core/tools/provider/builtin/json_process/_assets/icon.svg +++ /dev/null @@ -1,358 +0,0 @@ - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/json_process/json_process.py b/api/core/tools/provider/builtin/json_process/json_process.py deleted file mode 100644 index 10746210b5c652..00000000000000 --- a/api/core/tools/provider/builtin/json_process/json_process.py +++ /dev/null @@ -1,16 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.json_process.tools.parse import JSONParseTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class JsonExtractProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - JSONParseTool().invoke( - user_id="", - tool_parameters={"content": '{"name": "John", "age": 30, "city": "New York"}', "json_filter": "$.name"}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/json_process/json_process.yaml b/api/core/tools/provider/builtin/json_process/json_process.yaml deleted file mode 100644 index c7896bbea7a69f..00000000000000 --- a/api/core/tools/provider/builtin/json_process/json_process.yaml +++ /dev/null @@ -1,14 +0,0 @@ -identity: - author: Mingwei Zhang - name: json_process - label: - en_US: JSON Process - zh_Hans: JSON 处理 - pt_BR: JSON Process - description: - en_US: Tools for processing JSON content using jsonpath_ng - zh_Hans: 利用 jsonpath_ng 处理 JSON 内容的工具 - pt_BR: Tools for processing JSON content using jsonpath_ng - icon: icon.svg - tags: - - utilities diff --git a/api/core/tools/provider/builtin/json_process/tools/delete.py b/api/core/tools/provider/builtin/json_process/tools/delete.py deleted file mode 100644 index fcab3d71a93cf9..00000000000000 --- a/api/core/tools/provider/builtin/json_process/tools/delete.py +++ /dev/null @@ -1,61 +0,0 @@ -import json -from typing import Any, Union - -from jsonpath_ng import parse - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class JSONDeleteTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the JSON delete tool - """ - # Get content - content = tool_parameters.get("content", "") - if not content: - return self.create_text_message("Invalid parameter content") - - # Get query - query = tool_parameters.get("query", "") - if not query: - return self.create_text_message("Invalid parameter query") - - ensure_ascii = tool_parameters.get("ensure_ascii", True) - try: - result = self._delete(content, query, ensure_ascii) - return self.create_text_message(str(result)) - except Exception as e: - return self.create_text_message(f"Failed to delete JSON content: {str(e)}") - - def _delete(self, origin_json: str, query: str, ensure_ascii: bool) -> str: - try: - input_data = json.loads(origin_json) - expr = parse("$." + query.lstrip("$.")) # Ensure query path starts with $ - - matches = expr.find(input_data) - - if not matches: - return json.dumps(input_data, ensure_ascii=ensure_ascii) # No changes if no matches found - - for match in matches: - if isinstance(match.context.value, dict): - # Delete key from dictionary - del match.context.value[match.path.fields[-1]] - elif isinstance(match.context.value, list): - # Remove item from list - match.context.value.remove(match.value) - else: - # For other cases, we might want to set to None or remove the parent key - parent = match.context.parent - if parent: - del parent.value[match.path.fields[-1]] - - return json.dumps(input_data, ensure_ascii=ensure_ascii) - except Exception as e: - raise Exception(f"Delete operation failed: {str(e)}") diff --git a/api/core/tools/provider/builtin/json_process/tools/delete.yaml b/api/core/tools/provider/builtin/json_process/tools/delete.yaml deleted file mode 100644 index 4d390e40d17232..00000000000000 --- a/api/core/tools/provider/builtin/json_process/tools/delete.yaml +++ /dev/null @@ -1,52 +0,0 @@ -identity: - name: json_delete - author: Mingwei Zhang - label: - en_US: JSON Delete - zh_Hans: JSON 删除 - pt_BR: JSON Delete -description: - human: - en_US: A tool for deleting JSON content - zh_Hans: 一个删除 JSON 内容的工具 - pt_BR: A tool for deleting JSON content - llm: A tool for deleting JSON content -parameters: - - name: content - type: string - required: true - label: - en_US: JSON content - zh_Hans: JSON 内容 - pt_BR: JSON content - human_description: - en_US: JSON content to be processed - zh_Hans: 待处理的 JSON 内容 - pt_BR: JSON content to be processed - llm_description: JSON content to be processed - form: llm - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 查询 - pt_BR: Query - human_description: - en_US: JSONPath query to locate the element to delete - zh_Hans: 用于定位要删除元素的 JSONPath 查询 - pt_BR: JSONPath query to locate the element to delete - llm_description: JSONPath query to locate the element to delete - form: llm - - name: ensure_ascii - type: boolean - default: true - label: - en_US: Ensure ASCII - zh_Hans: 确保 ASCII - pt_BR: Ensure ASCII - human_description: - en_US: Ensure the JSON output is ASCII encoded - zh_Hans: 确保输出的 JSON 是 ASCII 编码 - pt_BR: Ensure the JSON output is ASCII encoded - form: form diff --git a/api/core/tools/provider/builtin/json_process/tools/insert.py b/api/core/tools/provider/builtin/json_process/tools/insert.py deleted file mode 100644 index 793c74e5f9df51..00000000000000 --- a/api/core/tools/provider/builtin/json_process/tools/insert.py +++ /dev/null @@ -1,105 +0,0 @@ -import json -from typing import Any, Union - -from jsonpath_ng import parse - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class JSONParseTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - # get content - content = tool_parameters.get("content", "") - if not content: - return self.create_text_message("Invalid parameter content") - - # get query - query = tool_parameters.get("query", "") - if not query: - return self.create_text_message("Invalid parameter query") - - # get new value - new_value = tool_parameters.get("new_value", "") - if not new_value: - return self.create_text_message("Invalid parameter new_value") - - # get insert position - index = tool_parameters.get("index") - - # get create path - create_path = tool_parameters.get("create_path", False) - - # get value decode. - # if true, it will be decoded to an dict - value_decode = tool_parameters.get("value_decode", False) - - ensure_ascii = tool_parameters.get("ensure_ascii", True) - try: - result = self._insert(content, query, new_value, ensure_ascii, value_decode, index, create_path) - return self.create_text_message(str(result)) - except Exception: - return self.create_text_message("Failed to insert JSON content") - - def _insert( - self, origin_json, query, new_value, ensure_ascii: bool, value_decode: bool, index=None, create_path=False - ): - try: - input_data = json.loads(origin_json) - expr = parse(query) - if value_decode is True: - try: - new_value = json.loads(new_value) - except json.JSONDecodeError: - return "Cannot decode new value to json object" - - matches = expr.find(input_data) - - if not matches and create_path: - # create new path - path_parts = query.strip("$").strip(".").split(".") - current = input_data - for i, part in enumerate(path_parts): - if "[" in part and "]" in part: - # process array index - array_name, index = part.split("[") - index = int(index.rstrip("]")) - if array_name not in current: - current[array_name] = [] - while len(current[array_name]) <= index: - current[array_name].append({}) - current = current[array_name][index] - else: - if i == len(path_parts) - 1: - current[part] = new_value - elif part not in current: - current[part] = {} - current = current[part] - else: - for match in matches: - if isinstance(match.value, dict): - # insert new value into dict - if isinstance(new_value, dict): - match.value.update(new_value) - else: - raise ValueError("Cannot insert non-dict value into dict") - elif isinstance(match.value, list): - # insert new value into list - if index is None: - match.value.append(new_value) - else: - match.value.insert(int(index), new_value) - else: - # replace old value with new value - match.full_path.update(input_data, new_value) - - return json.dumps(input_data, ensure_ascii=ensure_ascii) - except Exception as e: - return str(e) diff --git a/api/core/tools/provider/builtin/json_process/tools/insert.yaml b/api/core/tools/provider/builtin/json_process/tools/insert.yaml deleted file mode 100644 index 21b51312dab6b3..00000000000000 --- a/api/core/tools/provider/builtin/json_process/tools/insert.yaml +++ /dev/null @@ -1,101 +0,0 @@ -identity: - name: json_insert - author: Mingwei Zhang - label: - en_US: JSON Insert - zh_Hans: JSON 插入 - pt_BR: JSON Insert -description: - human: - en_US: A tool for inserting JSON content - zh_Hans: 一个插入 JSON 内容的工具 - pt_BR: A tool for inserting JSON content - llm: A tool for inserting JSON content -parameters: - - name: content - type: string - required: true - label: - en_US: JSON content - zh_Hans: JSON 内容 - pt_BR: JSON content - human_description: - en_US: JSON content - zh_Hans: JSON 内容 - pt_BR: JSON content - llm_description: JSON content to be processed - form: llm - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 查询 - pt_BR: Query - human_description: - en_US: Object to insert - zh_Hans: 待插入的对象 - pt_BR: Object to insert - llm_description: JSONPath query to locate the element to insert - form: llm - - name: new_value - type: string - required: true - label: - en_US: New Value - zh_Hans: 新值 - pt_BR: New Value - human_description: - en_US: New Value - zh_Hans: 插入的新值 - pt_BR: New Value - llm_description: New Value to insert - form: llm - - name: value_decode - type: boolean - default: false - label: - en_US: Decode Value - zh_Hans: 解码值 - pt_BR: Decode Value - human_description: - en_US: Whether to decode the value to a JSON object - zh_Hans: 是否将值解码为 JSON 对象 - pt_BR: Whether to decode the value to a JSON object - form: form - - name: create_path - type: select - required: true - default: "False" - label: - en_US: Whether to create a path - zh_Hans: 是否创建路径 - pt_BR: Whether to create a path - human_description: - en_US: Whether to create a path when the path does not exist - zh_Hans: 查询路径不存在时是否创建路径 - pt_BR: Whether to create a path when the path does not exist - options: - - value: "True" - label: - en_US: "Yes" - zh_Hans: 是 - pt_BR: "Yes" - - value: "False" - label: - en_US: "No" - zh_Hans: 否 - pt_BR: "No" - form: form - - name: ensure_ascii - type: boolean - default: true - label: - en_US: Ensure ASCII - zh_Hans: 确保 ASCII - pt_BR: Ensure ASCII - human_description: - en_US: Ensure the JSON output is ASCII encoded - zh_Hans: 确保输出的 JSON 是 ASCII 编码 - pt_BR: Ensure the JSON output is ASCII encoded - form: form diff --git a/api/core/tools/provider/builtin/json_process/tools/parse.py b/api/core/tools/provider/builtin/json_process/tools/parse.py deleted file mode 100644 index 37cae401533190..00000000000000 --- a/api/core/tools/provider/builtin/json_process/tools/parse.py +++ /dev/null @@ -1,53 +0,0 @@ -import json -from typing import Any, Union - -from jsonpath_ng import parse - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class JSONParseTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - # get content - content = tool_parameters.get("content", "") - if not content: - return self.create_text_message("Invalid parameter content") - - # get json filter - json_filter = tool_parameters.get("json_filter", "") - if not json_filter: - return self.create_text_message("Invalid parameter json_filter") - - ensure_ascii = tool_parameters.get("ensure_ascii", True) - try: - result = self._extract(content, json_filter, ensure_ascii) - return self.create_text_message(str(result)) - except Exception: - return self.create_text_message("Failed to extract JSON content") - - # Extract data from JSON content - def _extract(self, content: str, json_filter: str, ensure_ascii: bool) -> str: - try: - input_data = json.loads(content) - expr = parse(json_filter) - result = [match.value for match in expr.find(input_data)] - - if len(result) == 1: - result = result[0] - - if isinstance(result, dict | list): - return json.dumps(result, ensure_ascii=ensure_ascii) - elif isinstance(result, str | int | float | bool) or result is None: - return str(result) - else: - return repr(result) - except Exception as e: - return str(e) diff --git a/api/core/tools/provider/builtin/json_process/tools/parse.yaml b/api/core/tools/provider/builtin/json_process/tools/parse.yaml deleted file mode 100644 index c35f4eac0775ad..00000000000000 --- a/api/core/tools/provider/builtin/json_process/tools/parse.yaml +++ /dev/null @@ -1,52 +0,0 @@ -identity: - name: parse - author: Mingwei Zhang - label: - en_US: JSON Parse - zh_Hans: JSON 解析 - pt_BR: JSON Parse -description: - human: - en_US: A tool for extracting JSON objects - zh_Hans: 一个解析JSON对象的工具 - pt_BR: A tool for extracting JSON objects - llm: A tool for extracting JSON objects -parameters: - - name: content - type: string - required: true - label: - en_US: JSON data - zh_Hans: JSON数据 - pt_BR: JSON data - human_description: - en_US: JSON data - zh_Hans: JSON数据 - pt_BR: JSON数据 - llm_description: JSON data to be processed - form: llm - - name: json_filter - type: string - required: true - label: - en_US: JSON filter - zh_Hans: JSON解析对象 - pt_BR: JSON filter - human_description: - en_US: JSON fields to be parsed - zh_Hans: 需要解析的 JSON 字段 - pt_BR: JSON fields to be parsed - llm_description: JSON fields to be parsed - form: llm - - name: ensure_ascii - type: boolean - default: true - label: - en_US: Ensure ASCII - zh_Hans: 确保 ASCII - pt_BR: Ensure ASCII - human_description: - en_US: Ensure the JSON output is ASCII encoded - zh_Hans: 确保输出的 JSON 是 ASCII 编码 - pt_BR: Ensure the JSON output is ASCII encoded - form: form diff --git a/api/core/tools/provider/builtin/json_process/tools/replace.py b/api/core/tools/provider/builtin/json_process/tools/replace.py deleted file mode 100644 index 383825c2d0b259..00000000000000 --- a/api/core/tools/provider/builtin/json_process/tools/replace.py +++ /dev/null @@ -1,129 +0,0 @@ -import json -from typing import Any, Union - -from jsonpath_ng import parse - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class JSONReplaceTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - # get content - content = tool_parameters.get("content", "") - if not content: - return self.create_text_message("Invalid parameter content") - - # get query - query = tool_parameters.get("query", "") - if not query: - return self.create_text_message("Invalid parameter query") - - # get replace value - replace_value = tool_parameters.get("replace_value", "") - if not replace_value: - return self.create_text_message("Invalid parameter replace_value") - - # get replace model - replace_model = tool_parameters.get("replace_model", "") - if not replace_model: - return self.create_text_message("Invalid parameter replace_model") - - # get value decode. - # if true, it will be decoded to an dict - value_decode = tool_parameters.get("value_decode", False) - - ensure_ascii = tool_parameters.get("ensure_ascii", True) - try: - if replace_model == "pattern": - # get replace pattern - replace_pattern = tool_parameters.get("replace_pattern", "") - if not replace_pattern: - return self.create_text_message("Invalid parameter replace_pattern") - result = self._replace_pattern( - content, query, replace_pattern, replace_value, ensure_ascii, value_decode - ) - elif replace_model == "key": - result = self._replace_key(content, query, replace_value, ensure_ascii) - elif replace_model == "value": - result = self._replace_value(content, query, replace_value, ensure_ascii, value_decode) - return self.create_text_message(str(result)) - except Exception: - return self.create_text_message("Failed to replace JSON content") - - # Replace pattern - def _replace_pattern( - self, content: str, query: str, replace_pattern: str, replace_value: str, ensure_ascii: bool, value_decode: bool - ) -> str: - try: - input_data = json.loads(content) - expr = parse(query) - - matches = expr.find(input_data) - - for match in matches: - new_value = match.value.replace(replace_pattern, replace_value) - if value_decode is True: - try: - new_value = json.loads(new_value) - except json.JSONDecodeError: - return "Cannot decode replace value to json object" - - match.full_path.update(input_data, new_value) - - return json.dumps(input_data, ensure_ascii=ensure_ascii) - except Exception as e: - return str(e) - - # Replace key - def _replace_key(self, content: str, query: str, replace_value: str, ensure_ascii: bool) -> str: - try: - input_data = json.loads(content) - expr = parse(query) - - matches = expr.find(input_data) - - for match in matches: - parent = match.context.value - if isinstance(parent, dict): - old_key = match.path.fields[0] - if old_key in parent: - value = parent.pop(old_key) - parent[replace_value] = value - elif isinstance(parent, list): - for item in parent: - if isinstance(item, dict) and old_key in item: - value = item.pop(old_key) - item[replace_value] = value - return json.dumps(input_data, ensure_ascii=ensure_ascii) - except Exception as e: - return str(e) - - # Replace value - def _replace_value( - self, content: str, query: str, replace_value: str, ensure_ascii: bool, value_decode: bool - ) -> str: - try: - input_data = json.loads(content) - expr = parse(query) - if value_decode is True: - try: - replace_value = json.loads(replace_value) - except json.JSONDecodeError: - return "Cannot decode replace value to json object" - - matches = expr.find(input_data) - - for match in matches: - match.full_path.update(input_data, replace_value) - - return json.dumps(input_data, ensure_ascii=ensure_ascii) - except Exception as e: - return str(e) diff --git a/api/core/tools/provider/builtin/json_process/tools/replace.yaml b/api/core/tools/provider/builtin/json_process/tools/replace.yaml deleted file mode 100644 index ae238b1fbcd05e..00000000000000 --- a/api/core/tools/provider/builtin/json_process/tools/replace.yaml +++ /dev/null @@ -1,119 +0,0 @@ -identity: - name: json_replace - author: Mingwei Zhang - label: - en_US: JSON Replace - zh_Hans: JSON 替换 - pt_BR: JSON Replace -description: - human: - en_US: A tool for replacing JSON content - zh_Hans: 一个替换 JSON 内容的工具 - pt_BR: A tool for replacing JSON content - llm: A tool for replacing JSON content -parameters: - - name: content - type: string - required: true - label: - en_US: JSON content - zh_Hans: JSON 内容 - pt_BR: JSON content - human_description: - en_US: JSON content - zh_Hans: JSON 内容 - pt_BR: JSON content - llm_description: JSON content to be processed - form: llm - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 查询 - pt_BR: Query - human_description: - en_US: Query - zh_Hans: 查询 - pt_BR: Query - llm_description: JSONPath query to locate the element to replace - form: llm - - name: replace_pattern - type: string - required: false - label: - en_US: String to be replaced - zh_Hans: 待替换字符串 - pt_BR: String to be replaced - human_description: - en_US: String to be replaced - zh_Hans: 待替换字符串 - pt_BR: String to be replaced - llm_description: String to be replaced - form: llm - - name: replace_value - type: string - required: true - label: - en_US: Replace Value - zh_Hans: 替换值 - pt_BR: Replace Value - human_description: - en_US: New Value - zh_Hans: 新值 - pt_BR: New Value - llm_description: New Value to replace - form: llm - - name: value_decode - type: boolean - default: false - label: - en_US: Decode Value - zh_Hans: 解码值 - pt_BR: Decode Value - human_description: - en_US: Whether to decode the value to a JSON object (Does not apply to replace key) - zh_Hans: 是否将值解码为 JSON 对象 (不适用于键替换) - pt_BR: Whether to decode the value to a JSON object (Does not apply to replace key) - form: form - - name: replace_model - type: select - required: true - default: pattern - label: - en_US: Replace Model - zh_Hans: 替换模式 - pt_BR: Replace Model - human_description: - en_US: Replace Model - zh_Hans: 替换模式 - pt_BR: Replace Model - options: - - value: key - label: - en_US: replace key - zh_Hans: 键替换 - pt_BR: replace key - - value: value - label: - en_US: replace value - zh_Hans: 值替换 - pt_BR: replace value - - value: pattern - label: - en_US: replace string - zh_Hans: 字符串替换 - pt_BR: replace string - form: form - - name: ensure_ascii - type: boolean - default: true - label: - en_US: Ensure ASCII - zh_Hans: 确保 ASCII - pt_BR: Ensure ASCII - human_description: - en_US: Ensure the JSON output is ASCII encoded - zh_Hans: 确保输出的 JSON 是 ASCII 编码 - pt_BR: Ensure the JSON output is ASCII encoded - form: form diff --git a/api/core/tools/provider/builtin/judge0ce/_assets/icon.svg b/api/core/tools/provider/builtin/judge0ce/_assets/icon.svg deleted file mode 100644 index 3e7e33da6e8b25..00000000000000 --- a/api/core/tools/provider/builtin/judge0ce/_assets/icon.svg +++ /dev/null @@ -1,21 +0,0 @@ - - - - - - - - - - diff --git a/api/core/tools/provider/builtin/judge0ce/judge0ce.py b/api/core/tools/provider/builtin/judge0ce/judge0ce.py deleted file mode 100644 index 50db74dd9ebced..00000000000000 --- a/api/core/tools/provider/builtin/judge0ce/judge0ce.py +++ /dev/null @@ -1,23 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.judge0ce.tools.executeCode import ExecuteCodeTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class Judge0CEProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - ExecuteCodeTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "source_code": "print('hello world')", - "language_id": 71, - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/judge0ce/judge0ce.yaml b/api/core/tools/provider/builtin/judge0ce/judge0ce.yaml deleted file mode 100644 index 9ff8aaac6debc6..00000000000000 --- a/api/core/tools/provider/builtin/judge0ce/judge0ce.yaml +++ /dev/null @@ -1,32 +0,0 @@ -identity: - author: Richards Tu - name: judge0ce - label: - en_US: Judge0 CE - zh_Hans: Judge0 CE - pt_BR: Judge0 CE - description: - en_US: Judge0 CE is an open-source code execution system. Support various languages, including C, C++, Java, Python, Ruby, etc. - zh_Hans: Judge0 CE 是一个开源的代码执行系统。支持多种语言，包括 C、C++、Java、Python、Ruby 等。 - pt_BR: Judge0 CE é um sistema de execução de código de código aberto. Suporta várias linguagens, incluindo C, C++, Java, Python, Ruby, etc. - icon: icon.svg - tags: - - utilities - - other -credentials_for_provider: - X-RapidAPI-Key: - type: secret-input - required: true - label: - en_US: RapidAPI Key - zh_Hans: RapidAPI Key - pt_BR: RapidAPI Key - help: - en_US: RapidAPI Key is required to access the Judge0 CE API. - zh_Hans: RapidAPI Key 是访问 Judge0 CE API 所必需的。 - pt_BR: RapidAPI Key é necessário para acessar a API do Judge0 CE. - placeholder: - en_US: Enter your RapidAPI Key - zh_Hans: 输入你的 RapidAPI Key - pt_BR: Insira sua RapidAPI Key - url: https://rapidapi.com/judge0-official/api/judge0-ce diff --git a/api/core/tools/provider/builtin/judge0ce/tools/executeCode.py b/api/core/tools/provider/builtin/judge0ce/tools/executeCode.py deleted file mode 100644 index b8d654ff639575..00000000000000 --- a/api/core/tools/provider/builtin/judge0ce/tools/executeCode.py +++ /dev/null @@ -1,61 +0,0 @@ -import json -from typing import Any, Union - -import requests -from httpx import post - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class ExecuteCodeTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - api_key = self.runtime.credentials["X-RapidAPI-Key"] - - url = "https://judge0-ce.p.rapidapi.com/submissions" - - querystring = {"base64_encoded": "false", "fields": "*"} - - headers = { - "Content-Type": "application/json", - "X-RapidAPI-Key": api_key, - "X-RapidAPI-Host": "judge0-ce.p.rapidapi.com", - } - - payload = { - "language_id": tool_parameters["language_id"], - "source_code": tool_parameters["source_code"], - "stdin": tool_parameters.get("stdin", ""), - "expected_output": tool_parameters.get("expected_output", ""), - "additional_files": tool_parameters.get("additional_files", ""), - } - - response = post(url, data=json.dumps(payload), headers=headers, params=querystring) - - if response.status_code != 201: - raise Exception(response.text) - - token = response.json()["token"] - - url = f"https://judge0-ce.p.rapidapi.com/submissions/{token}" - headers = {"X-RapidAPI-Key": api_key} - - response = requests.get(url, headers=headers) - if response.status_code == 200: - result = response.json() - return self.create_text_message( - text=f"stdout: {result.get('stdout', '')}\n" - f"stderr: {result.get('stderr', '')}\n" - f"compile_output: {result.get('compile_output', '')}\n" - f"message: {result.get('message', '')}\n" - f"status: {result['status']['description']}\n" - f"time: {result.get('time', '')} seconds\n" - f"memory: {result.get('memory', '')} bytes" - ) - else: - return self.create_text_message(text=f"Error retrieving submission details: {response.text}") diff --git a/api/core/tools/provider/builtin/judge0ce/tools/executeCode.yaml b/api/core/tools/provider/builtin/judge0ce/tools/executeCode.yaml deleted file mode 100644 index a8c0776f40185e..00000000000000 --- a/api/core/tools/provider/builtin/judge0ce/tools/executeCode.yaml +++ /dev/null @@ -1,67 +0,0 @@ -identity: - name: submitCodeExecutionTask - author: Richards Tu - label: - en_US: Submit Code Execution Task to Judge0 CE and get execution result. - zh_Hans: 提交代码执行任务到 Judge0 CE 并获取执行结果。 -description: - human: - en_US: A tool for executing code and getting the result. - zh_Hans: 一个用于执行代码并获取结果的工具。 - llm: This tool is used for executing code and getting the result. -parameters: - - name: source_code - type: string - required: true - label: - en_US: Source Code - zh_Hans: 源代码 - human_description: - en_US: The source code to be executed. - zh_Hans: 要执行的源代码。 - llm_description: The source code to be executed. - form: llm - - name: language_id - type: number - required: true - label: - en_US: Language ID - zh_Hans: 语言 ID - human_description: - en_US: The ID of the language in which the source code is written. - zh_Hans: 源代码所使用的语言的 ID。 - llm_description: The ID of the language in which the source code is written. For example, 50 for C++, 71 for Python, etc. - form: llm - - name: stdin - type: string - required: false - label: - en_US: Standard Input - zh_Hans: 标准输入 - human_description: - en_US: The standard input to be provided to the program. - zh_Hans: 提供给程序的标准输入。 - llm_description: The standard input to be provided to the program. Optional. - form: llm - - name: expected_output - type: string - required: false - label: - en_US: Expected Output - zh_Hans: 期望输出 - human_description: - en_US: The expected output of the program. Used for comparison in some scenarios. - zh_Hans: 程序的期望输出。在某些场景下用于比较。 - llm_description: The expected output of the program. Used for comparison in some scenarios. Optional. - form: llm - - name: additional_files - type: string - required: false - label: - en_US: Additional Files - zh_Hans: 附加文件 - human_description: - en_US: Base64 encoded additional files for the submission. - zh_Hans: 提交的 Base64 编码的附加文件。 - llm_description: Base64 encoded additional files for the submission. Optional. - form: llm diff --git a/api/core/tools/provider/builtin/maths/_assets/icon.svg b/api/core/tools/provider/builtin/maths/_assets/icon.svg deleted file mode 100644 index f94d1152113830..00000000000000 --- a/api/core/tools/provider/builtin/maths/_assets/icon.svg +++ /dev/null @@ -1,10 +0,0 @@ - - - - - - - - - - diff --git a/api/core/tools/provider/builtin/maths/maths.py b/api/core/tools/provider/builtin/maths/maths.py deleted file mode 100644 index d4b449ec87a18a..00000000000000 --- a/api/core/tools/provider/builtin/maths/maths.py +++ /dev/null @@ -1,18 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.maths.tools.eval_expression import EvaluateExpressionTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class MathsProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - EvaluateExpressionTool().invoke( - user_id="", - tool_parameters={ - "expression": "1+(2+3)*4", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/maths/maths.yaml b/api/core/tools/provider/builtin/maths/maths.yaml deleted file mode 100644 index 35c2380e29a701..00000000000000 --- a/api/core/tools/provider/builtin/maths/maths.yaml +++ /dev/null @@ -1,15 +0,0 @@ -identity: - author: Bowen Liang - name: maths - label: - en_US: Maths - zh_Hans: 数学工具 - pt_BR: Maths - description: - en_US: A tool for maths. - zh_Hans: 一个用于数学计算的工具。 - pt_BR: A tool for maths. - icon: icon.svg - tags: - - utilities - - productivity diff --git a/api/core/tools/provider/builtin/maths/tools/eval_expression.py b/api/core/tools/provider/builtin/maths/tools/eval_expression.py deleted file mode 100644 index 0c5b5e41cbe1e1..00000000000000 --- a/api/core/tools/provider/builtin/maths/tools/eval_expression.py +++ /dev/null @@ -1,30 +0,0 @@ -import logging -from typing import Any, Union - -import numexpr as ne - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class EvaluateExpressionTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - # get expression - expression = tool_parameters.get("expression", "").strip() - if not expression: - return self.create_text_message("Invalid expression") - - try: - result = ne.evaluate(expression) - result_str = str(result) - except Exception as e: - logging.exception(f"Error evaluating expression: {expression}") - return self.create_text_message(f"Invalid expression: {expression}, error: {str(e)}") - return self.create_text_message(f'The result of the expression "{expression}" is {result_str}') diff --git a/api/core/tools/provider/builtin/maths/tools/eval_expression.yaml b/api/core/tools/provider/builtin/maths/tools/eval_expression.yaml deleted file mode 100644 index c936a4293fbe72..00000000000000 --- a/api/core/tools/provider/builtin/maths/tools/eval_expression.yaml +++ /dev/null @@ -1,26 +0,0 @@ -identity: - name: eval_expression - author: Bowen Liang - label: - en_US: Evaluate Math Expression - zh_Hans: 计算数学表达式 - pt_BR: Evaluate Math Expression -description: - human: - en_US: A tool for evaluating an math expression, calculated locally with NumExpr. - zh_Hans: 一个用于计算数学表达式的工具，表达式将通过NumExpr本地执行。 - pt_BR: A tool for evaluating an math expression, calculated locally with NumExpr. - llm: A tool for evaluating an math expression. -parameters: - - name: expression - type: string - required: true - label: - en_US: Math Expression - zh_Hans: 数学计算表达式 - pt_BR: Math Expression - human_description: - en_US: Math Expression - zh_Hans: 数学计算表达式 - pt_BR: Math Expression - form: llm diff --git a/api/core/tools/provider/builtin/nominatim/_assets/icon.svg b/api/core/tools/provider/builtin/nominatim/_assets/icon.svg deleted file mode 100644 index db5a4eb868c5e8..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/_assets/icon.svg +++ /dev/null @@ -1,277 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 010110010011010110010011 - 010110010011010110010011 - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/nominatim/nominatim.py b/api/core/tools/provider/builtin/nominatim/nominatim.py deleted file mode 100644 index 5a24bed7507eb6..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/nominatim.py +++ /dev/null @@ -1,27 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.nominatim.tools.nominatim_search import NominatimSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class NominatimProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - result = ( - NominatimSearchTool() - .fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ) - .invoke( - user_id="", - tool_parameters={ - "query": "London", - "limit": 1, - }, - ) - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/nominatim/nominatim.yaml b/api/core/tools/provider/builtin/nominatim/nominatim.yaml deleted file mode 100644 index 7d014bd78c6a59..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/nominatim.yaml +++ /dev/null @@ -1,43 +0,0 @@ -identity: - author: Charles Zhou - name: nominatim - label: - en_US: Nominatim - zh_Hans: Nominatim - de_DE: Nominatim - ja_JP: Nominatim - description: - en_US: Nominatim is a search engine for OpenStreetMap data - zh_Hans: Nominatim是OpenStreetMap数据的搜索引擎 - de_DE: Nominatim ist eine Suchmaschine für OpenStreetMap-Daten - ja_JP: NominatimはOpenStreetMapデータの検索エンジンです - icon: icon.svg - tags: - - search - - utilities -credentials_for_provider: - base_url: - type: text-input - required: false - default: https://nominatim.openstreetmap.org - label: - en_US: Nominatim Base URL - zh_Hans: Nominatim 基础 URL - de_DE: Nominatim Basis-URL - ja_JP: Nominatim ベースURL - placeholder: - en_US: "Enter your Nominatim instance URL (default: - https://nominatim.openstreetmap.org)" - zh_Hans: 输入您的Nominatim实例URL（默认：https://nominatim.openstreetmap.org） - de_DE: "Geben Sie Ihre Nominatim-Instanz-URL ein (Standard: - https://nominatim.openstreetmap.org)" - ja_JP: NominatimインスタンスのURLを入力してください（デフォルト：https://nominatim.openstreetmap.org） - help: - en_US: The base URL for the Nominatim instance. Use the default for the public - service or enter your self-hosted instance URL. - zh_Hans: Nominatim实例的基础URL。使用默认值可访问公共服务，或输入您的自托管实例URL。 - de_DE: Die Basis-URL für die Nominatim-Instanz. Verwenden Sie den Standardwert - für den öffentlichen Dienst oder geben Sie die URL Ihrer selbst - gehosteten Instanz ein. - ja_JP: NominatimインスタンスのベースURL。公共サービスにはデフォルトを使用するか、自己ホスティングインスタンスのURLを入力してください。 - url: https://nominatim.org/ diff --git a/api/core/tools/provider/builtin/nominatim/tools/nominatim_lookup.py b/api/core/tools/provider/builtin/nominatim/tools/nominatim_lookup.py deleted file mode 100644 index ffa8ad0fcc02e0..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/tools/nominatim_lookup.py +++ /dev/null @@ -1,40 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class NominatimLookupTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - osm_ids = tool_parameters.get("osm_ids", "") - - if not osm_ids: - return self.create_text_message("Please provide OSM IDs") - - params = {"osm_ids": osm_ids, "format": "json", "addressdetails": 1} - - return self._make_request(user_id, "lookup", params) - - def _make_request(self, user_id: str, endpoint: str, params: dict) -> ToolInvokeMessage: - base_url = self.runtime.credentials.get("base_url", "https://nominatim.openstreetmap.org") - - try: - headers = {"User-Agent": "DifyNominatimTool/1.0"} - s = requests.session() - response = s.request(method="GET", headers=headers, url=f"{base_url}/{endpoint}", params=params) - response_data = response.json() - - if response.status_code == 200: - s.close() - return self.create_text_message( - self.summary(user_id=user_id, content=json.dumps(response_data, ensure_ascii=False)) - ) - else: - return self.create_text_message(f"Error: {response.status_code} - {response.text}") - except Exception as e: - return self.create_text_message(f"An error occurred: {str(e)}") diff --git a/api/core/tools/provider/builtin/nominatim/tools/nominatim_lookup.yaml b/api/core/tools/provider/builtin/nominatim/tools/nominatim_lookup.yaml deleted file mode 100644 index 508c4dcd88ff15..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/tools/nominatim_lookup.yaml +++ /dev/null @@ -1,31 +0,0 @@ -identity: - name: nominatim_lookup - author: Charles Zhou - label: - en_US: Nominatim OSM Lookup - zh_Hans: Nominatim OSM 对象查找 - de_DE: Nominatim OSM-Objektsuche - ja_JP: Nominatim OSM ルックアップ -description: - human: - en_US: Look up OSM objects using their IDs with Nominatim - zh_Hans: 使用Nominatim通过ID查找OSM对象 - de_DE: Suchen Sie OSM-Objekte anhand ihrer IDs mit Nominatim - ja_JP: Nominatimを使用してIDでOSMオブジェクトを検索 - llm: A tool for looking up OpenStreetMap objects using their IDs with Nominatim. -parameters: - - name: osm_ids - type: string - required: true - label: - en_US: OSM IDs - zh_Hans: OSM ID - de_DE: OSM-IDs - ja_JP: OSM ID - human_description: - en_US: Comma-separated list of OSM IDs to lookup (e.g., N123,W456,R789) - zh_Hans: 要查找的OSM ID的逗号分隔列表（例如：N123,W456,R789） - de_DE: Kommagetrennte Liste von OSM-IDs für die Suche (z.B. N123,W456,R789) - ja_JP: 検索するOSM IDのカンマ区切りリスト（例：N123,W456,R789） - llm_description: A comma-separated list of OSM IDs (prefixed with N, W, or R) for lookup. - form: llm diff --git a/api/core/tools/provider/builtin/nominatim/tools/nominatim_reverse.py b/api/core/tools/provider/builtin/nominatim/tools/nominatim_reverse.py deleted file mode 100644 index f46691e1a3ebb4..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/tools/nominatim_reverse.py +++ /dev/null @@ -1,41 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class NominatimReverseTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - lat = tool_parameters.get("lat") - lon = tool_parameters.get("lon") - - if lat is None or lon is None: - return self.create_text_message("Please provide both latitude and longitude") - - params = {"lat": lat, "lon": lon, "format": "json", "addressdetails": 1} - - return self._make_request(user_id, "reverse", params) - - def _make_request(self, user_id: str, endpoint: str, params: dict) -> ToolInvokeMessage: - base_url = self.runtime.credentials.get("base_url", "https://nominatim.openstreetmap.org") - - try: - headers = {"User-Agent": "DifyNominatimTool/1.0"} - s = requests.session() - response = s.request(method="GET", headers=headers, url=f"{base_url}/{endpoint}", params=params) - response_data = response.json() - - if response.status_code == 200: - s.close() - return self.create_text_message( - self.summary(user_id=user_id, content=json.dumps(response_data, ensure_ascii=False)) - ) - else: - return self.create_text_message(f"Error: {response.status_code} - {response.text}") - except Exception as e: - return self.create_text_message(f"An error occurred: {str(e)}") diff --git a/api/core/tools/provider/builtin/nominatim/tools/nominatim_reverse.yaml b/api/core/tools/provider/builtin/nominatim/tools/nominatim_reverse.yaml deleted file mode 100644 index f1a2dd09fbc5d5..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/tools/nominatim_reverse.yaml +++ /dev/null @@ -1,47 +0,0 @@ -identity: - name: nominatim_reverse - author: Charles Zhou - label: - en_US: Nominatim Reverse Geocoding - zh_Hans: Nominatim 反向地理编码 - de_DE: Nominatim Rückwärts-Geocodierung - ja_JP: Nominatim リバースジオコーディング -description: - human: - en_US: Convert coordinates to addresses using Nominatim - zh_Hans: 使用Nominatim将坐标转换为地址 - de_DE: Konvertieren Sie Koordinaten in Adressen mit Nominatim - ja_JP: Nominatimを使用して座標を住所に変換 - llm: A tool for reverse geocoding using Nominatim, which can convert latitude - and longitude coordinates to an address. -parameters: - - name: lat - type: number - required: true - label: - en_US: Latitude - zh_Hans: 纬度 - de_DE: Breitengrad - ja_JP: 緯度 - human_description: - en_US: Latitude coordinate for reverse geocoding - zh_Hans: 用于反向地理编码的纬度坐标 - de_DE: Breitengrad-Koordinate für die Rückwärts-Geocodierung - ja_JP: リバースジオコーディングの緯度座標 - llm_description: The latitude coordinate for reverse geocoding. - form: llm - - name: lon - type: number - required: true - label: - en_US: Longitude - zh_Hans: 经度 - de_DE: Längengrad - ja_JP: 経度 - human_description: - en_US: Longitude coordinate for reverse geocoding - zh_Hans: 用于反向地理编码的经度坐标 - de_DE: Längengrad-Koordinate für die Rückwärts-Geocodierung - ja_JP: リバースジオコーディングの経度座標 - llm_description: The longitude coordinate for reverse geocoding. - form: llm diff --git a/api/core/tools/provider/builtin/nominatim/tools/nominatim_search.py b/api/core/tools/provider/builtin/nominatim/tools/nominatim_search.py deleted file mode 100644 index 34851d86dcaa5f..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/tools/nominatim_search.py +++ /dev/null @@ -1,41 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class NominatimSearchTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - query = tool_parameters.get("query", "") - limit = tool_parameters.get("limit", 10) - - if not query: - return self.create_text_message("Please input a search query") - - params = {"q": query, "format": "json", "limit": limit, "addressdetails": 1} - - return self._make_request(user_id, "search", params) - - def _make_request(self, user_id: str, endpoint: str, params: dict) -> ToolInvokeMessage: - base_url = self.runtime.credentials.get("base_url", "https://nominatim.openstreetmap.org") - - try: - headers = {"User-Agent": "DifyNominatimTool/1.0"} - s = requests.session() - response = s.request(method="GET", headers=headers, url=f"{base_url}/{endpoint}", params=params) - response_data = response.json() - - if response.status_code == 200: - s.close() - return self.create_text_message( - self.summary(user_id=user_id, content=json.dumps(response_data, ensure_ascii=False)) - ) - else: - return self.create_text_message(f"Error: {response.status_code} - {response.text}") - except Exception as e: - return self.create_text_message(f"An error occurred: {str(e)}") diff --git a/api/core/tools/provider/builtin/nominatim/tools/nominatim_search.yaml b/api/core/tools/provider/builtin/nominatim/tools/nominatim_search.yaml deleted file mode 100644 index e0c53c046a2a41..00000000000000 --- a/api/core/tools/provider/builtin/nominatim/tools/nominatim_search.yaml +++ /dev/null @@ -1,51 +0,0 @@ -identity: - name: nominatim_search - author: Charles Zhou - label: - en_US: Nominatim Search - zh_Hans: Nominatim 搜索 - de_DE: Nominatim Suche - ja_JP: Nominatim 検索 -description: - human: - en_US: Search for locations using Nominatim - zh_Hans: 使用Nominatim搜索位置 - de_DE: Suche nach Orten mit Nominatim - ja_JP: Nominatimを使用して場所を検索 - llm: A tool for geocoding using Nominatim, which can search for locations based - on addresses or place names. -parameters: - - name: query - type: string - required: true - label: - en_US: Search Query - zh_Hans: 搜索查询 - de_DE: Suchanfrage - ja_JP: 検索クエリ - human_description: - en_US: Enter an address or place name to search for - zh_Hans: 输入要搜索的地址或地名 - de_DE: Geben Sie eine Adresse oder einen Ortsnamen für die Suche ein - ja_JP: 検索する住所または場所の名前を入力してください - llm_description: The search query for Nominatim, which can be an address or place name. - form: llm - - name: limit - type: number - default: 10 - min: 1 - max: 40 - required: false - label: - en_US: Result Limit - zh_Hans: 结果限制 - de_DE: Ergebnislimit - ja_JP: 結果の制限 - human_description: - en_US: "Maximum number of results to return (default: 10, max: 40)" - zh_Hans: 要返回的最大结果数（默认：10，最大：40） - de_DE: "Maximale Anzahl der zurückzugebenden Ergebnisse (Standard: 10, max: 40)" - ja_JP: 返す結果の最大数（デフォルト：10、最大：40） - llm_description: Limit the number of returned results. 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z*A?ZoZ;}yQZB|z6Q5bv3&O%G>nC>=%)=}_YY0%%_Hyg7{OaEqB>sw7(7pC29Y|NT3 zhI+PvNZsG7b$wkO+eM`2>z;dJ%j1{Q)Eg};00@TAvB>Ji|F^e0cr$pl?#ETT#Cq9P z`*P|T+Rq4#AtEqi)GEK2+)F^aUD)SeuZ;#DA=%K|$@esMB0^oz82S(Y{qNCK)lsQZ HvJU+pg(G@~ diff --git a/api/core/tools/provider/builtin/novitaai/_novita_tool_base.py b/api/core/tools/provider/builtin/novitaai/_novita_tool_base.py deleted file mode 100644 index 762e158459cc2a..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/_novita_tool_base.py +++ /dev/null @@ -1,69 +0,0 @@ -from novita_client import ( - Txt2ImgV3Embedding, - Txt2ImgV3HiresFix, - Txt2ImgV3LoRA, - Txt2ImgV3Refiner, - V3TaskImage, -) - - -class NovitaAiToolBase: - def _extract_loras(self, loras_str: str): - if not loras_str: - return [] - - loras_ori_list = lora_str.strip().split(";") - result_list = [] - for lora_str in loras_ori_list: - lora_info = lora_str.strip().split(",") - lora = Txt2ImgV3LoRA( - model_name=lora_info[0].strip(), - strength=float(lora_info[1]), - ) - result_list.append(lora) - - return result_list - - def _extract_embeddings(self, embeddings_str: str): - if not embeddings_str: - return [] - - embeddings_ori_list = embeddings_str.strip().split(";") - result_list = [] - for embedding_str in embeddings_ori_list: - embedding = Txt2ImgV3Embedding(model_name=embedding_str.strip()) - result_list.append(embedding) - - return result_list - - def _extract_hires_fix(self, hires_fix_str: str): - hires_fix_info = hires_fix_str.strip().split(",") - if "upscaler" in hires_fix_info: - hires_fix = Txt2ImgV3HiresFix( - target_width=int(hires_fix_info[0]), - target_height=int(hires_fix_info[1]), - strength=float(hires_fix_info[2]), - upscaler=hires_fix_info[3].strip(), - ) - else: - hires_fix = Txt2ImgV3HiresFix( - target_width=int(hires_fix_info[0]), - target_height=int(hires_fix_info[1]), - strength=float(hires_fix_info[2]), - ) - - return hires_fix - - def _extract_refiner(self, switch_at: str): - refiner = Txt2ImgV3Refiner(switch_at=float(switch_at)) - return refiner - - def _is_hit_nsfw_detection(self, image: V3TaskImage, confidence_threshold: float) -> bool: - """ - is hit nsfw - """ - if image.nsfw_detection_result is None: - return False - if image.nsfw_detection_result.valid and image.nsfw_detection_result.confidence >= confidence_threshold: - return True - return False diff --git a/api/core/tools/provider/builtin/novitaai/novitaai.py b/api/core/tools/provider/builtin/novitaai/novitaai.py deleted file mode 100644 index d5e32eff29373a..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/novitaai.py +++ /dev/null @@ -1,34 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.novitaai.tools.novitaai_txt2img import NovitaAiTxt2ImgTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class NovitaAIProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - result = ( - NovitaAiTxt2ImgTool() - .fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ) - .invoke( - user_id="", - tool_parameters={ - "model_name": "cinenautXLATRUE_cinenautV10_392434.safetensors", - "prompt": "a futuristic city with flying cars", - "negative_prompt": "", - "width": 128, - "height": 128, - "image_num": 1, - "guidance_scale": 7.5, - "seed": -1, - "steps": 1, - }, - ) - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/novitaai/novitaai.yaml b/api/core/tools/provider/builtin/novitaai/novitaai.yaml deleted file mode 100644 index 3eed8a889c1bd8..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/novitaai.yaml +++ /dev/null @@ -1,32 +0,0 @@ -identity: - author: Xiao Ley - name: novitaai - label: - en_US: Novita AI - zh_Hans: Novita AI - pt_BR: Novita AI - description: - en_US: Innovative AI for Image Generation - zh_Hans: 用于图像生成的创新人工智能。 - pt_BR: Innovative AI for Image Generation - icon: icon.ico - tags: - - image - - productivity -credentials_for_provider: - api_key: - type: secret-input - required: true - label: - en_US: API Key - zh_Hans: API 密钥 - pt_BR: Chave API - placeholder: - en_US: Please enter your Novita AI API key - zh_Hans: 请输入你的 Novita AI API 密钥 - pt_BR: Por favor, insira sua chave de API do Novita AI - help: - en_US: Get your Novita AI API key from Novita AI - zh_Hans: 从 Novita AI 获取您的 Novita AI API 密钥 - pt_BR: Obtenha sua chave de API do Novita AI na Novita AI - url: https://novita.ai diff --git a/api/core/tools/provider/builtin/novitaai/tools/novitaai_createtile.py b/api/core/tools/provider/builtin/novitaai/tools/novitaai_createtile.py deleted file mode 100644 index 0b4f2edff3607f..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/tools/novitaai_createtile.py +++ /dev/null @@ -1,54 +0,0 @@ -from base64 import b64decode -from copy import deepcopy -from typing import Any, Union - -from novita_client import ( - NovitaClient, -) - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.tool.builtin_tool import BuiltinTool - - -class NovitaAiCreateTileTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - if "api_key" not in self.runtime.credentials or not self.runtime.credentials.get("api_key"): - raise ToolProviderCredentialValidationError("Novita AI API Key is required.") - - api_key = self.runtime.credentials.get("api_key") - - client = NovitaClient(api_key=api_key) - param = self._process_parameters(tool_parameters) - client_result = client.create_tile(**param) - - results = [] - results.append( - self.create_blob_message( - blob=b64decode(client_result.image_file), - meta={"mime_type": f"image/{client_result.image_type}"}, - save_as=self.VariableKey.IMAGE.value, - ) - ) - - return results - - def _process_parameters(self, parameters: dict[str, Any]) -> dict[str, Any]: - """ - process parameters - """ - res_parameters = deepcopy(parameters) - - # delete none and empty - keys_to_delete = [k for k, v in res_parameters.items() if v is None or v == ""] - for k in keys_to_delete: - del res_parameters[k] - - return res_parameters diff --git a/api/core/tools/provider/builtin/novitaai/tools/novitaai_createtile.yaml b/api/core/tools/provider/builtin/novitaai/tools/novitaai_createtile.yaml deleted file mode 100644 index 8e5df5042937d3..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/tools/novitaai_createtile.yaml +++ /dev/null @@ -1,80 +0,0 @@ -identity: - name: novitaai_createtile - author: Xiao Ley - label: - en_US: Novita AI Create Tile - zh_Hans: Novita AI 创建平铺图案 -description: - human: - en_US: This feature produces images designed for seamless tiling, ideal for creating continuous patterns in fabrics, wallpapers, and various textures. - zh_Hans: 该功能生成设计用于无缝平铺的图像，非常适合用于制作连续图案的织物、壁纸和各种纹理。 - llm: A tool for create images designed for seamless tiling, ideal for creating continuous patterns in fabrics, wallpapers, and various textures. -parameters: - - name: prompt - type: string - required: true - label: - en_US: prompt - zh_Hans: 提示 - human_description: - en_US: Positive prompt word of the created tile, divided by `,`, Range [1, 512]. Only English input is allowed. - zh_Hans: 生成平铺图案的正向提示，用 `,` 分隔，范围 [1, 512]。仅允许输入英文。 - llm_description: Image prompt of Novita AI, you should describe the image you want to generate as a list of words as possible as detailed, divided by `,`, Range [1, 512]. Only English input is allowed. - form: llm - - name: negative_prompt - type: string - required: false - label: - en_US: negative prompt - zh_Hans: 负向提示 - human_description: - en_US: Negtive prompt word of the created tile, divided by `,`, Range [1, 512]. Only English input is allowed. - zh_Hans: 生成平铺图案的负向提示，用 `,` 分隔，范围 [1, 512]。仅允许输入英文。 - llm_description: Image negative prompt of Novita AI, divided by `,`, Range [1, 512]. Only English input is allowed. - form: llm - - name: width - type: number - default: 256 - min: 128 - max: 1024 - required: true - label: - en_US: width - zh_Hans: 宽 - human_description: - en_US: Image width, Range [128, 1024]. - zh_Hans: 图像宽度，范围 [128, 1024] - form: form - - name: height - type: number - default: 256 - min: 128 - max: 1024 - required: true - label: - en_US: height - zh_Hans: 高 - human_description: - en_US: Image height, Range [128, 1024]. - zh_Hans: 图像高度，范围 [128, 1024] - form: form - - name: response_image_type - type: select - default: jpeg - required: false - label: - en_US: response image type - zh_Hans: 响应图像类型 - human_description: - en_US: Response image type, png or jpeg - zh_Hans: 响应图像类型，png 或 jpeg - form: form - options: - - value: jpeg - label: - en_US: jpeg - zh_Hans: jpeg - - value: png - label: - en_US: png - zh_Hans: png diff --git a/api/core/tools/provider/builtin/novitaai/tools/novitaai_modelquery.py b/api/core/tools/provider/builtin/novitaai/tools/novitaai_modelquery.py deleted file mode 100644 index a200ee81231f00..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/tools/novitaai_modelquery.py +++ /dev/null @@ -1,148 +0,0 @@ -import json -from copy import deepcopy -from typing import Any, Union - -from pandas import DataFrame -from yarl import URL - -from core.helper import ssrf_proxy -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.tool.builtin_tool import BuiltinTool - - -class NovitaAiModelQueryTool(BuiltinTool): - _model_query_endpoint = "https://api.novita.ai/v3/model" - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - if "api_key" not in self.runtime.credentials or not self.runtime.credentials.get("api_key"): - raise ToolProviderCredentialValidationError("Novita AI API Key is required.") - - api_key = self.runtime.credentials.get("api_key") - headers = {"Content-Type": "application/json", "Authorization": "Bearer " + api_key} - params = self._process_parameters(tool_parameters) - result_type = params.get("result_type") - del params["result_type"] - - models_data = self._query_models( - models_data=[], - headers=headers, - params=params, - recursive=result_type not in {"first sd_name", "first name sd_name pair"}, - ) - - result_str = "" - if result_type == "first sd_name": - result_str = models_data[0]["sd_name_in_api"] if len(models_data) > 0 else "" - elif result_type == "first name sd_name pair": - result_str = ( - json.dumps({"name": models_data[0]["name"], "sd_name": models_data[0]["sd_name_in_api"]}) - if len(models_data) > 0 - else "" - ) - elif result_type == "sd_name array": - sd_name_array = [model["sd_name_in_api"] for model in models_data] if len(models_data) > 0 else [] - result_str = json.dumps(sd_name_array) - elif result_type == "name array": - name_array = [model["name"] for model in models_data] if len(models_data) > 0 else [] - result_str = json.dumps(name_array) - elif result_type == "name sd_name pair array": - name_sd_name_pair_array = ( - [{"name": model["name"], "sd_name": model["sd_name_in_api"]} for model in models_data] - if len(models_data) > 0 - else [] - ) - result_str = json.dumps(name_sd_name_pair_array) - elif result_type == "whole info array": - result_str = json.dumps(models_data) - else: - raise NotImplementedError - - return self.create_text_message(result_str) - - def _query_models( - self, - models_data: list, - headers: dict[str, Any], - params: dict[str, Any], - pagination_cursor: str = "", - recursive: bool = True, - ) -> list: - """ - query models - """ - inside_params = deepcopy(params) - - if pagination_cursor != "": - inside_params["pagination.cursor"] = pagination_cursor - - response = ssrf_proxy.get( - url=str(URL(self._model_query_endpoint)), headers=headers, params=params, timeout=(10, 60) - ) - - res_data = response.json() - - models_data.extend(res_data["models"]) - - res_data_len = len(res_data["models"]) - if res_data_len == 0 or res_data_len < int(params["pagination.limit"]) or recursive is False: - # deduplicate - df = DataFrame.from_dict(models_data) - df_unique = df.drop_duplicates(subset=["id"]) - models_data = df_unique.to_dict("records") - return models_data - - return self._query_models( - models_data=models_data, - headers=headers, - params=inside_params, - pagination_cursor=res_data["pagination"]["next_cursor"], - ) - - def _process_parameters(self, parameters: dict[str, Any]) -> dict[str, Any]: - """ - process parameters - """ - process_parameters = deepcopy(parameters) - res_parameters = {} - - # delete none or empty - keys_to_delete = [k for k, v in process_parameters.items() if v is None or v == ""] - for k in keys_to_delete: - del process_parameters[k] - - if "query" in process_parameters and process_parameters.get("query") != "unspecified": - res_parameters["filter.query"] = process_parameters["query"] - - if "visibility" in process_parameters and process_parameters.get("visibility") != "unspecified": - res_parameters["filter.visibility"] = process_parameters["visibility"] - - if "source" in process_parameters and process_parameters.get("source") != "unspecified": - res_parameters["filter.source"] = process_parameters["source"] - - if "type" in process_parameters and process_parameters.get("type") != "unspecified": - res_parameters["filter.types"] = process_parameters["type"] - - if "is_sdxl" in process_parameters: - if process_parameters["is_sdxl"] == "true": - res_parameters["filter.is_sdxl"] = True - elif process_parameters["is_sdxl"] == "false": - res_parameters["filter.is_sdxl"] = False - - res_parameters["result_type"] = process_parameters.get("result_type", "first sd_name") - - res_parameters["pagination.limit"] = ( - 1 - if res_parameters.get("result_type") == "first sd_name" - or res_parameters.get("result_type") == "first name sd_name pair" - else 100 - ) - - return res_parameters diff --git a/api/core/tools/provider/builtin/novitaai/tools/novitaai_modelquery.yaml b/api/core/tools/provider/builtin/novitaai/tools/novitaai_modelquery.yaml deleted file mode 100644 index a14795e45e0e4f..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/tools/novitaai_modelquery.yaml +++ /dev/null @@ -1,175 +0,0 @@ -identity: - name: novitaai_modelquery - author: Xiao Ley - label: - en_US: Novita AI Model Query - zh_Hans: Novita AI 模型查询 -description: - human: - en_US: Retrieve information on both public and private models. It allows users to access details such as model specifications, status, and usage guidelines, ensuring comprehensive insight into the available modeling resources. - zh_Hans: 检索公开和私有模型信息。它允许用户访问模型规范、状态和使用指南等详细信息，确保了解可用的建模资源。 - llm: A tool for retrieve information on both public and private Novita AI models. -parameters: - - name: query - type: string - required: false - label: - en_US: query - zh_Hans: 查询 - human_description: - en_US: Seaching the content of sd_name, name, tags. - zh_Hans: 搜索 sd_name、name、tags 中的内容 - llm_description: Enter the content to search - form: llm - - name: result_type - type: select - default: "first sd_name" - required: true - label: - en_US: result format - zh_Hans: 结果格式 - human_description: - en_US: The format of result - zh_Hans: 请求结果的格式 - form: form - options: - - value: "first sd_name" - label: - en_US: "first sd_name" - zh_Hans: "第一个 sd_name" - - value: "first name sd_name pair" - label: - en_US: "first name and sd_name pair: {name, sd_name}" - zh_Hans: "第一个 name sd_name 组合：{name, sd_name}" - - value: "sd_name array" - label: - en_US: "sd_name array: [sd_name]" - zh_Hans: "sd_name 数组：[sd_name]" - - value: "name array" - label: - en_US: "name array: [name]" - zh_Hans: "name 数组：[name]" - - value: "name sd_name pair array" - label: - en_US: "name and sd_name pair array: [{name, sd_name}]" - zh_Hans: "name sd_name 组合数组：[{name, sd_name}]" - - value: "whole info array" - label: - en_US: whole info array - zh_Hans: 完整信息数组 - - name: visibility - type: select - default: unspecified - required: false - label: - en_US: visibility - zh_Hans: 可见性 - human_description: - en_US: Whether the model is public or private - zh_Hans: 模型是否公开或私有 - form: form - options: - - value: unspecified - label: - en_US: Unspecified - zh_Hans: 未指定 - - value: public - label: - en_US: Public - zh_Hans: 公开 - - value: private - label: - en_US: Private - zh_Hans: 私有 - - name: source - type: select - default: unspecified - required: false - label: - en_US: source - zh_Hans: 来源 - human_description: - en_US: Source of the model - zh_Hans: 模型来源 - form: form - options: - - value: unspecified - label: - en_US: Unspecified - zh_Hans: 未指定 - - value: civitai - label: - en_US: Civitai - zh_Hans: Civitai - - value: training - label: - en_US: Training - zh_Hans: 训练 - - value: uploading - label: - en_US: Uploading - zh_Hans: 上传 - - name: type - type: select - default: unspecified - required: false - label: - en_US: type - zh_Hans: 类型 - human_description: - en_US: Specifies the type of models to include in the query. - zh_Hans: 指定要查询的模型类型 - form: form - options: - - value: unspecified - label: - en_US: Unspecified - zh_Hans: 未指定 - - value: checkpoint - label: - en_US: Checkpoint - zh_Hans: Checkpoint - - value: lora - label: - en_US: LoRA - zh_Hans: LoRA - - value: vae - label: - en_US: VAE - zh_Hans: VAE - - value: controlnet - label: - en_US: ControlNet - zh_Hans: ControlNet - - value: upscaler - label: - en_US: Upscaler - zh_Hans: Upscaler - - value: textualinversion - label: - en_US: Textual inversion - zh_Hans: Textual Inversion - - name: is_sdxl - type: select - default: unspecified - required: false - label: - en_US: is sdxl - zh_Hans: 是否是 SDXL - human_description: - en_US: Whether sdxl model or not. Setting this parameter to `true` includes only sdxl models in the query results, which are typically large-scale, high-performance models designed for extensive data processing tasks. Conversely, setting it to `false` excludes these models from the results. If left unspecified, the filter will not discriminate based on the sdxl classification, including all model types in the search results. - zh_Hans: 是否是 SDXL 模型。设置此参数为 `是`，只查询 SDXL 模型，并包含大规模，高性能的模型。相反，设置为 `否`，将排除这些模型。如果未指定，将不会根据 SDXL 分类进行区分，包括查询结果中的所有模型类型。 - form: form - options: - - value: unspecified - label: - en_US: Unspecified - zh_Hans: 未指定 - - value: "true" - label: - en_US: "True" - zh_Hans: 是 - - value: "false" - label: - en_US: "False" - zh_Hans: 否 diff --git a/api/core/tools/provider/builtin/novitaai/tools/novitaai_txt2img.py b/api/core/tools/provider/builtin/novitaai/tools/novitaai_txt2img.py deleted file mode 100644 index 9c61eab9f95784..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/tools/novitaai_txt2img.py +++ /dev/null @@ -1,90 +0,0 @@ -from base64 import b64decode -from copy import deepcopy -from typing import Any, Union - -from novita_client import ( - NovitaClient, -) - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.novitaai._novita_tool_base import NovitaAiToolBase -from core.tools.tool.builtin_tool import BuiltinTool - - -class NovitaAiTxt2ImgTool(BuiltinTool, NovitaAiToolBase): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - if "api_key" not in self.runtime.credentials or not self.runtime.credentials.get("api_key"): - raise ToolProviderCredentialValidationError("Novita AI API Key is required.") - - api_key = self.runtime.credentials.get("api_key") - - client = NovitaClient(api_key=api_key) - param = self._process_parameters(tool_parameters) - client_result = client.txt2img_v3(**param) - - results = [] - for image_encoded, image in zip(client_result.images_encoded, client_result.images): - if self._is_hit_nsfw_detection(image, 0.8): - results = self.create_text_message(text="NSFW detected!") - break - - results.append( - self.create_blob_message( - blob=b64decode(image_encoded), - meta={"mime_type": f"image/{image.image_type}"}, - save_as=self.VariableKey.IMAGE.value, - ) - ) - - return results - - def _process_parameters(self, parameters: dict[str, Any]) -> dict[str, Any]: - """ - process parameters - """ - res_parameters = deepcopy(parameters) - - # delete none and empty - keys_to_delete = [k for k, v in res_parameters.items() if v is None or v == ""] - for k in keys_to_delete: - del res_parameters[k] - - if "clip_skip" in res_parameters and res_parameters.get("clip_skip") == 0: - del res_parameters["clip_skip"] - - if "refiner_switch_at" in res_parameters and res_parameters.get("refiner_switch_at") == 0: - del res_parameters["refiner_switch_at"] - - if "enabled_enterprise_plan" in res_parameters: - res_parameters["enterprise_plan"] = {"enabled": res_parameters["enabled_enterprise_plan"]} - del res_parameters["enabled_enterprise_plan"] - - if "nsfw_detection_level" in res_parameters: - res_parameters["nsfw_detection_level"] = int(res_parameters["nsfw_detection_level"]) - - # process loras - if "loras" in res_parameters: - res_parameters["loras"] = self._extract_loras(res_parameters.get("loras")) - - # process embeddings - if "embeddings" in res_parameters: - res_parameters["embeddings"] = self._extract_embeddings(res_parameters.get("embeddings")) - - # process hires_fix - if "hires_fix" in res_parameters: - res_parameters["hires_fix"] = self._extract_hires_fix(res_parameters.get("hires_fix")) - - # process refiner - if "refiner_switch_at" in res_parameters: - res_parameters["refiner"] = self._extract_refiner(res_parameters.get("refiner_switch_at")) - del res_parameters["refiner_switch_at"] - - return res_parameters diff --git a/api/core/tools/provider/builtin/novitaai/tools/novitaai_txt2img.yaml b/api/core/tools/provider/builtin/novitaai/tools/novitaai_txt2img.yaml deleted file mode 100644 index d625a643f915b1..00000000000000 --- a/api/core/tools/provider/builtin/novitaai/tools/novitaai_txt2img.yaml +++ /dev/null @@ -1,341 +0,0 @@ -identity: - name: novitaai_txt2img - author: Xiao Ley - label: - en_US: Novita AI Text to Image - zh_Hans: Novita AI 文字转图像 -description: - human: - en_US: Generate images from text prompts using Stable Diffusion models - zh_Hans: 通过 Stable Diffusion 模型根据文字提示生成图像 - llm: A tool for generate images from English text prompts. -parameters: - - name: model_name - type: string - required: true - label: - en_US: model name - zh_Hans: 模块名字 - human_description: - en_US: Specify the name of the model checkpoint. You can use the "Novita AI Model Query" tool to query the corresponding "sd_name" value (type select "Checkpoint"). - zh_Hans: 指定 Model Checkpoint 名称。可通过“Novita AI 模型请求”工具查询对应的“sd_name”值（类型选择“Checkpoint”）。 - form: form - - name: prompt - type: string - required: true - label: - en_US: prompt - zh_Hans: 提示 - human_description: - en_US: Text input required to guide the image generation, divided by `,`, Range [1, 1024]. Only English input is allowed. - zh_Hans: 生成图像的正向提示，用 `,` 分隔，范围 [1, 1024]。仅允许输入英文。 - llm_description: Image prompt of Novita AI, you should describe the image you want to generate as a list of words as possible as detailed, divided by `,`, Range [1, 1024]. Only English input is allowed. - form: llm - - name: negative_prompt - type: string - required: false - label: - en_US: negative prompt - zh_Hans: 负向提示 - human_description: - en_US: Text input that will not guide the image generation, divided by `,`, Range [1, 1024]. Only English input is allowed. - zh_Hans: 生成图像的负向提示，用 `,` 分隔，范围 [1, 1024]。仅允许输入英文。 - llm_description: Image negative prompt of Novita AI, divided by `,`, Range [1, 1024]. Only English input is allowed. - form: llm - - name: width - type: number - default: 512 - min: 128 - max: 2048 - required: true - label: - en_US: width - zh_Hans: 宽 - human_description: - en_US: Image width, Range [128, 2048]. - zh_Hans: 图像宽度，范围 [128, 2048] - form: form - - name: height - type: number - default: 512 - min: 128 - max: 2048 - required: true - label: - en_US: height - zh_Hans: 高 - human_description: - en_US: Image height, Range [128, 2048]. - zh_Hans: 图像高度，范围 [128, 2048] - form: form - - name: image_num - type: number - default: 1 - min: 1 - max: 8 - required: true - label: - en_US: image num - zh_Hans: 图片数 - human_description: - en_US: Image num, Range [1, 8]. - zh_Hans: 图片数，范围 [1, 8] - form: form - - name: steps - type: number - default: 20 - min: 1 - max: 100 - required: true - label: - en_US: steps - zh_Hans: 步数 - human_description: - en_US: The number of denoising steps. More steps usually can produce higher quality images, but take more time to generate, Range [1, 100]. - zh_Hans: 生成步数。更多步数可能会产生更好的图像，但生成时间更长，范围 [1, 100] - form: form - - name: seed - type: number - default: -1 - required: true - label: - en_US: seed - zh_Hans: 种子 - human_description: - en_US: A seed is a number from which Stable Diffusion generates noise, which, makes generation deterministic. Using the same seed and set of parameters will produce identical image each time, minimum -1. - zh_Hans: 种子是 Stable Diffusion 生成噪声的数字，它使生成具有确定性。使用相同的种子和参数设置将生成每次生成相同的图像，最小值 -1。 - form: form - - name: clip_skip - type: number - min: 1 - max: 12 - required: false - label: - en_US: clip skip - zh_Hans: 层跳过数 - human_description: - en_US: This parameter indicates the number of layers to stop from the bottom during optimization, so clip_skip on 2 would mean, that in SD1.x model where the CLIP has 12 layers, you would stop at 10th layer, Range [1, 12], get reference at https://novita.ai/get-started/Misc.html#what-s-clip-skip. - zh_Hans: 此参数表示优化过程中从底部停止的层数，因此 clip_skip 的值为 2，表示在 SD1.x 模型中，CLIP 有 12 层，你将停止在 10 层，范围 [1, 12]，参考 https://novita.ai/get-started/Misc.html#what-s-clip-skip。 - form: form - - name: guidance_scale - type: number - default: "7.5" - min: 1.0 - max: 30.0 - required: true - label: - en_US: guidance scale - zh_Hans: 提示词遵守程度 - human_description: - en_US: This setting says how close the Stable Diffusion will listen to your prompt, higer guidance forces the model to better follow the prompt, but result in lower quality output.Range [1, 30]. - zh_Hans: 此设置表明 Stable Diffusion 如何听从您的提示，较高的 guidance_scale 会强制模型更好跟随提示，但结果会更低质量输出。范围 [1.0, 30.0]。 - form: form - - name: sampler_name - type: select - required: true - label: - en_US: sampler name - zh_Hans: 采样器名称 - human_description: - en_US: This parameter determines the denoising algorithm employed during the sampling phase of Stable Diffusion. Get reference at https://novita.ai/get-started/Misc.htmll#what-is-samplers. - zh_Hans: 此参数决定了在稳定扩散采样阶段使用的去噪算法。参考 https://novita.ai/get-started/Misc.htmll#what-is-samplers。 - form: form - options: - - value: "Euler a" - label: - en_US: Euler a - zh_Hans: Euler a - - value: "Euler" - label: - en_US: Euler - zh_Hans: Euler - - value: "LMS" - label: - en_US: LMS - zh_Hans: LMS - - value: "Heun" - label: - en_US: Heun - zh_Hans: Heun - - value: "DPM2" - label: - en_US: DPM2 - zh_Hans: DPM2 - - value: "DPM2 a" - label: - en_US: DPM2 a - zh_Hans: DPM2 a - - value: "DPM++ 2S a" - label: - en_US: DPM++ 2S a - zh_Hans: DPM++ 2S a - - value: "DPM++ 2M" - label: - en_US: DPM++ 2M - zh_Hans: DPM++ 2M - - value: "DPM++ SDE" - label: - en_US: DPM++ SDE - zh_Hans: DPM++ SDE - - value: "DPM fast" - label: - en_US: DPM fast - zh_Hans: DPM fast - - value: "DPM adaptive" - label: - en_US: DPM adaptive - zh_Hans: DPM adaptive - - value: "LMS Karras" - label: - en_US: LMS Karras - zh_Hans: LMS Karras - - value: "DPM2 Karras" - label: - en_US: DPM2 Karras - zh_Hans: DPM2 Karras - - value: "DPM2 a Karras" - label: - en_US: DPM2 a Karras - zh_Hans: DPM2 a Karras - - value: "DPM++ 2S a Karras" - label: - en_US: DPM++ 2S a Karras - zh_Hans: DPM++ 2S a Karras - - value: "DPM++ 2M Karras" - label: - en_US: DPM++ 2M Karras - zh_Hans: DPM++ 2M Karras - - value: "DPM++ SDE Karras" - label: - en_US: DPM++ SDE Karras - zh_Hans: DPM++ SDE Karras - - value: "DDIM" - label: - en_US: DDIM - zh_Hans: DDIM - - value: "PLMS" - label: - en_US: PLMS - zh_Hans: PLMS - - value: "UniPC" - label: - en_US: UniPC - zh_Hans: UniPC - - name: sd_vae - type: string - required: false - label: - en_US: sd vae - zh_Hans: sd vae - human_description: - en_US: VAE(Variational Autoencoder), get reference at https://novita.ai/get-started/Misc.html#what-s-variational-autoencoders-vae. You can use the "Novita AI Model Query" tool to query the corresponding "sd_name" value (type select "VAE"). - zh_Hans: VAE（变分自编码器），参考 https://novita.ai/get-started/Misc.html#what-s-variational-autoencoders-vae。可通过“Novita AI 模型请求”工具查询对应的“sd_name”值（类型选择“VAE”）。 - form: form - - name: loras - type: string - required: false - label: - en_US: loRAs - zh_Hans: loRAs - human_description: - en_US: LoRA models. Currenlty supports up to 5 LoRAs. You can use the "Novita AI Model Query" tool to query the corresponding "sd_name" value (type select "LoRA"). Input template is ",;,;...". Such as"Film Grain style_331903,0.5;DoggystylePOV_9600,0.5" - zh_Hans: LoRA 模型。目前仅支持 5 个 LoRA。可通过“Novita AI 模型请求”工具查询对应的“sd_name”值（类型选择“LoRA”）。输入模板：“,;,;...”，例如：“Film Grain style_331903,0.5;DoggystylePOV_9600,0.5” - form: form - - name: embeddings - type: string - required: false - label: - en_US: text embeddings - zh_Hans: 文本嵌入 - human_description: - en_US: Textual Inversion is a training method for personalizing models by learning new text embeddings from a few example images, currenlty supports up to 5 embeddings. You can use the "Novita AI Model Query" tool to query the corresponding "sd_name" value (type select "Text Inversion"). Input template is ";;...". Such as "EasyNegativeV2_75525;AS-YoungerV2" - zh_Hans: 文本反转是一种通过从一些示例图像中学习新的文本嵌入来个性化模型的训练方法，目前仅支持 5 个嵌入。可通过“Novita AI 模型请求”工具查询对应的“sd_name”值（类型选择“Text Inversion”）。输入模板：“;;...”，例如：“EasyNegativeV2_75525;AS-YoungerV2” - form: form - - name: hires_fix - type: string - required: false - label: - en_US: hires fix - zh_Hans: 高分辨率修复 - human_description: - en_US: Use high resolution image fix. Input template is ",,,". Such as "1024,1024,0.8", "1024,1024,0.8,RealESRGAN_x4plus_anime_6B" - zh_Hans: 使用高分辨率修复。输入模板 “,,,”。例如 “1024,1024,0.8”、“1024,1024,0.8,RealESRGAN_x4plus_anime_6B” - form: form - - name: refiner_switch_at - type: number - min: 0.0 - max: 1.0 - required: false - label: - en_US: refiner switch at - zh_Hans: 重采样参与时刻 - human_description: - en_US: This parameter in the context of a refiner allows you to set the extent to which the refiner alters the output of a model. When set to 0, the refiner has no effect; at 1, it's fully active. Intermediate values like 0.5 provide a balanced effect, where the refiner is moderately engaged, enhancing or adjusting the output without dominating the original model's characteristics. This setting is particularly useful for fine-tuning the output to achieve a desired balance between refinement and the original generative features, Range [0, 1.0]. Is not all models support refiners! - zh_Hans: 此参数允许您设置重采样更改模型输出的程度。当设置为0时，重采样不起作用；1时，它处于完全活动状态。像0.5这样的中间值提供了一种平衡效果，其中重采样适度参与，增强或调整输出，而不会主导原始模型的特性。此设置对于微调输出特别有用，范围 [0, 1.0]。不是所有模型都支持重采样！ - form: form - - name: response_image_type - type: select - default: jpeg - required: false - label: - en_US: response image type - zh_Hans: 响应图像类型 - human_description: - en_US: Response image type, png or jpeg - zh_Hans: 响应图像类型，png 或 jpeg - form: form - options: - - value: jpeg - label: - en_US: jpeg - zh_Hans: jpeg - - value: png - label: - en_US: png - zh_Hans: png - - name: enabled_enterprise_plan - type: boolean - default: false - required: false - label: - en_US: enterprise plan enabled - zh_Hans: 企业版计划启用 - human_description: - en_US: Enable enterprise plan - zh_Hans: 启用企业版计划 - form: form - - name: enable_nsfw_detection - type: boolean - default: false - required: false - label: - en_US: enable nsfw detection - zh_Hans: 启用 NSFW 检测 - human_description: - en_US: Enable nsfw detection - zh_Hans: 启用 NSFW 检测 - form: form - - name: nsfw_detection_level - type: select - default: "2" - required: false - label: - en_US: nsfw detection level - zh_Hans: NSFW 检测级别 - human_description: - en_US: Nsfw detection level, from low to high - zh_Hans: NSFW 检测级别，越高越严格 - form: form - options: - - value: "0" - label: - en_US: low - zh_Hans: 低 - - value: "1" - label: - en_US: middle - zh_Hans: 中 - - value: "2" - label: - en_US: high - zh_Hans: 高 diff --git a/api/core/tools/provider/builtin/onebot/_assets/icon.ico b/api/core/tools/provider/builtin/onebot/_assets/icon.ico deleted file mode 100644 index 1b07e965b9910b4b006bc112378a8ba0306895a8..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 38078 zcmeI52douE7soFaiWQKeqLElp5s8Xju@}S-kfNf5r-`46AYwryvBqdL8u_AVVuOeY zU@u4%6rWg8?4S@!C>AUziqc`e|8L)$Wp>$pckk}r`yR+4|F^Sqch8(TGdpwU%-N+- zXrzBtRR#TRUl@OXq0pvKD0C2%Rj3xo_h@9zp+5f_V+uvEnSO66bQXFGBZS9ft`Pu-NW>>~BvTEBM`s)PrGw}b`4-@+Op zEpabA;5AJcB@7fOYbznPEy}5jO7gCwj!pC%ef&yclJJADS|~TIQUR1jnZpERK$gh1 zsHCp)EGw=)%5Ni_Eld!86zZFhVZ6{!Xf15;?GRIkU6emWcvo01G&Dk{cZ9(LvaZ(- zdG^n8@QRXId2I#s{;^Pr@kPaCB4qqXpdENt8+ji z;1U6y_&SQyW14)IZ*4i~ezCBLYBcbN4zxk;&w+UQZK^cmJ!8(MelI12i05FS;OZ+) zclYlJ^U^tUZG#%`moHy#!0OcvVu{UskjtDLp?hr1irP7A)~qqV{q~#r@%}y(INwn3KMow zX4_Oe+~8GDI z&6+jye&ct*dAoM)%+W_5ZLYZD3iIr<&w4y7*cPl00&6sXP)U#o>7MmA>)NssW5|2& zy=Shu<{HzfQ>XQGYIWP9MGN!FE3f#nEL^zI9C5@E0sY%+?UD94@W2Dj@ZrPFyYIeh zmMvT6-(SWA>*Rp1B7y3?OLU*x_nB}1DVLlpSFSYErcLw4kG5^w)~QFUPxNT}GRLd0 zzB* zC!BDCH?~VQkH(D~=Z{bJnqo)F95Q5xnK^T&WmAqLbHV;XqBd}^QyQQ57$JA!`5!xW ztU2I-0}}UJSD(A@zPtJAE2>sQ)2B~2ty{NF#cTil_cxC|`l$K)@3OhdiNgr&AE+*o zr0e{4Qo65@yHG#<^piIyZoBQasq`hmP0N-o&6{t&De-FP>#x5yd+f1CYJS^nvyHjz zvdg?V+Vaft$o>H_Furc1l<)qobX$Rat6XW;tXZae_wJ@qqeiK9h5onRdTaCIi!b`J zEm*L?bnMtM6HjEqw)*tbPkp{QCg?1Iz07bM=y$(;lpZ4Fx}f>+!w-wvDd;u{utl*c zEn% zn0+4CCwJa?XVa%oA8(EO!3Q50Y<=c#)@WhEj$OQXvH9kkZ_K1glgte_+~BRh(zXT9 zLC#|lzN!(u`5W=j1}nwT$<1`i;wP-@d))OL+hN_su{5q+fdc^2;xtFM?;L zdGqEa%fWoW*p?%`EnckzzYRj^vvp1!Qf6X3%i6z`xpuqlwlf!Ac%fmuTD6KHGap*A zWQlqH`RC1vC!S~+%i`KSoR92-1`W#7HeIF~VOK`!pBTsq`PA5$C!Tnsq;a@IhYn`U zm@#?Qb-k+m_~Vb}#v5-mty;B8+y>aDtPgUeapHxp!)-tuD*n^VG-u8n&xaH4PjTnR z9e14P`^j8z0tU_yj(%%l8Lc)a%7 zYi6&#_Da+S_%~jE9k+5WG*MjK_Ya7zH5a!i2=Wqw~){ zKa)M?)b)F%_Y>?hP^EO{^)B`z{@u7|*yiKI$7k6Pi22}_TW(2Y7qw~A#`BfuAUDR{ z00I58Xa9hZiC7a|d+oJFbx#`%9z57AUAi<=d3oNjx^hKV)vF~=NZ zdiU;~+NOH><(JL&+izdA4X{OXh<8Efy@V0Mns9weIsg6l-#uTK?dNgFi!Qn-^`7gD z88Zy?HoWh=^Un3e8#!{MuQ$f>GHOjbhRs#!YAJdj}%ySk1_6U&xm&Pu9(#wf-) zY#IE=M;&!kNn3f(QM5j+Vba=hP7C1gOuxaQo6+fj0RxK4d)HleImMQqOsapz z4r1J}m+)s3n-aBO7AFDqx%lFXi`EBQEQk25C6Z%hoGeN5@d@_q*|Sc0+4Fehkw=oS zi@l~4{lEP-+f3={`s=T+vpziEJR@25=4z$Gp^85=HQ`5KY>ygqY+mEWjlKPt)P?BA zO6os}4RrF!CmZ(FG7>(w%=$n5^wT%#KV3th|B8%14?XlyItgp6>=_n?^VIpNYwc>-RSQ z@WT)H*4JsuaPGnO94=IB|7F)*clB%8X|6& z_Op79JMykZ7GGAaY%Jb-2*hGlWdD)+@U9#&2Wf~o8M`RT?jVo-$Fx3HdZ3A?AcK>W$5tla2- zN#jq5V+P#P*^2oqNMRxyuUSS)TliC=b7Z? zX5v-xw{5xQmPN;X;;*9So)khb0QVQrJ;*KokobMuSL!-44!!#7t17yFiSHMn*Sci2 zzcD}L^zJ+_b#xG{{)q*xc>L`_2OVU1X6lRhmd8H(?2}0Mv=P_mM9+&)Gr{Vg>Mi-vh$6O9AmYYN}{ubDBY9STFC9?Z{9yW^UO07kFmDitb>Rj zdEtc@yx5Vb^{(VBO00(&*YI1|y&GFbk|TZLhaWP(mg34u%romROmyAX@>*I$2mvEkUYyi?J&YgYr0 zFyAES#CWES6^>CH>#IuyU*D3$BR5a!U4)N>+z4OoA%`52N)HmyyN_|0Z=4)^?6KZ{ z7;Qp~k0sjqth3HCykC$chS~CsI${^I_n9-na3^6s{nH3;zS6lq1LEiT%hP^`AWBE< zhY>4iiFfH(S4Ul2N*?{b47z8%d$Hi_SuzF4{Y~jMLS~((7#TPq<}|1^gCyV8Ax%mGH?5g_Jd?4q>a#jrZ$9SC>5 zaR2@H`!Tonnxsc$AwHEji!#t(;@MO1^((m|$-PEt*2klT+zH#1^+74?PYLWl2gK8j z9zEKZi@BKgaIZ<4X0QG6#~;tjuj9+)Bpz0}sZdn^G>Utj(yY@m$ES-&B(YBBy`@sW zzsI`-?s}AYxYW6YGU@YK-bsk8R4|i8^S*+wS9DyA-0PLD5_ngsEW{YXJM;KWle{}D z*}cB*`eG(eo?J9$f%^b@=UcgaKQ8S)TtY=Kb`KCr(mieC-lH_nPUig?@u-u~C%#bj zaQIfLjrFm5vq$_Cw3j7x$bPK-J?aQA#yY+m%HCT}-*K=a#2xR`5BPL^eM+{(vJ-16_A;?&7@Jssp>y_KiNoSMV{YF^pW%1UxR!4g^X>)T7v)=Ve521@ua&tX zQ^bE~A(ifFB=_FhbQc{n$I6LEVnScU%n@IN4vFD)zemOI_{Mtl=;7_1V^fF|gG5=s8pu@x+-?=c%L+9OvvKVRNn~E4qfNP7UVwBHKIE%UonRRcQA==bOzos>oQwkcfxO4HT@g$6YrNS;a(<2_?e+4{ZJy*;Wdzm03t%*hqCi&S1i zAncr6=US`dVn>x5ZUb!7imVSBg5o6u_I)lkW-(pI{jT!EZNM6hb#mE!72;jrginEW zZD4Js^Efq?HJ@@rz*jL)*citn#v8`^fKNf^Wz}&p=9C`+{?85GtD(Pa=!E|sA9BEt zsdKO1#q?8&->od6Bl`!v1@`<`2^$)%l)&s;v3J6Ay*$;q@WDbyp|KFqw>{sGbX}LMwmvb(t(3o?fPII3%{V}C4{M1vLRwrYhE?yOO=UCcPW!xix7<5_5A+ zni~4uN6ED{*@ePQKAS?JtIwuT*v)6-Nio-6FQ(NtEs1WnX%%3TlFnzZ0&1n?*RF25 zR$}sZbJJeM$yLE~y@U6siJPwWvb;Z=yXl+P#{ecHbxD&ZSAJ3*Ht#qPv)-6 zZ{nuizUTHyH|_ReH|_R$_gM%$Bh|KGJv)BEdZzq>^~C#y=^6A3(6i|maFbd0uqkN^ d@SgEnrrxt(%V;;Qsb$oav^$0b#uk6f`9C{jz#jkr diff --git a/api/core/tools/provider/builtin/onebot/onebot.py b/api/core/tools/provider/builtin/onebot/onebot.py deleted file mode 100644 index b8e5ed24d6b43f..00000000000000 --- a/api/core/tools/provider/builtin/onebot/onebot.py +++ /dev/null @@ -1,10 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class OneBotProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - if not credentials.get("ob11_http_url"): - raise ToolProviderCredentialValidationError("OneBot HTTP URL is required.") diff --git a/api/core/tools/provider/builtin/onebot/onebot.yaml b/api/core/tools/provider/builtin/onebot/onebot.yaml deleted file mode 100644 index 1922adc4de4d56..00000000000000 --- a/api/core/tools/provider/builtin/onebot/onebot.yaml +++ /dev/null @@ -1,35 +0,0 @@ -identity: - author: RockChinQ - name: onebot - label: - en_US: OneBot v11 Protocol - zh_Hans: OneBot v11 协议 - description: - en_US: Unofficial OneBot v11 Protocol Tool - zh_Hans: 非官方 OneBot v11 协议工具 - icon: icon.ico -credentials_for_provider: - ob11_http_url: - type: text-input - required: true - label: - en_US: HTTP URL - zh_Hans: HTTP URL - description: - en_US: Forward HTTP URL of OneBot v11 - zh_Hans: OneBot v11 正向 HTTP URL - help: - en_US: Fill this with the HTTP URL of your OneBot server - zh_Hans: 请在你的 OneBot 协议端开启 正向 HTTP 并填写其 URL - access_token: - type: secret-input - required: false - label: - en_US: Access Token - zh_Hans: 访问令牌 - description: - en_US: Access Token for OneBot v11 Protocol - zh_Hans: OneBot 协议访问令牌 - help: - en_US: Fill this if you set a access token in your OneBot server - zh_Hans: 如果你在 OneBot 服务器中设置了 access token，请填写此项 diff --git a/api/core/tools/provider/builtin/onebot/tools/__init__.py b/api/core/tools/provider/builtin/onebot/tools/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/tools/provider/builtin/onebot/tools/send_group_msg.py b/api/core/tools/provider/builtin/onebot/tools/send_group_msg.py deleted file mode 100644 index 9c95bbc2ae8d2d..00000000000000 --- a/api/core/tools/provider/builtin/onebot/tools/send_group_msg.py +++ /dev/null @@ -1,39 +0,0 @@ -from typing import Any, Union - -import requests -from yarl import URL - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class SendGroupMsg(BuiltinTool): - """OneBot v11 Tool: Send Group Message""" - - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - # Get parameters - send_group_id = tool_parameters.get("group_id", "") - - message = tool_parameters.get("message", "") - if not message: - return self.create_json_message({"error": "Message is empty."}) - - auto_escape = tool_parameters.get("auto_escape", False) - - try: - url = URL(self.runtime.credentials["ob11_http_url"]) / "send_group_msg" - - resp = requests.post( - url, - json={"group_id": send_group_id, "message": message, "auto_escape": auto_escape}, - headers={"Authorization": "Bearer " + self.runtime.credentials["access_token"]}, - ) - - if resp.status_code != 200: - return self.create_json_message({"error": f"Failed to send group message: {resp.text}"}) - - return self.create_json_message({"response": resp.json()}) - except Exception as e: - return self.create_json_message({"error": f"Failed to send group message: {e}"}) diff --git a/api/core/tools/provider/builtin/onebot/tools/send_group_msg.yaml b/api/core/tools/provider/builtin/onebot/tools/send_group_msg.yaml deleted file mode 100644 index 64beaa85457a3a..00000000000000 --- a/api/core/tools/provider/builtin/onebot/tools/send_group_msg.yaml +++ /dev/null @@ -1,46 +0,0 @@ -identity: - name: send_group_msg - author: RockChinQ - label: - en_US: Send Group Message - zh_Hans: 发送群消息 -description: - human: - en_US: Send a message to a group - zh_Hans: 发送消息到群聊 - llm: A tool for sending a message segment to a group -parameters: - - name: group_id - type: number - required: true - label: - en_US: Target Group ID - zh_Hans: 目标群 ID - human_description: - en_US: The group ID of the target group - zh_Hans: 目标群的群 ID - llm_description: The group ID of the target group - form: llm - - name: message - type: string - required: true - label: - en_US: Message - zh_Hans: 消息 - human_description: - en_US: The message to send - zh_Hans: 要发送的消息。支持 CQ码（需要同时设置 auto_escape 为 true） - llm_description: The message to send - form: llm - - name: auto_escape - type: boolean - required: false - default: false - label: - en_US: Auto Escape - zh_Hans: 自动转义 - human_description: - en_US: If true, the message will be treated as a CQ code for parsing, otherwise it will be treated as plain text for direct sending. Since Dify currently does not support passing Object-format message chains, developers can send complex message components through CQ codes. - zh_Hans: 若为 true 则会把 message 视为 CQ 码解析，否则视为 纯文本 直接发送。由于 Dify 目前不支持传入 Object格式 的消息，故开发者可以通过 CQ 码来发送复杂消息组件。 - llm_description: If true, the message will be treated as a CQ code for parsing, otherwise it will be treated as plain text for direct sending. - form: form diff --git a/api/core/tools/provider/builtin/onebot/tools/send_private_msg.py b/api/core/tools/provider/builtin/onebot/tools/send_private_msg.py deleted file mode 100644 index 1174c7f07d002f..00000000000000 --- a/api/core/tools/provider/builtin/onebot/tools/send_private_msg.py +++ /dev/null @@ -1,39 +0,0 @@ -from typing import Any, Union - -import requests -from yarl import URL - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class SendPrivateMsg(BuiltinTool): - """OneBot v11 Tool: Send Private Message""" - - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - # Get parameters - send_user_id = tool_parameters.get("user_id", "") - - message = tool_parameters.get("message", "") - if not message: - return self.create_json_message({"error": "Message is empty."}) - - auto_escape = tool_parameters.get("auto_escape", False) - - try: - url = URL(self.runtime.credentials["ob11_http_url"]) / "send_private_msg" - - resp = requests.post( - url, - json={"user_id": send_user_id, "message": message, "auto_escape": auto_escape}, - headers={"Authorization": "Bearer " + self.runtime.credentials["access_token"]}, - ) - - if resp.status_code != 200: - return self.create_json_message({"error": f"Failed to send private message: {resp.text}"}) - - return self.create_json_message({"response": resp.json()}) - except Exception as e: - return self.create_json_message({"error": f"Failed to send private message: {e}"}) diff --git a/api/core/tools/provider/builtin/onebot/tools/send_private_msg.yaml b/api/core/tools/provider/builtin/onebot/tools/send_private_msg.yaml deleted file mode 100644 index 8200ce4a83f4e2..00000000000000 --- a/api/core/tools/provider/builtin/onebot/tools/send_private_msg.yaml +++ /dev/null @@ -1,46 +0,0 @@ -identity: - name: send_private_msg - author: RockChinQ - label: - en_US: Send Private Message - zh_Hans: 发送私聊消息 -description: - human: - en_US: Send a private message to a user - zh_Hans: 发送私聊消息给用户 - llm: A tool for sending a message segment to a user in private chat -parameters: - - name: user_id - type: number - required: true - label: - en_US: Target User ID - zh_Hans: 目标用户 ID - human_description: - en_US: The user ID of the target user - zh_Hans: 目标用户的用户 ID - llm_description: The user ID of the target user - form: llm - - name: message - type: string - required: true - label: - en_US: Message - zh_Hans: 消息 - human_description: - en_US: The message to send - zh_Hans: 要发送的消息。支持 CQ码（需要同时设置 auto_escape 为 true） - llm_description: The message to send - form: llm - - name: auto_escape - type: boolean - required: false - default: false - label: - en_US: Auto Escape - zh_Hans: 自动转义 - human_description: - en_US: If true, the message will be treated as a CQ code for parsing, otherwise it will be treated as plain text for direct sending. Since Dify currently does not support passing Object-format message chains, developers can send complex message components through CQ codes. - zh_Hans: 若为 true 则会把 message 视为 CQ 码解析，否则视为 纯文本 直接发送。由于 Dify 目前不支持传入 Object格式 的消息，故开发者可以通过 CQ 码来发送复杂消息组件。 - llm_description: If true, the message will be treated as a CQ code for parsing, otherwise it will be treated as plain text for direct sending. - form: form diff --git a/api/core/tools/provider/builtin/openweather/_assets/icon.svg b/api/core/tools/provider/builtin/openweather/_assets/icon.svg deleted file mode 100644 index f06cd87e64c9d3..00000000000000 --- a/api/core/tools/provider/builtin/openweather/_assets/icon.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/openweather/openweather.py b/api/core/tools/provider/builtin/openweather/openweather.py deleted file mode 100644 index 9e40249aba6b40..00000000000000 --- a/api/core/tools/provider/builtin/openweather/openweather.py +++ /dev/null @@ -1,29 +0,0 @@ -import requests - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -def query_weather(city="Beijing", units="metric", language="zh_cn", api_key=None): - url = "https://api.openweathermap.org/data/2.5/weather" - params = {"q": city, "appid": api_key, "units": units, "lang": language} - - return requests.get(url, params=params) - - -class OpenweatherProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - if "api_key" not in credentials or not credentials.get("api_key"): - raise ToolProviderCredentialValidationError("Open weather API key is required.") - apikey = credentials.get("api_key") - try: - response = query_weather(api_key=apikey) - if response.status_code == 200: - pass - else: - raise ToolProviderCredentialValidationError((response.json()).get("info")) - except Exception as e: - raise ToolProviderCredentialValidationError("Open weather API Key is invalid. {}".format(e)) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/openweather/openweather.yaml b/api/core/tools/provider/builtin/openweather/openweather.yaml deleted file mode 100644 index d4b66f87f908c6..00000000000000 --- a/api/core/tools/provider/builtin/openweather/openweather.yaml +++ /dev/null @@ -1,31 +0,0 @@ -identity: - author: Onelevenvy - name: openweather - label: - en_US: Open weather query - zh_Hans: Open Weather - pt_BR: Consulta de clima open weather - description: - en_US: Weather query toolkit based on Open Weather - zh_Hans: 基于open weather的天气查询工具包 - pt_BR: Kit de consulta de clima baseado no Open Weather - icon: icon.svg - tags: - - weather -credentials_for_provider: - api_key: - type: secret-input - required: true - label: - en_US: API Key - zh_Hans: API Key - pt_BR: Fogo a chave - placeholder: - en_US: Please enter your open weather API Key - zh_Hans: 请输入你的open weather API Key - pt_BR: Insira sua chave de API open weather - help: - en_US: Get your API Key from open weather - zh_Hans: 从open weather获取您的 API Key - pt_BR: Obtenha sua chave de API do open weather - url: https://openweathermap.org diff --git a/api/core/tools/provider/builtin/openweather/tools/weather.py b/api/core/tools/provider/builtin/openweather/tools/weather.py deleted file mode 100644 index ed4ec487fa984a..00000000000000 --- a/api/core/tools/provider/builtin/openweather/tools/weather.py +++ /dev/null @@ -1,52 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class OpenweatherTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - city = tool_parameters.get("city", "") - if not city: - return self.create_text_message("Please tell me your city") - if "api_key" not in self.runtime.credentials or not self.runtime.credentials.get("api_key"): - return self.create_text_message("OpenWeather API key is required.") - - units = tool_parameters.get("units", "metric") - lang = tool_parameters.get("lang", "zh_cn") - try: - # request URL - url = "https://api.openweathermap.org/data/2.5/weather" - - # request params - params = { - "q": city, - "appid": self.runtime.credentials.get("api_key"), - "units": units, - "lang": lang, - } - response = requests.get(url, params=params) - - if response.status_code == 200: - data = response.json() - return self.create_text_message( - self.summary(user_id=user_id, content=json.dumps(data, ensure_ascii=False)) - ) - else: - error_message = { - "error": f"failed:{response.status_code}", - "data": response.text, - } - # return error - return json.dumps(error_message) - - except Exception as e: - return self.create_text_message("Openweather API Key is invalid. {}".format(e)) diff --git a/api/core/tools/provider/builtin/openweather/tools/weather.yaml b/api/core/tools/provider/builtin/openweather/tools/weather.yaml deleted file mode 100644 index f2dae5c2df9c08..00000000000000 --- a/api/core/tools/provider/builtin/openweather/tools/weather.yaml +++ /dev/null @@ -1,80 +0,0 @@ -identity: - name: weather - author: Onelevenvy - label: - en_US: Open Weather Query - zh_Hans: 天气查询 - pt_BR: Previsão do tempo - icon: icon.svg -description: - human: - en_US: Weather forecast inquiry - zh_Hans: 天气查询 - pt_BR: Inquérito sobre previsão meteorológica - llm: A tool when you want to ask about the weather or weather-related question -parameters: - - name: city - type: string - required: true - label: - en_US: city - zh_Hans: 城市 - pt_BR: cidade - human_description: - en_US: Target city for weather forecast query - zh_Hans: 天气预报查询的目标城市 - pt_BR: Cidade de destino para consulta de previsão do tempo - llm_description: If you don't know you can extract the city name from the - question or you can reply：Please tell me your city. You have to extract - the Chinese city name from the question.If the input region is in Chinese - characters for China, it should be replaced with the corresponding English - name, such as '北京' for correct input is 'Beijing' - form: llm - - name: lang - type: select - required: true - human_description: - en_US: language - zh_Hans: 语言 - pt_BR: language - label: - en_US: language - zh_Hans: 语言 - pt_BR: language - form: form - options: - - value: zh_cn - label: - en_US: cn - zh_Hans: 中国 - pt_BR: cn - - value: en_us - label: - en_US: usa - zh_Hans: 美国 - pt_BR: usa - default: zh_cn - - name: units - type: select - required: true - human_description: - en_US: units for temperature - zh_Hans: 温度单位 - pt_BR: units for temperature - label: - en_US: units - zh_Hans: 单位 - pt_BR: units - form: form - options: - - value: metric - label: - en_US: metric - zh_Hans: ℃ - pt_BR: metric - - value: imperial - label: - en_US: imperial - zh_Hans: ℉ - pt_BR: imperial - default: metric diff --git a/api/core/tools/provider/builtin/perplexity/_assets/icon.svg b/api/core/tools/provider/builtin/perplexity/_assets/icon.svg deleted file mode 100644 index c2974c142fc622..00000000000000 --- a/api/core/tools/provider/builtin/perplexity/_assets/icon.svg +++ /dev/null @@ -1,3 +0,0 @@ - - - diff --git a/api/core/tools/provider/builtin/perplexity/perplexity.py b/api/core/tools/provider/builtin/perplexity/perplexity.py deleted file mode 100644 index 80518853fb4a4b..00000000000000 --- a/api/core/tools/provider/builtin/perplexity/perplexity.py +++ /dev/null @@ -1,38 +0,0 @@ -from typing import Any - -import requests - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.perplexity.tools.perplexity_search import PERPLEXITY_API_URL -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class PerplexityProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - headers = { - "Authorization": f"Bearer {credentials.get('perplexity_api_key')}", - "Content-Type": "application/json", - } - - payload = { - "model": "llama-3.1-sonar-small-128k-online", - "messages": [ - {"role": "system", "content": "You are a helpful assistant."}, - {"role": "user", "content": "Hello"}, - ], - "max_tokens": 5, - "temperature": 0.1, - "top_p": 0.9, - "stream": False, - } - - try: - response = requests.post(PERPLEXITY_API_URL, json=payload, headers=headers) - response.raise_for_status() - except requests.RequestException as e: - raise ToolProviderCredentialValidationError(f"Failed to validate Perplexity API key: {str(e)}") - - if response.status_code != 200: - raise ToolProviderCredentialValidationError( - f"Perplexity API key is invalid. Status code: {response.status_code}" - ) diff --git a/api/core/tools/provider/builtin/perplexity/perplexity.yaml b/api/core/tools/provider/builtin/perplexity/perplexity.yaml deleted file mode 100644 index c0b504f300c45a..00000000000000 --- a/api/core/tools/provider/builtin/perplexity/perplexity.yaml +++ /dev/null @@ -1,26 +0,0 @@ -identity: - author: Dify - name: perplexity - label: - en_US: Perplexity - zh_Hans: Perplexity - description: - en_US: Perplexity.AI - zh_Hans: Perplexity.AI - icon: icon.svg - tags: - - search -credentials_for_provider: - perplexity_api_key: - type: secret-input - required: true - label: - en_US: Perplexity API key - zh_Hans: Perplexity API key - placeholder: - en_US: Please input your Perplexity API key - zh_Hans: 请输入你的 Perplexity API key - help: - en_US: Get your Perplexity API key from Perplexity - zh_Hans: 从 Perplexity 获取您的 Perplexity API key - url: https://www.perplexity.ai/settings/api diff --git a/api/core/tools/provider/builtin/perplexity/tools/perplexity_search.py b/api/core/tools/provider/builtin/perplexity/tools/perplexity_search.py deleted file mode 100644 index 5ed4b9ca993483..00000000000000 --- a/api/core/tools/provider/builtin/perplexity/tools/perplexity_search.py +++ /dev/null @@ -1,67 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -PERPLEXITY_API_URL = "https://api.perplexity.ai/chat/completions" - - -class PerplexityAITool(BuiltinTool): - def _parse_response(self, response: dict) -> dict: - """Parse the response from Perplexity AI API""" - if "choices" in response and len(response["choices"]) > 0: - message = response["choices"][0]["message"] - return { - "content": message.get("content", ""), - "role": message.get("role", ""), - "citations": response.get("citations", []), - } - else: - return {"content": "Unable to get a valid response", "role": "assistant", "citations": []} - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - headers = { - "Authorization": f"Bearer {self.runtime.credentials['perplexity_api_key']}", - "Content-Type": "application/json", - } - - payload = { - "model": tool_parameters.get("model", "llama-3.1-sonar-small-128k-online"), - "messages": [ - {"role": "system", "content": "Be precise and concise."}, - {"role": "user", "content": tool_parameters["query"]}, - ], - "max_tokens": tool_parameters.get("max_tokens", 4096), - "temperature": tool_parameters.get("temperature", 0.7), - "top_p": tool_parameters.get("top_p", 1), - "top_k": tool_parameters.get("top_k", 5), - "presence_penalty": tool_parameters.get("presence_penalty", 0), - "frequency_penalty": tool_parameters.get("frequency_penalty", 1), - "stream": False, - } - - if "search_recency_filter" in tool_parameters: - payload["search_recency_filter"] = tool_parameters["search_recency_filter"] - if "return_citations" in tool_parameters: - payload["return_citations"] = tool_parameters["return_citations"] - if "search_domain_filter" in tool_parameters: - if isinstance(tool_parameters["search_domain_filter"], str): - payload["search_domain_filter"] = [tool_parameters["search_domain_filter"]] - elif isinstance(tool_parameters["search_domain_filter"], list): - payload["search_domain_filter"] = tool_parameters["search_domain_filter"] - - response = requests.post(url=PERPLEXITY_API_URL, json=payload, headers=headers) - response.raise_for_status() - valuable_res = self._parse_response(response.json()) - - return [ - self.create_json_message(valuable_res), - self.create_text_message(json.dumps(valuable_res, ensure_ascii=False, indent=2)), - ] diff --git a/api/core/tools/provider/builtin/perplexity/tools/perplexity_search.yaml b/api/core/tools/provider/builtin/perplexity/tools/perplexity_search.yaml deleted file mode 100644 index 02a645df335aaf..00000000000000 --- a/api/core/tools/provider/builtin/perplexity/tools/perplexity_search.yaml +++ /dev/null @@ -1,178 +0,0 @@ -identity: - name: perplexity - author: Dify - label: - en_US: Perplexity Search -description: - human: - en_US: Search information using Perplexity AI's language models. - llm: This tool is used to search information using Perplexity AI's language models. -parameters: - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 查询 - human_description: - en_US: The text query to be processed by the AI model. - zh_Hans: 要由 AI 模型处理的文本查询。 - form: llm - - name: model - type: select - required: false - label: - en_US: Model Name - zh_Hans: 模型名称 - human_description: - en_US: The Perplexity AI model to use for generating the response. - zh_Hans: 用于生成响应的 Perplexity AI 模型。 - form: form - default: "llama-3.1-sonar-small-128k-online" - options: - - value: llama-3.1-sonar-small-128k-online - label: - en_US: llama-3.1-sonar-small-128k-online - zh_Hans: llama-3.1-sonar-small-128k-online - - value: llama-3.1-sonar-large-128k-online - label: - en_US: llama-3.1-sonar-large-128k-online - zh_Hans: llama-3.1-sonar-large-128k-online - - value: llama-3.1-sonar-huge-128k-online - label: - en_US: llama-3.1-sonar-huge-128k-online - zh_Hans: llama-3.1-sonar-huge-128k-online - - name: max_tokens - type: number - required: false - label: - en_US: Max Tokens - zh_Hans: 最大令牌数 - pt_BR: Máximo de Tokens - human_description: - en_US: The maximum number of tokens to generate in the response. - zh_Hans: 在响应中生成的最大令牌数。 - pt_BR: O número máximo de tokens a serem gerados na resposta. - form: form - default: 4096 - min: 1 - max: 4096 - - name: temperature - type: number - required: false - label: - en_US: Temperature - zh_Hans: 温度 - pt_BR: Temperatura - human_description: - en_US: Controls randomness in the output. Lower values make the output more focused and deterministic. - zh_Hans: 控制输出的随机性。较低的值使输出更加集中和确定。 - form: form - default: 0.7 - min: 0 - max: 1 - - name: top_k - type: number - required: false - label: - en_US: Top K - zh_Hans: 取样数量 - human_description: - en_US: The number of top results to consider for response generation. - zh_Hans: 用于生成响应的顶部结果数量。 - form: form - default: 5 - min: 1 - max: 100 - - name: top_p - type: number - required: false - label: - en_US: Top P - zh_Hans: Top P - human_description: - en_US: Controls diversity via nucleus sampling. - zh_Hans: 通过核心采样控制多样性。 - form: form - default: 1 - min: 0.1 - max: 1 - step: 0.1 - - name: presence_penalty - type: number - required: false - label: - en_US: Presence Penalty - zh_Hans: 存在惩罚 - human_description: - en_US: Positive values penalize new tokens based on whether they appear in the text so far. - zh_Hans: 正值会根据新词元是否已经出现在文本中来对其进行惩罚。 - form: form - default: 0 - min: -1.0 - max: 1.0 - step: 0.1 - - name: frequency_penalty - type: number - required: false - label: - en_US: Frequency Penalty - zh_Hans: 频率惩罚 - human_description: - en_US: Positive values penalize new tokens based on their existing frequency in the text so far. - zh_Hans: 正值会根据新词元在文本中已经出现的频率来对其进行惩罚。 - form: form - default: 1 - min: 0.1 - max: 1.0 - step: 0.1 - - name: return_citations - type: boolean - required: false - label: - en_US: Return Citations - zh_Hans: 返回引用 - human_description: - en_US: Whether to return citations in the response. - zh_Hans: 是否在响应中返回引用。 - form: form - default: true - - name: search_domain_filter - type: string - required: false - label: - en_US: Search Domain Filter - zh_Hans: 搜索域过滤器 - human_description: - en_US: Domain to filter the search results. - zh_Hans: 用于过滤搜索结果的域名。 - form: form - default: "" - - name: search_recency_filter - type: select - required: false - label: - en_US: Search Recency Filter - zh_Hans: 搜索时间过滤器 - human_description: - en_US: Filter for search results based on recency. - zh_Hans: 基于时间筛选搜索结果。 - form: form - default: "month" - options: - - value: day - label: - en_US: Day - zh_Hans: 天 - - value: week - label: - en_US: Week - zh_Hans: 周 - - value: month - label: - en_US: Month - zh_Hans: 月 - - value: year - label: - en_US: Year - zh_Hans: 年 diff --git a/api/core/tools/provider/builtin/pubmed/_assets/icon.svg b/api/core/tools/provider/builtin/pubmed/_assets/icon.svg deleted file mode 100644 index 6d6ff593f0c999..00000000000000 --- a/api/core/tools/provider/builtin/pubmed/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/pubmed/pubmed.py b/api/core/tools/provider/builtin/pubmed/pubmed.py deleted file mode 100644 index ea3a477c30178d..00000000000000 --- a/api/core/tools/provider/builtin/pubmed/pubmed.py +++ /dev/null @@ -1,20 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.pubmed.tools.pubmed_search import PubMedSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class PubMedProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - PubMedSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "query": "John Doe", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/pubmed/pubmed.yaml b/api/core/tools/provider/builtin/pubmed/pubmed.yaml deleted file mode 100644 index 5f8303147c397b..00000000000000 --- a/api/core/tools/provider/builtin/pubmed/pubmed.yaml +++ /dev/null @@ -1,13 +0,0 @@ -identity: - author: Pink Banana - name: pubmed - label: - en_US: PubMed - zh_Hans: PubMed - description: - en_US: A search engine for biomedical literature. - zh_Hans: 一款生物医学文献搜索引擎。 - icon: icon.svg - tags: - - medical - - search diff --git a/api/core/tools/provider/builtin/pubmed/tools/pubmed_search.py b/api/core/tools/provider/builtin/pubmed/tools/pubmed_search.py deleted file mode 100644 index 3a4f374ea0b0bc..00000000000000 --- a/api/core/tools/provider/builtin/pubmed/tools/pubmed_search.py +++ /dev/null @@ -1,191 +0,0 @@ -import json -import time -import urllib.error -import urllib.parse -import urllib.request -from typing import Any - -from pydantic import BaseModel, Field - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class PubMedAPIWrapper(BaseModel): - """ - Wrapper around PubMed API. - - This wrapper will use the PubMed API to conduct searches and fetch - document summaries. By default, it will return the document summaries - of the top-k results of an input search. - - Parameters: - top_k_results: number of the top-scored document used for the PubMed tool - load_max_docs: a limit to the number of loaded documents - load_all_available_meta: - if True: the `metadata` of the loaded Documents gets all available meta info - (see https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESearch) - if False: the `metadata` gets only the most informative fields. - """ - - base_url_esearch: str = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?" - base_url_efetch: str = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?" - max_retry: int = 5 - sleep_time: float = 0.2 - - # Default values for the parameters - top_k_results: int = 3 - load_max_docs: int = 25 - ARXIV_MAX_QUERY_LENGTH: int = 300 - doc_content_chars_max: int = 2000 - load_all_available_meta: bool = False - email: str = "your_email@example.com" - - def run(self, query: str) -> str: - """ - Run PubMed search and get the article meta information. - See https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESearch - It uses only the most informative fields of article meta information. - """ - - try: - # Retrieve the top-k results for the query - docs = [ - f"Published: {result['pub_date']}\nTitle: {result['title']}\nSummary: {result['summary']}" - for result in self.load(query[: self.ARXIV_MAX_QUERY_LENGTH]) - ] - - # Join the results and limit the character count - return "\n\n".join(docs)[: self.doc_content_chars_max] if docs else "No good PubMed Result was found" - except Exception as ex: - return f"PubMed exception: {ex}" - - def load(self, query: str) -> list[dict]: - """ - Search PubMed for documents matching the query. - Return a list of dictionaries containing the document metadata. - """ - - url = ( - self.base_url_esearch - + "db=pubmed&term=" - + str({urllib.parse.quote(query)}) - + f"&retmode=json&retmax={self.top_k_results}&usehistory=y" - ) - result = urllib.request.urlopen(url) - text = result.read().decode("utf-8") - json_text = json.loads(text) - - articles = [] - webenv = json_text["esearchresult"]["webenv"] - for uid in json_text["esearchresult"]["idlist"]: - article = self.retrieve_article(uid, webenv) - articles.append(article) - - # Convert the list of articles to a JSON string - return articles - - def retrieve_article(self, uid: str, webenv: str) -> dict: - url = self.base_url_efetch + "db=pubmed&retmode=xml&id=" + uid + "&webenv=" + webenv - - retry = 0 - while True: - try: - result = urllib.request.urlopen(url) - break - except urllib.error.HTTPError as e: - if e.code == 429 and retry < self.max_retry: - # Too Many Requests error - # wait for an exponentially increasing amount of time - print(f"Too Many Requests, waiting for {self.sleep_time:.2f} seconds...") - time.sleep(self.sleep_time) - self.sleep_time *= 2 - retry += 1 - else: - raise e - - xml_text = result.read().decode("utf-8") - - # Get title - title = "" - if "" in xml_text and "" in xml_text: - start_tag = "" - end_tag = "" - title = xml_text[xml_text.index(start_tag) + len(start_tag) : xml_text.index(end_tag)] - - # Get abstract - abstract = "" - if "" in xml_text and "" in xml_text: - start_tag = "" - end_tag = "" - abstract = xml_text[xml_text.index(start_tag) + len(start_tag) : xml_text.index(end_tag)] - - # Get publication date - pub_date = "" - if "" in xml_text and "" in xml_text: - start_tag = "" - end_tag = "" - pub_date = xml_text[xml_text.index(start_tag) + len(start_tag) : xml_text.index(end_tag)] - - # Return article as dictionary - article = { - "uid": uid, - "title": title, - "summary": abstract, - "pub_date": pub_date, - } - return article - - -class PubmedQueryRun(BaseModel): - """Tool that searches the PubMed API.""" - - name: str = "PubMed" - description: str = ( - "A wrapper around PubMed.org " - "Useful for when you need to answer questions about Physics, Mathematics, " - "Computer Science, Quantitative Biology, Quantitative Finance, Statistics, " - "Electrical Engineering, and Economics " - "from scientific articles on PubMed.org. " - "Input should be a search query." - ) - api_wrapper: PubMedAPIWrapper = Field(default_factory=PubMedAPIWrapper) - - def _run( - self, - query: str, - ) -> str: - """Use the Arxiv tool.""" - return self.api_wrapper.run(query) - - -class PubMedInput(BaseModel): - query: str = Field(..., description="Search query.") - - -class PubMedSearchTool(BuiltinTool): - """ - Tool for performing a search using PubMed search engine. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: - """ - Invoke the PubMed search tool. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Any]): The parameters for the tool invocation. - - Returns: - ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation. - """ - query = tool_parameters.get("query", "") - - if not query: - return self.create_text_message("Please input query") - - tool = PubmedQueryRun(args_schema=PubMedInput) - - result = tool._run(query) - - return self.create_text_message(self.summary(user_id=user_id, content=result)) diff --git a/api/core/tools/provider/builtin/pubmed/tools/pubmed_search.yaml b/api/core/tools/provider/builtin/pubmed/tools/pubmed_search.yaml deleted file mode 100644 index 77ab809fbc3e05..00000000000000 --- a/api/core/tools/provider/builtin/pubmed/tools/pubmed_search.yaml +++ /dev/null @@ -1,23 +0,0 @@ -identity: - name: pubmed_search - author: Pink Banana - label: - en_US: PubMed Search - zh_Hans: PubMed 搜索 -description: - human: - en_US: PubMed® comprises more than 35 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full text content from PubMed Central and publisher web sites. - zh_Hans: PubMed® 包含来自 MEDLINE、生命科学期刊和在线书籍的超过 3500 万篇生物医学文献引用。引用可能包括来自 PubMed Central 和出版商网站的全文内容链接。 - llm: Perform searches on PubMed and get results. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - human_description: - en_US: The search query. - zh_Hans: 搜索查询语句。 - llm_description: Key words for searching - form: llm diff --git a/api/core/tools/provider/builtin/regex/_assets/icon.svg b/api/core/tools/provider/builtin/regex/_assets/icon.svg deleted file mode 100644 index 0231a2b4aa9da2..00000000000000 --- a/api/core/tools/provider/builtin/regex/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/regex/regex.py b/api/core/tools/provider/builtin/regex/regex.py deleted file mode 100644 index c498105979f13e..00000000000000 --- a/api/core/tools/provider/builtin/regex/regex.py +++ /dev/null @@ -1,19 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.regex.tools.regex_extract import RegexExpressionTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class RegexProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - RegexExpressionTool().invoke( - user_id="", - tool_parameters={ - "content": "1+(2+3)*4", - "expression": r"(\d+)", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/regex/regex.yaml b/api/core/tools/provider/builtin/regex/regex.yaml deleted file mode 100644 index d05776f214e8d2..00000000000000 --- a/api/core/tools/provider/builtin/regex/regex.yaml +++ /dev/null @@ -1,15 +0,0 @@ -identity: - author: zhuhao - name: regex - label: - en_US: Regex - zh_Hans: 正则表达式提取 - pt_BR: Regex - description: - en_US: A tool for regex extraction. - zh_Hans: 一个用于正则表达式内容提取的工具。 - pt_BR: A tool for regex extraction. - icon: icon.svg - tags: - - utilities - - productivity diff --git a/api/core/tools/provider/builtin/regex/tools/regex_extract.py b/api/core/tools/provider/builtin/regex/tools/regex_extract.py deleted file mode 100644 index 786b4694040030..00000000000000 --- a/api/core/tools/provider/builtin/regex/tools/regex_extract.py +++ /dev/null @@ -1,28 +0,0 @@ -import re -from typing import Any, Union - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class RegexExpressionTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - # get expression - content = tool_parameters.get("content", "").strip() - if not content: - return self.create_text_message("Invalid content") - expression = tool_parameters.get("expression", "").strip() - if not expression: - return self.create_text_message("Invalid expression") - try: - result = re.findall(expression, content) - return self.create_text_message(str(result)) - except Exception as e: - return self.create_text_message(f"Failed to extract result, error: {str(e)}") diff --git a/api/core/tools/provider/builtin/regex/tools/regex_extract.yaml b/api/core/tools/provider/builtin/regex/tools/regex_extract.yaml deleted file mode 100644 index de4100def176c9..00000000000000 --- a/api/core/tools/provider/builtin/regex/tools/regex_extract.yaml +++ /dev/null @@ -1,38 +0,0 @@ -identity: - name: regex_extract - author: zhuhao - label: - en_US: Regex Extract - zh_Hans: 正则表达式内容提取 - pt_BR: Regex Extract -description: - human: - en_US: A tool for extracting matching content using regular expressions. - zh_Hans: 一个用于利用正则表达式提取匹配内容结果的工具。 - pt_BR: A tool for extracting matching content using regular expressions. - llm: A tool for extracting matching content using regular expressions. -parameters: - - name: content - type: string - required: true - label: - en_US: Content to be extracted - zh_Hans: 内容 - pt_BR: Content to be extracted - human_description: - en_US: Content to be extracted - zh_Hans: 内容 - pt_BR: Content to be extracted - form: llm - - name: expression - type: string - required: true - label: - en_US: Regular expression - zh_Hans: 正则表达式 - pt_BR: Regular expression - human_description: - en_US: Regular expression - zh_Hans: 正则表达式 - pt_BR: Regular expression - form: llm diff --git a/api/core/tools/provider/builtin/searchapi/_assets/icon.svg b/api/core/tools/provider/builtin/searchapi/_assets/icon.svg deleted file mode 100644 index 7660b2f351c43b..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/searchapi/searchapi.py b/api/core/tools/provider/builtin/searchapi/searchapi.py deleted file mode 100644 index 109bba8b2d8f79..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/searchapi.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.searchapi.tools.google import GoogleTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class SearchAPIProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - GoogleTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={"query": "SearchApi dify", "result_type": "link"}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/searchapi/searchapi.yaml b/api/core/tools/provider/builtin/searchapi/searchapi.yaml deleted file mode 100644 index c2fa3f398e192f..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/searchapi.yaml +++ /dev/null @@ -1,34 +0,0 @@ -identity: - author: SearchApi - name: searchapi - label: - en_US: SearchApi - zh_Hans: SearchApi - pt_BR: SearchApi - description: - en_US: SearchApi is a robust real-time SERP API delivering structured data from a collection of search engines including Google Search, Google Jobs, YouTube, Google News, and many more. - zh_Hans: SearchApi 是一个强大的实时 SERP API，可提供来自 Google 搜索、Google 招聘、YouTube、Google 新闻等搜索引擎集合的结构化数据。 - pt_BR: SearchApi is a robust real-time SERP API delivering structured data from a collection of search engines including Google Search, Google Jobs, YouTube, Google News, and many more. - icon: icon.svg - tags: - - search - - business - - news - - productivity -credentials_for_provider: - searchapi_api_key: - type: secret-input - required: true - label: - en_US: SearchApi API key - zh_Hans: SearchApi API key - pt_BR: SearchApi API key - placeholder: - en_US: Please input your SearchApi API key - zh_Hans: 请输入你的 SearchApi API key - pt_BR: Please input your SearchApi API key - help: - en_US: Get your SearchApi API key from SearchApi - zh_Hans: 从 SearchApi 获取您的 SearchApi API key - pt_BR: Get your SearchApi API key from SearchApi - url: https://www.searchapi.io/ diff --git a/api/core/tools/provider/builtin/searchapi/tools/google.py b/api/core/tools/provider/builtin/searchapi/tools/google.py deleted file mode 100644 index 17e2978194c6a3..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/tools/google.py +++ /dev/null @@ -1,112 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -SEARCH_API_URL = "https://www.searchapi.io/api/v1/search" - - -class SearchAPI: - """ - SearchAPI tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize SearchAPI tool provider.""" - self.searchapi_api_key = api_key - - def run(self, query: str, **kwargs: Any) -> str: - """Run query through SearchAPI and parse result.""" - type = kwargs.get("result_type", "text") - return self._process_response(self.results(query, **kwargs), type=type) - - def results(self, query: str, **kwargs: Any) -> dict: - """Run query through SearchAPI and return the raw result.""" - params = self.get_params(query, **kwargs) - response = requests.get( - url=SEARCH_API_URL, - params=params, - headers={"Authorization": f"Bearer {self.searchapi_api_key}"}, - ) - response.raise_for_status() - return response.json() - - def get_params(self, query: str, **kwargs: Any) -> dict[str, str]: - """Get parameters for SearchAPI.""" - return { - "engine": "google", - "q": query, - **{key: value for key, value in kwargs.items() if value not in {None, ""}}, - } - - @staticmethod - def _process_response(res: dict, type: str) -> str: - """Process response from SearchAPI.""" - if "error" in res: - raise ValueError(f"Got error from SearchApi: {res['error']}") - - toret = "" - if type == "text": - if "answer_box" in res and "answer" in res["answer_box"]: - toret += res["answer_box"]["answer"] + "\n" - if "answer_box" in res and "snippet" in res["answer_box"]: - toret += res["answer_box"]["snippet"] + "\n" - if "knowledge_graph" in res and "description" in res["knowledge_graph"]: - toret += res["knowledge_graph"]["description"] + "\n" - if "organic_results" in res and "snippet" in res["organic_results"][0]: - for item in res["organic_results"]: - toret += "content: " + item["snippet"] + "\n" + "link: " + item["link"] + "\n" - if toret == "": - toret = "No good search result found" - - elif type == "link": - if "answer_box" in res and "organic_result" in res["answer_box"]: - if "title" in res["answer_box"]["organic_result"]: - toret = ( - f"[{res['answer_box']['organic_result']['title']}]" - f"({res['answer_box']['organic_result']['link']})\n" - ) - elif "organic_results" in res and "link" in res["organic_results"][0]: - toret = "" - for item in res["organic_results"]: - toret += f"[{item['title']}]({item['link']})\n" - elif "related_questions" in res and "link" in res["related_questions"][0]: - toret = "" - for item in res["related_questions"]: - toret += f"[{item['title']}]({item['link']})\n" - elif "related_searches" in res and "link" in res["related_searches"][0]: - toret = "" - for item in res["related_searches"]: - toret += f"[{item['title']}]({item['link']})\n" - else: - toret = "No good search result found" - return toret - - -class GoogleTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SearchApi tool. - """ - query = tool_parameters["query"] - result_type = tool_parameters["result_type"] - num = tool_parameters.get("num", 10) - google_domain = tool_parameters.get("google_domain", "google.com") - gl = tool_parameters.get("gl", "us") - hl = tool_parameters.get("hl", "en") - location = tool_parameters.get("location") - - api_key = self.runtime.credentials["searchapi_api_key"] - result = SearchAPI(api_key).run( - query, result_type=result_type, num=num, google_domain=google_domain, gl=gl, hl=hl, location=location - ) - - if result_type == "text": - return self.create_text_message(text=result) - return self.create_link_message(link=result) diff --git a/api/core/tools/provider/builtin/searchapi/tools/google.yaml b/api/core/tools/provider/builtin/searchapi/tools/google.yaml deleted file mode 100644 index b69a0e1d3e706b..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/tools/google.yaml +++ /dev/null @@ -1,481 +0,0 @@ -identity: - name: google_search_api - author: SearchApi - label: - en_US: Google Search API - zh_Hans: Google Search API -description: - human: - en_US: A tool to retrieve answer boxes, knowledge graphs, snippets, and webpages from Google Search engine. - zh_Hans: 一种从 Google 搜索引擎检索答案框、知识图、片段和网页的工具。 - llm: A tool to retrieve answer boxes, knowledge graphs, snippets, and webpages from Google Search engine. -parameters: - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 询问 - human_description: - en_US: Defines the query you want to search. - zh_Hans: 定义您要搜索的查询。 - llm_description: Defines the search query you want to search. - form: llm - - name: result_type - type: select - required: true - options: - - value: text - label: - en_US: text - zh_Hans: 文本 - - value: link - label: - en_US: link - zh_Hans: 链接 - default: text - label: - en_US: Result type - zh_Hans: 结果类型 - human_description: - en_US: used for selecting the result type, text or link - zh_Hans: 用于选择结果类型，使用文本还是链接进行展示 - form: form - - name: location - type: string - required: false - label: - en_US: Location - zh_Hans: 询问 - human_description: - en_US: Defines from where you want the search to originate. (For example - New York) - zh_Hans: 定义您想要搜索的起始位置。 （例如 - 纽约） - llm_description: Defines from where you want the search to originate. (For example - New York) - form: llm - - name: gl - type: select - label: - en_US: Country - zh_Hans: 国家 - required: false - human_description: - en_US: Defines the country of the search. Default is "US". - zh_Hans: 定义搜索的国家/地区。默认为“美国”。 - llm_description: Defines the gl parameter of the Google search. - form: form - default: US - options: - - value: AR - label: - en_US: Argentina - zh_Hans: 阿根廷 - pt_BR: Argentina - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: AT - label: - en_US: Austria - zh_Hans: 奥地利 - pt_BR: Austria - - value: BE - label: - en_US: Belgium - zh_Hans: 比利时 - pt_BR: Belgium - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: CL - label: - en_US: Chile - zh_Hans: 智利 - pt_BR: Chile - - value: CO - label: - en_US: Colombia - zh_Hans: 哥伦比亚 - pt_BR: Colombia - - value: CN - label: - en_US: China - zh_Hans: 中国 - pt_BR: China - - value: CZ - label: - en_US: Czech Republic - zh_Hans: 捷克共和国 - pt_BR: Czech Republic - - value: DK - label: - en_US: Denmark - zh_Hans: 丹麦 - pt_BR: Denmark - - value: FI - label: - en_US: Finland - zh_Hans: 芬兰 - pt_BR: Finland - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: HK - label: - en_US: Hong Kong - zh_Hans: 香港 - pt_BR: Hong Kong - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: ID - label: - en_US: Indonesia - zh_Hans: 印度尼西亚 - pt_BR: Indonesia - - value: IT - label: - en_US: Italy - zh_Hans: 意大利 - pt_BR: Italy - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: MY - label: - en_US: Malaysia - zh_Hans: 马来西亚 - pt_BR: Malaysia - - value: MX - label: - en_US: Mexico - zh_Hans: 墨西哥 - pt_BR: Mexico - - value: NL - label: - en_US: Netherlands - zh_Hans: 荷兰 - pt_BR: Netherlands - - value: NZ - label: - en_US: New Zealand - zh_Hans: 新西兰 - pt_BR: New Zealand - - value: 'NO' - label: - en_US: Norway - zh_Hans: 挪威 - pt_BR: Norway - - value: PH - label: - en_US: Philippines - zh_Hans: 菲律宾 - pt_BR: Philippines - - value: PL - label: - en_US: Poland - zh_Hans: 波兰 - pt_BR: Poland - - value: PT - label: - en_US: Portugal - zh_Hans: 葡萄牙 - pt_BR: Portugal - - value: RU - label: - en_US: Russia - zh_Hans: 俄罗斯 - pt_BR: Russia - - value: SA - label: - en_US: Saudi Arabia - zh_Hans: 沙特阿拉伯 - pt_BR: Saudi Arabia - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: ZA - label: - en_US: South Africa - zh_Hans: 南非 - pt_BR: South Africa - - value: ES - label: - en_US: Spain - zh_Hans: 西班牙 - pt_BR: Spain - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - value: CH - label: - en_US: Switzerland - zh_Hans: 瑞士 - pt_BR: Switzerland - - value: TW - label: - en_US: Taiwan - zh_Hans: 台湾 - pt_BR: Taiwan - - value: TH - label: - en_US: Thailand - zh_Hans: 泰国 - pt_BR: Thailand - - value: TR - label: - en_US: Turkey - zh_Hans: 土耳其 - pt_BR: Turkey - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - name: hl - type: select - label: - en_US: Language - zh_Hans: 语言 - human_description: - en_US: Defines the interface language of the search. Default is "en". - zh_Hans: 定义搜索的界面语言。默认为“en”。 - required: false - default: en - form: form - options: - - value: ar - label: - en_US: Arabic - zh_Hans: 阿拉伯语 - - value: bg - label: - en_US: Bulgarian - zh_Hans: 保加利亚语 - - value: ca - label: - en_US: Catalan - zh_Hans: 加泰罗尼亚语 - - value: zh-cn - label: - en_US: Chinese (Simplified) - zh_Hans: 中文（简体） - - value: zh-tw - label: - en_US: Chinese (Traditional) - zh_Hans: 中文（繁体） - - value: cs - label: - en_US: Czech - zh_Hans: 捷克语 - - value: da - label: - en_US: Danish - zh_Hans: 丹麦语 - - value: nl - label: - en_US: Dutch - zh_Hans: 荷兰语 - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: et - label: - en_US: Estonian - zh_Hans: 爱沙尼亚语 - - value: fi - label: - en_US: Finnish - zh_Hans: 芬兰语 - - value: fr - label: - en_US: French - zh_Hans: 法语 - - value: de - label: - en_US: German - zh_Hans: 德语 - - value: el - label: - en_US: Greek - zh_Hans: 希腊语 - - value: iw - label: - en_US: Hebrew - zh_Hans: 希伯来语 - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - - value: hu - label: - en_US: Hungarian - zh_Hans: 匈牙利语 - - value: id - label: - en_US: Indonesian - zh_Hans: 印尼语 - - value: it - label: - en_US: Italian - zh_Hans: 意大利语 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - - value: kn - label: - en_US: Kannada - zh_Hans: 卡纳达语 - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - - value: lv - label: - en_US: Latvian - zh_Hans: 拉脱维亚语 - - value: lt - label: - en_US: Lithuanian - zh_Hans: 立陶宛语 - - value: my - label: - en_US: Malay - zh_Hans: 马来语 - - value: ml - label: - en_US: Malayalam - zh_Hans: 马拉雅拉姆语 - - value: mr - label: - en_US: Marathi - zh_Hans: 马拉地语 - - value: "no" - label: - en_US: Norwegian - zh_Hans: 挪威语 - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - - value: pt-br - label: - en_US: Portuguese (Brazil) - zh_Hans: 葡萄牙语（巴西） - - value: pt-pt - label: - en_US: Portuguese (Portugal) - zh_Hans: 葡萄牙语（葡萄牙） - - value: pa - label: - en_US: Punjabi - zh_Hans: 旁遮普语 - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - - value: ru - label: - en_US: Russian - zh_Hans: 俄语 - - value: sr - label: - en_US: Serbian - zh_Hans: 塞尔维亚语 - - value: sk - label: - en_US: Slovak - zh_Hans: 斯洛伐克语 - - value: sl - label: - en_US: Slovenian - zh_Hans: 斯洛文尼亚语 - - value: es - label: - en_US: Spanish - zh_Hans: 西班牙语 - - value: sv - label: - en_US: Swedish - zh_Hans: 瑞典语 - - value: ta - label: - en_US: Tamil - zh_Hans: 泰米尔语 - - value: te - label: - en_US: Telugu - zh_Hans: 泰卢固语 - - value: th - label: - en_US: Thai - zh_Hans: 泰语 - - value: tr - label: - en_US: Turkish - zh_Hans: 土耳其语 - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 - - name: google_domain - type: string - required: false - label: - en_US: google_domain - zh_Hans: google_domain - human_description: - en_US: Defines the Google domain of the search. Default is "google.com". - zh_Hans: 定义搜索的 Google 域。默认为“google.com”。 - llm_description: Defines Google domain in which you want to search. - form: llm - - name: num - type: number - required: false - label: - en_US: num - zh_Hans: num - human_description: - en_US: Specifies the number of results to display per page. Default is 10. Max number - 100, min - 1. - zh_Hans: 指定每页显示的结果数。默认值为 10。最大数量 - 100，最小数量 - 1。 - llm_description: Specifies the num of results to display per page. - form: llm diff --git a/api/core/tools/provider/builtin/searchapi/tools/google_jobs.py b/api/core/tools/provider/builtin/searchapi/tools/google_jobs.py deleted file mode 100644 index c478bc108b47e1..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/tools/google_jobs.py +++ /dev/null @@ -1,102 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -SEARCH_API_URL = "https://www.searchapi.io/api/v1/search" - - -class SearchAPI: - """ - SearchAPI tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize SearchAPI tool provider.""" - self.searchapi_api_key = api_key - - def run(self, query: str, **kwargs: Any) -> str: - """Run query through SearchAPI and parse result.""" - type = kwargs.get("result_type", "text") - return self._process_response(self.results(query, **kwargs), type=type) - - def results(self, query: str, **kwargs: Any) -> dict: - """Run query through SearchAPI and return the raw result.""" - params = self.get_params(query, **kwargs) - response = requests.get( - url=SEARCH_API_URL, - params=params, - headers={"Authorization": f"Bearer {self.searchapi_api_key}"}, - ) - response.raise_for_status() - return response.json() - - def get_params(self, query: str, **kwargs: Any) -> dict[str, str]: - """Get parameters for SearchAPI.""" - return { - "engine": "google_jobs", - "q": query, - **{key: value for key, value in kwargs.items() if value not in {None, ""}}, - } - - @staticmethod - def _process_response(res: dict, type: str) -> str: - """Process response from SearchAPI.""" - if "error" in res: - raise ValueError(f"Got error from SearchApi: {res['error']}") - - toret = "" - if type == "text": - if "jobs" in res and "title" in res["jobs"][0]: - for item in res["jobs"]: - toret += ( - "title: " - + item["title"] - + "\n" - + "company_name: " - + item["company_name"] - + "content: " - + item["description"] - + "\n" - ) - if toret == "": - toret = "No good search result found" - - elif type == "link": - if "jobs" in res and "apply_link" in res["jobs"][0]: - for item in res["jobs"]: - toret += f"[{item['title']} - {item['company_name']}]({item['apply_link']})\n" - else: - toret = "No good search result found" - return toret - - -class GoogleJobsTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SearchApi tool. - """ - query = tool_parameters["query"] - result_type = tool_parameters["result_type"] - is_remote = tool_parameters.get("is_remote") - google_domain = tool_parameters.get("google_domain", "google.com") - gl = tool_parameters.get("gl", "us") - hl = tool_parameters.get("hl", "en") - location = tool_parameters.get("location") - - ltype = 1 if is_remote else None - - api_key = self.runtime.credentials["searchapi_api_key"] - result = SearchAPI(api_key).run( - query, result_type=result_type, google_domain=google_domain, gl=gl, hl=hl, location=location, ltype=ltype - ) - - if result_type == "text": - return self.create_text_message(text=result) - return self.create_link_message(link=result) diff --git a/api/core/tools/provider/builtin/searchapi/tools/google_jobs.yaml b/api/core/tools/provider/builtin/searchapi/tools/google_jobs.yaml deleted file mode 100644 index 9033bc0f8784cc..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/tools/google_jobs.yaml +++ /dev/null @@ -1,478 +0,0 @@ -identity: - name: google_jobs_api - author: SearchApi - label: - en_US: Google Jobs API - zh_Hans: Google Jobs API -description: - human: - en_US: A tool to retrieve job titles, company names and description from Google Jobs engine. - zh_Hans: 一个从 Google 招聘引擎检索职位名称、公司名称和描述的工具。 - llm: A tool to retrieve job titles, company names and description from Google Jobs engine. -parameters: - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 询问 - human_description: - en_US: Defines the query you want to search. - zh_Hans: 定义您要搜索的查询。 - llm_description: Defines the search query you want to search. - form: llm - - name: result_type - type: select - required: true - options: - - value: text - label: - en_US: text - zh_Hans: 文本 - - value: link - label: - en_US: link - zh_Hans: 链接 - default: text - label: - en_US: Result type - zh_Hans: 结果类型 - human_description: - en_US: used for selecting the result type, text or link - zh_Hans: 用于选择结果类型，使用文本还是链接进行展示 - form: form - - name: location - type: string - required: false - label: - en_US: Location - zh_Hans: 询问 - human_description: - en_US: Defines from where you want the search to originate. (For example - New York) - zh_Hans: 定义您想要搜索的起始位置。 （例如 - 纽约） - llm_description: Defines from where you want the search to originate. (For example - New York) - form: llm - - name: gl - type: select - label: - en_US: Country - zh_Hans: 国家 - required: false - human_description: - en_US: Defines the country of the search. Default is "US". - zh_Hans: 定义搜索的国家/地区。默认为“美国”。 - llm_description: Defines the gl parameter of the Google search. - form: form - default: US - options: - - value: AR - label: - en_US: Argentina - zh_Hans: 阿根廷 - pt_BR: Argentina - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: AT - label: - en_US: Austria - zh_Hans: 奥地利 - pt_BR: Austria - - value: BE - label: - en_US: Belgium - zh_Hans: 比利时 - pt_BR: Belgium - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: CL - label: - en_US: Chile - zh_Hans: 智利 - pt_BR: Chile - - value: CO - label: - en_US: Colombia - zh_Hans: 哥伦比亚 - pt_BR: Colombia - - value: CN - label: - en_US: China - zh_Hans: 中国 - pt_BR: China - - value: CZ - label: - en_US: Czech Republic - zh_Hans: 捷克共和国 - pt_BR: Czech Republic - - value: DK - label: - en_US: Denmark - zh_Hans: 丹麦 - pt_BR: Denmark - - value: FI - label: - en_US: Finland - zh_Hans: 芬兰 - pt_BR: Finland - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: HK - label: - en_US: Hong Kong - zh_Hans: 香港 - pt_BR: Hong Kong - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: ID - label: - en_US: Indonesia - zh_Hans: 印度尼西亚 - pt_BR: Indonesia - - value: IT - label: - en_US: Italy - zh_Hans: 意大利 - pt_BR: Italy - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: MY - label: - en_US: Malaysia - zh_Hans: 马来西亚 - pt_BR: Malaysia - - value: MX - label: - en_US: Mexico - zh_Hans: 墨西哥 - pt_BR: Mexico - - value: NL - label: - en_US: Netherlands - zh_Hans: 荷兰 - pt_BR: Netherlands - - value: NZ - label: - en_US: New Zealand - zh_Hans: 新西兰 - pt_BR: New Zealand - - value: 'NO' - label: - en_US: Norway - zh_Hans: 挪威 - pt_BR: Norway - - value: PH - label: - en_US: Philippines - zh_Hans: 菲律宾 - pt_BR: Philippines - - value: PL - label: - en_US: Poland - zh_Hans: 波兰 - pt_BR: Poland - - value: PT - label: - en_US: Portugal - zh_Hans: 葡萄牙 - pt_BR: Portugal - - value: RU - label: - en_US: Russia - zh_Hans: 俄罗斯 - pt_BR: Russia - - value: SA - label: - en_US: Saudi Arabia - zh_Hans: 沙特阿拉伯 - pt_BR: Saudi Arabia - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: ZA - label: - en_US: South Africa - zh_Hans: 南非 - pt_BR: South Africa - - value: ES - label: - en_US: Spain - zh_Hans: 西班牙 - pt_BR: Spain - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - value: CH - label: - en_US: Switzerland - zh_Hans: 瑞士 - pt_BR: Switzerland - - value: TW - label: - en_US: Taiwan - zh_Hans: 台湾 - pt_BR: Taiwan - - value: TH - label: - en_US: Thailand - zh_Hans: 泰国 - pt_BR: Thailand - - value: TR - label: - en_US: Turkey - zh_Hans: 土耳其 - pt_BR: Turkey - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - name: hl - type: select - label: - en_US: Language - zh_Hans: 语言 - human_description: - en_US: Defines the interface language of the search. Default is "en". - zh_Hans: 定义搜索的界面语言。默认为“en”。 - required: false - default: en - form: form - options: - - value: ar - label: - en_US: Arabic - zh_Hans: 阿拉伯语 - - value: bg - label: - en_US: Bulgarian - zh_Hans: 保加利亚语 - - value: ca - label: - en_US: Catalan - zh_Hans: 加泰罗尼亚语 - - value: zh-cn - label: - en_US: Chinese (Simplified) - zh_Hans: 中文（简体） - - value: zh-tw - label: - en_US: Chinese (Traditional) - zh_Hans: 中文（繁体） - - value: cs - label: - en_US: Czech - zh_Hans: 捷克语 - - value: da - label: - en_US: Danish - zh_Hans: 丹麦语 - - value: nl - label: - en_US: Dutch - zh_Hans: 荷兰语 - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: et - label: - en_US: Estonian - zh_Hans: 爱沙尼亚语 - - value: fi - label: - en_US: Finnish - zh_Hans: 芬兰语 - - value: fr - label: - en_US: French - zh_Hans: 法语 - - value: de - label: - en_US: German - zh_Hans: 德语 - - value: el - label: - en_US: Greek - zh_Hans: 希腊语 - - value: iw - label: - en_US: Hebrew - zh_Hans: 希伯来语 - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - - value: hu - label: - en_US: Hungarian - zh_Hans: 匈牙利语 - - value: id - label: - en_US: Indonesian - zh_Hans: 印尼语 - - value: it - label: - en_US: Italian - zh_Hans: 意大利语 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - - value: kn - label: - en_US: Kannada - zh_Hans: 卡纳达语 - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - - value: lv - label: - en_US: Latvian - zh_Hans: 拉脱维亚语 - - value: lt - label: - en_US: Lithuanian - zh_Hans: 立陶宛语 - - value: my - label: - en_US: Malay - zh_Hans: 马来语 - - value: ml - label: - en_US: Malayalam - zh_Hans: 马拉雅拉姆语 - - value: mr - label: - en_US: Marathi - zh_Hans: 马拉地语 - - value: "no" - label: - en_US: Norwegian - zh_Hans: 挪威语 - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - - value: pt-br - label: - en_US: Portuguese (Brazil) - zh_Hans: 葡萄牙语（巴西） - - value: pt-pt - label: - en_US: Portuguese (Portugal) - zh_Hans: 葡萄牙语（葡萄牙） - - value: pa - label: - en_US: Punjabi - zh_Hans: 旁遮普语 - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - - value: ru - label: - en_US: Russian - zh_Hans: 俄语 - - value: sr - label: - en_US: Serbian - zh_Hans: 塞尔维亚语 - - value: sk - label: - en_US: Slovak - zh_Hans: 斯洛伐克语 - - value: sl - label: - en_US: Slovenian - zh_Hans: 斯洛文尼亚语 - - value: es - label: - en_US: Spanish - zh_Hans: 西班牙语 - - value: sv - label: - en_US: Swedish - zh_Hans: 瑞典语 - - value: ta - label: - en_US: Tamil - zh_Hans: 泰米尔语 - - value: te - label: - en_US: Telugu - zh_Hans: 泰卢固语 - - value: th - label: - en_US: Thai - zh_Hans: 泰语 - - value: tr - label: - en_US: Turkish - zh_Hans: 土耳其语 - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 - - name: is_remote - type: select - label: - en_US: is_remote - zh_Hans: 很遥远 - human_description: - en_US: Filter results based on the work arrangement. Set it to true to find jobs that offer work from home or remote work opportunities. - zh_Hans: 根据工作安排过滤结果。将其设置为 true 可查找提供在家工作或远程工作机会的工作。 - required: false - form: form - options: - - value: 'true' - label: - en_US: "true" - zh_Hans: "true" - - value: 'false' - label: - en_US: "false" - zh_Hans: "false" diff --git a/api/core/tools/provider/builtin/searchapi/tools/google_news.py b/api/core/tools/provider/builtin/searchapi/tools/google_news.py deleted file mode 100644 index 562bc01964b4c3..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/tools/google_news.py +++ /dev/null @@ -1,97 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -SEARCH_API_URL = "https://www.searchapi.io/api/v1/search" - - -class SearchAPI: - """ - SearchAPI tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize SearchAPI tool provider.""" - self.searchapi_api_key = api_key - - def run(self, query: str, **kwargs: Any) -> str: - """Run query through SearchAPI and parse result.""" - type = kwargs.get("result_type", "text") - return self._process_response(self.results(query, **kwargs), type=type) - - def results(self, query: str, **kwargs: Any) -> dict: - """Run query through SearchAPI and return the raw result.""" - params = self.get_params(query, **kwargs) - response = requests.get( - url=SEARCH_API_URL, - params=params, - headers={"Authorization": f"Bearer {self.searchapi_api_key}"}, - ) - response.raise_for_status() - return response.json() - - def get_params(self, query: str, **kwargs: Any) -> dict[str, str]: - """Get parameters for SearchAPI.""" - return { - "engine": "google_news", - "q": query, - **{key: value for key, value in kwargs.items() if value not in {None, ""}}, - } - - @staticmethod - def _process_response(res: dict, type: str) -> str: - """Process response from SearchAPI.""" - if "error" in res: - raise ValueError(f"Got error from SearchApi: {res['error']}") - - toret = "" - if type == "text": - if "organic_results" in res and "snippet" in res["organic_results"][0]: - for item in res["organic_results"]: - toret += "content: " + item["snippet"] + "\n" + "link: " + item["link"] + "\n" - if "top_stories" in res and "title" in res["top_stories"][0]: - for item in res["top_stories"]: - toret += "title: " + item["title"] + "\n" + "link: " + item["link"] + "\n" - if toret == "": - toret = "No good search result found" - - elif type == "link": - if "organic_results" in res and "title" in res["organic_results"][0]: - for item in res["organic_results"]: - toret += f"[{item['title']}]({item['link']})\n" - elif "top_stories" in res and "title" in res["top_stories"][0]: - for item in res["top_stories"]: - toret += f"[{item['title']}]({item['link']})\n" - else: - toret = "No good search result found" - return toret - - -class GoogleNewsTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SearchApi tool. - """ - query = tool_parameters["query"] - result_type = tool_parameters["result_type"] - num = tool_parameters.get("num", 10) - google_domain = tool_parameters.get("google_domain", "google.com") - gl = tool_parameters.get("gl", "us") - hl = tool_parameters.get("hl", "en") - location = tool_parameters.get("location") - - api_key = self.runtime.credentials["searchapi_api_key"] - result = SearchAPI(api_key).run( - query, result_type=result_type, num=num, google_domain=google_domain, gl=gl, hl=hl, location=location - ) - - if result_type == "text": - return self.create_text_message(text=result) - return self.create_link_message(link=result) diff --git a/api/core/tools/provider/builtin/searchapi/tools/google_news.yaml b/api/core/tools/provider/builtin/searchapi/tools/google_news.yaml deleted file mode 100644 index cbb0edf9829595..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/tools/google_news.yaml +++ /dev/null @@ -1,482 +0,0 @@ -identity: - name: google_news_api - author: SearchApi - label: - en_US: Google News API - zh_Hans: Google News API -description: - human: - en_US: A tool to retrieve organic search results snippets and links from Google News engine. - zh_Hans: 一种从 Google 新闻引擎检索有机搜索结果片段和链接的工具。 - llm: A tool to retrieve organic search results snippets and links from Google News engine. -parameters: - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 询问 - human_description: - en_US: Defines the query you want to search. - zh_Hans: 定义您要搜索的查询。 - llm_description: Defines the search query you want to search. - form: llm - - name: result_type - type: select - required: true - options: - - value: text - label: - en_US: text - zh_Hans: 文本 - - value: link - label: - en_US: link - zh_Hans: 链接 - default: text - label: - en_US: Result type - zh_Hans: 结果类型 - human_description: - en_US: used for selecting the result type, text or link. - zh_Hans: 用于选择结果类型，使用文本还是链接进行展示。 - form: form - - name: location - type: string - required: false - label: - en_US: Location - zh_Hans: 询问 - human_description: - en_US: Defines from where you want the search to originate. (For example - New York) - zh_Hans: 定义您想要搜索的起始位置。 （例如 - 纽约） - llm_description: Defines from where you want the search to originate. (For example - New York) - form: llm - - name: gl - type: select - label: - en_US: Country - zh_Hans: 国家 - required: false - human_description: - en_US: Defines the country of the search. Default is "US". - zh_Hans: 定义搜索的国家/地区。默认为“美国”。 - llm_description: Defines the gl parameter of the Google search. - form: form - default: US - options: - - value: AR - label: - en_US: Argentina - zh_Hans: 阿根廷 - pt_BR: Argentina - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: AT - label: - en_US: Austria - zh_Hans: 奥地利 - pt_BR: Austria - - value: BE - label: - en_US: Belgium - zh_Hans: 比利时 - pt_BR: Belgium - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: CL - label: - en_US: Chile - zh_Hans: 智利 - pt_BR: Chile - - value: CO - label: - en_US: Colombia - zh_Hans: 哥伦比亚 - pt_BR: Colombia - - value: CN - label: - en_US: China - zh_Hans: 中国 - pt_BR: China - - value: CZ - label: - en_US: Czech Republic - zh_Hans: 捷克共和国 - pt_BR: Czech Republic - - value: DK - label: - en_US: Denmark - zh_Hans: 丹麦 - pt_BR: Denmark - - value: FI - label: - en_US: Finland - zh_Hans: 芬兰 - pt_BR: Finland - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: HK - label: - en_US: Hong Kong - zh_Hans: 香港 - pt_BR: Hong Kong - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: ID - label: - en_US: Indonesia - zh_Hans: 印度尼西亚 - pt_BR: Indonesia - - value: IT - label: - en_US: Italy - zh_Hans: 意大利 - pt_BR: Italy - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: MY - label: - en_US: Malaysia - zh_Hans: 马来西亚 - pt_BR: Malaysia - - value: MX - label: - en_US: Mexico - zh_Hans: 墨西哥 - pt_BR: Mexico - - value: NL - label: - en_US: Netherlands - zh_Hans: 荷兰 - pt_BR: Netherlands - - value: NZ - label: - en_US: New Zealand - zh_Hans: 新西兰 - pt_BR: New Zealand - - value: 'NO' - label: - en_US: Norway - zh_Hans: 挪威 - pt_BR: Norway - - value: PH - label: - en_US: Philippines - zh_Hans: 菲律宾 - pt_BR: Philippines - - value: PL - label: - en_US: Poland - zh_Hans: 波兰 - pt_BR: Poland - - value: PT - label: - en_US: Portugal - zh_Hans: 葡萄牙 - pt_BR: Portugal - - value: RU - label: - en_US: Russia - zh_Hans: 俄罗斯 - pt_BR: Russia - - value: SA - label: - en_US: Saudi Arabia - zh_Hans: 沙特阿拉伯 - pt_BR: Saudi Arabia - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: ZA - label: - en_US: South Africa - zh_Hans: 南非 - pt_BR: South Africa - - value: ES - label: - en_US: Spain - zh_Hans: 西班牙 - pt_BR: Spain - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - value: CH - label: - en_US: Switzerland - zh_Hans: 瑞士 - pt_BR: Switzerland - - value: TW - label: - en_US: Taiwan - zh_Hans: 台湾 - pt_BR: Taiwan - - value: TH - label: - en_US: Thailand - zh_Hans: 泰国 - pt_BR: Thailand - - value: TR - label: - en_US: Turkey - zh_Hans: 土耳其 - pt_BR: Turkey - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - name: hl - type: select - label: - en_US: Language - zh_Hans: 语言 - human_description: - en_US: Defines the interface language of the search. Default is "en". - zh_Hans: 定义搜索的界面语言。默认为“en”。 - required: false - default: en - form: form - options: - - value: ar - label: - en_US: Arabic - zh_Hans: 阿拉伯语 - - value: bg - label: - en_US: Bulgarian - zh_Hans: 保加利亚语 - - value: ca - label: - en_US: Catalan - zh_Hans: 加泰罗尼亚语 - - value: zh-cn - label: - en_US: Chinese (Simplified) - zh_Hans: 中文（简体） - - value: zh-tw - label: - en_US: Chinese (Traditional) - zh_Hans: 中文（繁体） - - value: cs - label: - en_US: Czech - zh_Hans: 捷克语 - - value: da - label: - en_US: Danish - zh_Hans: 丹麦语 - - value: nl - label: - en_US: Dutch - zh_Hans: 荷兰语 - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: et - label: - en_US: Estonian - zh_Hans: 爱沙尼亚语 - - value: fi - label: - en_US: Finnish - zh_Hans: 芬兰语 - - value: fr - label: - en_US: French - zh_Hans: 法语 - - value: de - label: - en_US: German - zh_Hans: 德语 - - value: el - label: - en_US: Greek - zh_Hans: 希腊语 - - value: iw - label: - en_US: Hebrew - zh_Hans: 希伯来语 - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - - value: hu - label: - en_US: Hungarian - zh_Hans: 匈牙利语 - - value: id - label: - en_US: Indonesian - zh_Hans: 印尼语 - - value: it - label: - en_US: Italian - zh_Hans: 意大利语 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - - value: kn - label: - en_US: Kannada - zh_Hans: 卡纳达语 - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - - value: lv - label: - en_US: Latvian - zh_Hans: 拉脱维亚语 - - value: lt - label: - en_US: Lithuanian - zh_Hans: 立陶宛语 - - value: my - label: - en_US: Malay - zh_Hans: 马来语 - - value: ml - label: - en_US: Malayalam - zh_Hans: 马拉雅拉姆语 - - value: mr - label: - en_US: Marathi - zh_Hans: 马拉地语 - - value: "no" - label: - en_US: Norwegian - zh_Hans: 挪威语 - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - - value: pt-br - label: - en_US: Portuguese (Brazil) - zh_Hans: 葡萄牙语（巴西） - - value: pt-pt - label: - en_US: Portuguese (Portugal) - zh_Hans: 葡萄牙语（葡萄牙） - - value: pa - label: - en_US: Punjabi - zh_Hans: 旁遮普语 - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - - value: ru - label: - en_US: Russian - zh_Hans: 俄语 - - value: sr - label: - en_US: Serbian - zh_Hans: 塞尔维亚语 - - value: sk - label: - en_US: Slovak - zh_Hans: 斯洛伐克语 - - value: sl - label: - en_US: Slovenian - zh_Hans: 斯洛文尼亚语 - - value: es - label: - en_US: Spanish - zh_Hans: 西班牙语 - - value: sv - label: - en_US: Swedish - zh_Hans: 瑞典语 - - value: ta - label: - en_US: Tamil - zh_Hans: 泰米尔语 - - value: te - label: - en_US: Telugu - zh_Hans: 泰卢固语 - - value: th - label: - en_US: Thai - zh_Hans: 泰语 - - value: tr - label: - en_US: Turkish - zh_Hans: 土耳其语 - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 - - name: google_domain - type: string - required: false - label: - en_US: google_domain - zh_Hans: google_domain - human_description: - en_US: Defines the Google domain of the search. Default is "google.com". - zh_Hans: 定义搜索的 Google 域。默认为“google.com”。 - llm_description: Defines Google domain in which you want to search. - form: llm - - name: num - type: number - required: false - label: - en_US: num - zh_Hans: num - human_description: - en_US: Specifies the number of results to display per page. Default is 10. Max number - 100, min - 1. - zh_Hans: 指定每页显示的结果数。默认值为 10。最大数量 - 100，最小数量 - 1。 - pt_BR: Specifies the number of results to display per page. Default is 10. Max number - 100, min - 1. - llm_description: Specifies the num of results to display per page. - form: llm diff --git a/api/core/tools/provider/builtin/searchapi/tools/youtube_transcripts.py b/api/core/tools/provider/builtin/searchapi/tools/youtube_transcripts.py deleted file mode 100644 index 1867cf7be79be5..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/tools/youtube_transcripts.py +++ /dev/null @@ -1,75 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -SEARCH_API_URL = "https://www.searchapi.io/api/v1/search" - - -class SearchAPI: - """ - SearchAPI tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize SearchAPI tool provider.""" - self.searchapi_api_key = api_key - - def run(self, video_id: str, language: str, **kwargs: Any) -> str: - """Run video_id through SearchAPI and parse result.""" - return self._process_response(self.results(video_id, language, **kwargs)) - - def results(self, video_id: str, language: str, **kwargs: Any) -> dict: - """Run video_id through SearchAPI and return the raw result.""" - params = self.get_params(video_id, language, **kwargs) - response = requests.get( - url=SEARCH_API_URL, - params=params, - headers={"Authorization": f"Bearer {self.searchapi_api_key}"}, - ) - response.raise_for_status() - return response.json() - - def get_params(self, video_id: str, language: str, **kwargs: Any) -> dict[str, str]: - """Get parameters for SearchAPI.""" - return { - "engine": "youtube_transcripts", - "video_id": video_id, - "lang": language or "en", - **{key: value for key, value in kwargs.items() if value not in {None, ""}}, - } - - @staticmethod - def _process_response(res: dict) -> str: - """Process response from SearchAPI.""" - if "error" in res: - raise ValueError(f"Got error from SearchApi: {res['error']}") - - toret = "" - if "transcripts" in res and "text" in res["transcripts"][0]: - for item in res["transcripts"]: - toret += item["text"] + " " - if toret == "": - toret = "No good search result found" - - return toret - - -class YoutubeTranscriptsTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SearchApi tool. - """ - video_id = tool_parameters["video_id"] - language = tool_parameters.get("language", "en") - - api_key = self.runtime.credentials["searchapi_api_key"] - result = SearchAPI(api_key).run(video_id, language=language) - - return self.create_text_message(text=result) diff --git a/api/core/tools/provider/builtin/searchapi/tools/youtube_transcripts.yaml b/api/core/tools/provider/builtin/searchapi/tools/youtube_transcripts.yaml deleted file mode 100644 index 8bdcd6bb936d96..00000000000000 --- a/api/core/tools/provider/builtin/searchapi/tools/youtube_transcripts.yaml +++ /dev/null @@ -1,34 +0,0 @@ -identity: - name: youtube_transcripts_api - author: SearchApi - label: - en_US: YouTube Transcripts API - zh_Hans: YouTube 脚本 API -description: - human: - en_US: A tool to retrieve transcripts from the specific YouTube video. - zh_Hans: 一种从特定 YouTube 视频检索文字记录的工具。 - llm: A tool to retrieve transcripts from the specific YouTube video. -parameters: - - name: video_id - type: string - required: true - label: - en_US: video_id - zh_Hans: 视频ID - human_description: - en_US: Used to define the video you want to search. You can find the video id's in YouTube page that appears in URL. For example - https://www.youtube.com/watch?v=video_id. - zh_Hans: 用于定义要搜索的视频。您可以在 URL 中显示的 YouTube 页面中找到视频 ID。例如 - https://www.youtube.com/watch?v=video_id。 - llm_description: Used to define the video you want to search. - form: llm - - name: language - type: string - required: false - label: - en_US: language - zh_Hans: 语言 - human_description: - en_US: Used to set the language for transcripts. The default value is "en". You can find all supported languages in SearchApi documentation. - zh_Hans: 用于设置成绩单的语言。默认值为“en”。您可以在 SearchApi 文档中找到所有支持的语言。 - llm_description: Used to set the language for transcripts. - form: llm diff --git a/api/core/tools/provider/builtin/searxng/_assets/icon.svg b/api/core/tools/provider/builtin/searxng/_assets/icon.svg deleted file mode 100644 index b94fe3728adbff..00000000000000 --- a/api/core/tools/provider/builtin/searxng/_assets/icon.svg +++ /dev/null @@ -1,56 +0,0 @@ - - - - - - - image/svg+xml - - - - - - - - - - - - diff --git a/api/core/tools/provider/builtin/searxng/docker/settings.yml b/api/core/tools/provider/builtin/searxng/docker/settings.yml deleted file mode 100644 index 18e18688002cbc..00000000000000 --- a/api/core/tools/provider/builtin/searxng/docker/settings.yml +++ /dev/null @@ -1,2501 +0,0 @@ -general: - # Debug mode, only for development. Is overwritten by ${SEARXNG_DEBUG} - debug: false - # displayed name - instance_name: "searxng" - # For example: https://example.com/privacy - privacypolicy_url: false - # use true to use your own donation page written in searx/info/en/donate.md - # use false to disable the donation link - donation_url: false - # mailto:contact@example.com - contact_url: false - # record stats - enable_metrics: true - -brand: - new_issue_url: https://github.com/searxng/searxng/issues/new - docs_url: https://docs.searxng.org/ - public_instances: https://searx.space - wiki_url: https://github.com/searxng/searxng/wiki - issue_url: https://github.com/searxng/searxng/issues - # custom: - # maintainer: "Jon Doe" - # # Custom entries in the footer: [title]: [link] - # links: - # Uptime: https://uptime.searxng.org/history/darmarit-org - # About: "https://searxng.org" - -search: - # Filter results. 0: None, 1: Moderate, 2: Strict - safe_search: 0 - # Existing autocomplete backends: "dbpedia", "duckduckgo", "google", "yandex", "mwmbl", - # "seznam", "startpage", "stract", "swisscows", "qwant", "wikipedia" - leave blank to turn it off - # by default. - autocomplete: "" - # minimun characters to type before autocompleter starts - autocomplete_min: 4 - # Default search language - leave blank to detect from browser information or - # use codes from 'languages.py' - default_lang: "auto" - # max_page: 0 # if engine supports paging, 0 means unlimited numbers of pages - # Available languages - # languages: - # - all - # - en - # - en-US - # - de - # - it-IT - # - fr - # - fr-BE - # ban time in seconds after engine errors - ban_time_on_fail: 5 - # max ban time in seconds after engine errors - max_ban_time_on_fail: 120 - suspended_times: - # Engine suspension time after error (in seconds; set to 0 to disable) - # For error "Access denied" and "HTTP error [402, 403]" - SearxEngineAccessDenied: 86400 - # For error "CAPTCHA" - SearxEngineCaptcha: 86400 - # For error "Too many request" and "HTTP error 429" - SearxEngineTooManyRequests: 3600 - # Cloudflare CAPTCHA - cf_SearxEngineCaptcha: 1296000 - cf_SearxEngineAccessDenied: 86400 - # ReCAPTCHA - recaptcha_SearxEngineCaptcha: 604800 - - # remove format to deny access, use lower case. - # formats: [html, csv, json, rss] - formats: - - html - - json - -server: - # Is overwritten by ${SEARXNG_PORT} and ${SEARXNG_BIND_ADDRESS} - port: 8888 - bind_address: "127.0.0.1" - # public URL of the instance, to ensure correct inbound links. Is overwritten - # by ${SEARXNG_URL}. - base_url: http://0.0.0.0:8081/ # "http://example.com/location" - # rate limit the number of request on the instance, block some bots. - # Is overwritten by ${SEARXNG_LIMITER} - limiter: false - # enable features designed only for public instances. - # Is overwritten by ${SEARXNG_PUBLIC_INSTANCE} - public_instance: false - - # If your instance owns a /etc/searxng/settings.yml file, then set the following - # values there. - - secret_key: "772ba36386fb56d0f8fe818941552dabbe69220d4c0eb4a385a5729cdbc20c2d" # Is overwritten by ${SEARXNG_SECRET} - # Proxy image results through SearXNG. Is overwritten by ${SEARXNG_IMAGE_PROXY} - image_proxy: false - # 1.0 and 1.1 are supported - http_protocol_version: "1.0" - # POST queries are more secure as they don't show up in history but may cause - # problems when using Firefox containers - method: "POST" - default_http_headers: - X-Content-Type-Options: nosniff - X-Download-Options: noopen - X-Robots-Tag: noindex, nofollow - Referrer-Policy: no-referrer - -redis: - # URL to connect redis database. Is overwritten by ${SEARXNG_REDIS_URL}. - # https://docs.searxng.org/admin/settings/settings_redis.html#settings-redis - url: false - -ui: - # Custom static path - leave it blank if you didn't change - static_path: "" - # Is overwritten by ${SEARXNG_STATIC_USE_HASH}. - static_use_hash: false - # Custom templates path - leave it blank if you didn't change - templates_path: "" - # query_in_title: When true, the result page's titles contains the query - # it decreases the privacy, since the browser can records the page titles. - query_in_title: false - # infinite_scroll: When true, automatically loads the next page when scrolling to bottom of the current page. - infinite_scroll: false - # ui theme - default_theme: simple - # center the results ? - center_alignment: false - # URL prefix of the internet archive, don't forget trailing slash (if needed). - # cache_url: "https://webcache.googleusercontent.com/search?q=cache:" - # Default interface locale - leave blank to detect from browser information or - # use codes from the 'locales' config section - default_locale: "" - # Open result links in a new tab by default - # results_on_new_tab: false - theme_args: - # style of simple theme: auto, light, dark - simple_style: auto - # Perform search immediately if a category selected. - # Disable to select multiple categories at once and start the search manually. - search_on_category_select: true - # Hotkeys: default or vim - hotkeys: default - -# Lock arbitrary settings on the preferences page. To find the ID of the user -# setting you want to lock, check the ID of the form on the page "preferences". -# -# preferences: -# lock: -# - language -# - autocomplete -# - method -# - query_in_title - -# searx supports result proxification using an external service: -# https://github.com/asciimoo/morty uncomment below section if you have running -# morty proxy the key is base64 encoded (keep the !!binary notation) -# Note: since commit af77ec3, morty accepts a base64 encoded key. -# -# result_proxy: -# url: http://127.0.0.1:3000/ -# # the key is a base64 encoded string, the YAML !!binary prefix is optional -# key: !!binary "your_morty_proxy_key" -# # [true|false] enable the "proxy" button next to each result -# proxify_results: true - -# communication with search engines -# -outgoing: - # default timeout in seconds, can be override by engine - request_timeout: 3.0 - # the maximum timeout in seconds - # max_request_timeout: 10.0 - # suffix of searx_useragent, could contain information like an email address - # to the administrator - useragent_suffix: "" - # The maximum number of concurrent connections that may be established. - pool_connections: 100 - # Allow the connection pool to maintain keep-alive connections below this - # point. - pool_maxsize: 20 - # See https://www.python-httpx.org/http2/ - enable_http2: true - # uncomment below section if you want to use a custom server certificate - # see https://www.python-httpx.org/advanced/#changing-the-verification-defaults - # and https://www.python-httpx.org/compatibility/#ssl-configuration - # verify: ~/.mitmproxy/mitmproxy-ca-cert.cer - # - # uncomment below section if you want to use a proxyq see: SOCKS proxies - # https://2.python-requests.org/en/latest/user/advanced/#proxies - # are also supported: see - # https://2.python-requests.org/en/latest/user/advanced/#socks - # - # proxies: - # all://: - # - http://host.docker.internal:1080 - # - # using_tor_proxy: true - # - # Extra seconds to add in order to account for the time taken by the proxy - # - # extra_proxy_timeout: 10 - # - # uncomment below section only if you have more than one network interface - # which can be the source of outgoing search requests - # - # source_ips: - # - 1.1.1.1 - # - 1.1.1.2 - # - fe80::/126 - -# External plugin configuration, for more details see -# https://docs.searxng.org/dev/plugins.html -# -# plugins: -# - plugin1 -# - plugin2 -# - ... - -# Comment or un-comment plugin to activate / deactivate by default. -# -# enabled_plugins: -# # these plugins are enabled if nothing is configured .. -# - 'Hash plugin' -# - 'Self Information' -# - 'Tracker URL remover' -# - 'Ahmia blacklist' # activation depends on outgoing.using_tor_proxy -# # these plugins are disabled if nothing is configured .. -# - 'Hostnames plugin' # see 'hostnames' configuration below -# - 'Basic Calculator' -# - 'Open Access DOI rewrite' -# - 'Tor check plugin' -# # Read the docs before activate: auto-detection of the language could be -# # detrimental to users expectations / users can activate the plugin in the -# # preferences if they want. -# - 'Autodetect search language' - -# Configuration of the "Hostnames plugin": -# -# hostnames: -# replace: -# '(.*\.)?youtube\.com$': 'invidious.example.com' -# '(.*\.)?youtu\.be$': 'invidious.example.com' -# '(.*\.)?reddit\.com$': 'teddit.example.com' -# '(.*\.)?redd\.it$': 'teddit.example.com' -# '(www\.)?twitter\.com$': 'nitter.example.com' -# remove: -# - '(.*\.)?facebook.com$' -# low_priority: -# - '(.*\.)?google(\..*)?$' -# high_priority: -# - '(.*\.)?wikipedia.org$' -# -# Alternatively you can use external files for configuring the "Hostnames plugin": -# -# hostnames: -# replace: 'rewrite-hosts.yml' -# -# Content of 'rewrite-hosts.yml' (place the file in the same directory as 'settings.yml'): -# '(.*\.)?youtube\.com$': 'invidious.example.com' -# '(.*\.)?youtu\.be$': 'invidious.example.com' -# - -checker: - # disable checker when in debug mode - off_when_debug: true - - # use "scheduling: false" to disable scheduling - # scheduling: interval or int - - # to activate the scheduler: - # * uncomment "scheduling" section - # * add "cache2 = name=searxngcache,items=2000,blocks=2000,blocksize=4096,bitmap=1" - # to your uwsgi.ini - - # scheduling: - # start_after: [300, 1800] # delay to start the first run of the checker - # every: [86400, 90000] # how often the checker runs - - # additional tests: only for the YAML anchors (see the engines section) - # - additional_tests: - rosebud: &test_rosebud - matrix: - query: rosebud - lang: en - result_container: - - not_empty - - ['one_title_contains', 'citizen kane'] - test: - - unique_results - - android: &test_android - matrix: - query: ['android'] - lang: ['en', 'de', 'fr', 'zh-CN'] - result_container: - - not_empty - - ['one_title_contains', 'google'] - test: - - unique_results - - # tests: only for the YAML anchors (see the engines section) - tests: - infobox: &tests_infobox - infobox: - matrix: - query: ["linux", "new york", "bbc"] - result_container: - - has_infobox - -categories_as_tabs: - general: - images: - videos: - news: - map: - music: - it: - science: - files: - social media: - -engines: - - name: 9gag - engine: 9gag - shortcut: 9g - disabled: true - - - name: alpine linux packages - engine: alpinelinux - disabled: true - shortcut: alp - - - name: annas archive - engine: annas_archive - disabled: true - shortcut: aa - - # - name: annas articles - # engine: annas_archive - # shortcut: aaa - # # https://docs.searxng.org/dev/engines/online/annas_archive.html - # aa_content: 'magazine' # book_fiction, book_unknown, book_nonfiction, book_comic - # aa_ext: 'pdf' # pdf, epub, .. - # aa_sort: oldest' # newest, oldest, largest, smallest - - - name: apk mirror - engine: apkmirror - timeout: 4.0 - shortcut: apkm - disabled: true - - - name: apple app store - engine: apple_app_store - shortcut: aps - disabled: true - - # Requires Tor - - name: ahmia - engine: ahmia - categories: onions - enable_http: true - shortcut: ah - - - name: anaconda - engine: xpath - paging: true - first_page_num: 0 - search_url: https://anaconda.org/search?q={query}&page={pageno} - results_xpath: //tbody/tr - url_xpath: ./td/h5/a[last()]/@href - title_xpath: ./td/h5 - content_xpath: ./td[h5]/text() - categories: it - timeout: 6.0 - shortcut: conda - disabled: true - - - name: arch linux wiki - engine: archlinux - shortcut: al - - - name: artic - engine: artic - shortcut: arc - timeout: 4.0 - - - name: arxiv - engine: arxiv - shortcut: arx - timeout: 4.0 - - - name: ask - engine: ask - shortcut: ask - disabled: true - - # tmp suspended: dh key too small - # - name: base - # engine: base - # shortcut: bs - - - name: bandcamp - engine: bandcamp - shortcut: bc - categories: music - - - name: wikipedia - engine: wikipedia - shortcut: wp - # add "list" to the array to get results in the results list - display_type: ["infobox"] - base_url: 'https://{language}.wikipedia.org/' - categories: [general] - - - name: bilibili - engine: bilibili - shortcut: bil - disabled: true - - - name: bing - engine: bing - shortcut: bi - disabled: false - - - name: bing images - engine: bing_images - shortcut: bii - - - name: bing news - engine: bing_news - shortcut: bin - - - name: bing videos - engine: bing_videos - shortcut: biv - - - name: bitbucket - engine: xpath - paging: true - search_url: https://bitbucket.org/repo/all/{pageno}?name={query} - url_xpath: //article[@class="repo-summary"]//a[@class="repo-link"]/@href - title_xpath: //article[@class="repo-summary"]//a[@class="repo-link"] - content_xpath: //article[@class="repo-summary"]/p - categories: [it, repos] - timeout: 4.0 - disabled: true - shortcut: bb - about: - website: https://bitbucket.org/ - wikidata_id: Q2493781 - official_api_documentation: https://developer.atlassian.com/bitbucket - use_official_api: false - require_api_key: false - results: HTML - - - name: bpb - engine: bpb - shortcut: bpb - disabled: true - - - name: btdigg - engine: btdigg - shortcut: bt - disabled: true - - - name: openverse - engine: openverse - categories: images - shortcut: opv - - - name: media.ccc.de - engine: ccc_media - shortcut: c3tv - # We don't set language: de here because media.ccc.de is not just - # for a German audience. It contains many English videos and many - # German videos have English subtitles. - disabled: true - - - name: chefkoch - engine: chefkoch - shortcut: chef - # to show premium or plus results too: - # skip_premium: false - - # - name: core.ac.uk - # engine: core - # categories: science - # shortcut: cor - # # get your API key from: https://core.ac.uk/api-keys/register/ - # api_key: 'unset' - - - name: cppreference - engine: cppreference - shortcut: cpp - paging: false - disabled: true - - - name: crossref - engine: crossref - shortcut: cr - timeout: 30 - disabled: true - - - name: crowdview - engine: json_engine - shortcut: cv - categories: general - paging: false - search_url: https://crowdview-next-js.onrender.com/api/search-v3?query={query} - results_query: results - url_query: link - title_query: title - content_query: snippet - disabled: true - about: - website: https://crowdview.ai/ - - - name: yep - engine: yep - shortcut: yep - categories: general - search_type: web - timeout: 5 - disabled: true - - - name: yep images - engine: yep - shortcut: yepi - categories: images - search_type: images - disabled: true - - - name: yep news - engine: yep - shortcut: yepn - categories: news - search_type: news - disabled: true - - - name: curlie - engine: xpath - shortcut: cl - categories: general - disabled: true - paging: true - lang_all: '' - search_url: https://curlie.org/search?q={query}&lang={lang}&start={pageno}&stime=92452189 - page_size: 20 - results_xpath: //div[@id="site-list-content"]/div[@class="site-item"] - url_xpath: ./div[@class="title-and-desc"]/a/@href - title_xpath: ./div[@class="title-and-desc"]/a/div - content_xpath: ./div[@class="title-and-desc"]/div[@class="site-descr"] - about: - website: https://curlie.org/ - wikidata_id: Q60715723 - use_official_api: false - require_api_key: false - results: HTML - - - name: currency - engine: currency_convert - categories: general - shortcut: cc - - - name: bahnhof - engine: json_engine - search_url: https://www.bahnhof.de/api/stations/search/{query} - url_prefix: https://www.bahnhof.de/ - url_query: slug - title_query: name - content_query: state - shortcut: bf - disabled: true - about: - website: https://www.bahn.de - wikidata_id: Q22811603 - use_official_api: false - require_api_key: false - results: JSON - language: de - tests: - bahnhof: - matrix: - query: berlin - lang: en - result_container: - - not_empty - - ['one_title_contains', 'Berlin Hauptbahnhof'] - test: - - unique_results - - - name: deezer - engine: deezer - shortcut: dz - disabled: true - - - name: destatis - engine: destatis - shortcut: destat - disabled: true - - - name: deviantart - engine: deviantart - shortcut: da - timeout: 3.0 - - - name: ddg definitions - engine: duckduckgo_definitions - shortcut: ddd - weight: 2 - disabled: true - tests: *tests_infobox - - # cloudflare protected - # - name: digbt - # engine: digbt - # shortcut: dbt - # timeout: 6.0 - # disabled: true - - - name: docker hub - engine: docker_hub - shortcut: dh - categories: [it, packages] - - - name: encyclosearch - engine: json_engine - shortcut: es - categories: general - paging: true - search_url: https://encyclosearch.org/encyclosphere/search?q={query}&page={pageno}&resultsPerPage=15 - results_query: Results - url_query: SourceURL - title_query: Title - content_query: Description - disabled: true - about: - website: https://encyclosearch.org - official_api_documentation: https://encyclosearch.org/docs/#/rest-api - use_official_api: true - require_api_key: false - results: JSON - - - name: erowid - engine: xpath - paging: true - first_page_num: 0 - page_size: 30 - search_url: https://www.erowid.org/search.php?q={query}&s={pageno} - url_xpath: //dl[@class="results-list"]/dt[@class="result-title"]/a/@href - title_xpath: //dl[@class="results-list"]/dt[@class="result-title"]/a/text() - content_xpath: //dl[@class="results-list"]/dd[@class="result-details"] - categories: [] - shortcut: ew - disabled: true - about: - website: https://www.erowid.org/ - wikidata_id: Q1430691 - official_api_documentation: - use_official_api: false - require_api_key: false - results: HTML - - # - name: elasticsearch - # shortcut: es - # engine: elasticsearch - # base_url: http://localhost:9200 - # username: elastic - # password: changeme - # index: my-index - # # available options: match, simple_query_string, term, terms, custom - # query_type: match - # # if query_type is set to custom, provide your query here - # #custom_query_json: {"query":{"match_all": {}}} - # #show_metadata: false - # disabled: true - - - name: wikidata - engine: wikidata - shortcut: wd - timeout: 3.0 - weight: 2 - # add "list" to the array to get results in the results list - display_type: ["infobox"] - tests: *tests_infobox - categories: [general] - - - name: duckduckgo - engine: duckduckgo - shortcut: ddg - - - name: duckduckgo images - engine: duckduckgo_extra - categories: [images, web] - ddg_category: images - shortcut: ddi - disabled: true - - - name: duckduckgo videos - engine: duckduckgo_extra - categories: [videos, web] - ddg_category: videos - shortcut: ddv - disabled: true - - - name: duckduckgo news - engine: duckduckgo_extra - categories: [news, web] - ddg_category: news - shortcut: ddn - disabled: true - - - name: duckduckgo weather - engine: duckduckgo_weather - shortcut: ddw - disabled: true - - - name: apple maps - engine: apple_maps - shortcut: apm - disabled: true - timeout: 5.0 - - - name: emojipedia - engine: emojipedia - timeout: 4.0 - shortcut: em - disabled: true - - - name: tineye - engine: tineye - shortcut: tin - timeout: 9.0 - disabled: true - - - name: etymonline - engine: xpath - paging: true - search_url: https://etymonline.com/search?page={pageno}&q={query} - url_xpath: //a[contains(@class, "word__name--")]/@href - title_xpath: //a[contains(@class, "word__name--")] - content_xpath: //section[contains(@class, "word__defination")] - first_page_num: 1 - shortcut: et - categories: [dictionaries] - about: - website: https://www.etymonline.com/ - wikidata_id: Q1188617 - official_api_documentation: - use_official_api: false - require_api_key: false - results: HTML - - # - name: ebay - # engine: ebay - # shortcut: eb - # base_url: 'https://www.ebay.com' - # disabled: true - # timeout: 5 - - - name: 1x - engine: www1x - shortcut: 1x - timeout: 3.0 - disabled: true - - - name: fdroid - engine: fdroid - shortcut: fd - disabled: true - - - name: findthatmeme - engine: findthatmeme - shortcut: ftm - disabled: true - - - name: flickr - categories: images - shortcut: fl - # You can use the engine using the official stable API, but you need an API - # key, see: https://www.flickr.com/services/apps/create/ - # engine: flickr - # api_key: 'apikey' # required! - # Or you can use the html non-stable engine, activated by default - engine: flickr_noapi - - - name: free software directory - engine: mediawiki - shortcut: fsd - categories: [it, software wikis] - base_url: https://directory.fsf.org/ - search_type: title - timeout: 5.0 - disabled: true - about: - website: https://directory.fsf.org/ - wikidata_id: Q2470288 - - # - name: freesound - # engine: freesound - # shortcut: fnd - # disabled: true - # timeout: 15.0 - # API key required, see: https://freesound.org/docs/api/overview.html - # api_key: MyAPIkey - - - name: frinkiac - engine: frinkiac - shortcut: frk - disabled: true - - - name: fyyd - engine: fyyd - shortcut: fy - timeout: 8.0 - disabled: true - - - name: geizhals - engine: geizhals - shortcut: geiz - disabled: true - - - name: genius - engine: genius - shortcut: gen - - - name: gentoo - engine: mediawiki - shortcut: ge - categories: ["it", "software wikis"] - base_url: "https://wiki.gentoo.org/" - api_path: "api.php" - search_type: text - timeout: 10 - - - name: gitlab - engine: json_engine - paging: true - search_url: https://gitlab.com/api/v4/projects?search={query}&page={pageno} - url_query: web_url - title_query: name_with_namespace - content_query: description - page_size: 20 - categories: [it, repos] - shortcut: gl - timeout: 10.0 - disabled: true - about: - website: https://about.gitlab.com/ - wikidata_id: Q16639197 - official_api_documentation: https://docs.gitlab.com/ee/api/ - use_official_api: false - require_api_key: false - results: JSON - - - name: github - engine: github - shortcut: gh - - - name: codeberg - # https://docs.searxng.org/dev/engines/online/gitea.html - engine: gitea - base_url: https://codeberg.org - shortcut: cb - disabled: true - - - name: gitea.com - engine: gitea - base_url: https://gitea.com - shortcut: gitea - disabled: true - - - name: goodreads - engine: goodreads - shortcut: good - timeout: 4.0 - disabled: true - - - name: google - engine: google - shortcut: go - # additional_tests: - # android: *test_android - - - name: google images - engine: google_images - shortcut: goi - # additional_tests: - # android: *test_android - # dali: - # matrix: - # query: ['Dali Christ'] - # lang: ['en', 'de', 'fr', 'zh-CN'] - # result_container: - # - ['one_title_contains', 'Salvador'] - - - name: google news - engine: google_news - shortcut: gon - # additional_tests: - # android: *test_android - - - name: google videos - engine: google_videos - shortcut: gov - # additional_tests: - # android: *test_android - - - name: google scholar - engine: google_scholar - shortcut: gos - - - name: google play apps - engine: google_play - categories: [files, apps] - shortcut: gpa - play_categ: apps - disabled: true - - - name: google play movies - engine: google_play - categories: videos - shortcut: gpm - play_categ: movies - disabled: true - - - name: material icons - engine: material_icons - categories: images - shortcut: mi - disabled: true - - - name: gpodder - engine: json_engine - shortcut: gpod - timeout: 4.0 - paging: false - search_url: https://gpodder.net/search.json?q={query} - url_query: url - title_query: title - content_query: description - page_size: 19 - categories: music - disabled: true - about: - website: https://gpodder.net - wikidata_id: Q3093354 - official_api_documentation: https://gpoddernet.readthedocs.io/en/latest/api/ - use_official_api: false - requires_api_key: false - results: JSON - - - name: habrahabr - engine: xpath - paging: true - search_url: https://habr.com/en/search/page{pageno}/?q={query} - results_xpath: //article[contains(@class, "tm-articles-list__item")] - url_xpath: .//a[@class="tm-title__link"]/@href - title_xpath: .//a[@class="tm-title__link"] - content_xpath: .//div[contains(@class, "article-formatted-body")] - categories: it - timeout: 4.0 - disabled: true - shortcut: habr - about: - website: https://habr.com/ - wikidata_id: Q4494434 - official_api_documentation: https://habr.com/en/docs/help/api/ - use_official_api: false - require_api_key: false - results: HTML - - - name: hackernews - engine: hackernews - shortcut: hn - disabled: true - - - name: hex - engine: hex - shortcut: hex - disabled: true - # Valid values: name inserted_at updated_at total_downloads recent_downloads - sort_criteria: "recent_downloads" - page_size: 10 - - - name: crates.io - engine: crates - shortcut: crates - disabled: true - timeout: 6.0 - - - name: hoogle - engine: xpath - search_url: https://hoogle.haskell.org/?hoogle={query} - results_xpath: '//div[@class="result"]' - title_xpath: './/div[@class="ans"]//a' - url_xpath: './/div[@class="ans"]//a/@href' - content_xpath: './/div[@class="from"]' - page_size: 20 - categories: [it, packages] - shortcut: ho - about: - website: https://hoogle.haskell.org/ - wikidata_id: Q34010 - official_api_documentation: https://hackage.haskell.org/api - use_official_api: false - require_api_key: false - results: JSON - - - name: imdb - engine: imdb - shortcut: imdb - timeout: 6.0 - disabled: true - - - name: imgur - engine: imgur - shortcut: img - disabled: true - - - name: ina - engine: ina - shortcut: in - timeout: 6.0 - disabled: true - - - name: invidious - engine: invidious - # Instanes will be selected randomly, see https://api.invidious.io/ for - # instances that are stable (good uptime) and close to you. - base_url: - - https://invidious.io.lol - - https://invidious.fdn.fr - - https://yt.artemislena.eu - - https://invidious.tiekoetter.com - - https://invidious.flokinet.to - - https://vid.puffyan.us - - https://invidious.privacydev.net - - https://inv.tux.pizza - shortcut: iv - timeout: 3.0 - disabled: true - - - name: jisho - engine: jisho - shortcut: js - timeout: 3.0 - disabled: true - - - name: kickass - engine: kickass - base_url: - - https://kickasstorrents.to - - https://kickasstorrents.cr - - https://kickasstorrent.cr - - https://kickass.sx - - https://kat.am - shortcut: kc - timeout: 4.0 - disabled: true - - - name: lemmy communities - engine: lemmy - lemmy_type: Communities - shortcut: leco - - - name: lemmy users - engine: lemmy - network: lemmy communities - lemmy_type: Users - shortcut: leus - - - name: lemmy posts - engine: lemmy - network: lemmy communities - lemmy_type: Posts - shortcut: lepo - - - name: lemmy comments - engine: lemmy - network: lemmy communities - lemmy_type: Comments - shortcut: lecom - - - name: library genesis - engine: xpath - # search_url: https://libgen.is/search.php?req={query} - search_url: https://libgen.rs/search.php?req={query} - url_xpath: //a[contains(@href,"book/index.php?md5")]/@href - title_xpath: //a[contains(@href,"book/")]/text()[1] - content_xpath: //td/a[1][contains(@href,"=author")]/text() - categories: files - timeout: 7.0 - disabled: true - shortcut: lg - about: - website: https://libgen.fun/ - wikidata_id: Q22017206 - official_api_documentation: - use_official_api: false - require_api_key: false - results: HTML - - - name: z-library - engine: zlibrary - shortcut: zlib - categories: files - timeout: 7.0 - disabled: true - - - name: library of congress - engine: loc - shortcut: loc - categories: images - - - name: libretranslate - engine: libretranslate - # https://github.com/LibreTranslate/LibreTranslate?tab=readme-ov-file#mirrors - base_url: - - https://translate.terraprint.co - - https://trans.zillyhuhn.com - # api_key: abc123 - shortcut: lt - disabled: true - - - name: lingva - engine: lingva - shortcut: lv - # set lingva instance in url, by default it will use the official instance - # url: https://lingva.thedaviddelta.com - - - name: lobste.rs - engine: xpath - search_url: https://lobste.rs/search?q={query}&what=stories&order=relevance - results_xpath: //li[contains(@class, "story")] - url_xpath: .//a[@class="u-url"]/@href - title_xpath: .//a[@class="u-url"] - content_xpath: .//a[@class="domain"] - categories: it - shortcut: lo - timeout: 5.0 - disabled: true - about: - website: https://lobste.rs/ - wikidata_id: Q60762874 - official_api_documentation: - use_official_api: false - require_api_key: false - results: HTML - - - name: mastodon users - engine: mastodon - mastodon_type: accounts - base_url: https://mastodon.social - shortcut: mau - - - name: mastodon hashtags - engine: mastodon - mastodon_type: hashtags - base_url: https://mastodon.social - shortcut: mah - - # - name: matrixrooms - # engine: mrs - # # https://docs.searxng.org/dev/engines/online/mrs.html - # # base_url: https://mrs-api-host - # shortcut: mtrx - # disabled: true - - - name: mdn - shortcut: mdn - engine: json_engine - categories: [it] - paging: true - search_url: https://developer.mozilla.org/api/v1/search?q={query}&page={pageno} - results_query: documents - url_query: mdn_url - url_prefix: https://developer.mozilla.org - title_query: title - content_query: summary - about: - website: https://developer.mozilla.org - wikidata_id: Q3273508 - official_api_documentation: null - use_official_api: false - require_api_key: false - results: JSON - - - name: metacpan - engine: metacpan - shortcut: cpan - disabled: true - number_of_results: 20 - - # - name: meilisearch - # engine: meilisearch - # shortcut: mes - # enable_http: true - # base_url: http://localhost:7700 - # index: my-index - - - name: mixcloud - engine: mixcloud - shortcut: mc - - # MongoDB engine - # Required dependency: pymongo - # - name: mymongo - # engine: mongodb - # shortcut: md - # exact_match_only: false - # host: '127.0.0.1' - # port: 27017 - # enable_http: true - # results_per_page: 20 - # database: 'business' - # collection: 'reviews' # name of the db collection - # key: 'name' # key in the collection to search for - - - name: mozhi - engine: mozhi - base_url: - - https://mozhi.aryak.me - - https://translate.bus-hit.me - - https://nyc1.mz.ggtyler.dev - # mozhi_engine: google - see https://mozhi.aryak.me for supported engines - timeout: 4.0 - shortcut: mz - disabled: true - - - name: mwmbl - engine: mwmbl - # api_url: https://api.mwmbl.org - shortcut: mwm - disabled: true - - - name: npm - engine: npm - shortcut: npm - timeout: 5.0 - disabled: true - - - name: nyaa - engine: nyaa - shortcut: nt - disabled: true - - - name: mankier - engine: json_engine - search_url: https://www.mankier.com/api/v2/mans/?q={query} - results_query: results - url_query: url - title_query: name - content_query: description - categories: it - shortcut: man - about: - website: https://www.mankier.com/ - official_api_documentation: https://www.mankier.com/api - use_official_api: true - require_api_key: false - results: JSON - - # read https://docs.searxng.org/dev/engines/online/mullvad_leta.html - # - name: mullvadleta - # engine: mullvad_leta - # leta_engine: google # choose one of the following: google, brave - # use_cache: true # Only 100 non-cache searches per day, suggested only for private instances - # search_url: https://leta.mullvad.net - # categories: [general, web] - # shortcut: ml - - - name: odysee - engine: odysee - shortcut: od - disabled: true - - - name: openairedatasets - engine: json_engine - paging: true - search_url: https://api.openaire.eu/search/datasets?format=json&page={pageno}&size=10&title={query} - results_query: response/results/result - url_query: metadata/oaf:entity/oaf:result/children/instance/webresource/url/$ - title_query: metadata/oaf:entity/oaf:result/title/$ - content_query: metadata/oaf:entity/oaf:result/description/$ - content_html_to_text: true - categories: "science" - shortcut: oad - timeout: 5.0 - about: - website: https://www.openaire.eu/ - wikidata_id: Q25106053 - official_api_documentation: https://api.openaire.eu/ - use_official_api: false - require_api_key: false - results: JSON - - - name: openairepublications - engine: json_engine - paging: true - search_url: https://api.openaire.eu/search/publications?format=json&page={pageno}&size=10&title={query} - results_query: response/results/result - url_query: metadata/oaf:entity/oaf:result/children/instance/webresource/url/$ - title_query: metadata/oaf:entity/oaf:result/title/$ - content_query: metadata/oaf:entity/oaf:result/description/$ - content_html_to_text: true - categories: science - shortcut: oap - timeout: 5.0 - about: - website: https://www.openaire.eu/ - wikidata_id: Q25106053 - official_api_documentation: https://api.openaire.eu/ - use_official_api: false - require_api_key: false - results: JSON - - - name: openmeteo - engine: open_meteo - shortcut: om - disabled: true - - # - name: opensemanticsearch - # engine: opensemantic - # shortcut: oss - # base_url: 'http://localhost:8983/solr/opensemanticsearch/' - - - name: openstreetmap - engine: openstreetmap - shortcut: osm - - - name: openrepos - engine: xpath - paging: true - search_url: https://openrepos.net/search/node/{query}?page={pageno} - url_xpath: //li[@class="search-result"]//h3[@class="title"]/a/@href - title_xpath: //li[@class="search-result"]//h3[@class="title"]/a - content_xpath: //li[@class="search-result"]//div[@class="search-snippet-info"]//p[@class="search-snippet"] - categories: files - timeout: 4.0 - disabled: true - shortcut: or - about: - website: https://openrepos.net/ - wikidata_id: - official_api_documentation: - use_official_api: false - require_api_key: false - results: HTML - - - name: packagist - engine: json_engine - paging: true - search_url: https://packagist.org/search.json?q={query}&page={pageno} - results_query: results - url_query: url - title_query: name - content_query: description - categories: [it, packages] - disabled: true - timeout: 5.0 - shortcut: pack - about: - website: https://packagist.org - wikidata_id: Q108311377 - official_api_documentation: https://packagist.org/apidoc - use_official_api: true - require_api_key: false - results: JSON - - - name: pdbe - engine: pdbe - shortcut: pdb - # Hide obsolete PDB entries. Default is not to hide obsolete structures - # hide_obsolete: false - - - name: photon - engine: photon - shortcut: ph - - - name: pinterest - engine: pinterest - shortcut: pin - - - name: piped - engine: piped - shortcut: ppd - categories: videos - piped_filter: videos - timeout: 3.0 - - # URL to use as link and for embeds - frontend_url: https://srv.piped.video - # Instance will be selected randomly, for more see https://piped-instances.kavin.rocks/ - backend_url: - - https://pipedapi.kavin.rocks - - https://pipedapi-libre.kavin.rocks - - https://pipedapi.adminforge.de - - - name: piped.music - engine: piped - network: piped - shortcut: ppdm - categories: music - piped_filter: music_songs - timeout: 3.0 - - - name: piratebay - engine: piratebay - shortcut: tpb - # You may need to change this URL to a proxy if piratebay is blocked in your - # country - url: https://thepiratebay.org/ - timeout: 3.0 - - - name: pixiv - shortcut: pv - engine: pixiv - disabled: true - inactive: true - pixiv_image_proxies: - - https://pximg.example.org - # A proxy is required to load the images. Hosting an image proxy server - # for Pixiv: - # --> https://pixivfe.pages.dev/hosting-image-proxy-server/ - # Proxies from public instances. Ask the public instances owners if they - # agree to receive traffic from SearXNG! - # --> https://codeberg.org/VnPower/PixivFE#instances - # --> https://github.com/searxng/searxng/pull/3192#issuecomment-1941095047 - # image proxy of https://pixiv.cat - # - https://i.pixiv.cat - # image proxy of https://www.pixiv.pics - # - https://pximg.cocomi.eu.org - # image proxy of https://pixivfe.exozy.me - # - https://pximg.exozy.me - # image proxy of https://pixivfe.ducks.party - # - https://pixiv.ducks.party - # image proxy of https://pixiv.perennialte.ch - # - https://pximg.perennialte.ch - - - name: podcastindex - engine: podcastindex - shortcut: podcast - - # Required dependency: psychopg2 - # - name: postgresql - # engine: postgresql - # database: postgres - # username: postgres - # password: postgres - # limit: 10 - # query_str: 'SELECT * from my_table WHERE my_column = %(query)s' - # shortcut : psql - - - name: presearch - engine: presearch - search_type: search - categories: [general, web] - shortcut: ps - timeout: 4.0 - disabled: true - - - name: presearch images - engine: presearch - network: presearch - search_type: images - categories: [images, web] - timeout: 4.0 - shortcut: psimg - disabled: true - - - name: presearch videos - engine: presearch - network: presearch - search_type: videos - categories: [general, web] - timeout: 4.0 - shortcut: psvid - disabled: true - - - name: presearch news - engine: presearch - network: presearch - search_type: news - categories: [news, web] - timeout: 4.0 - shortcut: psnews - disabled: true - - - name: pub.dev - engine: xpath - shortcut: pd - search_url: https://pub.dev/packages?q={query}&page={pageno} - paging: true - results_xpath: //div[contains(@class,"packages-item")] - url_xpath: ./div/h3/a/@href - title_xpath: ./div/h3/a - content_xpath: ./div/div/div[contains(@class,"packages-description")]/span - categories: [packages, it] - timeout: 3.0 - disabled: true - first_page_num: 1 - about: - website: https://pub.dev/ - official_api_documentation: https://pub.dev/help/api - use_official_api: false - require_api_key: false - results: HTML - - - name: pubmed - engine: pubmed - shortcut: pub - timeout: 3.0 - - - name: pypi - shortcut: pypi - engine: pypi - - - name: qwant - qwant_categ: web - engine: qwant - disabled: true - shortcut: qw - categories: [general, web] - additional_tests: - rosebud: *test_rosebud - - - name: qwant news - qwant_categ: news - engine: qwant - shortcut: qwn - categories: news - network: qwant - - - name: qwant images - qwant_categ: images - engine: qwant - shortcut: qwi - categories: [images, web] - network: qwant - - - name: qwant videos - qwant_categ: videos - engine: qwant - shortcut: qwv - categories: [videos, web] - network: qwant - - # - name: library - # engine: recoll - # shortcut: lib - # base_url: 'https://recoll.example.org/' - # search_dir: '' - # mount_prefix: /export - # dl_prefix: 'https://download.example.org' - # timeout: 30.0 - # categories: files - # disabled: true - - # - name: recoll library reference - # engine: recoll - # base_url: 'https://recoll.example.org/' - # search_dir: reference - # mount_prefix: /export - # dl_prefix: 'https://download.example.org' - # shortcut: libr - # timeout: 30.0 - # categories: files - # disabled: true - - - name: radio browser - engine: radio_browser - shortcut: rb - - - name: reddit - engine: reddit - shortcut: re - page_size: 25 - disabled: true - - - name: rottentomatoes - engine: rottentomatoes - shortcut: rt - disabled: true - - # Required dependency: redis - # - name: myredis - # shortcut : rds - # engine: redis_server - # exact_match_only: false - # host: '127.0.0.1' - # port: 6379 - # enable_http: true - # password: '' - # db: 0 - - # tmp suspended: bad certificate - # - name: scanr structures - # shortcut: scs - # engine: scanr_structures - # disabled: true - - - name: searchmysite - engine: xpath - shortcut: sms - categories: general - paging: true - search_url: https://searchmysite.net/search/?q={query}&page={pageno} - results_xpath: //div[contains(@class,'search-result')] - url_xpath: .//a[contains(@class,'result-link')]/@href - title_xpath: .//span[contains(@class,'result-title-txt')]/text() - content_xpath: ./p[@id='result-hightlight'] - disabled: true - about: - website: https://searchmysite.net - - - name: sepiasearch - engine: sepiasearch - shortcut: sep - - - name: soundcloud - engine: soundcloud - shortcut: sc - - - name: stackoverflow - engine: stackexchange - shortcut: st - api_site: 'stackoverflow' - categories: [it, q&a] - - - name: askubuntu - engine: stackexchange - shortcut: ubuntu - api_site: 'askubuntu' - categories: [it, q&a] - - - name: internetarchivescholar - engine: internet_archive_scholar - shortcut: ias - timeout: 15.0 - - - name: superuser - engine: stackexchange - shortcut: su - api_site: 'superuser' - categories: [it, q&a] - - - name: discuss.python - engine: discourse - shortcut: dpy - base_url: 'https://discuss.python.org' - categories: [it, q&a] - disabled: true - - - name: caddy.community - engine: discourse - shortcut: caddy - base_url: 'https://caddy.community' - categories: [it, q&a] - disabled: true - - - name: pi-hole.community - engine: discourse - shortcut: pi - categories: [it, q&a] - base_url: 'https://discourse.pi-hole.net' - disabled: true - - - name: searchcode code - engine: searchcode_code - shortcut: scc - disabled: true - - # - name: searx - # engine: searx_engine - # shortcut: se - # instance_urls : - # - http://127.0.0.1:8888/ - # - ... - # disabled: true - - - name: semantic scholar - engine: semantic_scholar - disabled: true - shortcut: se - - # Spotify needs API credentials - # - name: spotify - # engine: spotify - # shortcut: stf - # api_client_id: ******* - # api_client_secret: ******* - - # - name: solr - # engine: solr - # shortcut: slr - # base_url: http://localhost:8983 - # collection: collection_name - # sort: '' # sorting: asc or desc - # field_list: '' # comma separated list of field names to display on the UI - # default_fields: '' # default field to query - # query_fields: '' # query fields - # enable_http: true - - # - name: springer nature - # engine: springer - # # get your API key from: https://dev.springernature.com/signup - # # working API key, for test & debug: "a69685087d07eca9f13db62f65b8f601" - # api_key: 'unset' - # shortcut: springer - # timeout: 15.0 - - - name: startpage - engine: startpage - shortcut: sp - timeout: 6.0 - disabled: true - additional_tests: - rosebud: *test_rosebud - - - name: tokyotoshokan - engine: tokyotoshokan - shortcut: tt - timeout: 6.0 - disabled: true - - - name: solidtorrents - engine: solidtorrents - shortcut: solid - timeout: 4.0 - base_url: - - https://solidtorrents.to - - https://bitsearch.to - - # For this demo of the sqlite engine download: - # https://liste.mediathekview.de/filmliste-v2.db.bz2 - # and unpack into searx/data/filmliste-v2.db - # Query to test: "!demo concert" - # - # - name: demo - # engine: sqlite - # shortcut: demo - # categories: general - # result_template: default.html - # database: searx/data/filmliste-v2.db - # query_str: >- - # SELECT title || ' (' || time(duration, 'unixepoch') || ')' AS title, - # COALESCE( NULLIF(url_video_hd,''), NULLIF(url_video_sd,''), url_video) AS url, - # description AS content - # FROM film - # WHERE title LIKE :wildcard OR description LIKE :wildcard - # ORDER BY duration DESC - - - name: tagesschau - engine: tagesschau - # when set to false, display URLs from Tagesschau, and not the actual source - # (e.g. NDR, WDR, SWR, HR, ...) - use_source_url: true - shortcut: ts - disabled: true - - - name: tmdb - engine: xpath - paging: true - categories: movies - search_url: https://www.themoviedb.org/search?page={pageno}&query={query} - results_xpath: //div[contains(@class,"movie") or contains(@class,"tv")]//div[contains(@class,"card")] - url_xpath: .//div[contains(@class,"poster")]/a/@href - thumbnail_xpath: .//img/@src - title_xpath: .//div[contains(@class,"title")]//h2 - content_xpath: .//div[contains(@class,"overview")] - shortcut: tm - disabled: true - - # Requires Tor - - name: torch - engine: xpath - paging: true - search_url: - http://xmh57jrknzkhv6y3ls3ubitzfqnkrwxhopf5aygthi7d6rplyvk3noyd.onion/cgi-bin/omega/omega?P={query}&DEFAULTOP=and - results_xpath: //table//tr - url_xpath: ./td[2]/a - title_xpath: ./td[2]/b - content_xpath: ./td[2]/small - categories: onions - enable_http: true - shortcut: tch - - # torznab engine lets you query any torznab compatible indexer. Using this - # engine in combination with Jackett opens the possibility to query a lot of - # public and private indexers directly from SearXNG. More details at: - # https://docs.searxng.org/dev/engines/online/torznab.html - # - # - name: Torznab EZTV - # engine: torznab - # shortcut: eztv - # base_url: http://localhost:9117/api/v2.0/indexers/eztv/results/torznab - # enable_http: true # if using localhost - # api_key: xxxxxxxxxxxxxxx - # show_magnet_links: true - # show_torrent_files: false - # # https://github.com/Jackett/Jackett/wiki/Jackett-Categories - # torznab_categories: # optional - # - 2000 - # - 5000 - - # tmp suspended - too slow, too many errors - # - name: urbandictionary - # engine : xpath - # search_url : https://www.urbandictionary.com/define.php?term={query} - # url_xpath : //*[@class="word"]/@href - # title_xpath : //*[@class="def-header"] - # content_xpath: //*[@class="meaning"] - # shortcut: ud - - - name: unsplash - engine: unsplash - shortcut: us - - - name: yandex music - engine: yandex_music - shortcut: ydm - disabled: true - # https://yandex.com/support/music/access.html - inactive: true - - - name: yahoo - engine: yahoo - shortcut: yh - disabled: true - - - name: yahoo news - engine: yahoo_news - shortcut: yhn - - - name: youtube - shortcut: yt - # You can use the engine using the official stable API, but you need an API - # key See: https://console.developers.google.com/project - # - # engine: youtube_api - # api_key: 'apikey' # required! - # - # Or you can use the html non-stable engine, activated by default - engine: youtube_noapi - - - name: dailymotion - engine: dailymotion - shortcut: dm - - - name: vimeo - engine: vimeo - shortcut: vm - disabled: true - - - name: wiby - engine: json_engine - paging: true - search_url: https://wiby.me/json/?q={query}&p={pageno} - url_query: URL - title_query: Title - content_query: Snippet - categories: [general, web] - shortcut: wib - disabled: true - about: - website: https://wiby.me/ - - - name: alexandria - engine: json_engine - shortcut: alx - categories: general - paging: true - search_url: https://api.alexandria.org/?a=1&q={query}&p={pageno} - results_query: results - title_query: title - url_query: url - content_query: snippet - timeout: 1.5 - disabled: true - about: - website: https://alexandria.org/ - official_api_documentation: https://github.com/alexandria-org/alexandria-api/raw/master/README.md - use_official_api: true - require_api_key: false - results: JSON - - - name: wikibooks - engine: mediawiki - weight: 0.5 - shortcut: wb - categories: [general, wikimedia] - base_url: "https://{language}.wikibooks.org/" - search_type: text - disabled: true - about: - website: https://www.wikibooks.org/ - wikidata_id: Q367 - - - name: wikinews - engine: mediawiki - shortcut: wn - categories: [news, wikimedia] - base_url: "https://{language}.wikinews.org/" - search_type: text - srsort: create_timestamp_desc - about: - website: https://www.wikinews.org/ - wikidata_id: Q964 - - - name: wikiquote - engine: mediawiki - weight: 0.5 - shortcut: wq - categories: [general, wikimedia] - base_url: "https://{language}.wikiquote.org/" - search_type: text - disabled: true - additional_tests: - rosebud: *test_rosebud - about: - website: https://www.wikiquote.org/ - wikidata_id: Q369 - - - name: wikisource - engine: mediawiki - weight: 0.5 - shortcut: ws - categories: [general, wikimedia] - base_url: "https://{language}.wikisource.org/" - search_type: text - disabled: true - about: - website: https://www.wikisource.org/ - wikidata_id: Q263 - - - name: wikispecies - engine: mediawiki - shortcut: wsp - categories: [general, science, wikimedia] - base_url: "https://species.wikimedia.org/" - search_type: text - disabled: true - about: - website: https://species.wikimedia.org/ - wikidata_id: Q13679 - tests: - wikispecies: - matrix: - query: "Campbell, L.I. et al. 2011: MicroRNAs" - lang: en - result_container: - - not_empty - - ['one_title_contains', 'Tardigrada'] - test: - - unique_results - - - name: wiktionary - engine: mediawiki - shortcut: wt - categories: [dictionaries, wikimedia] - base_url: "https://{language}.wiktionary.org/" - search_type: text - about: - website: https://www.wiktionary.org/ - wikidata_id: Q151 - - - name: wikiversity - engine: mediawiki - weight: 0.5 - shortcut: wv - categories: [general, wikimedia] - base_url: "https://{language}.wikiversity.org/" - search_type: text - disabled: true - about: - website: https://www.wikiversity.org/ - wikidata_id: Q370 - - - name: wikivoyage - engine: mediawiki - weight: 0.5 - shortcut: wy - categories: [general, wikimedia] - base_url: "https://{language}.wikivoyage.org/" - search_type: text - disabled: true - about: - website: https://www.wikivoyage.org/ - wikidata_id: Q373 - - - name: wikicommons.images - engine: wikicommons - shortcut: wc - categories: images - search_type: images - number_of_results: 10 - - - name: wikicommons.videos - engine: wikicommons - shortcut: wcv - categories: videos - search_type: videos - number_of_results: 10 - - - name: wikicommons.audio - engine: wikicommons - shortcut: wca - categories: music - search_type: audio - number_of_results: 10 - - - name: wikicommons.files - engine: wikicommons - shortcut: wcf - categories: files - search_type: files - number_of_results: 10 - - - name: wolframalpha - shortcut: wa - # You can use the engine using the official stable API, but you need an API - # key. See: https://products.wolframalpha.com/api/ - # - # engine: wolframalpha_api - # api_key: '' - # - # Or you can use the html non-stable engine, activated by default - engine: wolframalpha_noapi - timeout: 6.0 - categories: general - disabled: true - - - name: dictzone - engine: dictzone - shortcut: dc - - - name: mymemory translated - engine: translated - shortcut: tl - timeout: 5.0 - # You can use without an API key, but you are limited to 1000 words/day - # See: https://mymemory.translated.net/doc/usagelimits.php - # api_key: '' - - # Required dependency: mysql-connector-python - # - name: mysql - # engine: mysql_server - # database: mydatabase - # username: user - # password: pass - # limit: 10 - # query_str: 'SELECT * from mytable WHERE fieldname=%(query)s' - # shortcut: mysql - - - name: 1337x - engine: 1337x - shortcut: 1337x - disabled: true - - - name: duden - engine: duden - shortcut: du - disabled: true - - - name: seznam - shortcut: szn - engine: seznam - disabled: true - - # - name: deepl - # engine: deepl - # shortcut: dpl - # # You can use the engine using the official stable API, but you need an API key - # # See: https://www.deepl.com/pro-api?cta=header-pro-api - # api_key: '' # required! - # timeout: 5.0 - # disabled: true - - - name: mojeek - shortcut: mjk - engine: mojeek - categories: [general, web] - disabled: true - - - name: mojeek images - shortcut: mjkimg - engine: mojeek - categories: [images, web] - search_type: images - paging: false - disabled: true - - - name: mojeek news - shortcut: mjknews - engine: mojeek - categories: [news, web] - search_type: news - paging: false - disabled: true - - - name: moviepilot - engine: moviepilot - shortcut: mp - disabled: true - - - name: naver - shortcut: nvr - categories: [general, web] - engine: xpath - paging: true - search_url: https://search.naver.com/search.naver?where=webkr&sm=osp_hty&ie=UTF-8&query={query}&start={pageno} - url_xpath: //a[@class="link_tit"]/@href - title_xpath: //a[@class="link_tit"] - content_xpath: //div[@class="total_dsc_wrap"]/a - first_page_num: 1 - page_size: 10 - disabled: true - about: - website: https://www.naver.com/ - wikidata_id: Q485639 - official_api_documentation: https://developers.naver.com/docs/nmt/examples/ - use_official_api: false - require_api_key: false - results: HTML - language: ko - - - name: rubygems - shortcut: rbg - engine: xpath - paging: true - search_url: https://rubygems.org/search?page={pageno}&query={query} - results_xpath: /html/body/main/div/a[@class="gems__gem"] - url_xpath: ./@href - title_xpath: ./span/h2 - content_xpath: ./span/p - suggestion_xpath: /html/body/main/div/div[@class="search__suggestions"]/p/a - first_page_num: 1 - categories: [it, packages] - disabled: true - about: - website: https://rubygems.org/ - wikidata_id: Q1853420 - official_api_documentation: https://guides.rubygems.org/rubygems-org-api/ - use_official_api: false - require_api_key: false - results: HTML - - - name: peertube - engine: peertube - shortcut: ptb - paging: true - # alternatives see: https://instances.joinpeertube.org/instances - # base_url: https://tube.4aem.com - categories: videos - disabled: true - timeout: 6.0 - - - name: mediathekviewweb - engine: mediathekviewweb - shortcut: mvw - disabled: true - - - name: yacy - # https://docs.searxng.org/dev/engines/online/yacy.html - engine: yacy - categories: general - search_type: text - base_url: - - https://yacy.searchlab.eu - # see https://github.com/searxng/searxng/pull/3631#issuecomment-2240903027 - # - https://search.kyun.li - # - https://yacy.securecomcorp.eu - # - https://yacy.myserv.ca - # - https://yacy.nsupdate.info - # - https://yacy.electroncash.de - shortcut: ya - disabled: true - # if you aren't using HTTPS for your local yacy instance disable https - # enable_http: false - search_mode: 'global' - # timeout can be reduced in 'local' search mode - timeout: 5.0 - - - name: yacy images - engine: yacy - network: yacy - categories: images - search_type: image - shortcut: yai - disabled: true - # timeout can be reduced in 'local' search mode - timeout: 5.0 - - - name: rumble - engine: rumble - shortcut: ru - base_url: https://rumble.com/ - paging: true - categories: videos - disabled: true - - - name: livespace - engine: livespace - shortcut: ls - categories: videos - disabled: true - timeout: 5.0 - - - name: wordnik - engine: wordnik - shortcut: def - base_url: https://www.wordnik.com/ - categories: [dictionaries] - timeout: 5.0 - - - name: woxikon.de synonyme - engine: xpath - shortcut: woxi - categories: [dictionaries] - timeout: 5.0 - disabled: true - search_url: https://synonyme.woxikon.de/synonyme/{query}.php - url_xpath: //div[@class="upper-synonyms"]/a/@href - content_xpath: //div[@class="synonyms-list-group"] - title_xpath: //div[@class="upper-synonyms"]/a - no_result_for_http_status: [404] - about: - website: https://www.woxikon.de/ - wikidata_id: # No Wikidata ID - use_official_api: false - require_api_key: false - results: HTML - language: de - - - name: seekr news - engine: seekr - shortcut: senews - categories: news - seekr_category: news - disabled: true - - - name: seekr images - engine: seekr - network: seekr news - shortcut: seimg - categories: images - seekr_category: images - disabled: true - - - name: seekr videos - engine: seekr - network: seekr news - shortcut: sevid - categories: videos - seekr_category: videos - disabled: true - - - name: sjp.pwn - engine: sjp - shortcut: sjp - base_url: https://sjp.pwn.pl/ - timeout: 5.0 - disabled: true - - - name: stract - engine: stract - shortcut: str - disabled: true - - - name: svgrepo - engine: svgrepo - shortcut: svg - timeout: 10.0 - disabled: true - - - name: tootfinder - engine: tootfinder - shortcut: toot - - - name: voidlinux - engine: voidlinux - shortcut: void - disabled: true - - - name: wallhaven - engine: wallhaven - # api_key: abcdefghijklmnopqrstuvwxyz - shortcut: wh - - # wikimini: online encyclopedia for children - # The fulltext and title parameter is necessary for Wikimini because - # sometimes it will not show the results and redirect instead - - name: wikimini - engine: xpath - shortcut: wkmn - search_url: https://fr.wikimini.org/w/index.php?search={query}&title=Sp%C3%A9cial%3ASearch&fulltext=Search - url_xpath: //li/div[@class="mw-search-result-heading"]/a/@href - title_xpath: //li//div[@class="mw-search-result-heading"]/a - content_xpath: //li/div[@class="searchresult"] - categories: general - disabled: true - about: - website: https://wikimini.org/ - wikidata_id: Q3568032 - use_official_api: false - require_api_key: false - results: HTML - language: fr - - - name: wttr.in - engine: wttr - shortcut: wttr - timeout: 9.0 - - - name: yummly - engine: yummly - shortcut: yum - disabled: true - - - name: brave - engine: brave - shortcut: br - time_range_support: true - paging: true - categories: [general, web] - brave_category: search - # brave_spellcheck: true - - - name: brave.images - engine: brave - network: brave - shortcut: brimg - categories: [images, web] - brave_category: images - - - name: brave.videos - engine: brave - network: brave - shortcut: brvid - categories: [videos, web] - brave_category: videos - - - name: brave.news - engine: brave - network: brave - shortcut: brnews - categories: news - brave_category: news - - # - name: brave.goggles - # engine: brave - # network: brave - # shortcut: brgog - # time_range_support: true - # paging: true - # categories: [general, web] - # brave_category: goggles - # Goggles: # required! This should be a URL ending in .goggle - - - name: lib.rs - shortcut: lrs - engine: lib_rs - disabled: true - - - name: sourcehut - shortcut: srht - engine: xpath - paging: true - search_url: https://sr.ht/projects?page={pageno}&search={query} - results_xpath: (//div[@class="event-list"])[1]/div[@class="event"] - url_xpath: ./h4/a[2]/@href - title_xpath: ./h4/a[2] - content_xpath: ./p - first_page_num: 1 - categories: [it, repos] - disabled: true - about: - website: https://sr.ht - wikidata_id: Q78514485 - official_api_documentation: https://man.sr.ht/ - use_official_api: false - require_api_key: false - results: HTML - - - name: goo - shortcut: goo - engine: xpath - paging: true - search_url: https://search.goo.ne.jp/web.jsp?MT={query}&FR={pageno}0 - url_xpath: //div[@class="result"]/p[@class='title fsL1']/a/@href - title_xpath: //div[@class="result"]/p[@class='title fsL1']/a - content_xpath: //p[contains(@class,'url fsM')]/following-sibling::p - first_page_num: 0 - categories: [general, web] - disabled: true - timeout: 4.0 - about: - website: https://search.goo.ne.jp - wikidata_id: Q249044 - use_official_api: false - require_api_key: false - results: HTML - language: ja - - - name: bt4g - engine: bt4g - shortcut: bt4g - - - name: pkg.go.dev - engine: pkg_go_dev - shortcut: pgo - disabled: true - -# Doku engine lets you access to any Doku wiki instance: -# A public one or a privete/corporate one. -# - name: ubuntuwiki -# engine: doku -# shortcut: uw -# base_url: 'https://doc.ubuntu-fr.org' - -# Be careful when enabling this engine if you are -# running a public instance. Do not expose any sensitive -# information. You can restrict access by configuring a list -# of access tokens under tokens. -# - name: git grep -# engine: command -# command: ['git', 'grep', '{{QUERY}}'] -# shortcut: gg -# tokens: [] -# disabled: true -# delimiter: -# chars: ':' -# keys: ['filepath', 'code'] - -# Be careful when enabling this engine if you are -# running a public instance. Do not expose any sensitive -# information. You can restrict access by configuring a list -# of access tokens under tokens. -# - name: locate -# engine: command -# command: ['locate', '{{QUERY}}'] -# shortcut: loc -# tokens: [] -# disabled: true -# delimiter: -# chars: ' ' -# keys: ['line'] - -# Be careful when enabling this engine if you are -# running a public instance. Do not expose any sensitive -# information. You can restrict access by configuring a list -# of access tokens under tokens. -# - name: find -# engine: command -# command: ['find', '.', '-name', '{{QUERY}}'] -# query_type: path -# shortcut: fnd -# tokens: [] -# disabled: true -# delimiter: -# chars: ' ' -# keys: ['line'] - -# Be careful when enabling this engine if you are -# running a public instance. Do not expose any sensitive -# information. You can restrict access by configuring a list -# of access tokens under tokens. -# - name: pattern search in files -# engine: command -# command: ['fgrep', '{{QUERY}}'] -# shortcut: fgr -# tokens: [] -# disabled: true -# delimiter: -# chars: ' ' -# keys: ['line'] - -# Be careful when enabling this engine if you are -# running a public instance. Do not expose any sensitive -# information. You can restrict access by configuring a list -# of access tokens under tokens. -# - name: regex search in files -# engine: command -# command: ['grep', '{{QUERY}}'] -# shortcut: gr -# tokens: [] -# disabled: true -# delimiter: -# chars: ' ' -# keys: ['line'] - -doi_resolvers: - oadoi.org: 'https://oadoi.org/' - doi.org: 'https://doi.org/' - doai.io: 'https://dissem.in/' - sci-hub.se: 'https://sci-hub.se/' - sci-hub.st: 'https://sci-hub.st/' - sci-hub.ru: 'https://sci-hub.ru/' - -default_doi_resolver: 'oadoi.org' diff --git a/api/core/tools/provider/builtin/searxng/docker/uwsgi.ini b/api/core/tools/provider/builtin/searxng/docker/uwsgi.ini deleted file mode 100644 index 9db3d762649fc5..00000000000000 --- a/api/core/tools/provider/builtin/searxng/docker/uwsgi.ini +++ /dev/null @@ -1,54 +0,0 @@ -[uwsgi] -# Who will run the code -uid = searxng -gid = searxng - -# Number of workers (usually CPU count) -# default value: %k (= number of CPU core, see Dockerfile) -workers = %k - -# Number of threads per worker -# default value: 4 (see Dockerfile) -threads = 4 - -# The right granted on the created socket -chmod-socket = 666 - -# Plugin to use and interpreter config -single-interpreter = true -master = true -plugin = python3 -lazy-apps = true -enable-threads = 4 - -# Module to import -module = searx.webapp - -# Virtualenv and python path -pythonpath = /usr/local/searxng/ -chdir = /usr/local/searxng/searx/ - -# automatically set processes name to something meaningful -auto-procname = true - -# Disable request logging for privacy -disable-logging = true -log-5xx = true - -# Set the max size of a request (request-body excluded) -buffer-size = 8192 - -# No keep alive -# See https://github.com/searx/searx-docker/issues/24 -add-header = Connection: close - -# Follow SIGTERM convention -# See https://github.com/searxng/searxng/issues/3427 -die-on-term - -# uwsgi serves the static files -static-map = /static=/usr/local/searxng/searx/static -# expires set to one day -static-expires = /* 86400 -static-gzip-all = True -offload-threads = 4 diff --git a/api/core/tools/provider/builtin/searxng/searxng.py b/api/core/tools/provider/builtin/searxng/searxng.py deleted file mode 100644 index b7bbcc60b1ed26..00000000000000 --- a/api/core/tools/provider/builtin/searxng/searxng.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.searxng.tools.searxng_search import SearXNGSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class SearXNGProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - SearXNGSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={"query": "SearXNG", "limit": 1, "search_type": "general"}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/searxng/searxng.yaml b/api/core/tools/provider/builtin/searxng/searxng.yaml deleted file mode 100644 index 9554c93d5a0c53..00000000000000 --- a/api/core/tools/provider/builtin/searxng/searxng.yaml +++ /dev/null @@ -1,24 +0,0 @@ -identity: - author: Junytang - name: searxng - label: - en_US: SearXNG - zh_Hans: SearXNG - description: - en_US: A free internet metasearch engine. - zh_Hans: 开源免费的互联网元搜索引擎 - icon: icon.svg - tags: - - search - - productivity -credentials_for_provider: - searxng_base_url: - type: text-input - required: true - label: - en_US: SearXNG base URL - zh_Hans: SearXNG base URL - placeholder: - en_US: Please input your SearXNG base URL - zh_Hans: 请输入您的 SearXNG base URL - url: https://docs.dify.ai/tutorials/tool-configuration/searxng diff --git a/api/core/tools/provider/builtin/searxng/tools/searxng_search.py b/api/core/tools/provider/builtin/searxng/tools/searxng_search.py deleted file mode 100644 index c5e339a108e5b2..00000000000000 --- a/api/core/tools/provider/builtin/searxng/tools/searxng_search.py +++ /dev/null @@ -1,46 +0,0 @@ -from typing import Any - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class SearXNGSearchTool(BuiltinTool): - """ - Tool for performing a search using SearXNG engine. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: - """ - Invoke the SearXNG search tool. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Any]): The parameters for the tool invocation. - - Returns: - ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation. - """ - - host = self.runtime.credentials.get("searxng_base_url") - if not host: - raise Exception("SearXNG api is required") - - response = requests.get( - host, - params={ - "q": tool_parameters.get("query"), - "format": "json", - "categories": tool_parameters.get("search_type", "general"), - }, - ) - - if response.status_code != 200: - raise Exception(f"Error {response.status_code}: {response.text}") - - res = response.json().get("results", []) - if not res: - return self.create_text_message(f"No results found, get response: {response.content}") - - return [self.create_json_message(item) for item in res] diff --git a/api/core/tools/provider/builtin/searxng/tools/searxng_search.yaml b/api/core/tools/provider/builtin/searxng/tools/searxng_search.yaml deleted file mode 100644 index a5e448a30375b4..00000000000000 --- a/api/core/tools/provider/builtin/searxng/tools/searxng_search.yaml +++ /dev/null @@ -1,69 +0,0 @@ -identity: - name: searxng_search - author: Junytang - label: - en_US: SearXNG Search - zh_Hans: SearXNG 搜索 -description: - human: - en_US: SearXNG is a free internet metasearch engine which aggregates results from more than 70 search services. - zh_Hans: SearXNG 是一个免费的互联网元搜索引擎，它从70多个不同的搜索服务中聚合搜索结果。 - llm: Perform searches on SearXNG and get results. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - llm_description: Key words for searching - form: llm - - name: search_type - type: select - required: true - label: - en_US: search type - zh_Hans: 搜索类型 - default: general - options: - - value: general - label: - en_US: General - zh_Hans: 综合 - - value: images - label: - en_US: Images - zh_Hans: 图片 - - value: videos - label: - en_US: Videos - zh_Hans: 视频 - - value: news - label: - en_US: News - zh_Hans: 新闻 - - value: map - label: - en_US: Map - zh_Hans: 地图 - - value: music - label: - en_US: Music - zh_Hans: 音乐 - - value: it - label: - en_US: It - zh_Hans: 信息技术 - - value: science - label: - en_US: Science - zh_Hans: 科学 - - value: files - label: - en_US: Files - zh_Hans: 文件 - - value: social_media - label: - en_US: Social Media - zh_Hans: 社交媒体 - form: form diff --git a/api/core/tools/provider/builtin/serper/_assets/icon.svg b/api/core/tools/provider/builtin/serper/_assets/icon.svg deleted file mode 100644 index 3f973a552e5e17..00000000000000 --- a/api/core/tools/provider/builtin/serper/_assets/icon.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - serper - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/serper/serper.py b/api/core/tools/provider/builtin/serper/serper.py deleted file mode 100644 index cb1d090a9dd4b0..00000000000000 --- a/api/core/tools/provider/builtin/serper/serper.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.serper.tools.serper_search import SerperSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class SerperProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - SerperSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={"query": "test", "result_type": "link"}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/serper/serper.yaml b/api/core/tools/provider/builtin/serper/serper.yaml deleted file mode 100644 index b3b2d76c4b6573..00000000000000 --- a/api/core/tools/provider/builtin/serper/serper.yaml +++ /dev/null @@ -1,31 +0,0 @@ -identity: - author: zhuhao - name: serper - label: - en_US: Serper - zh_Hans: Serper - pt_BR: Serper - description: - en_US: Serper is a powerful real-time search engine tool API that provides structured data from Google Search. - zh_Hans: Serper 是一个强大的实时搜索引擎工具API，可提供来自 Google 搜索引擎搜索的结构化数据。 - pt_BR: Serper is a powerful real-time search engine tool API that provides structured data from Google Search. - icon: icon.svg - tags: - - search -credentials_for_provider: - serperapi_api_key: - type: secret-input - required: true - label: - en_US: Serper API key - zh_Hans: Serper API key - pt_BR: Serper API key - placeholder: - en_US: Please input your Serper API key - zh_Hans: 请输入你的 Serper API key - pt_BR: Please input your Serper API key - help: - en_US: Get your Serper API key from Serper - zh_Hans: 从 Serper 获取您的 Serper API key - pt_BR: Get your Serper API key from Serper - url: https://serper.dev/api-key diff --git a/api/core/tools/provider/builtin/serper/tools/serper_search.py b/api/core/tools/provider/builtin/serper/tools/serper_search.py deleted file mode 100644 index 7baebbf95855e0..00000000000000 --- a/api/core/tools/provider/builtin/serper/tools/serper_search.py +++ /dev/null @@ -1,34 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -SERPER_API_URL = "https://google.serper.dev/search" - - -class SerperSearchTool(BuiltinTool): - def _parse_response(self, response: dict) -> dict: - result = {} - if "knowledgeGraph" in response: - result["title"] = response["knowledgeGraph"].get("title", "") - result["description"] = response["knowledgeGraph"].get("description", "") - if "organic" in response: - result["organic"] = [ - {"title": item.get("title", ""), "link": item.get("link", ""), "snippet": item.get("snippet", "")} - for item in response["organic"] - ] - return result - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - params = {"q": tool_parameters["query"], "gl": "us", "hl": "en"} - headers = {"X-API-KEY": self.runtime.credentials["serperapi_api_key"], "Content-Type": "application/json"} - response = requests.get(url=SERPER_API_URL, params=params, headers=headers) - response.raise_for_status() - valuable_res = self._parse_response(response.json()) - return self.create_json_message(valuable_res) diff --git a/api/core/tools/provider/builtin/serper/tools/serper_search.yaml b/api/core/tools/provider/builtin/serper/tools/serper_search.yaml deleted file mode 100644 index e1c0a056e65513..00000000000000 --- a/api/core/tools/provider/builtin/serper/tools/serper_search.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: serper - author: zhuhao - label: - en_US: Serper - zh_Hans: Serper - pt_BR: Serper -description: - human: - en_US: A tool for performing a Google search and extracting snippets and webpages.Input should be a search query. - zh_Hans: 一个用于执行 Google 搜索并提取片段和网页的工具。输入应该是一个搜索查询。 - pt_BR: A tool for performing a Google search and extracting snippets and webpages.Input should be a search query. - llm: A tool for performing a Google search and extracting snippets and webpages.Input should be a search query. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - pt_BR: Query string - human_description: - en_US: used for searching - zh_Hans: 用于搜索网页内容 - pt_BR: used for searching - llm_description: key words for searching - form: llm diff --git a/api/core/tools/provider/builtin/siliconflow/_assets/icon.svg b/api/core/tools/provider/builtin/siliconflow/_assets/icon.svg deleted file mode 100644 index ad6b384f7acd21..00000000000000 --- a/api/core/tools/provider/builtin/siliconflow/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/siliconflow/siliconflow.py b/api/core/tools/provider/builtin/siliconflow/siliconflow.py deleted file mode 100644 index 37a0b0755b1d39..00000000000000 --- a/api/core/tools/provider/builtin/siliconflow/siliconflow.py +++ /dev/null @@ -1,17 +0,0 @@ -import requests - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class SiliconflowProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - url = "https://api.siliconflow.cn/v1/models" - headers = { - "accept": "application/json", - "authorization": f"Bearer {credentials.get('siliconFlow_api_key')}", - } - - response = requests.get(url, headers=headers) - if response.status_code != 200: - raise ToolProviderCredentialValidationError("SiliconFlow API key is invalid") diff --git a/api/core/tools/provider/builtin/siliconflow/siliconflow.yaml b/api/core/tools/provider/builtin/siliconflow/siliconflow.yaml deleted file mode 100644 index 46be99f262f211..00000000000000 --- a/api/core/tools/provider/builtin/siliconflow/siliconflow.yaml +++ /dev/null @@ -1,21 +0,0 @@ -identity: - author: hjlarry - name: siliconflow - label: - en_US: SiliconFlow - zh_CN: 硅基流动 - description: - en_US: The image generation API provided by SiliconFlow includes Flux and Stable Diffusion models. - zh_CN: 硅基流动提供的图片生成 API，包含 Flux 和 Stable Diffusion 模型。 - icon: icon.svg - tags: - - image -credentials_for_provider: - siliconFlow_api_key: - type: secret-input - required: true - label: - en_US: SiliconFlow API Key - placeholder: - en_US: Please input your SiliconFlow API key - url: https://cloud.siliconflow.cn/account/ak diff --git a/api/core/tools/provider/builtin/siliconflow/tools/flux.py b/api/core/tools/provider/builtin/siliconflow/tools/flux.py deleted file mode 100644 index 0d16ff385eb30d..00000000000000 --- a/api/core/tools/provider/builtin/siliconflow/tools/flux.py +++ /dev/null @@ -1,43 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -FLUX_URL = { - "schnell": "https://api.siliconflow.cn/v1/black-forest-labs/FLUX.1-schnell/text-to-image", - "dev": "https://api.siliconflow.cn/v1/image/generations", -} - - -class FluxTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - headers = { - "accept": "application/json", - "content-type": "application/json", - "authorization": f"Bearer {self.runtime.credentials['siliconFlow_api_key']}", - } - - payload = { - "prompt": tool_parameters.get("prompt"), - "image_size": tool_parameters.get("image_size", "1024x1024"), - "seed": tool_parameters.get("seed"), - "num_inference_steps": tool_parameters.get("num_inference_steps", 20), - } - model = tool_parameters.get("model", "schnell") - url = FLUX_URL.get(model) - if model == "dev": - payload["model"] = "black-forest-labs/FLUX.1-dev" - - response = requests.post(url, json=payload, headers=headers) - if response.status_code != 200: - return self.create_text_message(f"Got Error Response:{response.text}") - - res = response.json() - result = [self.create_json_message(res)] - for image in res.get("images", []): - result.append(self.create_image_message(image=image.get("url"), save_as=self.VariableKey.IMAGE.value)) - return result diff --git a/api/core/tools/provider/builtin/siliconflow/tools/flux.yaml b/api/core/tools/provider/builtin/siliconflow/tools/flux.yaml deleted file mode 100644 index d06b9bf3e1f489..00000000000000 --- a/api/core/tools/provider/builtin/siliconflow/tools/flux.yaml +++ /dev/null @@ -1,88 +0,0 @@ -identity: - name: flux - author: hjlarry - label: - en_US: Flux - icon: icon.svg -description: - human: - en_US: Generate image via SiliconFlow's flux model. - llm: This tool is used to generate image from prompt via SiliconFlow's flux model. -parameters: - - name: prompt - type: string - required: true - label: - en_US: prompt - zh_Hans: 提示词 - human_description: - en_US: The text prompt used to generate the image. - zh_Hans: 建议用英文的生成图片提示词以获得更好的生成效果。 - llm_description: this prompt text will be used to generate image. - form: llm - - name: model - type: select - required: true - options: - - value: schnell - label: - en_US: Flux.1-schnell - - value: dev - label: - en_US: Flux.1-dev - default: schnell - label: - en_US: Choose Image Model - zh_Hans: 选择生成图片的模型 - form: form - - name: image_size - type: select - required: true - options: - - value: 1024x1024 - label: - en_US: 1024x1024 - - value: 768x1024 - label: - en_US: 768x1024 - - value: 576x1024 - label: - en_US: 576x1024 - - value: 512x1024 - label: - en_US: 512x1024 - - value: 1024x576 - label: - en_US: 1024x576 - - value: 768x512 - label: - en_US: 768x512 - default: 1024x1024 - label: - en_US: Choose Image Size - zh_Hans: 选择生成的图片大小 - form: form - - name: num_inference_steps - type: number - required: true - default: 20 - min: 1 - max: 100 - label: - en_US: Num Inference Steps - zh_Hans: 生成图片的步数 - form: form - human_description: - en_US: The number of inference steps to perform. More steps produce higher quality but take longer. - zh_Hans: 执行的推理步骤数量。更多的步骤可以产生更高质量的结果，但需要更长的时间。 - - name: seed - type: number - min: 0 - max: 9999999999 - label: - en_US: Seed - zh_Hans: 种子 - human_description: - en_US: The same seed and prompt can produce similar images. - zh_Hans: 相同的种子和提示可以产生相似的图像。 - form: form diff --git a/api/core/tools/provider/builtin/siliconflow/tools/stable_diffusion.py b/api/core/tools/provider/builtin/siliconflow/tools/stable_diffusion.py deleted file mode 100644 index d6a0b03d1b185e..00000000000000 --- a/api/core/tools/provider/builtin/siliconflow/tools/stable_diffusion.py +++ /dev/null @@ -1,45 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -SDURL = { - "sd_3": "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-3-medium/text-to-image", - "sd_xl": "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-xl-base-1.0/text-to-image", -} - - -class StableDiffusionTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - headers = { - "accept": "application/json", - "content-type": "application/json", - "authorization": f"Bearer {self.runtime.credentials['siliconFlow_api_key']}", - } - - model = tool_parameters.get("model", "sd_3") - url = SDURL.get(model) - - payload = { - "prompt": tool_parameters.get("prompt"), - "negative_prompt": tool_parameters.get("negative_prompt", ""), - "image_size": tool_parameters.get("image_size", "1024x1024"), - "batch_size": tool_parameters.get("batch_size", 1), - "seed": tool_parameters.get("seed"), - "guidance_scale": tool_parameters.get("guidance_scale", 7.5), - "num_inference_steps": tool_parameters.get("num_inference_steps", 20), - } - - response = requests.post(url, json=payload, headers=headers) - if response.status_code != 200: - return self.create_text_message(f"Got Error Response:{response.text}") - - res = response.json() - result = [self.create_json_message(res)] - for image in res.get("images", []): - result.append(self.create_image_message(image=image.get("url"), save_as=self.VariableKey.IMAGE.value)) - return result diff --git a/api/core/tools/provider/builtin/siliconflow/tools/stable_diffusion.yaml b/api/core/tools/provider/builtin/siliconflow/tools/stable_diffusion.yaml deleted file mode 100644 index dce10adc87f222..00000000000000 --- a/api/core/tools/provider/builtin/siliconflow/tools/stable_diffusion.yaml +++ /dev/null @@ -1,121 +0,0 @@ -identity: - name: stable_diffusion - author: hjlarry - label: - en_US: Stable Diffusion - icon: icon.svg -description: - human: - en_US: Generate image via SiliconFlow's stable diffusion model. - llm: This tool is used to generate image from prompt via SiliconFlow's stable diffusion model. -parameters: - - name: prompt - type: string - required: true - label: - en_US: prompt - zh_Hans: 提示词 - human_description: - en_US: The text prompt used to generate the image. - zh_Hans: 用于生成图片的文字提示词 - llm_description: this prompt text will be used to generate image. - form: llm - - name: negative_prompt - type: string - label: - en_US: negative prompt - zh_Hans: 负面提示词 - human_description: - en_US: Describe what you don't want included in the image. - zh_Hans: 描述您不希望包含在图片中的内容。 - llm_description: Describe what you don't want included in the image. - form: llm - - name: model - type: select - required: true - options: - - value: sd_3 - label: - en_US: Stable Diffusion 3 - - value: sd_xl - label: - en_US: Stable Diffusion XL - default: sd_3 - label: - en_US: Choose Image Model - zh_Hans: 选择生成图片的模型 - form: form - - name: image_size - type: select - required: true - options: - - value: 1024x1024 - label: - en_US: 1024x1024 - - value: 1024x2048 - label: - en_US: 1024x2048 - - value: 1152x2048 - label: - en_US: 1152x2048 - - value: 1536x1024 - label: - en_US: 1536x1024 - - value: 1536x2048 - label: - en_US: 1536x2048 - - value: 2048x1152 - label: - en_US: 2048x1152 - default: 1024x1024 - label: - en_US: Choose Image Size - zh_Hans: 选择生成图片的大小 - form: form - - name: batch_size - type: number - required: true - default: 1 - min: 1 - max: 4 - label: - en_US: Number Images - zh_Hans: 生成图片的数量 - form: form - - name: guidance_scale - type: number - required: true - default: 7.5 - min: 0 - max: 100 - label: - en_US: Guidance Scale - zh_Hans: 与提示词紧密性 - human_description: - en_US: Classifier Free Guidance. How close you want the model to stick to your prompt when looking for a related image to show you. - zh_Hans: 无分类器引导。您希望模型在寻找相关图片向您展示时，与您的提示保持多紧密的关联度。 - form: form - - name: num_inference_steps - type: number - required: true - default: 20 - min: 1 - max: 100 - label: - en_US: Num Inference Steps - zh_Hans: 生成图片的步数 - human_description: - en_US: The number of inference steps to perform. More steps produce higher quality but take longer. - zh_Hans: 执行的推理步骤数量。更多的步骤可以产生更高质量的结果，但需要更长的时间。 - form: form - - name: seed - type: number - min: 0 - max: 9999999999 - label: - en_US: Seed - zh_Hans: 种子 - human_description: - en_US: The same seed and prompt can produce similar images. - zh_Hans: 相同的种子和提示可以产生相似的图像。 - form: form diff --git a/api/core/tools/provider/builtin/slack/_assets/icon.svg b/api/core/tools/provider/builtin/slack/_assets/icon.svg deleted file mode 100644 index e43c2c47dc128e..00000000000000 --- a/api/core/tools/provider/builtin/slack/_assets/icon.svg +++ /dev/null @@ -1,22 +0,0 @@ - - - Slack - - - - - - - diff --git a/api/core/tools/provider/builtin/slack/slack.py b/api/core/tools/provider/builtin/slack/slack.py deleted file mode 100644 index 2de7911f63072a..00000000000000 --- a/api/core/tools/provider/builtin/slack/slack.py +++ /dev/null @@ -1,8 +0,0 @@ -from core.tools.provider.builtin.slack.tools.slack_webhook import SlackWebhookTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class SlackProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - SlackWebhookTool() - pass diff --git a/api/core/tools/provider/builtin/slack/slack.yaml b/api/core/tools/provider/builtin/slack/slack.yaml deleted file mode 100644 index 1070ffbf038a40..00000000000000 --- a/api/core/tools/provider/builtin/slack/slack.yaml +++ /dev/null @@ -1,16 +0,0 @@ -identity: - author: Pan YANG - name: slack - label: - en_US: Slack - zh_Hans: Slack - pt_BR: Slack - description: - en_US: Slack Webhook - zh_Hans: Slack Webhook - pt_BR: Slack Webhook - icon: icon.svg - tags: - - social - - productivity -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/slack/tools/slack_webhook.py b/api/core/tools/provider/builtin/slack/tools/slack_webhook.py deleted file mode 100644 index 85e0de76755898..00000000000000 --- a/api/core/tools/provider/builtin/slack/tools/slack_webhook.py +++ /dev/null @@ -1,46 +0,0 @@ -from typing import Any, Union - -import httpx - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class SlackWebhookTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Incoming Webhooks - API Document: https://api.slack.com/messaging/webhooks - """ - - content = tool_parameters.get("content", "") - if not content: - return self.create_text_message("Invalid parameter content") - - webhook_url = tool_parameters.get("webhook_url", "") - - if not webhook_url.startswith("https://hooks.slack.com/"): - return self.create_text_message( - f"Invalid parameter webhook_url ${webhook_url}, not a valid Slack webhook URL" - ) - - headers = { - "Content-Type": "application/json", - } - params = {} - payload = { - "text": content, - } - - try: - res = httpx.post(webhook_url, headers=headers, params=params, json=payload) - if res.is_success: - return self.create_text_message("Text message was sent successfully") - else: - return self.create_text_message( - f"Failed to send the text message, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to send message through webhook. {}".format(e)) diff --git a/api/core/tools/provider/builtin/slack/tools/slack_webhook.yaml b/api/core/tools/provider/builtin/slack/tools/slack_webhook.yaml deleted file mode 100644 index b838d743733ec9..00000000000000 --- a/api/core/tools/provider/builtin/slack/tools/slack_webhook.yaml +++ /dev/null @@ -1,40 +0,0 @@ -identity: - name: slack_webhook - author: Pan YANG - label: - en_US: Incoming Webhook to send message - zh_Hans: 通过入站 Webhook 发送消息 - pt_BR: Incoming Webhook to send message - icon: icon.svg -description: - human: - en_US: Sending a message on Slack via the Incoming Webhook - zh_Hans: 通过入站 Webhook 在 Slack 上发送消息 - pt_BR: Sending a message on Slack via the Incoming Webhook - llm: A tool for sending messages to a chat on Slack. -parameters: - - name: webhook_url - type: string - required: true - label: - en_US: Slack Incoming Webhook url - zh_Hans: Slack 入站 Webhook 的 url - pt_BR: Slack Incoming Webhook url - human_description: - en_US: Slack Incoming Webhook url - zh_Hans: Slack 入站 Webhook 的 url - pt_BR: Slack Incoming Webhook url - form: form - - name: content - type: string - required: true - label: - en_US: content - zh_Hans: 消息内容 - pt_BR: content - human_description: - en_US: Content to sent to the channel or person. - zh_Hans: 消息内容文本 - pt_BR: Content to sent to the channel or person. - llm_description: Content of the message - form: llm diff --git a/api/core/tools/provider/builtin/spark/__init__.py b/api/core/tools/provider/builtin/spark/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/tools/provider/builtin/spark/_assets/icon.svg b/api/core/tools/provider/builtin/spark/_assets/icon.svg deleted file mode 100644 index ef0a9131a48e43..00000000000000 --- a/api/core/tools/provider/builtin/spark/_assets/icon.svg +++ /dev/null @@ -1,5 +0,0 @@ - - - - - diff --git a/api/core/tools/provider/builtin/spark/spark.py b/api/core/tools/provider/builtin/spark/spark.py deleted file mode 100644 index e0b1a58a3f679a..00000000000000 --- a/api/core/tools/provider/builtin/spark/spark.py +++ /dev/null @@ -1,36 +0,0 @@ -import json - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.spark.tools.spark_img_generation import spark_response -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class SparkProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - if "APPID" not in credentials or not credentials.get("APPID"): - raise ToolProviderCredentialValidationError("APPID is required.") - if "APISecret" not in credentials or not credentials.get("APISecret"): - raise ToolProviderCredentialValidationError("APISecret is required.") - if "APIKey" not in credentials or not credentials.get("APIKey"): - raise ToolProviderCredentialValidationError("APIKey is required.") - - appid = credentials.get("APPID") - apisecret = credentials.get("APISecret") - apikey = credentials.get("APIKey") - prompt = "a cute black dog" - - try: - response = spark_response(prompt, appid, apikey, apisecret) - data = json.loads(response) - code = data["header"]["code"] - - if code == 0: - # 0 success， - pass - else: - raise ToolProviderCredentialValidationError("image generate error, code:{}".format(code)) - except Exception as e: - raise ToolProviderCredentialValidationError("APPID APISecret APIKey is invalid. {}".format(e)) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/spark/spark.yaml b/api/core/tools/provider/builtin/spark/spark.yaml deleted file mode 100644 index fa1543443a2af8..00000000000000 --- a/api/core/tools/provider/builtin/spark/spark.yaml +++ /dev/null @@ -1,61 +0,0 @@ -identity: - author: Onelevenvy - name: spark - label: - en_US: Spark - zh_Hans: 讯飞星火 - pt_BR: Spark - description: - en_US: Spark Platform Toolkit - zh_Hans: 讯飞星火平台工具 - pt_BR: Pacote de Ferramentas da Plataforma Spark - icon: icon.svg - tags: - - image -credentials_for_provider: - APPID: - type: secret-input - required: true - label: - en_US: Spark APPID - zh_Hans: APPID - pt_BR: Spark APPID - help: - en_US: Please input your APPID - zh_Hans: 请输入你的 APPID - pt_BR: Please input your APPID - placeholder: - en_US: Please input your APPID - zh_Hans: 请输入你的 APPID - pt_BR: Please input your APPID - APISecret: - type: secret-input - required: true - label: - en_US: Spark APISecret - zh_Hans: APISecret - pt_BR: Spark APISecret - help: - en_US: Please input your Spark APISecret - zh_Hans: 请输入你的 APISecret - pt_BR: Please input your Spark APISecret - placeholder: - en_US: Please input your Spark APISecret - zh_Hans: 请输入你的 APISecret - pt_BR: Please input your Spark APISecret - APIKey: - type: secret-input - required: true - label: - en_US: Spark APIKey - zh_Hans: APIKey - pt_BR: Spark APIKey - help: - en_US: Please input your Spark APIKey - zh_Hans: 请输入你的 APIKey - pt_BR: Please input your Spark APIKey - placeholder: - en_US: Please input your Spark APIKey - zh_Hans: 请输入你的 APIKey - pt_BR: Please input Spark APIKey - url: https://console.xfyun.cn/services diff --git a/api/core/tools/provider/builtin/spark/tools/spark_img_generation.py b/api/core/tools/provider/builtin/spark/tools/spark_img_generation.py deleted file mode 100644 index 81d9e8d94185f7..00000000000000 --- a/api/core/tools/provider/builtin/spark/tools/spark_img_generation.py +++ /dev/null @@ -1,139 +0,0 @@ -import base64 -import hashlib -import hmac -import json -from base64 import b64decode -from datetime import datetime -from time import mktime -from typing import Any, Union -from urllib.parse import urlencode -from wsgiref.handlers import format_date_time - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class AssembleHeaderError(Exception): - def __init__(self, msg): - self.message = msg - - -class Url: - def __init__(self, host, path, schema): - self.host = host - self.path = path - self.schema = schema - - -# calculate sha256 and encode to base64 -def sha256base64(data): - sha256 = hashlib.sha256() - sha256.update(data) - digest = base64.b64encode(sha256.digest()).decode(encoding="utf-8") - return digest - - -def parse_url(request_url): - stidx = request_url.index("://") - host = request_url[stidx + 3 :] - schema = request_url[: stidx + 3] - edidx = host.index("/") - if edidx <= 0: - raise AssembleHeaderError("invalid request url:" + request_url) - path = host[edidx:] - host = host[:edidx] - u = Url(host, path, schema) - return u - - -def assemble_ws_auth_url(request_url, method="GET", api_key="", api_secret=""): - u = parse_url(request_url) - host = u.host - path = u.path - now = datetime.now() - date = format_date_time(mktime(now.timetuple())) - signature_origin = "host: {}\ndate: {}\n{} {} HTTP/1.1".format(host, date, method, path) - signature_sha = hmac.new( - api_secret.encode("utf-8"), - signature_origin.encode("utf-8"), - digestmod=hashlib.sha256, - ).digest() - signature_sha = base64.b64encode(signature_sha).decode(encoding="utf-8") - authorization_origin = ( - f'api_key="{api_key}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha}"' - ) - - authorization = base64.b64encode(authorization_origin.encode("utf-8")).decode(encoding="utf-8") - values = {"host": host, "date": date, "authorization": authorization} - - return request_url + "?" + urlencode(values) - - -def get_body(appid, text): - body = { - "header": {"app_id": appid, "uid": "123456789"}, - "parameter": {"chat": {"domain": "general", "temperature": 0.5, "max_tokens": 4096}}, - "payload": {"message": {"text": [{"role": "user", "content": text}]}}, - } - return body - - -def spark_response(text, appid, apikey, apisecret): - host = "http://spark-api.cn-huabei-1.xf-yun.com/v2.1/tti" - url = assemble_ws_auth_url(host, method="POST", api_key=apikey, api_secret=apisecret) - content = get_body(appid, text) - response = requests.post(url, json=content, headers={"content-type": "application/json"}).text - return response - - -class SparkImgGeneratorTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - - if "APPID" not in self.runtime.credentials or not self.runtime.credentials.get("APPID"): - return self.create_text_message("APPID is required.") - if "APISecret" not in self.runtime.credentials or not self.runtime.credentials.get("APISecret"): - return self.create_text_message("APISecret is required.") - if "APIKey" not in self.runtime.credentials or not self.runtime.credentials.get("APIKey"): - return self.create_text_message("APIKey is required.") - - prompt = tool_parameters.get("prompt", "") - if not prompt: - return self.create_text_message("Please input prompt") - res = self.img_generation(prompt) - result = [] - for image in res: - result.append( - self.create_blob_message( - blob=b64decode(image["base64_image"]), - meta={"mime_type": "image/png"}, - save_as=self.VariableKey.IMAGE.value, - ) - ) - return result - - def img_generation(self, prompt): - response = spark_response( - text=prompt, - appid=self.runtime.credentials.get("APPID"), - apikey=self.runtime.credentials.get("APIKey"), - apisecret=self.runtime.credentials.get("APISecret"), - ) - data = json.loads(response) - code = data["header"]["code"] - if code != 0: - return self.create_text_message(f"error: {code}, {data}") - else: - text = data["payload"]["choices"]["text"] - image_content = text[0] - image_base = image_content["content"] - json_data = {"base64_image": image_base} - return [json_data] diff --git a/api/core/tools/provider/builtin/spark/tools/spark_img_generation.yaml b/api/core/tools/provider/builtin/spark/tools/spark_img_generation.yaml deleted file mode 100644 index d44bbc9564ef88..00000000000000 --- a/api/core/tools/provider/builtin/spark/tools/spark_img_generation.yaml +++ /dev/null @@ -1,36 +0,0 @@ -identity: - name: spark_img_generation - author: Onelevenvy - label: - en_US: Spark Image Generation - zh_Hans: 图片生成 - pt_BR: Geração de imagens Spark - icon: icon.svg - description: - en_US: Spark Image Generation - zh_Hans: 图片生成 - pt_BR: Geração de imagens Spark -description: - human: - en_US: Generate images based on user input, with image generation API - provided by Spark - zh_Hans: 根据用户的输入生成图片，由讯飞星火提供图片生成api - pt_BR: Gerar imagens com base na entrada do usuário, com API de geração - de imagem fornecida pela Spark - llm: spark_img_generation is a tool used to generate images from text -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: Image prompt - zh_Hans: 图像提示词 - pt_BR: Image prompt - llm_description: Image prompt of spark_img_generation tooll, you should - describe the image you want to generate as a list of words as possible - as detailed - form: llm diff --git a/api/core/tools/provider/builtin/spider/_assets/icon.svg b/api/core/tools/provider/builtin/spider/_assets/icon.svg deleted file mode 100644 index 604a09d01d7444..00000000000000 --- a/api/core/tools/provider/builtin/spider/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ -Spider v1 Logo diff --git a/api/core/tools/provider/builtin/spider/spider.py b/api/core/tools/provider/builtin/spider/spider.py deleted file mode 100644 index 5959555318722e..00000000000000 --- a/api/core/tools/provider/builtin/spider/spider.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.spider.spiderApp import Spider -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class SpiderProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - app = Spider(api_key=credentials["spider_api_key"]) - app.scrape_url(url="https://spider.cloud") - except AttributeError as e: - # Handle cases where NoneType is not iterable, which might indicate API issues - if "NoneType" in str(e) and "not iterable" in str(e): - raise ToolProviderCredentialValidationError("API is currently down, try again in 15 minutes", str(e)) - else: - raise ToolProviderCredentialValidationError("An unexpected error occurred.", str(e)) - except Exception as e: - raise ToolProviderCredentialValidationError("An unexpected error occurred.", str(e)) diff --git a/api/core/tools/provider/builtin/spider/spider.yaml b/api/core/tools/provider/builtin/spider/spider.yaml deleted file mode 100644 index 45702c85ddea24..00000000000000 --- a/api/core/tools/provider/builtin/spider/spider.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - author: William Espegren - name: spider - label: - en_US: Spider - zh_CN: Spider - description: - en_US: Spider API integration, returning LLM-ready data by scraping & crawling websites. - zh_CN: Spider API 集成，通过爬取和抓取网站返回 LLM-ready 数据。 - icon: icon.svg - tags: - - search - - utilities -credentials_for_provider: - spider_api_key: - type: secret-input - required: true - label: - en_US: Spider API Key - zh_CN: Spider API 密钥 - placeholder: - en_US: Please input your Spider API key - zh_CN: 请输入您的 Spider API 密钥 - help: - en_US: Get your Spider API key from your Spider dashboard - zh_CN: 从您的 Spider 仪表板中获取 Spider API 密钥。 - url: https://spider.cloud/ diff --git a/api/core/tools/provider/builtin/spider/spiderApp.py b/api/core/tools/provider/builtin/spider/spiderApp.py deleted file mode 100644 index 4bc446a1a092a3..00000000000000 --- a/api/core/tools/provider/builtin/spider/spiderApp.py +++ /dev/null @@ -1,221 +0,0 @@ -import os -from typing import Literal, Optional, TypedDict - -import requests - - -class RequestParamsDict(TypedDict, total=False): - url: Optional[str] - request: Optional[Literal["http", "chrome", "smart"]] - limit: Optional[int] - return_format: Optional[Literal["raw", "markdown", "html2text", "text", "bytes"]] - tld: Optional[bool] - depth: Optional[int] - cache: Optional[bool] - budget: Optional[dict[str, int]] - locale: Optional[str] - cookies: Optional[str] - stealth: Optional[bool] - headers: Optional[dict[str, str]] - anti_bot: Optional[bool] - metadata: Optional[bool] - viewport: Optional[dict[str, int]] - encoding: Optional[str] - subdomains: Optional[bool] - user_agent: Optional[str] - store_data: Optional[bool] - gpt_config: Optional[list[str]] - fingerprint: Optional[bool] - storageless: Optional[bool] - readability: Optional[bool] - proxy_enabled: Optional[bool] - respect_robots: Optional[bool] - query_selector: Optional[str] - full_resources: Optional[bool] - request_timeout: Optional[int] - run_in_background: Optional[bool] - skip_config_checks: Optional[bool] - - -class Spider: - def __init__(self, api_key: Optional[str] = None): - """ - Initialize the Spider with an API key. - - :param api_key: A string of the API key for Spider. Defaults to the SPIDER_API_KEY environment variable. - :raises ValueError: If no API key is provided. - """ - self.api_key = api_key or os.getenv("SPIDER_API_KEY") - if self.api_key is None: - raise ValueError("No API key provided") - - def api_post( - self, - endpoint: str, - data: dict, - stream: bool, - content_type: str = "application/json", - ): - """ - Send a POST request to the specified API endpoint. - - :param endpoint: The API endpoint to which the POST request is sent. - :param data: The data (dictionary) to be sent in the POST request. - :param stream: Boolean indicating if the response should be streamed. - :return: The JSON response or the raw response stream if stream is True. - """ - headers = self._prepare_headers(content_type) - response = self._post_request(f"https://api.spider.cloud/v1/{endpoint}", data, headers, stream) - - if stream: - return response - elif response.status_code == 200: - return response.json() - else: - self._handle_error(response, f"post to {endpoint}") - - def api_get(self, endpoint: str, stream: bool, content_type: str = "application/json"): - """ - Send a GET request to the specified endpoint. - - :param endpoint: The API endpoint from which to retrieve data. - :return: The JSON decoded response. - """ - headers = self._prepare_headers(content_type) - response = self._get_request(f"https://api.spider.cloud/v1/{endpoint}", headers, stream) - if response.status_code == 200: - return response.json() - else: - self._handle_error(response, f"get from {endpoint}") - - def get_credits(self): - """ - Retrieve the account's remaining credits. - - :return: JSON response containing the number of credits left. - """ - return self.api_get("credits", stream=False) - - def scrape_url( - self, - url: str, - params: Optional[RequestParamsDict] = None, - stream: bool = False, - content_type: str = "application/json", - ): - """ - Scrape data from the specified URL. - - :param url: The URL from which to scrape data. - :param params: Optional dictionary of additional parameters for the scrape request. - :return: JSON response containing the scraping results. - """ - params = params or {} - - # Add { "return_format": "markdown" } to the params if not already present - if "return_format" not in params: - params["return_format"] = "markdown" - - # Set limit to 1 - params["limit"] = 1 - - return self.api_post("crawl", {"url": url, **(params or {})}, stream, content_type) - - def crawl_url( - self, - url: str, - params: Optional[RequestParamsDict] = None, - stream: bool = False, - content_type: str = "application/json", - ): - """ - Start crawling at the specified URL. - - :param url: The URL to begin crawling. - :param params: Optional dictionary with additional parameters to customize the crawl. - :param stream: Boolean indicating if the response should be streamed. Defaults to False. - :return: JSON response or the raw response stream if streaming enabled. - """ - params = params or {} - - # Add { "return_format": "markdown" } to the params if not already present - if "return_format" not in params: - params["return_format"] = "markdown" - - return self.api_post("crawl", {"url": url, **(params or {})}, stream, content_type) - - def links( - self, - url: str, - params: Optional[RequestParamsDict] = None, - stream: bool = False, - content_type: str = "application/json", - ): - """ - Retrieve links from the specified URL. - - :param url: The URL from which to extract links. - :param params: Optional parameters for the link retrieval request. - :return: JSON response containing the links. - """ - return self.api_post("links", {"url": url, **(params or {})}, stream, content_type) - - def extract_contacts( - self, - url: str, - params: Optional[RequestParamsDict] = None, - stream: bool = False, - content_type: str = "application/json", - ): - """ - Extract contact information from the specified URL. - - :param url: The URL from which to extract contact information. - :param params: Optional parameters for the contact extraction. - :return: JSON response containing extracted contact details. - """ - return self.api_post( - "pipeline/extract-contacts", - {"url": url, **(params or {})}, - stream, - content_type, - ) - - def label( - self, - url: str, - params: Optional[RequestParamsDict] = None, - stream: bool = False, - content_type: str = "application/json", - ): - """ - Apply labeling to data extracted from the specified URL. - - :param url: The URL to label data from. - :param params: Optional parameters to guide the labeling process. - :return: JSON response with labeled data. - """ - return self.api_post("pipeline/label", {"url": url, **(params or {})}, stream, content_type) - - def _prepare_headers(self, content_type: str = "application/json"): - return { - "Content-Type": content_type, - "Authorization": f"Bearer {self.api_key}", - "User-Agent": "Spider-Client/0.0.27", - } - - def _post_request(self, url: str, data, headers, stream=False): - return requests.post(url, headers=headers, json=data, stream=stream) - - def _get_request(self, url: str, headers, stream=False): - return requests.get(url, headers=headers, stream=stream) - - def _delete_request(self, url: str, headers, stream=False): - return requests.delete(url, headers=headers, stream=stream) - - def _handle_error(self, response, action): - if response.status_code in {402, 409, 500}: - error_message = response.json().get("error", "Unknown error occurred") - raise Exception(f"Failed to {action}. Status code: {response.status_code}. Error: {error_message}") - else: - raise Exception(f"Unexpected error occurred while trying to {action}. Status code: {response.status_code}") diff --git a/api/core/tools/provider/builtin/spider/tools/scraper_crawler.py b/api/core/tools/provider/builtin/spider/tools/scraper_crawler.py deleted file mode 100644 index 20d2daef550de1..00000000000000 --- a/api/core/tools/provider/builtin/spider/tools/scraper_crawler.py +++ /dev/null @@ -1,49 +0,0 @@ -from typing import Any, Union - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.spider.spiderApp import Spider -from core.tools.tool.builtin_tool import BuiltinTool - - -class ScrapeTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - # initialize the app object with the api key - app = Spider(api_key=self.runtime.credentials["spider_api_key"]) - - url = tool_parameters["url"] - mode = tool_parameters["mode"] - - options = { - "limit": tool_parameters.get("limit", 0), - "depth": tool_parameters.get("depth", 0), - "blacklist": tool_parameters.get("blacklist", "").split(",") if tool_parameters.get("blacklist") else [], - "whitelist": tool_parameters.get("whitelist", "").split(",") if tool_parameters.get("whitelist") else [], - "readability": tool_parameters.get("readability", False), - } - - result = "" - - try: - if mode == "scrape": - scrape_result = app.scrape_url( - url=url, - params=options, - ) - - for i in scrape_result: - result += "URL: " + i.get("url", "") + "\n" - result += "CONTENT: " + i.get("content", "") + "\n\n" - elif mode == "crawl": - crawl_result = app.crawl_url( - url=tool_parameters["url"], - params=options, - ) - for i in crawl_result: - result += "URL: " + i.get("url", "") + "\n" - result += "CONTENT: " + i.get("content", "") + "\n\n" - except Exception as e: - return self.create_text_message("An error occurred", str(e)) - - return self.create_text_message(result) diff --git a/api/core/tools/provider/builtin/spider/tools/scraper_crawler.yaml b/api/core/tools/provider/builtin/spider/tools/scraper_crawler.yaml deleted file mode 100644 index 5b20c2fc2f70ad..00000000000000 --- a/api/core/tools/provider/builtin/spider/tools/scraper_crawler.yaml +++ /dev/null @@ -1,102 +0,0 @@ -identity: - name: scraper_crawler - author: William Espegren - label: - en_US: Web Scraper & Crawler - zh_Hans: 网页抓取与爬虫 -description: - human: - en_US: A tool for scraping & crawling webpages. Input should be a url. - zh_Hans: 用于抓取和爬取网页的工具。输入应该是一个网址。 - llm: A tool for scraping & crawling webpages. Input should be a url. -parameters: - - name: url - type: string - required: true - label: - en_US: URL - zh_Hans: 网址 - human_description: - en_US: url to be scraped or crawled - zh_Hans: 要抓取或爬取的网址 - llm_description: url to either be scraped or crawled - form: llm - - name: mode - type: select - required: true - options: - - value: scrape - label: - en_US: scrape - zh_Hans: 抓取 - - value: crawl - label: - en_US: crawl - zh_Hans: 爬取 - default: crawl - label: - en_US: Mode - zh_Hans: 模式 - human_description: - en_US: used for selecting to either scrape the website or crawl the entire website following subpages - zh_Hans: 用于选择抓取网站或爬取整个网站及其子页面 - form: form - - name: limit - type: number - required: false - label: - en_US: maximum number of pages to crawl - zh_Hans: 最大爬取页面数 - human_description: - en_US: specify the maximum number of pages to crawl per website. the crawler will stop after reaching this limit. - zh_Hans: 指定每个网站要爬取的最大页面数。爬虫将在达到此限制后停止。 - form: form - min: 0 - default: 0 - - name: depth - type: number - required: false - label: - en_US: maximum depth of pages to crawl - zh_Hans: 最大爬取深度 - human_description: - en_US: the crawl limit for maximum depth. - zh_Hans: 最大爬取深度的限制。 - form: form - min: 0 - default: 0 - - name: blacklist - type: string - required: false - label: - en_US: url patterns to exclude - zh_Hans: 要排除的URL模式 - human_description: - en_US: blacklist a set of paths that you do not want to crawl. you can use regex patterns to help with the list. - zh_Hans: 指定一组不想爬取的路径。您可以使用正则表达式模式来帮助定义列表。 - placeholder: - en_US: /blog/*, /about - form: form - - name: whitelist - type: string - required: false - label: - en_US: URL patterns to include - zh_Hans: 要包含的URL模式 - human_description: - en_US: Whitelist a set of paths that you want to crawl, ignoring all other routes that do not match the patterns. You can use regex patterns to help with the list. - zh_Hans: 指定一组要爬取的路径，忽略所有不匹配模式的其他路由。您可以使用正则表达式模式来帮助定义列表。 - placeholder: - en_US: /blog/*, /about - form: form - - name: readability - type: boolean - required: false - label: - en_US: Pre-process the content for LLM usage - zh_Hans: 仅返回页面的主要内容 - human_description: - en_US: Use Mozilla's readability to pre-process the content for reading. This may drastically improve the content for LLM usage. - zh_Hans: 如果启用，爬虫将仅返回页面的主要内容，不包括标题、导航、页脚等。 - form: form - default: false diff --git a/api/core/tools/provider/builtin/stability/_assets/icon.svg b/api/core/tools/provider/builtin/stability/_assets/icon.svg deleted file mode 100644 index 56357a35557ac3..00000000000000 --- a/api/core/tools/provider/builtin/stability/_assets/icon.svg +++ /dev/null @@ -1,10 +0,0 @@ - - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/stability/stability.py b/api/core/tools/provider/builtin/stability/stability.py deleted file mode 100644 index f09d81ac270288..00000000000000 --- a/api/core/tools/provider/builtin/stability/stability.py +++ /dev/null @@ -1,16 +0,0 @@ -from typing import Any - -from core.tools.provider.builtin.stability.tools.base import BaseStabilityAuthorization -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class StabilityToolProvider(BuiltinToolProviderController, BaseStabilityAuthorization): - """ - This class is responsible for providing the stability tool. - """ - - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - """ - This method is responsible for validating the credentials. - """ - self.sd_validate_credentials(credentials) diff --git a/api/core/tools/provider/builtin/stability/stability.yaml b/api/core/tools/provider/builtin/stability/stability.yaml deleted file mode 100644 index c3e01c1e314d51..00000000000000 --- a/api/core/tools/provider/builtin/stability/stability.yaml +++ /dev/null @@ -1,31 +0,0 @@ -identity: - author: Dify - name: stability - label: - en_US: Stability - zh_Hans: Stability - pt_BR: Stability - description: - en_US: Activating humanity's potential through generative AI - zh_Hans: 通过生成式 AI 激活人类的潜力 - pt_BR: Activating humanity's potential through generative AI - icon: icon.svg - tags: - - image -credentials_for_provider: - api_key: - type: secret-input - required: true - label: - en_US: API key - zh_Hans: API key - pt_BR: API key - placeholder: - en_US: Please input your API key - zh_Hans: 请输入你的 API key - pt_BR: Please input your API key - help: - en_US: Get your API key from Stability - zh_Hans: 从 Stability 获取你的 API key - pt_BR: Get your API key from Stability - url: https://platform.stability.ai/account/keys diff --git a/api/core/tools/provider/builtin/stability/tools/base.py b/api/core/tools/provider/builtin/stability/tools/base.py deleted file mode 100644 index c3b7edbefa2447..00000000000000 --- a/api/core/tools/provider/builtin/stability/tools/base.py +++ /dev/null @@ -1,31 +0,0 @@ -import requests -from yarl import URL - -from core.tools.errors import ToolProviderCredentialValidationError - - -class BaseStabilityAuthorization: - def sd_validate_credentials(self, credentials: dict): - """ - This method is responsible for validating the credentials. - """ - api_key = credentials.get("api_key", "") - if not api_key: - raise ToolProviderCredentialValidationError("API key is required.") - - response = requests.get( - URL("https://api.stability.ai") / "v1" / "user" / "account", - headers=self.generate_authorization_headers(credentials), - timeout=(5, 30), - ) - - if not response.ok: - raise ToolProviderCredentialValidationError("Invalid API key.") - - return True - - def generate_authorization_headers(self, credentials: dict) -> dict[str, str]: - """ - This method is responsible for generating the authorization headers. - """ - return {"Authorization": f'Bearer {credentials.get("api_key", "")}'} diff --git a/api/core/tools/provider/builtin/stability/tools/text2image.py b/api/core/tools/provider/builtin/stability/tools/text2image.py deleted file mode 100644 index 6bcf315484ad50..00000000000000 --- a/api/core/tools/provider/builtin/stability/tools/text2image.py +++ /dev/null @@ -1,56 +0,0 @@ -from typing import Any - -from httpx import post - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.provider.builtin.stability.tools.base import BaseStabilityAuthorization -from core.tools.tool.builtin_tool import BuiltinTool - - -class StableDiffusionTool(BuiltinTool, BaseStabilityAuthorization): - """ - This class is responsible for providing the stable diffusion tool. - """ - - model_endpoint_map: dict[str, str] = { - "sd3": "https://api.stability.ai/v2beta/stable-image/generate/sd3", - "sd3-turbo": "https://api.stability.ai/v2beta/stable-image/generate/sd3", - "core": "https://api.stability.ai/v2beta/stable-image/generate/core", - } - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: - """ - Invoke the tool. - """ - payload = { - "prompt": tool_parameters.get("prompt", ""), - "aspect_ratio": tool_parameters.get("aspect_ratio", "16:9") or tool_parameters.get("aspect_radio", "16:9"), - "mode": "text-to-image", - "seed": tool_parameters.get("seed", 0), - "output_format": "png", - } - - model = tool_parameters.get("model", "core") - - if model in {"sd3", "sd3-turbo"}: - payload["model"] = tool_parameters.get("model") - - if model != "sd3-turbo": - payload["negative_prompt"] = tool_parameters.get("negative_prompt", "") - - response = post( - self.model_endpoint_map[tool_parameters.get("model", "core")], - headers={ - "accept": "image/*", - **self.generate_authorization_headers(self.runtime.credentials), - }, - files={key: (None, str(value)) for key, value in payload.items()}, - timeout=(5, 30), - ) - - if not response.status_code == 200: - raise Exception(response.text) - - return self.create_blob_message( - blob=response.content, meta={"mime_type": "image/png"}, save_as=self.VariableKey.IMAGE.value - ) diff --git a/api/core/tools/provider/builtin/stability/tools/text2image.yaml b/api/core/tools/provider/builtin/stability/tools/text2image.yaml deleted file mode 100644 index 21345f9f187f07..00000000000000 --- a/api/core/tools/provider/builtin/stability/tools/text2image.yaml +++ /dev/null @@ -1,142 +0,0 @@ -identity: - name: stability_text2image - author: Dify - label: - en_US: StableDiffusion - zh_Hans: 稳定扩散 - pt_BR: StableDiffusion -description: - human: - en_US: A tool for generate images based on the text input - zh_Hans: 一个基于文本输入生成图像的工具 - pt_BR: A tool for generate images based on the text input - llm: A tool for generate images based on the text input -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: used for generating images - zh_Hans: 用于生成图像 - pt_BR: used for generating images - llm_description: key words for generating images - form: llm - - name: model - type: select - default: sd3-turbo - required: true - label: - en_US: Model - zh_Hans: 模型 - pt_BR: Model - options: - - value: core - label: - en_US: Core - zh_Hans: Core - pt_BR: Core - - value: sd3 - label: - en_US: Stable Diffusion 3 - zh_Hans: Stable Diffusion 3 - pt_BR: Stable Diffusion 3 - - value: sd3-turbo - label: - en_US: Stable Diffusion 3 Turbo - zh_Hans: Stable Diffusion 3 Turbo - pt_BR: Stable Diffusion 3 Turbo - human_description: - en_US: Model for generating images - zh_Hans: 用于生成图像的模型 - pt_BR: Model for generating images - llm_description: Model for generating images - form: form - - name: negative_prompt - type: string - default: bad art, ugly, deformed, watermark, duplicated, discontinuous lines - required: false - label: - en_US: Negative Prompt - zh_Hans: 负面提示 - pt_BR: Negative Prompt - human_description: - en_US: Negative Prompt - zh_Hans: 负面提示 - pt_BR: Negative Prompt - llm_description: Negative Prompt - form: form - - name: seeds - type: number - default: 0 - required: false - label: - en_US: Seeds - zh_Hans: 种子 - pt_BR: Seeds - human_description: - en_US: Seeds - zh_Hans: 种子 - pt_BR: Seeds - llm_description: Seeds - min: 0 - max: 4294967294 - form: form - - name: aspect_ratio - type: select - default: '16:9' - options: - - value: '16:9' - label: - en_US: '16:9' - zh_Hans: '16:9' - pt_BR: '16:9' - - value: '1:1' - label: - en_US: '1:1' - zh_Hans: '1:1' - pt_BR: '1:1' - - value: '21:9' - label: - en_US: '21:9' - zh_Hans: '21:9' - pt_BR: '21:9' - - value: '2:3' - label: - en_US: '2:3' - zh_Hans: '2:3' - pt_BR: '2:3' - - value: '4:5' - label: - en_US: '4:5' - zh_Hans: '4:5' - pt_BR: '4:5' - - value: '5:4' - label: - en_US: '5:4' - zh_Hans: '5:4' - pt_BR: '5:4' - - value: '9:16' - label: - en_US: '9:16' - zh_Hans: '9:16' - pt_BR: '9:16' - - value: '9:21' - label: - en_US: '9:21' - zh_Hans: '9:21' - pt_BR: '9:21' - required: false - label: - en_US: Aspect Ratio - zh_Hans: 长宽比 - pt_BR: Aspect Ratio - human_description: - en_US: Aspect Ratio - zh_Hans: 长宽比 - pt_BR: Aspect Ratio - llm_description: Aspect Ratio - form: form diff --git a/api/core/tools/provider/builtin/stablediffusion/_assets/icon.png b/api/core/tools/provider/builtin/stablediffusion/_assets/icon.png deleted file 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q257{AYw-Uad;fp`8kgRGz^JYy`M|BjoefUs1Da2DRcn=PBmWQ3F(GCE diff --git a/api/core/tools/provider/builtin/stablediffusion/stablediffusion.py b/api/core/tools/provider/builtin/stablediffusion/stablediffusion.py deleted file mode 100644 index abaa297cf36eb1..00000000000000 --- a/api/core/tools/provider/builtin/stablediffusion/stablediffusion.py +++ /dev/null @@ -1,17 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.stablediffusion.tools.stable_diffusion import StableDiffusionTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class StableDiffusionProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - StableDiffusionTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).validate_models() - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/stablediffusion/stablediffusion.yaml b/api/core/tools/provider/builtin/stablediffusion/stablediffusion.yaml deleted file mode 100644 index 9b3c804f722dfc..00000000000000 --- a/api/core/tools/provider/builtin/stablediffusion/stablediffusion.yaml +++ /dev/null @@ -1,42 +0,0 @@ -identity: - author: Dify - name: stablediffusion - label: - en_US: Stable Diffusion - zh_Hans: Stable Diffusion - pt_BR: Stable Diffusion - description: - en_US: Stable Diffusion is a tool for generating images which can be deployed locally. - zh_Hans: Stable Diffusion 是一个可以在本地部署的图片生成的工具。 - pt_BR: Stable Diffusion is a tool for generating images which can be deployed locally. - icon: icon.png - tags: - - image -credentials_for_provider: - base_url: - type: secret-input - required: true - label: - en_US: Base URL - zh_Hans: StableDiffusion服务器的Base URL - pt_BR: Base URL - placeholder: - en_US: Please input your StableDiffusion server's Base URL - zh_Hans: 请输入你的 StableDiffusion 服务器的 Base URL - pt_BR: Please input your StableDiffusion server's Base URL - model: - type: text-input - required: true - label: - en_US: Model - zh_Hans: 模型 - pt_BR: Model - placeholder: - en_US: Please input your model - zh_Hans: 请输入你的模型名称 - pt_BR: Please input your model - help: - en_US: The model name of the StableDiffusion server - zh_Hans: StableDiffusion服务器的模型名称 - pt_BR: The model name of the StableDiffusion server - url: https://docs.dify.ai/tutorials/tool-configuration/stable-diffusion diff --git a/api/core/tools/provider/builtin/stablediffusion/tools/stable_diffusion.py b/api/core/tools/provider/builtin/stablediffusion/tools/stable_diffusion.py deleted file mode 100644 index 64fdc961b4c5db..00000000000000 --- a/api/core/tools/provider/builtin/stablediffusion/tools/stable_diffusion.py +++ /dev/null @@ -1,390 +0,0 @@ -import io -import json -from base64 import b64decode, b64encode -from copy import deepcopy -from typing import Any, Union - -from httpx import get, post -from PIL import Image -from yarl import URL - -from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter, ToolParameterOption -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.tool.builtin_tool import BuiltinTool - -# All commented out parameters default to null -DRAW_TEXT_OPTIONS = { - # Prompts - "prompt": "", - "negative_prompt": "", - # "styles": [], - # Seeds - "seed": -1, - "subseed": -1, - "subseed_strength": 0, - "seed_resize_from_h": -1, - "seed_resize_from_w": -1, - # Samplers - "sampler_name": "DPM++ 2M", - # "scheduler": "", - # "sampler_index": "Automatic", - # Latent Space Options - "batch_size": 1, - "n_iter": 1, - "steps": 10, - "cfg_scale": 7, - "width": 512, - "height": 512, - # "restore_faces": True, - # "tiling": True, - "do_not_save_samples": False, - "do_not_save_grid": False, - # "eta": 0, - # "denoising_strength": 0.75, - # "s_min_uncond": 0, - # "s_churn": 0, - # "s_tmax": 0, - # "s_tmin": 0, - # "s_noise": 0, - "override_settings": {}, - "override_settings_restore_afterwards": True, - # Refinement Options - "refiner_checkpoint": "", - "refiner_switch_at": 0, - "disable_extra_networks": False, - # "firstpass_image": "", - # "comments": "", - # High-Resolution Options - "enable_hr": False, - "firstphase_width": 0, - "firstphase_height": 0, - "hr_scale": 2, - # "hr_upscaler": "", - "hr_second_pass_steps": 0, - "hr_resize_x": 0, - "hr_resize_y": 0, - # "hr_checkpoint_name": "", - # "hr_sampler_name": "", - # "hr_scheduler": "", - "hr_prompt": "", - "hr_negative_prompt": "", - # Task Options - # "force_task_id": "", - # Script Options - # "script_name": "", - "script_args": [], - # Output Options - "send_images": True, - "save_images": False, - "alwayson_scripts": {}, - # "infotext": "", -} - - -class StableDiffusionTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - # base url - base_url = self.runtime.credentials.get("base_url", None) - if not base_url: - return self.create_text_message("Please input base_url") - - if tool_parameters.get("model"): - self.runtime.credentials["model"] = tool_parameters["model"] - - model = self.runtime.credentials.get("model", None) - if not model: - return self.create_text_message("Please input model") - - # set model - try: - url = str(URL(base_url) / "sdapi" / "v1" / "options") - response = post(url, data=json.dumps({"sd_model_checkpoint": model})) - if response.status_code != 200: - raise ToolProviderCredentialValidationError("Failed to set model, please tell user to set model") - except Exception as e: - raise ToolProviderCredentialValidationError("Failed to set model, please tell user to set model") - - # get image id and image variable - image_id = tool_parameters.get("image_id", "") - image_variable = self.get_default_image_variable() - # Return text2img if there's no image ID or no image variable - if not image_id or not image_variable: - return self.text2img(base_url=base_url, tool_parameters=tool_parameters) - - # Proceed with image-to-image generation - return self.img2img(base_url=base_url, tool_parameters=tool_parameters) - - def validate_models(self) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - validate models - """ - try: - base_url = self.runtime.credentials.get("base_url", None) - if not base_url: - raise ToolProviderCredentialValidationError("Please input base_url") - model = self.runtime.credentials.get("model", None) - if not model: - raise ToolProviderCredentialValidationError("Please input model") - - api_url = str(URL(base_url) / "sdapi" / "v1" / "sd-models") - response = get(url=api_url, timeout=10) - if response.status_code == 404: - # try draw a picture - self._invoke( - user_id="test", - tool_parameters={ - "prompt": "a cat", - "width": 1024, - "height": 1024, - "steps": 1, - "lora": "", - }, - ) - elif response.status_code != 200: - raise ToolProviderCredentialValidationError("Failed to get models") - else: - models = [d["model_name"] for d in response.json()] - if len([d for d in models if d == model]) > 0: - return self.create_text_message(json.dumps(models)) - else: - raise ToolProviderCredentialValidationError(f"model {model} does not exist") - except Exception as e: - raise ToolProviderCredentialValidationError(f"Failed to get models, {e}") - - def get_sd_models(self) -> list[str]: - """ - get sd models - """ - try: - base_url = self.runtime.credentials.get("base_url", None) - if not base_url: - return [] - api_url = str(URL(base_url) / "sdapi" / "v1" / "sd-models") - response = get(url=api_url, timeout=(2, 10)) - if response.status_code != 200: - return [] - else: - return [d["model_name"] for d in response.json()] - except Exception as e: - return [] - - def get_sample_methods(self) -> list[str]: - """ - get sample method - """ - try: - base_url = self.runtime.credentials.get("base_url", None) - if not base_url: - return [] - api_url = str(URL(base_url) / "sdapi" / "v1" / "samplers") - response = get(url=api_url, timeout=(2, 10)) - if response.status_code != 200: - return [] - else: - return [d["name"] for d in response.json()] - except Exception as e: - return [] - - def img2img( - self, base_url: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - generate image - """ - - # Fetch the binary data of the image - image_variable = self.get_default_image_variable() - image_binary = self.get_variable_file(image_variable.name) - if not image_binary: - return self.create_text_message("Image not found, please request user to generate image firstly.") - - # Convert image to RGB and save as PNG - try: - with Image.open(io.BytesIO(image_binary)) as image, io.BytesIO() as buffer: - image.convert("RGB").save(buffer, format="PNG") - image_binary = buffer.getvalue() - except Exception as e: - return self.create_text_message(f"Failed to process the image: {str(e)}") - - # copy draw options - draw_options = deepcopy(DRAW_TEXT_OPTIONS) - # set image options - model = tool_parameters.get("model", "") - draw_options_image = { - "init_images": [b64encode(image_binary).decode("utf-8")], - "denoising_strength": 0.9, - "restore_faces": False, - "script_args": [], - "override_settings": {"sd_model_checkpoint": model}, - "resize_mode": 0, - "image_cfg_scale": 0, - # "mask": None, - "mask_blur_x": 4, - "mask_blur_y": 4, - "mask_blur": 0, - "mask_round": True, - "inpainting_fill": 0, - "inpaint_full_res": True, - "inpaint_full_res_padding": 0, - "inpainting_mask_invert": 0, - "initial_noise_multiplier": 0, - # "latent_mask": None, - "include_init_images": True, - } - # update key and values - draw_options.update(draw_options_image) - draw_options.update(tool_parameters) - - # get prompt lora model - prompt = tool_parameters.get("prompt", "") - lora = tool_parameters.get("lora", "") - model = tool_parameters.get("model", "") - if lora: - draw_options["prompt"] = f"{lora},{prompt}" - else: - draw_options["prompt"] = prompt - - try: - url = str(URL(base_url) / "sdapi" / "v1" / "img2img") - response = post(url, data=json.dumps(draw_options), timeout=120) - if response.status_code != 200: - return self.create_text_message("Failed to generate image") - - image = response.json()["images"][0] - - return self.create_blob_message( - blob=b64decode(image), meta={"mime_type": "image/png"}, save_as=self.VariableKey.IMAGE.value - ) - - except Exception as e: - return self.create_text_message("Failed to generate image") - - def text2img( - self, base_url: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - generate image - """ - # copy draw options - draw_options = deepcopy(DRAW_TEXT_OPTIONS) - draw_options.update(tool_parameters) - # get prompt lora model - prompt = tool_parameters.get("prompt", "") - lora = tool_parameters.get("lora", "") - model = tool_parameters.get("model", "") - if lora: - draw_options["prompt"] = f"{lora},{prompt}" - else: - draw_options["prompt"] = prompt - draw_options["override_settings"]["sd_model_checkpoint"] = model - - try: - url = str(URL(base_url) / "sdapi" / "v1" / "txt2img") - response = post(url, data=json.dumps(draw_options), timeout=120) - if response.status_code != 200: - return self.create_text_message("Failed to generate image") - - image = response.json()["images"][0] - - return self.create_blob_message( - blob=b64decode(image), meta={"mime_type": "image/png"}, save_as=self.VariableKey.IMAGE.value - ) - - except Exception as e: - return self.create_text_message("Failed to generate image") - - def get_runtime_parameters(self) -> list[ToolParameter]: - parameters = [ - ToolParameter( - name="prompt", - label=I18nObject(en_US="Prompt", zh_Hans="Prompt"), - human_description=I18nObject( - en_US="Image prompt, you can check the official documentation of Stable Diffusion", - zh_Hans="图像提示词，您可以查看 Stable Diffusion 的官方文档", - ), - type=ToolParameter.ToolParameterType.STRING, - form=ToolParameter.ToolParameterForm.LLM, - llm_description="Image prompt of Stable Diffusion, you should describe the image you want to generate" - " as a list of words as possible as detailed, the prompt must be written in English.", - required=True, - ), - ] - if len(self.list_default_image_variables()) != 0: - parameters.append( - ToolParameter( - name="image_id", - label=I18nObject(en_US="image_id", zh_Hans="image_id"), - human_description=I18nObject( - en_US="Image id of the image you want to generate based on, if you want to generate image based" - " on the default image, you can leave this field empty.", - zh_Hans="您想要生成的图像的图像 ID，如果您想要基于默认图像生成图像，则可以将此字段留空。", - ), - type=ToolParameter.ToolParameterType.STRING, - form=ToolParameter.ToolParameterForm.LLM, - llm_description="Image id of the original image, you can leave this field empty if you want to" - " generate a new image.", - required=True, - options=[ - ToolParameterOption(value=i.name, label=I18nObject(en_US=i.name, zh_Hans=i.name)) - for i in self.list_default_image_variables() - ], - ) - ) - - if self.runtime.credentials: - try: - models = self.get_sd_models() - if len(models) != 0: - parameters.append( - ToolParameter( - name="model", - label=I18nObject(en_US="Model", zh_Hans="Model"), - human_description=I18nObject( - en_US="Model of Stable Diffusion, you can check the official documentation" - " of Stable Diffusion", - zh_Hans="Stable Diffusion 的模型，您可以查看 Stable Diffusion 的官方文档", - ), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - llm_description="Model of Stable Diffusion, you can check the official documentation" - " of Stable Diffusion", - required=True, - default=models[0], - options=[ - ToolParameterOption(value=i, label=I18nObject(en_US=i, zh_Hans=i)) for i in models - ], - ) - ) - - except: - pass - - sample_methods = self.get_sample_methods() - if len(sample_methods) != 0: - parameters.append( - ToolParameter( - name="sampler_name", - label=I18nObject(en_US="Sampling method", zh_Hans="Sampling method"), - human_description=I18nObject( - en_US="Sampling method of Stable Diffusion, you can check the official documentation" - " of Stable Diffusion", - zh_Hans="Stable Diffusion 的Sampling method，您可以查看 Stable Diffusion 的官方文档", - ), - type=ToolParameter.ToolParameterType.SELECT, - form=ToolParameter.ToolParameterForm.FORM, - llm_description="Sampling method of Stable Diffusion, you can check the official documentation" - " of Stable Diffusion", - required=True, - default=sample_methods[0], - options=[ - ToolParameterOption(value=i, label=I18nObject(en_US=i, zh_Hans=i)) for i in sample_methods - ], - ) - ) - return parameters diff --git a/api/core/tools/provider/builtin/stablediffusion/tools/stable_diffusion.yaml b/api/core/tools/provider/builtin/stablediffusion/tools/stable_diffusion.yaml deleted file mode 100644 index bbbdb16caf21bb..00000000000000 --- a/api/core/tools/provider/builtin/stablediffusion/tools/stable_diffusion.yaml +++ /dev/null @@ -1,104 +0,0 @@ -identity: - name: stable_diffusion - author: Dify - label: - en_US: Stable Diffusion WebUI - zh_Hans: Stable Diffusion WebUI - pt_BR: Stable Diffusion WebUI -description: - human: - en_US: A tool for generating images which can be deployed locally, you can use stable-diffusion-webui to deploy it. - zh_Hans: 一个可以在本地部署的图片生成的工具，您可以使用 stable-diffusion-webui 来部署它。 - pt_BR: A tool for generating images which can be deployed locally, you can use stable-diffusion-webui to deploy it. - llm: draw the image you want based on your prompt. -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: Image prompt, you can check the official documentation of Stable Diffusion - zh_Hans: 图像提示词，您可以查看 Stable Diffusion 的官方文档 - pt_BR: Image prompt, you can check the official documentation of Stable Diffusion - llm_description: Image prompt of Stable Diffusion, you should describe the image you want to generate as a list of words as possible as detailed, the prompt must be written in English. - form: llm - - name: model - type: string - required: false - label: - en_US: Model Name - zh_Hans: 模型名称 - pt_BR: Model Name - human_description: - en_US: Model Name - zh_Hans: 模型名称 - pt_BR: Model Name - form: form - - name: lora - type: string - required: false - label: - en_US: Lora - zh_Hans: Lora - pt_BR: Lora - human_description: - en_US: Lora - zh_Hans: Lora - pt_BR: Lora - form: form - default: "" - - name: steps - type: number - required: false - label: - en_US: Steps - zh_Hans: Steps - pt_BR: Steps - human_description: - en_US: Steps - zh_Hans: Steps - pt_BR: Steps - form: form - default: 10 - - name: width - type: number - required: false - label: - en_US: Width - zh_Hans: Width - pt_BR: Width - human_description: - en_US: Width - zh_Hans: Width - pt_BR: Width - form: form - default: 1024 - - name: height - type: number - required: false - label: - en_US: Height - zh_Hans: Height - pt_BR: Height - human_description: - en_US: Height - zh_Hans: Height - pt_BR: Height - form: form - default: 1024 - - name: negative_prompt - type: string - required: false - label: - en_US: Negative prompt - zh_Hans: Negative prompt - pt_BR: Negative prompt - human_description: - en_US: Negative prompt - zh_Hans: Negative prompt - pt_BR: Negative prompt - form: form - default: bad art, ugly, deformed, watermark, duplicated, discontinuous lines diff --git a/api/core/tools/provider/builtin/stackexchange/_assets/icon.svg b/api/core/tools/provider/builtin/stackexchange/_assets/icon.svg deleted file mode 100644 index 7042bc0e4156c9..00000000000000 --- a/api/core/tools/provider/builtin/stackexchange/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/stackexchange/stackexchange.py b/api/core/tools/provider/builtin/stackexchange/stackexchange.py deleted file mode 100644 index 9680c633cc701c..00000000000000 --- a/api/core/tools/provider/builtin/stackexchange/stackexchange.py +++ /dev/null @@ -1,25 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.stackexchange.tools.searchStackExQuestions import SearchStackExQuestionsTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class StackExchangeProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - SearchStackExQuestionsTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "intitle": "Test", - "sort": "relevance", - "order": "desc", - "site": "stackoverflow", - "accepted": True, - "pagesize": 1, - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/stackexchange/stackexchange.yaml b/api/core/tools/provider/builtin/stackexchange/stackexchange.yaml deleted file mode 100644 index d382a3cca9cef2..00000000000000 --- a/api/core/tools/provider/builtin/stackexchange/stackexchange.yaml +++ /dev/null @@ -1,13 +0,0 @@ -identity: - author: Richards Tu - name: stackexchange - label: - en_US: Stack Exchange - zh_Hans: Stack Exchange - description: - en_US: Access questions and answers from the Stack Exchange and its sub-sites. - zh_Hans: 从 Stack Exchange 和其子论坛获取问题和答案。 - icon: icon.svg - tags: - - search - - utilities diff --git a/api/core/tools/provider/builtin/stackexchange/tools/fetchAnsByStackExQuesID.py b/api/core/tools/provider/builtin/stackexchange/tools/fetchAnsByStackExQuesID.py deleted file mode 100644 index 534532009501f5..00000000000000 --- a/api/core/tools/provider/builtin/stackexchange/tools/fetchAnsByStackExQuesID.py +++ /dev/null @@ -1,39 +0,0 @@ -from typing import Any, Union - -import requests -from pydantic import BaseModel, Field - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class FetchAnsByStackExQuesIDInput(BaseModel): - id: int = Field(..., description="The question ID") - site: str = Field(..., description="The Stack Exchange site") - order: str = Field(..., description="asc or desc") - sort: str = Field(..., description="activity, votes, creation") - pagesize: int = Field(..., description="Number of answers per page") - page: int = Field(..., description="Page number") - - -class FetchAnsByStackExQuesIDTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - input = FetchAnsByStackExQuesIDInput(**tool_parameters) - - params = { - "site": input.site, - "filter": "!nNPvSNdWme", - "order": input.order, - "sort": input.sort, - "pagesize": input.pagesize, - "page": input.page, - } - - response = requests.get(f"https://api.stackexchange.com/2.3/questions/{input.id}/answers", params=params) - - if response.status_code == 200: - return self.create_text_message(self.summary(user_id=user_id, content=response.text)) - else: - return self.create_text_message(f"API request failed with status code {response.status_code}") diff --git a/api/core/tools/provider/builtin/stackexchange/tools/fetchAnsByStackExQuesID.yaml b/api/core/tools/provider/builtin/stackexchange/tools/fetchAnsByStackExQuesID.yaml deleted file mode 100644 index d663bce6097441..00000000000000 --- a/api/core/tools/provider/builtin/stackexchange/tools/fetchAnsByStackExQuesID.yaml +++ /dev/null @@ -1,107 +0,0 @@ -identity: - name: fetchAnsByStackExQuesID - author: Richards Tu - label: - en_US: Fetch Stack Exchange Answers - zh_Hans: 获取 Stack Exchange 答案 -description: - human: - en_US: A tool for retrieving answers for a specific Stack Exchange question ID. Must be used with the searchStackExQuesID tool. - zh_Hans: 用于检索特定Stack Exchange问题ID的答案的工具。必须与searchStackExQuesID工具一起使用。 - llm: A tool for retrieving answers for Stack Exchange question ID. -parameters: - - name: id - type: string - required: true - label: - en_US: Question ID - zh_Hans: 问题ID - human_description: - en_US: The ID of the Stack Exchange question to fetch answers for. - zh_Hans: 要获取答案的Stack Exchange问题的ID。 - llm_description: The ID of the Stack Exchange question. - form: llm - - name: site - type: string - required: true - label: - en_US: Stack Exchange site - zh_Hans: Stack Exchange站点 - human_description: - en_US: The Stack Exchange site the question is from, e.g. stackoverflow, unix, etc. - zh_Hans: 问题所在的Stack Exchange站点，例如stackoverflow、unix等。 - llm_description: Stack Exchange site identifier - 'stackoverflow', 'serverfault', 'superuser', 'askubuntu', 'unix', 'cs', 'softwareengineering', 'codegolf', 'codereview', 'cstheory', 'security', 'cryptography', 'reverseengineering', 'datascience', 'devops', 'ux', 'dba', 'gis', 'webmasters', 'arduino', 'raspberrypi', 'networkengineering', 'iot', 'tor', 'sqa', 'mathoverflow', 'math', 'mathematica', 'dsp', 'gamedev', 'robotics', 'genai', 'computergraphics'. - form: llm - - name: filter - type: string - required: true - label: - en_US: Filter - zh_Hans: 过滤器 - human_description: - en_US: This is required in order to actually get the body of the answer. - zh_Hans: 为了实际获取答案的正文是必需的。 - options: - - value: "!nNPvSNdWme" - label: - en_US: Must Select - zh_Hans: 必须选择 - form: form - default: "!nNPvSNdWme" - - name: order - type: string - required: true - label: - en_US: Sort direction - zh_Hans: 排序方向 - human_description: - en_US: The direction to sort the answers - ascending or descending. - zh_Hans: 答案的排序方向 - 升序或降序。 - form: form - options: - - value: asc - label: - en_US: Ascending - zh_Hans: 升序 - - value: desc - label: - en_US: Descending - zh_Hans: 降序 - default: desc - - name: sort - type: string - required: true - label: - en_US: Sort order - zh_Hans: 排序 - human_description: - en_US: The sort order for the answers - activity, votes, or creation date. - zh_Hans: 答案的排序顺序 - 活动、投票或创建日期。 - llm_description: activity, votes, or creation. - form: llm - - name: pagesize - type: number - required: true - label: - en_US: Results per page - zh_Hans: 每页结果数 - human_description: - en_US: The number of answers to return per page. - zh_Hans: 每页返回的答案数。 - form: form - min: 1 - max: 5 - default: 1 - - name: page - type: number - required: true - label: - en_US: Page number - zh_Hans: 页码 - human_description: - en_US: The page number of answers to retrieve. - zh_Hans: 要检索的答案的页码。 - form: form - min: 1 - max: 5 - default: 3 diff --git a/api/core/tools/provider/builtin/stackexchange/tools/searchStackExQuestions.py b/api/core/tools/provider/builtin/stackexchange/tools/searchStackExQuestions.py deleted file mode 100644 index 4a25a808adf26a..00000000000000 --- a/api/core/tools/provider/builtin/stackexchange/tools/searchStackExQuestions.py +++ /dev/null @@ -1,45 +0,0 @@ -from typing import Any, Union - -import requests -from pydantic import BaseModel, Field - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class SearchStackExQuestionsInput(BaseModel): - intitle: str = Field(..., description="The search query.") - sort: str = Field(..., description="The sort order - relevance, activity, votes, creation.") - order: str = Field(..., description="asc or desc") - site: str = Field(..., description="The Stack Exchange site.") - tagged: str = Field(None, description="Semicolon-separated tags to include.") - nottagged: str = Field(None, description="Semicolon-separated tags to exclude.") - accepted: bool = Field(..., description="true for only accepted answers, false otherwise") - pagesize: int = Field(..., description="Number of results per page") - - -class SearchStackExQuestionsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - input = SearchStackExQuestionsInput(**tool_parameters) - - params = { - "intitle": input.intitle, - "sort": input.sort, - "order": input.order, - "site": input.site, - "accepted": input.accepted, - "pagesize": input.pagesize, - } - if input.tagged: - params["tagged"] = input.tagged - if input.nottagged: - params["nottagged"] = input.nottagged - - response = requests.get("https://api.stackexchange.com/2.3/search", params=params) - - if response.status_code == 200: - return self.create_text_message(self.summary(user_id=user_id, content=response.text)) - else: - return self.create_text_message(f"API request failed with status code {response.status_code}") diff --git a/api/core/tools/provider/builtin/stackexchange/tools/searchStackExQuestions.yaml b/api/core/tools/provider/builtin/stackexchange/tools/searchStackExQuestions.yaml deleted file mode 100644 index bbfbae38b06e1a..00000000000000 --- a/api/core/tools/provider/builtin/stackexchange/tools/searchStackExQuestions.yaml +++ /dev/null @@ -1,121 +0,0 @@ -identity: - name: searchStackExQuestions - author: Richards Tu - label: - en_US: Search Stack Exchange Questions - zh_Hans: 搜索Stack Exchange问题 -description: - human: - en_US: A tool for searching questions on a Stack Exchange site. - zh_Hans: 在Stack Exchange站点上搜索问题的工具。 - llm: A tool for searching questions on Stack Exchange site. -parameters: - - name: intitle - type: string - required: true - label: - en_US: Search query - zh_Hans: 搜索查询 - human_description: - en_US: The search query to use for finding questions. - zh_Hans: 用于查找问题的搜索查询。 - llm_description: The search query. - form: llm - - name: sort - type: string - required: true - label: - en_US: Sort order - zh_Hans: 排序 - human_description: - en_US: The sort order for the search results - relevance, activity, votes, or creation date. - zh_Hans: 搜索结果的排序顺序 - 相关性、活动、投票或创建日期。 - llm_description: The sort order - 'relevance', 'activity', 'votes', or 'creation'. - form: llm - - name: order - type: select - required: true - label: - en_US: Sort direction - zh_Hans: 排序方向 - human_description: - en_US: The direction to sort - ascending or descending. - zh_Hans: 排序方向 - 升序或降序。 - form: form - options: - - value: asc - label: - en_US: Ascending - zh_Hans: 升序 - - value: desc - label: - en_US: Descending - zh_Hans: 降序 - default: desc - - name: site - type: string - required: true - label: - en_US: Stack Exchange site - zh_Hans: Stack Exchange 站点 - human_description: - en_US: The Stack Exchange site to search, e.g. stackoverflow, unix, etc. - zh_Hans: 要搜索的Stack Exchange站点，例如stackoverflow、unix等。 - llm_description: Stack Exchange site identifier - 'stackoverflow', 'serverfault', 'superuser', 'askubuntu', 'unix', 'cs', 'softwareengineering', 'codegolf', 'codereview', 'cstheory', 'security', 'cryptography', 'reverseengineering', 'datascience', 'devops', 'ux', 'dba', 'gis', 'webmasters', 'arduino', 'raspberrypi', 'networkengineering', 'iot', 'tor', 'sqa', 'mathoverflow', 'math', 'mathematica', 'dsp', 'gamedev', 'robotics', 'genai', 'computergraphics'. - form: llm - - name: tagged - type: string - required: false - label: - en_US: Include tags - zh_Hans: 包含标签 - human_description: - en_US: A semicolon-separated list of tags that questions must have. - zh_Hans: 问题必须具有的标签的分号分隔列表。 - llm_description: Semicolon-separated tags to include. Leave blank if not needed. - form: llm - - name: nottagged - type: string - required: false - label: - en_US: Exclude tags - zh_Hans: 排除标签 - human_description: - en_US: A semicolon-separated list of tags to exclude from the search. - zh_Hans: 从搜索中排除的标签的分号分隔列表。 - llm_description: Semicolon-separated tags to exclude. Leave blank if not needed. - form: llm - - name: accepted - type: boolean - required: true - label: - en_US: Has accepted answer - zh_Hans: 有已接受的答案 - human_description: - en_US: Whether to limit to only questions that have an accepted answer. - zh_Hans: 是否限制为只有已接受答案的问题。 - form: form - options: - - value: 'true' - label: - en_US: 'Yes' - zh_Hans: 是 - - value: 'false' - label: - en_US: 'No' - zh_Hans: 否 - default: 'true' - - name: pagesize - type: number - required: true - label: - en_US: Results per page - zh_Hans: 每页结果数 - human_description: - en_US: The number of results to return per page. - zh_Hans: 每页返回的结果数。 - llm_description: The number of results per page. - form: form - min: 1 - max: 50 - default: 10 diff --git a/api/core/tools/provider/builtin/stepfun/__init__.py b/api/core/tools/provider/builtin/stepfun/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/tools/provider/builtin/stepfun/_assets/icon.png b/api/core/tools/provider/builtin/stepfun/_assets/icon.png deleted file mode 100644 index 85b96d0c74c24c2c28ccd0d363f02b35e359f561..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1991 zcmc&#Yfuwc6kdW9h^0hYTcvf}2HHlac@iLrMhHoeR01@h;sY>`1yV^iZZ?vD3M!(g z9aA4|@c~t-Xr+LIFs*jVIHfk!_j77|j*lXWU{tVH@N|PfTL=5McV_qAd*=JT^WA&S z?3Se@O%0-l(h&p+QY9!f)a>#;0lw6Gb7^J`HH{^e>0~ONP3CI}43Qad9fqn*+8j)S zX$_7At=MD)@nsp)(#dpnqC}6II9e};V>ekSHiAr!v0JqI`51}nupFaV%IrGW%tVa_ zDRX9|ny0qNv0P(90fD6!B&F#K=Ig}%(P9oiny(i`XKQsIq5_^kz~za!{3y0SAc=^S z2>Iy1U{VPQL$*Yth#yEt?WD|HlC(&;-2D7}PJRRjCvv!au~^LI3Ah3Qn?kUy4l}8> zv(479K?Mb7)e}YwX~fN_S5d3OZKRY*nSFi=lVwQOY#q2M>dv@!t%b|y@VuuQ1gh2l z4KaUo`iCvX$me`<+w7%$P0 zaS`!6xrove4)5hT*YHv=BIQfHa49ofZ*Bik>%kD!K;Gq0^HQ6k_Q%Xr&l6O0?|oDr zgdjc(QWDdY$ZUAp3-9ECa1r1;K)n{)J@DNrKye712e&%GF9SZX!sT{2aSfzP;l@4C zZw8+^u>UyJAA|4(;GYFC%VFATV3DwTKa|$PdjyD}-QD4CPdyVmrr7hS zo|WL&xasrLGj8v(`_Ng}*(-_N*OvNETt!=5%)FC@w_hg@A4+sz5IWAZJ!u**XvGEP zmks*fo`hEzXlya!LsNtrgqqGKyQ^^LC8fu?flkl^7{}Nw*L08b2>rnf)Q~$lrG0Lk zEHnA?#80!QhRbTl0-hLBb!J3}FRiMl^UK(f^=NV;8ZkY#!q#DXyj1V(Y<+#xt|FE! z%OUi9Pj~&;w{}|R35QKw`AsDwcyHL2mb%7b#K>~h&P4ZSF5TKguNvu!ac;}|ssdZH zP?kBS``)sQ6RzzNxf?3}s0gk8S$?27xaEfD`e+ZM!6q4SJ|f`Xi&1{FNCpw+-oe(l z%3KdCkGTuFf0Mbo3vjO6FOcR#dyy~@sgaeQ!@Ae3%u^oe3kjZ375BAftjD?Bm)4TO z$U0oz(D3$aGWuug=HsWM$1S@_0)yYh2qzU0;Q=F7NuA=l*z=c0&T?$P8|QZUKaM-E zJlgRlx@7!wZ%qFOCoek_I>vf9$z6DUea None: - try: - StepfunTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "prompt": "cute girl, blue eyes, white hair, anime style", - "size": "1024x1024", - "n": 1, - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/stepfun/stepfun.yaml b/api/core/tools/provider/builtin/stepfun/stepfun.yaml deleted file mode 100644 index 1f841ec369b5c3..00000000000000 --- a/api/core/tools/provider/builtin/stepfun/stepfun.yaml +++ /dev/null @@ -1,46 +0,0 @@ -identity: - author: Stepfun - name: stepfun - label: - en_US: Image-1X - zh_Hans: 阶跃星辰绘画 - pt_BR: Image-1X - description: - en_US: Image-1X - zh_Hans: 阶跃星辰绘画 - pt_BR: Image-1X - icon: icon.png - tags: - - image - - productivity -credentials_for_provider: - stepfun_api_key: - type: secret-input - required: true - label: - en_US: Stepfun API key - zh_Hans: 阶跃星辰API key - pt_BR: Stepfun API key - help: - en_US: Please input your stepfun API key - zh_Hans: 请输入你的阶跃星辰 API key - pt_BR: Please input your stepfun API key - placeholder: - en_US: Please input your stepfun API key - zh_Hans: 请输入你的阶跃星辰 API key - pt_BR: Please input your stepfun API key - stepfun_base_url: - type: text-input - required: false - label: - en_US: Stepfun base URL - zh_Hans: 阶跃星辰 base URL - pt_BR: Stepfun base URL - help: - en_US: Please input your Stepfun base URL - zh_Hans: 请输入你的阶跃星辰 base URL - pt_BR: Please input your Stepfun base URL - placeholder: - en_US: Please input your Stepfun base URL - zh_Hans: 请输入你的阶跃星辰 base URL - pt_BR: Please input your Stepfun base URL diff --git a/api/core/tools/provider/builtin/stepfun/tools/image.py b/api/core/tools/provider/builtin/stepfun/tools/image.py deleted file mode 100644 index 0b92b122bf59bc..00000000000000 --- a/api/core/tools/provider/builtin/stepfun/tools/image.py +++ /dev/null @@ -1,75 +0,0 @@ -import random -from typing import Any, Union - -from openai import OpenAI -from yarl import URL - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class StepfunTool(BuiltinTool): - """Stepfun Image Generation Tool""" - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - base_url = self.runtime.credentials.get("stepfun_base_url", "https://api.stepfun.com") - base_url = str(URL(base_url) / "v1") - - client = OpenAI( - api_key=self.runtime.credentials["stepfun_api_key"], - base_url=base_url, - ) - - extra_body = {} - model = tool_parameters.get("model", "step-1x-medium") - if not model: - return self.create_text_message("Please input model name") - # prompt - prompt = tool_parameters.get("prompt", "") - if not prompt: - return self.create_text_message("Please input prompt") - - seed = tool_parameters.get("seed", 0) - if seed > 0: - extra_body["seed"] = seed - steps = tool_parameters.get("steps", 0) - if steps > 0: - extra_body["steps"] = steps - negative_prompt = tool_parameters.get("negative_prompt", "") - if negative_prompt: - extra_body["negative_prompt"] = negative_prompt - - # call openapi stepfun model - response = client.images.generate( - prompt=prompt, - model=model, - size=tool_parameters.get("size", "1024x1024"), - n=tool_parameters.get("n", 1), - extra_body=extra_body, - ) - print(response) - - result = [] - for image in response.data: - result.append(self.create_image_message(image=image.url)) - result.append( - self.create_json_message( - { - "url": image.url, - } - ) - ) - return result - - @staticmethod - def _generate_random_id(length=8): - characters = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789" - random_id = "".join(random.choices(characters, k=length)) - return random_id diff --git a/api/core/tools/provider/builtin/stepfun/tools/image.yaml b/api/core/tools/provider/builtin/stepfun/tools/image.yaml deleted file mode 100644 index dcc5bd2db2f5ba..00000000000000 --- a/api/core/tools/provider/builtin/stepfun/tools/image.yaml +++ /dev/null @@ -1,158 +0,0 @@ -identity: - name: stepfun - author: Stepfun - label: - en_US: step-1x - zh_Hans: 阶跃星辰绘画 - pt_BR: step-1x - description: - en_US: step-1x is a powerful drawing tool by stepfun, you can draw the image based on your prompt - zh_Hans: step-1x 系列是阶跃星辰提供的强大的绘画工具，它可以根据您的提示词绘制出您想要的图像。 - pt_BR: step-1x is a powerful drawing tool by stepfun, you can draw the image based on your prompt -description: - human: - en_US: step-1x is a text to image tool - zh_Hans: step-1x 是一个文本/图像到图像的工具 - pt_BR: step-1x is a text to image tool - llm: step-1x is a tool used to generate images from text or image -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: Image prompt, you can check the official documentation of step-1x - zh_Hans: 图像提示词，您可以查看 step-1x 的官方文档 - pt_BR: Image prompt, you can check the official documentation of step-1x - llm_description: Image prompt of step-1x you should describe the image you want to generate as a list of words as possible as detailed - form: llm - - name: model - type: select - required: false - human_description: - en_US: used for selecting the model name - zh_Hans: 用于选择模型的名字 - pt_BR: used for selecting the model name - label: - en_US: Model Name - zh_Hans: 模型名字 - pt_BR: Model Name - form: form - options: - - value: step-1x-turbo - label: - en_US: turbo - zh_Hans: turbo - pt_BR: turbo - - value: step-1x-medium - label: - en_US: medium - zh_Hans: medium - pt_BR: medium - - value: step-1x-large - label: - en_US: large - zh_Hans: large - pt_BR: large - default: step-1x-medium - - name: size - type: select - required: false - human_description: - en_US: used for selecting the image size - zh_Hans: 用于选择图像大小 - pt_BR: used for selecting the image size - label: - en_US: Image size - zh_Hans: 图像大小 - pt_BR: Image size - form: form - options: - - value: 256x256 - label: - en_US: 256x256 - zh_Hans: 256x256 - pt_BR: 256x256 - - value: 512x512 - label: - en_US: 512x512 - zh_Hans: 512x512 - pt_BR: 512x512 - - value: 768x768 - label: - en_US: 768x768 - zh_Hans: 768x768 - pt_BR: 768x768 - - value: 1024x1024 - label: - en_US: 1024x1024 - zh_Hans: 1024x1024 - pt_BR: 1024x1024 - - value: 1280x800 - label: - en_US: 1280x800 - zh_Hans: 1280x800 - pt_BR: 1280x800 - - value: 800x1280 - label: - en_US: 800x1280 - zh_Hans: 800x1280 - pt_BR: 800x1280 - default: 1024x1024 - - name: n - type: number - required: true - human_description: - en_US: used for selecting the number of images - zh_Hans: 用于选择图像数量 - pt_BR: used for selecting the number of images - label: - en_US: Number of images - zh_Hans: 图像数量 - pt_BR: Number of images - form: form - default: 1 - min: 1 - max: 10 - - name: seed - type: number - required: false - label: - en_US: seed - zh_Hans: seed - pt_BR: seed - human_description: - en_US: seed - zh_Hans: seed - pt_BR: seed - form: form - default: 10 - - name: steps - type: number - required: false - label: - en_US: Steps - zh_Hans: Steps - pt_BR: Steps - human_description: - en_US: Steps - zh_Hans: Steps - pt_BR: Steps - 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-from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.tavily.tools.tavily_search import TavilySearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class TavilyProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - TavilySearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "query": "Sachin Tendulkar", - "search_depth": "basic", - "include_answer": True, - "include_images": False, - "include_raw_content": False, - "max_results": 5, - "include_domains": "", - "exclude_domains": "", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/tavily/tavily.yaml b/api/core/tools/provider/builtin/tavily/tavily.yaml deleted file mode 100644 index 7b25a8184857ca..00000000000000 --- a/api/core/tools/provider/builtin/tavily/tavily.yaml +++ /dev/null @@ -1,31 +0,0 @@ -identity: - author: Yash Parmar - name: tavily - label: - en_US: Tavily - zh_Hans: Tavily - pt_BR: Tavily - description: - en_US: Tavily - zh_Hans: Tavily - pt_BR: Tavily - icon: icon.png - tags: - - search -credentials_for_provider: - tavily_api_key: - type: secret-input - required: true - label: - en_US: Tavily API key - zh_Hans: Tavily API key - pt_BR: Tavily API key - placeholder: - en_US: Please input your Tavily API key - zh_Hans: 请输入你的 Tavily API key - pt_BR: Please input your Tavily API key - help: - en_US: Get your Tavily API key from Tavily - zh_Hans: 从 TavilyApi 获取您的 Tavily API key - pt_BR: Get your Tavily API key from Tavily - url: https://docs.tavily.com/docs/tavily-api/introduction diff --git a/api/core/tools/provider/builtin/tavily/tools/tavily_search.py b/api/core/tools/provider/builtin/tavily/tools/tavily_search.py deleted file mode 100644 index ca6d8633e4b0af..00000000000000 --- a/api/core/tools/provider/builtin/tavily/tools/tavily_search.py +++ /dev/null @@ -1,124 +0,0 @@ -from typing import Any - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -TAVILY_API_URL = "https://api.tavily.com" - - -class TavilySearch: - """ - A class for performing search operations using the Tavily Search API. - - Args: - api_key (str): The API key for accessing the Tavily Search API. - - Methods: - raw_results: Retrieves raw search results from the Tavily Search API. - results: Retrieves cleaned search results from the Tavily Search API. - clean_results: Cleans the raw search results. - """ - - def __init__(self, api_key: str) -> None: - self.api_key = api_key - - def raw_results(self, params: dict[str, Any]) -> dict: - """ - Retrieves raw search results from the Tavily Search API. - - Args: - params (Dict[str, Any]): The search parameters. - - Returns: - dict: The raw search results. - - """ - params["api_key"] = self.api_key - if ( - "exclude_domains" in params - and isinstance(params["exclude_domains"], str) - and params["exclude_domains"] != "None" - ): - params["exclude_domains"] = params["exclude_domains"].split() - else: - params["exclude_domains"] = [] - if ( - "include_domains" in params - and isinstance(params["include_domains"], str) - and params["include_domains"] != "None" - ): - params["include_domains"] = params["include_domains"].split() - else: - params["include_domains"] = [] - - response = requests.post(f"{TAVILY_API_URL}/search", json=params) - response.raise_for_status() - return response.json() - - def results(self, params: dict[str, Any]) -> list[dict]: - """ - Retrieves cleaned search results from the Tavily Search API. - - Args: - params (Dict[str, Any]): The search parameters. - - Returns: - list: The cleaned search results. - - """ - raw_search_results = self.raw_results(params) - return self.clean_results(raw_search_results["results"]) - - def clean_results(self, results: list[dict]) -> list[dict]: - """ - Cleans the raw search results. - - Args: - results (list): The raw search results. - - Returns: - list: The cleaned search results. - - """ - clean_results = [] - for result in results: - clean_results.append( - { - "url": result["url"], - "content": result["content"], - } - ) - # return clean results as a string - return "\n".join([f"{res['url']}\n{res['content']}" for res in clean_results]) - - -class TavilySearchTool(BuiltinTool): - """ - A tool for searching Tavily using a given query. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> ToolInvokeMessage | list[ToolInvokeMessage]: - """ - Invokes the Tavily search tool with the given user ID and tool parameters. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (Dict[str, Any]): The parameters for the Tavily search tool. - - Returns: - ToolInvokeMessage | list[ToolInvokeMessage]: The result of the Tavily search tool invocation. - """ - query = tool_parameters.get("query", "") - - api_key = self.runtime.credentials["tavily_api_key"] - if not query: - return self.create_text_message("Please input query") - tavily_search = TavilySearch(api_key) - results = tavily_search.results(tool_parameters) - print(results) - if not results: - return self.create_text_message(f"No results found for '{query}' in Tavily") - else: - return self.create_text_message(text=results) diff --git a/api/core/tools/provider/builtin/tavily/tools/tavily_search.yaml b/api/core/tools/provider/builtin/tavily/tools/tavily_search.yaml deleted file mode 100644 index 88426056afb353..00000000000000 --- a/api/core/tools/provider/builtin/tavily/tools/tavily_search.yaml +++ /dev/null @@ -1,162 +0,0 @@ -identity: - name: tavily_search - author: Yash Parmar - label: - en_US: TavilySearch - zh_Hans: TavilySearch - pt_BR: TavilySearch -description: - human: - en_US: A tool for search engine built specifically for AI agents (LLMs), delivering real-time, accurate, and factual results at speed. - zh_Hans: 专为人工智能代理 (LLM) 构建的搜索引擎工具，可快速提供实时、准确和真实的结果。 - pt_BR: A tool for search engine built specifically for AI agents (LLMs), delivering real-time, accurate, and factual results at speed. - llm: A tool for search engine built specifically for AI agents (LLMs), delivering real-time, accurate, and factual results at speed. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - pt_BR: Query string - human_description: - en_US: used for searching - zh_Hans: 用于搜索网页内容 - pt_BR: used for searching - llm_description: key words for searching - form: llm - - name: search_depth - type: select - required: false - label: - en_US: Search Depth - zh_Hans: 搜索深度 - pt_BR: Search Depth - human_description: - en_US: The depth of search results - zh_Hans: 搜索结果的深度 - pt_BR: The depth of search results - form: form - options: - - value: basic - label: - en_US: Basic - zh_Hans: 基本 - pt_BR: Basic - - value: advanced - label: - en_US: Advanced - zh_Hans: 高级 - pt_BR: Advanced - default: basic - - name: include_images - type: boolean - required: false - label: - en_US: Include Images - zh_Hans: 包含图片 - pt_BR: Include Images - human_description: - en_US: Include images in the search results - zh_Hans: 在搜索结果中包含图片 - pt_BR: Include images in the search results - form: form - options: - - value: 'true' - label: - en_US: 'Yes' - zh_Hans: 是 - pt_BR: 'Yes' - - value: 'false' - label: - en_US: 'No' - zh_Hans: 否 - pt_BR: 'No' - default: 'false' - - name: include_answer - type: boolean - required: false - label: - en_US: Include Answer - zh_Hans: 包含答案 - pt_BR: Include Answer - human_description: - en_US: Include answers in the search results - zh_Hans: 在搜索结果中包含答案 - pt_BR: Include answers in the search results - form: form - options: - - value: 'true' - label: - en_US: 'Yes' - zh_Hans: 是 - pt_BR: 'Yes' - - value: 'false' - label: - en_US: 'No' - zh_Hans: 否 - pt_BR: 'No' - default: 'false' - - name: include_raw_content - type: boolean - required: false - label: - en_US: Include Raw Content - zh_Hans: 包含原始内容 - pt_BR: Include Raw Content - human_description: - en_US: Include raw content in the search results - zh_Hans: 在搜索结果中包含原始内容 - pt_BR: Include raw content in the search results - form: form - options: - - value: 'true' - label: - en_US: 'Yes' - zh_Hans: 是 - pt_BR: 'Yes' - - value: 'false' - label: - en_US: 'No' - zh_Hans: 否 - pt_BR: 'No' - default: 'false' - - name: max_results - type: number - required: false - label: - en_US: Max Results - zh_Hans: 最大结果 - pt_BR: Max Results - human_description: - en_US: The number of maximum search results to return - zh_Hans: 返回的最大搜索结果数 - pt_BR: The number of maximum search results to return - form: form - min: 1 - max: 20 - default: 5 - - name: include_domains - type: string - required: false - label: - en_US: Include Domains - zh_Hans: 包含域 - pt_BR: Include Domains - human_description: - en_US: A list of domains to specifically include in the search results - zh_Hans: 在搜索结果中特别包含的域名列表 - pt_BR: A list of domains to specifically include in the search results - form: form - - name: exclude_domains - type: string - required: false - label: - en_US: Exclude Domains - zh_Hans: 排除域 - pt_BR: Exclude Domains - human_description: - en_US: A list of domains to specifically exclude from the search results - zh_Hans: 从搜索结果中特别排除的域名列表 - pt_BR: A list of domains to specifically exclude from the search results - form: form diff --git a/api/core/tools/provider/builtin/tianditu/_assets/icon.svg b/api/core/tools/provider/builtin/tianditu/_assets/icon.svg deleted file mode 100644 index 749d4bda265ab0..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/_assets/icon.svg +++ /dev/null @@ -1,21 +0,0 @@ - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/tianditu/tianditu.py b/api/core/tools/provider/builtin/tianditu/tianditu.py deleted file mode 100644 index cb7d7bd8bb2c41..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/tianditu.py +++ /dev/null @@ -1,23 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.tianditu.tools.poisearch import PoiSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class TiandituProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - PoiSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "content": "北京", - "specify": "156110000", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/tianditu/tianditu.yaml b/api/core/tools/provider/builtin/tianditu/tianditu.yaml deleted file mode 100644 index 77af834bdc5893..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/tianditu.yaml +++ /dev/null @@ -1,32 +0,0 @@ -identity: - author: Listeng - name: tianditu - label: - en_US: Tianditu - zh_Hans: 天地图 - pt_BR: Tianditu - description: - en_US: The Tianditu tool provided the functions of place name search, geocoding, static maps generation, etc. in China region. - zh_Hans: 天地图工具可以调用天地图的接口，实现中国区域内的地名搜索、地理编码、静态地图等功能。 - pt_BR: The Tianditu tool provided the functions of place name search, geocoding, static maps generation, etc. in China region. - icon: icon.svg - tags: - - utilities - - travel -credentials_for_provider: - tianditu_api_key: - type: secret-input - required: true - label: - en_US: Tianditu API Key - zh_Hans: 天地图Key - pt_BR: Tianditu API key - placeholder: - en_US: Please input your Tianditu API key - zh_Hans: 请输入你的天地图Key - pt_BR: Please input your Tianditu API key - help: - en_US: Get your Tianditu API key from Tianditu - zh_Hans: 获取您的天地图Key - pt_BR: Get your Tianditu API key from Tianditu - url: http://lbs.tianditu.gov.cn/home.html diff --git a/api/core/tools/provider/builtin/tianditu/tools/geocoder.py b/api/core/tools/provider/builtin/tianditu/tools/geocoder.py deleted file mode 100644 index 690a0aed6f5aff..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/tools/geocoder.py +++ /dev/null @@ -1,33 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GeocoderTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - base_url = "http://api.tianditu.gov.cn/geocoder" - - keyword = tool_parameters.get("keyword", "") - if not keyword: - return self.create_text_message("Invalid parameter keyword") - - tk = self.runtime.credentials["tianditu_api_key"] - - params = { - "keyWord": keyword, - } - - result = requests.get(base_url + "?ds=" + json.dumps(params, ensure_ascii=False) + "&tk=" + tk).json() - - return self.create_json_message(result) diff --git a/api/core/tools/provider/builtin/tianditu/tools/geocoder.yaml b/api/core/tools/provider/builtin/tianditu/tools/geocoder.yaml deleted file mode 100644 index d6a168f9502019..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/tools/geocoder.yaml +++ /dev/null @@ -1,26 +0,0 @@ -identity: - name: geocoder - author: Listeng - label: - en_US: Get coords converted from address name - zh_Hans: 地理编码 - pt_BR: Get coords converted from address name -description: - human: - en_US: Geocoder - zh_Hans: 中国区域地理编码查询 - pt_BR: Geocoder - llm: A tool for geocoder in China -parameters: - - name: keyword - type: string - required: true - label: - en_US: keyword - zh_Hans: 搜索的关键字 - pt_BR: keyword - human_description: - en_US: keyword - zh_Hans: 搜索的关键字 - pt_BR: keyword - form: llm diff --git a/api/core/tools/provider/builtin/tianditu/tools/poisearch.py b/api/core/tools/provider/builtin/tianditu/tools/poisearch.py deleted file mode 100644 index 798dd94d335654..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/tools/poisearch.py +++ /dev/null @@ -1,58 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class PoiSearchTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - geocoder_base_url = "http://api.tianditu.gov.cn/geocoder" - base_url = "http://api.tianditu.gov.cn/v2/search" - - keyword = tool_parameters.get("keyword", "") - if not keyword: - return self.create_text_message("Invalid parameter keyword") - - baseAddress = tool_parameters.get("baseAddress", "") - if not baseAddress: - return self.create_text_message("Invalid parameter baseAddress") - - tk = self.runtime.credentials["tianditu_api_key"] - - base_coords = requests.get( - geocoder_base_url - + "?ds=" - + json.dumps( - { - "keyWord": baseAddress, - }, - ensure_ascii=False, - ) - + "&tk=" - + tk - ).json() - - params = { - "keyWord": keyword, - "queryRadius": 5000, - "queryType": 3, - "pointLonlat": base_coords["location"]["lon"] + "," + base_coords["location"]["lat"], - "start": 0, - "count": 100, - } - - result = requests.get( - base_url + "?postStr=" + json.dumps(params, ensure_ascii=False) + "&type=query&tk=" + tk - ).json() - - return self.create_json_message(result) diff --git a/api/core/tools/provider/builtin/tianditu/tools/poisearch.yaml b/api/core/tools/provider/builtin/tianditu/tools/poisearch.yaml deleted file mode 100644 index 01289d24e3d29a..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/tools/poisearch.yaml +++ /dev/null @@ -1,38 +0,0 @@ -identity: - name: point_of_interest_search - author: Listeng - label: - en_US: Point of Interest search - zh_Hans: 兴趣点搜索 - pt_BR: Point of Interest search -description: - human: - en_US: Search for certain types of points of interest around a location - zh_Hans: 搜索某个位置周边的5公里内某种类型的兴趣点 - pt_BR: Search for certain types of points of interest around a location - llm: A tool for searching for certain types of points of interest around a location -parameters: - - name: keyword - type: string - required: true - label: - en_US: poi keyword - zh_Hans: 兴趣点的关键字 - pt_BR: poi keyword - human_description: - en_US: poi keyword - zh_Hans: 兴趣点的关键字 - pt_BR: poi keyword - form: llm - - name: baseAddress - type: string - required: true - label: - en_US: base current point - zh_Hans: 当前位置的关键字 - pt_BR: base current point - human_description: - en_US: base current point - zh_Hans: 当前位置的关键字 - pt_BR: base current point - form: llm diff --git a/api/core/tools/provider/builtin/tianditu/tools/staticmap.py b/api/core/tools/provider/builtin/tianditu/tools/staticmap.py deleted file mode 100644 index aeaef088057686..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/tools/staticmap.py +++ /dev/null @@ -1,49 +0,0 @@ -import json -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class PoiSearchTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - - geocoder_base_url = "http://api.tianditu.gov.cn/geocoder" - base_url = "http://api.tianditu.gov.cn/staticimage" - - keyword = tool_parameters.get("keyword", "") - if not keyword: - return self.create_text_message("Invalid parameter keyword") - - tk = self.runtime.credentials["tianditu_api_key"] - - keyword_coords = requests.get( - geocoder_base_url - + "?ds=" - + json.dumps( - { - "keyWord": keyword, - }, - ensure_ascii=False, - ) - + "&tk=" - + tk - ).json() - coords = keyword_coords["location"]["lon"] + "," + keyword_coords["location"]["lat"] - - result = requests.get( - base_url + "?center=" + coords + "&markers=" + coords + "&width=400&height=300&zoom=14&tk=" + tk - ).content - - return self.create_blob_message( - blob=result, meta={"mime_type": "image/png"}, save_as=self.VariableKey.IMAGE.value - ) diff --git a/api/core/tools/provider/builtin/tianditu/tools/staticmap.yaml b/api/core/tools/provider/builtin/tianditu/tools/staticmap.yaml deleted file mode 100644 index fc54c428066af5..00000000000000 --- a/api/core/tools/provider/builtin/tianditu/tools/staticmap.yaml +++ /dev/null @@ -1,26 +0,0 @@ -identity: - name: generate_static_map - author: Listeng - label: - en_US: Generate a static map - zh_Hans: 生成静态地图 - pt_BR: Generate a static map -description: - human: - en_US: Generate a static map - zh_Hans: 生成静态地图 - pt_BR: Generate a static map - llm: A tool for generate a static map -parameters: - - name: keyword - type: string - required: true - label: - en_US: keyword - zh_Hans: 搜索的关键字 - pt_BR: keyword - human_description: - en_US: keyword - zh_Hans: 搜索的关键字 - pt_BR: keyword - form: llm diff --git a/api/core/tools/provider/builtin/trello/_assets/icon.svg b/api/core/tools/provider/builtin/trello/_assets/icon.svg deleted file mode 100644 index f8e2bd47c0b818..00000000000000 --- a/api/core/tools/provider/builtin/trello/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/trello/tools/create_board.py b/api/core/tools/provider/builtin/trello/tools/create_board.py deleted file mode 100644 index 5a61d221578995..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/create_board.py +++ /dev/null @@ -1,44 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class CreateBoardTool(BuiltinTool): - """ - Tool for creating a new Trello board. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to create a new Trello board. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_name = tool_parameters.get("name") - - if not (api_key and token and board_name): - return self.create_text_message("Missing required parameters: API key, token, or board name.") - - url = "https://api.trello.com/1/boards/" - query_params = {"name": board_name, "key": api_key, "token": token} - - try: - response = requests.post(url, params=query_params) - response.raise_for_status() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to create board") - - board = response.json() - return self.create_text_message( - text=f"Board created successfully! Board name: {board['name']}, ID: {board['id']}" - ) diff --git a/api/core/tools/provider/builtin/trello/tools/create_board.yaml b/api/core/tools/provider/builtin/trello/tools/create_board.yaml deleted file mode 100644 index 60dbab61f5ee5c..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/create_board.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: create_board - author: Yash Parmar - label: - en_US: Create Board - zh_Hans: 创建看板 - pt_BR: Criar Quadro -description: - human: - en_US: Creates a new Trello board with a specified name. This tool allows users to quickly add new boards to their Trello account, facilitating project organization and management. - zh_Hans: 使用指定的名称创建一个新的 Trello 看板。此工具允许用户快速向其 Trello 账户添加新的看板，促进项目组织和管理。 - pt_BR: Cria um novo quadro Trello com um nome especificado. Esta ferramenta permite que os usuários adicionem rapidamente novos quadros à sua conta Trello, facilitando a organização e gestão de projetos. - llm: Create a new Trello board using the specified name. This functionality simplifies the addition of boards, enhancing project organization and management within Trello. -parameters: - - name: name - type: string - required: true - label: - en_US: Board Name - zh_Hans: 看板名称 - pt_BR: Nome do Quadro - human_description: - en_US: The name for the new Trello board. This name helps in identifying and organizing your projects on Trello. - zh_Hans: 新 Trello 看板的名称。这个名称有助于在 Trello 上识别和组织您的项目。 - pt_BR: O nome para o novo quadro Trello. Este nome ajuda a identificar e organizar seus projetos no Trello. - llm_description: Specify the name for your new Trello board, aiding in project identification and organization within Trello. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/create_list_on_board.py b/api/core/tools/provider/builtin/trello/tools/create_list_on_board.py deleted file mode 100644 index b32b0124dd31da..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/create_list_on_board.py +++ /dev/null @@ -1,46 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class CreateListOnBoardTool(BuiltinTool): - """ - Tool for creating a list on a Trello board by its ID. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to create a list on a Trello board by its ID. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, - including the board ID and list name. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_id = tool_parameters.get("id") - list_name = tool_parameters.get("name") - - if not (api_key and token and board_id and list_name): - return self.create_text_message("Missing required parameters: API key, token, board ID, or list name.") - - url = f"https://api.trello.com/1/boards/{board_id}/lists" - params = {"name": list_name, "key": api_key, "token": token} - - try: - response = requests.post(url, params=params) - response.raise_for_status() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to create list") - - new_list = response.json() - return self.create_text_message( - text=f"List '{new_list['name']}' created successfully with Id {new_list['id']} on board {board_id}." - ) diff --git a/api/core/tools/provider/builtin/trello/tools/create_list_on_board.yaml b/api/core/tools/provider/builtin/trello/tools/create_list_on_board.yaml deleted file mode 100644 index 789b92437a3b3e..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/create_list_on_board.yaml +++ /dev/null @@ -1,40 +0,0 @@ -identity: - name: create_list_on_board - author: Yash Parmar - label: - en_US: Create List on Board - zh_Hans: 在看板上创建列表 - pt_BR: Criar Lista no Quadro -description: - human: - en_US: Creates a new list on a specified Trello board by providing the board's ID and the desired name for the list. Streamlines the process of organizing board content. - zh_Hans: 通过提供看板的 ID 和列表的所需名称，在指定的 Trello 看板上创建一个新列表。简化了组织看板内容的过程。 - pt_BR: Cria uma nova lista em um quadro Trello especificado, fornecendo o ID do quadro e o nome desejado para a lista. Facilita o processo de organização do conteúdo do quadro. - llm: Generate a new list within a Trello board by specifying the board's ID and a name for the list. Enhances board management by allowing quick additions of new lists. -parameters: - - name: id - type: string - required: true - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: The unique identifier of the Trello board where the new list will be created. - zh_Hans: 新列表将被创建在其上的 Trello 看板的唯一标识符。 - pt_BR: O identificador único do quadro Trello onde a nova lista será criada. - llm_description: Input the ID of the Trello board to pinpoint where the new list should be added, ensuring correct placement. - form: llm - - name: name - type: string - required: true - label: - en_US: List Name - zh_Hans: 列表名称 - pt_BR: Nome da Lista - human_description: - en_US: The name for the new list to be created on the Trello board. - zh_Hans: 将在 Trello 看板上创建的新列表的名称。 - pt_BR: O nome para a nova lista que será criada no quadro Trello. - llm_description: Provide a name for the new list, defining its purpose or content focus, to facilitate board organization. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/create_new_card_on_board.py b/api/core/tools/provider/builtin/trello/tools/create_new_card_on_board.py deleted file mode 100644 index e98efb81ca673e..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/create_new_card_on_board.py +++ /dev/null @@ -1,45 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class CreateNewCardOnBoardTool(BuiltinTool): - """ - Tool for creating a new card on a Trello board. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool, None]]) -> ToolInvokeMessage: - """ - Invoke the tool to create a new card on a Trello board. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation, - including details for the new card. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - - # Ensure required parameters are present - if "name" not in tool_parameters or "idList" not in tool_parameters: - return self.create_text_message("Missing required parameters: name or idList.") - - url = "https://api.trello.com/1/cards" - params = {**tool_parameters, "key": api_key, "token": token} - - try: - response = requests.post(url, params=params) - response.raise_for_status() - new_card = response.json() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to create card") - - return self.create_text_message( - text=f"New card '{new_card['name']}' created successfully with ID {new_card['id']}." - ) diff --git a/api/core/tools/provider/builtin/trello/tools/create_new_card_on_board.yaml b/api/core/tools/provider/builtin/trello/tools/create_new_card_on_board.yaml deleted file mode 100644 index 9953af718ddd58..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/create_new_card_on_board.yaml +++ /dev/null @@ -1,145 +0,0 @@ -identity: - name: create_new_card_on_board - author: Yash Parmar - label: - en_US: Create New Card on Board - zh_Hans: 在看板上创建新卡片 - pt_BR: Criar Novo Cartão no Quadro -description: - human: - en_US: Creates a new card on a Trello board with specified details like name, description, list ID, and other optional parameters. Facilitates task addition and project management within Trello. - zh_Hans: 用指定的详情（如名称、描述、列表 ID 和其他可选参数）在 Trello 看板上创建一个新卡片。便于在 Trello 中添加任务和管理项目。 - pt_BR: Cria um novo cartão em um quadro Trello com detalhes especificados, como nome, descrição, ID da lista e outros parâmetros opcionais. Facilita a adição de tarefas e a gestão de projetos dentro do Trello. - llm: Initiate a new card on a Trello board by specifying essential details such as the card's name, description, and the list it belongs to, among other settings. Streamlines project task additions and organizational workflows. -parameters: - - name: name - type: string - required: true - label: - en_US: Card Name - zh_Hans: 卡片名称 - pt_BR: Nome do Cartão - human_description: - en_US: The name for the new card. Acts as the primary identifier and summary of the card's purpose. - zh_Hans: 新卡片的名称。作为卡片目的的主要标识和总结。 - pt_BR: O nome para o novo cartão. Funciona como o identificador principal e resumo do propósito do cartão. - llm_description: Provide a concise, descriptive name for the card, outlining its main focus or task. - form: llm - # Include additional parameters like desc, pos, due, idList, etc., following the same pattern. - - name: desc - type: string - required: false - label: - en_US: Card Description - zh_Hans: 卡片描述 - pt_BR: Descrição do Cartão - human_description: - en_US: Optional. A brief description of the card's purpose or contents. - zh_Hans: 可选。卡片目的或内容的简要描述。 - pt_BR: Opcional. Uma breve descrição do propósito ou conteúdo do cartão. - llm_description: Add a brief description to the card to provide context or additional information about its purpose. - form: llm - - name: pos - type: string - required: false - label: - en_US: Position - zh_Hans: 位置 - pt_BR: Posição - human_description: - en_US: Optional. The position of the card in the list. Can be 'top', 'bottom', or a positive number. - zh_Hans: 可选。卡片在列表中的位置。可以是“top”、“bottom” 或正数。 - pt_BR: Opcional. A posição do cartão na lista. Pode ser 'top', 'bottom' ou um número positivo. - llm_description: Specify the position of the card within the list, either at the top, bottom, or a specific numerical index. - form: llm - - name: due - type: string - required: false - label: - en_US: Due Date - zh_Hans: 截止日期 - pt_BR: Data de Vencimento - human_description: - en_US: Optional. The due date for the card in the format 'MM/DD/YYYY'. - zh_Hans: 可选。卡片的截止日期，格式为“MM/DD/YYYY”。 - pt_BR: Opcional. A data de vencimento do cartão no formato 'MM/DD/YYYY'. - llm_description: Set a due date for the card to establish a deadline for completion or action. - form: llm - - name: start - type: string - required: false - label: - en_US: Start Date - zh_Hans: 开始日期 - pt_BR: Data de Início - human_description: - en_US: Optional. The start date for the card in the format 'MM/DD/YYYY'. - zh_Hans: 可选。卡片的开始日期，格式为“MM/DD/YYYY”。 - pt_BR: Opcional. A data de início do cartão no formato 'MM/DD/YYYY'. - llm_description: Specify a start date for the card to mark the beginning of a task or project phase. - form: llm - - name: dueComplete - type: boolean - required: false - label: - en_US: Due Complete - zh_Hans: 截止日期已完成 - pt_BR: Vencimento Concluído - human_description: - en_US: Optional. Set to true if the due date has been completed, or false if it is pending. - zh_Hans: 可选。如果截止日期已完成，则设置为 true；如果尚未完成，则设置为 false。 - pt_BR: Opcional. Defina como true se a data de vencimento foi concluída, ou como false se estiver pendente. - llm_description: Indicate whether the due date for the card has been marked as complete or is still pending. - form: llm - - name: idList - type: string - required: true - label: - en_US: List ID - zh_Hans: 列表 ID - pt_BR: ID da Lista - human_description: - en_US: The unique identifier of the list where the card will be added. - zh_Hans: 卡片将被添加到的列表的唯一标识符。 - pt_BR: O identificador único da lista onde o cartão será adicionado. - llm_description: Input the ID of the list where the card should be placed, ensuring it is added to the correct list. - form: llm - - name: idMembers - type: string - required: false - label: - en_US: Member IDs - zh_Hans: 成员 ID - pt_BR: IDs de Membros - human_description: - en_US: Optional. The IDs of members to assign to the card. - zh_Hans: 可选。要分配给卡片的成员的 ID。 - pt_BR: Opcional. Os IDs dos membros a serem atribuídos ao cartão. - llm_description: Specify the IDs of members to assign to the card, allowing for task delegation or collaboration. - form: llm - - name: idLabels - type: string - required: false - label: - en_US: Label IDs - zh_Hans: 标签 ID - pt_BR: IDs de Etiquetas - human_description: - en_US: Optional. The IDs of labels to assign to the card. - zh_Hans: 可选。要分配给卡片的标签的 ID。 - pt_BR: Opcional. Os IDs das etiquetas a serem atribuídos ao cartão. - llm_description: Assign specific labels to the card by providing their IDs, aiding in visual categorization or prioritization. - form: llm - - name: urlSource - type: string - required: false - label: - en_US: Source URL - zh_Hans: 来源 URL - pt_BR: URL de Origem - human_description: - en_US: Optional. The URL to attach as the card's source. - zh_Hans: 可选。要附加为卡片来源的 URL。 - pt_BR: Opcional. O URL a ser anexado como a fonte do cartão. - llm_description: Provide a URL to serve as the source reference for the card, linking to external resources or documents. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/delete_board.py b/api/core/tools/provider/builtin/trello/tools/delete_board.py deleted file mode 100644 index 7fc9d1f13c2664..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/delete_board.py +++ /dev/null @@ -1,41 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DeleteBoardTool(BuiltinTool): - """ - Tool for deleting a Trello board by ID. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to delete a Trello board by its ID. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, - including the board ID. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_id = tool_parameters.get("boardId") - - if not (api_key and token and board_id): - return self.create_text_message("Missing required parameters: API key, token, or board ID.") - - url = f"https://api.trello.com/1/boards/{board_id}?key={api_key}&token={token}" - - try: - response = requests.delete(url) - response.raise_for_status() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to delete board") - - return self.create_text_message(text=f"Board with ID {board_id} deleted successfully.") diff --git a/api/core/tools/provider/builtin/trello/tools/delete_board.yaml b/api/core/tools/provider/builtin/trello/tools/delete_board.yaml deleted file mode 100644 index f043e78870d062..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/delete_board.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: delete_board - author: Yash Parmar - label: - en_US: Delete Board - zh_Hans: 删除看板 - pt_BR: Excluir Quadro -description: - human: - en_US: Deletes a Trello board using its unique ID. This tool allows for the removal of boards that are no longer needed, ensuring a tidy workspace. - zh_Hans: 使用其唯一 ID 删除 Trello 看板。此工具允许删除不再需要的看板，确保工作区整洁。 - pt_BR: Exclui um quadro Trello usando seu ID único. Esta ferramenta permite a remoção de quadros que não são mais necessários, garantindo um espaço de trabalho organizado. - llm: Remove a Trello board by specifying its ID. This functionality is helpful for cleaning up unnecessary boards from your Trello account. -parameters: - - name: boardId - type: string - required: true - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: The unique identifier for the Trello board you wish to delete. This ensures the specific board is accurately targeted for deletion. - zh_Hans: 您希望删除的 Trello 看板的唯一标识符。这确保了准确地针对特定看板进行删除。 - pt_BR: O identificador único para o quadro Trello que você deseja excluir. Isso garante que o quadro específico seja precisamente direcionado para exclusão. - llm_description: Enter the ID of the Trello board you want to remove. This ID is essential to identify the board precisely and perform the deletion. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/delete_card.py b/api/core/tools/provider/builtin/trello/tools/delete_card.py deleted file mode 100644 index 1de98d639ebb7d..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/delete_card.py +++ /dev/null @@ -1,41 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class DeleteCardByIdTool(BuiltinTool): - """ - Tool for deleting a Trello card by its ID. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to delete a Trello card by its ID. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, - including the card ID. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - card_id = tool_parameters.get("id") - - if not (api_key and token and card_id): - return self.create_text_message("Missing required parameters: API key, token, or card ID.") - - url = f"https://api.trello.com/1/cards/{card_id}?key={api_key}&token={token}" - - try: - response = requests.delete(url) - response.raise_for_status() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to delete card") - - return self.create_text_message(text=f"Card with ID {card_id} has been successfully deleted.") diff --git a/api/core/tools/provider/builtin/trello/tools/delete_card.yaml b/api/core/tools/provider/builtin/trello/tools/delete_card.yaml deleted file mode 100644 index 8898ef1bde3680..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/delete_card.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: delete_card_by_id - author: Yash Parmar - label: - en_US: Delete Card by ID - zh_Hans: 通过 ID 删除卡片 - pt_BR: Deletar Cartão por ID -description: - human: - en_US: Deletes a Trello card using its unique ID. This tool facilitates the removal of cards that are no longer needed, maintaining an organized board. - zh_Hans: 使用其唯一 ID 删除 Trello 卡片。此工具便于删除不再需要的卡片，保持看板的有序。 - pt_BR: Exclui um cartão Trello usando seu ID único. Esta ferramenta facilita a remoção de cartões que não são mais necessários, mantendo um quadro organizado. - llm: Remove a specific Trello card by providing its ID. Ideal for cleaning up and organizing your Trello boards by eliminating unwanted cards. -parameters: - - name: id - type: string - required: true - label: - en_US: Card ID - zh_Hans: 卡片 ID - pt_BR: ID do Cartão - human_description: - en_US: The unique identifier of the Trello card you wish to delete. This ensures the precise card is removed. - zh_Hans: 您希望删除的 Trello 卡片的唯一标识符。这确保了精确移除特定卡片。 - pt_BR: O identificador único do cartão Trello que você deseja excluir. Isso garante que o cartão exato seja removido. - llm_description: Input the ID of the Trello card targeted for deletion to ensure accurate and specific removal. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/fetch_all_boards.py b/api/core/tools/provider/builtin/trello/tools/fetch_all_boards.py deleted file mode 100644 index 0c5ed9ea8533ff..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/fetch_all_boards.py +++ /dev/null @@ -1,50 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class FetchAllBoardsTool(BuiltinTool): - """ - Tool for fetching all boards from Trello. - """ - - def _invoke( - self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the fetch all boards tool. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation. - - Returns: - Union[ToolInvokeMessage, List[ToolInvokeMessage]]: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - - if not (api_key and token): - return self.create_text_message("Missing Trello API key or token in credentials.") - - # Including board filter in the request if provided - board_filter = tool_parameters.get("boards", "open") - url = f"https://api.trello.com/1/members/me/boards?filter={board_filter}&key={api_key}&token={token}" - - try: - response = requests.get(url) - response.raise_for_status() # Raises stored HTTPError, if one occurred. - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to fetch boards") - - boards = response.json() - - if not boards: - return self.create_text_message("No boards found in Trello.") - - # Creating a string with both board names and IDs - boards_info = ", ".join([f"{board['name']} (ID: {board['id']})" for board in boards]) - return self.create_text_message(text=f"Boards: {boards_info}") diff --git a/api/core/tools/provider/builtin/trello/tools/fetch_all_boards.yaml b/api/core/tools/provider/builtin/trello/tools/fetch_all_boards.yaml deleted file mode 100644 index d0ac4beaaa723a..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/fetch_all_boards.yaml +++ /dev/null @@ -1,28 +0,0 @@ -identity: - name: fetch_all_boards - author: Yash Parmar - label: - en_US: Fetch All Boards - zh_Hans: 获取所有看板 - pt_BR: Buscar Todos os Quadros -description: - human: - en_US: Retrieves all the Trello boards associated with the user's account. This tool provides a quick overview of all open boards, aiding in efficient project management and organization. - zh_Hans: 检索与用户账户关联的所有 Trello 看板。该工具提供了所有打开的看板的快速概览，有助于高效的项目管理和组织。 - pt_BR: Recupera todos os quadros do Trello associados à conta do usuário. Esta ferramenta oferece uma visão geral rápida de todos os quadros abertos, auxiliando na gestão e organização eficiente do projeto. - llm: This tool fetches all Trello boards linked to the user's account, offering a swift snapshot of open boards to streamline project management and organization tasks. -parameters: - - name: boards - type: string - required: false - default: open - label: - en_US: Boards filter - zh_Hans: 看板过滤器 - pt_BR: Filtro de quadros - human_description: - en_US: Specifies the type of boards to retrieve. Default is 'open', fetching all open boards. Other options include 'closed', 'members', 'organization', etc. - zh_Hans: 指定要检索的看板类型。默认为“open”，获取所有打开的看板。其他选项包括“closed”，“members”，“organization”等。 - pt_BR: Especifica o tipo de quadros a serem recuperados. O padrão é 'open', buscando todos os quadros abertos. Outras opções incluem 'closed', 'members', 'organization', etc. - llm_description: Determines the category of boards to be displayed, with 'open' as the default setting to show all open boards. Variants like 'closed', 'members', and 'organization' are also selectable. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/get_board_actions.py b/api/core/tools/provider/builtin/trello/tools/get_board_actions.py deleted file mode 100644 index cabc7ce09359d5..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_board_actions.py +++ /dev/null @@ -1,45 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetBoardActionsTool(BuiltinTool): - """ - Tool for retrieving actions for a Trello board by its ID. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to retrieve actions for a Trello board by its ID. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, - including the board ID. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_id = tool_parameters.get("boardId") - - if not (api_key and token and board_id): - return self.create_text_message("Missing required parameters: API key, token, or board ID.") - - url = f"https://api.trello.com/1/boards/{board_id}/actions?key={api_key}&token={token}" - - try: - response = requests.get(url) - response.raise_for_status() - actions = response.json() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to retrieve board actions") - - actions_summary = "\n".join( - [f"{action['type']}: {action.get('data', {}).get('text', 'No details available')}" for action in actions] - ) - return self.create_text_message(text=f"Actions for Board ID {board_id}:\n{actions_summary}") diff --git a/api/core/tools/provider/builtin/trello/tools/get_board_actions.yaml b/api/core/tools/provider/builtin/trello/tools/get_board_actions.yaml deleted file mode 100644 index 1ba89f9e44abbd..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_board_actions.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: get_board_actions - author: Yash Parmar - label: - en_US: Get Board Actions - zh_Hans: 获取看板操作 - pt_BR: Obter Ações do Quadro -description: - human: - en_US: Retrieves a list of actions (such as updates, movements, and comments) for a Trello board by its ID. This tool provides insights into the board's activity history. - zh_Hans: 通过其 ID 为 Trello 看板检索操作列表（如更新、移动和评论）。此工具提供了看板活动历史的见解。 - pt_BR: Recupera uma lista de ações (como atualizações, movimentos e comentários) para um quadro Trello pelo seu ID. Esta ferramenta oferece insights sobre o histórico de atividades do quadro. - llm: Fetch the sequence of actions performed on a Trello board, such as card updates, movements, and comments, by providing the board's ID. Offers a historical view of board activities. -parameters: - - name: boardId - type: string - required: true - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: The unique identifier of the Trello board for which you want to retrieve actions. It targets the specific board to fetch its activity log. - zh_Hans: 您想要检索操作的 Trello 看板的唯一标识符。它定位特定的看板以获取其活动日志。 - pt_BR: O identificador único do quadro Trello para o qual você deseja recuperar ações. Direciona especificamente para o quadro para buscar seu registro de atividades. - llm_description: Input the ID of the Trello board to access its detailed action history, including all updates, comments, and movements related to the board. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/get_board_by_id.py b/api/core/tools/provider/builtin/trello/tools/get_board_by_id.py deleted file mode 100644 index fe42cd9c5cbf86..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_board_by_id.py +++ /dev/null @@ -1,66 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetBoardByIdTool(BuiltinTool): - """ - Tool for retrieving detailed information about a Trello board by its ID. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to retrieve a Trello board by its ID. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, - including the board ID. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_id = tool_parameters.get("boardId") - - if not (api_key and token and board_id): - return self.create_text_message("Missing required parameters: API key, token, or board ID.") - - url = f"https://api.trello.com/1/boards/{board_id}?key={api_key}&token={token}" - - try: - response = requests.get(url) - response.raise_for_status() - board = response.json() - board_details = self.format_board_details(board) - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to retrieve board") - - return self.create_text_message(text=board_details) - - def format_board_details(self, board: dict) -> str: - """ - Format the board details into a human-readable string. - - Args: - board (dict): The board information as a dictionary. - - Returns: - str: Formatted board details. - """ - details = ( - f"Board Name: {board['name']}\n" - f"Board ID: {board['id']}\n" - f"Description: {board['desc'] or 'No description provided.'}\n" - f"Status: {'Closed' if board['closed'] else 'Open'}\n" - f"Organization ID: {board['idOrganization'] or 'Not part of an organization.'}\n" - f"URL: {board['url']}\n" - f"Short URL: {board['shortUrl']}\n" - f"Permission Level: {board['prefs']['permissionLevel']}\n" - f"Background Color: {board['prefs']['backgroundColor']}" - ) - return details diff --git a/api/core/tools/provider/builtin/trello/tools/get_board_by_id.yaml b/api/core/tools/provider/builtin/trello/tools/get_board_by_id.yaml deleted file mode 100644 index 45c93006ba4414..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_board_by_id.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: get_board_by_id - author: Yash Parmar - label: - en_US: Get Board by ID - zh_Hans: 通过 ID 获取看板 - pt_BR: Obter Quadro por ID -description: - human: - en_US: Retrieves detailed information about a specific Trello board using its unique ID. This tool enables users to quickly access board details without navigating through the Trello interface. - zh_Hans: 使用其唯一 ID 检索有关特定 Trello 看板的详细信息。此工具使用户能够快速访问看板详情，无需通过 Trello 界面导航。 - pt_BR: Recupera informações detalhadas sobre um quadro Trello específico usando seu ID único. Esta ferramenta permite que os usuários acessem rapidamente os detalhes do quadro sem navegar pela interface do Trello. - llm: Access details of a Trello board by providing its ID. This tool offers a direct way to view board information, simplifying the process of managing and reviewing Trello boards. -parameters: - - name: boardId - type: string - required: true - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: The unique identifier for the Trello board you wish to retrieve. This ID enables precise targeting and fetching of the board's details. - zh_Hans: 您希望检索的 Trello 看板的唯一标识符。此 ID 使能够准确定位和获取看板的详细信息。 - pt_BR: O identificador único do quadro Trello que você deseja recuperar. Este ID permite o direcionamento preciso e a obtenção dos detalhes do quadro. - llm_description: Input the ID of the Trello board to get its details. This unique ID ensures accurate retrieval of information about the specified board. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/get_board_cards.py b/api/core/tools/provider/builtin/trello/tools/get_board_cards.py deleted file mode 100644 index ff2b1221e767de..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_board_cards.py +++ /dev/null @@ -1,43 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetBoardCardsTool(BuiltinTool): - """ - Tool for retrieving cards on a Trello board by its ID. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to retrieve cards on a Trello board by its ID. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, - including the board ID. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_id = tool_parameters.get("boardId") - - if not (api_key and token and board_id): - return self.create_text_message("Missing required parameters: API key, token, or board ID.") - - url = f"https://api.trello.com/1/boards/{board_id}/cards?key={api_key}&token={token}" - - try: - response = requests.get(url) - response.raise_for_status() - cards = response.json() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to retrieve board cards") - - cards_summary = "\n".join([f"{card['name']} (ID: {card['id']})" for card in cards]) - return self.create_text_message(text=f"Cards for Board ID {board_id}:\n{cards_summary}") diff --git a/api/core/tools/provider/builtin/trello/tools/get_board_cards.yaml b/api/core/tools/provider/builtin/trello/tools/get_board_cards.yaml deleted file mode 100644 index 852ea278af341c..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_board_cards.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: get_board_cards - author: Yash Parmar - label: - en_US: Get Board Cards - zh_Hans: 获取看板卡片 - pt_BR: Obter Cartões do Quadro -description: - human: - en_US: Retrieves all cards present on a specific Trello board by its ID, providing a list of card names and their IDs. Useful for managing and organizing project tasks. - zh_Hans: 通过其 ID 检索特定 Trello 看板上的所有卡片，提供卡片名称及其 ID 的列表。用于管理和组织项目任务。 - pt_BR: Recupera todos os cartões presentes em um quadro Trello específico pelo seu ID, fornecendo uma lista dos nomes dos cartões e seus IDs. Útil para gerenciar e organizar tarefas de projetos. - llm: Obtain a list of all cards on a specific Trello board by entering the board's ID. This tool helps in quickly assessing the tasks or items associated with the board. -parameters: - - name: boardId - type: string - required: true - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: The unique identifier of the Trello board from which you want to retrieve cards. It specifies the exact board to gather card details from. - zh_Hans: 您想要从中检索卡片的 Trello 看板的唯一标识符。它指定了要从中收集卡片详细信息的确切看板。 - pt_BR: O identificador único do quadro Trello do qual você deseja recuperar os cartões. Especifica o quadro exato para obter detalhes dos cartões. - llm_description: Input the ID of the Trello board to fetch its cards, allowing for a detailed overview of the board's contents. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/get_filterd_board_cards.py b/api/core/tools/provider/builtin/trello/tools/get_filterd_board_cards.py deleted file mode 100644 index 3d7f9f4ad1c996..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_filterd_board_cards.py +++ /dev/null @@ -1,46 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetFilteredBoardCardsTool(BuiltinTool): - """ - Tool for retrieving filtered cards on a Trello board by its ID and a specified filter. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to retrieve filtered cards on a Trello board by its ID and filter. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, - including the board ID and filter. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_id = tool_parameters.get("boardId") - filter = tool_parameters.get("filter") - - if not (api_key and token and board_id and filter): - return self.create_text_message("Missing required parameters: API key, token, board ID, or filter.") - - url = f"https://api.trello.com/1/boards/{board_id}/cards/{filter}?key={api_key}&token={token}" - - try: - response = requests.get(url) - response.raise_for_status() - filtered_cards = response.json() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to retrieve filtered cards") - - card_details = "\n".join([f"{card['name']} (ID: {card['id']})" for card in filtered_cards]) - return self.create_text_message( - text=f"Filtered Cards for Board ID {board_id} with Filter '{filter}':\n{card_details}" - ) diff --git a/api/core/tools/provider/builtin/trello/tools/get_filterd_board_cards.yaml b/api/core/tools/provider/builtin/trello/tools/get_filterd_board_cards.yaml deleted file mode 100644 index 390595645771e4..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_filterd_board_cards.yaml +++ /dev/null @@ -1,40 +0,0 @@ -identity: - name: get_filtered_board_cards - author: Yash Parmar - label: - en_US: Get Filtered Board Cards - zh_Hans: 获取筛选的看板卡片 - pt_BR: Obter Cartões Filtrados do Quadro -description: - human: - en_US: Retrieves cards from a Trello board using a specified filter and the board's ID. Filters include options like 'all', 'open', 'closed', 'none', and 'visible', allowing for tailored views of board content. - zh_Hans: 使用指定的过滤器和看板的 ID 从 Trello 看板检索卡片。过滤器包括 'all', 'open', 'closed', 'none' 和 'visible' 等选项，允许对看板内容进行定制查看。 - pt_BR: Recupera cartões de um quadro Trello usando um filtro especificado e o ID do quadro. Os filtros incluem opções como 'all', 'open', 'closed', 'none' e 'visible', permitindo visualizações personalizadas do conteúdo do quadro. - llm: Access cards on a Trello board through specific filters such as 'all', 'open', 'closed', 'none', and 'visible' by providing the board's ID. This feature enables focused examination of the board's cards. -parameters: - - name: boardId - type: string - required: true - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: The unique identifier for the Trello board from which to retrieve the filtered cards. - zh_Hans: 用于检索筛选卡片的 Trello 看板的唯一标识符。 - pt_BR: O identificador único do quadro Trello do qual os cartões filtrados serão recuperados. - llm_description: Enter the Trello board's ID to specify from which board to fetch the cards using the filter. - form: llm - - name: filter - type: string - required: true - label: - en_US: Filter - zh_Hans: 过滤器 - pt_BR: Filtro - human_description: - en_US: The filter to apply when retrieving cards. Valid values are 'all', 'open', 'closed', 'none', and 'visible'. - zh_Hans: 检索卡片时应用的过滤器。有效值为 'all', 'open', 'closed', 'none', 和 'visible'。 - pt_BR: O filtro a ser aplicado ao recuperar cartões. Os valores válidos são 'all', 'open', 'closed', 'none' e 'visible'. - llm_description: Specify the filter for card retrieval. Choose from 'all', 'open', 'closed', 'none', or 'visible' to control which cards are fetched. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/get_lists_on_board.py b/api/core/tools/provider/builtin/trello/tools/get_lists_on_board.py deleted file mode 100644 index ccf404068f225e..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_lists_on_board.py +++ /dev/null @@ -1,43 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class GetListsFromBoardTool(BuiltinTool): - """ - Tool for retrieving all lists from a specified Trello board by its ID. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool]]) -> ToolInvokeMessage: - """ - Invoke the tool to get all lists from a specified Trello board. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, - including the board ID. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_id = tool_parameters.get("boardId") - - if not (api_key and token and board_id): - return self.create_text_message("Missing required parameters: API key, token, or board ID.") - - url = f"https://api.trello.com/1/boards/{board_id}/lists?key={api_key}&token={token}" - - try: - response = requests.get(url) - response.raise_for_status() - lists = response.json() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to retrieve lists") - - lists_info = "\n".join([f"{list['name']} (ID: {list['id']})" for list in lists]) - return self.create_text_message(text=f"Lists on Board ID {board_id}:\n{lists_info}") diff --git a/api/core/tools/provider/builtin/trello/tools/get_lists_on_board.yaml b/api/core/tools/provider/builtin/trello/tools/get_lists_on_board.yaml deleted file mode 100644 index 31028a80404de3..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/get_lists_on_board.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: get_lists_from_board - author: Yash Parmar - label: - en_US: Get Lists from Board - zh_Hans: 获取看板的列表 - pt_BR: Obter Listas do Quadro -description: - human: - en_US: Retrieves all lists from a specified Trello board by its ID, providing an overview of the board's organization and current phases or categories. - zh_Hans: 通过其 ID 从指定的 Trello 看板检索所有列表，提供看板组织和当前阶段或类别的概览。 - pt_BR: Recupera todas as listas de um quadro Trello especificado pelo seu ID, fornecendo uma visão geral da organização do quadro e das fases ou categorias atuais. - llm: Fetch and display all lists from a specific Trello board by inputting the board's ID. This aids in understanding the board's structure and task categorization. -parameters: - - name: boardId - type: string - required: true - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: The unique identifier of the Trello board from which to retrieve the lists. - zh_Hans: 用于检索列表的 Trello 看板的唯一标识符。 - pt_BR: O identificador único do quadro Trello do qual as listas serão recuperadas. - llm_description: Enter the ID of the Trello board to obtain a detailed list of all its lists, providing insight into the board's structure. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/update_board.py b/api/core/tools/provider/builtin/trello/tools/update_board.py deleted file mode 100644 index 1e358b00f49add..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/update_board.py +++ /dev/null @@ -1,47 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class UpdateBoardByIdTool(BuiltinTool): - """ - Tool for updating a Trello board by its ID with various parameters. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool, None]]) -> ToolInvokeMessage: - """ - Invoke the tool to update a Trello board by its ID. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation, - including board ID and updates. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - board_id = tool_parameters.pop("boardId", None) - - if not (api_key and token and board_id): - return self.create_text_message("Missing required parameters: API key, token, or board ID.") - - url = f"https://api.trello.com/1/boards/{board_id}" - - # Removing parameters not intended for update action or with None value - params = {k: v for k, v in tool_parameters.items() if v is not None} - params["key"] = api_key - params["token"] = token - - try: - response = requests.put(url, params=params) - response.raise_for_status() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to update board") - - updated_board = response.json() - return self.create_text_message(text=f"Board '{updated_board['name']}' updated successfully.") diff --git a/api/core/tools/provider/builtin/trello/tools/update_board.yaml b/api/core/tools/provider/builtin/trello/tools/update_board.yaml deleted file mode 100644 index 487919631ade34..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/update_board.yaml +++ /dev/null @@ -1,157 +0,0 @@ -identity: - name: update_board_by_id - author: Yash Parmar - label: - en_US: Update Board by ID - zh_Hans: 通过 ID 更新看板 - pt_BR: Atualizar Quadro por ID -description: - human: - en_US: Updates a Trello board's settings based on the provided ID and parameters. Allows for changing the board's name, description, status, and other preferences. - zh_Hans: 根据提供的 ID 和参数更新 Trello 看板的设置。允许更改看板的名称、描述、状态和其他偏好设置。 - pt_BR: Atualiza as configurações de um quadro Trello com base no ID fornecido e nos parâmetros. Permite alterar o nome, descrição, status e outras preferências do quadro. - llm: Modify a Trello board's attributes like its name, description, and visibility settings using the board's ID. This tool streamlines board customization and management. -parameters: - - name: boardId - type: string - required: true - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: The unique identifier of the Trello board you want to update. Ensures targeted and precise updates. - zh_Hans: 您要更新的 Trello 看板的唯一标识符。确保目标准确和更新精确。 - pt_BR: O identificador único do quadro Trello que você deseja atualizar. Garante atualizações direcionadas e precisas. - llm_description: Provide the specific ID of the Trello board you aim to update to ensure accuracy in modification process. - form: llm - - name: name - type: string - required: false - label: - en_US: Board Name - zh_Hans: 看板名称 - pt_BR: Nome do Quadro - human_description: - en_US: Optional. The new name for the board. - zh_Hans: 可选。看板的新名称。 - pt_BR: Opcional. O novo nome para o quadro. - llm_description: Enter a new name for the board if you wish to change it; this name identifies the board in Trello. - form: llm - - name: desc - type: string - required: false - label: - en_US: Board Description - zh_Hans: 看板描述 - pt_BR: Descrição do Quadro - human_description: - en_US: Optional. The new description for the board. - zh_Hans: 可选。看板的新描述。 - pt_BR: Opcional. A nova descrição para o quadro. - llm_description: Provide a new description for the board if you wish to update it; this description provides additional context about the board. - form: llm - - name: closed - type: boolean - required: false - label: - en_US: Closed - zh_Hans: 已关闭 - pt_BR: Fechado - human_description: - en_US: Optional. Set to true to close the board, or false to keep it open. - zh_Hans: 可选。设置为 true 以关闭看板，或设置为 false 以保持打开。 - pt_BR: Opcional. Defina como true para fechar o quadro ou como false para mantê-lo aberto. - llm_description: Specify whether the board should be closed or kept open by setting this parameter to true or false. - form: llm - - name: subscribed - type: string - required: false - label: - en_US: Subscribed - zh_Hans: 订阅 - pt_BR: Inscrito - human_description: - en_US: Optional. Set to true to subscribe to the board, or false to unsubscribe. - zh_Hans: 可选。设置为 true 以订阅看板，或设置为 false 以取消订阅。 - pt_BR: Opcional. Defina como true para se inscrever no quadro ou como false para cancelar a inscrição. - llm_description: Choose to subscribe or unsubscribe from the board by setting this parameter to true or false. - form: llm - - name: idOrganization - type: string - required: false - label: - en_US: Organization ID - zh_Hans: 组织 ID - pt_BR: ID da Organização - human_description: - en_US: Optional. The ID of the organization to which the board belongs. - zh_Hans: 可选。看板所属组织的 ID。 - pt_BR: Opcional. O ID da organização à qual o quadro pertence. - llm_description: Input the ID of the organization to which the board is associated, if applicable. - form: llm - - name: prefs_permissionLevel - type: string - required: false - label: - en_US: Permission Level - zh_Hans: 权限级别 - pt_BR: Nível de Permissão - human_description: - en_US: Optional. The permission level for the board. Valid values are 'private', 'org', or 'public'. - zh_Hans: 可选。看板的权限级别。有效值为 'private'、'org' 或 'public'。 - pt_BR: Opcional. O nível de permissão para o quadro. Os valores válidos são 'private', 'org' ou 'public'. - llm_description: Specify the permission level for the board by choosing from 'private', 'org', or 'public'. - form: llm - - name: prefs_selfJoin - type: boolean - required: false - label: - en_US: Allow Self-Join - zh_Hans: 允许自行加入 - pt_BR: Permitir Auto-Inscrição - human_description: - en_US: Optional. Set to true to allow members to join the board without an invitation, or false to require an invitation. - zh_Hans: 可选。设置为 true 以允许成员加入看板而无需邀请，或设置为 false 以要求邀请。 - pt_BR: Opcional. Defina como true para permitir que os membros se inscrevam no quadro sem um convite, ou como false para exigir um convite. - llm_description: Choose whether to allow members to join the board without an invitation by setting this parameter to true or false. - form: llm - - name: prefs_cardCovers - type: boolean - required: false - label: - en_US: Card Covers - zh_Hans: 卡片封面 - pt_BR: Capas de Cartão - human_description: - en_US: Optional. Set to true to enable card covers, or false to disable them. - zh_Hans: 可选。设置为 true 以启用卡片封面，或设置为 false 以禁用卡片封面。 - pt_BR: Opcional. Defina como true para habilitar capas de cartão ou como false para desabilitá-las. - llm_description: Enable or disable card covers by setting this parameter to true or false. - form: llm - - name: prefs_hideVotes - type: boolean - required: false - label: - en_US: Hide Votes - zh_Hans: 隐藏投票 - pt_BR: Ocultar Votos - human_description: - en_US: Optional. Set to true to hide votes, or false to show them. - zh_Hans: 可选。设置为 true 以隐藏投票，或设置为 false 以显示投票。 - pt_BR: Opcional. Defina como true para ocultar votos ou como false para mostrá-los. - llm_description: Choose to hide or show votes by setting this parameter to true or false. - form: llm - - name: prefs_invitations - type: string - required: false - label: - en_US: Invitations - zh_Hans: 邀请 - pt_BR: Convites - human_description: - en_US: Optional. Set to 'members' to allow only board members to send invitations, or 'admins' to allow admins to send invitations. - zh_Hans: 可选。设置为 'members' 以仅允许看板成员发送邀请，或设置为 'admins' 以允许管理员发送邀请。 - pt_BR: Opcional. Defina como 'members' para permitir que apenas membros do quadro enviem convites, ou 'admins' para permitir que os administradores enviem convites. - llm_description: Choose who can send invitations by setting this parameter to 'members' or 'admins'. - form: llm diff --git a/api/core/tools/provider/builtin/trello/tools/update_card.py b/api/core/tools/provider/builtin/trello/tools/update_card.py deleted file mode 100644 index d25fcbafaa6326..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/update_card.py +++ /dev/null @@ -1,45 +0,0 @@ -from typing import Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class UpdateCardByIdTool(BuiltinTool): - """ - Tool for updating a Trello card by its ID. - """ - - def _invoke(self, user_id: str, tool_parameters: dict[str, Union[str, int, bool, None]]) -> ToolInvokeMessage: - """ - Invoke the tool to update a Trello card by its ID. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation, - including the card ID and updates. - - Returns: - ToolInvokeMessage: The result of the tool invocation. - """ - api_key = self.runtime.credentials.get("trello_api_key") - token = self.runtime.credentials.get("trello_api_token") - card_id = tool_parameters.get("id") - - if not (api_key and token and card_id): - return self.create_text_message("Missing required parameters: API key, token, or card ID.") - - # Constructing the URL and the payload for the PUT request - url = f"https://api.trello.com/1/cards/{card_id}" - params = {k: v for k, v in tool_parameters.items() if v is not None and k != "id"} - params.update({"key": api_key, "token": token}) - - try: - response = requests.put(url, params=params) - response.raise_for_status() - except requests.exceptions.RequestException as e: - return self.create_text_message("Failed to update card") - - updated_card_info = f"Card '{card_id}' updated successfully." - return self.create_text_message(text=updated_card_info) diff --git a/api/core/tools/provider/builtin/trello/tools/update_card.yaml b/api/core/tools/provider/builtin/trello/tools/update_card.yaml deleted file mode 100644 index 5240dfc3ed2564..00000000000000 --- a/api/core/tools/provider/builtin/trello/tools/update_card.yaml +++ /dev/null @@ -1,81 +0,0 @@ -identity: - name: update_card_by_id - author: Yash Parmar - label: - en_US: Update Card by ID - zh_Hans: 通过 ID 更新卡片 - pt_BR: Atualizar Cartão por ID -description: - human: - en_US: Updates specified attributes of a Trello card, such as its name, description, list ID, and board ID, by providing the card's unique ID. - zh_Hans: 通过提供卡片的唯一 ID，更新 Trello 卡片的特定属性，如其名称、描述、列表 ID 和看板 ID。 - pt_BR: Atualiza atributos específicos de um cartão Trello, como seu nome, descrição, ID da lista e ID do quadro, fornecendo o ID único do cartão. - llm: Modify a Trello card's key details, including name, description, and its placement on the board, by using the card's ID. Enables precise and targeted updates to card information. -parameters: - - name: id - type: string - required: true - label: - en_US: Card ID - zh_Hans: 卡片 ID - pt_BR: ID do Cartão - human_description: - en_US: The unique identifier of the Trello card you intend to update. - zh_Hans: 您打算更新的 Trello 卡片的唯一标识符。 - pt_BR: O identificador único do cartão Trello que você pretende atualizar. - llm_description: Input the ID of the Trello card to be updated to ensure the correct card is targeted. - form: llm - # Include other parameters following the same pattern - - name: name - type: string - required: false - label: - en_US: New Name - zh_Hans: 新名称 - pt_BR: Novo Nome - human_description: - en_US: Optional. The new name to assign to the card. - zh_Hans: 可选。要分配给卡片的新名称。 - pt_BR: Opcional. O novo nome a ser atribuído ao cartão. - llm_description: Specify a new name for the card if changing it. This name is what will be displayed on the Trello board. - form: llm - # Add definitions for desc, idList and idBoard parameters - - name: desc - type: string - required: false - label: - en_US: New Description - zh_Hans: 新描述 - pt_BR: Nova Descrição - human_description: - en_US: Optional. The new description to assign to the card. - zh_Hans: 可选。要分配给卡片的新描述。 - pt_BR: Opcional. A nova descrição a ser atribuída ao cartão. - llm_description: Provide a new description for the card if you wish to update it; this description provides additional context about the card. - form: llm - - name: idList - type: string - required: false - label: - en_US: List ID - zh_Hans: 列表 ID - pt_BR: ID da Lista - human_description: - en_US: Optional. The ID of the list to which the card should be moved. - zh_Hans: 可选。卡片应移动到的列表的 ID。 - pt_BR: Opcional. O ID da lista para a qual o cartão deve ser movido. - llm_description: Enter the ID of the list where you want to move the card. This action relocates the card to the specified list. - form: llm - - name: idBoard - type: string - required: false - label: - en_US: Board ID - zh_Hans: 看板 ID - pt_BR: ID do Quadro - human_description: - en_US: Optional. The ID of the board to which the card should be moved. - zh_Hans: 可选。卡片应移动到的看板的 ID。 - pt_BR: Opcional. O ID do quadro para o qual o cartão deve ser movido. - llm_description: Provide the ID of the board where you want to move the card. This action relocates the card to the specified board. - form: llm diff --git a/api/core/tools/provider/builtin/trello/trello.py b/api/core/tools/provider/builtin/trello/trello.py deleted file mode 100644 index e0dca50ec99aee..00000000000000 --- a/api/core/tools/provider/builtin/trello/trello.py +++ /dev/null @@ -1,34 +0,0 @@ -from typing import Any - -import requests - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class TrelloProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - """Validate Trello API credentials by making a test API call. - - Args: - credentials (dict[str, Any]): The Trello API credentials to validate. - - Raises: - ToolProviderCredentialValidationError: If the credentials are invalid. - """ - api_key = credentials.get("trello_api_key") - token = credentials.get("trello_api_token") - url = f"https://api.trello.com/1/members/me?key={api_key}&token={token}" - - try: - response = requests.get(url) - response.raise_for_status() # Raises an HTTPError for bad responses - except requests.exceptions.HTTPError as e: - if response.status_code == 401: - # Unauthorized, indicating invalid credentials - raise ToolProviderCredentialValidationError("Invalid Trello credentials: Unauthorized.") - # Handle other potential HTTP errors - raise ToolProviderCredentialValidationError("Error validating Trello credentials") - except requests.exceptions.RequestException as e: - # Handle other exceptions, such as connection errors - raise ToolProviderCredentialValidationError("Error validating Trello credentials") diff --git a/api/core/tools/provider/builtin/trello/trello.yaml b/api/core/tools/provider/builtin/trello/trello.yaml deleted file mode 100644 index 49c9f4f9a178f8..00000000000000 --- a/api/core/tools/provider/builtin/trello/trello.yaml +++ /dev/null @@ -1,47 +0,0 @@ -identity: - author: Yash Parmar - name: trello - label: - en_US: Trello - zh_Hans: Trello - pt_BR: Trello - description: - en_US: "Trello: A visual tool for organizing your work and life." - zh_Hans: "Trello: 一个用于组织工作和生活的视觉工具。" - pt_BR: "Trello: Uma ferramenta visual para organizar seu trabalho e vida." - icon: icon.svg - tags: - - productivity -credentials_for_provider: - trello_api_key: - type: secret-input - required: true - label: - en_US: Trello API key - zh_Hans: Trello API key - pt_BR: Trello API key - placeholder: - en_US: Enter your Trello API key - zh_Hans: 输入您的 Trello API key - pt_BR: Insira sua chave API do Trello - help: - en_US: Obtain your API key from Trello's website. - zh_Hans: 从 Trello 网站获取您的 API key。 - pt_BR: Obtenha sua chave API no site do Trello. - url: https://developer.atlassian.com/cloud/trello/guides/rest-api/api-introduction/ - trello_api_token: - type: secret-input - required: true - label: - en_US: Trello API token - zh_Hans: Trello API token - pt_BR: Trello API token - placeholder: - en_US: Enter your Trello API token - zh_Hans: 输入您的 Trello API token - pt_BR: Insira seu token API do Trello - help: - en_US: Secure your API token from Trello's website. - zh_Hans: 从 Trello 网站获取您的 API token。 - pt_BR: Garanta seu token API no site do Trello. - url: https://developer.atlassian.com/cloud/trello/guides/rest-api/api-introduction/ diff --git a/api/core/tools/provider/builtin/twilio/_assets/icon.svg b/api/core/tools/provider/builtin/twilio/_assets/icon.svg deleted file mode 100644 index a1e2bd12c27d64..00000000000000 --- a/api/core/tools/provider/builtin/twilio/_assets/icon.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/twilio/tools/send_message.py b/api/core/tools/provider/builtin/twilio/tools/send_message.py deleted file mode 100644 index 5ee839baa56f02..00000000000000 --- a/api/core/tools/provider/builtin/twilio/tools/send_message.py +++ /dev/null @@ -1,97 +0,0 @@ -from typing import Any, Optional, Union - -from pydantic import BaseModel, field_validator - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class TwilioAPIWrapper(BaseModel): - """Messaging Client using Twilio. - - To use, you should have the ``twilio`` python package installed, - and the environment variables ``TWILIO_ACCOUNT_SID``, ``TWILIO_AUTH_TOKEN``, and - ``TWILIO_FROM_NUMBER``, or pass `account_sid`, `auth_token`, and `from_number` as - named parameters to the constructor. - """ - - client: Any = None #: :meta private: - account_sid: Optional[str] = None - """Twilio account string identifier.""" - auth_token: Optional[str] = None - """Twilio auth token.""" - from_number: Optional[str] = None - """A Twilio phone number in [E.164](https://www.twilio.com/docs/glossary/what-e164) - format, an - [alphanumeric sender ID](https://www.twilio.com/docs/sms/send-messages#use-an-alphanumeric-sender-id), - or a [Channel Endpoint address](https://www.twilio.com/docs/sms/channels#channel-addresses) - that is enabled for the type of message you want to send. Phone numbers or - [short codes](https://www.twilio.com/docs/sms/api/short-code) purchased from - Twilio also work here. You cannot, for example, spoof messages from a private - cell phone number. If you are using `messaging_service_sid`, this parameter - must be empty. - """ - - @field_validator("client", mode="before") - @classmethod - def set_validator(cls, values: dict) -> dict: - """Validate that api key and python package exists in environment.""" - try: - from twilio.rest import Client - except ImportError: - raise ImportError("Could not import twilio python package. Please install it with `pip install twilio`.") - account_sid = values.get("account_sid") - auth_token = values.get("auth_token") - values["from_number"] = values.get("from_number") - values["client"] = Client(account_sid, auth_token) - - return values - - def run(self, body: str, to: str) -> str: - """Run body through Twilio and respond with message sid. - - Args: - body: The text of the message you want to send. Can be up to 1,600 - characters in length. - to: The destination phone number in - [E.164](https://www.twilio.com/docs/glossary/what-e164) format for - SMS/MMS or - [Channel user address](https://www.twilio.com/docs/sms/channels#channel-addresses) - for other 3rd-party channels. - """ - message = self.client.messages.create(to, from_=self.from_number, body=body) - return message.sid - - -class SendMessageTool(BuiltinTool): - """ - A tool for sending messages using Twilio API. - - Args: - user_id (str): The ID of the user invoking the tool. - tool_parameters (Dict[str, Any]): The parameters required for sending the message. - - Returns: - Union[ToolInvokeMessage, List[ToolInvokeMessage]]: The result of invoking the tool, - which includes the status of the message sending operation. - """ - - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - account_sid = self.runtime.credentials["account_sid"] - auth_token = self.runtime.credentials["auth_token"] - from_number = self.runtime.credentials["from_number"] - - message = tool_parameters["message"] - to_number = tool_parameters["to_number"] - - if to_number.startswith("whatsapp:"): - from_number = f"whatsapp: {from_number}" - - twilio = TwilioAPIWrapper(account_sid=account_sid, auth_token=auth_token, from_number=from_number) - - # Sending the message through Twilio - result = twilio.run(message, to_number) - - return self.create_text_message(text="Message sent successfully.") diff --git a/api/core/tools/provider/builtin/twilio/tools/send_message.yaml b/api/core/tools/provider/builtin/twilio/tools/send_message.yaml deleted file mode 100644 index e129698c86aeb6..00000000000000 --- a/api/core/tools/provider/builtin/twilio/tools/send_message.yaml +++ /dev/null @@ -1,40 +0,0 @@ -identity: - name: send_message - author: Yash Parmar - label: - en_US: SendMessage - zh_Hans: 发送消息 - pt_BR: SendMessage -description: - human: - en_US: Send SMS or Twilio Messaging Channels messages. - zh_Hans: 发送SMS或Twilio消息通道消息。 - pt_BR: Send SMS or Twilio Messaging Channels messages. - llm: Send SMS or Twilio Messaging Channels messages. Supports different channels including WhatsApp. -parameters: - - name: message - type: string - required: true - label: - en_US: Message - zh_Hans: 消息内容 - pt_BR: Message - human_description: - en_US: The content of the message to be sent. - zh_Hans: 要发送的消息内容。 - pt_BR: The content of the message to be sent. - llm_description: The content of the message to be sent. - form: llm - - name: to_number - type: string - required: true - label: - en_US: To Number - zh_Hans: 收信号码 - pt_BR: Para Número - human_description: - en_US: The recipient's phone number. Prefix with 'whatsapp:' for WhatsApp messages, e.g., "whatsapp:+1234567890". - zh_Hans: 收件人的电话号码。WhatsApp消息前缀为'whatsapp:'，例如，"whatsapp:+1234567890"。 - pt_BR: The recipient's phone number. Prefix with 'whatsapp:' for WhatsApp messages, e.g., "whatsapp:+1234567890". - llm_description: The recipient's phone number. Prefix with 'whatsapp:' for WhatsApp messages, e.g., "whatsapp:+1234567890". - form: llm diff --git a/api/core/tools/provider/builtin/twilio/twilio.py b/api/core/tools/provider/builtin/twilio/twilio.py deleted file mode 100644 index b1d100aad93dba..00000000000000 --- a/api/core/tools/provider/builtin/twilio/twilio.py +++ /dev/null @@ -1,29 +0,0 @@ -from typing import Any - -from twilio.base.exceptions import TwilioRestException -from twilio.rest import Client - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class TwilioProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - # Extract credentials - account_sid = credentials["account_sid"] - auth_token = credentials["auth_token"] - from_number = credentials["from_number"] - - # Initialize twilio client - client = Client(account_sid, auth_token) - - # fetch account - client.api.accounts(account_sid).fetch() - - except TwilioRestException as e: - raise ToolProviderCredentialValidationError(f"Twilio API error: {e.msg}") from e - except KeyError as e: - raise ToolProviderCredentialValidationError(f"Missing required credential: {e}") from e - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/twilio/twilio.yaml b/api/core/tools/provider/builtin/twilio/twilio.yaml deleted file mode 100644 index 21867c1da5dc32..00000000000000 --- a/api/core/tools/provider/builtin/twilio/twilio.yaml +++ /dev/null @@ -1,48 +0,0 @@ -identity: - author: Yash Parmar - name: twilio - label: - en_US: Twilio - zh_Hans: Twilio - pt_BR: Twilio - description: - en_US: Send messages through SMS or Twilio Messaging Channels. - zh_Hans: 通过SMS或Twilio消息通道发送消息。 - pt_BR: Send messages through SMS or Twilio Messaging Channels. - icon: icon.svg - tags: - - social -credentials_for_provider: - account_sid: - type: secret-input - required: true - label: - en_US: Account SID - zh_Hans: 账户SID - pt_BR: Account SID - placeholder: - en_US: Please input your Twilio Account SID - zh_Hans: 请输入您的Twilio账户SID - pt_BR: Please input your Twilio Account SID - auth_token: - type: secret-input - required: true - label: - en_US: Auth Token - zh_Hans: 认证令牌 - pt_BR: Auth Token - placeholder: - en_US: Please input your Twilio Auth Token - zh_Hans: 请输入您的Twilio认证令牌 - pt_BR: Please input your Twilio Auth Token - from_number: - type: secret-input - required: true - label: - en_US: From Number - zh_Hans: 发信号码 - pt_BR: De Número - placeholder: - en_US: Please input your Twilio phone number - zh_Hans: 请输入您的Twilio电话号码 - pt_BR: Please input your Twilio phone number diff --git a/api/core/tools/provider/builtin/vanna/_assets/icon.png b/api/core/tools/provider/builtin/vanna/_assets/icon.png deleted file mode 100644 index 3a9011b54d8a07f01e6b2fb934f3937bca0fd85a..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 4612 zcmb7Ic{r49`+mm04=H<05wZ=Vk}<}<8)VBikzID9#%>VVDJ`-WLPcbcWX+PSk)7-m z#xVBfqu$^9e!t`RzCXVEKJMo_pX<8L^SbW)e*Su*^mNqdX*g&A0HD`USJpqVR;P=K z;^aACqpptv06%^Jz}*Lcy%QI15diLr1HiHs0Kk(0 zfYl@I!wtkq;J%%ShCK=e2%TUmfE;uNAU#2#lL>%0fK#;-1ZaXd|Hk?t!M}1y0N{ZW zK=xOT*@-L=@z^T(2Af&NjXC%7K;_b zN{YFAIY1?(rKO?bFenTrdXgcE@pbdQ?IY@j;r%1>e>%!`7#lAq4{s-TH^`~(ZEN?t z-m(`jo)-Fh{OQx%$^M^8ZkWHeb+SR|X#^@ECJy~iG&>)s|3W*B{Gt8c*Pn8TQ!%)% zmy_K|!>4T_B@n+0{6F76?IBK8;CfCzb}lB$POf%tnBN?6*cAlyKZgDz)%3qp|1Iz5f7I(Q>0 z9z#a%GgjtDak%Kka6#m8->AW@@hhfsTURS5tFfQiWw!jVvNaP~)lsrF8&%t5YiS$l z7#^F?wbK`-{^yw}NfKIGsMx)`#k`_gQXad{57eQNF`7fmfMu~wVEH~GTa6Rn+PpB# zTY$+Gsk!g2YUfq5-cpldXUW0_M#F-A`q>SMuxGUj7?mz~o(g_pXx^LGys`hS$_~09 zm_pczQS_+d($^))IFvKng6^IQ3^nat3cp!ff1doHNl~!jjGjsgB{7fKdWN;691)(( zn5=L>+=E!)CktcKAYr_FgSc-gxxVR)#B0hZf7V8T|RvC>M0i1l*+OL|_wIABIGkq2g z)m_wWh8lQ(qlSCgYPk^`3;hz?HAYOyzO4EF5-No6P)ZhwWd7t})~1Rh?=S%^C7y{7 z!W1b@#H!Ota?{DK2K!BU4Vq-yuHX}4qVz7=IqA^5a&^%UKy?z@hd7yRDDD$m3mTlC zsBflO-=I&z86|1VH1aEWZ}Eu>6A4Dkf7nj#+DhlX&zC#gMI*{n*_1%0bp1k+a|4=O zox*DZXXI@Yhnti2gzWv3c-~qWe6v+N5y~tx#s6JVr>m{!NodR`3 z+hK!T@P}LR$)lQY$y8+OuGR4c`h72T_N{tPKFrWY(InEon?wxTH0UyA^aY;X688kh zw~#eN?2*%|tx_Km@${FBNa8$X3@b2u4RYwh2XDAxaTloQN1o$01Xd&c9mdyj;Vg?3 z7V@^91{zoJ*6~c&{W_;f`N1k{bgn-?Xb8P{(#7hT2H;sGdl(1@{a_@voTbQ*af-Px zAD7BpG$R?8#+|asfATfnv}9Ls@XFG-OFI(5l10W6e|T;4;5aCn2@_FXzVx54q9U^034* z-$TnY(fCwEqcj`^fw9Ue^yxg%H9PVj9b8x60d?Hd(^l8^yu2NHAuhEAP0oig#Ep|K z??_y-En7|*ZGv*|RBzrNG{!DQzI>FEu2N9FR_jAg`+zC{?jL*4C9HTZ+ z2TxUdQDbEFD!Cq&4Q+bk9LzLvbX54ZM50NM|BB6CZjW^@gHna$_R1%8jNwL*Bm-Ve zRF0?rnPQ|i;-Mu^UgAf57s}9+%b?d#z1d|rv9^7eR=%DY&&Em`$S!(jT<@??hBHS% z#AS}Wg^arHWqP%{`zPZ!4C4ZA1nPsg1+NUm792V_lI3jn=0fS5F}H*dN@ZxWrZlt? zouvuVrBMZ!*p?2eqbL@iNIXL5HTGUfXm*QR9Xr-qqBhh(X2`FTHq_emzWkOZg|&E4 zoxZQltK+aiU8U(w7bTJRWKbxKZ)QBb*XUyzm&P00<%p$2e)GHU7}dXyeY+;WV|U~D z90K{sD#f&+I_k&AJy36t9#0_0c6!ka*J>-1boEn-@)VBD$nB#K!R-g;IV35N*R_{p z+Q=|!4-!BJ29smH>D&b$Sf4+Y-%q|(A5Z^4}4dl`X%Z=bu{O8R-gJ!tAvG<#H_h>2;4mIl?E==TIqY(fqH+QZs+sdzH7`BWR% z{UD`iJI-r*oyivV0z2t4-<@CJKicj(W+vwD3Ua;OdIitl*Eh?BCbF|Fvs^3*<$g%J zDHftjoD*UgPc^sC_5sV3vQ;kYOTeXN@#nd~%eyyH#ZWJ29#gnZ9OzqVH2JGM)8 z_}A$~Yv-&aDgN_?I{P!TgNBX+WJu9wOP1l*&Q2k2K7nF3B+p$fT?onGmFD}8S>nb` z_B%MSOmgjepMUjV7#UtPnEK=;`!0S=G`4CMJf^$ka`Z7|V8@y%gI)8g7G7qYGV^{1 z<)Z_5Z*10BXa61#rPR9PfDqD=&&u;$GUHcnQWtP>ytXf`XVoUzHILc44EG?{LpEK< zRub^_C z42#ka4L^>Y1l910gTm!6{*l|}(iGt;LfPZO`iI(|Nq^DPAO?ajzsjsEepq)UpDI0# zkG{O?&Ci+3N>_1?szzfQ|)09deVTeh>Q))4cu#)g73x}6T#cFPgLdt^N=xW3SGv? zJBeaxX2vx-Y-*Mc4OIE+kn~i|V`lWT00q(uC_dHVW@(pxr5}L`pPPh9L8b1+qt7%o zCLCNj#T`rEOF39t99dNL>{2PN*N?F0dD5@fv)%qM8BIwBlYde*Z*qA&hKVF2=dL}6 z6)LBIOIQhYKMh3Tgc+jj?HX5=}ex`WMp+ z(vv<2ma~HoiHqe-U%51|@m#lS>Ds$Ex8EvN)TQ0(#s5Zf-&dI1O5uo`r4ZdcJ?<4C zeoe4HfRWq@=jT+6n#-6ven1Xj+nX0OPnYxj|_Sx8f{mb)d~#rbO8RA&W~8GBLNy!UEl$umNr zadSX0%t`AV@TfVSaxx~6O6!2>U4EK4T|S${^F{KEn{bpAQ8-X8i0sDl*uiY9;$O!@9|` z#E5#g9pj8Xu3-ONLELl*@t&-40%y2{$74#8W;JqiAx8d*Rs^_buxt*E>He8p5b=CI zFpr}{4a9fuBRb(+QA4if4%t$J=Bs{MgvoHnox&ux_p;s0G1h}uhP@YK7V1P6e3!@3 zhS*TkHV0PqibVT7p9teVJk0W|mb?2@$xvbA^_PQS@oRb*rLJm7%6VtD_CxqAiDsDI@uZess7goI! zUF0_%C^FVvkI=oRFfc$c1lm>Cff-VprBH4UZQk6R9m-rtk-aBbzF1+)ORhI|s0YiR zvgdt^Ju+$8Bt3PX7Iogg&Rpiy5@s^WDc66;Ip`9FUsCchIQBbCT}@5>9)-5b3( z>tts(5X_tNRR(iEK^6Hz+>UCj!Mpcd(7_6C;wh}IQu_|;-~_)mt3SIiDMcCUhTb-> zO|TGhrm&NOVOj|{aj}%HnmUtHnu0&XX$^b$-)%bTMaba%0=&Fih;wM7Wu*_#D88fi z@h1{0c|Ui$QLukEJZ9^;rHFQvF#VZCOe4>Ib?2*7ft?!xgaP;3F`U0slksz#V3KIH zVY-gDvghRrMz=GPiEB3vO1D>0Y41N7SUFEm+9iDBd^*Q7sw2PC-nZ@`F<=QrIAQ&N z{_3i1{;y>y{px(55b0~ytg&-^Mvn>!3NaV~FFeDWvA?5m7B`*-sX+tyjKCQnva<%ORi&yP@c#*?;yUbly6Q)+=%V diff --git a/api/core/tools/provider/builtin/vanna/tools/vanna.py b/api/core/tools/provider/builtin/vanna/tools/vanna.py deleted file mode 100644 index c90d766e483aaa..00000000000000 --- a/api/core/tools/provider/builtin/vanna/tools/vanna.py +++ /dev/null @@ -1,129 +0,0 @@ -from typing import Any, Union - -from vanna.remote import VannaDefault - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.tool.builtin_tool import BuiltinTool - - -class VannaTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - api_key = self.runtime.credentials.get("api_key", None) - if not api_key: - raise ToolProviderCredentialValidationError("Please input api key") - - model = tool_parameters.get("model", "") - if not model: - return self.create_text_message("Please input RAG model") - - prompt = tool_parameters.get("prompt", "") - if not prompt: - return self.create_text_message("Please input prompt") - - url = tool_parameters.get("url", "") - if not url: - return self.create_text_message("Please input URL/Host/DSN") - - db_name = tool_parameters.get("db_name", "") - username = tool_parameters.get("username", "") - password = tool_parameters.get("password", "") - port = tool_parameters.get("port", 0) - - vn = VannaDefault(model=model, api_key=api_key) - - db_type = tool_parameters.get("db_type", "") - if db_type in {"Postgres", "MySQL", "Hive", "ClickHouse"}: - if not db_name: - return self.create_text_message("Please input database name") - if not username: - return self.create_text_message("Please input username") - if port < 1: - return self.create_text_message("Please input port") - - schema_sql = "SELECT * FROM INFORMATION_SCHEMA.COLUMNS" - match db_type: - case "SQLite": - schema_sql = "SELECT type, sql FROM sqlite_master WHERE sql is not null" - vn.connect_to_sqlite(url) - case "Postgres": - vn.connect_to_postgres(host=url, dbname=db_name, user=username, password=password, port=port) - case "DuckDB": - vn.connect_to_duckdb(url=url) - case "SQLServer": - vn.connect_to_mssql(url) - case "MySQL": - vn.connect_to_mysql(host=url, dbname=db_name, user=username, password=password, port=port) - case "Oracle": - vn.connect_to_oracle(user=username, password=password, dsn=url) - case "Hive": - vn.connect_to_hive(host=url, dbname=db_name, user=username, password=password, port=port) - case "ClickHouse": - vn.connect_to_clickhouse(host=url, dbname=db_name, user=username, password=password, port=port) - - enable_training = tool_parameters.get("enable_training", False) - reset_training_data = tool_parameters.get("reset_training_data", False) - if enable_training: - if reset_training_data: - existing_training_data = vn.get_training_data() - if len(existing_training_data) > 0: - for _, training_data in existing_training_data.iterrows(): - vn.remove_training_data(training_data["id"]) - - ddl = tool_parameters.get("ddl", "") - question = tool_parameters.get("question", "") - sql = tool_parameters.get("sql", "") - memos = tool_parameters.get("memos", "") - training_metadata = tool_parameters.get("training_metadata", False) - - if training_metadata: - if db_type == "SQLite": - df_ddl = vn.run_sql(schema_sql) - for ddl in df_ddl["sql"].to_list(): - vn.train(ddl=ddl) - else: - df_information_schema = vn.run_sql(schema_sql) - plan = vn.get_training_plan_generic(df_information_schema) - vn.train(plan=plan) - - if ddl: - vn.train(ddl=ddl) - - if sql: - if question: - vn.train(question=question, sql=sql) - else: - vn.train(sql=sql) - if memos: - vn.train(documentation=memos) - - ######################################################################################### - # Due to CVE-2024-5565, we have to disable the chart generation feature - # The Vanna library uses a prompt function to present the user with visualized results, - # it is possible to alter the prompt using prompt injection and run arbitrary Python code - # instead of the intended visualization code. - # Specifically - allowing external input to the library’s “ask” method - # with "visualize" set to True (default behavior) leads to remote code execution. - # Affected versions: <= 0.5.5 - ######################################################################################### - generate_chart = False - # generate_chart = tool_parameters.get("generate_chart", True) - res = vn.ask(prompt, False, True, generate_chart) - - result = [] - - if res is not None: - result.append(self.create_text_message(res[0])) - if len(res) > 1 and res[1] is not None: - result.append(self.create_text_message(res[1].to_markdown())) - if len(res) > 2 and res[2] is not None: - result.append( - self.create_blob_message(blob=res[2].to_image(format="svg"), meta={"mime_type": "image/svg+xml"}) - ) - - return result diff --git a/api/core/tools/provider/builtin/vanna/tools/vanna.yaml b/api/core/tools/provider/builtin/vanna/tools/vanna.yaml deleted file mode 100644 index ae2eae94c4dbc4..00000000000000 --- a/api/core/tools/provider/builtin/vanna/tools/vanna.yaml +++ /dev/null @@ -1,213 +0,0 @@ -identity: - name: vanna - author: QCTC - label: - en_US: Vanna.AI - zh_Hans: Vanna.AI -description: - human: - en_US: The fastest way to get actionable insights from your database just by asking questions. - zh_Hans: 一个基于大模型和RAG的Text2SQL工具。 - llm: A tool for converting text to SQL. -parameters: - - name: prompt - type: string - required: true - label: - en_US: Prompt - zh_Hans: 提示词 - pt_BR: Prompt - human_description: - en_US: used for generating SQL - zh_Hans: 用于生成SQL - llm_description: key words for generating SQL - form: llm - - name: model - type: string - required: true - label: - en_US: RAG Model - zh_Hans: RAG模型 - human_description: - en_US: RAG Model for your database DDL - zh_Hans: 存储数据库训练数据的RAG模型 - llm_description: RAG Model for generating SQL - form: form - - name: db_type - type: select - required: true - options: - - value: SQLite - label: - en_US: SQLite - zh_Hans: SQLite - - value: Postgres - label: - en_US: Postgres - zh_Hans: Postgres - - value: DuckDB - label: - en_US: DuckDB - zh_Hans: DuckDB - - value: SQLServer - label: - en_US: Microsoft SQL Server - zh_Hans: 微软 SQL Server - - value: MySQL - label: - en_US: MySQL - zh_Hans: MySQL - - value: Oracle - label: - en_US: Oracle - zh_Hans: Oracle - - value: Hive - label: - en_US: Hive - zh_Hans: Hive - - value: ClickHouse - label: - en_US: ClickHouse - zh_Hans: ClickHouse - default: SQLite - label: - en_US: DB Type - zh_Hans: 数据库类型 - human_description: - en_US: Database type. - zh_Hans: 选择要链接的数据库类型。 - form: form - - name: url - type: string - required: true - label: - en_US: URL/Host/DSN - zh_Hans: URL/Host/DSN - human_description: - en_US: Please input depending on DB type, visit https://vanna.ai/docs/ for more specification - zh_Hans: 请根据数据库类型，填入对应值，详情参考https://vanna.ai/docs/ - form: form - - name: db_name - type: string - required: false - label: - en_US: DB name - zh_Hans: 数据库名 - human_description: - en_US: Database name - zh_Hans: 数据库名 - form: form - - name: username - type: string - required: false - label: - en_US: Username - zh_Hans: 用户名 - human_description: - en_US: Username - zh_Hans: 用户名 - form: form - - name: password - type: secret-input - required: false - label: - en_US: Password - zh_Hans: 密码 - human_description: - en_US: Password - zh_Hans: 密码 - form: form - - name: port - type: number - required: false - label: - en_US: Port - zh_Hans: 端口 - human_description: - en_US: Port - zh_Hans: 端口 - form: form - - name: ddl - type: string - required: false - label: - en_US: Training DDL - zh_Hans: 训练DDL - human_description: - en_US: DDL statements for training data - zh_Hans: 用于训练RAG Model的建表语句 - form: form - - name: question - type: string - required: false - label: - en_US: Training Question - zh_Hans: 训练问题 - human_description: - en_US: Question-SQL Pairs - zh_Hans: Question-SQL中的问题 - form: form - - name: sql - type: string - required: false - label: - en_US: Training SQL - zh_Hans: 训练SQL - human_description: - en_US: SQL queries to your training data - zh_Hans: 用于训练RAG Model的SQL语句 - form: form - - name: memos - type: string - required: false - label: - en_US: Training Memos - zh_Hans: 训练说明 - human_description: - en_US: Sometimes you may want to add documentation about your business terminology or definitions - zh_Hans: 添加更多关于数据库的业务说明 - form: form - - name: enable_training - type: boolean - required: false - default: false - label: - en_US: Training Data - zh_Hans: 训练数据 - human_description: - en_US: You only need to train once. Do not train again unless you want to add more training data - zh_Hans: 训练数据无更新时，训练一次即可 - form: form - - name: reset_training_data - type: boolean - required: false - default: false - label: - en_US: Reset Training Data - zh_Hans: 重置训练数据 - human_description: - en_US: Remove all training data in the current RAG Model - zh_Hans: 删除当前RAG Model中的所有训练数据 - form: form - - name: training_metadata - type: boolean - required: false - default: false - label: - en_US: Training Metadata - zh_Hans: 训练元数据 - human_description: - en_US: If enabled, it will attempt to train on the metadata of that database - zh_Hans: 是否自动从数据库获取元数据来训练 - form: form - - name: generate_chart - type: boolean - required: false - default: True - label: - en_US: Generate Charts - zh_Hans: 生成图表 - human_description: - en_US: Generate Charts - zh_Hans: 是否生成图表 - form: form diff --git a/api/core/tools/provider/builtin/vanna/vanna.py b/api/core/tools/provider/builtin/vanna/vanna.py deleted file mode 100644 index 84724e921a1b00..00000000000000 --- a/api/core/tools/provider/builtin/vanna/vanna.py +++ /dev/null @@ -1,25 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.vanna.tools.vanna import VannaTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class VannaProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - VannaTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "model": "chinook", - "db_type": "SQLite", - "url": "https://vanna.ai/Chinook.sqlite", - "query": "What are the top 10 customers by sales?", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/vanna/vanna.yaml b/api/core/tools/provider/builtin/vanna/vanna.yaml deleted file mode 100644 index b29fa103e1d8c9..00000000000000 --- a/api/core/tools/provider/builtin/vanna/vanna.yaml +++ /dev/null @@ -1,25 +0,0 @@ -identity: - author: QCTC - name: vanna - label: - en_US: Vanna.AI - zh_Hans: Vanna.AI - description: - en_US: The fastest way to get actionable insights from your database just by asking questions. - zh_Hans: 一个基于大模型和RAG的Text2SQL工具。 - icon: icon.png -credentials_for_provider: - api_key: - type: secret-input - required: true - label: - en_US: API key - zh_Hans: API key - placeholder: - en_US: Please input your API key - zh_Hans: 请输入你的 API key - pt_BR: Please input your API key - help: - en_US: Get your API key from Vanna.AI - zh_Hans: 从 Vanna.AI 获取你的 API key - url: https://vanna.ai/account/profile diff --git a/api/core/tools/provider/builtin/vectorizer/_assets/icon.png b/api/core/tools/provider/builtin/vectorizer/_assets/icon.png deleted file mode 100644 index 52f18db84372dcfc2968be27d75aec0fca430d55..0000000000000000000000000000000000000000 GIT binary patch literal 0 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"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" # noqa: E501 diff --git a/api/core/tools/provider/builtin/vectorizer/tools/vectorizer.py b/api/core/tools/provider/builtin/vectorizer/tools/vectorizer.py deleted file mode 100644 index 4bd601c0bd31e0..00000000000000 --- a/api/core/tools/provider/builtin/vectorizer/tools/vectorizer.py +++ /dev/null @@ -1,69 +0,0 @@ -from base64 import b64decode -from typing import Any, Union - -from httpx import post - -from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.vectorizer.tools.test_data import VECTORIZER_ICON_PNG -from core.tools.tool.builtin_tool import BuiltinTool - - -class VectorizerTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - api_key_name = self.runtime.credentials.get("api_key_name", None) - api_key_value = self.runtime.credentials.get("api_key_value", None) - mode = tool_parameters.get("mode", "test") - if mode == "production": - mode = "preview" - - if not api_key_name or not api_key_value: - raise ToolProviderCredentialValidationError("Please input api key name and value") - - image_id = tool_parameters.get("image_id", "") - if not image_id: - return self.create_text_message("Please input image id") - - if image_id.startswith("__test_"): - image_binary = b64decode(VECTORIZER_ICON_PNG) - else: - image_binary = self.get_variable_file(self.VariableKey.IMAGE) - if not image_binary: - return self.create_text_message("Image not found, please request user to generate image firstly.") - - response = post( - "https://vectorizer.ai/api/v1/vectorize", - files={"image": image_binary}, - data={"mode": mode} if mode == "test" else {}, - auth=(api_key_name, api_key_value), - timeout=30, - ) - - if response.status_code != 200: - raise Exception(response.text) - - return [ - self.create_text_message("the vectorized svg is saved as an image."), - self.create_blob_message(blob=response.content, meta={"mime_type": "image/svg+xml"}), - ] - - def get_runtime_parameters(self) -> list[ToolParameter]: - """ - override the runtime parameters - """ - return [ - ToolParameter.get_simple_instance( - name="image_id", - llm_description=f"the image id that you want to vectorize, \ - and the image id should be specified in \ - {[i.name for i in self.list_default_image_variables()]}", - type=ToolParameter.ToolParameterType.SELECT, - required=True, - options=[i.name for i in self.list_default_image_variables()], - ) - ] diff --git a/api/core/tools/provider/builtin/vectorizer/tools/vectorizer.yaml b/api/core/tools/provider/builtin/vectorizer/tools/vectorizer.yaml deleted file mode 100644 index 4b4fb9e2452c3c..00000000000000 --- a/api/core/tools/provider/builtin/vectorizer/tools/vectorizer.yaml +++ /dev/null @@ -1,38 +0,0 @@ -identity: - name: vectorizer - author: Dify - label: - en_US: Vectorizer.AI - zh_Hans: Vectorizer.AI - pt_BR: Vectorizer.AI -description: - human: - en_US: Convert your PNG and JPG images to SVG vectors quickly and easily. Fully automatically. Using AI. - zh_Hans: 一个将 PNG 和 JPG 图像快速轻松地转换为 SVG 矢量图的工具。 - pt_BR: Convert your PNG and JPG images to SVG vectors quickly and easily. Fully automatically. Using AI. - llm: A tool for converting images to SVG vectors. you should input the image id as the input of this tool. the image id can be got from parameters. -parameters: - - name: mode - type: select - required: true - options: - - value: production - label: - en_US: production - zh_Hans: 生产模式 - pt_BR: production - - value: test - label: - en_US: test - zh_Hans: 测试模式 - pt_BR: test - default: test - label: - en_US: Mode - zh_Hans: 模式 - pt_BR: Mode - human_description: - en_US: It is free to integrate with and test out the API in test mode, no subscription required. - zh_Hans: 在测试模式下，可以免费测试API。 - pt_BR: It is free to integrate with and test out the API in test mode, no subscription required. - form: form diff --git a/api/core/tools/provider/builtin/vectorizer/vectorizer.py b/api/core/tools/provider/builtin/vectorizer/vectorizer.py deleted file mode 100644 index 3b868572f93bae..00000000000000 --- a/api/core/tools/provider/builtin/vectorizer/vectorizer.py +++ /dev/null @@ -1,20 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.vectorizer.tools.vectorizer import VectorizerTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class VectorizerProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - VectorizerTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={"mode": "test", "image_id": "__test_123"}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/vectorizer/vectorizer.yaml b/api/core/tools/provider/builtin/vectorizer/vectorizer.yaml deleted file mode 100644 index 1257f8d285c986..00000000000000 --- a/api/core/tools/provider/builtin/vectorizer/vectorizer.yaml +++ /dev/null @@ -1,47 +0,0 @@ -identity: - author: Dify - name: vectorizer - label: - en_US: Vectorizer.AI - zh_Hans: Vectorizer.AI - pt_BR: Vectorizer.AI - description: - en_US: Convert your PNG and JPG images to SVG vectors quickly and easily. Fully automatically. Using AI. - zh_Hans: 一个将 PNG 和 JPG 图像快速轻松地转换为 SVG 矢量图的工具。 - pt_BR: Convert your PNG and JPG images to SVG vectors quickly and easily. Fully automatically. Using AI. - icon: icon.png - tags: - - productivity - - image -credentials_for_provider: - api_key_name: - type: secret-input - required: true - label: - en_US: Vectorizer.AI API Key name - zh_Hans: Vectorizer.AI API Key name - pt_BR: Vectorizer.AI API Key name - placeholder: - en_US: Please input your Vectorizer.AI ApiKey name - zh_Hans: 请输入你的 Vectorizer.AI ApiKey name - pt_BR: Please input your Vectorizer.AI ApiKey name - help: - en_US: Get your Vectorizer.AI API Key from Vectorizer.AI. - zh_Hans: 从 Vectorizer.AI 获取您的 Vectorizer.AI API Key。 - pt_BR: Get your Vectorizer.AI API Key from Vectorizer.AI. - url: https://vectorizer.ai/api - api_key_value: - type: secret-input - required: true - label: - en_US: Vectorizer.AI API Key - zh_Hans: Vectorizer.AI API Key - pt_BR: Vectorizer.AI API Key - placeholder: - en_US: Please input your Vectorizer.AI ApiKey - zh_Hans: 请输入你的 Vectorizer.AI ApiKey - pt_BR: Please input your Vectorizer.AI ApiKey - help: - en_US: Get your Vectorizer.AI API Key from Vectorizer.AI. - zh_Hans: 从 Vectorizer.AI 获取您的 Vectorizer.AI API Key。 - pt_BR: Get your Vectorizer.AI API Key from Vectorizer.AI. diff --git a/api/core/tools/provider/builtin/webscraper/_assets/icon.svg b/api/core/tools/provider/builtin/webscraper/_assets/icon.svg deleted file mode 100644 index 8123199a38a5e7..00000000000000 --- a/api/core/tools/provider/builtin/webscraper/_assets/icon.svg +++ /dev/null @@ -1,3 +0,0 @@ - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/webscraper/tools/webscraper.py b/api/core/tools/provider/builtin/webscraper/tools/webscraper.py deleted file mode 100644 index 12670b4b8b9289..00000000000000 --- a/api/core/tools/provider/builtin/webscraper/tools/webscraper.py +++ /dev/null @@ -1,33 +0,0 @@ -from typing import Any, Union - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.errors import ToolInvokeError -from core.tools.tool.builtin_tool import BuiltinTool - - -class WebscraperTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - try: - url = tool_parameters.get("url", "") - user_agent = tool_parameters.get("user_agent", "") - if not url: - return self.create_text_message("Please input url") - - # get webpage - result = self.get_url(url, user_agent=user_agent) - - if tool_parameters.get("generate_summary"): - # summarize and return - return self.create_text_message(self.summary(user_id=user_id, content=result)) - else: - # return full webpage - return self.create_text_message(result) - except Exception as e: - raise ToolInvokeError(str(e)) diff --git a/api/core/tools/provider/builtin/webscraper/tools/webscraper.yaml b/api/core/tools/provider/builtin/webscraper/tools/webscraper.yaml deleted file mode 100644 index 0bb48a941dcffe..00000000000000 --- a/api/core/tools/provider/builtin/webscraper/tools/webscraper.yaml +++ /dev/null @@ -1,60 +0,0 @@ -identity: - name: webscraper - author: Dify - label: - en_US: Web Scraper - zh_Hans: 网页爬虫 - pt_BR: Web Scraper -description: - human: - en_US: A tool for scraping webpages. - zh_Hans: 一个用于爬取网页的工具。 - pt_BR: A tool for scraping webpages. - llm: A tool for scraping webpages. Input should be a URL. -parameters: - - name: url - type: string - required: true - label: - en_US: URL - zh_Hans: 网页链接 - pt_BR: URL - human_description: - en_US: used for linking to webpages - zh_Hans: 用于链接到网页 - pt_BR: used for linking to webpages - llm_description: url for scraping - form: llm - - name: user_agent - type: string - required: false - label: - en_US: User Agent - zh_Hans: User Agent - pt_BR: User Agent - human_description: - en_US: used for identifying the browser. - zh_Hans: 用于识别浏览器。 - pt_BR: used for identifying the browser. - form: form - default: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.1000.0 Safari/537.36 - - name: generate_summary - type: boolean - required: false - label: - en_US: Whether to generate summary - zh_Hans: 是否生成摘要 - human_description: - en_US: If true, the crawler will only return the page summary content. - zh_Hans: 如果启用，爬虫将仅返回页面摘要内容。 - form: form - options: - - value: 'true' - label: - en_US: 'Yes' - zh_Hans: 是 - - value: 'false' - label: - en_US: 'No' - zh_Hans: 否 - default: 'false' diff --git a/api/core/tools/provider/builtin/webscraper/webscraper.py b/api/core/tools/provider/builtin/webscraper/webscraper.py deleted file mode 100644 index 3c51393ac64cc4..00000000000000 --- a/api/core/tools/provider/builtin/webscraper/webscraper.py +++ /dev/null @@ -1,23 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.webscraper.tools.webscraper import WebscraperTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class WebscraperProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - WebscraperTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "url": "https://www.google.com", - "user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 ", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/webscraper/webscraper.yaml b/api/core/tools/provider/builtin/webscraper/webscraper.yaml deleted file mode 100644 index 6c2eb97784e298..00000000000000 --- a/api/core/tools/provider/builtin/webscraper/webscraper.yaml +++ /dev/null @@ -1,15 +0,0 @@ -identity: - author: Dify - name: webscraper - label: - en_US: WebScraper - zh_Hans: 网页抓取 - pt_BR: WebScraper - description: - en_US: Web Scrapper tool kit is used to scrape web - zh_Hans: 一个用于抓取网页的工具。 - pt_BR: Web Scrapper tool kit is used to scrape web - icon: icon.svg - tags: - - productivity -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/websearch/_assets/icon.svg b/api/core/tools/provider/builtin/websearch/_assets/icon.svg deleted file mode 100644 index d6ef5d878f8636..00000000000000 --- a/api/core/tools/provider/builtin/websearch/_assets/icon.svg +++ /dev/null @@ -1,23 +0,0 @@ - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/websearch/tools/get_markdown.py b/api/core/tools/provider/builtin/websearch/tools/get_markdown.py deleted file mode 100644 index 043879deeab18f..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/get_markdown.py +++ /dev/null @@ -1,51 +0,0 @@ -from typing import Any, Union - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -BASE_URL = "https://api.serply.io/v1/request" - - -class SerplyApi: - """ - SerplyAPI tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize SerplyAPI tool provider.""" - self.serply_api_key = api_key - - def run(self, url: str, **kwargs: Any) -> str: - """Run query through SerplyAPI and parse result.""" - - location = kwargs.get("location", "US") - - headers = { - "X-API-KEY": self.serply_api_key, - "X-User-Agent": kwargs.get("device", "desktop"), - "X-Proxy-Location": location, - "User-Agent": "Dify", - } - data = {"url": url, "method": "GET", "response_type": "markdown"} - res = requests.post(url, headers=headers, json=data) - return res.text - - -class GetMarkdownTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SerplyApi tool. - """ - url = tool_parameters["url"] - location = tool_parameters.get("location") - - api_key = self.runtime.credentials["serply_api_key"] - result = SerplyApi(api_key).run(url, location=location) - - return self.create_text_message(text=result) diff --git a/api/core/tools/provider/builtin/websearch/tools/get_markdown.yaml b/api/core/tools/provider/builtin/websearch/tools/get_markdown.yaml deleted file mode 100644 index 06a302bd14b82d..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/get_markdown.yaml +++ /dev/null @@ -1,96 +0,0 @@ -identity: - name: get_markdown - author: Dify - label: - en_US: Get Markdown API - zh_Hans: Get Markdown API -description: - human: - en_US: A tool to perform convert a webpage to markdown to make it easier for LLMs to understand. - zh_Hans: 一个将网页转换为 Markdown 的工具，以便模型更容易理解 - llm: A tool to perform convert a webpage to markdown to make it easier for LLMs to understand. -parameters: - - name: url - type: string - required: true - label: - en_US: URL - zh_Hans: URL - human_description: - en_US: URL that you want to grab the content from - zh_Hans: 您要从中获取内容的 URL - llm_description: Defines the link want to grab content from. - form: llm - - name: location - type: string - required: false - default: US - label: - en_US: Location - zh_Hans: 询问 - human_description: - en_US: Defines from where you want the search to originate. (For example - New York) - zh_Hans: 定义您想要搜索的起始位置。 （例如 - 纽约） - llm_description: Defines from where you want the search to originate. (For example - New York) - form: form - options: - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden diff --git a/api/core/tools/provider/builtin/websearch/tools/job_search.py b/api/core/tools/provider/builtin/websearch/tools/job_search.py deleted file mode 100644 index 293f4f63297120..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/job_search.py +++ /dev/null @@ -1,88 +0,0 @@ -from typing import Any, Union -from urllib.parse import urlencode - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -BASE_URL = "https://api.serply.io/v1/news/" - - -class SerplyApi: - """ - SerplyAPI tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize SerplyAPI tool provider.""" - self.serply_api_key = api_key - - def run(self, query: str, **kwargs: Any) -> str: - """Run query through SerplyAPI and parse result.""" - params = {"q": query, "hl": kwargs.get("hl", "en"), "gl": kwargs.get("gl", "US"), "num": kwargs.get("num", 10)} - location = kwargs.get("location", "US") - - headers = { - "X-API-KEY": self.serply_api_key, - "X-User-Agent": kwargs.get("device", "desktop"), - "X-Proxy-Location": location, - "User-Agent": "Dify", - } - - url = f"{BASE_URL}{urlencode(params)}" - res = requests.get( - url, - headers=headers, - ) - res = res.json() - - return self.parse_results(res) - - @staticmethod - def parse_results(res: dict) -> str: - """Process response from Serply Job Search.""" - jobs = res.get("jobs", []) - if not jobs: - raise ValueError(f"Got error from Serply: {res}") - - string = [] - for job in jobs[:10]: - try: - string.append( - "\n".join( - [ - f"Position: {job['position']}", - f"Employer: {job['employer']}", - f"Location: {job['location']}", - f"Link: {job['link']}", - f"""Highest: {", ".join(list(job["highlights"]))}""", - "---", - ] - ) - ) - except KeyError: - continue - - content = "\n".join(string) - return f"\nJobs results:\n {content}\n" - - -class JobSearchTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SerplyApi tool. - """ - query = tool_parameters["query"] - gl = tool_parameters.get("gl", "us") - hl = tool_parameters.get("hl", "en") - location = tool_parameters.get("location") - - api_key = self.runtime.credentials["serply_api_key"] - result = SerplyApi(api_key).run(query, gl=gl, hl=hl, location=location) - - return self.create_text_message(text=result) diff --git a/api/core/tools/provider/builtin/websearch/tools/job_search.yaml b/api/core/tools/provider/builtin/websearch/tools/job_search.yaml deleted file mode 100644 index b5ede3df46ab01..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/job_search.yaml +++ /dev/null @@ -1,41 +0,0 @@ -identity: - name: job_search - author: Dify - label: - en_US: Job Search API - zh_Hans: Job Search API -description: - human: - en_US: A tool to retrieve job titles, company names and description from Google Jobs engine. - zh_Hans: 一个从 Google 招聘引擎检索职位名称、公司名称和描述的工具。 - llm: A tool to retrieve job titles, company names and description from Google Jobs engine. -parameters: - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 询问 - human_description: - en_US: Defines the query you want to search. - zh_Hans: 定义您要搜索的查询。 - llm_description: Defines the search query you want to search. - form: llm - - name: location - type: string - required: false - default: US - label: - en_US: Location - zh_Hans: 询问 - human_description: - en_US: Defines from where you want the search to originate. (For example - New York) - zh_Hans: 定义您想要搜索的起始位置。 （例如 - 纽约） - llm_description: Defines from where you want the search to originate. (For example - New York) - form: form - options: - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States diff --git a/api/core/tools/provider/builtin/websearch/tools/news_search.py b/api/core/tools/provider/builtin/websearch/tools/news_search.py deleted file mode 100644 index 9b5482fe183e18..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/news_search.py +++ /dev/null @@ -1,90 +0,0 @@ -from typing import Any, Union -from urllib.parse import urlencode - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -BASE_URL = "https://api.serply.io/v1/news/" - - -class SerplyApi: - """ - SerplyApi tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize SerplyApi tool provider.""" - self.serply_api_key = api_key - - def run(self, query: str, **kwargs: Any) -> str: - """Run query through SerplyApi and parse result.""" - params = {"q": query, "hl": kwargs.get("hl", "en"), "gl": kwargs.get("gl", "US"), "num": kwargs.get("num", 10)} - location = kwargs.get("location", "US") - - headers = { - "X-API-KEY": self.serply_api_key, - "X-User-Agent": kwargs.get("device", "desktop"), - "X-Proxy-Location": location, - "User-Agent": "Dify", - } - - url = f"{BASE_URL}{urlencode(params)}" - res = requests.get( - url, - headers=headers, - ) - res = res.json() - - return self.parse_results(res) - - @staticmethod - def parse_results(res: dict) -> str: - """Process response from Serply News Search.""" - news = res.get("entries", []) - if not news: - raise ValueError(f"Got error from Serply: {res}") - - string = [] - for entry in news: - try: - # follow url - r = requests.get(entry["link"]) - final_link = r.history[-1].headers["Location"] - string.append( - "\n".join( - [ - f"Title: {entry['title']}", - f"Link: {final_link}", - f"Source: {entry['source']['title']}", - f"Published: {entry['published']}", - "---", - ] - ) - ) - except KeyError: - continue - - content = "\n".join(string) - return f"\nNews:\n {content}\n" - - -class NewsSearchTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SerplyApi tool. - """ - query = tool_parameters["query"] - gl = tool_parameters.get("gl", "us") - hl = tool_parameters.get("hl", "en") - location = tool_parameters.get("location") - - api_key = self.runtime.credentials["serply_api_key"] - result = SerplyApi(api_key).run(query, gl=gl, hl=hl, location=location) - - return self.create_text_message(text=result) diff --git a/api/core/tools/provider/builtin/websearch/tools/news_search.yaml b/api/core/tools/provider/builtin/websearch/tools/news_search.yaml deleted file mode 100644 index 126c610825ebbb..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/news_search.yaml +++ /dev/null @@ -1,501 +0,0 @@ -identity: - name: news_search - author: Dify - label: - en_US: News Search API - zh_Hans: News Search API -description: - human: - en_US: A tool to retrieve organic search results snippets and links from Google News engine. - zh_Hans: 一种从 Google 新闻引擎检索有机搜索结果片段和链接的工具。 - llm: A tool to retrieve organic search results snippets and links from Google News engine. -parameters: - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 询问 - human_description: - en_US: Defines the query you want to search. - zh_Hans: 定义您要搜索的查询。 - llm_description: Defines the search query you want to search. - form: llm - - name: location - type: string - required: false - default: US - label: - en_US: Location - zh_Hans: 询问 - human_description: - en_US: Defines from where you want the search to originate. (For example - New York) - zh_Hans: 定义您想要搜索的起始位置。 （例如 - 纽约） - llm_description: Defines from where you want the search to originate. (For example - New York) - form: form - options: - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - name: gl - type: select - label: - en_US: Country - zh_Hans: 国家/地区 - required: false - human_description: - en_US: Defines the country of the search. Default is "US". - zh_Hans: 定义搜索的国家/地区。默认为“美国”。 - llm_description: Defines the gl parameter of the Google search. - form: form - default: US - options: - - value: AR - label: - en_US: Argentina - zh_Hans: 阿根廷 - pt_BR: Argentina - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: AT - label: - en_US: Austria - zh_Hans: 奥地利 - pt_BR: Austria - - value: BE - label: - en_US: Belgium - zh_Hans: 比利时 - pt_BR: Belgium - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: CL - label: - en_US: Chile - zh_Hans: 智利 - pt_BR: Chile - - value: CO - label: - en_US: Colombia - zh_Hans: 哥伦比亚 - pt_BR: Colombia - - value: CN - label: - en_US: China - zh_Hans: 中国 - pt_BR: China - - value: CZ - label: - en_US: Czech Republic - zh_Hans: 捷克共和国 - pt_BR: Czech Republic - - value: DK - label: - en_US: Denmark - zh_Hans: 丹麦 - pt_BR: Denmark - - value: FI - label: - en_US: Finland - zh_Hans: 芬兰 - pt_BR: Finland - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: HK - label: - en_US: Hong Kong - zh_Hans: 香港 - pt_BR: Hong Kong - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: ID - label: - en_US: Indonesia - zh_Hans: 印度尼西亚 - pt_BR: Indonesia - - value: IT - label: - en_US: Italy - zh_Hans: 意大利 - pt_BR: Italy - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: MY - label: - en_US: Malaysia - zh_Hans: 马来西亚 - pt_BR: Malaysia - - value: MX - label: - en_US: Mexico - zh_Hans: 墨西哥 - pt_BR: Mexico - - value: NL - label: - en_US: Netherlands - zh_Hans: 荷兰 - pt_BR: Netherlands - - value: NZ - label: - en_US: New Zealand - zh_Hans: 新西兰 - pt_BR: New Zealand - - value: NO - label: - en_US: Norway - zh_Hans: 挪威 - pt_BR: Norway - - value: PH - label: - en_US: Philippines - zh_Hans: 菲律宾 - pt_BR: Philippines - - value: PL - label: - en_US: Poland - zh_Hans: 波兰 - pt_BR: Poland - - value: PT - label: - en_US: Portugal - zh_Hans: 葡萄牙 - pt_BR: Portugal - - value: RU - label: - en_US: Russia - zh_Hans: 俄罗斯 - pt_BR: Russia - - value: SA - label: - en_US: Saudi Arabia - zh_Hans: 沙特阿拉伯 - pt_BR: Saudi Arabia - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: ZA - label: - en_US: South Africa - zh_Hans: 南非 - pt_BR: South Africa - - value: ES - label: - en_US: Spain - zh_Hans: 西班牙 - pt_BR: Spain - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - value: CH - label: - en_US: Switzerland - zh_Hans: 瑞士 - pt_BR: Switzerland - - value: TW - label: - en_US: Taiwan - zh_Hans: 台湾 - pt_BR: Taiwan - - value: TH - label: - en_US: Thailand - zh_Hans: 泰国 - pt_BR: Thailand - - value: TR - label: - en_US: Turkey - zh_Hans: 土耳其 - pt_BR: Turkey - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - name: hl - type: select - label: - en_US: Language - zh_Hans: 语言 - human_description: - en_US: Defines the interface language of the search. Default is "en". - zh_Hans: 定义搜索的界面语言。默认为“en”。 - required: false - default: en - form: form - options: - - value: ar - label: - en_US: Arabic - zh_Hans: 阿拉伯语 - - value: bg - label: - en_US: Bulgarian - zh_Hans: 保加利亚语 - - value: ca - label: - en_US: Catalan - zh_Hans: 加泰罗尼亚语 - - value: zh-cn - label: - en_US: Chinese (Simplified) - zh_Hans: 中文（简体） - - value: zh-tw - label: - en_US: Chinese (Traditional) - zh_Hans: 中文（繁体） - - value: cs - label: - en_US: Czech - zh_Hans: 捷克语 - - value: da - label: - en_US: Danish - zh_Hans: 丹麦语 - - value: nl - label: - en_US: Dutch - zh_Hans: 荷兰语 - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: et - label: - en_US: Estonian - zh_Hans: 爱沙尼亚语 - - value: fi - label: - en_US: Finnish - zh_Hans: 芬兰语 - - value: fr - label: - en_US: French - zh_Hans: 法语 - - value: de - label: - en_US: German - zh_Hans: 德语 - - value: el - label: - en_US: Greek - zh_Hans: 希腊语 - - value: iw - label: - en_US: Hebrew - zh_Hans: 希伯来语 - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - - value: hu - label: - en_US: Hungarian - zh_Hans: 匈牙利语 - - value: id - label: - en_US: Indonesian - zh_Hans: 印尼语 - - value: it - label: - en_US: Italian - zh_Hans: 意大利语 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - - value: kn - label: - en_US: Kannada - zh_Hans: 卡纳达语 - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - - value: lv - label: - en_US: Latvian - zh_Hans: 拉脱维亚语 - - value: lt - label: - en_US: Lithuanian - zh_Hans: 立陶宛语 - - value: my - label: - en_US: Malay - zh_Hans: 马来语 - - value: ml - label: - en_US: Malayalam - zh_Hans: 马拉雅拉姆语 - - value: mr - label: - en_US: Marathi - zh_Hans: 马拉地语 - - value: "no" - label: - en_US: Norwegian - zh_Hans: 挪威语 - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - - value: pt-br - label: - en_US: Portuguese (Brazil) - zh_Hans: 葡萄牙语（巴西） - - value: pt-pt - label: - en_US: Portuguese (Portugal) - zh_Hans: 葡萄牙语（葡萄牙） - - value: pa - label: - en_US: Punjabi - zh_Hans: 旁遮普语 - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - - value: ru - label: - en_US: Russian - zh_Hans: 俄语 - - value: sr - label: - en_US: Serbian - zh_Hans: 塞尔维亚语 - - value: sk - label: - en_US: Slovak - zh_Hans: 斯洛伐克语 - - value: sl - label: - en_US: Slovenian - zh_Hans: 斯洛文尼亚语 - - value: es - label: - en_US: Spanish - zh_Hans: 西班牙语 - - value: sv - label: - en_US: Swedish - zh_Hans: 瑞典语 - - value: ta - label: - en_US: Tamil - zh_Hans: 泰米尔语 - - value: te - label: - en_US: Telugu - zh_Hans: 泰卢固语 - - value: th - label: - en_US: Thai - zh_Hans: 泰语 - - value: tr - label: - en_US: Turkish - zh_Hans: 土耳其语 - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 diff --git a/api/core/tools/provider/builtin/websearch/tools/scholar_search.py b/api/core/tools/provider/builtin/websearch/tools/scholar_search.py deleted file mode 100644 index 798d059b512edf..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/scholar_search.py +++ /dev/null @@ -1,93 +0,0 @@ -from typing import Any, Union -from urllib.parse import urlencode - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -BASE_URL = "https://api.serply.io/v1/scholar/" - - -class SerplyApi: - """ - SerplyApi tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize SerplyApi tool provider.""" - self.serply_api_key = api_key - - def run(self, query: str, **kwargs: Any) -> str: - """Run query through SerplyApi and parse result.""" - params = {"q": query, "hl": kwargs.get("hl", "en"), "gl": kwargs.get("gl", "US"), "num": kwargs.get("num", 10)} - location = kwargs.get("location", "US") - - headers = { - "X-API-KEY": self.serply_api_key, - "X-User-Agent": kwargs.get("device", "desktop"), - "X-Proxy-Location": location, - "User-Agent": "Dify", - } - - url = f"{BASE_URL}{urlencode(params)}" - res = requests.get( - url, - headers=headers, - ) - res = res.json() - - return self.parse_results(res) - - @staticmethod - def parse_results(res: dict) -> str: - """Process response from Serply News Search.""" - articles = res.get("articles", []) - if not articles: - raise ValueError(f"Got error from Serply: {res}") - - string = [] - for article in articles: - try: - if "doc" in article: - link = article["doc"]["link"] - else: - link = article["link"] - authors = [author["name"] for author in article["author"]["authors"]] - string.append( - "\n".join( - [ - f"Title: {article['title']}", - f"Link: {link}", - f"Description: {article['description']}", - f"Cite: {article['cite']}", - f"Authors: {', '.join(authors)}", - "---", - ] - ) - ) - except KeyError: - continue - - content = "\n".join(string) - return f"\nScholar results:\n {content}\n" - - -class ScholarSearchTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SerplyApi tool. - """ - query = tool_parameters["query"] - gl = tool_parameters.get("gl", "us") - hl = tool_parameters.get("hl", "en") - location = tool_parameters.get("location") - - api_key = self.runtime.credentials["serply_api_key"] - result = SerplyApi(api_key).run(query, gl=gl, hl=hl, location=location) - - return self.create_text_message(text=result) diff --git a/api/core/tools/provider/builtin/websearch/tools/scholar_search.yaml b/api/core/tools/provider/builtin/websearch/tools/scholar_search.yaml deleted file mode 100644 index 63e79d7ebfaa49..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/scholar_search.yaml +++ /dev/null @@ -1,501 +0,0 @@ -identity: - name: scholar_search - author: Dify - label: - en_US: Scholar API - zh_Hans: Scholar API -description: - human: - en_US: A tool to retrieve scholarly literature. - zh_Hans: 学术文献检索工具 - llm: A tool to retrieve scholarly literature. -parameters: - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 询问 - human_description: - en_US: Defines the query you want to search. - zh_Hans: 定义您要搜索的查询。 - llm_description: Defines the search query you want to search. - form: llm - - name: location - type: string - required: false - default: US - label: - en_US: Location - zh_Hans: 询问 - human_description: - en_US: Defines from where you want the search to originate. (For example - New York) - zh_Hans: 定义您想要搜索的起始位置。 （例如 - 纽约） - llm_description: Defines from where you want the search to originate. (For example - New York) - form: form - options: - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - name: gl - type: select - label: - en_US: Country - zh_Hans: 国家/地区 - required: false - human_description: - en_US: Defines the country of the search. Default is "US". - zh_Hans: 定义搜索的国家/地区。默认为“美国”。 - llm_description: Defines the gl parameter of the Google search. - form: form - default: US - options: - - value: AR - label: - en_US: Argentina - zh_Hans: 阿根廷 - pt_BR: Argentina - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: AT - label: - en_US: Austria - zh_Hans: 奥地利 - pt_BR: Austria - - value: BE - label: - en_US: Belgium - zh_Hans: 比利时 - pt_BR: Belgium - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: CL - label: - en_US: Chile - zh_Hans: 智利 - pt_BR: Chile - - value: CO - label: - en_US: Colombia - zh_Hans: 哥伦比亚 - pt_BR: Colombia - - value: CN - label: - en_US: China - zh_Hans: 中国 - pt_BR: China - - value: CZ - label: - en_US: Czech Republic - zh_Hans: 捷克共和国 - pt_BR: Czech Republic - - value: DK - label: - en_US: Denmark - zh_Hans: 丹麦 - pt_BR: Denmark - - value: FI - label: - en_US: Finland - zh_Hans: 芬兰 - pt_BR: Finland - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: HK - label: - en_US: Hong Kong - zh_Hans: 香港 - pt_BR: Hong Kong - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: ID - label: - en_US: Indonesia - zh_Hans: 印度尼西亚 - pt_BR: Indonesia - - value: IT - label: - en_US: Italy - zh_Hans: 意大利 - pt_BR: Italy - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: MY - label: - en_US: Malaysia - zh_Hans: 马来西亚 - pt_BR: Malaysia - - value: MX - label: - en_US: Mexico - zh_Hans: 墨西哥 - pt_BR: Mexico - - value: NL - label: - en_US: Netherlands - zh_Hans: 荷兰 - pt_BR: Netherlands - - value: NZ - label: - en_US: New Zealand - zh_Hans: 新西兰 - pt_BR: New Zealand - - value: "NO" - label: - en_US: Norway - zh_Hans: 挪威 - pt_BR: Norway - - value: PH - label: - en_US: Philippines - zh_Hans: 菲律宾 - pt_BR: Philippines - - value: PL - label: - en_US: Poland - zh_Hans: 波兰 - pt_BR: Poland - - value: PT - label: - en_US: Portugal - zh_Hans: 葡萄牙 - pt_BR: Portugal - - value: RU - label: - en_US: Russia - zh_Hans: 俄罗斯 - pt_BR: Russia - - value: SA - label: - en_US: Saudi Arabia - zh_Hans: 沙特阿拉伯 - pt_BR: Saudi Arabia - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: ZA - label: - en_US: South Africa - zh_Hans: 南非 - pt_BR: South Africa - - value: ES - label: - en_US: Spain - zh_Hans: 西班牙 - pt_BR: Spain - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - value: CH - label: - en_US: Switzerland - zh_Hans: 瑞士 - pt_BR: Switzerland - - value: TW - label: - en_US: Taiwan - zh_Hans: 台湾 - pt_BR: Taiwan - - value: TH - label: - en_US: Thailand - zh_Hans: 泰国 - pt_BR: Thailand - - value: TR - label: - en_US: Turkey - zh_Hans: 土耳其 - pt_BR: Turkey - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - name: hl - type: select - label: - en_US: Language - zh_Hans: 语言 - human_description: - en_US: Defines the interface language of the search. Default is "en". - zh_Hans: 定义搜索的界面语言。默认为“en”。 - required: false - default: en - form: form - options: - - value: ar - label: - en_US: Arabic - zh_Hans: 阿拉伯语 - - value: bg - label: - en_US: Bulgarian - zh_Hans: 保加利亚语 - - value: ca - label: - en_US: Catalan - zh_Hans: 加泰罗尼亚语 - - value: zh-cn - label: - en_US: Chinese (Simplified) - zh_Hans: 中文（简体） - - value: zh-tw - label: - en_US: Chinese (Traditional) - zh_Hans: 中文（繁体） - - value: cs - label: - en_US: Czech - zh_Hans: 捷克语 - - value: da - label: - en_US: Danish - zh_Hans: 丹麦语 - - value: nl - label: - en_US: Dutch - zh_Hans: 荷兰语 - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: et - label: - en_US: Estonian - zh_Hans: 爱沙尼亚语 - - value: fi - label: - en_US: Finnish - zh_Hans: 芬兰语 - - value: fr - label: - en_US: French - zh_Hans: 法语 - - value: de - label: - en_US: German - zh_Hans: 德语 - - value: el - label: - en_US: Greek - zh_Hans: 希腊语 - - value: iw - label: - en_US: Hebrew - zh_Hans: 希伯来语 - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - - value: hu - label: - en_US: Hungarian - zh_Hans: 匈牙利语 - - value: id - label: - en_US: Indonesian - zh_Hans: 印尼语 - - value: it - label: - en_US: Italian - zh_Hans: 意大利语 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - - value: kn - label: - en_US: Kannada - zh_Hans: 卡纳达语 - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - - value: lv - label: - en_US: Latvian - zh_Hans: 拉脱维亚语 - - value: lt - label: - en_US: Lithuanian - zh_Hans: 立陶宛语 - - value: my - label: - en_US: Malay - zh_Hans: 马来语 - - value: ml - label: - en_US: Malayalam - zh_Hans: 马拉雅拉姆语 - - value: mr - label: - en_US: Marathi - zh_Hans: 马拉地语 - - value: "no" - label: - en_US: Norwegian - zh_Hans: 挪威语 - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - - value: pt-br - label: - en_US: Portuguese (Brazil) - zh_Hans: 葡萄牙语（巴西） - - value: pt-pt - label: - en_US: Portuguese (Portugal) - zh_Hans: 葡萄牙语（葡萄牙） - - value: pa - label: - en_US: Punjabi - zh_Hans: 旁遮普语 - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - - value: ru - label: - en_US: Russian - zh_Hans: 俄语 - - value: sr - label: - en_US: Serbian - zh_Hans: 塞尔维亚语 - - value: sk - label: - en_US: Slovak - zh_Hans: 斯洛伐克语 - - value: sl - label: - en_US: Slovenian - zh_Hans: 斯洛文尼亚语 - - value: es - label: - en_US: Spanish - zh_Hans: 西班牙语 - - value: sv - label: - en_US: Swedish - zh_Hans: 瑞典语 - - value: ta - label: - en_US: Tamil - zh_Hans: 泰米尔语 - - value: te - label: - en_US: Telugu - zh_Hans: 泰卢固语 - - value: th - label: - en_US: Thai - zh_Hans: 泰语 - - value: tr - label: - en_US: Turkish - zh_Hans: 土耳其语 - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 diff --git a/api/core/tools/provider/builtin/websearch/tools/web_search.py b/api/core/tools/provider/builtin/websearch/tools/web_search.py deleted file mode 100644 index fe363ac7a4d5d0..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/web_search.py +++ /dev/null @@ -1,90 +0,0 @@ -import typing -from urllib.parse import urlencode - -import requests - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class SerplyApi: - """ - SerplyApi tool provider. - """ - - def __init__(self, api_key: str) -> None: - """Initialize Serply Web Search Tool provider.""" - self.serply_api_key = api_key - self.base_url = "https://api.serply.io/v1/search/" - - def run(self, query: str, **kwargs: typing.Any) -> str: - """Run query through Serply and parse result.""" - params = {"q": query, "hl": kwargs.get("hl", "en"), "gl": kwargs.get("gl", "US"), "num": kwargs.get("num", 10)} - location = kwargs.get("location", "US") - - headers = { - "X-API-KEY": self.serply_api_key, - "X-User-Agent": kwargs.get("device", "desktop"), - "X-Proxy-Location": location, - "User-Agent": "Dify", - } - - url = f"{self.base_url}{urlencode(params)}" - res = requests.get( - url, - headers=headers, - ) - res = res.json() - - return self.parse_results(res) - - @staticmethod - def parse_results(res: dict) -> str: - """Process response from Serply Web Search.""" - results = res.get("results", []) - if not results: - raise ValueError(f"Got error from Serply: {res}") - - string = [] - for result in results: - try: - string.append( - "\n".join( - [ - f"Title: {result['title']}", - f"Link: {result['link']}", - f"Description: {result['description'].strip()}", - "---", - ] - ) - ) - except KeyError: - continue - - if related_questions := res.get("related_questions", []): - string.append("---") - string.append("Related Questions: ") - string.append("\n".join(related_questions)) - - content = "\n".join(string) - return f"\nSearch results:\n {content}\n" - - -class WebSearchTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, typing.Any], - ) -> typing.Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - Invoke the SerplyApi tool. - """ - query = tool_parameters["query"] - num = tool_parameters.get("num", 10) - gl = tool_parameters.get("gl", "us") - hl = tool_parameters.get("hl", "en") - location = tool_parameters.get("location", "None") - - api_key = self.runtime.credentials["serply_api_key"] - result = SerplyApi(api_key).run(query=query, num=num, gl=gl, hl=hl, location=location) - return self.create_text_message(text=result) diff --git a/api/core/tools/provider/builtin/websearch/tools/web_search.yaml b/api/core/tools/provider/builtin/websearch/tools/web_search.yaml deleted file mode 100644 index 055029253c1753..00000000000000 --- a/api/core/tools/provider/builtin/websearch/tools/web_search.yaml +++ /dev/null @@ -1,376 +0,0 @@ -identity: - name: web_search - author: Dify - label: - en_US: Web Search API - zh_Hans: Web Search API -description: - human: - en_US: A tool to retrieve answer boxes, knowledge graphs, snippets, and webpages from Google Search engine. - zh_Hans: 一种从 Google 搜索引擎检索答案框、知识图、片段和网页的工具。 - llm: A tool to retrieve answer boxes, knowledge graphs, snippets, and webpages from Google Search engine. -parameters: - - name: query - type: string - required: true - label: - en_US: Query - zh_Hans: 询问 - human_description: - en_US: Defines the query you want to search. - zh_Hans: 定义您要搜索的查询。 - llm_description: Defines the search query you want to search. - form: llm - - name: location - type: string - required: false - default: US - label: - en_US: Location - zh_Hans: 询问 - human_description: - en_US: Defines from where you want the search to originate. (For example - New York) - zh_Hans: 定义您想要搜索的起始位置。 （例如 - 纽约） - llm_description: Defines from where you want the search to originate. (For example - New York) - form: form - options: - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - value: JP - label: - en_US: Japan - zh_Hans: 日本 - pt_BR: Japan - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - name: device - type: select - label: - en_US: Device Type - zh_Hans: 汉斯先生 - human_description: - en_US: Defines the device to make interface search. Default is "desktop". - zh_Hans: 定义进行接口搜索的设备。默认为“桌面” - required: false - default: desktop - form: form - options: - - value: desktop - label: - en_US: Desktop - zh_Hans: 桌面 - - value: mobile - label: - en_US: Mobile - zh_Hans: 移动的 - - name: gl - type: select - label: - en_US: Country - zh_Hans: 国家/地区 - required: false - human_description: - en_US: Defines the country of the search. Default is "US". - zh_Hans: 定义搜索的国家/地区。默认为“美国”。 - llm_description: Defines the gl parameter of the Google search. - form: form - default: US - options: - - value: AU - label: - en_US: Australia - zh_Hans: 澳大利亚 - pt_BR: Australia - - value: BR - label: - en_US: Brazil - zh_Hans: 巴西 - pt_BR: Brazil - - value: CA - label: - en_US: Canada - zh_Hans: 加拿大 - pt_BR: Canada - - value: DE - label: - en_US: Germany - zh_Hans: 德国 - pt_BR: Germany - - value: FR - label: - en_US: France - zh_Hans: 法国 - pt_BR: France - - value: GB - label: - en_US: United Kingdom - zh_Hans: 英国 - pt_BR: United Kingdom - - value: IN - label: - en_US: India - zh_Hans: 印度 - pt_BR: India - - value: KR - label: - en_US: Korea - zh_Hans: 韩国 - pt_BR: Korea - - value: SE - label: - en_US: Sweden - zh_Hans: 瑞典 - pt_BR: Sweden - - value: SG - label: - en_US: Singapore - zh_Hans: 新加坡 - pt_BR: Singapore - - value: US - label: - en_US: United States - zh_Hans: 美国 - pt_BR: United States - - name: hl - type: select - label: - en_US: Language - zh_Hans: 语言 - human_description: - en_US: Defines the interface language of the search. Default is "en". - zh_Hans: 定义搜索的界面语言。默认为“en”。 - required: false - default: en - form: form - options: - - value: ar - label: - en_US: Arabic - zh_Hans: 阿拉伯语 - - value: bg - label: - en_US: Bulgarian - zh_Hans: 保加利亚语 - - value: ca - label: - en_US: Catalan - zh_Hans: 加泰罗尼亚语 - - value: zh-cn - label: - en_US: Chinese (Simplified) - zh_Hans: 中文（简体） - - value: zh-tw - label: - en_US: Chinese (Traditional) - zh_Hans: 中文（繁体） - - value: cs - label: - en_US: Czech - zh_Hans: 捷克语 - - value: da - label: - en_US: Danish - zh_Hans: 丹麦语 - - value: nl - label: - en_US: Dutch - zh_Hans: 荷兰语 - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: et - label: - en_US: Estonian - zh_Hans: 爱沙尼亚语 - - value: fi - label: - en_US: Finnish - zh_Hans: 芬兰语 - - value: fr - label: - en_US: French - zh_Hans: 法语 - - value: de - label: - en_US: German - zh_Hans: 德语 - - value: el - label: - en_US: Greek - zh_Hans: 希腊语 - - value: iw - label: - en_US: Hebrew - zh_Hans: 希伯来语 - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - - value: hu - label: - en_US: Hungarian - zh_Hans: 匈牙利语 - - value: id - label: - en_US: Indonesian - zh_Hans: 印尼语 - - value: it - label: - en_US: Italian - zh_Hans: 意大利语 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - - value: kn - label: - en_US: Kannada - zh_Hans: 卡纳达语 - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - - value: lv - label: - en_US: Latvian - zh_Hans: 拉脱维亚语 - - value: lt - label: - en_US: Lithuanian - zh_Hans: 立陶宛语 - - value: my - label: - en_US: Malay - zh_Hans: 马来语 - - value: ml - label: - en_US: Malayalam - zh_Hans: 马拉雅拉姆语 - - value: mr - label: - en_US: Marathi - zh_Hans: 马拉地语 - - value: "no" - label: - en_US: Norwegian - zh_Hans: 挪威语 - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - - value: pt-br - label: - en_US: Portuguese (Brazil) - zh_Hans: 葡萄牙语（巴西） - - value: pt-pt - label: - en_US: Portuguese (Portugal) - zh_Hans: 葡萄牙语（葡萄牙） - - value: pa - label: - en_US: Punjabi - zh_Hans: 旁遮普语 - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - - value: ru - label: - en_US: Russian - zh_Hans: 俄语 - - value: sr - label: - en_US: Serbian - zh_Hans: 塞尔维亚语 - - value: sk - label: - en_US: Slovak - zh_Hans: 斯洛伐克语 - - value: sl - label: - en_US: Slovenian - zh_Hans: 斯洛文尼亚语 - - value: es - label: - en_US: Spanish - zh_Hans: 西班牙语 - - value: sv - label: - en_US: Swedish - zh_Hans: 瑞典语 - - value: ta - label: - en_US: Tamil - zh_Hans: 泰米尔语 - - value: te - label: - en_US: Telugu - zh_Hans: 泰卢固语 - - value: th - label: - en_US: Thai - zh_Hans: 泰语 - - value: tr - label: - en_US: Turkish - zh_Hans: 土耳其语 - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 diff --git a/api/core/tools/provider/builtin/websearch/websearch.py b/api/core/tools/provider/builtin/websearch/websearch.py deleted file mode 100644 index 90cc0c573ac97e..00000000000000 --- a/api/core/tools/provider/builtin/websearch/websearch.py +++ /dev/null @@ -1,21 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.websearch.tools.web_search import WebSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class WebSearchAPIProvider(BuiltinToolProviderController): - # validate when saving the api_key - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - WebSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={"query": "what is llm"}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/websearch/websearch.yaml b/api/core/tools/provider/builtin/websearch/websearch.yaml deleted file mode 100644 index c4267e1022dfa1..00000000000000 --- a/api/core/tools/provider/builtin/websearch/websearch.yaml +++ /dev/null @@ -1,34 +0,0 @@ -identity: - name: websearch - author: Serply.io - label: - en_US: Serply.io - zh_Hans: Serply.io - pt_BR: Serply.io - description: - en_US: Serply.io is a robust real-time SERP API delivering structured data from a collection of search engines including Web Search, Jobs, News, and many more. - zh_Hans: Serply.io 是一个强大的实时 SERP API，可提供来自 搜索 招聘 新闻等搜索引擎集合的结构化数据。 - pt_BR: Serply.io is a robust real-time SERP API delivering structured data from a collection of search engines including Web Search, Jobs, News, and many more. - icon: icon.svg - tags: - - search - - business - - news - - productivity -credentials_for_provider: - serply_api_key: - type: secret-input - required: true - label: - en_US: Serply.io API key - zh_Hans: Serply.io API key - pt_BR: Serply.io API key - placeholder: - en_US: Please input your Serply.io API key - zh_Hans: 请输入你的 Serply.io API key - pt_BR: Please input your Serply.io API key - help: - en_US: Get your Serply.io API key from https://Serply.io/ - zh_Hans: 从 Serply.io 获取您的 Serply.io API key - pt_BR: Get your Serply.io API 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zaK8|{^HsxS1I>0}VE2aO?v4(_{@ToeD`dYX#39ts>bf{>o26%vDz3Zo<%{6=ZpMs& zQn_S}cS_`MhwPe4zTV%|qn!#EJn*eQ6*d>XVD154kiZbrAa;kkQ$rYHcSXJDx9OI9ObIN%JPldN{tqk*dsKtdaLh*KFs) jX&3#w=>?RVRhuHlX1xbR)vItE;Lj Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - content = tool_parameters.get("content", "") - if not content: - return self.create_text_message("Invalid parameter content") - - hook_key = tool_parameters.get("hook_key", "") - if not is_valid_uuid(hook_key): - return self.create_text_message(f"Invalid parameter hook_key ${hook_key}, not a valid UUID") - - message_type = tool_parameters.get("message_type", "text") - if message_type == "markdown": - payload = { - "msgtype": "markdown", - "markdown": { - "content": content, - }, - } - else: - payload = { - "msgtype": "text", - "text": { - "content": content, - }, - } - api_url = "https://qyapi.weixin.qq.com/cgi-bin/webhook/send" - headers = { - "Content-Type": "application/json", - } - params = { - "key": hook_key, - } - - try: - res = httpx.post(api_url, headers=headers, params=params, json=payload) - if res.is_success: - return self.create_text_message("Text message sent successfully") - else: - return self.create_text_message( - f"Failed to send the text message, status code: {res.status_code}, response: {res.text}" - ) - except Exception as e: - return self.create_text_message("Failed to send message to group chat bot. {}".format(e)) diff --git a/api/core/tools/provider/builtin/wecom/tools/wecom_group_bot.yaml b/api/core/tools/provider/builtin/wecom/tools/wecom_group_bot.yaml deleted file mode 100644 index 379005a1021420..00000000000000 --- a/api/core/tools/provider/builtin/wecom/tools/wecom_group_bot.yaml +++ /dev/null @@ -1,64 +0,0 @@ -identity: - name: wecom_group_bot - author: Bowen Liang - label: - en_US: Send Group Message - zh_Hans: 发送群消息 - pt_BR: Send Group Message - icon: icon.svg -description: - human: - en_US: Sending a group message on Wecom via the webhook of group bot - zh_Hans: 通过企业微信的群机器人webhook发送群消息 - pt_BR: Sending a group message on Wecom via the webhook of group bot - llm: A tool for sending messages to a chat group on Wecom(企业微信) . -parameters: - - name: hook_key - type: secret-input - required: true - label: - en_US: Wecom Group bot webhook key - zh_Hans: 群机器人webhook的key - pt_BR: Wecom Group bot webhook key - human_description: - en_US: Wecom Group bot webhook key - zh_Hans: 群机器人webhook的key - pt_BR: Wecom Group bot webhook key - form: form - - name: content - type: string - required: true - label: - en_US: content - zh_Hans: 消息内容 - pt_BR: content - human_description: - en_US: Content to sent to the group. - zh_Hans: 群消息文本 - pt_BR: Content to sent to the group. - llm_description: Content of the message - form: llm - - name: message_type - type: select - default: text - required: true - label: - en_US: Wecom Group bot message type - zh_Hans: 群机器人webhook的消息类型 - pt_BR: Wecom Group bot message type - human_description: - en_US: Wecom Group bot message type - zh_Hans: 群机器人webhook的消息类型 - pt_BR: Wecom Group bot message type - options: - - value: text - label: - en_US: Text - zh_Hans: 文本 - pt_BR: Text - - value: markdown - label: - en_US: Markdown - zh_Hans: Markdown - pt_BR: Markdown - form: form diff --git a/api/core/tools/provider/builtin/wecom/wecom.py b/api/core/tools/provider/builtin/wecom/wecom.py deleted file mode 100644 index 573f76ee56da67..00000000000000 --- a/api/core/tools/provider/builtin/wecom/wecom.py +++ /dev/null @@ -1,7 +0,0 @@ -from core.tools.provider.builtin.wecom.tools.wecom_group_bot import WecomGroupBotTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class WecomProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - WecomGroupBotTool() diff --git a/api/core/tools/provider/builtin/wecom/wecom.yaml b/api/core/tools/provider/builtin/wecom/wecom.yaml deleted file mode 100644 index a544055ba4cb67..00000000000000 --- a/api/core/tools/provider/builtin/wecom/wecom.yaml +++ /dev/null @@ -1,15 +0,0 @@ -identity: - author: Bowen Liang - name: wecom - label: - en_US: Wecom - zh_Hans: 企业微信 - pt_BR: Wecom - description: - en_US: Wecom group bot - zh_Hans: 企业微信群机器人 - pt_BR: Wecom group bot - icon: icon.png - tags: - - social -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/wikipedia/_assets/icon.svg b/api/core/tools/provider/builtin/wikipedia/_assets/icon.svg deleted file mode 100644 index fe652aacf9c871..00000000000000 --- a/api/core/tools/provider/builtin/wikipedia/_assets/icon.svg +++ /dev/null @@ -1,3 +0,0 @@ - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/wikipedia/tools/wikipedia_search.py b/api/core/tools/provider/builtin/wikipedia/tools/wikipedia_search.py deleted file mode 100644 index cb88e9519a4346..00000000000000 --- a/api/core/tools/provider/builtin/wikipedia/tools/wikipedia_search.py +++ /dev/null @@ -1,105 +0,0 @@ -from typing import Any, Optional, Union - -import wikipedia - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - -WIKIPEDIA_MAX_QUERY_LENGTH = 300 - - -class WikipediaAPIWrapper: - """Wrapper around WikipediaAPI. - - To use, you should have the ``wikipedia`` python package installed. - This wrapper will use the Wikipedia API to conduct searches and - fetch page summaries. By default, it will return the page summaries - of the top-k results. - It limits the Document content by doc_content_chars_max. - """ - - top_k_results: int = 3 - lang: str = "en" - load_all_available_meta: bool = False - doc_content_chars_max: int = 4000 - - def __init__(self, doc_content_chars_max: int = 4000): - self.doc_content_chars_max = doc_content_chars_max - - def run(self, query: str, lang: str = "") -> str: - if lang in wikipedia.languages(): - self.lang = lang - - wikipedia.set_lang(self.lang) - wiki_client = wikipedia - - """Run Wikipedia search and get page summaries.""" - page_titles = wiki_client.search(query[:WIKIPEDIA_MAX_QUERY_LENGTH]) - summaries = [] - for page_title in page_titles[: self.top_k_results]: - if wiki_page := self._fetch_page(page_title): - if summary := self._formatted_page_summary(page_title, wiki_page): - summaries.append(summary) - if not summaries: - return "No good Wikipedia Search Result was found" - return "\n\n".join(summaries)[: self.doc_content_chars_max] - - @staticmethod - def _formatted_page_summary(page_title: str, wiki_page: Any) -> Optional[str]: - return f"Page: {page_title}\nSummary: {wiki_page.summary}" - - def _fetch_page(self, page: str) -> Optional[str]: - try: - return wikipedia.page(title=page, auto_suggest=False) - except ( - wikipedia.exceptions.PageError, - wikipedia.exceptions.DisambiguationError, - ): - return None - - -class WikipediaQueryRun: - """Tool that searches the Wikipedia API.""" - - name = "Wikipedia" - description = ( - "A wrapper around Wikipedia. " - "Useful for when you need to answer general questions about " - "people, places, companies, facts, historical events, or other subjects. " - "Input should be a search query." - ) - api_wrapper: WikipediaAPIWrapper - - def __init__(self, api_wrapper: WikipediaAPIWrapper): - self.api_wrapper = api_wrapper - - def _run( - self, - query: str, - lang: str = "", - ) -> str: - """Use the Wikipedia tool.""" - return self.api_wrapper.run(query, lang) - - -class WikiPediaSearchTool(BuiltinTool): - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - query = tool_parameters.get("query", "") - lang = tool_parameters.get("language", "") - if not query: - return self.create_text_message("Please input query") - - tool = WikipediaQueryRun( - api_wrapper=WikipediaAPIWrapper(doc_content_chars_max=4000), - ) - - result = tool._run(query, lang) - - return self.create_text_message(self.summary(user_id=user_id, content=result)) diff --git a/api/core/tools/provider/builtin/wikipedia/tools/wikipedia_search.yaml b/api/core/tools/provider/builtin/wikipedia/tools/wikipedia_search.yaml deleted file mode 100644 index 98d002df1c0daa..00000000000000 --- a/api/core/tools/provider/builtin/wikipedia/tools/wikipedia_search.yaml +++ /dev/null @@ -1,101 +0,0 @@ -identity: - name: wikipedia_search - author: Dify - label: - en_US: WikipediaSearch - zh_Hans: 维基百科搜索 - pt_BR: WikipediaSearch - icon: icon.svg -description: - human: - en_US: A tool for performing a Wikipedia search and extracting snippets and webpages. - zh_Hans: 一个用于执行维基百科搜索并提取片段和网页的工具。 - pt_BR: A tool for performing a Wikipedia search and extracting snippets and webpages. - llm: A tool for performing a Wikipedia search and extracting snippets and webpages. Input should be a search query. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 查询语句 - pt_BR: Query string - human_description: - en_US: key words for searching - zh_Hans: 查询关键词 - pt_BR: key words for searching - llm_description: key words for searching, this should be in the language of "language" parameter - form: llm - - name: language - type: string - required: true - label: - en_US: Language - zh_Hans: 语言 - human_description: - en_US: The language of the Wikipedia to be searched - zh_Hans: 要搜索的维基百科语言 - llm_description: >- - language of the wikipedia to be searched, - only "de" for German, - "en" for English, - "fr" for French, - "hi" for Hindi, - "ja" for Japanese, - "ko" for Korean, - "pl" for Polish, - "pt" for Portuguese, - "ro" for Romanian, - "uk" for Ukrainian, - "vi" for Vietnamese, - and "zh" for Chinese are supported - form: llm - options: - - value: de - label: - en_US: German - zh_Hans: 德语 - - value: en - label: - en_US: English - zh_Hans: 英语 - - value: fr - label: - en_US: French - zh_Hans: 法语 - - value: hi - label: - en_US: Hindi - zh_Hans: 印地语 - - value: ja - label: - en_US: Japanese - zh_Hans: 日语 - - value: ko - label: - en_US: Korean - zh_Hans: 韩语 - - value: pl - label: - en_US: Polish - zh_Hans: 波兰语 - - value: pt - label: - en_US: Portuguese - zh_Hans: 葡萄牙语 - - value: ro - label: - en_US: Romanian - zh_Hans: 罗马尼亚语 - - value: uk - label: - en_US: Ukrainian - zh_Hans: 乌克兰语 - - value: vi - label: - en_US: Vietnamese - zh_Hans: 越南语 - - value: zh - label: - en_US: Chinese - zh_Hans: 中文 diff --git a/api/core/tools/provider/builtin/wikipedia/wikipedia.py b/api/core/tools/provider/builtin/wikipedia/wikipedia.py deleted file mode 100644 index 178bf7b0ceb2e9..00000000000000 --- a/api/core/tools/provider/builtin/wikipedia/wikipedia.py +++ /dev/null @@ -1,20 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.wikipedia.tools.wikipedia_search import WikiPediaSearchTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class WikiPediaProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - WikiPediaSearchTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "query": "misaka mikoto", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/wikipedia/wikipedia.yaml b/api/core/tools/provider/builtin/wikipedia/wikipedia.yaml deleted file mode 100644 index c5828240225d00..00000000000000 --- a/api/core/tools/provider/builtin/wikipedia/wikipedia.yaml +++ /dev/null @@ -1,15 +0,0 @@ -identity: - author: Dify - name: wikipedia - label: - en_US: Wikipedia - zh_Hans: 维基百科 - pt_BR: Wikipedia - description: - en_US: Wikipedia is a free online encyclopedia, created and edited by volunteers around the world. - zh_Hans: 维基百科是一个由全世界的志愿者创建和编辑的免费在线百科全书。 - pt_BR: Wikipedia is a free online encyclopedia, created and edited by volunteers around the world. - icon: icon.svg - tags: - - social -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/wolframalpha/_assets/icon.svg b/api/core/tools/provider/builtin/wolframalpha/_assets/icon.svg deleted file mode 100644 index 2caf32ee67be0a..00000000000000 --- a/api/core/tools/provider/builtin/wolframalpha/_assets/icon.svg +++ /dev/null @@ -1,23 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/wolframalpha/tools/wolframalpha.py b/api/core/tools/provider/builtin/wolframalpha/tools/wolframalpha.py deleted file mode 100644 index 9dc5bed824d715..00000000000000 --- a/api/core/tools/provider/builtin/wolframalpha/tools/wolframalpha.py +++ /dev/null @@ -1,72 +0,0 @@ -from typing import Any, Union - -from httpx import get - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.errors import ToolInvokeError, ToolProviderCredentialValidationError -from core.tools.tool.builtin_tool import BuiltinTool - - -class WolframAlphaTool(BuiltinTool): - _base_url = "https://api.wolframalpha.com/v2/query" - - def _invoke( - self, - user_id: str, - tool_parameters: dict[str, Any], - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - query = tool_parameters.get("query", "") - if not query: - return self.create_text_message("Please input query") - appid = self.runtime.credentials.get("appid", "") - if not appid: - raise ToolProviderCredentialValidationError("Please input appid") - - params = {"appid": appid, "input": query, "includepodid": "Result", "format": "plaintext", "output": "json"} - - finished = False - result = None - # try 3 times at most - counter = 0 - - while not finished and counter < 3: - counter += 1 - try: - response = get(self._base_url, params=params, timeout=20) - response.raise_for_status() - response_data = response.json() - except Exception as e: - raise ToolInvokeError(str(e)) - - if "success" not in response_data["queryresult"] or response_data["queryresult"]["success"] != True: - query_result = response_data.get("queryresult", {}) - if query_result.get("error"): - if "msg" in query_result["error"]: - if query_result["error"]["msg"] == "Invalid appid": - raise ToolProviderCredentialValidationError("Invalid appid") - raise ToolInvokeError("Failed to invoke tool") - - if "didyoumeans" in response_data["queryresult"]: - # get the most likely interpretation - query = "" - max_score = 0 - for didyoumean in response_data["queryresult"]["didyoumeans"]: - if float(didyoumean["score"]) > max_score: - query = didyoumean["val"] - max_score = float(didyoumean["score"]) - - params["input"] = query - else: - finished = True - if "souces" in response_data["queryresult"]: - return self.create_link_message(response_data["queryresult"]["sources"]["url"]) - elif "pods" in response_data["queryresult"]: - result = response_data["queryresult"]["pods"][0]["subpods"][0]["plaintext"] - - if not finished or not result: - return self.create_text_message("No result found") - - return self.create_text_message(result) diff --git a/api/core/tools/provider/builtin/wolframalpha/tools/wolframalpha.yaml b/api/core/tools/provider/builtin/wolframalpha/tools/wolframalpha.yaml deleted file mode 100644 index 08b5668691e23a..00000000000000 --- a/api/core/tools/provider/builtin/wolframalpha/tools/wolframalpha.yaml +++ /dev/null @@ -1,27 +0,0 @@ -identity: - name: wolframalpha - author: Dify - label: - en_US: WolframAlpha - zh_Hans: WolframAlpha - pt_BR: WolframAlpha -description: - human: - en_US: WolframAlpha is a powerful computational knowledge engine. - zh_Hans: WolframAlpha 是一个强大的计算知识引擎。 - pt_BR: WolframAlpha is a powerful computational knowledge engine. - llm: WolframAlpha is a powerful computational knowledge engine. one single query can get the answer of a question. -parameters: - - name: query - type: string - required: true - label: - en_US: Query string - zh_Hans: 计算语句 - pt_BR: Query string - human_description: - en_US: used for calculating - zh_Hans: 用于计算最终结果 - pt_BR: used for calculating - llm_description: a single query for calculating - form: llm diff --git a/api/core/tools/provider/builtin/wolframalpha/wolframalpha.py b/api/core/tools/provider/builtin/wolframalpha/wolframalpha.py deleted file mode 100644 index 7be288b5387f34..00000000000000 --- a/api/core/tools/provider/builtin/wolframalpha/wolframalpha.py +++ /dev/null @@ -1,22 +0,0 @@ -from typing import Any - -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.wolframalpha.tools.wolframalpha import WolframAlphaTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class GoogleProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - WolframAlphaTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "query": "1+2+....+111", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/wolframalpha/wolframalpha.yaml b/api/core/tools/provider/builtin/wolframalpha/wolframalpha.yaml deleted file mode 100644 index 91265eb3c00d0a..00000000000000 --- a/api/core/tools/provider/builtin/wolframalpha/wolframalpha.yaml +++ /dev/null @@ -1,32 +0,0 @@ -identity: - author: Dify - name: wolframalpha - label: - en_US: WolframAlpha - zh_Hans: WolframAlpha - pt_BR: WolframAlpha - description: - en_US: WolframAlpha is a powerful computational knowledge engine. - zh_Hans: WolframAlpha 是一个强大的计算知识引擎。 - pt_BR: WolframAlpha is a powerful computational knowledge engine. - icon: icon.svg - tags: - - productivity - - utilities -credentials_for_provider: - appid: - type: secret-input - required: true - label: - en_US: WolframAlpha AppID - zh_Hans: WolframAlpha AppID - pt_BR: WolframAlpha AppID - placeholder: - en_US: Please input your WolframAlpha AppID - zh_Hans: 请输入你的 WolframAlpha AppID - pt_BR: Please input your WolframAlpha AppID - help: - en_US: Get your WolframAlpha AppID from WolframAlpha, please use "full results" api access. - zh_Hans: 从 WolframAlpha 获取您的 WolframAlpha AppID，请使用 "full results" API。 - pt_BR: Get your WolframAlpha AppID from WolframAlpha, please use "full results" api access. - url: https://products.wolframalpha.com/api diff --git a/api/core/tools/provider/builtin/yahoo/_assets/icon.png b/api/core/tools/provider/builtin/yahoo/_assets/icon.png deleted file mode 100644 index 35d756f75410dbdf74ca14c8fba6e660e20b27d8..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 7647 zcmV<59U$U~P)@~0drDELIAGL9O(c600d`2O+f$vv5yPY47U@2jewnGN83KVCjEO!wE-RbTzTv#Yyj zfo-&nw$V1)M*m;Q!&cH|&7!ua0?h)L3V}(orzZJbThz%y`2Vtli;M_Z@>^(u!hPB{ 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z8SmcJ^D^@R>Y||L1u(Y`SO5uA1ZW7*`^9E^GooN!n&42xrk^Y+973-Je1f<~5QU0V^P+IZaDy`^u8dGI8ze32zrEX_N5(2AK(RL2!)UQy_rnzTApnkNVN% z41jxsAj(4?BQVCKPtw`ckqtARw Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - symbol = tool_parameters.get("symbol", "") - if not symbol: - return self.create_text_message("Please input symbol") - - time_range = [None, None] - start_date = tool_parameters.get("start_date", "") - if start_date: - time_range[0] = start_date - else: - time_range[0] = "1800-01-01" - - end_date = tool_parameters.get("end_date", "") - if end_date: - time_range[1] = end_date - else: - time_range[1] = datetime.now().strftime("%Y-%m-%d") - - stock_data = download(symbol, start=time_range[0], end=time_range[1]) - max_segments = min(15, len(stock_data)) - rows_per_segment = len(stock_data) // (max_segments or 1) - summary_data = [] - for i in range(max_segments): - start_idx = i * rows_per_segment - end_idx = (i + 1) * rows_per_segment if i < max_segments - 1 else len(stock_data) - segment_data = stock_data.iloc[start_idx:end_idx] - segment_summary = { - "Start Date": segment_data.index[0], - "End Date": segment_data.index[-1], - "Average Close": segment_data["Close"].mean(), - "Average Volume": segment_data["Volume"].mean(), - "Average Open": segment_data["Open"].mean(), - "Average High": segment_data["High"].mean(), - "Average Low": segment_data["Low"].mean(), - "Average Adj Close": segment_data["Adj Close"].mean(), - "Max Close": segment_data["Close"].max(), - "Min Close": segment_data["Close"].min(), - "Max Volume": segment_data["Volume"].max(), - "Min Volume": segment_data["Volume"].min(), - "Max Open": segment_data["Open"].max(), - "Min Open": segment_data["Open"].min(), - "Max High": segment_data["High"].max(), - "Min High": segment_data["High"].min(), - } - - summary_data.append(segment_summary) - - summary_df = pd.DataFrame(summary_data) - - try: - return self.create_text_message(str(summary_df.to_dict())) - except (HTTPError, ReadTimeout): - return self.create_text_message("There is a internet connection problem. Please try again later.") diff --git a/api/core/tools/provider/builtin/yahoo/tools/analytics.yaml b/api/core/tools/provider/builtin/yahoo/tools/analytics.yaml deleted file mode 100644 index 89e66fb5814908..00000000000000 --- a/api/core/tools/provider/builtin/yahoo/tools/analytics.yaml +++ /dev/null @@ -1,54 +0,0 @@ -identity: - name: yahoo_finance_analytics - author: Dify - label: - en_US: Analytics - zh_Hans: 分析 - pt_BR: Análises - icon: icon.svg -description: - human: - en_US: A tool for get analytics about a ticker from Yahoo Finance. - zh_Hans: 一个用于从雅虎财经获取分析数据的工具。 - pt_BR: Uma ferramenta para obter análises sobre um ticker do Yahoo Finance. - llm: A tool for get analytics from Yahoo Finance. Input should be the ticker symbol like AAPL. -parameters: - - name: symbol - type: string - required: true - label: - en_US: Ticker symbol - zh_Hans: 股票代码 - pt_BR: Símbolo do ticker - human_description: - en_US: The ticker symbol of the company you want to analyze. - zh_Hans: 你想要搜索的公司的股票代码。 - pt_BR: O símbolo do ticker da empresa que você deseja analisar. - llm_description: The ticker symbol of the company you want to analyze. - form: llm - - name: start_date - type: string - required: false - label: - en_US: Start date - zh_Hans: 开始日期 - pt_BR: Data de início - human_description: - en_US: The start date of the analytics. - zh_Hans: 分析的开始日期。 - pt_BR: A data de início das análises. - llm_description: The start date of the analytics, the format of the date must be YYYY-MM-DD like 2020-01-01. - form: llm - - name: end_date - type: string - required: false - label: - en_US: End date - zh_Hans: 结束日期 - pt_BR: Data de término - human_description: - en_US: The end date of the analytics. - zh_Hans: 分析的结束日期。 - pt_BR: A data de término das análises. - llm_description: The end date of the analytics, the format of the date must be YYYY-MM-DD like 2024-01-01. - form: llm diff --git a/api/core/tools/provider/builtin/yahoo/tools/news.py b/api/core/tools/provider/builtin/yahoo/tools/news.py deleted file mode 100644 index ff820430f9f366..00000000000000 --- a/api/core/tools/provider/builtin/yahoo/tools/news.py +++ /dev/null @@ -1,46 +0,0 @@ -from typing import Any, Union - -import yfinance -from requests.exceptions import HTTPError, ReadTimeout - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class YahooFinanceSearchTickerTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - - query = tool_parameters.get("symbol", "") - if not query: - return self.create_text_message("Please input symbol") - - try: - return self.run(ticker=query, user_id=user_id) - except (HTTPError, ReadTimeout): - return self.create_text_message("There is a internet connection problem. Please try again later.") - - def run(self, ticker: str, user_id: str) -> ToolInvokeMessage: - company = yfinance.Ticker(ticker) - try: - if company.isin is None: - return self.create_text_message(f"Company ticker {ticker} not found.") - except (HTTPError, ReadTimeout, ConnectionError): - return self.create_text_message(f"Company ticker {ticker} not found.") - - links = [] - try: - links = [n["link"] for n in company.news if n["type"] == "STORY"] - except (HTTPError, ReadTimeout, ConnectionError): - if not links: - return self.create_text_message(f"There is nothing about {ticker} ticker") - if not links: - return self.create_text_message(f"No news found for company that searched with {ticker} ticker.") - - result = "\n\n".join([self.get_url(link) for link in links]) - - return self.create_text_message(self.summary(user_id=user_id, content=result)) diff --git a/api/core/tools/provider/builtin/yahoo/tools/news.yaml b/api/core/tools/provider/builtin/yahoo/tools/news.yaml deleted file mode 100644 index 4118c1a82f280f..00000000000000 --- a/api/core/tools/provider/builtin/yahoo/tools/news.yaml +++ /dev/null @@ -1,28 +0,0 @@ -identity: - name: yahoo_finance_news - author: Dify - label: - en_US: News - zh_Hans: 新闻 - pt_BR: Notícias - icon: icon.svg -description: - human: - en_US: A tool for get news about a ticker from Yahoo Finance. - zh_Hans: 一个用于从雅虎财经获取新闻的工具。 - pt_BR: Uma ferramenta para obter notícias sobre um ticker da Yahoo Finance. - llm: A tool for get news from Yahoo Finance. Input should be the ticker symbol like AAPL. -parameters: - - name: symbol - type: string - required: true - label: - en_US: Ticker symbol - zh_Hans: 股票代码 - pt_BR: Símbolo do ticker - human_description: - en_US: The ticker symbol of the company you want to search. - zh_Hans: 你想要搜索的公司的股票代码。 - pt_BR: O símbolo do ticker da empresa que você deseja pesquisar. - llm_description: The ticker symbol of the company you want to search. - form: llm diff --git a/api/core/tools/provider/builtin/yahoo/tools/ticker.py b/api/core/tools/provider/builtin/yahoo/tools/ticker.py deleted file mode 100644 index dfc7e460473c33..00000000000000 --- a/api/core/tools/provider/builtin/yahoo/tools/ticker.py +++ /dev/null @@ -1,27 +0,0 @@ -from typing import Any, Union - -from requests.exceptions import HTTPError, ReadTimeout -from yfinance import Ticker - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class YahooFinanceSearchTickerTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - query = tool_parameters.get("symbol", "") - if not query: - return self.create_text_message("Please input symbol") - - try: - return self.create_text_message(self.run(ticker=query)) - except (HTTPError, ReadTimeout): - return self.create_text_message("There is a internet connection problem. Please try again later.") - - def run(self, ticker: str) -> str: - return str(Ticker(ticker).info) diff --git a/api/core/tools/provider/builtin/yahoo/tools/ticker.yaml b/api/core/tools/provider/builtin/yahoo/tools/ticker.yaml deleted file mode 100644 index 3c1ee9cf316be9..00000000000000 --- a/api/core/tools/provider/builtin/yahoo/tools/ticker.yaml +++ /dev/null @@ -1,28 +0,0 @@ -identity: - name: yahoo_finance_ticker - author: Dify - label: - en_US: Ticker - zh_Hans: 股票信息 - pt_BR: Ticker - icon: icon.svg -description: - human: - en_US: A tool for search ticker information from Yahoo Finance. - zh_Hans: 一个用于从雅虎财经搜索股票信息的工具。 - pt_BR: Uma ferramenta para buscar informações de ticker do Yahoo Finance. - llm: A tool for search ticker information from Yahoo Finance. Input should be the ticker symbol like AAPL. -parameters: - - name: symbol - type: string - required: true - label: - en_US: Ticker symbol - zh_Hans: 股票代码 - pt_BR: Símbolo do ticker - human_description: - en_US: The ticker symbol of the company you want to search. - zh_Hans: 你想要搜索的公司的股票代码。 - pt_BR: O símbolo do ticker da empresa que você deseja pesquisar. - llm_description: The ticker symbol of the company you want to search. - form: llm diff --git a/api/core/tools/provider/builtin/yahoo/yahoo.py b/api/core/tools/provider/builtin/yahoo/yahoo.py deleted file mode 100644 index 8d82084e769703..00000000000000 --- a/api/core/tools/provider/builtin/yahoo/yahoo.py +++ /dev/null @@ -1,20 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.yahoo.tools.ticker import YahooFinanceSearchTickerTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class YahooFinanceProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - YahooFinanceSearchTickerTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "ticker": "MSFT", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/yahoo/yahoo.yaml b/api/core/tools/provider/builtin/yahoo/yahoo.yaml deleted file mode 100644 index f1e82952c09ba4..00000000000000 --- a/api/core/tools/provider/builtin/yahoo/yahoo.yaml +++ /dev/null @@ -1,16 +0,0 @@ -identity: - author: Dify - name: yahoo - label: - en_US: YahooFinance - zh_Hans: 雅虎财经 - pt_BR: YahooFinance - description: - en_US: Finance, and Yahoo! get the latest news, stock quotes, and interactive chart with Yahoo! - zh_Hans: 雅虎财经，获取并整理出最新的新闻、股票报价等一切你想要的财经信息。 - pt_BR: Finance, and Yahoo! get the latest news, stock quotes, and interactive chart with Yahoo! - icon: icon.png - tags: - - business - - finance -credentials_for_provider: diff --git a/api/core/tools/provider/builtin/youtube/_assets/icon.svg b/api/core/tools/provider/builtin/youtube/_assets/icon.svg deleted file mode 100644 index 83b0700fecbf30..00000000000000 --- a/api/core/tools/provider/builtin/youtube/_assets/icon.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - - - - - \ No newline at end of file diff --git a/api/core/tools/provider/builtin/youtube/tools/videos.py b/api/core/tools/provider/builtin/youtube/tools/videos.py deleted file mode 100644 index 95dec2eac9a752..00000000000000 --- a/api/core/tools/provider/builtin/youtube/tools/videos.py +++ /dev/null @@ -1,74 +0,0 @@ -from datetime import datetime -from typing import Any, Union - -from googleapiclient.discovery import build - -from core.tools.entities.tool_entities import ToolInvokeMessage -from core.tools.tool.builtin_tool import BuiltinTool - - -class YoutubeVideosAnalyticsTool(BuiltinTool): - def _invoke( - self, user_id: str, tool_parameters: dict[str, Any] - ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: - """ - invoke tools - """ - channel = tool_parameters.get("channel", "") - if not channel: - return self.create_text_message("Please input symbol") - - time_range = [None, None] - start_date = tool_parameters.get("start_date", "") - if start_date: - time_range[0] = start_date - else: - time_range[0] = "1800-01-01" - - end_date = tool_parameters.get("end_date", "") - if end_date: - time_range[1] = end_date - else: - time_range[1] = datetime.now().strftime("%Y-%m-%d") - - if "google_api_key" not in self.runtime.credentials or not self.runtime.credentials["google_api_key"]: - return self.create_text_message("Please input api key") - - youtube = build("youtube", "v3", developerKey=self.runtime.credentials["google_api_key"]) - - # try to get channel id - search_results = youtube.search().list(q=channel, type="channel", order="relevance", part="id").execute() - channel_id = search_results["items"][0]["id"]["channelId"] - - start_date, end_date = time_range - - start_date = datetime.strptime(start_date, "%Y-%m-%d").strftime("%Y-%m-%dT%H:%M:%SZ") - end_date = datetime.strptime(end_date, "%Y-%m-%d").strftime("%Y-%m-%dT%H:%M:%SZ") - - # get videos - time_range_videos = ( - youtube.search() - .list( - part="snippet", - channelId=channel_id, - order="date", - type="video", - publishedAfter=start_date, - publishedBefore=end_date, - ) - .execute() - ) - - def extract_video_data(video_list): - data = [] - for video in video_list["items"]: - video_id = video["id"]["videoId"] - video_info = youtube.videos().list(part="snippet,statistics", id=video_id).execute() - title = video_info["items"][0]["snippet"]["title"] - views = video_info["items"][0]["statistics"]["viewCount"] - data.append({"Title": title, "Views": views}) - return data - - summary = extract_video_data(time_range_videos) - - return self.create_text_message(str(summary)) diff --git a/api/core/tools/provider/builtin/youtube/tools/videos.yaml b/api/core/tools/provider/builtin/youtube/tools/videos.yaml deleted file mode 100644 index 976699eb627910..00000000000000 --- a/api/core/tools/provider/builtin/youtube/tools/videos.yaml +++ /dev/null @@ -1,54 +0,0 @@ -identity: - name: youtube_video_statistics - author: Dify - label: - en_US: Video statistics - zh_Hans: 视频统计 - pt_BR: Estatísticas de vídeo - icon: icon.svg -description: - human: - en_US: A tool for get statistics about a channel's videos. - zh_Hans: 一个用于获取油管频道视频统计数据的工具。 - pt_BR: Uma ferramenta para obter estatísticas sobre os vídeos de um canal. - llm: A tool for get statistics about a channel's videos. Input should be the name of the channel like PewDiePie. -parameters: - - name: channel - type: string - required: true - label: - en_US: Channel name - zh_Hans: 频道名 - pt_BR: Nome do canal - human_description: - en_US: The name of the channel you want to search. - zh_Hans: 你想要搜索的油管频道名。 - pt_BR: O nome do canal que você deseja pesquisar. - llm_description: The name of the channel you want to search. - form: llm - - name: start_date - type: string - required: false - label: - en_US: Start date - zh_Hans: 开始日期 - pt_BR: Data de início - human_description: - en_US: The start date of the analytics. - zh_Hans: 分析的开始日期。 - pt_BR: A data de início da análise. - llm_description: The start date of the analytics, the format of the date must be YYYY-MM-DD like 2020-01-01. - form: llm - - name: end_date - type: string - required: false - label: - en_US: End date - zh_Hans: 结束日期 - pt_BR: Data de término - human_description: - en_US: The end date of the analytics. - zh_Hans: 分析的结束日期。 - pt_BR: A data de término da análise. - llm_description: The end date of the analytics, the format of the date must be YYYY-MM-DD like 2024-01-01. - form: llm diff --git a/api/core/tools/provider/builtin/youtube/youtube.py b/api/core/tools/provider/builtin/youtube/youtube.py deleted file mode 100644 index aad876491c85dc..00000000000000 --- a/api/core/tools/provider/builtin/youtube/youtube.py +++ /dev/null @@ -1,22 +0,0 @@ -from core.tools.errors import ToolProviderCredentialValidationError -from core.tools.provider.builtin.youtube.tools.videos import YoutubeVideosAnalyticsTool -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController - - -class YahooFinanceProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict) -> None: - try: - YoutubeVideosAnalyticsTool().fork_tool_runtime( - runtime={ - "credentials": credentials, - } - ).invoke( - user_id="", - tool_parameters={ - "channel": "TOKYO GIRLS COLLECTION", - "start_date": "2020-01-01", - "end_date": "2024-12-31", - }, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) diff --git a/api/core/tools/provider/builtin/youtube/youtube.yaml b/api/core/tools/provider/builtin/youtube/youtube.yaml deleted file mode 100644 index d6915b9a324767..00000000000000 --- a/api/core/tools/provider/builtin/youtube/youtube.yaml +++ /dev/null @@ -1,31 +0,0 @@ -identity: - author: Dify - name: youtube - label: - en_US: YouTube - zh_Hans: YouTube - pt_BR: YouTube - description: - en_US: YouTube - zh_Hans: YouTube（油管）是全球最大的视频分享网站，用户可以在上面上传、观看和分享视频。 - pt_BR: YouTube é o maior site de compartilhamento de vídeos do mundo, onde os usuários podem fazer upload, assistir e compartilhar vídeos. - icon: icon.svg - tags: - - videos -credentials_for_provider: - google_api_key: - type: secret-input - required: true - label: - en_US: Google API key - zh_Hans: Google API key - pt_BR: Chave da API do Google - placeholder: - en_US: Please input your Google API key - zh_Hans: 请输入你的 Google API key - pt_BR: Insira sua chave da API do Google - help: - en_US: Get your Google API key from Google - zh_Hans: 从 Google 获取您的 Google API key - pt_BR: Obtenha sua chave da API do Google no Google - url: https://console.developers.google.com/apis/credentials diff --git a/api/core/tools/tool_engine.py b/api/core/tools/tool_engine.py index 469eea67a6920d..cb2f6a899cd8e8 100644 --- a/api/core/tools/tool_engine.py +++ b/api/core/tools/tool_engine.py @@ -13,6 +13,7 @@ from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler from core.file.file_obj import FileTransferMethod from core.ops.ops_trace_manager import TraceQueueManager +from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ToolInvokeMessage, ToolInvokeMessageBinary, ToolInvokeMeta, ToolParameter from core.tools.errors import ( ToolEngineInvokeError, @@ -23,9 +24,8 @@ ToolProviderCredentialValidationError, ToolProviderNotFoundError, ) -from core.tools.tool.tool import Tool -from core.tools.tool.workflow_tool import WorkflowTool from core.tools.utils.message_transformer import ToolFileMessageTransformer +from core.tools.workflow_as_tool.tool import WorkflowTool from extensions.ext_database import db from models.model import Message, MessageFile diff --git a/api/core/tools/tool_label_manager.py b/api/core/tools/tool_label_manager.py index 2a5a2944ef8471..f9a126bf9bfc65 100644 --- a/api/core/tools/tool_label_manager.py +++ b/api/core/tools/tool_label_manager.py @@ -1,8 +1,8 @@ +from core.tools.__base.tool_provider import ToolProviderController +from core.tools.builtin_tool.provider import BuiltinToolProviderController +from core.tools.custom_tool.provider import ApiToolProviderController from core.tools.entities.values import default_tool_label_name_list -from core.tools.provider.api_tool_provider import ApiToolProviderController -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController -from core.tools.provider.tool_provider import ToolProviderController -from core.tools.provider.workflow_tool_provider import WorkflowToolProviderController +from core.tools.workflow_as_tool.provider import WorkflowToolProviderController from extensions.ext_database import db from models.tools import ToolLabelBinding @@ -55,7 +55,7 @@ def get_tool_labels(cls, controller: ToolProviderController) -> list[str]: else: raise ValueError("Unsupported tool type") - labels: list[ToolLabelBinding] = ( + labels = ( db.session.query(ToolLabelBinding.label_name) .filter( ToolLabelBinding.tool_id == provider_id, @@ -84,7 +84,10 @@ def get_tools_labels(cls, tool_providers: list[ToolProviderController]) -> dict[ if not isinstance(controller, ApiToolProviderController | WorkflowToolProviderController): raise ValueError("Unsupported tool type") - provider_ids = [controller.provider_id for controller in tool_providers] + provider_ids = [] + for controller in tool_providers: + assert isinstance(controller, ApiToolProviderController | WorkflowToolProviderController) + provider_ids.append(controller.provider_id) labels: list[ToolLabelBinding] = ( db.session.query(ToolLabelBinding).filter(ToolLabelBinding.tool_id.in_(provider_ids)).all() diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 108b74018daf07..0cfcb6d9b9dbaf 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -4,7 +4,11 @@ from collections.abc import Generator from os import listdir, path from threading import Lock -from typing import Any, Union, cast +from typing import TYPE_CHECKING, Any, Union, cast + +if TYPE_CHECKING: + from core.workflow.nodes.tool.entities import ToolEntity + from configs import dify_config from core.agent.entities import AgentToolEntity @@ -12,20 +16,20 @@ from core.helper.module_import_helper import load_single_subclass_from_source from core.helper.position_helper import is_filtered from core.model_runtime.utils.encoders import jsonable_encoder +from core.tools.__base.tool import Tool +from core.tools.builtin_tool.provider import BuiltinToolProviderController +from core.tools.builtin_tool.providers._positions import BuiltinToolProviderSort +from core.tools.builtin_tool.tool import BuiltinTool +from core.tools.custom_tool.provider import ApiToolProviderController +from core.tools.custom_tool.tool import ApiTool from core.tools.entities.api_entities import UserToolProvider, UserToolProviderTypeLiteral from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ApiProviderAuthType, ToolInvokeFrom, ToolParameter, ToolProviderType from core.tools.errors import ToolProviderNotFoundError -from core.tools.provider.api_tool_provider import ApiToolProviderController -from core.tools.provider.builtin._positions import BuiltinToolProviderSort -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController -from core.tools.tool.api_tool import ApiTool -from core.tools.tool.builtin_tool import BuiltinTool -from core.tools.tool.tool import Tool -from core.tools.tool.workflow_tool import WorkflowTool from core.tools.tool_label_manager import ToolLabelManager from core.tools.utils.configuration import ProviderConfigEncrypter, ToolParameterConfigurationManager from core.tools.utils.tool_parameter_converter import ToolParameterConverter +from core.tools.workflow_as_tool.tool import WorkflowTool from extensions.ext_database import db from models.tools import ApiToolProvider, BuiltinToolProvider, WorkflowToolProvider from services.tools.tools_transform_service import ToolTransformService @@ -328,8 +332,8 @@ def get_builtin_provider_icon(cls, provider: str) -> tuple[str, str]: absolute_path = path.join( path.dirname(path.realpath(__file__)), - "provider", - "builtin", + "builtin_tool", + "providers", provider, "_assets", provider_controller.identity.icon, @@ -363,22 +367,22 @@ def _list_builtin_providers(cls) -> Generator[BuiltinToolProviderController, Non """ list all the builtin providers """ - for provider_path in listdir(path.join(path.dirname(path.realpath(__file__)), "provider", "builtin")): + for provider_path in listdir(path.join(path.dirname(path.realpath(__file__)), "builtin_tool", "providers")): if provider_path.startswith("__"): continue - if path.isdir(path.join(path.dirname(path.realpath(__file__)), "provider", "builtin", provider_path)): + if path.isdir(path.join(path.dirname(path.realpath(__file__)), "builtin_tool", "providers", provider_path)): if provider_path.startswith("__"): continue # init provider try: provider_class = load_single_subclass_from_source( - module_name=f"core.tools.provider.builtin.{provider_path}.{provider_path}", + module_name=f"core.tools.builtin_tool.providers.{provider_path}.{provider_path}", script_path=path.join( path.dirname(path.realpath(__file__)), - "provider", - "builtin", + "builtin_tool", + "providers", provider_path, f"{provider_path}.py", ), @@ -391,7 +395,7 @@ def _list_builtin_providers(cls) -> Generator[BuiltinToolProviderController, Non yield provider except Exception as e: - logger.error(f"load builtin provider {provider} error: {e}") + logger.error(f"load builtin provider error: {e}") continue # set builtin providers loaded cls._builtin_providers_loaded = True diff --git a/api/core/tools/utils/configuration.py b/api/core/tools/utils/configuration.py index f3fce03f8cee2f..0ab2b0021a36dd 100644 --- a/api/core/tools/utils/configuration.py +++ b/api/core/tools/utils/configuration.py @@ -8,11 +8,11 @@ from core.helper import encrypter from core.helper.tool_parameter_cache import ToolParameterCache, ToolParameterCacheType from core.helper.tool_provider_cache import ToolProviderCredentialsCache, ToolProviderCredentialsCacheType +from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ( ToolParameter, ToolProviderType, ) -from core.tools.tool.tool import Tool class ProviderConfigEncrypter(BaseModel): @@ -27,7 +27,7 @@ def _deep_copy(self, data: dict[str, str]) -> dict[str, str]: """ return deepcopy(data) - def encrypt(self, data: dict[str, str]) -> Mapping[str, str]: + def encrypt(self, data: dict[str, str]) -> dict[str, str]: """ encrypt tool credentials with tenant id @@ -45,7 +45,7 @@ def encrypt(self, data: dict[str, str]) -> Mapping[str, str]: return data - def mask_tool_credentials(self, data: dict[str, Any]) -> Mapping[str, Any]: + def mask_tool_credentials(self, data: dict[str, Any]) -> dict[str, Any]: """ mask tool credentials @@ -68,7 +68,7 @@ def mask_tool_credentials(self, data: dict[str, Any]) -> Mapping[str, Any]: return data - def decrypt(self, data: dict[str, str]) -> Mapping[str, str]: + def decrypt(self, data: dict[str, str]) -> dict[str, str]: """ decrypt tool credentials with tenant id diff --git a/api/core/tools/tool/dataset_retriever/dataset_multi_retriever_tool.py b/api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py similarity index 98% rename from api/core/tools/tool/dataset_retriever/dataset_multi_retriever_tool.py rename to api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py index ab7b40a2536db8..408dd43d228814 100644 --- a/api/core/tools/tool/dataset_retriever/dataset_multi_retriever_tool.py +++ b/api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py @@ -9,7 +9,7 @@ from core.rag.datasource.retrieval_service import RetrievalService from core.rag.rerank.rerank_model import RerankModelRunner from core.rag.retrieval.retrieval_methods import RetrievalMethod -from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool +from core.tools.utils.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool from extensions.ext_database import db from models.dataset import Dataset, Document, DocumentSegment diff --git a/api/core/tools/tool/dataset_retriever/dataset_retriever_base_tool.py b/api/core/tools/utils/dataset_retriever/dataset_retriever_base_tool.py similarity index 100% rename from api/core/tools/tool/dataset_retriever/dataset_retriever_base_tool.py rename to api/core/tools/utils/dataset_retriever/dataset_retriever_base_tool.py diff --git a/api/core/tools/tool/dataset_retriever/dataset_retriever_tool.py b/api/core/tools/utils/dataset_retriever/dataset_retriever_tool.py similarity index 100% rename from api/core/tools/tool/dataset_retriever/dataset_retriever_tool.py rename to api/core/tools/utils/dataset_retriever/dataset_retriever_tool.py diff --git a/api/core/tools/tool/dataset_retriever_tool.py b/api/core/tools/utils/dataset_retriever_tool.py similarity index 96% rename from api/core/tools/tool/dataset_retriever_tool.py rename to api/core/tools/utils/dataset_retriever_tool.py index 9f41b5d5eb2fe9..7b612227227dc4 100644 --- a/api/core/tools/tool/dataset_retriever_tool.py +++ b/api/core/tools/utils/dataset_retriever_tool.py @@ -5,6 +5,7 @@ from core.app.entities.app_invoke_entities import InvokeFrom from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler from core.rag.retrieval.dataset_retrieval import DatasetRetrieval +from core.tools.__base.tool import Tool from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ( ToolDescription, @@ -13,8 +14,7 @@ ToolParameter, ToolProviderType, ) -from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool -from core.tools.tool.tool import Tool +from core.tools.utils.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool class DatasetRetrieverTool(Tool): diff --git a/api/core/tools/utils/web_reader_tool.py b/api/core/tools/utils/web_reader_tool.py index 1ced7d0488e3f2..dcbae9f5aa2260 100644 --- a/api/core/tools/utils/web_reader_tool.py +++ b/api/core/tools/utils/web_reader_tool.py @@ -36,7 +36,7 @@ def page_result(text: str, cursor: int, max_length: int) -> str: return text[cursor : cursor + max_length] -def get_url(url: str, user_agent: str = None) -> str: +def get_url(url: str, user_agent: str | None = None) -> str: """Fetch URL and return the contents as a string.""" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)" diff --git a/api/core/tools/workflow_as_tool/provider.py b/api/core/tools/workflow_as_tool/provider.py new file mode 100644 index 00000000000000..cab5f84506d1c0 --- /dev/null +++ b/api/core/tools/workflow_as_tool/provider.py @@ -0,0 +1,207 @@ +from collections.abc import Mapping +from typing import Optional + +from pydantic import Field + +from core.app.app_config.entities import VariableEntity, VariableEntityType +from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager +from core.tools.__base.tool_provider import ToolProviderController +from core.tools.entities.common_entities import I18nObject +from core.tools.entities.tool_entities import ( + ToolDescription, + ToolIdentity, + ToolParameter, + ToolParameterOption, + ToolProviderType, +) +from core.tools.utils.workflow_configuration_sync import WorkflowToolConfigurationUtils +from core.tools.workflow_as_tool.tool import WorkflowTool +from extensions.ext_database import db +from models.model import App, AppMode +from models.tools import WorkflowToolProvider +from models.workflow import Workflow + +VARIABLE_TO_PARAMETER_TYPE_MAPPING = { + VariableEntityType.TEXT_INPUT: ToolParameter.ToolParameterType.STRING, + VariableEntityType.PARAGRAPH: ToolParameter.ToolParameterType.STRING, + VariableEntityType.SELECT: ToolParameter.ToolParameterType.SELECT, + VariableEntityType.NUMBER: ToolParameter.ToolParameterType.NUMBER, +} + + +class WorkflowToolProviderController(ToolProviderController): + provider_id: str + tools: list[WorkflowTool] = Field(default_factory=list) + + @classmethod + def from_db(cls, db_provider: WorkflowToolProvider) -> "WorkflowToolProviderController": + app = db_provider.app + + if not app: + raise ValueError("app not found") + + controller = WorkflowToolProviderController( + **{ + "identity": { + "author": db_provider.user.name if db_provider.user_id and db_provider.user else "", + "name": db_provider.label, + "label": {"en_US": db_provider.label, "zh_Hans": db_provider.label}, + "description": {"en_US": db_provider.description, "zh_Hans": db_provider.description}, + "icon": db_provider.icon, + }, + "credentials_schema": {}, + "provider_id": db_provider.id or "", + } + ) + + # init tools + + controller.tools = [controller._get_db_provider_tool(db_provider, app)] + + return controller + + @property + def provider_type(self) -> ToolProviderType: + return ToolProviderType.WORKFLOW + + def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> WorkflowTool: + """ + get db provider tool + :param db_provider: the db provider + :param app: the app + :return: the tool + """ + workflow: Workflow | None = db.session.query(Workflow).filter( + Workflow.app_id == db_provider.app_id, + Workflow.version == db_provider.version + ).first() + + if not workflow: + raise ValueError("workflow not found") + + # fetch start node + graph: Mapping = workflow.graph_dict + features_dict: Mapping = workflow.features_dict + features = WorkflowAppConfigManager.convert_features( + config_dict=features_dict, + app_mode=AppMode.WORKFLOW + ) + + parameters = db_provider.parameter_configurations + variables = WorkflowToolConfigurationUtils.get_workflow_graph_variables(graph) + + def fetch_workflow_variable(variable_name: str) -> VariableEntity | None: + return next(filter(lambda x: x.variable == variable_name, variables), None) + + user = db_provider.user + + workflow_tool_parameters = [] + for parameter in parameters: + variable = fetch_workflow_variable(parameter.name) + if variable: + parameter_type = None + options = [] + if variable.type not in VARIABLE_TO_PARAMETER_TYPE_MAPPING: + raise ValueError(f"unsupported variable type {variable.type}") + parameter_type = VARIABLE_TO_PARAMETER_TYPE_MAPPING[variable.type] + + if variable.type == VariableEntityType.SELECT and variable.options: + options = [ + ToolParameterOption(value=option, label=I18nObject(en_US=option, zh_Hans=option)) + for option in variable.options + ] + + workflow_tool_parameters.append( + ToolParameter( + name=parameter.name, + label=I18nObject(en_US=variable.label, zh_Hans=variable.label), + human_description=I18nObject(en_US=parameter.description, zh_Hans=parameter.description), + type=parameter_type, + form=parameter.form, + llm_description=parameter.description, + required=variable.required, + options=options, + default=variable.default, + ) + ) + elif features.file_upload: + workflow_tool_parameters.append( + ToolParameter( + name=parameter.name, + label=I18nObject(en_US=parameter.name, zh_Hans=parameter.name), + human_description=I18nObject(en_US=parameter.description, zh_Hans=parameter.description), + type=ToolParameter.ToolParameterType.FILE, + llm_description=parameter.description, + required=False, + form=parameter.form, + ) + ) + else: + raise ValueError("variable not found") + + return WorkflowTool( + identity=ToolIdentity( + author=user.name if user else "", + name=db_provider.name, + label=I18nObject(en_US=db_provider.label, zh_Hans=db_provider.label), + provider=self.provider_id, + icon=db_provider.icon, + ), + description=ToolDescription( + human=I18nObject(en_US=db_provider.description, zh_Hans=db_provider.description), + llm=db_provider.description, + ), + parameters=workflow_tool_parameters, + is_team_authorization=True, + workflow_app_id=app.id, + workflow_entities={ + "app": app, + "workflow": workflow, + }, + version=db_provider.version, + workflow_call_depth=0, + label=db_provider.label, + ) + + def get_tools(self, tenant_id: str) -> list[WorkflowTool]: + """ + fetch tools from database + + :param user_id: the user id + :param tenant_id: the tenant id + :return: the tools + """ + if self.tools is not None: + return self.tools + + db_providers: WorkflowToolProvider | None = db.session.query(WorkflowToolProvider).filter( + WorkflowToolProvider.tenant_id == tenant_id, + WorkflowToolProvider.app_id == self.provider_id, + ).first() + + if not db_providers: + return [] + + app = db_providers.app + if not app: + raise ValueError("can not read app of workflow") + + self.tools = [self._get_db_provider_tool(db_providers, app)] + + return self.tools + + def get_tool(self, tool_name: str) -> Optional[WorkflowTool]: + """ + get tool by name + + :param tool_name: the name of the tool + :return: the tool + """ + if self.tools is None: + return None + + for tool in self.tools: + if tool.identity.name == tool_name: + return tool + + return None diff --git a/api/core/tools/tool/workflow_tool.py b/api/core/tools/workflow_as_tool/tool.py similarity index 99% rename from api/core/tools/tool/workflow_tool.py rename to api/core/tools/workflow_as_tool/tool.py index 42ceffb834ee83..72aae2796c893b 100644 --- a/api/core/tools/tool/workflow_tool.py +++ b/api/core/tools/workflow_as_tool/tool.py @@ -5,8 +5,8 @@ from typing import Any, Optional, Union from core.file.file_obj import FileTransferMethod, FileVar +from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter, ToolProviderType -from core.tools.tool.tool import Tool from extensions.ext_database import db from models.account import Account from models.model import App, EndUser diff --git a/api/core/tools/provider/workflow_tool_provider.py b/api/core/tools/workflow_as_tool/workflow_tool_provider.py similarity index 98% rename from api/core/tools/provider/workflow_tool_provider.py rename to api/core/tools/workflow_as_tool/workflow_tool_provider.py index 6f80767bd55b7d..cab5f84506d1c0 100644 --- a/api/core/tools/provider/workflow_tool_provider.py +++ b/api/core/tools/workflow_as_tool/workflow_tool_provider.py @@ -5,6 +5,7 @@ from core.app.app_config.entities import VariableEntity, VariableEntityType from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager +from core.tools.__base.tool_provider import ToolProviderController from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ( ToolDescription, @@ -13,9 +14,8 @@ ToolParameterOption, ToolProviderType, ) -from core.tools.provider.tool_provider import ToolProviderController -from core.tools.tool.workflow_tool import WorkflowTool from core.tools.utils.workflow_configuration_sync import WorkflowToolConfigurationUtils +from core.tools.workflow_as_tool.tool import WorkflowTool from extensions.ext_database import db from models.model import App, AppMode from models.tools import WorkflowToolProvider diff --git a/api/services/tools/api_tools_manage_service.py b/api/services/tools/api_tools_manage_service.py index e1962305b92c12..11aa3ba529f605 100644 --- a/api/services/tools/api_tools_manage_service.py +++ b/api/services/tools/api_tools_manage_service.py @@ -5,6 +5,7 @@ from core.entities.provider_entities import ProviderConfig from core.model_runtime.utils.encoders import jsonable_encoder +from core.tools.custom_tool.provider import ApiToolProviderController from core.tools.entities.api_entities import UserTool, UserToolProvider from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle @@ -12,7 +13,6 @@ ApiProviderAuthType, ApiProviderSchemaType, ) -from core.tools.provider.api_tool_provider import ApiToolProviderController from core.tools.tool_label_manager import ToolLabelManager from core.tools.tool_manager import ToolManager from core.tools.utils.configuration import ProviderConfigEncrypter diff --git a/api/services/tools/builtin_tools_manage_service.py b/api/services/tools/builtin_tools_manage_service.py index af1cdbacac3450..6db8718b6b46c0 100644 --- a/api/services/tools/builtin_tools_manage_service.py +++ b/api/services/tools/builtin_tools_manage_service.py @@ -5,10 +5,10 @@ from configs import dify_config from core.helper.position_helper import is_filtered from core.model_runtime.utils.encoders import jsonable_encoder +from core.tools.__base.tool_provider import ToolProviderController +from core.tools.builtin_tool.providers._positions import BuiltinToolProviderSort from core.tools.entities.api_entities import UserTool, UserToolProvider from core.tools.errors import ToolNotFoundError, ToolProviderCredentialValidationError, ToolProviderNotFoundError -from core.tools.provider.builtin._positions import BuiltinToolProviderSort -from core.tools.provider.tool_provider import ToolProviderController from core.tools.tool_label_manager import ToolLabelManager from core.tools.tool_manager import ToolManager from core.tools.utils.configuration import ProviderConfigEncrypter diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index 552e2a0fbc7585..b7488621c643cb 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -3,6 +3,9 @@ from typing import Optional, Union from configs import dify_config +from core.tools.__base.tool import Tool +from core.tools.builtin_tool.provider import BuiltinToolProviderController +from core.tools.custom_tool.provider import ApiToolProviderController from core.tools.entities.api_entities import UserTool, UserToolProvider from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle @@ -11,12 +14,9 @@ ToolParameter, ToolProviderType, ) -from core.tools.provider.api_tool_provider import ApiToolProviderController -from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController -from core.tools.provider.workflow_tool_provider import WorkflowToolProviderController -from core.tools.tool.tool import Tool -from core.tools.tool.workflow_tool import WorkflowTool from core.tools.utils.configuration import ProviderConfigEncrypter +from core.tools.workflow_as_tool.provider import WorkflowToolProviderController +from core.tools.workflow_as_tool.tool import WorkflowTool from models.tools import ApiToolProvider, BuiltinToolProvider, WorkflowToolProvider logger = logging.getLogger(__name__) diff --git a/api/services/tools/workflow_tools_manage_service.py b/api/services/tools/workflow_tools_manage_service.py index 1544b39c23571e..60e26aa28281ec 100644 --- a/api/services/tools/workflow_tools_manage_service.py +++ b/api/services/tools/workflow_tools_manage_service.py @@ -5,9 +5,9 @@ from core.model_runtime.utils.encoders import jsonable_encoder from core.tools.entities.api_entities import UserTool, UserToolProvider -from core.tools.provider.workflow_tool_provider import WorkflowToolProviderController from core.tools.tool_label_manager import ToolLabelManager from core.tools.utils.workflow_configuration_sync import WorkflowToolConfigurationUtils +from core.tools.workflow_as_tool.provider import WorkflowToolProviderController from extensions.ext_database import db from models.model import App from models.tools import WorkflowToolProvider diff --git a/api/tests/integration_tests/tools/api_tool/test_api_tool.py b/api/tests/integration_tests/tools/api_tool/test_api_tool.py index 09729a961eff33..e4798e02c38148 100644 --- a/api/tests/integration_tests/tools/api_tool/test_api_tool.py +++ b/api/tests/integration_tests/tools/api_tool/test_api_tool.py @@ -1,5 +1,5 @@ -from core.tools.tool.api_tool import ApiTool -from core.tools.tool.tool import Tool +from core.tools.__base.tool import Tool +from core.tools.custom_tool.tool import ApiTool from tests.integration_tests.tools.__mock.http import setup_http_mock tool_bundle = { From 73ce692e24153f76652e306711ea3af6b3691cf4 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 20 Sep 2024 13:32:11 +0800 Subject: [PATCH 033/325] feat: add inner api key --- api/.env.example | 9 +++++---- api/configs/feature/__init__.py | 17 +++++++++++------ api/controllers/inner_api/wraps.py | 10 +++++----- .../dataset_multi_retriever_tool.py | 7 +++++-- 4 files changed, 26 insertions(+), 17 deletions(-) diff --git a/api/.env.example b/api/.env.example index 21940402f4561e..3cff88c400f05e 100644 --- a/api/.env.example +++ b/api/.env.example @@ -278,10 +278,6 @@ WORKFLOW_CALL_MAX_DEPTH=5 APP_MAX_EXECUTION_TIME=1200 APP_MAX_ACTIVE_REQUESTS=0 -# Plugin configuration -PLUGIN_INNER_API_URL=http://127.0.0.1:5002 -PLUGIN_INNER_API_KEY=lYkiYYT6owG+71oLerGzA7GXCgOT++6ovaezWAjpCjf+Sjc3ZtU+qUEi - # Celery beat configuration CELERY_BEAT_SCHEDULER_TIME=1 @@ -293,3 +289,8 @@ POSITION_TOOL_EXCLUDES= POSITION_PROVIDER_PINS= POSITION_PROVIDER_INCLUDES= POSITION_PROVIDER_EXCLUDES= + +# Plugin configuration +PLUGIN_API_KEY=lYkiYYT6owG+71oLerGzA7GXCgOT++6ovaezWAjpCjf+Sjc3ZtU+qUEi+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1 +PLUGIN_API_URL=http://127.0.0.1:5002 +INNER_API_KEY=QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1 \ No newline at end of file diff --git a/api/configs/feature/__init__.py b/api/configs/feature/__init__.py index 4e1dfe73ad0787..30b97749ee9454 100644 --- a/api/configs/feature/__init__.py +++ b/api/configs/feature/__init__.py @@ -115,14 +115,19 @@ class PluginConfig(BaseSettings): """ Plugin configs """ - PLUGIN_INNER_API_URL: str = Field( - description='Plugin inner API URL', - default='http://plugin:8194', + PLUGIN_API_URL: str = Field( + description='Plugin API URL', + default='http://plugin:5002', ) - PLUGIN_INNER_API_KEY: str = Field( - description='Plugin inner API key', - default='dify-inner-api-key', + PLUGIN_API_KEY: str = Field( + description='Plugin API key', + default='plugin-api-key', + ) + + INNER_API_KEY_FOR_PLUGIN: str = Field( + description='Inner api key for plugin', + default='inner-api-key' ) diff --git a/api/controllers/inner_api/wraps.py b/api/controllers/inner_api/wraps.py index 3e184515d3a796..b543b5e1641f50 100644 --- a/api/controllers/inner_api/wraps.py +++ b/api/controllers/inner_api/wraps.py @@ -18,7 +18,7 @@ def decorated(*args, **kwargs): # get header 'X-Inner-Api-Key' inner_api_key = request.headers.get("X-Inner-Api-Key") - if not inner_api_key or inner_api_key != dify_config.INNER_API_KEY: + if not inner_api_key or inner_api_key != dify_config.INNER_API_KEY_FOR_PLUGIN: abort(401) return view(*args, **kwargs) @@ -67,14 +67,14 @@ def decorated(*args, **kwargs): def plugin_inner_api_only(view): @wraps(view) def decorated(*args, **kwargs): - if not dify_config.PLUGIN_INNER_API_KEY: + if not dify_config.PLUGIN_API_KEY: abort(404) # get header 'X-Inner-Api-Key' - inner_api_key = request.headers.get('X-Inner-Api-Key') - if not inner_api_key or inner_api_key != dify_config.PLUGIN_INNER_API_KEY: + inner_api_key = request.headers.get("X-Inner-Api-Key") + if not inner_api_key or inner_api_key != dify_config.INNER_API_KEY_FOR_PLUGIN: abort(404) return view(*args, **kwargs) - return decorated \ No newline at end of file + return decorated diff --git a/api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py b/api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py index 408dd43d228814..d3a8752d9ae37a 100644 --- a/api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py +++ b/api/core/tools/utils/dataset_retriever/dataset_multi_retriever_tool.py @@ -49,7 +49,7 @@ def _run(self, query: str) -> str: retrieval_thread = threading.Thread( target=self._retriever, kwargs={ - "flask_app": current_app._get_current_object(), + "flask_app": current_app._get_current_object(), # type: ignore "dataset_id": dataset_id, "query": query, "all_documents": all_documents, @@ -77,11 +77,12 @@ def _run(self, query: str) -> str: document_score_list = {} for item in all_documents: + assert item.metadata if item.metadata.get("score"): document_score_list[item.metadata["doc_id"]] = item.metadata["score"] document_context_list = [] - index_node_ids = [document.metadata["doc_id"] for document in all_documents] + index_node_ids = [document.metadata["doc_id"] for document in all_documents if document.metadata] segments = DocumentSegment.query.filter( DocumentSegment.dataset_id.in_(self.dataset_ids), DocumentSegment.completed_at.isnot(None), @@ -140,6 +141,8 @@ def _run(self, query: str) -> str: return str("\n".join(document_context_list)) + raise RuntimeError("not segments found") + def _retriever( self, flask_app: Flask, From d4bf575d0a87641bc64e0ab6eccfdcb8f9323d41 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 20 Sep 2024 13:55:09 +0800 Subject: [PATCH 034/325] impl: basic plugin manager --- api/configs/feature/__init__.py | 2 +- api/core/plugin/manager/asset.py | 5 +++ api/core/plugin/manager/base.py | 48 +++++++++++++++++++++++++++++ api/core/plugin/manager/endpoint.py | 5 +++ api/core/plugin/manager/model.py | 5 +++ api/core/plugin/manager/tool.py | 5 +++ 6 files changed, 69 insertions(+), 1 deletion(-) create mode 100644 api/core/plugin/manager/asset.py create mode 100644 api/core/plugin/manager/base.py create mode 100644 api/core/plugin/manager/endpoint.py create mode 100644 api/core/plugin/manager/model.py create mode 100644 api/core/plugin/manager/tool.py diff --git a/api/configs/feature/__init__.py b/api/configs/feature/__init__.py index 30b97749ee9454..660ca5a2a07eca 100644 --- a/api/configs/feature/__init__.py +++ b/api/configs/feature/__init__.py @@ -115,7 +115,7 @@ class PluginConfig(BaseSettings): """ Plugin configs """ - PLUGIN_API_URL: str = Field( + PLUGIN_API_URL: HttpUrl = Field( description='Plugin API URL', default='http://plugin:5002', ) diff --git a/api/core/plugin/manager/asset.py b/api/core/plugin/manager/asset.py new file mode 100644 index 00000000000000..f55ff748cace84 --- /dev/null +++ b/api/core/plugin/manager/asset.py @@ -0,0 +1,5 @@ +from core.plugin.manager.base import BasePluginManager + + +class PluginAssetManager(BasePluginManager): + pass \ No newline at end of file diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py new file mode 100644 index 00000000000000..5f1e5cd1d2bf66 --- /dev/null +++ b/api/core/plugin/manager/base.py @@ -0,0 +1,48 @@ +import json +from collections.abc import Generator +from typing import TypeVar + +import requests +from pydantic import BaseModel +from yarl import URL + +from configs import dify_config + +plugin_daemon_inner_api_baseurl = dify_config.PLUGIN_API_URL +plugin_daemon_inner_api_key = dify_config.INNER_API_KEY_FOR_PLUGIN + +T = TypeVar("T", bound=(BaseModel | dict)) + + +class BasePluginManager: + def _request(self, method: str, path: str, headers: dict, data: bytes, stream: bool = False) -> requests.Response: + """ + Make a request to the plugin daemon inner API. + """ + url = URL(str(plugin_daemon_inner_api_baseurl)) / path + headers["X-Api-Key"] = plugin_daemon_inner_api_key + response = requests.request(method=method, url=str(url), headers=headers, data=data, stream=stream) + return response + + def _stream_request(self, method: str, path: str, headers: dict, data: bytes) -> Generator[bytes, None, None]: + """ + Make a stream request to the plugin daemon inner API + """ + response = self._request(method, path, headers, data, stream=True) + yield from response.iter_lines() + + def _stream_request_with_model( + self, method: str, path: str, headers: dict, data: bytes, type: type[T] + ) -> Generator[T, None, None]: + """ + Make a stream request to the plugin daemon inner API and yield the response as a model. + """ + for line in self._stream_request(method, path, headers, data): + yield type(**json.loads(line)) + + def _request_with_model(self, method: str, path: str, headers: dict, data: bytes, type: type[T]) -> T: + """ + Make a request to the plugin daemon inner API and return the response as a model. + """ + response = self._request(method, path, headers, data) + return type(**response.json()) diff --git a/api/core/plugin/manager/endpoint.py b/api/core/plugin/manager/endpoint.py new file mode 100644 index 00000000000000..a3f49903fd8595 --- /dev/null +++ b/api/core/plugin/manager/endpoint.py @@ -0,0 +1,5 @@ +from core.plugin.manager.base import BasePluginManager + + +class PluginEndpointManager(BasePluginManager): + pass \ No newline at end of file diff --git a/api/core/plugin/manager/model.py b/api/core/plugin/manager/model.py new file mode 100644 index 00000000000000..f03dbfd1e33100 --- /dev/null +++ b/api/core/plugin/manager/model.py @@ -0,0 +1,5 @@ +from core.plugin.manager.base import BasePluginManager + + +class PluginModelManager(BasePluginManager): + pass \ No newline at end of file diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py new file mode 100644 index 00000000000000..83517f1caf6fc8 --- /dev/null +++ b/api/core/plugin/manager/tool.py @@ -0,0 +1,5 @@ +from core.plugin.manager.base import BasePluginManager + + +class PluginToolManager(BasePluginManager): + pass \ No newline at end of file From 9693b5ad0c62e14de69e430c5491e541a970f796 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 20 Sep 2024 14:43:01 +0800 Subject: [PATCH 035/325] feat: debugging key --- api/core/plugin/entities/plugin_daemon.py | 15 +++++++ api/core/plugin/manager/asset.py | 9 +++- api/core/plugin/manager/base.py | 51 +++++++++++++++++++++-- api/core/plugin/manager/debugging.py | 17 ++++++++ 4 files changed, 87 insertions(+), 5 deletions(-) create mode 100644 api/core/plugin/entities/plugin_daemon.py create mode 100644 api/core/plugin/manager/debugging.py diff --git a/api/core/plugin/entities/plugin_daemon.py b/api/core/plugin/entities/plugin_daemon.py new file mode 100644 index 00000000000000..ca8ea0f780edcd --- /dev/null +++ b/api/core/plugin/entities/plugin_daemon.py @@ -0,0 +1,15 @@ +from typing import Generic, Optional, TypeVar + +from pydantic import BaseModel + +T = TypeVar("T", bound=(BaseModel | dict)) + + +class PluginDaemonBasicResponse(BaseModel, Generic[T]): + """ + Basic response from plugin daemon. + """ + + code: int + message: str + data: Optional[T] diff --git a/api/core/plugin/manager/asset.py b/api/core/plugin/manager/asset.py index f55ff748cace84..df76f56a6dc8d9 100644 --- a/api/core/plugin/manager/asset.py +++ b/api/core/plugin/manager/asset.py @@ -2,4 +2,11 @@ class PluginAssetManager(BasePluginManager): - pass \ No newline at end of file + def fetch_asset(self, id: str) -> bytes: + """ + Fetch an asset by id. + """ + response = self._request(method="GET", path=f"/assets/plugin/{id}") + if response.status_code != 200: + raise ValueError(f"can not found asset {id}") + return response.content diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index 5f1e5cd1d2bf66..b26ab851c72f2e 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -7,6 +7,7 @@ from yarl import URL from configs import dify_config +from core.plugin.entities.plugin_daemon import PluginDaemonBasicResponse plugin_daemon_inner_api_baseurl = dify_config.PLUGIN_API_URL plugin_daemon_inner_api_key = dify_config.INNER_API_KEY_FOR_PLUGIN @@ -15,16 +16,21 @@ class BasePluginManager: - def _request(self, method: str, path: str, headers: dict, data: bytes, stream: bool = False) -> requests.Response: + def _request( + self, method: str, path: str, headers: dict | None = None, data: bytes | None = None, stream: bool = False + ) -> requests.Response: """ Make a request to the plugin daemon inner API. """ url = URL(str(plugin_daemon_inner_api_baseurl)) / path + headers = headers or {} headers["X-Api-Key"] = plugin_daemon_inner_api_key response = requests.request(method=method, url=str(url), headers=headers, data=data, stream=stream) return response - def _stream_request(self, method: str, path: str, headers: dict, data: bytes) -> Generator[bytes, None, None]: + def _stream_request( + self, method: str, path: str, headers: dict | None = None, data: bytes | None = None + ) -> Generator[bytes, None, None]: """ Make a stream request to the plugin daemon inner API """ @@ -32,7 +38,12 @@ def _stream_request(self, method: str, path: str, headers: dict, data: bytes) -> yield from response.iter_lines() def _stream_request_with_model( - self, method: str, path: str, headers: dict, data: bytes, type: type[T] + self, + method: str, + path: str, + type: type[T], + headers: dict | None = None, + data: bytes | None = None, ) -> Generator[T, None, None]: """ Make a stream request to the plugin daemon inner API and yield the response as a model. @@ -40,9 +51,41 @@ def _stream_request_with_model( for line in self._stream_request(method, path, headers, data): yield type(**json.loads(line)) - def _request_with_model(self, method: str, path: str, headers: dict, data: bytes, type: type[T]) -> T: + def _request_with_model( + self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | None = None + ) -> T: """ Make a request to the plugin daemon inner API and return the response as a model. """ response = self._request(method, path, headers, data) return type(**response.json()) + + def _request_with_plugin_daemon_response( + self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | None = None + ) -> T: + """ + Make a request to the plugin daemon inner API and return the response as a model. + """ + response = self._request(method, path, headers, data) + rep = PluginDaemonBasicResponse[type](**response.json()) + if rep.code != 0: + raise Exception(f"got error from plugin daemon: {rep.message}, code: {rep.code}") + if rep.data is None: + raise Exception("got empty data from plugin daemon") + + return rep.data + + def _request_with_plugin_daemon_response_stream( + self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | None = None + ) -> Generator[T, None, None]: + """ + Make a stream request to the plugin daemon inner API and yield the response as a model. + """ + for line in self._stream_request(method, path, headers, data): + line_data = json.loads(line) + rep = PluginDaemonBasicResponse[type](**line_data) + if rep.code != 0: + raise Exception(f"got error from plugin daemon: {rep.message}, code: {rep.code}") + if rep.data is None: + raise Exception("got empty data from plugin daemon") + yield rep.data \ No newline at end of file diff --git a/api/core/plugin/manager/debugging.py b/api/core/plugin/manager/debugging.py new file mode 100644 index 00000000000000..6b26e3ad676dda --- /dev/null +++ b/api/core/plugin/manager/debugging.py @@ -0,0 +1,17 @@ +from pydantic import BaseModel + +from core.plugin.manager.base import BasePluginManager + + +class PluginDebuggingManager(BasePluginManager): + def get_debugging_key(self, tenant_id: str) -> str: + """ + Get the debugging key for the given tenant. + """ + + class Response(BaseModel): + key: str + + response = self._request_with_plugin_daemon_response("POST", f"/plugin/{tenant_id}/debugging/key", Response) + + return response.key From 2223dfb26679f32dff0fb7dddbaa43193c202445 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 20 Sep 2024 15:08:39 +0800 Subject: [PATCH 036/325] feat: get debugging key --- api/controllers/console/__init__.py | 2 +- api/controllers/console/workspace/plugin.py | 27 +++++++++++++++++++ api/core/plugin/manager/base.py | 6 ++--- api/core/plugin/manager/debugging.py | 2 +- api/core/plugin/manager/tool.py | 6 ++++- .../plugin/plugin_debugging_service.py | 8 ++++++ 6 files changed, 45 insertions(+), 6 deletions(-) create mode 100644 api/controllers/console/workspace/plugin.py create mode 100644 api/services/plugin/plugin_debugging_service.py diff --git a/api/controllers/console/__init__.py b/api/controllers/console/__init__.py index eb7c1464d39722..f36703192a9444 100644 --- a/api/controllers/console/__init__.py +++ b/api/controllers/console/__init__.py @@ -56,4 +56,4 @@ from .tag import tags # Import workspace controllers -from .workspace import account, load_balancing_config, members, model_providers, models, tool_providers, workspace +from .workspace import account, load_balancing_config, members, model_providers, models, tool_providers, workspace, plugin diff --git a/api/controllers/console/workspace/plugin.py b/api/controllers/console/workspace/plugin.py new file mode 100644 index 00000000000000..c3e89321d6bbf5 --- /dev/null +++ b/api/controllers/console/workspace/plugin.py @@ -0,0 +1,27 @@ +from flask_login import current_user +from flask_restful import Resource +from werkzeug.exceptions import Forbidden + +from controllers.console import api +from controllers.console.setup import setup_required +from controllers.console.wraps import account_initialization_required +from libs.login import login_required +from services.plugin.plugin_debugging_service import PluginDebuggingService + + +class PluginDebuggingKeyApi(Resource): + @setup_required + @login_required + @account_initialization_required + def get(self): + user = current_user + if not user.is_admin_or_owner: + raise Forbidden() + + tenant_id = user.current_tenant_id + return { + "key": PluginDebuggingService.get_plugin_debugging_key(tenant_id) + } + + +api.add_resource(PluginDebuggingKeyApi, "/workspaces/current/plugin/debugging-key") \ No newline at end of file diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index b26ab851c72f2e..704afe71d1c173 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -10,7 +10,7 @@ from core.plugin.entities.plugin_daemon import PluginDaemonBasicResponse plugin_daemon_inner_api_baseurl = dify_config.PLUGIN_API_URL -plugin_daemon_inner_api_key = dify_config.INNER_API_KEY_FOR_PLUGIN +plugin_daemon_inner_api_key = dify_config.PLUGIN_API_KEY T = TypeVar("T", bound=(BaseModel | dict)) @@ -69,9 +69,9 @@ def _request_with_plugin_daemon_response( response = self._request(method, path, headers, data) rep = PluginDaemonBasicResponse[type](**response.json()) if rep.code != 0: - raise Exception(f"got error from plugin daemon: {rep.message}, code: {rep.code}") + raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") if rep.data is None: - raise Exception("got empty data from plugin daemon") + raise ValueError("got empty data from plugin daemon") return rep.data diff --git a/api/core/plugin/manager/debugging.py b/api/core/plugin/manager/debugging.py index 6b26e3ad676dda..fb6bad7fa3132c 100644 --- a/api/core/plugin/manager/debugging.py +++ b/api/core/plugin/manager/debugging.py @@ -12,6 +12,6 @@ def get_debugging_key(self, tenant_id: str) -> str: class Response(BaseModel): key: str - response = self._request_with_plugin_daemon_response("POST", f"/plugin/{tenant_id}/debugging/key", Response) + response = self._request_with_plugin_daemon_response("POST", f"plugin/{tenant_id}/debugging/key", Response) return response.key diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py index 83517f1caf6fc8..10ce33d5e7a243 100644 --- a/api/core/plugin/manager/tool.py +++ b/api/core/plugin/manager/tool.py @@ -2,4 +2,8 @@ class PluginToolManager(BasePluginManager): - pass \ No newline at end of file + def fetch_tool_providers(self, asset_id: str) -> list[str]: + """ + Fetch tool providers for the given asset. + """ + response = self._request('GET', f'/plugin/asset/{asset_id}') \ No newline at end of file diff --git a/api/services/plugin/plugin_debugging_service.py b/api/services/plugin/plugin_debugging_service.py new file mode 100644 index 00000000000000..2bf24e6de89805 --- /dev/null +++ b/api/services/plugin/plugin_debugging_service.py @@ -0,0 +1,8 @@ +from core.plugin.manager.debugging import PluginDebuggingManager + + +class PluginDebuggingService: + @staticmethod + def get_plugin_debugging_key(tenant_id: str) -> str: + manager = PluginDebuggingManager() + return manager.get_debugging_key(tenant_id) From eef79a519602e0759eb78bbd205ee00303be705a Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 20 Sep 2024 21:35:19 +0800 Subject: [PATCH 037/325] feat: support install plugin --- api/controllers/console/__init__.py | 11 +++++- api/core/plugin/entities/plugin_daemon.py | 16 +++++++- api/core/plugin/manager/base.py | 27 +++++++------ api/core/plugin/manager/plugin.py | 46 +++++++++++++++++++++++ 4 files changed, 87 insertions(+), 13 deletions(-) create mode 100644 api/core/plugin/manager/plugin.py diff --git a/api/controllers/console/__init__.py b/api/controllers/console/__init__.py index f36703192a9444..1cf987050a7866 100644 --- a/api/controllers/console/__init__.py +++ b/api/controllers/console/__init__.py @@ -56,4 +56,13 @@ from .tag import tags # Import workspace controllers -from .workspace import account, load_balancing_config, members, model_providers, models, tool_providers, workspace, plugin +from .workspace import ( + account, + load_balancing_config, + members, + model_providers, + models, + plugin, + tool_providers, + workspace, +) diff --git a/api/core/plugin/entities/plugin_daemon.py b/api/core/plugin/entities/plugin_daemon.py index ca8ea0f780edcd..63c839a4e4a5d5 100644 --- a/api/core/plugin/entities/plugin_daemon.py +++ b/api/core/plugin/entities/plugin_daemon.py @@ -1,8 +1,9 @@ +from enum import Enum from typing import Generic, Optional, TypeVar from pydantic import BaseModel -T = TypeVar("T", bound=(BaseModel | dict)) +T = TypeVar("T", bound=(BaseModel | dict | bool)) class PluginDaemonBasicResponse(BaseModel, Generic[T]): @@ -13,3 +14,16 @@ class PluginDaemonBasicResponse(BaseModel, Generic[T]): code: int message: str data: Optional[T] + + +class InstallPluginMessage(BaseModel): + """ + Message for installing a plugin. + """ + class Event(Enum): + Info = "info" + Done = "done" + Error = "error" + + event: Event + data: str \ No newline at end of file diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index 704afe71d1c173..f6b44d05dd264d 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -12,12 +12,17 @@ plugin_daemon_inner_api_baseurl = dify_config.PLUGIN_API_URL plugin_daemon_inner_api_key = dify_config.PLUGIN_API_KEY -T = TypeVar("T", bound=(BaseModel | dict)) +T = TypeVar("T", bound=(BaseModel | dict | bool)) class BasePluginManager: def _request( - self, method: str, path: str, headers: dict | None = None, data: bytes | None = None, stream: bool = False + self, + method: str, + path: str, + headers: dict | None = None, + data: bytes | dict | None = None, + stream: bool = False, ) -> requests.Response: """ Make a request to the plugin daemon inner API. @@ -29,7 +34,7 @@ def _request( return response def _stream_request( - self, method: str, path: str, headers: dict | None = None, data: bytes | None = None + self, method: str, path: str, headers: dict | None = None, data: bytes | dict | None = None ) -> Generator[bytes, None, None]: """ Make a stream request to the plugin daemon inner API @@ -43,7 +48,7 @@ def _stream_request_with_model( path: str, type: type[T], headers: dict | None = None, - data: bytes | None = None, + data: bytes | dict | None = None, ) -> Generator[T, None, None]: """ Make a stream request to the plugin daemon inner API and yield the response as a model. @@ -61,7 +66,7 @@ def _request_with_model( return type(**response.json()) def _request_with_plugin_daemon_response( - self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | None = None + self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | dict | None = None ) -> T: """ Make a request to the plugin daemon inner API and return the response as a model. @@ -72,11 +77,11 @@ def _request_with_plugin_daemon_response( raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") if rep.data is None: raise ValueError("got empty data from plugin daemon") - + return rep.data - + def _request_with_plugin_daemon_response_stream( - self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | None = None + self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | dict | None = None ) -> Generator[T, None, None]: """ Make a stream request to the plugin daemon inner API and yield the response as a model. @@ -85,7 +90,7 @@ def _request_with_plugin_daemon_response_stream( line_data = json.loads(line) rep = PluginDaemonBasicResponse[type](**line_data) if rep.code != 0: - raise Exception(f"got error from plugin daemon: {rep.message}, code: {rep.code}") + raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") if rep.data is None: - raise Exception("got empty data from plugin daemon") - yield rep.data \ No newline at end of file + raise ValueError("got empty data from plugin daemon") + yield rep.data diff --git a/api/core/plugin/manager/plugin.py b/api/core/plugin/manager/plugin.py new file mode 100644 index 00000000000000..85e865bb93b8f8 --- /dev/null +++ b/api/core/plugin/manager/plugin.py @@ -0,0 +1,46 @@ +from collections.abc import Generator +from urllib.parse import quote + +from core.plugin.entities.plugin_daemon import InstallPluginMessage +from core.plugin.manager.base import BasePluginManager + + +class PluginInstallationManager(BasePluginManager): + def fetch_plugin_by_identifier(self, tenant_id: str, identifier: str) -> bool: + # urlencode the identifier + + identifier = quote(identifier) + return self._request_with_plugin_daemon_response( + "GET", f"/plugin/{tenant_id}/fetch/identifier?plugin_unique_identifier={identifier}", bool + ) + + def install_from_pkg(self, tenant_id: str, pkg: bytes) -> Generator[InstallPluginMessage, None, None]: + """ + Install a plugin from a package. + """ + # using multipart/form-data to encode body + body = {"dify_pkg": ("dify_pkg", pkg, "application/octet-stream")} + + return self._request_with_plugin_daemon_response_stream( + "POST", f"/plugin/{tenant_id}/install/pkg", InstallPluginMessage, data=body + ) + + def install_from_identifier(self, tenant_id: str, identifier: str) -> bool: + """ + Install a plugin from an identifier. + """ + identifier = quote(identifier) + # exception will be raised if the request failed + self._request_with_plugin_daemon_response( + "POST", + f"/plugin/{tenant_id}/install/identifier", + dict, + headers={ + "Content-Type": "application/json", + }, + data={ + "plugin_unique_identifier": identifier, + }, + ) + + return True From 3c1d32e3ac687486785c307789b7a93f79aadb2f Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 20 Sep 2024 21:50:44 +0800 Subject: [PATCH 038/325] feat: uninstall plugin --- api/core/plugin/manager/plugin.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/api/core/plugin/manager/plugin.py b/api/core/plugin/manager/plugin.py index 85e865bb93b8f8..101827246ac773 100644 --- a/api/core/plugin/manager/plugin.py +++ b/api/core/plugin/manager/plugin.py @@ -31,10 +31,10 @@ def install_from_identifier(self, tenant_id: str, identifier: str) -> bool: """ identifier = quote(identifier) # exception will be raised if the request failed - self._request_with_plugin_daemon_response( + return self._request_with_plugin_daemon_response( "POST", f"/plugin/{tenant_id}/install/identifier", - dict, + bool, headers={ "Content-Type": "application/json", }, @@ -43,4 +43,10 @@ def install_from_identifier(self, tenant_id: str, identifier: str) -> bool: }, ) - return True + def uninstall(self, tenant_id: str, identifier: str) -> bool: + """ + Uninstall a plugin. + """ + return self._request_with_plugin_daemon_response( + "DELETE", f"/plugin/{tenant_id}/uninstall?plugin_unique_identifier={identifier}", bool + ) From 91cb80f795789773a419d8ecb0d7264034df9dc1 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 20 Sep 2024 23:48:48 +0800 Subject: [PATCH 039/325] refactor: tool --- api/core/agent/base_agent_runner.py | 104 ++++----- api/core/agent/cot_agent_runner.py | 49 ++-- api/core/agent/cot_chat_agent_runner.py | 10 +- api/core/agent/fc_agent_runner.py | 33 ++- api/core/app/apps/agent_chat/app_runner.py | 56 ----- api/core/model_manager.py | 38 +++- api/core/tools/__base/tool.py | 209 +++--------------- api/core/tools/__base/tool_provider.py | 21 +- api/core/tools/__base/tool_runtime.py | 36 +++ api/core/tools/builtin_tool/provider.py | 51 +++-- .../builtin_tool/providers/qrcode/qrcode.py | 7 +- .../tools/builtin_tool/providers/time/time.py | 10 +- api/core/tools/builtin_tool/tool.py | 5 +- api/core/tools/custom_tool/provider.py | 40 ++-- api/core/tools/custom_tool/tool.py | 17 +- api/core/tools/entities/tool_entities.py | 171 +++----------- api/core/tools/tool_engine.py | 20 +- api/core/tools/tool_manager.py | 68 +++--- api/core/tools/utils/configuration.py | 42 ++-- .../tools/utils/dataset_retriever_tool.py | 25 ++- api/core/tools/workflow_as_tool/provider.py | 32 +-- api/core/tools/workflow_as_tool/tool.py | 32 ++- .../workflow_tool_provider.py | 207 ----------------- api/models/model.py | 2 +- .../tools/api_tools_manage_service.py | 16 +- .../tools/builtin_tools_manage_service.py | 12 +- api/services/tools/tools_transform_service.py | 61 ++--- .../tools/workflow_tools_manage_service.py | 18 +- .../tools/api_tool/test_api_tool.py | 12 +- 29 files changed, 498 insertions(+), 906 deletions(-) create mode 100644 api/core/tools/__base/tool_runtime.py delete mode 100644 api/core/tools/workflow_as_tool/workflow_tool_provider.py diff --git a/api/core/agent/base_agent_runner.py b/api/core/agent/base_agent_runner.py index 55fd8825de6909..64075ed231f4af 100644 --- a/api/core/agent/base_agent_runner.py +++ b/api/core/agent/base_agent_runner.py @@ -2,7 +2,6 @@ import logging import uuid from collections.abc import Mapping, Sequence -from datetime import datetime, timezone from typing import Optional, Union, cast from core.agent.entities import AgentEntity, AgentToolEntity @@ -23,6 +22,7 @@ from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, PromptMessage, + PromptMessageContent, PromptMessageTool, SystemPromptMessage, TextPromptMessageContent, @@ -31,18 +31,15 @@ ) from core.model_runtime.entities.model_entities import ModelFeature from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.utils.encoders import jsonable_encoder from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ( ToolParameter, - ToolRuntimeVariablePool, ) from core.tools.tool_manager import ToolManager from core.tools.utils.dataset_retriever_tool import DatasetRetrieverTool from core.tools.utils.tool_parameter_converter import ToolParameterConverter from extensions.ext_database import db from models.model import Conversation, Message, MessageAgentThought -from models.tools import ToolConversationVariables logger = logging.getLogger(__name__) @@ -59,11 +56,9 @@ def __init__( queue_manager: AppQueueManager, message: Message, user_id: str, + model_instance: ModelInstance, memory: Optional[TokenBufferMemory] = None, prompt_messages: Optional[list[PromptMessage]] = None, - variables_pool: Optional[ToolRuntimeVariablePool] = None, - db_variables: Optional[ToolConversationVariables] = None, - model_instance: ModelInstance = None, ) -> None: """ Agent runner @@ -93,8 +88,6 @@ def __init__( self.user_id = user_id self.memory = memory self.history_prompt_messages = self.organize_agent_history(prompt_messages=prompt_messages or []) - self.variables_pool = variables_pool - self.db_variables_pool = db_variables self.model_instance = model_instance # init callback @@ -162,11 +155,10 @@ def _convert_tool_to_prompt_message_tool(self, tool: AgentToolEntity) -> tuple[P agent_tool=tool, invoke_from=self.application_generate_entity.invoke_from, ) - tool_entity.load_variables(self.variables_pool) - + assert tool_entity.entity.description message_tool = PromptMessageTool( name=tool.tool_name, - description=tool_entity.description.llm, + description=tool_entity.entity.description.llm, parameters={ "type": "object", "properties": {}, @@ -201,9 +193,11 @@ def _convert_dataset_retriever_tool_to_prompt_message_tool(self, tool: DatasetRe """ convert dataset retriever tool to prompt message tool """ + assert tool.entity.description + prompt_tool = PromptMessageTool( - name=tool.identity.name, - description=tool.description.llm, + name=tool.entity.identity.name, + description=tool.entity.description.llm, parameters={ "type": "object", "properties": {}, @@ -232,7 +226,7 @@ def _init_prompt_tools(self) -> tuple[Mapping[str, Tool], Sequence[PromptMessage tool_instances = {} prompt_messages_tools = [] - for tool in self.app_config.agent.tools if self.app_config.agent else []: + for tool in self.app_config.agent.tools or [] if self.app_config.agent else []: try: prompt_tool, tool_entity = self._convert_tool_to_prompt_message_tool(tool) except Exception: @@ -249,7 +243,7 @@ def _init_prompt_tools(self) -> tuple[Mapping[str, Tool], Sequence[PromptMessage # save prompt tool prompt_messages_tools.append(prompt_tool) # save tool entity - tool_instances[dataset_tool.identity.name] = dataset_tool + tool_instances[dataset_tool.entity.identity.name] = dataset_tool return tool_instances, prompt_messages_tools @@ -328,25 +322,29 @@ def create_agent_thought( def save_agent_thought( self, agent_thought: MessageAgentThought, - tool_name: str, - tool_input: Union[str, dict], - thought: str, - observation: Union[str, dict], - tool_invoke_meta: Union[str, dict], - answer: str, + tool_name: str | None, + tool_input: Union[str, dict, None], + thought: str | None, + observation: Union[str, dict, None], + tool_invoke_meta: Union[str, dict, None], + answer: str | None, messages_ids: list[str], - llm_usage: LLMUsage = None, - ) -> MessageAgentThought: + llm_usage: LLMUsage | None = None, + ): """ Save agent thought """ - agent_thought = db.session.query(MessageAgentThought).filter(MessageAgentThought.id == agent_thought.id).first() + updated_agent_thought = ( + db.session.query(MessageAgentThought).filter(MessageAgentThought.id == agent_thought.id).first() + ) + if not updated_agent_thought: + raise ValueError("agent thought not found") if thought is not None: - agent_thought.thought = thought + updated_agent_thought.thought = thought if tool_name is not None: - agent_thought.tool = tool_name + updated_agent_thought.tool = tool_name if tool_input is not None: if isinstance(tool_input, dict): @@ -355,7 +353,7 @@ def save_agent_thought( except Exception as e: tool_input = json.dumps(tool_input) - agent_thought.tool_input = tool_input + updated_agent_thought.tool_input = tool_input if observation is not None: if isinstance(observation, dict): @@ -364,27 +362,27 @@ def save_agent_thought( except Exception as e: observation = json.dumps(observation) - agent_thought.observation = observation + updated_agent_thought.observation = observation if answer is not None: - agent_thought.answer = answer + updated_agent_thought.answer = answer if messages_ids is not None and len(messages_ids) > 0: - agent_thought.message_files = json.dumps(messages_ids) + updated_agent_thought.message_files = json.dumps(messages_ids) if llm_usage: - agent_thought.message_token = llm_usage.prompt_tokens - agent_thought.message_price_unit = llm_usage.prompt_price_unit - agent_thought.message_unit_price = llm_usage.prompt_unit_price - agent_thought.answer_token = llm_usage.completion_tokens - agent_thought.answer_price_unit = llm_usage.completion_price_unit - agent_thought.answer_unit_price = llm_usage.completion_unit_price - agent_thought.tokens = llm_usage.total_tokens - agent_thought.total_price = llm_usage.total_price + updated_agent_thought.message_token = llm_usage.prompt_tokens + updated_agent_thought.message_price_unit = llm_usage.prompt_price_unit + updated_agent_thought.message_unit_price = llm_usage.prompt_unit_price + updated_agent_thought.answer_token = llm_usage.completion_tokens + updated_agent_thought.answer_price_unit = llm_usage.completion_price_unit + updated_agent_thought.answer_unit_price = llm_usage.completion_unit_price + updated_agent_thought.tokens = llm_usage.total_tokens + updated_agent_thought.total_price = llm_usage.total_price # check if tool labels is not empty - labels = agent_thought.tool_labels or {} - tools = agent_thought.tool.split(";") if agent_thought.tool else [] + labels = updated_agent_thought.tool_labels or {} + tools = updated_agent_thought.tool.split(";") if updated_agent_thought.tool else [] for tool in tools: if not tool: continue @@ -395,7 +393,7 @@ def save_agent_thought( else: labels[tool] = {"en_US": tool, "zh_Hans": tool} - agent_thought.tool_labels_str = json.dumps(labels) + updated_agent_thought.tool_labels_str = json.dumps(labels) if tool_invoke_meta is not None: if isinstance(tool_invoke_meta, dict): @@ -404,25 +402,8 @@ def save_agent_thought( except Exception as e: tool_invoke_meta = json.dumps(tool_invoke_meta) - agent_thought.tool_meta_str = tool_invoke_meta - - db.session.commit() - db.session.close() - - def update_db_variables(self, tool_variables: ToolRuntimeVariablePool, db_variables: ToolConversationVariables): - """ - convert tool variables to db variables - """ - db_variables = ( - db.session.query(ToolConversationVariables) - .filter( - ToolConversationVariables.conversation_id == self.message.conversation_id, - ) - .first() - ) + updated_agent_thought.tool_meta_str = tool_invoke_meta - db_variables.updated_at = datetime.now(timezone.utc).replace(tzinfo=None) - db_variables.variables_str = json.dumps(jsonable_encoder(tool_variables.pool)) db.session.commit() db.session.close() @@ -515,6 +496,7 @@ def organize_agent_user_prompt(self, message: Message) -> UserPromptMessage: files = message.message_files if files: + assert message.app_model_config file_extra_config = FileUploadConfigManager.convert(message.app_model_config.to_dict()) if file_extra_config: @@ -525,7 +507,7 @@ def organize_agent_user_prompt(self, message: Message) -> UserPromptMessage: if not file_objs: return UserPromptMessage(content=message.query) else: - prompt_message_contents = [TextPromptMessageContent(data=message.query)] + prompt_message_contents: list[PromptMessageContent] = [TextPromptMessageContent(data=message.query)] for file_obj in file_objs: prompt_message_contents.append(file_obj.prompt_message_content) diff --git a/api/core/agent/cot_agent_runner.py b/api/core/agent/cot_agent_runner.py index 0d74b1e5ebe933..1e62b4308d2c0c 100644 --- a/api/core/agent/cot_agent_runner.py +++ b/api/core/agent/cot_agent_runner.py @@ -1,6 +1,6 @@ import json from abc import ABC, abstractmethod -from collections.abc import Generator +from collections.abc import Generator, Mapping, Sequence from typing import Optional, Union from core.agent.base_agent_runner import BaseAgentRunner @@ -12,6 +12,7 @@ from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, PromptMessage, + PromptMessageTool, ToolPromptMessage, UserPromptMessage, ) @@ -26,11 +27,11 @@ class CotAgentRunner(BaseAgentRunner, ABC): _is_first_iteration = True _ignore_observation_providers = ["wenxin"] - _historic_prompt_messages: list[PromptMessage] = None - _agent_scratchpad: list[AgentScratchpadUnit] = None - _instruction: str = None - _query: str = None - _prompt_messages_tools: list[PromptMessage] = None + _historic_prompt_messages: list[PromptMessage] + _agent_scratchpad: list[AgentScratchpadUnit] + _instruction: str + _query: str + _prompt_messages_tools: Sequence[PromptMessageTool] def run( self, @@ -41,6 +42,7 @@ def run( """ Run Cot agent application """ + app_generate_entity = self.application_generate_entity self._repack_app_generate_entity(app_generate_entity) self._init_react_state(query) @@ -53,9 +55,11 @@ def run( app_generate_entity.model_conf.stop.append("Observation") app_config = self.app_config + assert app_config.agent # init instruction inputs = inputs or {} + assert app_config.prompt_template.simple_prompt_template instruction = app_config.prompt_template.simple_prompt_template self._instruction = self._fill_in_inputs_from_external_data_tools(instruction, inputs) @@ -63,13 +67,14 @@ def run( max_iteration_steps = min(app_config.agent.max_iteration, 5) + 1 # convert tools into ModelRuntime Tool format - tool_instances, self._prompt_messages_tools = self._init_prompt_tools() + tool_instances, prompt_messages_tools = self._init_prompt_tools() + self._prompt_messages_tools = prompt_messages_tools function_call_state = True - llm_usage = {"usage": None} + llm_usage: dict[str, Optional[LLMUsage]] = {"usage": None} final_answer = "" - def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): + def increase_usage(final_llm_usage_dict: dict[str, Optional[LLMUsage]], usage: LLMUsage): if not final_llm_usage_dict["usage"]: final_llm_usage_dict["usage"] = usage else: @@ -115,10 +120,6 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): callbacks=[], ) - # check llm result - if not chunks: - raise ValueError("failed to invoke llm") - usage_dict = {} react_chunks = CotAgentOutputParser.handle_react_stream_output(chunks, usage_dict) scratchpad = AgentScratchpadUnit( @@ -139,11 +140,14 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): if isinstance(chunk, AgentScratchpadUnit.Action): action = chunk # detect action + assert scratchpad.agent_response is not None scratchpad.agent_response += json.dumps(chunk.model_dump()) scratchpad.action_str = json.dumps(chunk.model_dump()) scratchpad.action = action else: + assert scratchpad.agent_response is not None scratchpad.agent_response += chunk + assert scratchpad.thought is not None scratchpad.thought += chunk yield LLMResultChunk( model=self.model_config.model, @@ -152,6 +156,7 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): delta=LLMResultChunkDelta(index=0, message=AssistantPromptMessage(content=chunk), usage=None), ) + assert scratchpad.thought is not None scratchpad.thought = scratchpad.thought.strip() or "I am thinking about how to help you" self._agent_scratchpad.append(scratchpad) @@ -168,7 +173,7 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): tool_invoke_meta={}, thought=scratchpad.thought, observation="", - answer=scratchpad.agent_response, + answer=scratchpad.agent_response or "", messages_ids=[], llm_usage=usage_dict["usage"], ) @@ -248,7 +253,6 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): messages_ids=[], ) - self.update_db_variables(self.variables_pool, self.db_variables_pool) # publish end event self.queue_manager.publish( QueueMessageEndEvent( @@ -266,7 +270,7 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): def _handle_invoke_action( self, action: AgentScratchpadUnit.Action, - tool_instances: dict[str, Tool], + tool_instances: Mapping[str, Tool], message_file_ids: list[str], trace_manager: Optional[TraceQueueManager] = None, ) -> tuple[str, ToolInvokeMeta]: @@ -307,15 +311,12 @@ def _handle_invoke_action( # publish files for message_file_id, save_as in message_files: - if save_as: - self.variables_pool.set_file(tool_name=tool_call_name, value=message_file_id, name=save_as) - # publish message file self.queue_manager.publish( - QueueMessageFileEvent(message_file_id=message_file_id), PublishFrom.APPLICATION_MANAGER + QueueMessageFileEvent(message_file_id=message_file_id.id), PublishFrom.APPLICATION_MANAGER ) # add message file ids - message_file_ids.append(message_file_id) + message_file_ids.append(message_file_id.id) return tool_invoke_response, tool_invoke_meta @@ -369,18 +370,19 @@ def _format_assistant_message(self, agent_scratchpad: list[AgentScratchpadUnit]) return message def _organize_historic_prompt_messages( - self, current_session_messages: list[PromptMessage] = None + self, current_session_messages: list[PromptMessage] | None = None ) -> list[PromptMessage]: """ organize historic prompt messages """ result: list[PromptMessage] = [] scratchpads: list[AgentScratchpadUnit] = [] - current_scratchpad: AgentScratchpadUnit = None + current_scratchpad: AgentScratchpadUnit | None = None for message in self.history_prompt_messages: if isinstance(message, AssistantPromptMessage): if not current_scratchpad: + assert isinstance(message.content, str) current_scratchpad = AgentScratchpadUnit( agent_response=message.content, thought=message.content or "I am thinking about how to help you", @@ -400,6 +402,7 @@ def _organize_historic_prompt_messages( pass elif isinstance(message, ToolPromptMessage): if current_scratchpad: + assert isinstance(message.content, str) current_scratchpad.observation = message.content elif isinstance(message, UserPromptMessage): if scratchpads: diff --git a/api/core/agent/cot_chat_agent_runner.py b/api/core/agent/cot_chat_agent_runner.py index bdec6b7ed15d7b..095f8775aeed03 100644 --- a/api/core/agent/cot_chat_agent_runner.py +++ b/api/core/agent/cot_chat_agent_runner.py @@ -4,6 +4,7 @@ from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, PromptMessage, + PromptMessageContent, SystemPromptMessage, TextPromptMessageContent, UserPromptMessage, @@ -16,6 +17,9 @@ def _organize_system_prompt(self) -> SystemPromptMessage: """ Organize system prompt """ + assert self.app_config.agent + assert self.app_config.agent.prompt + prompt_entity = self.app_config.agent.prompt first_prompt = prompt_entity.first_prompt @@ -27,12 +31,12 @@ def _organize_system_prompt(self) -> SystemPromptMessage: return SystemPromptMessage(content=system_prompt) - def _organize_user_query(self, query, prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]: + def _organize_user_query(self, query, prompt_messages: list[PromptMessage]) -> list[PromptMessage]: """ Organize user query """ if self.files: - prompt_message_contents = [TextPromptMessageContent(data=query)] + prompt_message_contents: list[PromptMessageContent] = [TextPromptMessageContent(data=query)] for file_obj in self.files: prompt_message_contents.append(file_obj.prompt_message_content) @@ -57,8 +61,10 @@ def _organize_prompt_messages(self) -> list[PromptMessage]: assistant_message = AssistantPromptMessage(content="") for unit in agent_scratchpad: if unit.is_final(): + assert isinstance(assistant_message.content, str) assistant_message.content += f"Final Answer: {unit.agent_response}" else: + assert isinstance(assistant_message.content, str) assistant_message.content += f"Thought: {unit.thought}\n\n" if unit.action_str: assistant_message.content += f"Action: {unit.action_str}\n\n" diff --git a/api/core/agent/fc_agent_runner.py b/api/core/agent/fc_agent_runner.py index 13164e0bfca218..991c542846626a 100644 --- a/api/core/agent/fc_agent_runner.py +++ b/api/core/agent/fc_agent_runner.py @@ -2,7 +2,7 @@ import logging from collections.abc import Generator from copy import deepcopy -from typing import Any, Union +from typing import Any, Optional, Union from core.agent.base_agent_runner import BaseAgentRunner from core.app.apps.base_app_queue_manager import PublishFrom @@ -11,6 +11,7 @@ from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, PromptMessage, + PromptMessageContent, PromptMessageContentType, SystemPromptMessage, TextPromptMessageContent, @@ -38,18 +39,20 @@ def run(self, message: Message, query: str, **kwargs: Any) -> Generator[LLMResul # convert tools into ModelRuntime Tool format tool_instances, prompt_messages_tools = self._init_prompt_tools() + assert app_config.agent + iteration_step = 1 max_iteration_steps = min(app_config.agent.max_iteration, 5) + 1 # continue to run until there is not any tool call function_call_state = True - llm_usage = {"usage": None} + llm_usage: dict[str, Optional[LLMUsage]] = {"usage": None} final_answer = "" # get tracing instance trace_manager = app_generate_entity.trace_manager - def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): + def increase_usage(final_llm_usage_dict: dict[str, Optional[LLMUsage]], usage: LLMUsage): if not final_llm_usage_dict["usage"]: final_llm_usage_dict["usage"] = usage else: @@ -99,7 +102,7 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): current_llm_usage = None - if self.stream_tool_call: + if isinstance(chunks, Generator): is_first_chunk = True for chunk in chunks: if is_first_chunk: @@ -133,7 +136,7 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): yield chunk else: - result: LLMResult = chunks + result = chunks # check if there is any tool call if self.check_blocking_tool_calls(result): function_call_state = True @@ -236,15 +239,12 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): ) # publish files for message_file_id, save_as in message_files: - if save_as: - self.variables_pool.set_file(tool_name=tool_call_name, value=message_file_id, name=save_as) - # publish message file self.queue_manager.publish( - QueueMessageFileEvent(message_file_id=message_file_id), PublishFrom.APPLICATION_MANAGER + QueueMessageFileEvent(message_file_id=message_file_id.id), PublishFrom.APPLICATION_MANAGER ) # add message file ids - message_file_ids.append(message_file_id) + message_file_ids.append(message_file_id.id) tool_response = { "tool_call_id": tool_call_id, @@ -290,7 +290,6 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): iteration_step += 1 - self.update_db_variables(self.variables_pool, self.db_variables_pool) # publish end event self.queue_manager.publish( QueueMessageEndEvent( @@ -321,9 +320,7 @@ def check_blocking_tool_calls(self, llm_result: LLMResult) -> bool: return True return False - def extract_tool_calls( - self, llm_result_chunk: LLMResultChunk - ) -> Union[None, list[tuple[str, str, dict[str, Any]]]]: + def extract_tool_calls(self, llm_result_chunk: LLMResultChunk) -> list[tuple[str, str, dict[str, Any]]]: """ Extract tool calls from llm result chunk @@ -346,7 +343,7 @@ def extract_tool_calls( return tool_calls - def extract_blocking_tool_calls(self, llm_result: LLMResult) -> Union[None, list[tuple[str, str, dict[str, Any]]]]: + def extract_blocking_tool_calls(self, llm_result: LLMResult) -> list[tuple[str, str, dict[str, Any]]]: """ Extract blocking tool calls from llm result @@ -370,7 +367,7 @@ def extract_blocking_tool_calls(self, llm_result: LLMResult) -> Union[None, list return tool_calls def _init_system_message( - self, prompt_template: str, prompt_messages: list[PromptMessage] = None + self, prompt_template: str, prompt_messages: list[PromptMessage] ) -> list[PromptMessage]: """ Initialize system message @@ -385,12 +382,12 @@ def _init_system_message( return prompt_messages - def _organize_user_query(self, query, prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]: + def _organize_user_query(self, query, prompt_messages: list[PromptMessage]) -> list[PromptMessage]: """ Organize user query """ if self.files: - prompt_message_contents = [TextPromptMessageContent(data=query)] + prompt_message_contents: list[PromptMessageContent] = [TextPromptMessageContent(data=query)] for file_obj in self.files: prompt_message_contents.append(file_obj.prompt_message_content) diff --git a/api/core/app/apps/agent_chat/app_runner.py b/api/core/app/apps/agent_chat/app_runner.py index 45b1bf00934d35..3a9262f54e7dcc 100644 --- a/api/core/app/apps/agent_chat/app_runner.py +++ b/api/core/app/apps/agent_chat/app_runner.py @@ -16,10 +16,8 @@ from core.model_runtime.entities.model_entities import ModelFeature, ModelPropertyKey from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel from core.moderation.base import ModerationError -from core.tools.entities.tool_entities import ToolRuntimeVariablePool from extensions.ext_database import db from models.model import App, Conversation, Message, MessageAgentThought -from models.tools import ToolConversationVariables logger = logging.getLogger(__name__) @@ -174,14 +172,6 @@ def run( agent_entity = app_config.agent - # load tool variables - tool_conversation_variables = self._load_tool_variables( - conversation_id=conversation.id, user_id=application_generate_entity.user_id, tenant_id=app_config.tenant_id - ) - - # convert db variables to tool variables - tool_variables = self._convert_db_variables_to_tool_variables(tool_conversation_variables) - # init model instance model_instance = ModelInstance( provider_model_bundle=application_generate_entity.model_conf.provider_model_bundle, @@ -234,8 +224,6 @@ def run( user_id=application_generate_entity.user_id, memory=memory, prompt_messages=prompt_message, - variables_pool=tool_variables, - db_variables=tool_conversation_variables, model_instance=model_instance, ) @@ -253,50 +241,6 @@ def run( agent=True, ) - def _load_tool_variables(self, conversation_id: str, user_id: str, tenant_id: str) -> ToolConversationVariables: - """ - load tool variables from database - """ - tool_variables: ToolConversationVariables = ( - db.session.query(ToolConversationVariables) - .filter( - ToolConversationVariables.conversation_id == conversation_id, - ToolConversationVariables.tenant_id == tenant_id, - ) - .first() - ) - - if tool_variables: - # save tool variables to session, so that we can update it later - db.session.add(tool_variables) - else: - # create new tool variables - tool_variables = ToolConversationVariables( - conversation_id=conversation_id, - user_id=user_id, - tenant_id=tenant_id, - variables_str="[]", - ) - db.session.add(tool_variables) - db.session.commit() - - return tool_variables - - def _convert_db_variables_to_tool_variables( - self, db_variables: ToolConversationVariables - ) -> ToolRuntimeVariablePool: - """ - convert db variables to tool variables - """ - return ToolRuntimeVariablePool( - **{ - "conversation_id": db_variables.conversation_id, - "user_id": db_variables.user_id, - "tenant_id": db_variables.tenant_id, - "pool": db_variables.variables, - } - ) - def _get_usage_of_all_agent_thoughts( self, model_config: ModelConfigWithCredentialsEntity, message: Message ) -> LLMUsage: diff --git a/api/core/model_manager.py b/api/core/model_manager.py index 990efd36c609c2..28f01e1a19c050 100644 --- a/api/core/model_manager.py +++ b/api/core/model_manager.py @@ -1,7 +1,7 @@ import logging import os from collections.abc import Callable, Generator, Sequence -from typing import IO, Optional, Union, cast +from typing import IO, Literal, Optional, Union, cast, overload from core.entities.provider_configuration import ProviderConfiguration, ProviderModelBundle from core.entities.provider_entities import ModelLoadBalancingConfiguration @@ -97,6 +97,42 @@ def _get_load_balancing_manager( return None + @overload + def invoke_llm( + self, + prompt_messages: list[PromptMessage], + model_parameters: Optional[dict] = None, + tools: Sequence[PromptMessageTool] | None = None, + stop: Optional[list[str]] = None, + stream: Literal[True] = True, + user: Optional[str] = None, + callbacks: Optional[list[Callback]] = None, + ) -> Generator: ... + + @overload + def invoke_llm( + self, + prompt_messages: list[PromptMessage], + model_parameters: Optional[dict] = None, + tools: Sequence[PromptMessageTool] | None = None, + stop: Optional[list[str]] = None, + stream: Literal[False] = False, + user: Optional[str] = None, + callbacks: Optional[list[Callback]] = None, + ) -> LLMResult: ... + + @overload + def invoke_llm( + self, + prompt_messages: list[PromptMessage], + model_parameters: Optional[dict] = None, + tools: Sequence[PromptMessageTool] | None = None, + stop: Optional[list[str]] = None, + stream: bool = True, + user: Optional[str] = None, + callbacks: Optional[list[Callback]] = None, + ) -> Union[LLMResult, Generator]: ... + def invoke_llm( self, prompt_messages: list[PromptMessage], diff --git a/api/core/tools/__base/tool.py b/api/core/tools/__base/tool.py index 49f9bf68eaf9a3..548db51a2aedfb 100644 --- a/api/core/tools/__base/tool.py +++ b/api/core/tools/__base/tool.py @@ -1,72 +1,34 @@ from abc import ABC, abstractmethod from collections.abc import Generator from copy import deepcopy -from enum import Enum -from typing import TYPE_CHECKING, Any, Optional, Union +from typing import TYPE_CHECKING, Any, Optional -from pydantic import BaseModel, ConfigDict, Field, field_validator -from pydantic_core.core_schema import ValidationInfo - -from core.app.entities.app_invoke_entities import InvokeFrom +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.entities.tool_entities import ( - ToolDescription, - ToolIdentity, - ToolInvokeFrom, + ToolEntity, ToolInvokeMessage, ToolParameter, ToolProviderType, - ToolRuntimeImageVariable, - ToolRuntimeVariable, - ToolRuntimeVariablePool, ) -from core.tools.tool_file_manager import ToolFileManager from core.tools.utils.tool_parameter_converter import ToolParameterConverter if TYPE_CHECKING: from core.file.file_obj import FileVar -class Tool(BaseModel, ABC): - identity: ToolIdentity - parameters: list[ToolParameter] = Field(default_factory=list) - description: Optional[ToolDescription] = None - is_team_authorization: bool = False +class Tool(ABC): + """ + The base class of a tool + """ - # pydantic configs - model_config = ConfigDict(protected_namespaces=()) + entity: ToolEntity + runtime: ToolRuntime - @field_validator("parameters", mode="before") - @classmethod - def set_parameters(cls, v, validation_info: ValidationInfo) -> list[ToolParameter]: - return v or [] + def __init__(self, entity: ToolEntity, runtime: ToolRuntime) -> None: + self.entity = entity + self.runtime = runtime - class Runtime(BaseModel): - """ - Meta data of a tool call processing - """ - - def __init__(self, **data: Any): - super().__init__(**data) - if not self.runtime_parameters: - self.runtime_parameters = {} - - tenant_id: Optional[str] = None - tool_id: Optional[str] = None - invoke_from: Optional[InvokeFrom] = None - tool_invoke_from: Optional[ToolInvokeFrom] = None - credentials: Optional[dict[str, Any]] = None - runtime_parameters: dict[str, Any] = Field(default_factory=dict) - - runtime: Optional[Runtime] = None - variables: Optional[ToolRuntimeVariablePool] = None - - def __init__(self, **data: Any): - super().__init__(**data) - - class VariableKey(Enum): - IMAGE = "image" - - def fork_tool_runtime(self, runtime: dict[str, Any]) -> "Tool": + def fork_tool_runtime(self, runtime: ToolRuntime) -> "Tool": """ fork a new tool with meta data @@ -74,10 +36,8 @@ def fork_tool_runtime(self, runtime: dict[str, Any]) -> "Tool": :return: the new tool """ return self.__class__( - identity=self.identity.model_copy() if self.identity else None, - parameters=self.parameters.copy() if self.parameters else None, - description=self.description.model_copy() if self.description else None, - runtime=Tool.Runtime(**runtime), + entity=self.entity.model_copy(), + runtime=runtime, ) @abstractmethod @@ -88,112 +48,6 @@ def tool_provider_type(self) -> ToolProviderType: :return: the tool provider type """ - def load_variables(self, variables: ToolRuntimeVariablePool): - """ - load variables from database - - :param conversation_id: the conversation id - """ - self.variables = variables - - def set_image_variable(self, variable_name: str, image_key: str) -> None: - """ - set an image variable - """ - if not self.variables: - return - - self.variables.set_file(self.identity.name, variable_name, image_key) - - def set_text_variable(self, variable_name: str, text: str) -> None: - """ - set a text variable - """ - if not self.variables: - return - - self.variables.set_text(self.identity.name, variable_name, text) - - def get_variable(self, name: Union[str, Enum]) -> Optional[ToolRuntimeVariable]: - """ - get a variable - - :param name: the name of the variable - :return: the variable - """ - if not self.variables: - return None - - if isinstance(name, Enum): - name = name.value - - for variable in self.variables.pool: - if variable.name == name: - return variable - - return None - - def get_default_image_variable(self) -> Optional[ToolRuntimeVariable]: - """ - get the default image variable - - :return: the image variable - """ - if not self.variables: - return None - - return self.get_variable(self.VariableKey.IMAGE) - - def get_variable_file(self, name: Union[str, Enum]) -> Optional[bytes]: - """ - get a variable file - - :param name: the name of the variable - :return: the variable file - """ - variable = self.get_variable(name) - if not variable: - return None - - if not isinstance(variable, ToolRuntimeImageVariable): - return None - - message_file_id = variable.value - # get file binary - file_binary = ToolFileManager.get_file_binary_by_message_file_id(message_file_id) - if not file_binary: - return None - - return file_binary[0] - - def list_variables(self) -> list[ToolRuntimeVariable]: - """ - list all variables - - :return: the variables - """ - if not self.variables: - return [] - - return self.variables.pool - - def list_default_image_variables(self) -> list[ToolRuntimeVariable]: - """ - list all image variables - - :return: the image variables - """ - if not self.variables: - return [] - - result = [] - - for variable in self.variables.pool: - if variable.name.startswith(self.VariableKey.IMAGE.value): - result.append(variable) - - return result - def invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage]: if self.runtime and self.runtime.runtime_parameters: tool_parameters.update(self.runtime.runtime_parameters) @@ -227,7 +81,7 @@ def _transform_tool_parameters_type(self, tool_parameters: dict[str, Any]) -> di """ # Temp fix for the issue that the tool parameters will be converted to empty while validating the credentials result = deepcopy(tool_parameters) - for parameter in self.parameters or []: + for parameter in self.entity.parameters: if parameter.name in tool_parameters: result[parameter.name] = ToolParameterConverter.cast_parameter_by_type( tool_parameters[parameter.name], parameter.type @@ -241,15 +95,6 @@ def _invoke( ) -> ToolInvokeMessage | list[ToolInvokeMessage] | Generator[ToolInvokeMessage, None, None]: pass - def validate_credentials(self, credentials: dict[str, Any], parameters: dict[str, Any]) -> None: - """ - validate the credentials - - :param credentials: the credentials - :param parameters: the parameters - """ - pass - def get_runtime_parameters(self) -> list[ToolParameter]: """ get the runtime parameters @@ -258,7 +103,7 @@ def get_runtime_parameters(self) -> list[ToolParameter]: :return: the runtime parameters """ - return self.parameters or [] + return self.entity.parameters def get_all_runtime_parameters(self) -> list[ToolParameter]: """ @@ -266,7 +111,7 @@ def get_all_runtime_parameters(self) -> list[ToolParameter]: :return: all runtime parameters """ - parameters = self.parameters or [] + parameters = self.entity.parameters parameters = parameters.copy() user_parameters = self.get_runtime_parameters() or [] user_parameters = user_parameters.copy() @@ -274,20 +119,16 @@ def get_all_runtime_parameters(self) -> list[ToolParameter]: # override parameters for parameter in user_parameters: # check if parameter in tool parameters - found = False for tool_parameter in parameters: if tool_parameter.name == parameter.name: - found = True + # override parameter + tool_parameter.type = parameter.type + tool_parameter.form = parameter.form + tool_parameter.required = parameter.required + tool_parameter.default = parameter.default + tool_parameter.options = parameter.options + tool_parameter.llm_description = parameter.llm_description break - - if found: - # override parameter - tool_parameter.type = parameter.type - tool_parameter.form = parameter.form - tool_parameter.required = parameter.required - tool_parameter.default = parameter.default - tool_parameter.options = parameter.options - tool_parameter.llm_description = parameter.llm_description else: # add new parameter parameters.append(parameter) diff --git a/api/core/tools/__base/tool_provider.py b/api/core/tools/__base/tool_provider.py index 7960ed5f84d5dc..c71885e48de191 100644 --- a/api/core/tools/__base/tool_provider.py +++ b/api/core/tools/__base/tool_provider.py @@ -1,23 +1,22 @@ from abc import ABC, abstractmethod from typing import Any -from pydantic import BaseModel, ConfigDict, Field - from core.entities.provider_entities import ProviderConfig from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ( - ToolProviderIdentity, + ToolProviderEntity, ToolProviderType, ) from core.tools.errors import ToolProviderCredentialValidationError -class ToolProviderController(BaseModel, ABC): - identity: ToolProviderIdentity - tools: list[Tool] = Field(default_factory=list) - credentials_schema: dict[str, ProviderConfig] = Field(default_factory=dict) +class ToolProviderController(ABC): + entity: ToolProviderEntity + tools: list[Tool] - model_config = ConfigDict(validate_assignment=True) + def __init__(self, entity: ToolProviderEntity) -> None: + self.entity = entity + self.tools = [] def get_credentials_schema(self) -> dict[str, ProviderConfig]: """ @@ -25,7 +24,7 @@ def get_credentials_schema(self) -> dict[str, ProviderConfig]: :return: the credentials schema """ - return self.credentials_schema.copy() + return self.entity.credentials_schema.copy() @abstractmethod def get_tool(self, tool_name: str) -> Tool: @@ -51,7 +50,7 @@ def validate_credentials_format(self, credentials: dict[str, Any]) -> None: :param credentials: the credentials of the tool """ - credentials_schema = self.credentials_schema + credentials_schema = self.entity.credentials_schema if credentials_schema is None: return @@ -62,7 +61,7 @@ def validate_credentials_format(self, credentials: dict[str, Any]) -> None: for credential_name in credentials: if credential_name not in credentials_need_to_validate: raise ToolProviderCredentialValidationError( - f"credential {credential_name} not found in provider {self.identity.name}" + f"credential {credential_name} not found in provider {self.entity.identity.name}" ) # check type diff --git a/api/core/tools/__base/tool_runtime.py b/api/core/tools/__base/tool_runtime.py new file mode 100644 index 00000000000000..d4b2ef61049d92 --- /dev/null +++ b/api/core/tools/__base/tool_runtime.py @@ -0,0 +1,36 @@ +from typing import Any, Optional + +from openai import BaseModel +from pydantic import Field + +from core.app.entities.app_invoke_entities import InvokeFrom +from core.tools.entities.tool_entities import ToolInvokeFrom + + +class ToolRuntime(BaseModel): + """ + Meta data of a tool call processing + """ + + tenant_id: str + tool_id: Optional[str] = None + invoke_from: Optional[InvokeFrom] = None + tool_invoke_from: Optional[ToolInvokeFrom] = None + credentials: Optional[dict[str, Any]] = None + runtime_parameters: dict[str, Any] = Field(default_factory=dict) + + +class FakeToolRuntime(ToolRuntime): + """ + Fake tool runtime for testing + """ + + def __init__(self): + super().__init__( + tenant_id="fake_tenant_id", + tool_id="fake_tool_id", + invoke_from=InvokeFrom.DEBUGGER, + tool_invoke_from=ToolInvokeFrom.AGENT, + credentials={}, + runtime_parameters={}, + ) diff --git a/api/core/tools/builtin_tool/provider.py b/api/core/tools/builtin_tool/provider.py index 7d1775b7f561fa..4ebd82f8e778a8 100644 --- a/api/core/tools/builtin_tool/provider.py +++ b/api/core/tools/builtin_tool/provider.py @@ -2,13 +2,12 @@ from os import listdir, path from typing import Any -from pydantic import Field - from core.entities.provider_entities import ProviderConfig from core.helper.module_import_helper import load_single_subclass_from_source from core.tools.__base.tool_provider import ToolProviderController +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.builtin_tool.tool import BuiltinTool -from core.tools.entities.tool_entities import ToolProviderType +from core.tools.entities.tool_entities import ToolEntity, ToolProviderEntity, ToolProviderType from core.tools.entities.values import ToolLabelEnum, default_tool_label_dict from core.tools.errors import ( ToolProviderNotFoundError, @@ -17,10 +16,10 @@ class BuiltinToolProviderController(ToolProviderController): - tools: list[BuiltinTool] = Field(default_factory=list) + tools: list[BuiltinTool] def __init__(self, **data: Any) -> None: - if self.provider_type in {ToolProviderType.API, ToolProviderType.APP}: + if self.provider_type == ToolProviderType.API: super().__init__(**data) return @@ -37,10 +36,12 @@ def __init__(self, **data: Any) -> None: for credential_name in provider_yaml["credentials_for_provider"]: provider_yaml["credentials_for_provider"][credential_name]["name"] = credential_name - super().__init__(**{ - 'identity': provider_yaml['identity'], - 'credentials_schema': provider_yaml.get('credentials_for_provider', {}) or {}, - }) + super().__init__( + entity=ToolProviderEntity( + identity=provider_yaml["identity"], + credentials_schema=provider_yaml.get("credentials_for_provider", {}) or {}, + ), + ) def _get_builtin_tools(self) -> list[BuiltinTool]: """ @@ -51,7 +52,7 @@ def _get_builtin_tools(self) -> list[BuiltinTool]: if self.tools: return self.tools - provider = self.identity.name + provider = self.entity.identity.name tool_path = path.join(path.dirname(path.realpath(__file__)), "providers", provider, "tools") # get all the yaml files in the tool path tool_files = list(filter(lambda x: x.endswith(".yaml") and not x.startswith("__"), listdir(tool_path))) @@ -62,30 +63,36 @@ def _get_builtin_tools(self) -> list[BuiltinTool]: tool = load_yaml_file(path.join(tool_path, tool_file), ignore_error=False) # get tool class, import the module - assistant_tool_class = load_single_subclass_from_source( + assistant_tool_class: type[BuiltinTool] = load_single_subclass_from_source( module_name=f"core.tools.builtin_tool.providers.{provider}.tools.{tool_name}", script_path=path.join( - path.dirname(path.realpath(__file__)), - "builtin_tool", "providers", provider, "tools", f"{tool_name}.py" + path.dirname(path.realpath(__file__)), + "builtin_tool", + "providers", + provider, + "tools", + f"{tool_name}.py", ), parent_type=BuiltinTool, ) tool["identity"]["provider"] = provider - tools.append(assistant_tool_class(**tool)) + tools.append(assistant_tool_class( + entity=ToolEntity(**tool), runtime=ToolRuntime(tenant_id=""), + )) self.tools = tools return tools - + def get_credentials_schema(self) -> dict[str, ProviderConfig]: """ returns the credentials schema of the provider :return: the credentials schema """ - if not self.credentials_schema: + if not self.entity.credentials_schema: return {} - return self.credentials_schema.copy() + return self.entity.credentials_schema.copy() def get_tools(self) -> list[BuiltinTool]: """ @@ -94,12 +101,12 @@ def get_tools(self) -> list[BuiltinTool]: :return: list of tools """ return self._get_builtin_tools() - + def get_tool(self, tool_name: str) -> BuiltinTool | None: """ returns the tool that the provider can provide """ - return next(filter(lambda x: x.identity.name == tool_name, self.get_tools()), None) + return next(filter(lambda x: x.entity.identity.name == tool_name, self.get_tools()), None) @property def need_credentials(self) -> bool: @@ -108,7 +115,7 @@ def need_credentials(self) -> bool: :return: whether the provider needs credentials """ - return self.credentials_schema is not None and len(self.credentials_schema) != 0 + return self.entity.credentials_schema is not None and len(self.entity.credentials_schema) != 0 @property def provider_type(self) -> ToolProviderType: @@ -133,8 +140,8 @@ def _get_tool_labels(self) -> list[ToolLabelEnum]: """ returns the labels of the provider """ - return self.identity.tags or [] - + return self.entity.identity.tags or [] + def validate_credentials(self, credentials: dict[str, Any]) -> None: """ validate the credentials of the provider diff --git a/api/core/tools/builtin_tool/providers/qrcode/qrcode.py b/api/core/tools/builtin_tool/providers/qrcode/qrcode.py index 542ee7b63e9e09..e792382ee3f451 100644 --- a/api/core/tools/builtin_tool/providers/qrcode/qrcode.py +++ b/api/core/tools/builtin_tool/providers/qrcode/qrcode.py @@ -1,13 +1,8 @@ from typing import Any from core.tools.builtin_tool.provider import BuiltinToolProviderController -from core.tools.builtin_tool.providers.qrcode.tools.qrcode_generator import QRCodeGeneratorTool -from core.tools.errors import ToolProviderCredentialValidationError class QRCodeProvider(BuiltinToolProviderController): def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - QRCodeGeneratorTool().invoke(user_id="", tool_parameters={"content": "Dify 123 😊"}) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) + pass diff --git a/api/core/tools/builtin_tool/providers/time/time.py b/api/core/tools/builtin_tool/providers/time/time.py index 234ca9d9d6389b..d70fc22dfcae51 100644 --- a/api/core/tools/builtin_tool/providers/time/time.py +++ b/api/core/tools/builtin_tool/providers/time/time.py @@ -1,16 +1,8 @@ from typing import Any from core.tools.builtin_tool.provider import BuiltinToolProviderController -from core.tools.builtin_tool.providers.time.tools.current_time import CurrentTimeTool -from core.tools.errors import ToolProviderCredentialValidationError class WikiPediaProvider(BuiltinToolProviderController): def _validate_credentials(self, credentials: dict[str, Any]) -> None: - try: - CurrentTimeTool().invoke( - user_id="", - tool_parameters={}, - ) - except Exception as e: - raise ToolProviderCredentialValidationError(str(e)) + pass diff --git a/api/core/tools/builtin_tool/tool.py b/api/core/tools/builtin_tool/tool.py index 243d99dee3f36c..fe77f9ac77bc74 100644 --- a/api/core/tools/builtin_tool/tool.py +++ b/api/core/tools/builtin_tool/tool.py @@ -32,9 +32,9 @@ def invoke_model(self, user_id: str, prompt_messages: list[PromptMessage], stop: # invoke model return ModelInvocationUtils.invoke( user_id=user_id, - tenant_id=self.runtime.tenant_id or "", + tenant_id=self.runtime.tenant_id, tool_type="builtin", - tool_name=self.identity.name, + tool_name=self.entity.identity.name, prompt_messages=prompt_messages, ) @@ -79,6 +79,7 @@ def summarize(content: str) -> str: stop=[], ) + assert isinstance(summary.message.content, str) return summary.message.content lines = content.split("\n") diff --git a/api/core/tools/custom_tool/provider.py b/api/core/tools/custom_tool/provider.py index 7ebaa6c5c6fc29..32eda1d9bcda8a 100644 --- a/api/core/tools/custom_tool/provider.py +++ b/api/core/tools/custom_tool/provider.py @@ -7,6 +7,8 @@ from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( ApiProviderAuthType, + ToolProviderEntity, + ToolProviderIdentity, ToolProviderType, ) from extensions.ext_database import db @@ -18,6 +20,11 @@ class ApiToolProviderController(ToolProviderController): tenant_id: str tools: list[ApiTool] = Field(default_factory=list) + def __init__(self, entity: ToolProviderEntity, provider_id: str, tenant_id: str) -> None: + super().__init__(entity) + self.provider_id = provider_id + self.tenant_id = tenant_id + @staticmethod def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> "ApiToolProviderController": credentials_schema = { @@ -64,25 +71,23 @@ def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> "Ap } elif auth_type == ApiProviderAuthType.NONE: pass - else: - raise ValueError(f"invalid auth type {auth_type}") user = db_provider.user user_name = user.name if user else "" return ApiToolProviderController( - **{ - "identity": { - "author": user_name, - "name": db_provider.name, - "label": {"en_US": db_provider.name, "zh_Hans": db_provider.name}, - "description": {"en_US": db_provider.description, "zh_Hans": db_provider.description}, - "icon": db_provider.icon, - }, - "credentials_schema": credentials_schema, - "provider_id": db_provider.id or "", - "tenant_id": db_provider.tenant_id or "", - }, + entity=ToolProviderEntity( + identity=ToolProviderIdentity( + author=user_name, + name=db_provider.name, + label=I18nObject(en_US=db_provider.name, zh_Hans=db_provider.name), + description=I18nObject(en_US=db_provider.description, zh_Hans=db_provider.description), + icon=db_provider.icon, + ), + credentials_schema=credentials_schema, + ), + provider_id=db_provider.id or "", + tenant_id=db_provider.tenant_id or "", ) @property @@ -103,7 +108,7 @@ def _parse_tool_bundle(self, tool_bundle: ApiToolBundle) -> ApiTool: "author": tool_bundle.author, "name": tool_bundle.operation_id, "label": {"en_US": tool_bundle.operation_id, "zh_Hans": tool_bundle.operation_id}, - "icon": self.identity.icon, + "icon": self.entity.identity.icon, "provider": self.provider_id, }, "description": { @@ -141,7 +146,7 @@ def get_tools(self, tenant_id: str) -> list[ApiTool]: # get tenant api providers db_providers: list[ApiToolProvider] = ( db.session.query(ApiToolProvider) - .filter(ApiToolProvider.tenant_id == tenant_id, ApiToolProvider.name == self.identity.name) + .filter(ApiToolProvider.tenant_id == tenant_id, ApiToolProvider.name == self.entity.identity.name) .all() ) @@ -149,7 +154,6 @@ def get_tools(self, tenant_id: str) -> list[ApiTool]: for db_provider in db_providers: for tool in db_provider.tools: assistant_tool = self._parse_tool_bundle(tool) - assistant_tool.is_team_authorization = True tools.append(assistant_tool) self.tools = tools @@ -166,7 +170,7 @@ def get_tool(self, tool_name: str) -> ApiTool: self.get_tools(self.tenant_id) for tool in self.tools: - if tool.identity.name == tool_name: + if tool.entity.identity.name == tool_name: return tool raise ValueError(f"tool {tool_name} not found") diff --git a/api/core/tools/custom_tool/tool.py b/api/core/tools/custom_tool/tool.py index 9a728bb684b664..e36c97a2defcec 100644 --- a/api/core/tools/custom_tool/tool.py +++ b/api/core/tools/custom_tool/tool.py @@ -8,8 +8,9 @@ from core.helper import ssrf_proxy from core.tools.__base.tool import Tool +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.entities.tool_bundle import ApiToolBundle -from core.tools.entities.tool_entities import ToolInvokeMessage, ToolProviderType +from core.tools.entities.tool_entities import ToolEntity, ToolInvokeMessage, ToolProviderType from core.tools.errors import ToolInvokeError, ToolParameterValidationError, ToolProviderCredentialValidationError API_TOOL_DEFAULT_TIMEOUT = ( @@ -25,7 +26,11 @@ class ApiTool(Tool): Api tool """ - def fork_tool_runtime(self, runtime: dict[str, Any]) -> "Tool": + def __init__(self, entity: ToolEntity, api_bundle: ApiToolBundle, runtime: ToolRuntime): + super().__init__(entity, runtime) + self.api_bundle = api_bundle + + def fork_tool_runtime(self, runtime: ToolRuntime): """ fork a new tool with meta data @@ -33,11 +38,9 @@ def fork_tool_runtime(self, runtime: dict[str, Any]) -> "Tool": :return: the new tool """ return self.__class__( - identity=self.identity.model_copy(), - parameters=self.parameters.copy() if self.parameters else [], - description=self.description.model_copy() if self.description else None, + entity=self.entity, api_bundle=self.api_bundle.model_copy(), - runtime=Tool.Runtime(**runtime), + runtime=runtime, ) def validate_credentials( @@ -62,7 +65,7 @@ def tool_provider_type(self) -> ToolProviderType: def assembling_request(self, parameters: dict[str, Any]) -> dict[str, Any]: if self.runtime == None: raise ToolProviderCredentialValidationError("runtime not initialized") - + headers = {} credentials = self.runtime.credentials or {} diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index cc84f6eaada186..80334a274ec441 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -1,10 +1,11 @@ import base64 from enum import Enum -from typing import Any, Optional, Union, cast +from typing import Any, Optional, Union -from pydantic import BaseModel, Field, field_serializer, field_validator +from pydantic import BaseModel, ConfigDict, Field, ValidationInfo, field_serializer, field_validator from core.entities.parameter_entities import AppSelectorScope, CommonParameterType, ModelConfigScope +from core.entities.provider_entities import ProviderConfig from core.tools.entities.common_entities import I18nObject @@ -122,14 +123,14 @@ def transform_variable_value(cls, value, values) -> Any: """ if not isinstance(value, dict | list | str | int | float | bool): raise ValueError("Only basic types and lists are allowed.") - + # if stream is true, the value must be a string - if values.get('stream'): + if values.get("stream"): if not isinstance(value, str): raise ValueError("When 'stream' is True, 'variable_value' must be a string.") return value - + @field_validator("variable_name", mode="before") @classmethod def transform_variable_name(cls, value) -> str: @@ -158,22 +159,20 @@ class MessageType(Enum): meta: dict[str, Any] | None = None save_as: str = "" - @field_validator('message', mode='before') + @field_validator("message", mode="before") @classmethod def decode_blob_message(cls, v): - if isinstance(v, dict) and 'blob' in v: + if isinstance(v, dict) and "blob" in v: try: - v['blob'] = base64.b64decode(v['blob']) + v["blob"] = base64.b64decode(v["blob"]) except Exception: pass return v - @field_serializer('message') + @field_serializer("message") def serialize_message(self, v): if isinstance(v, self.BlobMessage): - return { - 'blob': base64.b64encode(v.blob).decode('utf-8') - } + return {"blob": base64.b64encode(v.blob).decode("utf-8")} return v @@ -252,9 +251,9 @@ def get_simple_instance( option_objs = [] return cls( name=name, - label=I18nObject(en_US='', zh_Hans=''), + label=I18nObject(en_US="", zh_Hans=""), placeholder=None, - human_description=I18nObject(en_US='', zh_Hans=''), + human_description=I18nObject(en_US="", zh_Hans=""), type=type, form=cls.ToolParameterForm.LLM, llm_description=llm_description, @@ -275,6 +274,11 @@ class ToolProviderIdentity(BaseModel): ) +class ToolProviderEntity(BaseModel): + identity: ToolProviderIdentity + credentials_schema: dict[str, ProviderConfig] = Field(default_factory=dict) + + class ToolDescription(BaseModel): human: I18nObject = Field(..., description="The description presented to the user") llm: str = Field(..., description="The description presented to the LLM") @@ -288,131 +292,6 @@ class ToolIdentity(BaseModel): icon: Optional[str] = None -class ToolRuntimeVariableType(Enum): - TEXT = "text" - IMAGE = "image" - - -class ToolRuntimeVariable(BaseModel): - type: ToolRuntimeVariableType = Field(..., description="The type of the variable") - name: str = Field(..., description="The name of the variable") - position: int = Field(..., description="The position of the variable") - tool_name: str = Field(..., description="The name of the tool") - - -class ToolRuntimeTextVariable(ToolRuntimeVariable): - value: str = Field(..., description="The value of the variable") - - -class ToolRuntimeImageVariable(ToolRuntimeVariable): - value: str = Field(..., description="The path of the image") - - -class ToolRuntimeVariablePool(BaseModel): - conversation_id: str = Field(..., description="The conversation id") - user_id: str = Field(..., description="The user id") - tenant_id: str = Field(..., description="The tenant id of assistant") - - pool: list[ToolRuntimeVariable] = Field(..., description="The pool of variables") - - def __init__(self, **data: Any): - pool = data.get("pool", []) - # convert pool into correct type - for index, variable in enumerate(pool): - if variable["type"] == ToolRuntimeVariableType.TEXT.value: - pool[index] = ToolRuntimeTextVariable(**variable) - elif variable["type"] == ToolRuntimeVariableType.IMAGE.value: - pool[index] = ToolRuntimeImageVariable(**variable) - super().__init__(**data) - - def dict(self) -> dict: - return { - "conversation_id": self.conversation_id, - "user_id": self.user_id, - "tenant_id": self.tenant_id, - "pool": [variable.model_dump() for variable in self.pool], - } - - def set_text(self, tool_name: str, name: str, value: str) -> None: - """ - set a text variable - """ - for variable in self.pool: - if variable.name == name: - if variable.type == ToolRuntimeVariableType.TEXT: - variable = cast(ToolRuntimeTextVariable, variable) - variable.value = value - return - - variable = ToolRuntimeTextVariable( - type=ToolRuntimeVariableType.TEXT, - name=name, - position=len(self.pool), - tool_name=tool_name, - value=value, - ) - - self.pool.append(variable) - - def set_file(self, tool_name: str, value: str, name: Optional[str] = None) -> None: - """ - set an image variable - - :param tool_name: the name of the tool - :param value: the id of the file - """ - # check how many image variables are there - image_variable_count = 0 - for variable in self.pool: - if variable.type == ToolRuntimeVariableType.IMAGE: - image_variable_count += 1 - - if name is None: - name = f"file_{image_variable_count}" - - for variable in self.pool: - if variable.name == name: - if variable.type == ToolRuntimeVariableType.IMAGE: - variable = cast(ToolRuntimeImageVariable, variable) - variable.value = value - return - - variable = ToolRuntimeImageVariable( - type=ToolRuntimeVariableType.IMAGE, - name=name, - position=len(self.pool), - tool_name=tool_name, - value=value, - ) - - self.pool.append(variable) - - -class ModelToolPropertyKey(Enum): - IMAGE_PARAMETER_NAME = "image_parameter_name" - - -class ModelToolConfiguration(BaseModel): - """ - Model tool configuration - """ - - type: str = Field(..., description="The type of the model tool") - model: str = Field(..., description="The model") - label: I18nObject = Field(..., description="The label of the model tool") - properties: dict[ModelToolPropertyKey, Any] = Field(..., description="The properties of the model tool") - - -class ModelToolProviderConfiguration(BaseModel): - """ - Model tool provider configuration - """ - - provider: str = Field(..., description="The provider of the model tool") - models: list[ModelToolConfiguration] = Field(..., description="The models of the model tool") - label: I18nObject = Field(..., description="The label of the model tool") - - class WorkflowToolParameterConfiguration(BaseModel): """ Workflow tool configuration @@ -471,3 +350,17 @@ class ToolInvokeFrom(Enum): WORKFLOW = "workflow" AGENT = "agent" + + +class ToolEntity(BaseModel): + identity: ToolIdentity + parameters: list[ToolParameter] = Field(default_factory=list) + description: Optional[ToolDescription] = None + + # pydantic configs + model_config = ConfigDict(protected_namespaces=()) + + @field_validator("parameters", mode="before") + @classmethod + def set_parameters(cls, v, validation_info: ValidationInfo) -> list[ToolParameter]: + return v or [] diff --git a/api/core/tools/tool_engine.py b/api/core/tools/tool_engine.py index cb2f6a899cd8e8..d8889917f0ded5 100644 --- a/api/core/tools/tool_engine.py +++ b/api/core/tools/tool_engine.py @@ -65,7 +65,7 @@ def agent_invoke( # invoke the tool try: # hit the callback handler - agent_tool_callback.on_tool_start(tool_name=tool.identity.name, tool_inputs=tool_parameters) + agent_tool_callback.on_tool_start(tool_name=tool.entity.identity.name, tool_inputs=tool_parameters) messages = ToolEngine._invoke(tool, tool_parameters, user_id) invocation_meta_dict: dict[str, ToolInvokeMeta] = {} @@ -99,7 +99,7 @@ def message_callback( # hit the callback handler agent_tool_callback.on_tool_end( - tool_name=tool.identity.name, + tool_name=tool.entity.identity.name, tool_inputs=tool_parameters, tool_outputs=plain_text, message_id=message.id, @@ -112,7 +112,7 @@ def message_callback( error_response = "Please check your tool provider credentials" agent_tool_callback.on_tool_error(e) except (ToolNotFoundError, ToolNotSupportedError, ToolProviderNotFoundError) as e: - error_response = f"there is not a tool named {tool.identity.name}" + error_response = f"there is not a tool named {tool.entity.identity.name}" agent_tool_callback.on_tool_error(e) except ToolParameterValidationError as e: error_response = f"tool parameters validation error: {e}, please check your tool parameters" @@ -145,7 +145,7 @@ def workflow_invoke( """ try: # hit the callback handler - workflow_tool_callback.on_tool_start(tool_name=tool.identity.name, tool_inputs=tool_parameters) + workflow_tool_callback.on_tool_start(tool_name=tool.entity.identity.name, tool_inputs=tool_parameters) if isinstance(tool, WorkflowTool): tool.workflow_call_depth = workflow_call_depth + 1 @@ -158,7 +158,7 @@ def workflow_invoke( # hit the callback handler workflow_tool_callback.on_tool_end( - tool_name=tool.identity.name, + tool_name=tool.entity.identity.name, tool_inputs=tool_parameters, tool_outputs=response, ) @@ -177,13 +177,13 @@ def plugin_invoke( """ try: # hit the callback handler - callback.on_tool_start(tool_name=tool.identity.name, tool_inputs=tool_parameters) + callback.on_tool_start(tool_name=tool.entity.identity.name, tool_inputs=tool_parameters) response = tool.invoke(user_id, tool_parameters) # hit the callback handler callback.on_tool_end( - tool_name=tool.identity.name, + tool_name=tool.entity.identity.name, tool_inputs=tool_parameters, tool_outputs=response, ) @@ -208,11 +208,11 @@ def _invoke( time_cost=0.0, error=None, tool_config={ - "tool_name": tool.identity.name, - "tool_provider": tool.identity.provider, + "tool_name": tool.entity.identity.name, + "tool_provider": tool.entity.identity.provider, "tool_provider_type": tool.tool_provider_type().value, "tool_parameters": deepcopy(tool.runtime.runtime_parameters), - "tool_icon": tool.identity.icon, + "tool_icon": tool.entity.identity.icon, }, ) try: diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 0cfcb6d9b9dbaf..c37ee730c832e9 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -6,6 +6,8 @@ from threading import Lock from typing import TYPE_CHECKING, Any, Union, cast +from core.tools.__base.tool_runtime import ToolRuntime + if TYPE_CHECKING: from core.workflow.nodes.tool.entities import ToolEntity @@ -105,12 +107,12 @@ def get_tool_runtime( return cast( BuiltinTool, builtin_tool.fork_tool_runtime( - runtime={ - "tenant_id": tenant_id, - "credentials": {}, - "invoke_from": invoke_from, - "tool_invoke_from": tool_invoke_from, - } + runtime=ToolRuntime( + tenant_id=tenant_id, + credentials={}, + invoke_from=invoke_from, + tool_invoke_from=tool_invoke_from, + ) ), ) @@ -134,7 +136,7 @@ def get_tool_runtime( tenant_id=tenant_id, config=controller.get_credentials_schema(), provider_type=controller.provider_type.value, - provider_identity=controller.identity.name, + provider_identity=controller.entity.identity.name, ) decrypted_credentials = tool_configuration.decrypt(credentials) @@ -142,13 +144,13 @@ def get_tool_runtime( return cast( BuiltinTool, builtin_tool.fork_tool_runtime( - runtime={ - "tenant_id": tenant_id, - "credentials": decrypted_credentials, - "runtime_parameters": {}, - "invoke_from": invoke_from, - "tool_invoke_from": tool_invoke_from, - } + runtime=ToolRuntime( + tenant_id=tenant_id, + credentials=decrypted_credentials, + runtime_parameters={}, + invoke_from=invoke_from, + tool_invoke_from=tool_invoke_from, + ) ), ) @@ -163,19 +165,19 @@ def get_tool_runtime( tenant_id=tenant_id, config=api_provider.get_credentials_schema(), provider_type=api_provider.provider_type.value, - provider_identity=api_provider.identity.name, + provider_identity=api_provider.entity.identity.name, ) decrypted_credentials = tool_configuration.decrypt(credentials) return cast( ApiTool, api_provider.get_tool(tool_name).fork_tool_runtime( - runtime={ - "tenant_id": tenant_id, - "credentials": decrypted_credentials, - "invoke_from": invoke_from, - "tool_invoke_from": tool_invoke_from, - } + runtime=ToolRuntime( + tenant_id=tenant_id, + credentials=decrypted_credentials, + invoke_from=invoke_from, + tool_invoke_from=tool_invoke_from, + ) ), ) elif provider_type == ToolProviderType.WORKFLOW: @@ -193,12 +195,12 @@ def get_tool_runtime( return cast( WorkflowTool, controller.get_tools(tenant_id=workflow_provider.tenant_id)[0].fork_tool_runtime( - runtime={ - "tenant_id": tenant_id, - "credentials": {}, - "invoke_from": invoke_from, - "tool_invoke_from": tool_invoke_from, - } + runtime=ToolRuntime( + tenant_id=tenant_id, + credentials={}, + invoke_from=invoke_from, + tool_invoke_from=tool_invoke_from, + ) ), ) elif provider_type == ToolProviderType.APP: @@ -336,7 +338,7 @@ def get_builtin_provider_icon(cls, provider: str) -> tuple[str, str]: "providers", provider, "_assets", - provider_controller.identity.icon, + provider_controller.entity.identity.icon, ) # check if the icon exists if not path.exists(absolute_path): @@ -389,9 +391,9 @@ def _list_builtin_providers(cls) -> Generator[BuiltinToolProviderController, Non parent_type=BuiltinToolProviderController, ) provider: BuiltinToolProviderController = provider_class() - cls._builtin_providers[provider.identity.name] = provider + cls._builtin_providers[provider.entity.identity.name] = provider for tool in provider.get_tools(): - cls._builtin_tools_labels[tool.identity.name] = tool.identity.label + cls._builtin_tools_labels[tool.entity.identity.name] = tool.entity.identity.label yield provider except Exception as e: @@ -466,11 +468,11 @@ def user_list_providers( user_provider = ToolTransformService.builtin_provider_to_user_provider( provider_controller=provider, - db_provider=find_db_builtin_provider(provider.identity.name), + db_provider=find_db_builtin_provider(provider.entity.identity.name), decrypt_credentials=False, ) - result_providers[provider.identity.name] = user_provider + result_providers[provider.entity.identity.name] = user_provider # get db api providers @@ -589,7 +591,7 @@ def user_get_api_provider(cls, provider: str, tenant_id: str) -> dict: tenant_id=tenant_id, config=controller.get_credentials_schema(), provider_type=controller.provider_type.value, - provider_identity=controller.identity.name, + provider_identity=controller.entity.identity.name, ) decrypted_credentials = tool_configuration.decrypt(credentials) diff --git a/api/core/tools/utils/configuration.py b/api/core/tools/utils/configuration.py index 0ab2b0021a36dd..9f685a89b6a627 100644 --- a/api/core/tools/utils/configuration.py +++ b/api/core/tools/utils/configuration.py @@ -59,12 +59,11 @@ def mask_tool_credentials(self, data: dict[str, Any]) -> dict[str, Any]: if field.type == BasicProviderConfig.Type.SECRET_INPUT: if field_name in data: if len(data[field_name]) > 6: - data[field_name] = \ - data[field_name][:2] + \ - '*' * (len(data[field_name]) - 4) + \ - data[field_name][-2:] + data[field_name] = ( + data[field_name][:2] + "*" * (len(data[field_name]) - 4) + data[field_name][-2:] + ) else: - data[field_name] = '*' * len(data[field_name]) + data[field_name] = "*" * len(data[field_name]) return data @@ -75,9 +74,9 @@ def decrypt(self, data: dict[str, str]) -> dict[str, str]: return a deep copy of credentials with decrypted values """ cache = ToolProviderCredentialsCache( - tenant_id=self.tenant_id, - identity_id=f'{self.provider_type}.{self.provider_identity}', - cache_type=ToolProviderCredentialsCacheType.PROVIDER + tenant_id=self.tenant_id, + identity_id=f"{self.provider_type}.{self.provider_identity}", + cache_type=ToolProviderCredentialsCacheType.PROVIDER, ) cached_credentials = cache.get() if cached_credentials: @@ -98,14 +97,14 @@ def decrypt(self, data: dict[str, str]) -> dict[str, str]: def delete_tool_credentials_cache(self): cache = ToolProviderCredentialsCache( - tenant_id=self.tenant_id, - identity_id=f'{self.provider_type}.{self.provider_identity}', - cache_type=ToolProviderCredentialsCacheType.PROVIDER + tenant_id=self.tenant_id, + identity_id=f"{self.provider_type}.{self.provider_identity}", + cache_type=ToolProviderCredentialsCacheType.PROVIDER, ) cache.delete() -class ToolParameterConfigurationManager(BaseModel): +class ToolParameterConfigurationManager: """ Tool parameter configuration manager """ @@ -116,6 +115,15 @@ class ToolParameterConfigurationManager(BaseModel): provider_type: ToolProviderType identity_id: str + def __init__( + self, tenant_id: str, tool_runtime: Tool, provider_name: str, provider_type: ToolProviderType, identity_id: str + ) -> None: + self.tenant_id = tenant_id + self.tool_runtime = tool_runtime + self.provider_name = provider_name + self.provider_type = provider_type + self.identity_id = identity_id + def _deep_copy(self, parameters: dict[str, Any]) -> dict[str, Any]: """ deep copy parameters @@ -127,7 +135,7 @@ def _merge_parameters(self) -> list[ToolParameter]: merge parameters """ # get tool parameters - tool_parameters = self.tool_runtime.parameters or [] + tool_parameters = self.tool_runtime.entity.parameters or [] # get tool runtime parameters runtime_parameters = self.tool_runtime.get_runtime_parameters() or [] # override parameters @@ -203,8 +211,8 @@ def decrypt_tool_parameters(self, parameters: dict[str, Any]) -> dict[str, Any]: """ cache = ToolParameterCache( tenant_id=self.tenant_id, - provider=f'{self.provider_type.value}.{self.provider_name}', - tool_name=self.tool_runtime.identity.name, + provider=f"{self.provider_type.value}.{self.provider_name}", + tool_name=self.tool_runtime.entity.identity.name, cache_type=ToolParameterCacheType.PARAMETER, identity_id=self.identity_id, ) @@ -236,8 +244,8 @@ def decrypt_tool_parameters(self, parameters: dict[str, Any]) -> dict[str, Any]: def delete_tool_parameters_cache(self): cache = ToolParameterCache( tenant_id=self.tenant_id, - provider=f'{self.provider_type.value}.{self.provider_name}', - tool_name=self.tool_runtime.identity.name, + provider=f"{self.provider_type.value}.{self.provider_name}", + tool_name=self.tool_runtime.entity.identity.name, cache_type=ToolParameterCacheType.PARAMETER, identity_id=self.identity_id, ) diff --git a/api/core/tools/utils/dataset_retriever_tool.py b/api/core/tools/utils/dataset_retriever_tool.py index 7b612227227dc4..136491005c38a2 100644 --- a/api/core/tools/utils/dataset_retriever_tool.py +++ b/api/core/tools/utils/dataset_retriever_tool.py @@ -6,9 +6,11 @@ from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler from core.rag.retrieval.dataset_retrieval import DatasetRetrieval from core.tools.__base.tool import Tool +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ( ToolDescription, + ToolEntity, ToolIdentity, ToolInvokeMessage, ToolParameter, @@ -20,11 +22,15 @@ class DatasetRetrieverTool(Tool): retrieval_tool: DatasetRetrieverBaseTool + def __init__(self, entity: ToolEntity, runtime: ToolRuntime, retrieval_tool: DatasetRetrieverBaseTool) -> None: + super().__init__(entity, runtime) + self.retrieval_tool = retrieval_tool + @staticmethod def get_dataset_tools( tenant_id: str, dataset_ids: list[str], - retrieve_config: DatasetRetrieveConfigEntity, + retrieve_config: DatasetRetrieveConfigEntity | None, return_resource: bool, invoke_from: InvokeFrom, hit_callback: DatasetIndexToolCallbackHandler, @@ -54,7 +60,7 @@ def get_dataset_tools( ) if retrieval_tools is None or len(retrieval_tools) == 0: return [] - + # restore retrieve strategy retrieve_config.retrieve_strategy = original_retriever_mode @@ -63,13 +69,14 @@ def get_dataset_tools( for retrieval_tool in retrieval_tools: tool = DatasetRetrieverTool( retrieval_tool=retrieval_tool, - identity=ToolIdentity( - provider="", author="", name=retrieval_tool.name, label=I18nObject(en_US="", zh_Hans="") + entity=ToolEntity( + identity=ToolIdentity( + provider="", author="", name=retrieval_tool.name, label=I18nObject(en_US="", zh_Hans="") + ), + parameters=[], + description=ToolDescription(human=I18nObject(en_US="", zh_Hans=""), llm=retrieval_tool.description), ), - parameters=[], - is_team_authorization=True, - description=ToolDescription(human=I18nObject(en_US="", zh_Hans=""), llm=retrieval_tool.description), - runtime=DatasetRetrieverTool.Runtime(), + runtime=ToolRuntime(tenant_id=tenant_id), ) tools.append(tool) @@ -99,7 +106,7 @@ def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[To """ query = tool_parameters.get("query") if not query: - yield self.create_text_message(text='please input query') + yield self.create_text_message(text="please input query") else: # invoke dataset retriever tool result = self.retrieval_tool._run(query=query) diff --git a/api/core/tools/workflow_as_tool/provider.py b/api/core/tools/workflow_as_tool/provider.py index cab5f84506d1c0..2d0d33ffd9a138 100644 --- a/api/core/tools/workflow_as_tool/provider.py +++ b/api/core/tools/workflow_as_tool/provider.py @@ -6,9 +6,11 @@ from core.app.app_config.entities import VariableEntity, VariableEntityType from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager from core.tools.__base.tool_provider import ToolProviderController +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ( ToolDescription, + ToolEntity, ToolIdentity, ToolParameter, ToolParameterOption, @@ -63,7 +65,7 @@ def from_db(cls, db_provider: WorkflowToolProvider) -> "WorkflowToolProviderCont @property def provider_type(self) -> ToolProviderType: return ToolProviderType.WORKFLOW - + def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> WorkflowTool: """ get db provider tool @@ -140,19 +142,23 @@ def fetch_workflow_variable(variable_name: str) -> VariableEntity | None: raise ValueError("variable not found") return WorkflowTool( - identity=ToolIdentity( - author=user.name if user else "", - name=db_provider.name, - label=I18nObject(en_US=db_provider.label, zh_Hans=db_provider.label), - provider=self.provider_id, - icon=db_provider.icon, + entity=ToolEntity( + identity=ToolIdentity( + author=user.name if user else "", + name=db_provider.name, + label=I18nObject(en_US=db_provider.label, zh_Hans=db_provider.label), + provider=self.provider_id, + icon=db_provider.icon, + ), + description=ToolDescription( + human=I18nObject(en_US=db_provider.description, zh_Hans=db_provider.description), + llm=db_provider.description, + ), + parameters=workflow_tool_parameters, ), - description=ToolDescription( - human=I18nObject(en_US=db_provider.description, zh_Hans=db_provider.description), - llm=db_provider.description, + runtime=ToolRuntime( + tenant_id=db_provider.tenant_id, ), - parameters=workflow_tool_parameters, - is_team_authorization=True, workflow_app_id=app.id, workflow_entities={ "app": app, @@ -201,7 +207,7 @@ def get_tool(self, tool_name: str) -> Optional[WorkflowTool]: return None for tool in self.tools: - if tool.identity.name == tool_name: + if tool.entity.identity.name == tool_name: return tool return None diff --git a/api/core/tools/workflow_as_tool/tool.py b/api/core/tools/workflow_as_tool/tool.py index 72aae2796c893b..e1fc5140d0d72a 100644 --- a/api/core/tools/workflow_as_tool/tool.py +++ b/api/core/tools/workflow_as_tool/tool.py @@ -1,12 +1,12 @@ import json import logging from collections.abc import Generator -from copy import deepcopy from typing import Any, Optional, Union from core.file.file_obj import FileTransferMethod, FileVar from core.tools.__base.tool import Tool -from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter, ToolProviderType +from core.tools.__base.tool_runtime import ToolRuntime +from core.tools.entities.tool_entities import ToolEntity, ToolInvokeMessage, ToolParameter, ToolProviderType from extensions.ext_database import db from models.account import Account from models.model import App, EndUser @@ -28,6 +28,26 @@ class WorkflowTool(Tool): Workflow tool. """ + def __init__( + self, + workflow_app_id: str, + version: str, + workflow_entities: dict[str, Any], + workflow_call_depth: int, + entity: ToolEntity, + runtime: ToolRuntime, + label: str = "Workflow", + thread_pool_id: Optional[str] = None, + ): + self.workflow_app_id = workflow_app_id + self.version = version + self.workflow_entities = workflow_entities + self.workflow_call_depth = workflow_call_depth + self.thread_pool_id = thread_pool_id + self.label = label + + super().__init__(entity=entity, runtime=runtime) + def tool_provider_type(self) -> ToolProviderType: """ get the tool provider type @@ -94,7 +114,7 @@ def _get_user(self, user_id: str) -> Union[EndUser, Account]: return user - def fork_tool_runtime(self, runtime: dict[str, Any]) -> "WorkflowTool": + def fork_tool_runtime(self, runtime: ToolRuntime) -> "WorkflowTool": """ fork a new tool with meta data @@ -102,10 +122,8 @@ def fork_tool_runtime(self, runtime: dict[str, Any]) -> "WorkflowTool": :return: the new tool """ return self.__class__( - identity=deepcopy(self.identity), - parameters=deepcopy(self.parameters), - description=deepcopy(self.description), - runtime=Tool.Runtime(**runtime), + entity=self.entity.model_copy(), + runtime=runtime, workflow_app_id=self.workflow_app_id, workflow_entities=self.workflow_entities, workflow_call_depth=self.workflow_call_depth, diff --git a/api/core/tools/workflow_as_tool/workflow_tool_provider.py b/api/core/tools/workflow_as_tool/workflow_tool_provider.py deleted file mode 100644 index cab5f84506d1c0..00000000000000 --- a/api/core/tools/workflow_as_tool/workflow_tool_provider.py +++ /dev/null @@ -1,207 +0,0 @@ -from collections.abc import Mapping -from typing import Optional - -from pydantic import Field - -from core.app.app_config.entities import VariableEntity, VariableEntityType -from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager -from core.tools.__base.tool_provider import ToolProviderController -from core.tools.entities.common_entities import I18nObject -from core.tools.entities.tool_entities import ( - ToolDescription, - ToolIdentity, - ToolParameter, - ToolParameterOption, - ToolProviderType, -) -from core.tools.utils.workflow_configuration_sync import WorkflowToolConfigurationUtils -from core.tools.workflow_as_tool.tool import WorkflowTool -from extensions.ext_database import db -from models.model import App, AppMode -from models.tools import WorkflowToolProvider -from models.workflow import Workflow - -VARIABLE_TO_PARAMETER_TYPE_MAPPING = { - VariableEntityType.TEXT_INPUT: ToolParameter.ToolParameterType.STRING, - VariableEntityType.PARAGRAPH: ToolParameter.ToolParameterType.STRING, - VariableEntityType.SELECT: ToolParameter.ToolParameterType.SELECT, - VariableEntityType.NUMBER: ToolParameter.ToolParameterType.NUMBER, -} - - -class WorkflowToolProviderController(ToolProviderController): - provider_id: str - tools: list[WorkflowTool] = Field(default_factory=list) - - @classmethod - def from_db(cls, db_provider: WorkflowToolProvider) -> "WorkflowToolProviderController": - app = db_provider.app - - if not app: - raise ValueError("app not found") - - controller = WorkflowToolProviderController( - **{ - "identity": { - "author": db_provider.user.name if db_provider.user_id and db_provider.user else "", - "name": db_provider.label, - "label": {"en_US": db_provider.label, "zh_Hans": db_provider.label}, - "description": {"en_US": db_provider.description, "zh_Hans": db_provider.description}, - "icon": db_provider.icon, - }, - "credentials_schema": {}, - "provider_id": db_provider.id or "", - } - ) - - # init tools - - controller.tools = [controller._get_db_provider_tool(db_provider, app)] - - return controller - - @property - def provider_type(self) -> ToolProviderType: - return ToolProviderType.WORKFLOW - - def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> WorkflowTool: - """ - get db provider tool - :param db_provider: the db provider - :param app: the app - :return: the tool - """ - workflow: Workflow | None = db.session.query(Workflow).filter( - Workflow.app_id == db_provider.app_id, - Workflow.version == db_provider.version - ).first() - - if not workflow: - raise ValueError("workflow not found") - - # fetch start node - graph: Mapping = workflow.graph_dict - features_dict: Mapping = workflow.features_dict - features = WorkflowAppConfigManager.convert_features( - config_dict=features_dict, - app_mode=AppMode.WORKFLOW - ) - - parameters = db_provider.parameter_configurations - variables = WorkflowToolConfigurationUtils.get_workflow_graph_variables(graph) - - def fetch_workflow_variable(variable_name: str) -> VariableEntity | None: - return next(filter(lambda x: x.variable == variable_name, variables), None) - - user = db_provider.user - - workflow_tool_parameters = [] - for parameter in parameters: - variable = fetch_workflow_variable(parameter.name) - if variable: - parameter_type = None - options = [] - if variable.type not in VARIABLE_TO_PARAMETER_TYPE_MAPPING: - raise ValueError(f"unsupported variable type {variable.type}") - parameter_type = VARIABLE_TO_PARAMETER_TYPE_MAPPING[variable.type] - - if variable.type == VariableEntityType.SELECT and variable.options: - options = [ - ToolParameterOption(value=option, label=I18nObject(en_US=option, zh_Hans=option)) - for option in variable.options - ] - - workflow_tool_parameters.append( - ToolParameter( - name=parameter.name, - label=I18nObject(en_US=variable.label, zh_Hans=variable.label), - human_description=I18nObject(en_US=parameter.description, zh_Hans=parameter.description), - type=parameter_type, - form=parameter.form, - llm_description=parameter.description, - required=variable.required, - options=options, - default=variable.default, - ) - ) - elif features.file_upload: - workflow_tool_parameters.append( - ToolParameter( - name=parameter.name, - label=I18nObject(en_US=parameter.name, zh_Hans=parameter.name), - human_description=I18nObject(en_US=parameter.description, zh_Hans=parameter.description), - type=ToolParameter.ToolParameterType.FILE, - llm_description=parameter.description, - required=False, - form=parameter.form, - ) - ) - else: - raise ValueError("variable not found") - - return WorkflowTool( - identity=ToolIdentity( - author=user.name if user else "", - name=db_provider.name, - label=I18nObject(en_US=db_provider.label, zh_Hans=db_provider.label), - provider=self.provider_id, - icon=db_provider.icon, - ), - description=ToolDescription( - human=I18nObject(en_US=db_provider.description, zh_Hans=db_provider.description), - llm=db_provider.description, - ), - parameters=workflow_tool_parameters, - is_team_authorization=True, - workflow_app_id=app.id, - workflow_entities={ - "app": app, - "workflow": workflow, - }, - version=db_provider.version, - workflow_call_depth=0, - label=db_provider.label, - ) - - def get_tools(self, tenant_id: str) -> list[WorkflowTool]: - """ - fetch tools from database - - :param user_id: the user id - :param tenant_id: the tenant id - :return: the tools - """ - if self.tools is not None: - return self.tools - - db_providers: WorkflowToolProvider | None = db.session.query(WorkflowToolProvider).filter( - WorkflowToolProvider.tenant_id == tenant_id, - WorkflowToolProvider.app_id == self.provider_id, - ).first() - - if not db_providers: - return [] - - app = db_providers.app - if not app: - raise ValueError("can not read app of workflow") - - self.tools = [self._get_db_provider_tool(db_providers, app)] - - return self.tools - - def get_tool(self, tool_name: str) -> Optional[WorkflowTool]: - """ - get tool by name - - :param tool_name: the name of the tool - :return: the tool - """ - if self.tools is None: - return None - - for tool in self.tools: - if tool.identity.name == tool_name: - return tool - - return None diff --git a/api/models/model.py b/api/models/model.py index f4e768684900be..26b42963ccbc93 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -1304,7 +1304,7 @@ class MessageChain(db.Model): created_at = db.Column(db.DateTime, nullable=False, server_default=db.func.current_timestamp()) -class MessageAgentThought(db.Model): +class MessageAgentThought(Base): __tablename__ = "message_agent_thoughts" __table_args__ = ( db.PrimaryKeyConstraint("id", name="message_agent_thought_pkey"), diff --git a/api/services/tools/api_tools_manage_service.py b/api/services/tools/api_tools_manage_service.py index 11aa3ba529f605..e39c2b8a5bc83e 100644 --- a/api/services/tools/api_tools_manage_service.py +++ b/api/services/tools/api_tools_manage_service.py @@ -5,6 +5,7 @@ from core.entities.provider_entities import ProviderConfig from core.model_runtime.utils.encoders import jsonable_encoder +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.custom_tool.provider import ApiToolProviderController from core.tools.entities.api_entities import UserTool, UserToolProvider from core.tools.entities.common_entities import I18nObject @@ -160,7 +161,7 @@ def create_api_tool_provider( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name + provider_identity=provider_controller.entity.identity.name ) encrypted_credentials = tool_configuration.encrypt(credentials) @@ -222,6 +223,7 @@ def list_api_tool_provider_tools(user_id: str, tenant_id: str, provider_name: st return [ ToolTransformService.tool_to_user_tool( tool_bundle, + tenant_id=tenant_id, labels=labels, ) for tool_bundle in provider.tools @@ -291,7 +293,7 @@ def update_api_tool_provider( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name + provider_identity=provider_controller.entity.identity.name ) original_credentials = tool_configuration.decrypt(provider.credentials) @@ -410,7 +412,7 @@ def test_api_tool_preview( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name + provider_identity=provider_controller.entity.identity.name ) decrypted_credentials = tool_configuration.decrypt(credentials) # check if the credential has changed, save the original credential @@ -424,10 +426,10 @@ def test_api_tool_preview( # get tool tool = provider_controller.get_tool(tool_name) tool = tool.fork_tool_runtime( - runtime={ - "credentials": credentials, - "tenant_id": tenant_id, - } + runtime=ToolRuntime( + credentials=credentials, + tenant_id=tenant_id, + ) ) result = tool.validate_credentials(credentials, parameters) except Exception as e: diff --git a/api/services/tools/builtin_tools_manage_service.py b/api/services/tools/builtin_tools_manage_service.py index 6db8718b6b46c0..83b363bb580588 100644 --- a/api/services/tools/builtin_tools_manage_service.py +++ b/api/services/tools/builtin_tools_manage_service.py @@ -32,7 +32,7 @@ def list_builtin_tool_provider_tools(user_id: str, tenant_id: str, provider: str tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name, + provider_identity=provider_controller.entity.identity.name, ) # check if user has added the provider builtin_provider: BuiltinToolProvider | None = ( @@ -71,7 +71,7 @@ def list_builtin_provider_credentials_schema(provider_name): :return: the list of tool providers """ provider = ToolManager.get_builtin_provider(provider_name) - return jsonable_encoder([v for _, v in (provider.credentials_schema or {}).items()]) + return jsonable_encoder([v for _, v in (provider.entity.credentials_schema or {}).items()]) @staticmethod def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: str, credentials: dict): @@ -97,7 +97,7 @@ def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name, + provider_identity=provider_controller.entity.identity.name, ) # get original credentials if exists @@ -159,7 +159,7 @@ def get_builtin_tool_provider_credentials(user_id: str, tenant_id: str, provider tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name, + provider_identity=provider_controller.entity.identity.name, ) credentials = tool_configuration.decrypt(provider_obj.credentials) credentials = tool_configuration.mask_tool_credentials(credentials) @@ -191,7 +191,7 @@ def delete_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name, + provider_identity=provider_controller.entity.identity.name, ) tool_configuration.delete_tool_credentials_cache() @@ -241,7 +241,7 @@ def list_builtin_tools(user_id: str, tenant_id: str) -> list[UserToolProvider]: # convert provider controller to user provider user_builtin_provider = ToolTransformService.builtin_provider_to_user_provider( provider_controller=provider_controller, - db_provider=find_provider(provider_controller.identity.name), + db_provider=find_provider(provider_controller.entity.identity.name), decrypt_credentials=True, ) diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index b7488621c643cb..d4f132e902d08e 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -4,6 +4,7 @@ from configs import dify_config from core.tools.__base.tool import Tool +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.builtin_tool.provider import BuiltinToolProviderController from core.tools.custom_tool.provider import ApiToolProviderController from core.tools.entities.api_entities import UserTool, UserToolProvider @@ -69,19 +70,19 @@ def builtin_provider_to_user_provider( convert provider controller to user provider """ result = UserToolProvider( - id=provider_controller.identity.name, - author=provider_controller.identity.author, - name=provider_controller.identity.name, + id=provider_controller.entity.identity.name, + author=provider_controller.entity.identity.author, + name=provider_controller.entity.identity.name, description=I18nObject( - en_US=provider_controller.identity.description.en_US, - zh_Hans=provider_controller.identity.description.zh_Hans, - pt_BR=provider_controller.identity.description.pt_BR, + en_US=provider_controller.entity.identity.description.en_US, + zh_Hans=provider_controller.entity.identity.description.zh_Hans, + pt_BR=provider_controller.entity.identity.description.pt_BR, ), - icon=provider_controller.identity.icon, + icon=provider_controller.entity.identity.icon, label=I18nObject( - en_US=provider_controller.identity.label.en_US, - zh_Hans=provider_controller.identity.label.zh_Hans, - pt_BR=provider_controller.identity.label.pt_BR, + en_US=provider_controller.entity.identity.label.en_US, + zh_Hans=provider_controller.entity.identity.label.zh_Hans, + pt_BR=provider_controller.entity.identity.label.pt_BR, ), type=ToolProviderType.BUILT_IN, masked_credentials={}, @@ -111,7 +112,7 @@ def builtin_provider_to_user_provider( tenant_id=db_provider.tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name + provider_identity=provider_controller.entity.identity.name, ) # decrypt the credentials and mask the credentials decrypted_credentials = tool_configuration.decrypt(data=credentials) @@ -155,16 +156,16 @@ def workflow_provider_to_user_provider( """ return UserToolProvider( id=provider_controller.provider_id, - author=provider_controller.identity.author, - name=provider_controller.identity.name, + author=provider_controller.entity.identity.author, + name=provider_controller.entity.identity.name, description=I18nObject( - en_US=provider_controller.identity.description.en_US, - zh_Hans=provider_controller.identity.description.zh_Hans, + en_US=provider_controller.entity.identity.description.en_US, + zh_Hans=provider_controller.entity.identity.description.zh_Hans, ), - icon=provider_controller.identity.icon, + icon=provider_controller.entity.identity.icon, label=I18nObject( - en_US=provider_controller.identity.label.en_US, - zh_Hans=provider_controller.identity.label.zh_Hans, + en_US=provider_controller.entity.identity.label.en_US, + zh_Hans=provider_controller.entity.identity.label.zh_Hans, ), type=ToolProviderType.WORKFLOW, masked_credentials={}, @@ -189,7 +190,7 @@ def api_provider_to_user_provider( user = db_provider.user if not user: raise ValueError("user not found") - + username = user.name except Exception as e: logger.error(f"failed to get user name for api provider {db_provider.id}: {str(e)}") @@ -222,7 +223,7 @@ def api_provider_to_user_provider( tenant_id=db_provider.tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.identity.name + provider_identity=provider_controller.entity.identity.name, ) # decrypt the credentials and mask the credentials @@ -236,8 +237,8 @@ def api_provider_to_user_provider( @staticmethod def tool_to_user_tool( tool: Union[ApiToolBundle, WorkflowTool, Tool], + tenant_id: str, credentials: dict | None = None, - tenant_id: str | None = None, labels: list[str] | None = None, ) -> UserTool: """ @@ -246,14 +247,14 @@ def tool_to_user_tool( if isinstance(tool, Tool): # fork tool runtime tool = tool.fork_tool_runtime( - runtime={ - "credentials": credentials, - "tenant_id": tenant_id, - } + runtime=ToolRuntime( + credentials=credentials, + tenant_id=tenant_id, + ) ) # get tool parameters - parameters = tool.parameters or [] + parameters = tool.entity.parameters or [] # get tool runtime parameters runtime_parameters = tool.get_runtime_parameters() or [] # override parameters @@ -270,10 +271,10 @@ def tool_to_user_tool( current_parameters.append(runtime_parameter) return UserTool( - author=tool.identity.author, - name=tool.identity.name, - label=tool.identity.label, - description=tool.description.human if tool.description else I18nObject(en_US=''), + author=tool.entity.identity.author, + name=tool.entity.identity.name, + label=tool.entity.identity.label, + description=tool.entity.description.human if tool.entity.description else I18nObject(en_US=""), parameters=current_parameters, labels=labels or [], ) diff --git a/api/services/tools/workflow_tools_manage_service.py b/api/services/tools/workflow_tools_manage_service.py index 60e26aa28281ec..58bf7946bf190f 100644 --- a/api/services/tools/workflow_tools_manage_service.py +++ b/api/services/tools/workflow_tools_manage_service.py @@ -211,7 +211,9 @@ def list_tenant_workflow_tools(cls, user_id: str, tenant_id: str) -> list[UserTo ToolTransformService.repack_provider(user_tool_provider) user_tool_provider.tools = [ ToolTransformService.tool_to_user_tool( - tool.get_tools(user_id, tenant_id)[0], labels=labels.get(tool.provider_id, []) + tool=tool.get_tools(user_id, tenant_id)[0], + labels=labels.get(tool.provider_id, []), + tenant_id=tenant_id, ) ] result.append(user_tool_provider) @@ -248,7 +250,7 @@ def get_workflow_tool_by_tool_id(cls, user_id: str, tenant_id: str, workflow_too .filter(WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.id == workflow_tool_id) .first() ) - return cls._get_workflow_tool(db_tool) + return cls._get_workflow_tool(tenant_id, db_tool) @classmethod def get_workflow_tool_by_app_id(cls, user_id: str, tenant_id: str, workflow_app_id: str) -> dict: @@ -264,10 +266,10 @@ def get_workflow_tool_by_app_id(cls, user_id: str, tenant_id: str, workflow_app_ .filter(WorkflowToolProvider.tenant_id == tenant_id, WorkflowToolProvider.app_id == workflow_app_id) .first() ) - return cls._get_workflow_tool(db_tool) + return cls._get_workflow_tool(tenant_id, db_tool) @classmethod - def _get_workflow_tool(cls, db_tool: WorkflowToolProvider | None): + def _get_workflow_tool(cls, tenant_id: str, db_tool: WorkflowToolProvider | None): """ Get a workflow tool. :db_tool: the database tool @@ -298,7 +300,9 @@ def _get_workflow_tool(cls, db_tool: WorkflowToolProvider | None): "description": db_tool.description, "parameters": jsonable_encoder(db_tool.parameter_configurations), "tool": ToolTransformService.tool_to_user_tool( - tool.get_tools(db_tool.tenant_id)[0], labels=ToolLabelManager.get_tool_labels(tool) + tool=tool.get_tools(db_tool.tenant_id)[0], + labels=ToolLabelManager.get_tool_labels(tool), + tenant_id=tenant_id, ), "synced": workflow.version == db_tool.version, "privacy_policy": db_tool.privacy_policy, @@ -326,6 +330,8 @@ def list_single_workflow_tools(cls, user_id: str, tenant_id: str, workflow_tool_ return [ ToolTransformService.tool_to_user_tool( - tool=tool.get_tools(db_tool.tenant_id)[0], labels=ToolLabelManager.get_tool_labels(tool) + tool=tool.get_tools(db_tool.tenant_id)[0], + labels=ToolLabelManager.get_tool_labels(tool), + tenant_id=tenant_id, ) ] diff --git a/api/tests/integration_tests/tools/api_tool/test_api_tool.py b/api/tests/integration_tests/tools/api_tool/test_api_tool.py index e4798e02c38148..b945d3fef7b697 100644 --- a/api/tests/integration_tests/tools/api_tool/test_api_tool.py +++ b/api/tests/integration_tests/tools/api_tool/test_api_tool.py @@ -1,5 +1,9 @@ from core.tools.__base.tool import Tool +from core.tools.__base.tool_runtime import ToolRuntime from core.tools.custom_tool.tool import ApiTool +from core.tools.entities.common_entities import I18nObject +from core.tools.entities.tool_bundle import ApiToolBundle +from core.tools.entities.tool_entities import ToolEntity, ToolIdentity from tests.integration_tests.tools.__mock.http import setup_http_mock tool_bundle = { @@ -29,7 +33,13 @@ def test_api_tool(setup_http_mock): - tool = ApiTool(api_bundle=tool_bundle, runtime=Tool.Runtime(credentials={"auth_type": "none"})) + tool = ApiTool( + entity=ToolEntity( + identity=ToolIdentity(provider="", author="", name="", label=I18nObject()), + ), + api_bundle=ApiToolBundle(**tool_bundle), + runtime=ToolRuntime(tenant_id="", credentials={"auth_type": "none"}), + ) headers = tool.assembling_request(parameters) response = tool.do_http_request(tool.api_bundle.server_url, tool.api_bundle.method, headers, parameters) From 435e71eb60f319d48f69dfca93e2316329c189e7 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Mon, 23 Sep 2024 13:09:46 +0800 Subject: [PATCH 040/325] refactor --- api/core/plugin/entities/plugin_daemon.py | 2 +- api/core/plugin/manager/base.py | 49 ++++++++++---- api/core/plugin/manager/model.py | 10 ++- api/core/plugin/manager/plugin.py | 15 ++--- api/core/plugin/manager/tool.py | 8 ++- api/core/tools/entities/tool_entities.py | 44 +++++++------ api/tests/integration_tests/.env.example | 5 ++ .../integration_tests/plugin/__mock/http.py | 66 +++++++++++++++++++ .../plugin/tools/test_fetch_all_tools.py | 9 +++ .../tools/test_all_provider.py | 23 ------- 10 files changed, 164 insertions(+), 67 deletions(-) create mode 100644 api/tests/integration_tests/plugin/__mock/http.py create mode 100644 api/tests/integration_tests/plugin/tools/test_fetch_all_tools.py delete mode 100644 api/tests/integration_tests/tools/test_all_provider.py diff --git a/api/core/plugin/entities/plugin_daemon.py b/api/core/plugin/entities/plugin_daemon.py index 63c839a4e4a5d5..0c710c87161c39 100644 --- a/api/core/plugin/entities/plugin_daemon.py +++ b/api/core/plugin/entities/plugin_daemon.py @@ -3,7 +3,7 @@ from pydantic import BaseModel -T = TypeVar("T", bound=(BaseModel | dict | bool)) +T = TypeVar("T", bound=(BaseModel | dict | list | bool)) class PluginDaemonBasicResponse(BaseModel, Generic[T]): diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index f6b44d05dd264d..3f6a87dca8b8e0 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -12,7 +12,7 @@ plugin_daemon_inner_api_baseurl = dify_config.PLUGIN_API_URL plugin_daemon_inner_api_key = dify_config.PLUGIN_API_KEY -T = TypeVar("T", bound=(BaseModel | dict | bool)) +T = TypeVar("T", bound=(BaseModel | dict | list | bool)) class BasePluginManager: @@ -22,6 +22,7 @@ def _request( path: str, headers: dict | None = None, data: bytes | dict | None = None, + params: dict | None = None, stream: bool = False, ) -> requests.Response: """ @@ -30,16 +31,23 @@ def _request( url = URL(str(plugin_daemon_inner_api_baseurl)) / path headers = headers or {} headers["X-Api-Key"] = plugin_daemon_inner_api_key - response = requests.request(method=method, url=str(url), headers=headers, data=data, stream=stream) + response = requests.request( + method=method, url=str(url), headers=headers, data=data, params=params, stream=stream + ) return response def _stream_request( - self, method: str, path: str, headers: dict | None = None, data: bytes | dict | None = None + self, + method: str, + path: str, + params: dict | None = None, + headers: dict | None = None, + data: bytes | dict | None = None, ) -> Generator[bytes, None, None]: """ Make a stream request to the plugin daemon inner API """ - response = self._request(method, path, headers, data, stream=True) + response = self._request(method, path, headers, data, params, stream=True) yield from response.iter_lines() def _stream_request_with_model( @@ -49,29 +57,42 @@ def _stream_request_with_model( type: type[T], headers: dict | None = None, data: bytes | dict | None = None, + params: dict | None = None, ) -> Generator[T, None, None]: """ Make a stream request to the plugin daemon inner API and yield the response as a model. """ - for line in self._stream_request(method, path, headers, data): + for line in self._stream_request(method, path, params, headers, data): yield type(**json.loads(line)) def _request_with_model( - self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | None = None + self, + method: str, + path: str, + type: type[T], + headers: dict | None = None, + data: bytes | None = None, + params: dict | None = None, ) -> T: """ Make a request to the plugin daemon inner API and return the response as a model. """ - response = self._request(method, path, headers, data) + response = self._request(method, path, headers, data, params) return type(**response.json()) def _request_with_plugin_daemon_response( - self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | dict | None = None + self, + method: str, + path: str, + type: type[T], + headers: dict | None = None, + data: bytes | dict | None = None, + params: dict | None = None, ) -> T: """ Make a request to the plugin daemon inner API and return the response as a model. """ - response = self._request(method, path, headers, data) + response = self._request(method, path, headers, data, params) rep = PluginDaemonBasicResponse[type](**response.json()) if rep.code != 0: raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") @@ -81,12 +102,18 @@ def _request_with_plugin_daemon_response( return rep.data def _request_with_plugin_daemon_response_stream( - self, method: str, path: str, type: type[T], headers: dict | None = None, data: bytes | dict | None = None + self, + method: str, + path: str, + type: type[T], + headers: dict | None = None, + data: bytes | dict | None = None, + params: dict | None = None, ) -> Generator[T, None, None]: """ Make a stream request to the plugin daemon inner API and yield the response as a model. """ - for line in self._stream_request(method, path, headers, data): + for line in self._stream_request(method, path, params, headers, data): line_data = json.loads(line) rep = PluginDaemonBasicResponse[type](**line_data) if rep.code != 0: diff --git a/api/core/plugin/manager/model.py b/api/core/plugin/manager/model.py index f03dbfd1e33100..4411d76fe10079 100644 --- a/api/core/plugin/manager/model.py +++ b/api/core/plugin/manager/model.py @@ -1,5 +1,13 @@ +from core.model_runtime.entities.provider_entities import ProviderEntity from core.plugin.manager.base import BasePluginManager class PluginModelManager(BasePluginManager): - pass \ No newline at end of file + def fetch_model_providers(self, tenant_id: str) -> list[ProviderEntity]: + """ + Fetch model providers for the given tenant. + """ + response = self._request_with_plugin_daemon_response( + "GET", f"plugin/{tenant_id}/models", list[ProviderEntity], params={"page": 1, "page_size": 256} + ) + return response diff --git a/api/core/plugin/manager/plugin.py b/api/core/plugin/manager/plugin.py index 101827246ac773..cabe028ff34058 100644 --- a/api/core/plugin/manager/plugin.py +++ b/api/core/plugin/manager/plugin.py @@ -1,5 +1,4 @@ from collections.abc import Generator -from urllib.parse import quote from core.plugin.entities.plugin_daemon import InstallPluginMessage from core.plugin.manager.base import BasePluginManager @@ -9,9 +8,8 @@ class PluginInstallationManager(BasePluginManager): def fetch_plugin_by_identifier(self, tenant_id: str, identifier: str) -> bool: # urlencode the identifier - identifier = quote(identifier) return self._request_with_plugin_daemon_response( - "GET", f"/plugin/{tenant_id}/fetch/identifier?plugin_unique_identifier={identifier}", bool + "GET", f"plugin/{tenant_id}/fetch/identifier", bool, params={"plugin_unique_identifier": identifier} ) def install_from_pkg(self, tenant_id: str, pkg: bytes) -> Generator[InstallPluginMessage, None, None]: @@ -22,21 +20,20 @@ def install_from_pkg(self, tenant_id: str, pkg: bytes) -> Generator[InstallPlugi body = {"dify_pkg": ("dify_pkg", pkg, "application/octet-stream")} return self._request_with_plugin_daemon_response_stream( - "POST", f"/plugin/{tenant_id}/install/pkg", InstallPluginMessage, data=body + "POST", f"plugin/{tenant_id}/install/pkg", InstallPluginMessage, data=body ) def install_from_identifier(self, tenant_id: str, identifier: str) -> bool: """ Install a plugin from an identifier. """ - identifier = quote(identifier) # exception will be raised if the request failed return self._request_with_plugin_daemon_response( "POST", - f"/plugin/{tenant_id}/install/identifier", + f"plugin/{tenant_id}/install/identifier", bool, - headers={ - "Content-Type": "application/json", + params={ + "plugin_unique_identifier": identifier, }, data={ "plugin_unique_identifier": identifier, @@ -48,5 +45,5 @@ def uninstall(self, tenant_id: str, identifier: str) -> bool: Uninstall a plugin. """ return self._request_with_plugin_daemon_response( - "DELETE", f"/plugin/{tenant_id}/uninstall?plugin_unique_identifier={identifier}", bool + "DELETE", f"plugin/{tenant_id}/uninstall", bool, params={"plugin_unique_identifier": identifier} ) diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py index 10ce33d5e7a243..f617400355c082 100644 --- a/api/core/plugin/manager/tool.py +++ b/api/core/plugin/manager/tool.py @@ -1,9 +1,13 @@ from core.plugin.manager.base import BasePluginManager +from core.tools.entities.tool_entities import ToolProviderEntity class PluginToolManager(BasePluginManager): - def fetch_tool_providers(self, asset_id: str) -> list[str]: + def fetch_tool_providers(self, tenant_id: str) -> list[ToolProviderEntity]: """ Fetch tool providers for the given asset. """ - response = self._request('GET', f'/plugin/asset/{asset_id}') \ No newline at end of file + response = self._request_with_plugin_daemon_response( + "GET", f"plugin/{tenant_id}/tools", list[ToolProviderEntity], params={"page": 1, "page_size": 256} + ) + return response diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 80334a274ec441..2a85c0f882bf21 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -274,9 +274,12 @@ class ToolProviderIdentity(BaseModel): ) -class ToolProviderEntity(BaseModel): - identity: ToolProviderIdentity - credentials_schema: dict[str, ProviderConfig] = Field(default_factory=dict) +class ToolIdentity(BaseModel): + author: str = Field(..., description="The author of the tool") + name: str = Field(..., description="The name of the tool") + label: I18nObject = Field(..., description="The label of the tool") + provider: str = Field(..., description="The provider of the tool") + icon: Optional[str] = None class ToolDescription(BaseModel): @@ -284,12 +287,24 @@ class ToolDescription(BaseModel): llm: str = Field(..., description="The description presented to the LLM") -class ToolIdentity(BaseModel): - author: str = Field(..., description="The author of the tool") - name: str = Field(..., description="The name of the tool") - label: I18nObject = Field(..., description="The label of the tool") - provider: str = Field(..., description="The provider of the tool") - icon: Optional[str] = None +class ToolEntity(BaseModel): + identity: ToolIdentity + parameters: list[ToolParameter] = Field(default_factory=list) + description: Optional[ToolDescription] = None + + # pydantic configs + model_config = ConfigDict(protected_namespaces=()) + + @field_validator("parameters", mode="before") + @classmethod + def set_parameters(cls, v, validation_info: ValidationInfo) -> list[ToolParameter]: + return v or [] + + +class ToolProviderEntity(BaseModel): + identity: ToolProviderIdentity + credentials_schema: dict[str, ProviderConfig] = Field(default_factory=dict) + tools: list[ToolEntity] = Field(default_factory=list) class WorkflowToolParameterConfiguration(BaseModel): @@ -352,15 +367,4 @@ class ToolInvokeFrom(Enum): AGENT = "agent" -class ToolEntity(BaseModel): - identity: ToolIdentity - parameters: list[ToolParameter] = Field(default_factory=list) - description: Optional[ToolDescription] = None - - # pydantic configs - model_config = ConfigDict(protected_namespaces=()) - @field_validator("parameters", mode="before") - @classmethod - def set_parameters(cls, v, validation_info: ValidationInfo) -> list[ToolParameter]: - return v or [] diff --git a/api/tests/integration_tests/.env.example b/api/tests/integration_tests/.env.example index 2d52399d29a995..8bb1ab96fc0033 100644 --- a/api/tests/integration_tests/.env.example +++ b/api/tests/integration_tests/.env.example @@ -83,3 +83,8 @@ VOLC_EMBEDDING_ENDPOINT_ID= # 360 AI Credentials ZHINAO_API_KEY= + +# Plugin configuration +PLUGIN_API_KEY= +PLUGIN_API_URL= +INNER_API_KEY= \ No newline at end of file diff --git a/api/tests/integration_tests/plugin/__mock/http.py b/api/tests/integration_tests/plugin/__mock/http.py new file mode 100644 index 00000000000000..25177274c6c049 --- /dev/null +++ b/api/tests/integration_tests/plugin/__mock/http.py @@ -0,0 +1,66 @@ +import os +from typing import Literal + +import pytest +import requests +from _pytest.monkeypatch import MonkeyPatch + +from core.plugin.entities.plugin_daemon import PluginDaemonBasicResponse +from core.tools.entities.common_entities import I18nObject +from core.tools.entities.tool_entities import ToolProviderEntity, ToolProviderIdentity + + +class MockedHttp: + @classmethod + def list_tools(cls) -> list[ToolProviderEntity]: + return [ + ToolProviderEntity( + identity=ToolProviderIdentity( + author="Yeuoly", + name="Yeuoly", + description=I18nObject(en_US="Yeuoly"), + icon="ssss.svg", + label=I18nObject(en_US="Yeuoly"), + ) + ) + ] + + @classmethod + def requests_request( + cls, method: Literal["GET", "POST", "PUT", "DELETE", "PATCH", "HEAD"], url: str, **kwargs + ) -> requests.Response: + """ + Mocked requests.request + """ + request = requests.PreparedRequest() + request.method = method + request.url = url + if url.endswith("/tools"): + content = PluginDaemonBasicResponse[list[ToolProviderEntity]]( + code=0, message="success", data=cls.list_tools() + ).model_dump_json() + else: + raise ValueError("") + + response = requests.Response() + response.status_code = 200 + response.request = request + response._content = content.encode("utf-8") + return response + + +MOCK_SWITCH = os.getenv("MOCK_SWITCH", "false").lower() == "true" + + +@pytest.fixture +def setup_http_mock(request, monkeypatch: MonkeyPatch): + if MOCK_SWITCH: + monkeypatch.setattr(requests, "request", MockedHttp.requests_request) + + def unpatch(): + monkeypatch.undo() + + yield + + if MOCK_SWITCH: + unpatch() diff --git a/api/tests/integration_tests/plugin/tools/test_fetch_all_tools.py b/api/tests/integration_tests/plugin/tools/test_fetch_all_tools.py new file mode 100644 index 00000000000000..d50bba4eccc103 --- /dev/null +++ b/api/tests/integration_tests/plugin/tools/test_fetch_all_tools.py @@ -0,0 +1,9 @@ +from core.plugin.manager.tool import PluginToolManager +from tests.integration_tests.plugin.__mock.http import setup_http_mock + + +def test_fetch_all_plugin_tools(setup_http_mock): + manager = PluginToolManager() + tools = manager.fetch_tool_providers(tenant_id="test-tenant") + assert len(tools) >= 1 + diff --git a/api/tests/integration_tests/tools/test_all_provider.py b/api/tests/integration_tests/tools/test_all_provider.py deleted file mode 100644 index 2dfce749b3e16f..00000000000000 --- a/api/tests/integration_tests/tools/test_all_provider.py +++ /dev/null @@ -1,23 +0,0 @@ -import pytest - -from core.tools.tool_manager import ToolManager - -provider_generator = ToolManager.list_builtin_providers() -provider_names = [provider.identity.name for provider in provider_generator] -ToolManager.clear_builtin_providers_cache() -provider_generator = ToolManager.list_builtin_providers() - - -@pytest.mark.parametrize("name", provider_names) -def test_tool_providers(benchmark, name): - """ - Test that all tool providers can be loaded - """ - - def test(generator): - try: - return next(generator) - except StopIteration: - return None - - benchmark.pedantic(test, args=(provider_generator,), iterations=1, rounds=1) From 7a3e756020b8867f65b2a2cd711a246d015e0b2b Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Mon, 23 Sep 2024 18:06:16 +0800 Subject: [PATCH 041/325] refactor: list tools --- .../console/workspace/tool_providers.py | 7 +- api/core/agent/base_agent_runner.py | 2 +- api/core/plugin/entities/plugin_daemon.py | 11 +- api/core/plugin/manager/base.py | 9 +- api/core/plugin/manager/tool.py | 58 ++++++++- api/core/tools/__base/tool.py | 6 +- api/core/tools/__base/tool_provider.py | 2 - api/core/tools/__base/tool_runtime.py | 2 +- api/core/tools/builtin_tool/provider.py | 19 +-- .../builtin_tool/providers/_positions.py | 6 +- .../tools/builtin_tool/providers/code/code.py | 2 +- .../builtin_tool/providers/qrcode/qrcode.py | 2 +- .../tools/builtin_tool/providers/time/time.py | 2 +- api/core/tools/custom_tool/provider.py | 5 +- api/core/tools/entities/api_entities.py | 10 +- api/core/tools/entities/tool_entities.py | 10 ++ .../tools/plugin_tool/plugin_tool_provider.py | 30 ----- api/core/tools/plugin_tool/provider.py | 72 +++++++++++ api/core/tools/plugin_tool/tool.py | 41 ++++++ api/core/tools/tool_manager.py | 122 +++++++++++++----- api/core/tools/workflow_as_tool/tool.py | 2 +- .../tools/api_tools_manage_service.py | 8 +- .../tools/builtin_tools_manage_service.py | 39 +++--- api/services/tools/tools_manage_service.py | 4 +- api/services/tools/tools_transform_service.py | 27 ++-- .../tools/workflow_tools_manage_service.py | 6 +- 26 files changed, 365 insertions(+), 139 deletions(-) delete mode 100644 api/core/tools/plugin_tool/plugin_tool_provider.py create mode 100644 api/core/tools/plugin_tool/provider.py create mode 100644 api/core/tools/plugin_tool/tool.py diff --git a/api/controllers/console/workspace/tool_providers.py b/api/controllers/console/workspace/tool_providers.py index d2a17b133b6d12..68ad383a744d70 100644 --- a/api/controllers/console/workspace/tool_providers.py +++ b/api/controllers/console/workspace/tool_providers.py @@ -118,7 +118,9 @@ def get(self, provider): class ToolBuiltinProviderIconApi(Resource): @setup_required def get(self, provider): - icon_bytes, mimetype = BuiltinToolManageService.get_builtin_tool_provider_icon(provider) + tenant_id = current_user.current_tenant_id + + icon_bytes, mimetype = BuiltinToolManageService.get_builtin_tool_provider_icon(provider, tenant_id) icon_cache_max_age = dify_config.TOOL_ICON_CACHE_MAX_AGE return send_file(io.BytesIO(icon_bytes), mimetype=mimetype, max_age=icon_cache_max_age) @@ -290,7 +292,8 @@ class ToolBuiltinProviderCredentialsSchemaApi(Resource): @login_required @account_initialization_required def get(self, provider): - return BuiltinToolManageService.list_builtin_provider_credentials_schema(provider) + tenant_id = current_user.current_tenant_id + return BuiltinToolManageService.list_builtin_provider_credentials_schema(provider, tenant_id) class ToolApiProviderSchemaApi(Resource): diff --git a/api/core/agent/base_agent_runner.py b/api/core/agent/base_agent_runner.py index 64075ed231f4af..aea68050bdf3e1 100644 --- a/api/core/agent/base_agent_runner.py +++ b/api/core/agent/base_agent_runner.py @@ -166,7 +166,7 @@ def _convert_tool_to_prompt_message_tool(self, tool: AgentToolEntity) -> tuple[P }, ) - parameters = tool_entity.get_all_runtime_parameters() + parameters = tool_entity.get_merged_runtime_parameters() for parameter in parameters: if parameter.form != ToolParameter.ToolParameterForm.LLM: continue diff --git a/api/core/plugin/entities/plugin_daemon.py b/api/core/plugin/entities/plugin_daemon.py index 0c710c87161c39..51cc36d7dfeda8 100644 --- a/api/core/plugin/entities/plugin_daemon.py +++ b/api/core/plugin/entities/plugin_daemon.py @@ -3,6 +3,8 @@ from pydantic import BaseModel +from core.tools.entities.tool_entities import ToolProviderEntityWithPlugin + T = TypeVar("T", bound=(BaseModel | dict | list | bool)) @@ -26,4 +28,11 @@ class Event(Enum): Error = "error" event: Event - data: str \ No newline at end of file + data: str + + +class PluginToolProviderEntity(BaseModel): + provider: str + plugin_unique_identifier: str + plugin_id: str + declaration: ToolProviderEntityWithPlugin \ No newline at end of file diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index 3f6a87dca8b8e0..8b80d923f64425 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -93,7 +93,14 @@ def _request_with_plugin_daemon_response( Make a request to the plugin daemon inner API and return the response as a model. """ response = self._request(method, path, headers, data, params) - rep = PluginDaemonBasicResponse[type](**response.json()) + json_response = response.json() + for provider in json_response.get("data", []): + declaration = provider.get("declaration", {}) or {} + provider_name = declaration.get("identity", {}).get("name") + for tool in declaration.get("tools", []): + tool["identity"]["provider"] = provider_name + + rep = PluginDaemonBasicResponse[type](**json_response) if rep.code != 0: raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") if rep.data is None: diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py index f617400355c082..fe5f7bb757d84e 100644 --- a/api/core/plugin/manager/tool.py +++ b/api/core/plugin/manager/tool.py @@ -1,13 +1,65 @@ +from collections.abc import Generator +from typing import Any + +from core.plugin.entities.plugin_daemon import PluginToolProviderEntity from core.plugin.manager.base import BasePluginManager -from core.tools.entities.tool_entities import ToolProviderEntity +from core.tools.entities.tool_entities import ToolInvokeMessage class PluginToolManager(BasePluginManager): - def fetch_tool_providers(self, tenant_id: str) -> list[ToolProviderEntity]: + def fetch_tool_providers(self, tenant_id: str) -> list[PluginToolProviderEntity]: """ Fetch tool providers for the given asset. """ response = self._request_with_plugin_daemon_response( - "GET", f"plugin/{tenant_id}/tools", list[ToolProviderEntity], params={"page": 1, "page_size": 256} + "GET", f"plugin/{tenant_id}/tools", list[PluginToolProviderEntity], params={"page": 1, "page_size": 256} + ) + return response + + def invoke( + self, + tenant_id: str, + user_id: str, + plugin_unique_identifier: str, + tool_provider: str, + tool_name: str, + credentials: dict[str, Any], + tool_parameters: dict[str, Any], + ) -> Generator[ToolInvokeMessage, None, None]: + response = self._request_with_plugin_daemon_response_stream( + "POST", + f"plugin/{tenant_id}/tool/invoke", + ToolInvokeMessage, + data={ + "plugin_unique_identifier": plugin_unique_identifier, + "user_id": user_id, + "data": { + "provider": tool_provider, + "tool": tool_name, + "credentials": credentials, + "tool_parameters": tool_parameters, + }, + }, + ) + return response + + def validate_provider_credentials( + self, tenant_id: str, user_id: str, plugin_unique_identifier: str, provider: str, credentials: dict[str, Any] + ) -> bool: + """ + validate the credentials of the provider + """ + response = self._request_with_plugin_daemon_response( + "POST", + f"plugin/{tenant_id}/tool/validate_credentials", + bool, + data={ + "plugin_unique_identifier": plugin_unique_identifier, + "user_id": user_id, + "data": { + "provider": provider, + "credentials": credentials, + }, + }, ) return response diff --git a/api/core/tools/__base/tool.py b/api/core/tools/__base/tool.py index 548db51a2aedfb..d0bf2f0c31cb02 100644 --- a/api/core/tools/__base/tool.py +++ b/api/core/tools/__base/tool.py @@ -105,11 +105,11 @@ def get_runtime_parameters(self) -> list[ToolParameter]: """ return self.entity.parameters - def get_all_runtime_parameters(self) -> list[ToolParameter]: + def get_merged_runtime_parameters(self) -> list[ToolParameter]: """ - get all runtime parameters + get merged runtime parameters - :return: all runtime parameters + :return: merged runtime parameters """ parameters = self.entity.parameters parameters = parameters.copy() diff --git a/api/core/tools/__base/tool_provider.py b/api/core/tools/__base/tool_provider.py index c71885e48de191..795812a1096a7a 100644 --- a/api/core/tools/__base/tool_provider.py +++ b/api/core/tools/__base/tool_provider.py @@ -12,11 +12,9 @@ class ToolProviderController(ABC): entity: ToolProviderEntity - tools: list[Tool] def __init__(self, entity: ToolProviderEntity) -> None: self.entity = entity - self.tools = [] def get_credentials_schema(self) -> dict[str, ProviderConfig]: """ diff --git a/api/core/tools/__base/tool_runtime.py b/api/core/tools/__base/tool_runtime.py index d4b2ef61049d92..c9e157cb77a26d 100644 --- a/api/core/tools/__base/tool_runtime.py +++ b/api/core/tools/__base/tool_runtime.py @@ -16,7 +16,7 @@ class ToolRuntime(BaseModel): tool_id: Optional[str] = None invoke_from: Optional[InvokeFrom] = None tool_invoke_from: Optional[ToolInvokeFrom] = None - credentials: Optional[dict[str, Any]] = None + credentials: dict[str, Any] = Field(default_factory=dict) runtime_parameters: dict[str, Any] = Field(default_factory=dict) diff --git a/api/core/tools/builtin_tool/provider.py b/api/core/tools/builtin_tool/provider.py index 4ebd82f8e778a8..e7e374f2e66d4d 100644 --- a/api/core/tools/builtin_tool/provider.py +++ b/api/core/tools/builtin_tool/provider.py @@ -19,9 +19,7 @@ class BuiltinToolProviderController(ToolProviderController): tools: list[BuiltinTool] def __init__(self, **data: Any) -> None: - if self.provider_type == ToolProviderType.API: - super().__init__(**data) - return + self.tools = [] # load provider yaml provider = self.__class__.__module__.split(".")[-1] @@ -76,9 +74,12 @@ def _get_builtin_tools(self) -> list[BuiltinTool]: parent_type=BuiltinTool, ) tool["identity"]["provider"] = provider - tools.append(assistant_tool_class( - entity=ToolEntity(**tool), runtime=ToolRuntime(tenant_id=""), - )) + tools.append( + assistant_tool_class( + entity=ToolEntity(**tool), + runtime=ToolRuntime(tenant_id=""), + ) + ) self.tools = tools return tools @@ -142,7 +143,7 @@ def _get_tool_labels(self) -> list[ToolLabelEnum]: """ return self.entity.identity.tags or [] - def validate_credentials(self, credentials: dict[str, Any]) -> None: + def validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> None: """ validate the credentials of the provider @@ -153,10 +154,10 @@ def validate_credentials(self, credentials: dict[str, Any]) -> None: self.validate_credentials_format(credentials) # validate credentials - self._validate_credentials(credentials) + self._validate_credentials(user_id, credentials) @abstractmethod - def _validate_credentials(self, credentials: dict[str, Any]) -> None: + def _validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> None: """ validate the credentials of the provider diff --git a/api/core/tools/builtin_tool/providers/_positions.py b/api/core/tools/builtin_tool/providers/_positions.py index 5c10f72fdaed01..224b695ff979da 100644 --- a/api/core/tools/builtin_tool/providers/_positions.py +++ b/api/core/tools/builtin_tool/providers/_positions.py @@ -1,18 +1,18 @@ import os.path from core.helper.position_helper import get_tool_position_map, sort_by_position_map -from core.tools.entities.api_entities import UserToolProvider +from core.tools.entities.api_entities import ToolProviderApiEntity class BuiltinToolProviderSort: _position = {} @classmethod - def sort(cls, providers: list[UserToolProvider]) -> list[UserToolProvider]: + def sort(cls, providers: list[ToolProviderApiEntity]) -> list[ToolProviderApiEntity]: if not cls._position: cls._position = get_tool_position_map(os.path.join(os.path.dirname(__file__), "..")) - def name_func(provider: UserToolProvider) -> str: + def name_func(provider: ToolProviderApiEntity) -> str: return provider.name sorted_providers = sort_by_position_map(cls._position, providers, name_func) diff --git a/api/core/tools/builtin_tool/providers/code/code.py b/api/core/tools/builtin_tool/providers/code/code.py index 53210e9c439cb6..18b7cd4c9010e8 100644 --- a/api/core/tools/builtin_tool/providers/code/code.py +++ b/api/core/tools/builtin_tool/providers/code/code.py @@ -4,5 +4,5 @@ class CodeToolProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: + def _validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> None: pass diff --git a/api/core/tools/builtin_tool/providers/qrcode/qrcode.py b/api/core/tools/builtin_tool/providers/qrcode/qrcode.py index e792382ee3f451..3999f3b3ef1ff6 100644 --- a/api/core/tools/builtin_tool/providers/qrcode/qrcode.py +++ b/api/core/tools/builtin_tool/providers/qrcode/qrcode.py @@ -4,5 +4,5 @@ class QRCodeProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: + def _validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> None: pass diff --git a/api/core/tools/builtin_tool/providers/time/time.py b/api/core/tools/builtin_tool/providers/time/time.py index d70fc22dfcae51..323a7c41b8f7a1 100644 --- a/api/core/tools/builtin_tool/providers/time/time.py +++ b/api/core/tools/builtin_tool/providers/time/time.py @@ -4,5 +4,5 @@ class WikiPediaProvider(BuiltinToolProviderController): - def _validate_credentials(self, credentials: dict[str, Any]) -> None: + def _validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> None: pass diff --git a/api/core/tools/custom_tool/provider.py b/api/core/tools/custom_tool/provider.py index 32eda1d9bcda8a..c5e3e8488e21e0 100644 --- a/api/core/tools/custom_tool/provider.py +++ b/api/core/tools/custom_tool/provider.py @@ -24,9 +24,10 @@ def __init__(self, entity: ToolProviderEntity, provider_id: str, tenant_id: str) super().__init__(entity) self.provider_id = provider_id self.tenant_id = tenant_id + self.tools = [] - @staticmethod - def from_db(db_provider: ApiToolProvider, auth_type: ApiProviderAuthType) -> "ApiToolProviderController": + @classmethod + def from_db(cls, db_provider: ApiToolProvider, auth_type: ApiProviderAuthType): credentials_schema = { "auth_type": ProviderConfig( name="auth_type", diff --git a/api/core/tools/entities/api_entities.py b/api/core/tools/entities/api_entities.py index b3a98b4a6dcf79..18db659bb9f830 100644 --- a/api/core/tools/entities/api_entities.py +++ b/api/core/tools/entities/api_entities.py @@ -9,7 +9,7 @@ from core.tools.entities.tool_entities import ToolProviderType -class UserTool(BaseModel): +class ToolApiEntity(BaseModel): author: str name: str # identifier label: I18nObject # label @@ -18,10 +18,10 @@ class UserTool(BaseModel): labels: list[str] = Field(default_factory=list) -UserToolProviderTypeLiteral = Optional[Literal["builtin", "api", "workflow"]] +ToolProviderTypeApiLiteral = Optional[Literal["builtin", "api", "workflow"]] -class UserToolProvider(BaseModel): +class ToolProviderApiEntity(BaseModel): id: str author: str name: str # identifier @@ -33,7 +33,7 @@ class UserToolProvider(BaseModel): original_credentials: Optional[dict] = None is_team_authorization: bool = False allow_delete: bool = True - tools: list[UserTool] = Field(default_factory=list) + tools: list[ToolApiEntity] = Field(default_factory=list) labels: list[str] = Field(default_factory=list) def to_dict(self) -> dict: @@ -63,5 +63,5 @@ def to_dict(self) -> dict: } -class UserToolProviderCredentials(BaseModel): +class ToolProviderCredentialsApiEntity(BaseModel): credentials: dict[str, ProviderConfig] diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 2a85c0f882bf21..07ea2d2b11f1fe 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -224,6 +224,13 @@ class ToolParameterForm(Enum): max: Optional[Union[float, int]] = None options: list[ToolParameterOption] = Field(default_factory=list) + @field_validator("options", mode="before") + @classmethod + def transform_options(cls, v): + if not isinstance(v, list): + return [] + return v + @classmethod def get_simple_instance( cls, @@ -304,6 +311,9 @@ def set_parameters(cls, v, validation_info: ValidationInfo) -> list[ToolParamete class ToolProviderEntity(BaseModel): identity: ToolProviderIdentity credentials_schema: dict[str, ProviderConfig] = Field(default_factory=dict) + + +class ToolProviderEntityWithPlugin(ToolProviderEntity): tools: list[ToolEntity] = Field(default_factory=list) diff --git a/api/core/tools/plugin_tool/plugin_tool_provider.py b/api/core/tools/plugin_tool/plugin_tool_provider.py deleted file mode 100644 index 47a78ee3183fda..00000000000000 --- a/api/core/tools/plugin_tool/plugin_tool_provider.py +++ /dev/null @@ -1,30 +0,0 @@ - - -from core.entities.provider_entities import ProviderConfig -from core.tools.__base.tool import Tool -from core.tools.__base.tool_provider import ToolProviderController -from core.tools.entities.tool_entities import ToolProviderType - - -class PluginToolProvider(ToolProviderController): - @property - def provider_type(self) -> ToolProviderType: - """ - returns the type of the provider - - :return: type of the provider - """ - return ToolProviderType.PLUGIN - - def get_tool(self, tool_name: str) -> Tool: - """ - return tool with given name - """ - return super().get_tool(tool_name) - - def get_credentials_schema(self) -> dict[str, ProviderConfig]: - """ - get credentials schema - """ - return super().get_credentials_schema() - \ No newline at end of file diff --git a/api/core/tools/plugin_tool/provider.py b/api/core/tools/plugin_tool/provider.py new file mode 100644 index 00000000000000..a52e7c967f4be0 --- /dev/null +++ b/api/core/tools/plugin_tool/provider.py @@ -0,0 +1,72 @@ +from typing import Any + +from core.plugin.manager.tool import PluginToolManager +from core.tools.__base.tool_runtime import ToolRuntime +from core.tools.builtin_tool.provider import BuiltinToolProviderController +from core.tools.entities.tool_entities import ToolProviderEntityWithPlugin, ToolProviderType +from core.tools.errors import ToolProviderCredentialValidationError +from core.tools.plugin_tool.tool import PluginTool + + +class PluginToolProviderController(BuiltinToolProviderController): + entity: ToolProviderEntityWithPlugin + tenant_id: str + plugin_unique_identifier: str + + def __init__(self, entity: ToolProviderEntityWithPlugin, tenant_id: str, plugin_unique_identifier: str) -> None: + self.entity = entity + self.tenant_id = tenant_id + self.plugin_unique_identifier = plugin_unique_identifier + + @property + def provider_type(self) -> ToolProviderType: + """ + returns the type of the provider + + :return: type of the provider + """ + return ToolProviderType.PLUGIN + + def _validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> None: + """ + validate the credentials of the provider + """ + manager = PluginToolManager() + if not manager.validate_provider_credentials( + tenant_id=self.tenant_id, + user_id=user_id, + plugin_unique_identifier=self.plugin_unique_identifier, + provider=self.entity.identity.name, + credentials=credentials, + ): + raise ToolProviderCredentialValidationError("Invalid credentials") + + def get_tool(self, tool_name: str) -> PluginTool: + """ + return tool with given name + """ + tool_entity = next(tool_entity for tool_entity in self.entity.tools if tool_entity.identity.name == tool_name) + + if not tool_entity: + raise ValueError(f"Tool with name {tool_name} not found") + + return PluginTool( + entity=tool_entity, + runtime=ToolRuntime(tenant_id=self.tenant_id), + tenant_id=self.tenant_id, + plugin_unique_identifier=self.plugin_unique_identifier, + ) + + def get_tools(self) -> list[PluginTool]: + """ + get all tools + """ + return [ + PluginTool( + entity=tool_entity, + runtime=ToolRuntime(tenant_id=self.tenant_id), + tenant_id=self.tenant_id, + plugin_unique_identifier=self.plugin_unique_identifier, + ) + for tool_entity in self.entity.tools + ] diff --git a/api/core/tools/plugin_tool/tool.py b/api/core/tools/plugin_tool/tool.py new file mode 100644 index 00000000000000..898e8a552d0f6d --- /dev/null +++ b/api/core/tools/plugin_tool/tool.py @@ -0,0 +1,41 @@ +from collections.abc import Generator +from typing import Any + +from core.plugin.manager.tool import PluginToolManager +from core.tools.__base.tool import Tool +from core.tools.__base.tool_runtime import ToolRuntime +from core.tools.entities.tool_entities import ToolEntity, ToolInvokeMessage, ToolProviderType + + +class PluginTool(Tool): + tenant_id: str + plugin_unique_identifier: str + + def __init__(self, entity: ToolEntity, runtime: ToolRuntime, tenant_id: str, plugin_unique_identifier: str) -> None: + super().__init__(entity, runtime) + self.tenant_id = tenant_id + self.plugin_unique_identifier = plugin_unique_identifier + + @property + def tool_provider_type(self) -> ToolProviderType: + return ToolProviderType.PLUGIN + + def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[ToolInvokeMessage, None, None]: + manager = PluginToolManager() + return manager.invoke( + tenant_id=self.tenant_id, + user_id=user_id, + plugin_unique_identifier=self.plugin_unique_identifier, + tool_provider=self.entity.identity.provider, + tool_name=self.entity.identity.name, + credentials=self.runtime.credentials, + tool_parameters=tool_parameters, + ) + + def fork_tool_runtime(self, runtime: ToolRuntime) -> "PluginTool": + return PluginTool( + entity=self.entity, + runtime=runtime, + tenant_id=self.tenant_id, + plugin_unique_identifier=self.plugin_unique_identifier, + ) \ No newline at end of file diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index c37ee730c832e9..76c7232e01129d 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -6,7 +6,10 @@ from threading import Lock from typing import TYPE_CHECKING, Any, Union, cast +from core.plugin.manager.tool import PluginToolManager from core.tools.__base.tool_runtime import ToolRuntime +from core.tools.plugin_tool.provider import PluginToolProviderController +from core.tools.plugin_tool.tool import PluginTool if TYPE_CHECKING: from core.workflow.nodes.tool.entities import ToolEntity @@ -24,7 +27,7 @@ from core.tools.builtin_tool.tool import BuiltinTool from core.tools.custom_tool.provider import ApiToolProviderController from core.tools.custom_tool.tool import ApiTool -from core.tools.entities.api_entities import UserToolProvider, UserToolProviderTypeLiteral +from core.tools.entities.api_entities import ToolProviderApiEntity, ToolProviderTypeApiLiteral from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_entities import ApiProviderAuthType, ToolInvokeFrom, ToolParameter, ToolProviderType from core.tools.errors import ToolProviderNotFoundError @@ -41,38 +44,61 @@ class ToolManager: _builtin_provider_lock = Lock() - _builtin_providers = {} + _hardcoded_providers = {} _builtin_providers_loaded = False _builtin_tools_labels = {} @classmethod - def get_builtin_provider(cls, provider: str) -> BuiltinToolProviderController: + def get_builtin_provider( + cls, provider: str, tenant_id: str + ) -> BuiltinToolProviderController | PluginToolProviderController: """ get the builtin provider :param provider: the name of the provider + :param tenant_id: the id of the tenant :return: the provider """ - if len(cls._builtin_providers) == 0: + if len(cls._hardcoded_providers) == 0: # init the builtin providers - cls.load_builtin_providers_cache() + cls.load_hardcoded_providers_cache() - if provider not in cls._builtin_providers: - raise ToolProviderNotFoundError(f"builtin provider {provider} not found") + if provider not in cls._hardcoded_providers: + # get plugin provider + plugin_provider = cls.get_plugin_provider(provider, tenant_id) + if plugin_provider: + return plugin_provider - return cls._builtin_providers[provider] + return cls._hardcoded_providers[provider] @classmethod - def get_builtin_tool(cls, provider: str, tool_name: str) -> BuiltinTool | None: + def get_plugin_provider(cls, provider: str, tenant_id: str) -> PluginToolProviderController: + """ + get the plugin provider + """ + manager = PluginToolManager() + providers = manager.fetch_tool_providers(tenant_id) + provider_entity = next((x for x in providers if x.declaration.identity.name == provider), None) + if not provider_entity: + raise ToolProviderNotFoundError(f"plugin provider {provider} not found") + + return PluginToolProviderController( + entity=provider_entity.declaration, + tenant_id=tenant_id, + plugin_unique_identifier=provider_entity.plugin_unique_identifier, + ) + + @classmethod + def get_builtin_tool(cls, provider: str, tool_name: str, tenant_id: str) -> BuiltinTool | PluginTool | None: """ get the builtin tool :param provider: the name of the provider :param tool_name: the name of the tool - + :param tenant_id: the id of the tenant :return: the provider, the tool """ - provider_controller = cls.get_builtin_provider(provider) + provider_controller = cls.get_builtin_provider(provider, tenant_id) tool = provider_controller.get_tool(tool_name) return tool @@ -97,12 +123,12 @@ def get_tool_runtime( :return: the tool """ if provider_type == ToolProviderType.BUILT_IN: - builtin_tool = cls.get_builtin_tool(provider_id, tool_name) + builtin_tool = cls.get_builtin_tool(provider_id, tool_name, tenant_id) if not builtin_tool: raise ValueError(f"tool {tool_name} not found") # check if the builtin tool need credentials - provider_controller = cls.get_builtin_provider(provider_id) + provider_controller = cls.get_builtin_provider(provider_id, tenant_id) if not provider_controller.need_credentials: return cast( BuiltinTool, @@ -131,7 +157,7 @@ def get_tool_runtime( # decrypt the credentials credentials = builtin_provider.credentials - controller = cls.get_builtin_provider(provider_id) + controller = cls.get_builtin_provider(provider_id, tenant_id) tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=controller.get_credentials_schema(), @@ -246,7 +272,7 @@ def get_agent_tool_runtime( tool_invoke_from=ToolInvokeFrom.AGENT, ) runtime_parameters = {} - parameters = tool_entity.get_all_runtime_parameters() + parameters = tool_entity.get_merged_runtime_parameters() for parameter in parameters: # check file types if parameter.type == ToolParameter.ToolParameterType.FILE: @@ -294,7 +320,7 @@ def get_workflow_tool_runtime( tool_invoke_from=ToolInvokeFrom.WORKFLOW, ) runtime_parameters = {} - parameters = tool_entity.get_all_runtime_parameters() + parameters = tool_entity.get_merged_runtime_parameters() for parameter in parameters: # save tool parameter to tool entity memory @@ -321,16 +347,17 @@ def get_workflow_tool_runtime( return tool_entity @classmethod - def get_builtin_provider_icon(cls, provider: str) -> tuple[str, str]: + def get_builtin_provider_icon(cls, provider: str, tenant_id: str) -> tuple[str, str]: """ get the absolute path of the icon of the builtin provider :param provider: the name of the provider + :param tenant_id: the id of the tenant :return: the absolute path of the icon, the mime type of the icon """ # get provider - provider_controller = cls.get_builtin_provider(provider) + provider_controller = cls.get_builtin_provider(provider, tenant_id) absolute_path = path.join( path.dirname(path.realpath(__file__)), @@ -351,21 +378,48 @@ def get_builtin_provider_icon(cls, provider: str) -> tuple[str, str]: return absolute_path, mime_type @classmethod - def list_builtin_providers(cls) -> Generator[BuiltinToolProviderController, None, None]: + def list_hardcoded_providers(cls): # use cache first if cls._builtin_providers_loaded: - yield from list(cls._builtin_providers.values()) + yield from list(cls._hardcoded_providers.values()) return with cls._builtin_provider_lock: if cls._builtin_providers_loaded: - yield from list(cls._builtin_providers.values()) + yield from list(cls._hardcoded_providers.values()) return - yield from cls._list_builtin_providers() + yield from cls._list_hardcoded_providers() + + @classmethod + def list_plugin_providers(cls, tenant_id: str) -> list[PluginToolProviderController]: + """ + list all the plugin providers + """ + manager = PluginToolManager() + provider_entities = manager.fetch_tool_providers(tenant_id) + return [ + PluginToolProviderController( + entity=provider.declaration, + tenant_id=tenant_id, + plugin_unique_identifier=provider.plugin_unique_identifier, + ) + for provider in provider_entities + ] + + @classmethod + def list_builtin_providers( + cls, tenant_id: str + ) -> Generator[BuiltinToolProviderController | PluginToolProviderController, None, None]: + """ + list all the builtin providers + """ + yield from cls.list_hardcoded_providers() + # get plugin providers + yield from cls.list_plugin_providers(tenant_id) @classmethod - def _list_builtin_providers(cls) -> Generator[BuiltinToolProviderController, None, None]: + def _list_hardcoded_providers(cls) -> Generator[BuiltinToolProviderController, None, None]: """ list all the builtin providers """ @@ -391,7 +445,7 @@ def _list_builtin_providers(cls) -> Generator[BuiltinToolProviderController, Non parent_type=BuiltinToolProviderController, ) provider: BuiltinToolProviderController = provider_class() - cls._builtin_providers[provider.entity.identity.name] = provider + cls._hardcoded_providers[provider.entity.identity.name] = provider for tool in provider.get_tools(): cls._builtin_tools_labels[tool.entity.identity.name] = tool.entity.identity.label yield provider @@ -403,13 +457,13 @@ def _list_builtin_providers(cls) -> Generator[BuiltinToolProviderController, Non cls._builtin_providers_loaded = True @classmethod - def load_builtin_providers_cache(cls): - for _ in cls.list_builtin_providers(): + def load_hardcoded_providers_cache(cls): + for _ in cls.list_hardcoded_providers(): pass @classmethod - def clear_builtin_providers_cache(cls): - cls._builtin_providers = {} + def clear_hardcoded_providers_cache(cls): + cls._hardcoded_providers = {} cls._builtin_providers_loaded = False @classmethod @@ -423,7 +477,7 @@ def get_tool_label(cls, tool_name: str) -> Union[I18nObject, None]: """ if len(cls._builtin_tools_labels) == 0: # init the builtin providers - cls.load_builtin_providers_cache() + cls.load_hardcoded_providers_cache() if tool_name not in cls._builtin_tools_labels: return None @@ -432,9 +486,9 @@ def get_tool_label(cls, tool_name: str) -> Union[I18nObject, None]: @classmethod def user_list_providers( - cls, user_id: str, tenant_id: str, typ: UserToolProviderTypeLiteral - ) -> list[UserToolProvider]: - result_providers: dict[str, UserToolProvider] = {} + cls, user_id: str, tenant_id: str, typ: ToolProviderTypeApiLiteral + ) -> list[ToolProviderApiEntity]: + result_providers: dict[str, ToolProviderApiEntity] = {} filters = [] if not typ: @@ -444,7 +498,7 @@ def user_list_providers( if "builtin" in filters: # get builtin providers - builtin_providers = cls.list_builtin_providers() + builtin_providers = cls.list_builtin_providers(tenant_id) # get db builtin providers db_builtin_providers: list[BuiltinToolProvider] = ( @@ -666,4 +720,4 @@ def get_tool_icon(cls, tenant_id: str, provider_type: ToolProviderType, provider raise ValueError(f"provider type {provider_type} not found") -ToolManager.load_builtin_providers_cache() +ToolManager.load_hardcoded_providers_cache() diff --git a/api/core/tools/workflow_as_tool/tool.py b/api/core/tools/workflow_as_tool/tool.py index e1fc5140d0d72a..d8cddd02d8c060 100644 --- a/api/core/tools/workflow_as_tool/tool.py +++ b/api/core/tools/workflow_as_tool/tool.py @@ -167,7 +167,7 @@ def _transform_args(self, tool_parameters: dict) -> tuple[dict, list[dict]]: :param tool_parameters: the tool parameters :return: tool_parameters, files """ - parameter_rules = self.get_all_runtime_parameters() + parameter_rules = self.get_merged_runtime_parameters() parameters_result = {} files = [] for parameter in parameter_rules: diff --git a/api/services/tools/api_tools_manage_service.py b/api/services/tools/api_tools_manage_service.py index e39c2b8a5bc83e..58f0e7bbf52098 100644 --- a/api/services/tools/api_tools_manage_service.py +++ b/api/services/tools/api_tools_manage_service.py @@ -7,7 +7,7 @@ from core.model_runtime.utils.encoders import jsonable_encoder from core.tools.__base.tool_runtime import ToolRuntime from core.tools.custom_tool.provider import ApiToolProviderController -from core.tools.entities.api_entities import UserTool, UserToolProvider +from core.tools.entities.api_entities import ToolApiEntity, ToolProviderApiEntity from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( @@ -201,7 +201,7 @@ def get_api_tool_provider_remote_schema(user_id: str, tenant_id: str, url: str): return {"schema": schema} @staticmethod - def list_api_tool_provider_tools(user_id: str, tenant_id: str, provider_name: str) -> list[UserTool]: + def list_api_tool_provider_tools(user_id: str, tenant_id: str, provider_name: str) -> list[ToolApiEntity]: """ list api tool provider tools """ @@ -438,7 +438,7 @@ def test_api_tool_preview( return {"result": result or "empty response"} @staticmethod - def list_api_tools(user_id: str, tenant_id: str) -> list[UserToolProvider]: + def list_api_tools(user_id: str, tenant_id: str) -> list[ToolProviderApiEntity]: """ list api tools """ @@ -447,7 +447,7 @@ def list_api_tools(user_id: str, tenant_id: str) -> list[UserToolProvider]: db.session.query(ApiToolProvider).filter(ApiToolProvider.tenant_id == tenant_id).all() or [] ) - result: list[UserToolProvider] = [] + result: list[ToolProviderApiEntity] = [] for provider in db_providers: # convert provider controller to user provider diff --git a/api/services/tools/builtin_tools_manage_service.py b/api/services/tools/builtin_tools_manage_service.py index 83b363bb580588..c3d778558bedaf 100644 --- a/api/services/tools/builtin_tools_manage_service.py +++ b/api/services/tools/builtin_tools_manage_service.py @@ -5,9 +5,8 @@ from configs import dify_config from core.helper.position_helper import is_filtered from core.model_runtime.utils.encoders import jsonable_encoder -from core.tools.__base.tool_provider import ToolProviderController from core.tools.builtin_tool.providers._positions import BuiltinToolProviderSort -from core.tools.entities.api_entities import UserTool, UserToolProvider +from core.tools.entities.api_entities import ToolApiEntity, ToolProviderApiEntity from core.tools.errors import ToolNotFoundError, ToolProviderCredentialValidationError, ToolProviderNotFoundError from core.tools.tool_label_manager import ToolLabelManager from core.tools.tool_manager import ToolManager @@ -21,11 +20,17 @@ class BuiltinToolManageService: @staticmethod - def list_builtin_tool_provider_tools(user_id: str, tenant_id: str, provider: str) -> list[UserTool]: + def list_builtin_tool_provider_tools(user_id: str, tenant_id: str, provider: str) -> list[ToolApiEntity]: """ list builtin tool provider tools + + :param user_id: the id of the user + :param tenant_id: the id of the tenant + :param provider: the name of the provider + + :return: the list of tools """ - provider_controller: ToolProviderController = ToolManager.get_builtin_provider(provider) + provider_controller = ToolManager.get_builtin_provider(provider, tenant_id) tools = provider_controller.get_tools() tool_provider_configurations = ProviderConfigEncrypter( @@ -64,14 +69,16 @@ def list_builtin_tool_provider_tools(user_id: str, tenant_id: str, provider: str return result @staticmethod - def list_builtin_provider_credentials_schema(provider_name): + def list_builtin_provider_credentials_schema(provider_name: str, tenant_id: str): """ list builtin provider credentials schema + :param provider_name: the name of the provider + :param tenant_id: the id of the tenant :return: the list of tool providers """ - provider = ToolManager.get_builtin_provider(provider_name) - return jsonable_encoder([v for _, v in (provider.entity.credentials_schema or {}).items()]) + provider = ToolManager.get_builtin_provider(provider_name, tenant_id) + return jsonable_encoder([v for _, v in (provider.get_credentials_schema() or {}).items()]) @staticmethod def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: str, credentials: dict): @@ -90,7 +97,7 @@ def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st try: # get provider - provider_controller = ToolManager.get_builtin_provider(provider_name) + provider_controller = ToolManager.get_builtin_provider(provider_name, tenant_id) if not provider_controller.need_credentials: raise ValueError(f"provider {provider_name} does not need credentials") tool_configuration = ProviderConfigEncrypter( @@ -109,7 +116,7 @@ def update_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st if name in masked_credentials and value == masked_credentials[name]: credentials[name] = original_credentials[name] # validate credentials - provider_controller.validate_credentials(credentials) + provider_controller.validate_credentials(user_id, credentials) # encrypt credentials credentials = tool_configuration.encrypt(credentials) except (ToolProviderNotFoundError, ToolNotFoundError, ToolProviderCredentialValidationError) as e: @@ -154,7 +161,7 @@ def get_builtin_tool_provider_credentials(user_id: str, tenant_id: str, provider if provider_obj is None: return {} - provider_controller = ToolManager.get_builtin_provider(provider_obj.provider) + provider_controller = ToolManager.get_builtin_provider(provider_obj.provider, tenant_id) tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), @@ -186,7 +193,7 @@ def delete_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st db.session.commit() # delete cache - provider_controller = ToolManager.get_builtin_provider(provider_name) + provider_controller = ToolManager.get_builtin_provider(provider_name, tenant_id) tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), @@ -198,22 +205,22 @@ def delete_builtin_tool_provider(user_id: str, tenant_id: str, provider_name: st return {"result": "success"} @staticmethod - def get_builtin_tool_provider_icon(provider: str): + def get_builtin_tool_provider_icon(provider: str, tenant_id: str): """ get tool provider icon and it's mimetype """ - icon_path, mime_type = ToolManager.get_builtin_provider_icon(provider) + icon_path, mime_type = ToolManager.get_builtin_provider_icon(provider, tenant_id) icon_bytes = Path(icon_path).read_bytes() return icon_bytes, mime_type @staticmethod - def list_builtin_tools(user_id: str, tenant_id: str) -> list[UserToolProvider]: + def list_builtin_tools(user_id: str, tenant_id: str) -> list[ToolProviderApiEntity]: """ list builtin tools """ # get all builtin providers - provider_controllers = ToolManager.list_builtin_providers() + provider_controllers = ToolManager.list_builtin_providers(tenant_id) # get all user added providers db_providers: list[BuiltinToolProvider] = ( @@ -225,7 +232,7 @@ def list_builtin_tools(user_id: str, tenant_id: str) -> list[UserToolProvider]: filter(lambda db_provider: db_provider.provider == provider, db_providers), None ) - result: list[UserToolProvider] = [] + result: list[ToolProviderApiEntity] = [] for provider_controller in provider_controllers: try: diff --git a/api/services/tools/tools_manage_service.py b/api/services/tools/tools_manage_service.py index 1c67f7648ca99f..184596fc23c95b 100644 --- a/api/services/tools/tools_manage_service.py +++ b/api/services/tools/tools_manage_service.py @@ -1,6 +1,6 @@ import logging -from core.tools.entities.api_entities import UserToolProviderTypeLiteral +from core.tools.entities.api_entities import ToolProviderTypeApiLiteral from core.tools.tool_manager import ToolManager from services.tools.tools_transform_service import ToolTransformService @@ -9,7 +9,7 @@ class ToolCommonService: @staticmethod - def list_tool_providers(user_id: str, tenant_id: str, typ: UserToolProviderTypeLiteral = None): + def list_tool_providers(user_id: str, tenant_id: str, typ: ToolProviderTypeApiLiteral = None): """ list tool providers diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index d4f132e902d08e..4c2876dca34a06 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -7,7 +7,7 @@ from core.tools.__base.tool_runtime import ToolRuntime from core.tools.builtin_tool.provider import BuiltinToolProviderController from core.tools.custom_tool.provider import ApiToolProviderController -from core.tools.entities.api_entities import UserTool, UserToolProvider +from core.tools.entities.api_entities import ToolApiEntity, ToolProviderApiEntity from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ( @@ -15,6 +15,7 @@ ToolParameter, ToolProviderType, ) +from core.tools.plugin_tool.provider import PluginToolProviderController from core.tools.utils.configuration import ProviderConfigEncrypter from core.tools.workflow_as_tool.provider import WorkflowToolProviderController from core.tools.workflow_as_tool.tool import WorkflowTool @@ -44,7 +45,7 @@ def get_tool_provider_icon_url(cls, provider_type: str, provider_name: str, icon return "" @staticmethod - def repack_provider(provider: Union[dict, UserToolProvider]): + def repack_provider(provider: Union[dict, ToolProviderApiEntity]): """ repack provider @@ -54,7 +55,7 @@ def repack_provider(provider: Union[dict, UserToolProvider]): provider["icon"] = ToolTransformService.get_tool_provider_icon_url( provider_type=provider["type"], provider_name=provider["name"], icon=provider["icon"] ) - elif isinstance(provider, UserToolProvider): + elif isinstance(provider, ToolProviderApiEntity): provider.icon = ToolTransformService.get_tool_provider_icon_url( provider_type=provider.type.value, provider_name=provider.name, icon=provider.icon ) @@ -62,14 +63,14 @@ def repack_provider(provider: Union[dict, UserToolProvider]): @classmethod def builtin_provider_to_user_provider( cls, - provider_controller: BuiltinToolProviderController, + provider_controller: BuiltinToolProviderController | PluginToolProviderController, db_provider: Optional[BuiltinToolProvider], decrypt_credentials: bool = True, - ) -> UserToolProvider: + ) -> ToolProviderApiEntity: """ convert provider controller to user provider """ - result = UserToolProvider( + result = ToolProviderApiEntity( id=provider_controller.entity.identity.name, author=provider_controller.entity.identity.author, name=provider_controller.entity.identity.name, @@ -154,7 +155,7 @@ def workflow_provider_to_user_provider( """ convert provider controller to user provider """ - return UserToolProvider( + return ToolProviderApiEntity( id=provider_controller.provider_id, author=provider_controller.entity.identity.author, name=provider_controller.entity.identity.name, @@ -181,7 +182,7 @@ def api_provider_to_user_provider( db_provider: ApiToolProvider, decrypt_credentials: bool = True, labels: list[str] | None = None, - ) -> UserToolProvider: + ) -> ToolProviderApiEntity: """ convert provider controller to user provider """ @@ -197,7 +198,7 @@ def api_provider_to_user_provider( # add provider into providers credentials = db_provider.credentials - result = UserToolProvider( + result = ToolProviderApiEntity( id=db_provider.id, author=username, name=db_provider.name, @@ -240,7 +241,7 @@ def tool_to_user_tool( tenant_id: str, credentials: dict | None = None, labels: list[str] | None = None, - ) -> UserTool: + ) -> ToolApiEntity: """ convert tool to user tool """ @@ -248,7 +249,7 @@ def tool_to_user_tool( # fork tool runtime tool = tool.fork_tool_runtime( runtime=ToolRuntime( - credentials=credentials, + credentials=credentials or {}, tenant_id=tenant_id, ) ) @@ -270,7 +271,7 @@ def tool_to_user_tool( if not found and runtime_parameter.form == ToolParameter.ToolParameterForm.FORM: current_parameters.append(runtime_parameter) - return UserTool( + return ToolApiEntity( author=tool.entity.identity.author, name=tool.entity.identity.name, label=tool.entity.identity.label, @@ -279,7 +280,7 @@ def tool_to_user_tool( labels=labels or [], ) if isinstance(tool, ApiToolBundle): - return UserTool( + return ToolApiEntity( author=tool.author, name=tool.operation_id, label=I18nObject(en_US=tool.operation_id, zh_Hans=tool.operation_id), diff --git a/api/services/tools/workflow_tools_manage_service.py b/api/services/tools/workflow_tools_manage_service.py index 58bf7946bf190f..3178fe7999ee6b 100644 --- a/api/services/tools/workflow_tools_manage_service.py +++ b/api/services/tools/workflow_tools_manage_service.py @@ -4,7 +4,7 @@ from sqlalchemy import or_ from core.model_runtime.utils.encoders import jsonable_encoder -from core.tools.entities.api_entities import UserTool, UserToolProvider +from core.tools.entities.api_entities import ToolApiEntity, ToolProviderApiEntity from core.tools.tool_label_manager import ToolLabelManager from core.tools.utils.workflow_configuration_sync import WorkflowToolConfigurationUtils from core.tools.workflow_as_tool.provider import WorkflowToolProviderController @@ -183,7 +183,7 @@ def update_workflow_tool( return {"result": "success"} @classmethod - def list_tenant_workflow_tools(cls, user_id: str, tenant_id: str) -> list[UserToolProvider]: + def list_tenant_workflow_tools(cls, user_id: str, tenant_id: str) -> list[ToolProviderApiEntity]: """ List workflow tools. :param user_id: the user id @@ -309,7 +309,7 @@ def _get_workflow_tool(cls, tenant_id: str, db_tool: WorkflowToolProvider | None } @classmethod - def list_single_workflow_tools(cls, user_id: str, tenant_id: str, workflow_tool_id: str) -> list[UserTool]: + def list_single_workflow_tools(cls, user_id: str, tenant_id: str, workflow_tool_id: str) -> list[ToolApiEntity]: """ List workflow tool provider tools. :param user_id: the user id From 947bfdc8075d9f3a3ef4392770bb991050cfb473 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Mon, 23 Sep 2024 21:13:02 +0800 Subject: [PATCH 042/325] feat: validate credentials --- api/core/plugin/entities/plugin_daemon.py | 9 ++++- api/core/plugin/manager/base.py | 23 ++++++++----- api/core/plugin/manager/tool.py | 40 +++++++++++++++++++---- 3 files changed, 56 insertions(+), 16 deletions(-) diff --git a/api/core/plugin/entities/plugin_daemon.py b/api/core/plugin/entities/plugin_daemon.py index 51cc36d7dfeda8..c5dced121faa05 100644 --- a/api/core/plugin/entities/plugin_daemon.py +++ b/api/core/plugin/entities/plugin_daemon.py @@ -35,4 +35,11 @@ class PluginToolProviderEntity(BaseModel): provider: str plugin_unique_identifier: str plugin_id: str - declaration: ToolProviderEntityWithPlugin \ No newline at end of file + declaration: ToolProviderEntityWithPlugin + + +class PluginBasicBooleanResponse(BaseModel): + """ + Basic boolean response from plugin daemon. + """ + result: bool \ No newline at end of file diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index 8b80d923f64425..dac6d9d63f387a 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -1,5 +1,5 @@ import json -from collections.abc import Generator +from collections.abc import Callable, Generator from typing import TypeVar import requests @@ -21,7 +21,7 @@ def _request( method: str, path: str, headers: dict | None = None, - data: bytes | dict | None = None, + data: bytes | dict | str | None = None, params: dict | None = None, stream: bool = False, ) -> requests.Response: @@ -31,6 +31,10 @@ def _request( url = URL(str(plugin_daemon_inner_api_baseurl)) / path headers = headers or {} headers["X-Api-Key"] = plugin_daemon_inner_api_key + + if headers.get("Content-Type") == "application/json" and isinstance(data, dict): + data = json.dumps(data) + response = requests.request( method=method, url=str(url), headers=headers, data=data, params=params, stream=stream ) @@ -48,7 +52,11 @@ def _stream_request( Make a stream request to the plugin daemon inner API """ response = self._request(method, path, headers, data, params, stream=True) - yield from response.iter_lines() + for line in response.iter_lines(): + line = line.decode("utf-8").strip() + if line.startswith("data:"): + line = line[5:].strip() + yield line def _stream_request_with_model( self, @@ -88,17 +96,15 @@ def _request_with_plugin_daemon_response( headers: dict | None = None, data: bytes | dict | None = None, params: dict | None = None, + transformer: Callable[[dict], dict] | None = None, ) -> T: """ Make a request to the plugin daemon inner API and return the response as a model. """ response = self._request(method, path, headers, data, params) json_response = response.json() - for provider in json_response.get("data", []): - declaration = provider.get("declaration", {}) or {} - provider_name = declaration.get("identity", {}).get("name") - for tool in declaration.get("tools", []): - tool["identity"]["provider"] = provider_name + if transformer: + json_response = transformer(json_response) rep = PluginDaemonBasicResponse[type](**json_response) if rep.code != 0: @@ -128,3 +134,4 @@ def _request_with_plugin_daemon_response_stream( if rep.data is None: raise ValueError("got empty data from plugin daemon") yield rep.data + \ No newline at end of file diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py index fe5f7bb757d84e..a26fa0dd2673cd 100644 --- a/api/core/plugin/manager/tool.py +++ b/api/core/plugin/manager/tool.py @@ -1,7 +1,7 @@ from collections.abc import Generator from typing import Any -from core.plugin.entities.plugin_daemon import PluginToolProviderEntity +from core.plugin.entities.plugin_daemon import PluginBasicBooleanResponse, PluginToolProviderEntity from core.plugin.manager.base import BasePluginManager from core.tools.entities.tool_entities import ToolInvokeMessage @@ -11,8 +11,22 @@ def fetch_tool_providers(self, tenant_id: str) -> list[PluginToolProviderEntity] """ Fetch tool providers for the given asset. """ + + def transformer(json_response: dict[str, Any]) -> dict: + for provider in json_response.get("data", []): + declaration = provider.get("declaration", {}) or {} + provider_name = declaration.get("identity", {}).get("name") + for tool in declaration.get("tools", []): + tool["identity"]["provider"] = provider_name + + return json_response + response = self._request_with_plugin_daemon_response( - "GET", f"plugin/{tenant_id}/tools", list[PluginToolProviderEntity], params={"page": 1, "page_size": 256} + "GET", + f"plugin/{tenant_id}/management/tools", + list[PluginToolProviderEntity], + params={"page": 1, "page_size": 256}, + transformer=transformer, ) return response @@ -28,7 +42,7 @@ def invoke( ) -> Generator[ToolInvokeMessage, None, None]: response = self._request_with_plugin_daemon_response_stream( "POST", - f"plugin/{tenant_id}/tool/invoke", + f"plugin/{tenant_id}/dispatch/tool/invoke", ToolInvokeMessage, data={ "plugin_unique_identifier": plugin_unique_identifier, @@ -40,6 +54,10 @@ def invoke( "tool_parameters": tool_parameters, }, }, + headers={ + "X-Plugin-Identifier": plugin_unique_identifier, + "Content-Type": "application/json", + } ) return response @@ -49,10 +67,10 @@ def validate_provider_credentials( """ validate the credentials of the provider """ - response = self._request_with_plugin_daemon_response( + response = self._request_with_plugin_daemon_response_stream( "POST", - f"plugin/{tenant_id}/tool/validate_credentials", - bool, + f"plugin/{tenant_id}/dispatch/tool/validate_credentials", + PluginBasicBooleanResponse, data={ "plugin_unique_identifier": plugin_unique_identifier, "user_id": user_id, @@ -61,5 +79,13 @@ def validate_provider_credentials( "credentials": credentials, }, }, + headers={ + "X-Plugin-Identifier": plugin_unique_identifier, + "Content-Type": "application/json", + } ) - return response + + for resp in response: + return resp.result + + return False From fb3a701c86b0bc29ef6d627a65274ddd95ba97dd Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 24 Sep 2024 16:02:01 +0800 Subject: [PATCH 043/325] fix: stream with empty line --- api/core/plugin/manager/base.py | 3 ++- api/core/workflow/nodes/tool/tool_node.py | 4 ++-- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index dac6d9d63f387a..fdc15f633c043d 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -56,7 +56,8 @@ def _stream_request( line = line.decode("utf-8").strip() if line.startswith("data:"): line = line[5:].strip() - yield line + if line: + yield line def _stream_request_with_model( self, diff --git a/api/core/workflow/nodes/tool/tool_node.py b/api/core/workflow/nodes/tool/tool_node.py index 73c22bc700407a..2bcd0b10f2f3a5 100644 --- a/api/core/workflow/nodes/tool/tool_node.py +++ b/api/core/workflow/nodes/tool/tool_node.py @@ -212,8 +212,8 @@ def _transform_message( chunk_content=message.message.text, from_variable_selector=[self.node_id, "text"] ) elif message.type == ToolInvokeMessage.MessageType.JSON: - assert isinstance(message, ToolInvokeMessage.JsonMessage) - json.append(message.json_object) + assert isinstance(message.message, ToolInvokeMessage.JsonMessage) + json.append(message.message.json_object) elif message.type == ToolInvokeMessage.MessageType.LINK: assert isinstance(message.message, ToolInvokeMessage.TextMessage) stream_text = f"Link: {message.message.text}\n" From 1907d791e1762aae7db732eae63ead3c98c62638 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 24 Sep 2024 16:15:50 +0800 Subject: [PATCH 044/325] enhance: add gzip --- api/core/plugin/manager/base.py | 1 + 1 file changed, 1 insertion(+) diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index fdc15f633c043d..fd18b3798e9b6a 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -31,6 +31,7 @@ def _request( url = URL(str(plugin_daemon_inner_api_baseurl)) / path headers = headers or {} headers["X-Api-Key"] = plugin_daemon_inner_api_key + headers["Accept-Encoding"] = "gzip, deflate, br" if headers.get("Content-Type") == "application/json" and isinstance(data, dict): data = json.dumps(data) From 9722e6bcb1a49e18e7a736d940082b439d457bb2 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 24 Sep 2024 16:33:19 +0800 Subject: [PATCH 045/325] fix: allow duplicate tool providers --- api/core/tools/plugin_tool/tool.py | 2 +- api/core/tools/tool_manager.py | 11 +++++++++-- 2 files changed, 10 insertions(+), 3 deletions(-) diff --git a/api/core/tools/plugin_tool/tool.py b/api/core/tools/plugin_tool/tool.py index 898e8a552d0f6d..dd47f11ba27a2e 100644 --- a/api/core/tools/plugin_tool/tool.py +++ b/api/core/tools/plugin_tool/tool.py @@ -38,4 +38,4 @@ def fork_tool_runtime(self, runtime: ToolRuntime) -> "PluginTool": runtime=runtime, tenant_id=self.tenant_id, plugin_unique_identifier=self.plugin_unique_identifier, - ) \ No newline at end of file + ) diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 76c7232e01129d..a4b834e8d88af6 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -485,7 +485,7 @@ def get_tool_label(cls, tool_name: str) -> Union[I18nObject, None]: return cls._builtin_tools_labels[tool_name] @classmethod - def user_list_providers( + def list_providers_from_api( cls, user_id: str, tenant_id: str, typ: ToolProviderTypeApiLiteral ) -> list[ToolProviderApiEntity]: result_providers: dict[str, ToolProviderApiEntity] = {} @@ -526,7 +526,14 @@ def user_list_providers( decrypt_credentials=False, ) - result_providers[provider.entity.identity.name] = user_provider + if isinstance(provider, PluginToolProviderController): + result_providers[f"plugin_provider.{user_provider.name}.{provider.plugin_unique_identifier}"] = ( + user_provider + ) + else: + result_providers[f"builtin_provider.{user_provider.name}"] = ( + user_provider + ) # get db api providers From 64706c709cfb4526d43865224f2cad09b57ff3bc Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 24 Sep 2024 16:35:01 +0800 Subject: [PATCH 046/325] fix --- api/services/tools/tools_manage_service.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/api/services/tools/tools_manage_service.py b/api/services/tools/tools_manage_service.py index 184596fc23c95b..a9d0d0f86a0c92 100644 --- a/api/services/tools/tools_manage_service.py +++ b/api/services/tools/tools_manage_service.py @@ -15,7 +15,7 @@ def list_tool_providers(user_id: str, tenant_id: str, typ: ToolProviderTypeApiLi :return: the list of tool providers """ - providers = ToolManager.user_list_providers(user_id, tenant_id, typ) + providers = ToolManager.list_providers_from_api(user_id, tenant_id, typ) # add icon for provider in providers: From 592f85f7a904076592f78e83900af4ab1a3ef141 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 24 Sep 2024 16:40:42 +0800 Subject: [PATCH 047/325] formatter --- api/services/tools/tools_transform_service.py | 24 ++++--------------- 1 file changed, 4 insertions(+), 20 deletions(-) diff --git a/api/services/tools/tools_transform_service.py b/api/services/tools/tools_transform_service.py index 81d0ed762b6d11..e74301fe9de471 100644 --- a/api/services/tools/tools_transform_service.py +++ b/api/services/tools/tools_transform_service.py @@ -74,19 +74,9 @@ def builtin_provider_to_user_provider( id=provider_controller.entity.identity.name, author=provider_controller.entity.identity.author, name=provider_controller.entity.identity.name, - description=I18nObject( - en_US=provider_controller.entity.identity.description.en_US, - zh_Hans=provider_controller.entity.identity.description.zh_Hans, - pt_BR=provider_controller.entity.identity.description.pt_BR, - ja_JP=provider_controller.entity.identity.description.ja_JP, - ), + description=provider_controller.entity.identity.description, icon=provider_controller.entity.identity.icon, - label=I18nObject( - en_US=provider_controller.entity.identity.label.en_US, - zh_Hans=provider_controller.entity.identity.label.zh_Hans, - pt_BR=provider_controller.entity.identity.label.pt_BR, - ja_JP=provider_controller.entity.identity.label.ja_JP, - ), + label=provider_controller.entity.identity.label, type=ToolProviderType.BUILT_IN, masked_credentials={}, is_team_authorization=False, @@ -161,15 +151,9 @@ def workflow_provider_to_user_provider( id=provider_controller.provider_id, author=provider_controller.entity.identity.author, name=provider_controller.entity.identity.name, - description=I18nObject( - en_US=provider_controller.entity.identity.description.en_US, - zh_Hans=provider_controller.entity.identity.description.zh_Hans, - ), + description=provider_controller.entity.identity.description, icon=provider_controller.entity.identity.icon, - label=I18nObject( - en_US=provider_controller.entity.identity.label.en_US, - zh_Hans=provider_controller.entity.identity.label.zh_Hans, - ), + label=provider_controller.entity.identity.label, type=ToolProviderType.WORKFLOW, masked_credentials={}, is_team_authorization=True, From 68c10a1672f51c3f3ddb45f1e20615fc15a0cb99 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 24 Sep 2024 18:03:48 +0800 Subject: [PATCH 048/325] feat: add backwards invoke node api --- api/controllers/inner_api/plugin/plugin.py | 70 ++++++++---- api/core/plugin/backwards_invocation/node.py | 114 +++++++++++++++++++ api/core/plugin/entities/request.py | 30 ++++- api/core/workflow/workflow_entry.py | 82 +++++++++++++ api/services/workflow_service.py | 81 ++++++++++--- 5 files changed, 335 insertions(+), 42 deletions(-) create mode 100644 api/core/plugin/backwards_invocation/node.py diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index 4c28e6acb3c202..ae3533268927a2 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -8,13 +8,15 @@ from controllers.inner_api.wraps import plugin_inner_api_only from core.plugin.backwards_invocation.app import PluginAppBackwardsInvocation from core.plugin.backwards_invocation.model import PluginModelBackwardsInvocation +from core.plugin.backwards_invocation.node import PluginNodeBackwardsInvocation from core.plugin.encrypt import PluginEncrypter from core.plugin.entities.request import ( RequestInvokeApp, RequestInvokeEncrypt, RequestInvokeLLM, RequestInvokeModeration, - RequestInvokeNode, + RequestInvokeParameterExtractorNode, + RequestInvokeQuestionClassifierNode, RequestInvokeRerank, RequestInvokeSpeech2Text, RequestInvokeTextEmbedding, @@ -96,23 +98,46 @@ def generator(): yield ( ToolInvokeMessage( type=ToolInvokeMessage.MessageType.TEXT, - message=ToolInvokeMessage.TextMessage(text='helloworld'), + message=ToolInvokeMessage.TextMessage(text="helloworld"), ) .model_dump_json() .encode() - + b'\n\n' + + b"\n\n" ) return compact_generate_response(generator()) -class PluginInvokeNodeApi(Resource): +class PluginInvokeParameterExtractorNodeApi(Resource): @setup_required @plugin_inner_api_only @get_tenant - @plugin_data(payload_type=RequestInvokeNode) - def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeNode): - pass + @plugin_data(payload_type=RequestInvokeParameterExtractorNode) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeParameterExtractorNode): + return PluginNodeBackwardsInvocation.invoke_parameter_extractor( + tenant_id=tenant_model.id, + user_id=user_id, + parameters=payload.parameters, + model_config=payload.model, + instruction=payload.instruction, + query=payload.query, + ) + + +class PluginInvokeQuestionClassifierNodeApi(Resource): + @setup_required + @plugin_inner_api_only + @get_tenant + @plugin_data(payload_type=RequestInvokeQuestionClassifierNode) + def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeQuestionClassifierNode): + return PluginNodeBackwardsInvocation.invoke_question_classifier( + tenant_id=tenant_model.id, + user_id=user_id, + query=payload.query, + model_config=payload.model, + classes=payload.classes, + instruction=payload.instruction, + ) class PluginInvokeAppApi(Resource): @@ -127,15 +152,13 @@ def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeApp): tenant_id=tenant_model.id, conversation_id=payload.conversation_id, query=payload.query, - stream=payload.response_mode == 'streaming', + stream=payload.response_mode == "streaming", inputs=payload.inputs, - files=payload.files - ) - - return compact_generate_response( - PluginAppBackwardsInvocation.convert_to_event_stream(response) + files=payload.files, ) + return compact_generate_response(PluginAppBackwardsInvocation.convert_to_event_stream(response)) + class PluginInvokeEncryptApi(Resource): @setup_required @@ -149,13 +172,14 @@ def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeEncrypt return PluginEncrypter.invoke_encrypt(tenant_model, payload) -api.add_resource(PluginInvokeLLMApi, '/invoke/llm') -api.add_resource(PluginInvokeTextEmbeddingApi, '/invoke/text-embedding') -api.add_resource(PluginInvokeRerankApi, '/invoke/rerank') -api.add_resource(PluginInvokeTTSApi, '/invoke/tts') -api.add_resource(PluginInvokeSpeech2TextApi, '/invoke/speech2text') -api.add_resource(PluginInvokeModerationApi, '/invoke/moderation') -api.add_resource(PluginInvokeToolApi, '/invoke/tool') -api.add_resource(PluginInvokeNodeApi, '/invoke/node') -api.add_resource(PluginInvokeAppApi, '/invoke/app') -api.add_resource(PluginInvokeEncryptApi, '/invoke/encrypt') +api.add_resource(PluginInvokeLLMApi, "/invoke/llm") +api.add_resource(PluginInvokeTextEmbeddingApi, "/invoke/text-embedding") +api.add_resource(PluginInvokeRerankApi, "/invoke/rerank") +api.add_resource(PluginInvokeTTSApi, "/invoke/tts") +api.add_resource(PluginInvokeSpeech2TextApi, "/invoke/speech2text") +api.add_resource(PluginInvokeModerationApi, "/invoke/moderation") +api.add_resource(PluginInvokeToolApi, "/invoke/tool") +api.add_resource(PluginInvokeParameterExtractorNodeApi, "/invoke/parameter-extractor") +api.add_resource(PluginInvokeQuestionClassifierNodeApi, "/invoke/question-classifier") +api.add_resource(PluginInvokeAppApi, "/invoke/app") +api.add_resource(PluginInvokeEncryptApi, "/invoke/encrypt") diff --git a/api/core/plugin/backwards_invocation/node.py b/api/core/plugin/backwards_invocation/node.py new file mode 100644 index 00000000000000..9a7fd5fc3a3491 --- /dev/null +++ b/api/core/plugin/backwards_invocation/node.py @@ -0,0 +1,114 @@ +from core.plugin.backwards_invocation.base import BaseBackwardsInvocation +from core.workflow.nodes.parameter_extractor.entities import ( + ModelConfig as ParameterExtractorModelConfig, +) +from core.workflow.nodes.parameter_extractor.entities import ( + ParameterConfig, + ParameterExtractorNodeData, +) +from core.workflow.nodes.question_classifier.entities import ( + ClassConfig, + QuestionClassifierNodeData, +) +from core.workflow.nodes.question_classifier.entities import ( + ModelConfig as QuestionClassifierModelConfig, +) +from services.workflow_service import WorkflowService + + +class PluginNodeBackwardsInvocation(BaseBackwardsInvocation): + @classmethod + def invoke_parameter_extractor( + cls, + tenant_id: str, + user_id: str, + parameters: list[ParameterConfig], + model_config: ParameterExtractorModelConfig, + instruction: str, + query: str, + ) -> dict: + """ + Invoke parameter extractor node. + + :param tenant_id: str + :param user_id: str + :param parameters: list[ParameterConfig] + :param model_config: ModelConfig + :param instruction: str + :param query: str + :return: dict with __reason, __is_success, and other parameters + """ + workflow_service = WorkflowService() + node_id = "1919810" + node_data = ParameterExtractorNodeData( + title="parameter_extractor", + desc="parameter_extractor", + parameters=parameters, + reasoning_mode="function_call", + query=[node_id, "query"], + model=model_config, + instruction=instruction, # instruct with variables are not supported + ) + node_data_dict = node_data.model_dump() + execution = workflow_service.run_free_workflow_node( + node_data_dict, + tenant_id=tenant_id, + user_id=user_id, + node_id=node_id, + user_inputs={ + f"{node_id}.query": query, + }, + ) + + output = execution.outputs_dict + return output or { + "__reason": "No parameters extracted", + "__is_success": False, + } + + @classmethod + def invoke_question_classifier( + cls, + tenant_id: str, + user_id: str, + model_config: QuestionClassifierModelConfig, + classes: list[ClassConfig], + instruction: str, + query: str, + ) -> dict: + """ + Invoke question classifier node. + + :param tenant_id: str + :param user_id: str + :param model_config: ModelConfig + :param classes: list[ClassConfig] + :param instruction: str + :param query: str + :return: dict with class_name + """ + workflow_service = WorkflowService() + node_id = "1919810" + node_data = QuestionClassifierNodeData( + title="question_classifier", + desc="question_classifier", + query_variable_selector=[node_id, "query"], + model=model_config, + classes=classes, + instruction=instruction, # instruct with variables are not supported + ) + node_data_dict = node_data.model_dump() + execution = workflow_service.run_free_workflow_node( + node_data_dict, + tenant_id=tenant_id, + user_id=user_id, + node_id=node_id, + user_inputs={ + f"{node_id}.query": query, + }, + ) + + output = execution.outputs_dict + return output or { + "class_name": classes[0].name, + } diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 2e87b76636ca2d..bf4c4448c77243 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -14,6 +14,16 @@ UserPromptMessage, ) from core.model_runtime.entities.model_entities import ModelType +from core.workflow.nodes.question_classifier.entities import ( + ClassConfig, + ModelConfig as QuestionClassifierModelConfig, +) +from core.workflow.nodes.parameter_extractor.entities import ( + ModelConfig as ParameterExtractorModelConfig, +) +from core.workflow.nodes.parameter_extractor.entities import ( + ParameterConfig, +) class RequestInvokeTool(BaseModel): @@ -92,11 +102,27 @@ class RequestInvokeModeration(BaseModel): """ -class RequestInvokeNode(BaseModel): +class RequestInvokeParameterExtractorNode(BaseModel): """ - Request to invoke node + Request to invoke parameter extractor node """ + parameters: list[ParameterConfig] + model: ParameterExtractorModelConfig + instruction: str + query: str + + +class RequestInvokeQuestionClassifierNode(BaseModel): + """ + Request to invoke question classifier node + """ + + query: str + model: QuestionClassifierModelConfig + classes: list[ClassConfig] + instruction: str + class RequestInvokeApp(BaseModel): """ diff --git a/api/core/workflow/workflow_entry.py b/api/core/workflow/workflow_entry.py index 74a598ada58544..9477e98c926881 100644 --- a/api/core/workflow/workflow_entry.py +++ b/api/core/workflow/workflow_entry.py @@ -205,6 +205,88 @@ def single_step_run( except Exception as e: raise WorkflowNodeRunFailedError(node_instance=node_instance, error=str(e)) + @classmethod + def run_free_node( + cls, node_data: dict, node_id: str, tenant_id: str, user_id: str, user_inputs: dict[str, Any] + ) -> tuple[BaseNode, Generator[RunEvent | InNodeEvent, None, None]]: + """ + Run free node + + NOTE: only parameter_extractor/question_classifier are supported + + :param node_data: node data + :param user_id: user id + :param user_inputs: user inputs + :return: + """ + # generate a fake graph + node_config = {"id": node_id, "width": 114, "height": 514, "type": "custom", "data": node_data} + graph_dict = { + "nodes": [node_config], + } + + node_type = NodeType.value_of(node_data.get("type", "")) + if node_type not in {NodeType.PARAMETER_EXTRACTOR, NodeType.QUESTION_CLASSIFIER}: + raise ValueError(f"Node type {node_type} not supported") + + node_cls = node_classes.get(node_type) + if not node_cls: + raise ValueError(f"Node class not found for node type {node_type}") + + graph = Graph.init(graph_config=graph_dict) + + # init variable pool + variable_pool = VariablePool( + system_variables={}, + user_inputs={}, + environment_variables=[], + ) + + node_cls = cast(type[BaseNode], node_cls) + # init workflow run state + node_instance: BaseNode = node_cls( + id=str(uuid.uuid4()), + config=node_config, + graph_init_params=GraphInitParams( + tenant_id=tenant_id, + app_id="", + workflow_type=WorkflowType.WORKFLOW, + workflow_id="", + graph_config=graph_dict, + user_id=user_id, + user_from=UserFrom.ACCOUNT, + invoke_from=InvokeFrom.DEBUGGER, + call_depth=0, + ), + graph=graph, + graph_runtime_state=GraphRuntimeState(variable_pool=variable_pool, start_at=time.perf_counter()), + ) + + try: + # variable selector to variable mapping + try: + variable_mapping = node_cls.extract_variable_selector_to_variable_mapping( + graph_config=graph_dict, config=node_config + ) + except NotImplementedError: + variable_mapping = {} + + cls.mapping_user_inputs_to_variable_pool( + variable_mapping=variable_mapping, + user_inputs=user_inputs, + variable_pool=variable_pool, + tenant_id=tenant_id, + node_type=node_type, + node_data=node_instance.node_data, + ) + + # run node + generator = node_instance.run() + + return node_instance, generator + except Exception as e: + raise WorkflowNodeRunFailedError(node_instance=node_instance, error=str(e)) + @classmethod def handle_special_values(cls, value: Optional[Mapping[str, Any]]) -> Optional[dict]: """ diff --git a/api/services/workflow_service.py b/api/services/workflow_service.py index 0ff81f1f7e834d..399451cb8e446c 100644 --- a/api/services/workflow_service.py +++ b/api/services/workflow_service.py @@ -1,8 +1,8 @@ import json import time -from collections.abc import Sequence +from collections.abc import Callable, Generator, Sequence from datetime import datetime, timezone -from typing import Optional +from typing import Any, Optional from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager @@ -10,7 +10,9 @@ from core.model_runtime.utils.encoders import jsonable_encoder from core.workflow.entities.node_entities import NodeRunResult, NodeType from core.workflow.errors import WorkflowNodeRunFailedError -from core.workflow.nodes.event import RunCompletedEvent +from core.workflow.graph_engine.entities.event import InNodeEvent +from core.workflow.nodes.base_node import BaseNode +from core.workflow.nodes.event import RunCompletedEvent, RunEvent from core.workflow.nodes.node_mapping import node_classes from core.workflow.workflow_entry import WorkflowEntry from events.app_event import app_draft_workflow_was_synced, app_published_workflow_was_updated @@ -216,13 +218,64 @@ def run_draft_workflow_node( # run draft workflow node start_at = time.perf_counter() - try: - node_instance, generator = WorkflowEntry.single_step_run( + workflow_node_execution = self._handle_node_run_result( + getter=lambda: WorkflowEntry.single_step_run( workflow=draft_workflow, node_id=node_id, user_inputs=user_inputs, user_id=account.id, - ) + ), + start_at=start_at, + tenant_id=app_model.tenant_id, + node_id=node_id, + ) + + db.session.add(workflow_node_execution) + db.session.commit() + + return workflow_node_execution + + def run_free_workflow_node( + self, node_data: dict, tenant_id: str, user_id: str, node_id: str, user_inputs: dict[str, Any] + ) -> WorkflowNodeExecution: + """ + Run draft workflow node + """ + # run draft workflow node + start_at = time.perf_counter() + + workflow_node_execution = self._handle_node_run_result( + getter=lambda: WorkflowEntry.run_free_node( + node_id=node_id, + node_data=node_data, + tenant_id=tenant_id, + user_id=user_id, + user_inputs=user_inputs, + ), + start_at=start_at, + tenant_id=tenant_id, + node_id=node_id + ) + + return workflow_node_execution + + def _handle_node_run_result( + self, + getter: Callable[[], tuple[BaseNode, Generator[RunEvent | InNodeEvent, None, None]]], + start_at: float, + tenant_id: str, + node_id: str, + ): + """ + Handle node run result + + :param getter: Callable[[], tuple[BaseNode, Generator[RunEvent | InNodeEvent, None, None]]] + :param start_at: float + :param tenant_id: str + :param node_id: str + """ + try: + node_instance, generator = getter() node_run_result: NodeRunResult | None = None for event in generator: @@ -245,9 +298,7 @@ def run_draft_workflow_node( error = e.error workflow_node_execution = WorkflowNodeExecution() - workflow_node_execution.tenant_id = app_model.tenant_id - workflow_node_execution.app_id = app_model.id - workflow_node_execution.workflow_id = draft_workflow.id + workflow_node_execution.tenant_id = tenant_id workflow_node_execution.triggered_from = WorkflowNodeExecutionTriggeredFrom.SINGLE_STEP.value workflow_node_execution.index = 1 workflow_node_execution.node_id = node_id @@ -255,7 +306,6 @@ def run_draft_workflow_node( workflow_node_execution.title = node_instance.node_data.title workflow_node_execution.elapsed_time = time.perf_counter() - start_at workflow_node_execution.created_by_role = CreatedByRole.ACCOUNT.value - workflow_node_execution.created_by = account.id workflow_node_execution.created_at = datetime.now(timezone.utc).replace(tzinfo=None) workflow_node_execution.finished_at = datetime.now(timezone.utc).replace(tzinfo=None) @@ -277,9 +327,6 @@ def run_draft_workflow_node( workflow_node_execution.status = WorkflowNodeExecutionStatus.FAILED.value workflow_node_execution.error = error - db.session.add(workflow_node_execution) - db.session.commit() - return workflow_node_execution def convert_to_workflow(self, app_model: App, account: Account, args: dict) -> App: @@ -302,10 +349,10 @@ def convert_to_workflow(self, app_model: App, account: Account, args: dict) -> A new_app = workflow_converter.convert_to_workflow( app_model=app_model, account=account, - name=args.get("name"), - icon_type=args.get("icon_type"), - icon=args.get("icon"), - icon_background=args.get("icon_background"), + name=args.get("name", ""), + icon_type=args.get("icon_type", ""), + icon=args.get("icon", ""), + icon_background=args.get("icon_background", ""), ) return new_app From a91951b3742c02c6017e1afaac8afa3fc472a4f9 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Tue, 24 Sep 2024 20:15:13 +0800 Subject: [PATCH 049/325] feat: invoke node --- api/core/plugin/backwards_invocation/node.py | 23 +++++++++++--------- api/core/plugin/entities/request.py | 10 +++++---- api/core/workflow/workflow_entry.py | 21 +++++++++++++++++- api/services/workflow_service.py | 4 ++++ 4 files changed, 43 insertions(+), 15 deletions(-) diff --git a/api/core/plugin/backwards_invocation/node.py b/api/core/plugin/backwards_invocation/node.py index 9a7fd5fc3a3491..4c1d21437e609f 100644 --- a/api/core/plugin/backwards_invocation/node.py +++ b/api/core/plugin/backwards_invocation/node.py @@ -1,4 +1,5 @@ from core.plugin.backwards_invocation.base import BaseBackwardsInvocation +from core.workflow.entities.node_entities import NodeType from core.workflow.nodes.parameter_extractor.entities import ( ModelConfig as ParameterExtractorModelConfig, ) @@ -36,7 +37,7 @@ def invoke_parameter_extractor( :param model_config: ModelConfig :param instruction: str :param query: str - :return: dict with __reason, __is_success, and other parameters + :return: dict """ workflow_service = WorkflowService() node_id = "1919810" @@ -50,6 +51,7 @@ def invoke_parameter_extractor( instruction=instruction, # instruct with variables are not supported ) node_data_dict = node_data.model_dump() + node_data_dict["type"] = NodeType.PARAMETER_EXTRACTOR.value execution = workflow_service.run_free_workflow_node( node_data_dict, tenant_id=tenant_id, @@ -60,10 +62,10 @@ def invoke_parameter_extractor( }, ) - output = execution.outputs_dict - return output or { - "__reason": "No parameters extracted", - "__is_success": False, + return { + "inputs": execution.inputs_dict, + "outputs": execution.outputs_dict, + "process_data": execution.process_data_dict, } @classmethod @@ -85,7 +87,7 @@ def invoke_question_classifier( :param classes: list[ClassConfig] :param instruction: str :param query: str - :return: dict with class_name + :return: dict """ workflow_service = WorkflowService() node_id = "1919810" @@ -108,7 +110,8 @@ def invoke_question_classifier( }, ) - output = execution.outputs_dict - return output or { - "class_name": classes[0].name, - } + return { + "inputs": execution.inputs_dict, + "outputs": execution.outputs_dict, + "process_data": execution.process_data_dict, + } \ No newline at end of file diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index bf4c4448c77243..00ac53ca72e64c 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -14,16 +14,18 @@ UserPromptMessage, ) from core.model_runtime.entities.model_entities import ModelType -from core.workflow.nodes.question_classifier.entities import ( - ClassConfig, - ModelConfig as QuestionClassifierModelConfig, -) from core.workflow.nodes.parameter_extractor.entities import ( ModelConfig as ParameterExtractorModelConfig, ) from core.workflow.nodes.parameter_extractor.entities import ( ParameterConfig, ) +from core.workflow.nodes.question_classifier.entities import ( + ClassConfig, +) +from core.workflow.nodes.question_classifier.entities import ( + ModelConfig as QuestionClassifierModelConfig, +) class RequestInvokeTool(BaseModel): diff --git a/api/core/workflow/workflow_entry.py b/api/core/workflow/workflow_entry.py index 9477e98c926881..0420d62ef79b80 100644 --- a/api/core/workflow/workflow_entry.py +++ b/api/core/workflow/workflow_entry.py @@ -221,8 +221,27 @@ def run_free_node( """ # generate a fake graph node_config = {"id": node_id, "width": 114, "height": 514, "type": "custom", "data": node_data} + start_node_config = { + "id": "start", + "width": 114, + "height": 514, + "type": "custom", + "data": { + "type": NodeType.START.value, + "title": "Start", + "desc": "Start", + }, + } graph_dict = { - "nodes": [node_config], + "nodes": [start_node_config, node_config], + "edges": [ + { + "source": "start", + "target": node_id, + "sourceHandle": "source", + "targetHandle": "target", + } + ], } node_type = NodeType.value_of(node_data.get("type", "")) diff --git a/api/services/workflow_service.py b/api/services/workflow_service.py index 399451cb8e446c..a1e2f3105738b8 100644 --- a/api/services/workflow_service.py +++ b/api/services/workflow_service.py @@ -230,6 +230,10 @@ def run_draft_workflow_node( node_id=node_id, ) + workflow_node_execution.app_id = app_model.id + workflow_node_execution.created_by = account.id + workflow_node_execution.workflow_id = draft_workflow.id + db.session.add(workflow_node_execution) db.session.commit() From 153dc5b3f39546a8f383dabe0b2d467b3c803b86 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 10:26:45 +0800 Subject: [PATCH 050/325] feat: endpoint apis --- api/controllers/console/__init__.py | 1 + api/controllers/console/workspace/endpoint.py | 62 ++++++++ .../console/workspace/tool_providers.py | 144 ++++++++++++------ api/services/plugin/endpoint_service.py | 2 + 4 files changed, 161 insertions(+), 48 deletions(-) create mode 100644 api/controllers/console/workspace/endpoint.py create mode 100644 api/services/plugin/endpoint_service.py diff --git a/api/controllers/console/__init__.py b/api/controllers/console/__init__.py index 1cf987050a7866..d17d5bc827b58c 100644 --- a/api/controllers/console/__init__.py +++ b/api/controllers/console/__init__.py @@ -58,6 +58,7 @@ # Import workspace controllers from .workspace import ( account, + endpoint, load_balancing_config, members, model_providers, diff --git a/api/controllers/console/workspace/endpoint.py b/api/controllers/console/workspace/endpoint.py new file mode 100644 index 00000000000000..668e4ea9534cd1 --- /dev/null +++ b/api/controllers/console/workspace/endpoint.py @@ -0,0 +1,62 @@ +from flask_restful import Resource + +from controllers.console import api +from controllers.console.setup import setup_required +from controllers.console.wraps import account_initialization_required +from libs.login import login_required + + +class EndpointCreateApi(Resource): + @setup_required + @login_required + @account_initialization_required + def post(self): + pass + + +class EndpointListApi(Resource): + @setup_required + @login_required + @account_initialization_required + def get(self): + pass + + +class EndpointDeleteApi(Resource): + @setup_required + @login_required + @account_initialization_required + def post(self): + pass + + +class EndpointUpdateApi(Resource): + @setup_required + @login_required + @account_initialization_required + def post(self): + pass + + +class EndpointEnableApi(Resource): + @setup_required + @login_required + @account_initialization_required + def post(self): + pass + + +class EndpointDisableApi(Resource): + @setup_required + @login_required + @account_initialization_required + def post(self): + pass + + +api.add_resource(EndpointCreateApi, "/workspaces/current/endpoints/create") +api.add_resource(EndpointListApi, "/workspaces/current/endpoints/list") +api.add_resource(EndpointDeleteApi, "/workspaces/current/endpoints/delete") +api.add_resource(EndpointUpdateApi, "/workspaces/current/endpoints/update") +api.add_resource(EndpointEnableApi, "/workspaces/current/endpoints/enable") +api.add_resource(EndpointDisableApi, "/workspaces/current/endpoints/disable") \ No newline at end of file diff --git a/api/controllers/console/workspace/tool_providers.py b/api/controllers/console/workspace/tool_providers.py index 68ad383a744d70..1b49103ced63ed 100644 --- a/api/controllers/console/workspace/tool_providers.py +++ b/api/controllers/console/workspace/tool_providers.py @@ -24,8 +24,10 @@ class ToolProviderListApi(Resource): @login_required @account_initialization_required def get(self): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id req = reqparse.RequestParser() req.add_argument( @@ -46,8 +48,10 @@ class ToolBuiltinProviderListToolsApi(Resource): @login_required @account_initialization_required def get(self, provider): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id return jsonable_encoder( BuiltinToolManageService.list_builtin_tool_provider_tools( @@ -63,11 +67,13 @@ class ToolBuiltinProviderDeleteApi(Resource): @login_required @account_initialization_required def post(self, provider): - if not current_user.is_admin_or_owner: + user = current_user + + if not user.is_admin_or_owner: raise Forbidden() - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user_id = user.id + tenant_id = user.current_tenant_id return BuiltinToolManageService.delete_builtin_tool_provider( user_id, @@ -81,11 +87,13 @@ class ToolBuiltinProviderUpdateApi(Resource): @login_required @account_initialization_required def post(self, provider): - if not current_user.is_admin_or_owner: + user = current_user + + if not user.is_admin_or_owner: raise Forbidden() - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user_id = user.id + tenant_id = user.current_tenant_id parser = reqparse.RequestParser() parser.add_argument("credentials", type=dict, required=True, nullable=False, location="json") @@ -105,8 +113,10 @@ class ToolBuiltinProviderGetCredentialsApi(Resource): @login_required @account_initialization_required def get(self, provider): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id return BuiltinToolManageService.get_builtin_tool_provider_credentials( user_id, @@ -118,7 +128,10 @@ def get(self, provider): class ToolBuiltinProviderIconApi(Resource): @setup_required def get(self, provider): - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id icon_bytes, mimetype = BuiltinToolManageService.get_builtin_tool_provider_icon(provider, tenant_id) icon_cache_max_age = dify_config.TOOL_ICON_CACHE_MAX_AGE @@ -130,11 +143,13 @@ class ToolApiProviderAddApi(Resource): @login_required @account_initialization_required def post(self): - if not current_user.is_admin_or_owner: + user = current_user + + if not user.is_admin_or_owner: raise Forbidden() - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user_id = user.id + tenant_id = user.current_tenant_id parser = reqparse.RequestParser() parser.add_argument("credentials", type=dict, required=True, nullable=False, location="json") @@ -167,6 +182,11 @@ class ToolApiProviderGetRemoteSchemaApi(Resource): @login_required @account_initialization_required def get(self): + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id + parser = reqparse.RequestParser() parser.add_argument("url", type=str, required=True, nullable=False, location="args") @@ -174,8 +194,8 @@ def get(self): args = parser.parse_args() return ApiToolManageService.get_api_tool_provider_remote_schema( - current_user.id, - current_user.current_tenant_id, + user_id, + tenant_id, args["url"], ) @@ -185,8 +205,10 @@ class ToolApiProviderListToolsApi(Resource): @login_required @account_initialization_required def get(self): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id parser = reqparse.RequestParser() @@ -208,11 +230,13 @@ class ToolApiProviderUpdateApi(Resource): @login_required @account_initialization_required def post(self): - if not current_user.is_admin_or_owner: + user = current_user + + if not user.is_admin_or_owner: raise Forbidden() - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user_id = user.id + tenant_id = user.current_tenant_id parser = reqparse.RequestParser() parser.add_argument("credentials", type=dict, required=True, nullable=False, location="json") @@ -247,11 +271,13 @@ class ToolApiProviderDeleteApi(Resource): @login_required @account_initialization_required def post(self): - if not current_user.is_admin_or_owner: + user = current_user + + if not user.is_admin_or_owner: raise Forbidden() - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user_id = user.id + tenant_id = user.current_tenant_id parser = reqparse.RequestParser() @@ -271,8 +297,10 @@ class ToolApiProviderGetApi(Resource): @login_required @account_initialization_required def get(self): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id parser = reqparse.RequestParser() @@ -292,7 +320,11 @@ class ToolBuiltinProviderCredentialsSchemaApi(Resource): @login_required @account_initialization_required def get(self, provider): - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id + return BuiltinToolManageService.list_builtin_provider_credentials_schema(provider, tenant_id) @@ -344,11 +376,13 @@ class ToolWorkflowProviderCreateApi(Resource): @login_required @account_initialization_required def post(self): - if not current_user.is_admin_or_owner: + user = current_user + + if not user.is_admin_or_owner: raise Forbidden() - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user_id = user.id + tenant_id = user.current_tenant_id reqparser = reqparse.RequestParser() reqparser.add_argument("workflow_app_id", type=uuid_value, required=True, nullable=False, location="json") @@ -381,11 +415,13 @@ class ToolWorkflowProviderUpdateApi(Resource): @login_required @account_initialization_required def post(self): - if not current_user.is_admin_or_owner: + user = current_user + + if not user.is_admin_or_owner: raise Forbidden() - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user_id = user.id + tenant_id = user.current_tenant_id reqparser = reqparse.RequestParser() reqparser.add_argument("workflow_tool_id", type=uuid_value, required=True, nullable=False, location="json") @@ -421,11 +457,13 @@ class ToolWorkflowProviderDeleteApi(Resource): @login_required @account_initialization_required def post(self): - if not current_user.is_admin_or_owner: + user = current_user + + if not user.is_admin_or_owner: raise Forbidden() - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user_id = user.id + tenant_id = user.current_tenant_id reqparser = reqparse.RequestParser() reqparser.add_argument("workflow_tool_id", type=uuid_value, required=True, nullable=False, location="json") @@ -444,8 +482,10 @@ class ToolWorkflowProviderGetApi(Resource): @login_required @account_initialization_required def get(self): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id parser = reqparse.RequestParser() parser.add_argument("workflow_tool_id", type=uuid_value, required=False, nullable=True, location="args") @@ -476,8 +516,10 @@ class ToolWorkflowProviderListToolApi(Resource): @login_required @account_initialization_required def get(self): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id parser = reqparse.RequestParser() parser.add_argument("workflow_tool_id", type=uuid_value, required=True, nullable=False, location="args") @@ -498,8 +540,10 @@ class ToolBuiltinListApi(Resource): @login_required @account_initialization_required def get(self): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id return jsonable_encoder( [ @@ -517,8 +561,10 @@ class ToolApiListApi(Resource): @login_required @account_initialization_required def get(self): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id return jsonable_encoder( [ @@ -536,8 +582,10 @@ class ToolWorkflowListApi(Resource): @login_required @account_initialization_required def get(self): - user_id = current_user.id - tenant_id = current_user.current_tenant_id + user = current_user + + user_id = user.id + tenant_id = user.current_tenant_id return jsonable_encoder( [ diff --git a/api/services/plugin/endpoint_service.py b/api/services/plugin/endpoint_service.py new file mode 100644 index 00000000000000..e9b395efcc84b7 --- /dev/null +++ b/api/services/plugin/endpoint_service.py @@ -0,0 +1,2 @@ +class EndpointService: + pass \ No newline at end of file From ea497f828f0df394a91c98bbbd761944c2340d30 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 12:49:00 +0800 Subject: [PATCH 051/325] feat: endpoint management --- api/controllers/console/workspace/endpoint.py | 86 +++++++++++++-- api/core/plugin/entities/base.py | 9 ++ api/core/plugin/entities/endpoint.py | 11 ++ api/core/plugin/entities/plugin.py | 10 ++ api/core/plugin/manager/endpoint.py | 101 +++++++++++++++++- api/core/plugin/manager/plugin.py | 9 ++ api/services/plugin/endpoint_service.py | 52 ++++++++- 7 files changed, 268 insertions(+), 10 deletions(-) create mode 100644 api/core/plugin/entities/base.py create mode 100644 api/core/plugin/entities/endpoint.py create mode 100644 api/core/plugin/entities/plugin.py diff --git a/api/controllers/console/workspace/endpoint.py b/api/controllers/console/workspace/endpoint.py index 668e4ea9534cd1..44e35f32bd2b91 100644 --- a/api/controllers/console/workspace/endpoint.py +++ b/api/controllers/console/workspace/endpoint.py @@ -1,9 +1,12 @@ -from flask_restful import Resource +from flask_login import current_user +from flask_restful import Resource, reqparse +from werkzeug.exceptions import Forbidden from controllers.console import api from controllers.console.setup import setup_required from controllers.console.wraps import account_initialization_required from libs.login import login_required +from services.plugin.endpoint_service import EndpointService class EndpointCreateApi(Resource): @@ -11,7 +14,24 @@ class EndpointCreateApi(Resource): @login_required @account_initialization_required def post(self): - pass + user = current_user + if not user.is_admin_or_owner: + raise Forbidden() + + parser = reqparse.RequestParser() + parser.add_argument("plugin_unique_identifier", type=str, required=True) + parser.add_argument("settings", type=dict, required=True) + args = parser.parse_args() + + plugin_unique_identifier = args["plugin_unique_identifier"] + settings = args["settings"] + + return EndpointService.create_endpoint( + tenant_id=user.current_tenant_id, + user_id=user.id, + plugin_unique_identifier=plugin_unique_identifier, + settings=settings, + ) class EndpointListApi(Resource): @@ -19,7 +39,12 @@ class EndpointListApi(Resource): @login_required @account_initialization_required def get(self): - pass + user = current_user + + return EndpointService.list_endpoints( + tenant_id=user.current_tenant_id, + user_id=user.id, + ) class EndpointDeleteApi(Resource): @@ -27,7 +52,17 @@ class EndpointDeleteApi(Resource): @login_required @account_initialization_required def post(self): - pass + user = current_user + + parser = reqparse.RequestParser() + parser.add_argument("endpoint_id", type=str, required=True) + args = parser.parse_args() + + endpoint_id = args["endpoint_id"] + + return EndpointService.delete_endpoint( + tenant_id=user.current_tenant_id, user_id=user.id, endpoint_id=endpoint_id + ) class EndpointUpdateApi(Resource): @@ -35,7 +70,22 @@ class EndpointUpdateApi(Resource): @login_required @account_initialization_required def post(self): - pass + user = current_user + + parser = reqparse.RequestParser() + parser.add_argument("endpoint_id", type=str, required=True) + parser.add_argument("settings", type=dict, required=True) + args = parser.parse_args() + + endpoint_id = args["endpoint_id"] + settings = args["settings"] + + return EndpointService.update_endpoint( + tenant_id=user.current_tenant_id, + user_id=user.id, + endpoint_id=endpoint_id, + settings=settings, + ) class EndpointEnableApi(Resource): @@ -43,7 +93,17 @@ class EndpointEnableApi(Resource): @login_required @account_initialization_required def post(self): - pass + user = current_user + + parser = reqparse.RequestParser() + parser.add_argument("endpoint_id", type=str, required=True) + args = parser.parse_args() + + endpoint_id = args["endpoint_id"] + + return EndpointService.enable_endpoint( + tenant_id=user.current_tenant_id, user_id=user.id, endpoint_id=endpoint_id + ) class EndpointDisableApi(Resource): @@ -51,7 +111,17 @@ class EndpointDisableApi(Resource): @login_required @account_initialization_required def post(self): - pass + user = current_user + + parser = reqparse.RequestParser() + parser.add_argument("endpoint_id", type=str, required=True) + args = parser.parse_args() + + endpoint_id = args["endpoint_id"] + + return EndpointService.disable_endpoint( + tenant_id=user.current_tenant_id, user_id=user.id, endpoint_id=endpoint_id + ) api.add_resource(EndpointCreateApi, "/workspaces/current/endpoints/create") @@ -59,4 +129,4 @@ def post(self): api.add_resource(EndpointDeleteApi, "/workspaces/current/endpoints/delete") api.add_resource(EndpointUpdateApi, "/workspaces/current/endpoints/update") api.add_resource(EndpointEnableApi, "/workspaces/current/endpoints/enable") -api.add_resource(EndpointDisableApi, "/workspaces/current/endpoints/disable") \ No newline at end of file +api.add_resource(EndpointDisableApi, "/workspaces/current/endpoints/disable") diff --git a/api/core/plugin/entities/base.py b/api/core/plugin/entities/base.py new file mode 100644 index 00000000000000..bfec0d43025b93 --- /dev/null +++ b/api/core/plugin/entities/base.py @@ -0,0 +1,9 @@ +from datetime import datetime + +from pydantic import BaseModel + + +class BasePluginEntity(BaseModel): + id: str + created_at: datetime + updated_at: datetime diff --git a/api/core/plugin/entities/endpoint.py b/api/core/plugin/entities/endpoint.py new file mode 100644 index 00000000000000..54d718fd5b2316 --- /dev/null +++ b/api/core/plugin/entities/endpoint.py @@ -0,0 +1,11 @@ +from datetime import datetime + +from core.plugin.entities.base import BasePluginEntity + + +class EndpointEntity(BasePluginEntity): + settings: dict + hook_id: str + tenant_id: str + plugin_id: str + expired_at: datetime diff --git a/api/core/plugin/entities/plugin.py b/api/core/plugin/entities/plugin.py new file mode 100644 index 00000000000000..8098ade025b763 --- /dev/null +++ b/api/core/plugin/entities/plugin.py @@ -0,0 +1,10 @@ +from core.plugin.entities.base import BasePluginEntity + + +class PluginEntity(BasePluginEntity): + name: str + plugin_id: str + plugin_unique_identifier: str + tenant_id: str + endpoints_setups: int + endpoints_active: int diff --git a/api/core/plugin/manager/endpoint.py b/api/core/plugin/manager/endpoint.py index a3f49903fd8595..1c48f8200fe761 100644 --- a/api/core/plugin/manager/endpoint.py +++ b/api/core/plugin/manager/endpoint.py @@ -1,5 +1,104 @@ +from core.plugin.entities.endpoint import EndpointEntity from core.plugin.manager.base import BasePluginManager class PluginEndpointManager(BasePluginManager): - pass \ No newline at end of file + def create_endpoint(self, tenant_id: str, user_id: str, plugin_unique_identifier: str, settings: dict): + """ + Create an endpoint for the given plugin. + + Errors will be raised if any error occurs. + """ + self._request_with_plugin_daemon_response( + "POST", + f"plugin/{tenant_id}/endpoint/setup", + dict, + headers={ + "Content-Type": "application/json", + }, + data={ + "user_id": user_id, + "plugin_unique_identifier": plugin_unique_identifier, + "settings": settings, + }, + ) + + def list_endpoints(self, tenant_id: str, user_id: str): + """ + List all endpoints for the given tenant and user. + """ + return self._request_with_plugin_daemon_response( + "GET", + f"plugin/{tenant_id}/endpoint/list", + list[EndpointEntity], + params={"page": 1, "page_size": 256}, + ) + + def list_plugin_endpoints(self, tenant_id: str, user_id: str, plugin_unique_identifier: str): + """ + List all endpoints for the given tenant, user and plugin. + """ + return self._request_with_plugin_daemon_response( + "GET", + f"plugin/{tenant_id}/endpoint/list/plugin", + list[EndpointEntity], + headers={ + "Content-Type": "application/json", + }, + data={ + "plugin_unique_identifier": plugin_unique_identifier, + }, + ) + + def update_endpoint(self, tenant_id: str, user_id: str, endpoint_id: str, settings: dict): + """ + Update the settings of the given endpoint. + """ + self._request_with_plugin_daemon_response( + "POST", + f"plugin/{tenant_id}/endpoint/update", + dict, + data={ + "endpoint_id": endpoint_id, + "settings": settings, + }, + ) + + def delete_endpoint(self, tenant_id: str, user_id: str, endpoint_id: str): + """ + Delete the given endpoint. + """ + self._request_with_plugin_daemon_response( + "DELETE", + f"plugin/{tenant_id}/endpoint/remove", + dict, + data={ + "endpoint_id": endpoint_id, + }, + ) + + def enable_endpoint(self, tenant_id: str, user_id: str, endpoint_id: str): + """ + Enable the given endpoint. + """ + self._request_with_plugin_daemon_response( + "POST", + f"plugin/{tenant_id}/endpoint/enable", + dict, + data={ + "endpoint_id": endpoint_id, + }, + ) + + def disable_endpoint(self, tenant_id: str, user_id: str, endpoint_id: str): + """ + Disable the given endpoint. + """ + self._request_with_plugin_daemon_response( + "POST", + f"plugin/{tenant_id}/endpoint/disable", + dict, + data={ + "endpoint_id": endpoint_id, + }, + ) diff --git a/api/core/plugin/manager/plugin.py b/api/core/plugin/manager/plugin.py index cabe028ff34058..5a9eb336c5adac 100644 --- a/api/core/plugin/manager/plugin.py +++ b/api/core/plugin/manager/plugin.py @@ -1,5 +1,6 @@ from collections.abc import Generator +from core.plugin.entities.plugin import PluginEntity from core.plugin.entities.plugin_daemon import InstallPluginMessage from core.plugin.manager.base import BasePluginManager @@ -12,6 +13,14 @@ def fetch_plugin_by_identifier(self, tenant_id: str, identifier: str) -> bool: "GET", f"plugin/{tenant_id}/fetch/identifier", bool, params={"plugin_unique_identifier": identifier} ) + def list_plugins(self, tenant_id: str) -> list[PluginEntity]: + return self._request_with_plugin_daemon_response( + "GET", + f"plugin/{tenant_id}/management/list", + list[PluginEntity], + params={"page": 1, "page_size": 256}, + ) + def install_from_pkg(self, tenant_id: str, pkg: bytes) -> Generator[InstallPluginMessage, None, None]: """ Install a plugin from a package. diff --git a/api/services/plugin/endpoint_service.py b/api/services/plugin/endpoint_service.py index e9b395efcc84b7..4b3258ef6e5d52 100644 --- a/api/services/plugin/endpoint_service.py +++ b/api/services/plugin/endpoint_service.py @@ -1,2 +1,52 @@ +from core.plugin.manager.endpoint import PluginEndpointManager + + class EndpointService: - pass \ No newline at end of file + @classmethod + def create_endpoint(cls, tenant_id: str, user_id: str, plugin_unique_identifier: str, settings: dict): + return PluginEndpointManager().create_endpoint( + tenant_id=tenant_id, + user_id=user_id, + plugin_unique_identifier=plugin_unique_identifier, + settings=settings, + ) + + @classmethod + def list_endpoints(cls, tenant_id: str, user_id: str): + return PluginEndpointManager().list_endpoints( + tenant_id=tenant_id, + user_id=user_id, + ) + + @classmethod + def update_endpoint(cls, tenant_id: str, user_id: str, endpoint_id: str, settings: dict): + return PluginEndpointManager().update_endpoint( + tenant_id=tenant_id, + user_id=user_id, + endpoint_id=endpoint_id, + settings=settings, + ) + + @classmethod + def delete_endpoint(cls, tenant_id: str, user_id: str, endpoint_id: str): + return PluginEndpointManager().delete_endpoint( + tenant_id=tenant_id, + user_id=user_id, + endpoint_id=endpoint_id, + ) + + @classmethod + def enable_endpoint(cls, tenant_id: str, user_id: str, endpoint_id: str): + return PluginEndpointManager().enable_endpoint( + tenant_id=tenant_id, + user_id=user_id, + endpoint_id=endpoint_id, + ) + + @classmethod + def disable_endpoint(cls, tenant_id: str, user_id: str, endpoint_id: str): + return PluginEndpointManager().disable_endpoint( + tenant_id=tenant_id, + user_id=user_id, + endpoint_id=endpoint_id, + ) From 1d575524c3862447eed628ffcc49c666b84254fe Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 14:20:05 +0800 Subject: [PATCH 052/325] fix: missing user id --- api/core/plugin/manager/endpoint.py | 1 + 1 file changed, 1 insertion(+) diff --git a/api/core/plugin/manager/endpoint.py b/api/core/plugin/manager/endpoint.py index 1c48f8200fe761..c4718b72ddd782 100644 --- a/api/core/plugin/manager/endpoint.py +++ b/api/core/plugin/manager/endpoint.py @@ -59,6 +59,7 @@ def update_endpoint(self, tenant_id: str, user_id: str, endpoint_id: str, settin f"plugin/{tenant_id}/endpoint/update", dict, data={ + "user_id": user_id, "endpoint_id": endpoint_id, "settings": settings, }, From 4c28034224dee2b60c39a5634c2252fe2fcf5a92 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 14:51:10 +0800 Subject: [PATCH 053/325] refactor: encryption --- api/core/plugin/encrypt/__init__.py | 17 +++++++++++++---- api/core/plugin/entities/endpoint.py | 17 +++++++++++++++++ 2 files changed, 30 insertions(+), 4 deletions(-) diff --git a/api/core/plugin/encrypt/__init__.py b/api/core/plugin/encrypt/__init__.py index 614ce81d20c196..313d161ec93d25 100644 --- a/api/core/plugin/encrypt/__init__.py +++ b/api/core/plugin/encrypt/__init__.py @@ -16,7 +16,16 @@ def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> Mappin provider_identity=payload.identity, ) - if payload.opt == "encrypt": - return encrypter.encrypt(payload.data) - else: - return encrypter.decrypt(payload.data) \ No newline at end of file + try: + if payload.opt == "encrypt": + return { + "data": encrypter.encrypt(payload.data), + } + else: + return { + "data": encrypter.decrypt(payload.data), + } + except Exception as e: + return { + "error": str(e), + } diff --git a/api/core/plugin/entities/endpoint.py b/api/core/plugin/entities/endpoint.py index 54d718fd5b2316..2faa0e8f5806bb 100644 --- a/api/core/plugin/entities/endpoint.py +++ b/api/core/plugin/entities/endpoint.py @@ -1,11 +1,28 @@ +from collections.abc import Mapping from datetime import datetime +from pydantic import BaseModel, Field + +from core.entities.provider_entities import ProviderConfig from core.plugin.entities.base import BasePluginEntity +class EndpointDeclaration(BaseModel): + """ + declaration of an endpoint + """ + + settings: Mapping[str, ProviderConfig] = Field(default_factory=Mapping) + + class EndpointEntity(BasePluginEntity): + """ + entity of an endpoint + """ + settings: dict hook_id: str tenant_id: str plugin_id: str expired_at: datetime + declaration: EndpointDeclaration = Field(default_factory=EndpointDeclaration) From 0ad9dbea63ac532e9194ee403c51a20218e7c6da Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 15:38:22 +0800 Subject: [PATCH 054/325] feat: backwards invoke model --- api/controllers/inner_api/plugin/plugin.py | 6 +- api/core/model_manager.py | 4 +- api/core/plugin/backwards_invocation/model.py | 131 +++++++++++++++++- api/core/plugin/entities/request.py | 38 ++++- 4 files changed, 169 insertions(+), 10 deletions(-) diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index ae3533268927a2..7dde4f01483394 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -47,7 +47,11 @@ class PluginInvokeTextEmbeddingApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeTextEmbedding) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeTextEmbedding): - pass + return PluginModelBackwardsInvocation.invoke_text_embedding( + user_id=user_id, + tenant=tenant_model, + payload=payload, + ) class PluginInvokeRerankApi(Resource): diff --git a/api/core/model_manager.py b/api/core/model_manager.py index 482ca2d4b9702e..1a4a03e27751bc 100644 --- a/api/core/model_manager.py +++ b/api/core/model_manager.py @@ -310,7 +310,9 @@ def invoke_speech2text(self, file: IO[bytes], user: Optional[str] = None) -> str user=user, ) - def invoke_tts(self, content_text: str, tenant_id: str, voice: str, user: Optional[str] = None) -> str: + def invoke_tts( + self, content_text: str, tenant_id: str, voice: str, user: Optional[str] = None + ) -> Generator[bytes, None, None]: """ Invoke large language tts model diff --git a/api/core/plugin/backwards_invocation/model.py b/api/core/plugin/backwards_invocation/model.py index 7904fd62340ccf..b3ecced55c0294 100644 --- a/api/core/plugin/backwards_invocation/model.py +++ b/api/core/plugin/backwards_invocation/model.py @@ -1,9 +1,18 @@ +import tempfile +from binascii import hexlify, unhexlify from collections.abc import Generator from core.model_manager import ModelManager from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk from core.plugin.backwards_invocation.base import BaseBackwardsInvocation -from core.plugin.entities.request import RequestInvokeLLM +from core.plugin.entities.request import ( + RequestInvokeLLM, + RequestInvokeModeration, + RequestInvokeRerank, + RequestInvokeSpeech2Text, + RequestInvokeTextEmbedding, + RequestInvokeTTS, +) from core.workflow.nodes.llm.llm_node import LLMNode from models.account import Tenant @@ -48,5 +57,121 @@ def handle() -> Generator[LLMResultChunk, None, None]: if response.usage: LLMNode.deduct_llm_quota(tenant_id=tenant.id, model_instance=model_instance, usage=response.usage) return response - - \ No newline at end of file + + @classmethod + def invoke_text_embedding(cls, user_id: str, tenant: Tenant, payload: RequestInvokeTextEmbedding): + """ + invoke text embedding + """ + model_instance = ModelManager().get_model_instance( + tenant_id=tenant.id, + provider=payload.provider, + model_type=payload.model_type, + model=payload.model, + ) + + # invoke model + response = model_instance.invoke_text_embedding( + texts=payload.texts, + user=user_id, + ) + + return response + + @classmethod + def invoke_rerank(cls, user_id: str, tenant: Tenant, payload: RequestInvokeRerank): + """ + invoke rerank + """ + model_instance = ModelManager().get_model_instance( + tenant_id=tenant.id, + provider=payload.provider, + model_type=payload.model_type, + model=payload.model, + ) + + # invoke model + response = model_instance.invoke_rerank( + query=payload.query, + docs=payload.docs, + score_threshold=payload.score_threshold, + top_n=payload.top_n, + user=user_id, + ) + + return response + + @classmethod + def invoke_tts(cls, user_id: str, tenant: Tenant, payload: RequestInvokeTTS): + """ + invoke tts + """ + model_instance = ModelManager().get_model_instance( + tenant_id=tenant.id, + provider=payload.provider, + model_type=payload.model_type, + model=payload.model, + ) + + # invoke model + response = model_instance.invoke_tts( + content_text=payload.content_text, + tenant_id=tenant.id, + voice=payload.voice, + user=user_id, + ) + + def handle() -> Generator[dict, None, None]: + for chunk in response: + yield {"result": hexlify(chunk).decode("utf-8")} + + return handle() + + @classmethod + def invoke_speech2text(cls, user_id: str, tenant: Tenant, payload: RequestInvokeSpeech2Text): + """ + invoke speech2text + """ + model_instance = ModelManager().get_model_instance( + tenant_id=tenant.id, + provider=payload.provider, + model_type=payload.model_type, + model=payload.model, + ) + + # invoke model + with tempfile.NamedTemporaryFile(suffix=".mp3", mode="wb", delete=True) as temp: + temp.write(unhexlify(payload.file)) + temp.flush() + temp.seek(0) + + response = model_instance.invoke_speech2text( + file=temp, + user=user_id, + ) + + return { + "result": response, + } + + @classmethod + def invoke_moderation(cls, user_id: str, tenant: Tenant, payload: RequestInvokeModeration): + """ + invoke moderation + """ + model_instance = ModelManager().get_model_instance( + tenant_id=tenant.id, + provider=payload.provider, + model_type=payload.model_type, + model=payload.model, + ) + + # invoke model + response = model_instance.invoke_moderation( + text=payload.text, + user=user_id, + ) + + return { + "result": response, + } diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 00ac53ca72e64c..a27f8751a64485 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -74,35 +74,63 @@ def convert_prompt_messages(cls, v): return v -class RequestInvokeTextEmbedding(BaseModel): +class RequestInvokeTextEmbedding(BaseRequestInvokeModel): """ Request to invoke text embedding """ + model_type: ModelType = ModelType.TEXT_EMBEDDING + texts: list[str] -class RequestInvokeRerank(BaseModel): + +class RequestInvokeRerank(BaseRequestInvokeModel): """ Request to invoke rerank """ + model_type: ModelType = ModelType.RERANK + query: str + docs: list[str] + score_threshold: float + top_n: int + -class RequestInvokeTTS(BaseModel): +class RequestInvokeTTS(BaseRequestInvokeModel): """ Request to invoke TTS """ + model_type: ModelType = ModelType.TTS + content_text: str + voice: str + -class RequestInvokeSpeech2Text(BaseModel): +class RequestInvokeSpeech2Text(BaseRequestInvokeModel): """ Request to invoke speech2text """ + model_type: ModelType = ModelType.SPEECH2TEXT + file: bytes -class RequestInvokeModeration(BaseModel): + @field_validator("file", mode="before") + @classmethod + def convert_file(cls, v): + # hex string to bytes + if isinstance(v, str): + return bytes.fromhex(v) + else: + raise ValueError("file must be a hex string") + + +class RequestInvokeModeration(BaseRequestInvokeModel): """ Request to invoke moderation """ + model_type: ModelType = ModelType.MODERATION + text: str + class RequestInvokeParameterExtractorNode(BaseModel): """ From 507fff0259535988ce9c09405466466da8df2fbd Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 15:47:16 +0800 Subject: [PATCH 055/325] fix: tts file was deleted before invocation --- api/core/plugin/backwards_invocation/model.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/api/core/plugin/backwards_invocation/model.py b/api/core/plugin/backwards_invocation/model.py index b3ecced55c0294..405fcb069ddf8e 100644 --- a/api/core/plugin/backwards_invocation/model.py +++ b/api/core/plugin/backwards_invocation/model.py @@ -145,14 +145,14 @@ def invoke_speech2text(cls, user_id: str, tenant: Tenant, payload: RequestInvoke temp.flush() temp.seek(0) - response = model_instance.invoke_speech2text( - file=temp, - user=user_id, - ) - - return { - "result": response, - } + response = model_instance.invoke_speech2text( + file=temp, + user=user_id, + ) + + return { + "result": response, + } @classmethod def invoke_moderation(cls, user_id: str, tenant: Tenant, payload: RequestInvokeModeration): From 5dcd25a61308b8ffe28cf89581ae257fbc029c09 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 17:22:39 +0800 Subject: [PATCH 056/325] fix: missing error message --- api/controllers/inner_api/plugin/plugin.py | 108 ++++++++++++++----- api/core/plugin/backwards_invocation/base.py | 32 ++++-- api/core/plugin/encrypt/__init__.py | 19 +--- 3 files changed, 110 insertions(+), 49 deletions(-) diff --git a/api/controllers/inner_api/plugin/plugin.py b/api/controllers/inner_api/plugin/plugin.py index 7dde4f01483394..f785b2aed610a3 100644 --- a/api/controllers/inner_api/plugin/plugin.py +++ b/api/controllers/inner_api/plugin/plugin.py @@ -7,6 +7,7 @@ from controllers.inner_api.plugin.wraps import get_tenant, plugin_data from controllers.inner_api.wraps import plugin_inner_api_only from core.plugin.backwards_invocation.app import PluginAppBackwardsInvocation +from core.plugin.backwards_invocation.base import BaseBackwardsInvocationResponse from core.plugin.backwards_invocation.model import PluginModelBackwardsInvocation from core.plugin.backwards_invocation.node import PluginNodeBackwardsInvocation from core.plugin.encrypt import PluginEncrypter @@ -47,11 +48,16 @@ class PluginInvokeTextEmbeddingApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeTextEmbedding) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeTextEmbedding): - return PluginModelBackwardsInvocation.invoke_text_embedding( - user_id=user_id, - tenant=tenant_model, - payload=payload, - ) + try: + return BaseBackwardsInvocationResponse( + data=PluginModelBackwardsInvocation.invoke_text_embedding( + user_id=user_id, + tenant=tenant_model, + payload=payload, + ) + ).model_dump() + except Exception as e: + return BaseBackwardsInvocationResponse(error=str(e)).model_dump() class PluginInvokeRerankApi(Resource): @@ -60,7 +66,16 @@ class PluginInvokeRerankApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeRerank) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeRerank): - pass + try: + return BaseBackwardsInvocationResponse( + data=PluginModelBackwardsInvocation.invoke_rerank( + user_id=user_id, + tenant=tenant_model, + payload=payload, + ) + ).model_dump() + except Exception as e: + return BaseBackwardsInvocationResponse(error=str(e)).model_dump() class PluginInvokeTTSApi(Resource): @@ -69,7 +84,15 @@ class PluginInvokeTTSApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeTTS) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeTTS): - pass + def generator(): + response = PluginModelBackwardsInvocation.invoke_tts( + user_id=user_id, + tenant=tenant_model, + payload=payload, + ) + return PluginModelBackwardsInvocation.convert_to_event_stream(response) + + return compact_generate_response(generator()) class PluginInvokeSpeech2TextApi(Resource): @@ -78,7 +101,16 @@ class PluginInvokeSpeech2TextApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeSpeech2Text) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeSpeech2Text): - pass + try: + return BaseBackwardsInvocationResponse( + data=PluginModelBackwardsInvocation.invoke_speech2text( + user_id=user_id, + tenant=tenant_model, + payload=payload, + ) + ).model_dump() + except Exception as e: + return BaseBackwardsInvocationResponse(error=str(e)).model_dump() class PluginInvokeModerationApi(Resource): @@ -87,7 +119,16 @@ class PluginInvokeModerationApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeModeration) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeModeration): - pass + try: + return BaseBackwardsInvocationResponse( + data=PluginModelBackwardsInvocation.invoke_moderation( + user_id=user_id, + tenant=tenant_model, + payload=payload, + ) + ).model_dump() + except Exception as e: + return BaseBackwardsInvocationResponse(error=str(e)).model_dump() class PluginInvokeToolApi(Resource): @@ -118,14 +159,19 @@ class PluginInvokeParameterExtractorNodeApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeParameterExtractorNode) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeParameterExtractorNode): - return PluginNodeBackwardsInvocation.invoke_parameter_extractor( - tenant_id=tenant_model.id, - user_id=user_id, - parameters=payload.parameters, - model_config=payload.model, - instruction=payload.instruction, - query=payload.query, - ) + try: + return BaseBackwardsInvocationResponse( + data=PluginNodeBackwardsInvocation.invoke_parameter_extractor( + tenant_id=tenant_model.id, + user_id=user_id, + parameters=payload.parameters, + model_config=payload.model, + instruction=payload.instruction, + query=payload.query, + ) + ).model_dump() + except Exception as e: + return BaseBackwardsInvocationResponse(error=str(e)).model_dump() class PluginInvokeQuestionClassifierNodeApi(Resource): @@ -134,14 +180,19 @@ class PluginInvokeQuestionClassifierNodeApi(Resource): @get_tenant @plugin_data(payload_type=RequestInvokeQuestionClassifierNode) def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeQuestionClassifierNode): - return PluginNodeBackwardsInvocation.invoke_question_classifier( - tenant_id=tenant_model.id, - user_id=user_id, - query=payload.query, - model_config=payload.model, - classes=payload.classes, - instruction=payload.instruction, - ) + try: + return BaseBackwardsInvocationResponse( + data=PluginNodeBackwardsInvocation.invoke_question_classifier( + tenant_id=tenant_model.id, + user_id=user_id, + query=payload.query, + model_config=payload.model, + classes=payload.classes, + instruction=payload.instruction, + ) + ).model_dump() + except Exception as e: + return BaseBackwardsInvocationResponse(error=str(e)).model_dump() class PluginInvokeAppApi(Resource): @@ -173,7 +224,12 @@ def post(self, user_id: str, tenant_model: Tenant, payload: RequestInvokeEncrypt """ encrypt or decrypt data """ - return PluginEncrypter.invoke_encrypt(tenant_model, payload) + try: + return BaseBackwardsInvocationResponse( + data=PluginEncrypter.invoke_encrypt(tenant_model, payload) + ).model_dump() + except Exception as e: + return BaseBackwardsInvocationResponse(error=str(e)).model_dump() api.add_resource(PluginInvokeLLMApi, "/invoke/llm") diff --git a/api/core/plugin/backwards_invocation/base.py b/api/core/plugin/backwards_invocation/base.py index 7b699b4d6784f5..2ec71fdc5b4921 100644 --- a/api/core/plugin/backwards_invocation/base.py +++ b/api/core/plugin/backwards_invocation/base.py @@ -1,5 +1,6 @@ import json from collections.abc import Generator +from typing import Generic, Optional, TypeVar from pydantic import BaseModel @@ -8,15 +9,28 @@ class BaseBackwardsInvocation: @classmethod def convert_to_event_stream(cls, response: Generator[BaseModel | dict | str, None, None] | BaseModel | dict): if isinstance(response, Generator): - for chunk in response: - if isinstance(chunk, BaseModel): - yield chunk.model_dump_json().encode() + b'\n\n' - elif isinstance(chunk, str): - yield f"event: {chunk}\n\n".encode() - else: - yield json.dumps(chunk).encode() + b'\n\n' + try: + for chunk in response: + if isinstance(chunk, BaseModel): + yield BaseBackwardsInvocationResponse(data=chunk).model_dump_json().encode() + b"\n\n" + + elif isinstance(chunk, str): + yield f"event: {chunk}\n\n".encode() + else: + yield json.dumps(chunk).encode() + b"\n\n" + except Exception as e: + error_message = BaseBackwardsInvocationResponse(error=str(e)).model_dump_json() + yield f"{error_message}\n\n".encode() else: if isinstance(response, BaseModel): - yield response.model_dump_json().encode() + b'\n\n' + yield response.model_dump_json().encode() + b"\n\n" else: - yield json.dumps(response).encode() + b'\n\n' + yield json.dumps(response).encode() + b"\n\n" + + +T = TypeVar("T", bound=BaseModel | dict | str | bool | int) + + +class BaseBackwardsInvocationResponse(BaseModel, Generic[T]): + data: Optional[T] = None + error: str = "" diff --git a/api/core/plugin/encrypt/__init__.py b/api/core/plugin/encrypt/__init__.py index 313d161ec93d25..95c416d28c70e0 100644 --- a/api/core/plugin/encrypt/__init__.py +++ b/api/core/plugin/encrypt/__init__.py @@ -8,7 +8,7 @@ class PluginEncrypter: @classmethod - def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> Mapping[str, Any]: + def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> dict: encrypter = ProviderConfigEncrypter( tenant_id=tenant.id, config=payload.data, @@ -16,16 +16,7 @@ def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> Mappin provider_identity=payload.identity, ) - try: - if payload.opt == "encrypt": - return { - "data": encrypter.encrypt(payload.data), - } - else: - return { - "data": encrypter.decrypt(payload.data), - } - except Exception as e: - return { - "error": str(e), - } + if payload.opt == "encrypt": + return encrypter.encrypt(payload.data) + else: + return encrypter.decrypt(payload.data) From 1837692a66418eff52f184b980b8cb37e0b1a71e Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 17:40:27 +0800 Subject: [PATCH 057/325] fix: sse error message --- api/core/plugin/backwards_invocation/base.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/api/core/plugin/backwards_invocation/base.py b/api/core/plugin/backwards_invocation/base.py index 2ec71fdc5b4921..1ce126b893191b 100644 --- a/api/core/plugin/backwards_invocation/base.py +++ b/api/core/plugin/backwards_invocation/base.py @@ -11,13 +11,10 @@ def convert_to_event_stream(cls, response: Generator[BaseModel | dict | str, Non if isinstance(response, Generator): try: for chunk in response: - if isinstance(chunk, BaseModel): + if isinstance(chunk, BaseModel | dict): yield BaseBackwardsInvocationResponse(data=chunk).model_dump_json().encode() + b"\n\n" - elif isinstance(chunk, str): yield f"event: {chunk}\n\n".encode() - else: - yield json.dumps(chunk).encode() + b"\n\n" except Exception as e: error_message = BaseBackwardsInvocationResponse(error=str(e)).model_dump_json() yield f"{error_message}\n\n".encode() @@ -28,7 +25,7 @@ def convert_to_event_stream(cls, response: Generator[BaseModel | dict | str, Non yield json.dumps(response).encode() + b"\n\n" -T = TypeVar("T", bound=BaseModel | dict | str | bool | int) +T = TypeVar("T", bound=dict | str | bool | int | BaseModel) class BaseBackwardsInvocationResponse(BaseModel, Generic[T]): From 2da32e49d0de9ca418ec685838d9398baacb630e Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Thu, 26 Sep 2024 17:51:13 +0800 Subject: [PATCH 058/325] fix: tests --- api/core/plugin/encrypt/__init__.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/api/core/plugin/encrypt/__init__.py b/api/core/plugin/encrypt/__init__.py index 95c416d28c70e0..285e97b45fcf70 100644 --- a/api/core/plugin/encrypt/__init__.py +++ b/api/core/plugin/encrypt/__init__.py @@ -17,6 +17,10 @@ def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> dict: ) if payload.opt == "encrypt": - return encrypter.encrypt(payload.data) + return { + "data": encrypter.encrypt(payload.data), + } else: - return encrypter.decrypt(payload.data) + return { + "data": encrypter.decrypt(payload.data), + } From c3359a92915ddca90e94edd08d1ec45971452a04 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Fri, 27 Sep 2024 21:48:48 +0800 Subject: [PATCH 059/325] refactor: using plugin id to dispatch request instead --- api/core/plugin/encrypt/__init__.py | 8 +++++++- api/core/plugin/entities/request.py | 2 +- api/core/plugin/manager/tool.py | 16 +++++++--------- api/core/tools/plugin_tool/provider.py | 12 ++++++------ api/core/tools/plugin_tool/tool.py | 10 +++++----- api/core/tools/tool_manager.py | 12 ++++-------- api/services/app_service.py | 5 ++++- 7 files changed, 34 insertions(+), 31 deletions(-) diff --git a/api/core/plugin/encrypt/__init__.py b/api/core/plugin/encrypt/__init__.py index 285e97b45fcf70..6303e2ade10ec0 100644 --- a/api/core/plugin/encrypt/__init__.py +++ b/api/core/plugin/encrypt/__init__.py @@ -20,7 +20,13 @@ def invoke_encrypt(cls, tenant: Tenant, payload: RequestInvokeEncrypt) -> dict: return { "data": encrypter.encrypt(payload.data), } - else: + elif payload.opt == "decrypt": return { "data": encrypter.decrypt(payload.data), } + elif payload.opt == "clear": + return { + "data": encrypter.delete_tool_credentials_cache(), + } + else: + raise ValueError(f"Invalid opt: {payload.opt}") diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index a27f8751a64485..5fe9ea1ddaf878 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -173,7 +173,7 @@ class RequestInvokeEncrypt(BaseModel): Request to encryption """ - opt: Literal["encrypt", "decrypt"] + opt: Literal["encrypt", "decrypt", "clear"] namespace: Literal["endpoint"] identity: str data: dict = Field(default_factory=dict) diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py index a26fa0dd2673cd..4f5fa1fa5ccfba 100644 --- a/api/core/plugin/manager/tool.py +++ b/api/core/plugin/manager/tool.py @@ -34,7 +34,7 @@ def invoke( self, tenant_id: str, user_id: str, - plugin_unique_identifier: str, + plugin_id: str, tool_provider: str, tool_name: str, credentials: dict[str, Any], @@ -45,7 +45,6 @@ def invoke( f"plugin/{tenant_id}/dispatch/tool/invoke", ToolInvokeMessage, data={ - "plugin_unique_identifier": plugin_unique_identifier, "user_id": user_id, "data": { "provider": tool_provider, @@ -55,14 +54,14 @@ def invoke( }, }, headers={ - "X-Plugin-Identifier": plugin_unique_identifier, + "X-Plugin-ID": plugin_id, "Content-Type": "application/json", - } + }, ) return response def validate_provider_credentials( - self, tenant_id: str, user_id: str, plugin_unique_identifier: str, provider: str, credentials: dict[str, Any] + self, tenant_id: str, user_id: str, plugin_id: str, provider: str, credentials: dict[str, Any] ) -> bool: """ validate the credentials of the provider @@ -72,7 +71,6 @@ def validate_provider_credentials( f"plugin/{tenant_id}/dispatch/tool/validate_credentials", PluginBasicBooleanResponse, data={ - "plugin_unique_identifier": plugin_unique_identifier, "user_id": user_id, "data": { "provider": provider, @@ -80,12 +78,12 @@ def validate_provider_credentials( }, }, headers={ - "X-Plugin-Identifier": plugin_unique_identifier, + "X-Plugin-ID": plugin_id, "Content-Type": "application/json", - } + }, ) for resp in response: return resp.result - + return False diff --git a/api/core/tools/plugin_tool/provider.py b/api/core/tools/plugin_tool/provider.py index a52e7c967f4be0..4982e7405662d2 100644 --- a/api/core/tools/plugin_tool/provider.py +++ b/api/core/tools/plugin_tool/provider.py @@ -11,12 +11,12 @@ class PluginToolProviderController(BuiltinToolProviderController): entity: ToolProviderEntityWithPlugin tenant_id: str - plugin_unique_identifier: str + plugin_id: str - def __init__(self, entity: ToolProviderEntityWithPlugin, tenant_id: str, plugin_unique_identifier: str) -> None: + def __init__(self, entity: ToolProviderEntityWithPlugin, tenant_id: str, plugin_id: str) -> None: self.entity = entity self.tenant_id = tenant_id - self.plugin_unique_identifier = plugin_unique_identifier + self.plugin_id = plugin_id @property def provider_type(self) -> ToolProviderType: @@ -35,7 +35,7 @@ def _validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> No if not manager.validate_provider_credentials( tenant_id=self.tenant_id, user_id=user_id, - plugin_unique_identifier=self.plugin_unique_identifier, + plugin_id=self.plugin_id, provider=self.entity.identity.name, credentials=credentials, ): @@ -54,7 +54,7 @@ def get_tool(self, tool_name: str) -> PluginTool: entity=tool_entity, runtime=ToolRuntime(tenant_id=self.tenant_id), tenant_id=self.tenant_id, - plugin_unique_identifier=self.plugin_unique_identifier, + plugin_id=self.plugin_id, ) def get_tools(self) -> list[PluginTool]: @@ -66,7 +66,7 @@ def get_tools(self) -> list[PluginTool]: entity=tool_entity, runtime=ToolRuntime(tenant_id=self.tenant_id), tenant_id=self.tenant_id, - plugin_unique_identifier=self.plugin_unique_identifier, + plugin_id=self.plugin_id, ) for tool_entity in self.entity.tools ] diff --git a/api/core/tools/plugin_tool/tool.py b/api/core/tools/plugin_tool/tool.py index dd47f11ba27a2e..7a4f147cd04085 100644 --- a/api/core/tools/plugin_tool/tool.py +++ b/api/core/tools/plugin_tool/tool.py @@ -9,12 +9,12 @@ class PluginTool(Tool): tenant_id: str - plugin_unique_identifier: str + plugin_id: str - def __init__(self, entity: ToolEntity, runtime: ToolRuntime, tenant_id: str, plugin_unique_identifier: str) -> None: + def __init__(self, entity: ToolEntity, runtime: ToolRuntime, tenant_id: str, plugin_id: str) -> None: super().__init__(entity, runtime) self.tenant_id = tenant_id - self.plugin_unique_identifier = plugin_unique_identifier + self.plugin_id = plugin_id @property def tool_provider_type(self) -> ToolProviderType: @@ -25,7 +25,7 @@ def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[To return manager.invoke( tenant_id=self.tenant_id, user_id=user_id, - plugin_unique_identifier=self.plugin_unique_identifier, + plugin_id=self.plugin_id, tool_provider=self.entity.identity.provider, tool_name=self.entity.identity.name, credentials=self.runtime.credentials, @@ -37,5 +37,5 @@ def fork_tool_runtime(self, runtime: ToolRuntime) -> "PluginTool": entity=self.entity, runtime=runtime, tenant_id=self.tenant_id, - plugin_unique_identifier=self.plugin_unique_identifier, + plugin_id=self.plugin_id, ) diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index a4b834e8d88af6..225cd0c251f596 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -85,7 +85,7 @@ def get_plugin_provider(cls, provider: str, tenant_id: str) -> PluginToolProvide return PluginToolProviderController( entity=provider_entity.declaration, tenant_id=tenant_id, - plugin_unique_identifier=provider_entity.plugin_unique_identifier, + plugin_id=provider_entity.plugin_id, ) @classmethod @@ -402,7 +402,7 @@ def list_plugin_providers(cls, tenant_id: str) -> list[PluginToolProviderControl PluginToolProviderController( entity=provider.declaration, tenant_id=tenant_id, - plugin_unique_identifier=provider.plugin_unique_identifier, + plugin_id=provider.plugin_id, ) for provider in provider_entities ] @@ -527,13 +527,9 @@ def list_providers_from_api( ) if isinstance(provider, PluginToolProviderController): - result_providers[f"plugin_provider.{user_provider.name}.{provider.plugin_unique_identifier}"] = ( - user_provider - ) + result_providers[f"plugin_provider.{user_provider.name}.{provider.plugin_id}"] = user_provider else: - result_providers[f"builtin_provider.{user_provider.name}"] = ( - user_provider - ) + result_providers[f"builtin_provider.{user_provider.name}"] = user_provider # get db api providers diff --git a/api/services/app_service.py b/api/services/app_service.py index ac45d623e84bc9..cd20a13d5a5a71 100644 --- a/api/services/app_service.py +++ b/api/services/app_service.py @@ -155,7 +155,10 @@ def get_app(self, app: App) -> App: """ # get original app model config if app.mode == AppMode.AGENT_CHAT.value or app.is_agent: - model_config: AppModelConfig = app.app_model_config + model_config: AppModelConfig | None = app.app_model_config + if not model_config: + return app + agent_mode = model_config.agent_mode_dict # decrypt agent tool parameters if it's secret-input for tool in agent_mode.get("tools") or []: From 1c3213184e1b3784a25c520d4b23cb6c7f28c36e Mon Sep 17 00:00:00 2001 From: takatost Date: Sun, 29 Sep 2024 00:13:53 +0800 Subject: [PATCH 060/325] feat: move model request to plugin daemon --- .../console/workspace/model_providers.py | 2 +- .../model_config/converter.py | 13 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api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/web_search_chunk.py delete mode 100644 api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/__init__.py delete mode 100644 api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/video_create_params.py delete mode 100644 api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/video_object.py diff --git a/api/controllers/console/workspace/model_providers.py b/api/controllers/console/workspace/model_providers.py index fe0bcf73384ed2..03d11b56197291 100644 --- a/api/controllers/console/workspace/model_providers.py +++ b/api/controllers/console/workspace/model_providers.py @@ -132,7 +132,7 @@ class ModelProviderIconApi(Resource): def get(self, provider: str, icon_type: str, lang: str): model_provider_service = ModelProviderService() icon, mimetype = model_provider_service.get_model_provider_icon( - provider=provider, icon_type=icon_type, lang=lang + tenant_id=current_user.current_tenant_id, provider=provider, icon_type=icon_type, lang=lang ) return send_file(io.BytesIO(icon), mimetype=mimetype) diff --git a/api/core/app/app_config/easy_ui_based_app/model_config/converter.py b/api/core/app/app_config/easy_ui_based_app/model_config/converter.py index a91b9f0f020073..c72c838d066a02 100644 --- a/api/core/app/app_config/easy_ui_based_app/model_config/converter.py +++ b/api/core/app/app_config/easy_ui_based_app/model_config/converter.py @@ -4,7 +4,8 @@ from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity from core.entities.model_entities import ModelStatus from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError -from core.model_runtime.entities.model_entities import ModelType +from core.model_runtime.entities.llm_entities import LLMMode +from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel from core.provider_manager import ProviderManager @@ -67,14 +68,14 @@ def convert(cls, app_config: EasyUIBasedAppConfig, skip_check: bool = False) -> stop = completion_params["stop"] del completion_params["stop"] + model_schema = model_type_instance.get_model_schema(model_config.model, model_credentials) + # get model mode model_mode = model_config.mode if not model_mode: - mode_enum = model_type_instance.get_model_mode(model=model_config.model, credentials=model_credentials) - - model_mode = mode_enum.value - - model_schema = model_type_instance.get_model_schema(model_config.model, model_credentials) + model_mode = LLMMode.CHAT.value + if model_schema and model_schema.model_properties.get(ModelPropertyKey.MODE): + model_mode = LLMMode.value_of(model_schema.model_properties[ModelPropertyKey.MODE]).value if not skip_check and not model_schema: raise ValueError(f"Model {model_name} not exist.") diff --git a/api/core/app/app_config/easy_ui_based_app/model_config/manager.py b/api/core/app/app_config/easy_ui_based_app/model_config/manager.py index b5e4554181c06e..acc1a2d35b1a28 100644 --- a/api/core/app/app_config/easy_ui_based_app/model_config/manager.py +++ b/api/core/app/app_config/easy_ui_based_app/model_config/manager.py @@ -1,6 +1,6 @@ from core.app.app_config.entities import ModelConfigEntity from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType -from core.model_runtime.model_providers import model_provider_factory +from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory from core.provider_manager import ProviderManager @@ -50,6 +50,7 @@ def validate_and_set_defaults(cls, tenant_id: str, config: dict) -> tuple[dict, raise ValueError("model must be of object type") # model.provider + model_provider_factory = ModelProviderFactory(tenant_id) provider_entities = model_provider_factory.get_providers() model_provider_names = [provider.provider for provider in provider_entities] if "provider" not in config["model"] or config["model"]["provider"] not in model_provider_names: diff --git a/api/core/entities/provider_configuration.py b/api/core/entities/provider_configuration.py index 807f09598c7607..764221dec5d091 100644 --- a/api/core/entities/provider_configuration.py +++ b/api/core/entities/provider_configuration.py @@ -2,7 +2,7 @@ import json import logging from collections import defaultdict -from collections.abc import Iterator +from collections.abc import Iterator, Sequence from json import JSONDecodeError from typing import Optional @@ -18,16 +18,15 @@ ) from core.helper import encrypter from core.helper.model_provider_cache import ProviderCredentialsCache, ProviderCredentialsCacheType -from core.model_runtime.entities.model_entities import FetchFrom, ModelType +from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType from core.model_runtime.entities.provider_entities import ( ConfigurateMethod, CredentialFormSchema, FormType, ProviderEntity, ) -from core.model_runtime.model_providers import model_provider_factory from core.model_runtime.model_providers.__base.ai_model import AIModel -from core.model_runtime.model_providers.__base.model_provider import ModelProvider +from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory from extensions.ext_database import db from models.provider import ( LoadBalancingModelConfig, @@ -100,7 +99,9 @@ def get_current_credentials(self, model_type: ModelType, model: str) -> Optional restrict_models = quota_configuration.restrict_models - copy_credentials = self.system_configuration.credentials.copy() + copy_credentials = ( + self.system_configuration.credentials.copy() if self.system_configuration.credentials else {} + ) if restrict_models: for restrict_model in restrict_models: if ( @@ -137,6 +138,9 @@ def get_system_configuration_status(self) -> SystemConfigurationStatus: (q for q in self.system_configuration.quota_configurations if q.quota_type == current_quota_type), None ) + if not current_quota_configuration: + return SystemConfigurationStatus.UNSUPPORTED + return ( SystemConfigurationStatus.ACTIVE if current_quota_configuration.is_valid @@ -172,7 +176,7 @@ def get_custom_credentials(self, obfuscated: bool = False) -> Optional[dict]: else [], ) - def custom_credentials_validate(self, credentials: dict) -> tuple[Provider, dict]: + def custom_credentials_validate(self, credentials: dict) -> tuple[Provider | None, dict]: """ Validate custom credentials. :param credentials: provider credentials @@ -216,6 +220,7 @@ def custom_credentials_validate(self, credentials: dict) -> tuple[Provider, dict if value == HIDDEN_VALUE and key in original_credentials: credentials[key] = encrypter.decrypt_token(self.tenant_id, original_credentials[key]) + model_provider_factory = ModelProviderFactory(self.tenant_id) credentials = model_provider_factory.provider_credentials_validate( provider=self.provider.provider, credentials=credentials ) @@ -243,13 +248,13 @@ def add_or_update_custom_credentials(self, credentials: dict) -> None: provider_record.updated_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None) db.session.commit() else: - provider_record = Provider( - tenant_id=self.tenant_id, - provider_name=self.provider.provider, - provider_type=ProviderType.CUSTOM.value, - encrypted_config=json.dumps(credentials), - is_valid=True, - ) + provider_record = Provider() + provider_record.tenant_id = self.tenant_id + provider_record.provider_name = self.provider.provider + provider_record.provider_type = ProviderType.CUSTOM.value + provider_record.encrypted_config = json.dumps(credentials) + provider_record.is_valid = True + db.session.add(provider_record) db.session.commit() @@ -324,7 +329,7 @@ def get_custom_model_credentials( def custom_model_credentials_validate( self, model_type: ModelType, model: str, credentials: dict - ) -> tuple[ProviderModel, dict]: + ) -> tuple[ProviderModel | None, dict]: """ Validate custom model credentials. @@ -367,6 +372,7 @@ def custom_model_credentials_validate( if value == HIDDEN_VALUE and key in original_credentials: credentials[key] = encrypter.decrypt_token(self.tenant_id, original_credentials[key]) + model_provider_factory = ModelProviderFactory(self.tenant_id) credentials = model_provider_factory.model_credentials_validate( provider=self.provider.provider, model_type=model_type, model=model, credentials=credentials ) @@ -397,14 +403,13 @@ def add_or_update_custom_model_credentials(self, model_type: ModelType, model: s provider_model_record.updated_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None) db.session.commit() else: - provider_model_record = ProviderModel( - tenant_id=self.tenant_id, - provider_name=self.provider.provider, - model_name=model, - model_type=model_type.to_origin_model_type(), - encrypted_config=json.dumps(credentials), - is_valid=True, - ) + provider_model_record = ProviderModel() + provider_model_record.tenant_id = self.tenant_id + provider_model_record.provider_name = self.provider.provider + provider_model_record.model_name = model + provider_model_record.model_type = model_type.to_origin_model_type() + provider_model_record.encrypted_config = json.dumps(credentials) + provider_model_record.is_valid = True db.session.add(provider_model_record) db.session.commit() @@ -471,13 +476,12 @@ def enable_model(self, model_type: ModelType, model: str) -> ProviderModelSettin model_setting.updated_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None) db.session.commit() else: - model_setting = ProviderModelSetting( - tenant_id=self.tenant_id, - provider_name=self.provider.provider, - model_type=model_type.to_origin_model_type(), - model_name=model, - enabled=True, - ) + model_setting = ProviderModelSetting() + model_setting.tenant_id = self.tenant_id + model_setting.provider_name = self.provider.provider + model_setting.model_type = model_type.to_origin_model_type() + model_setting.model_name = model + model_setting.enabled = True db.session.add(model_setting) db.session.commit() @@ -506,13 +510,12 @@ def disable_model(self, model_type: ModelType, model: str) -> ProviderModelSetti model_setting.updated_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None) db.session.commit() else: - model_setting = ProviderModelSetting( - tenant_id=self.tenant_id, - provider_name=self.provider.provider, - model_type=model_type.to_origin_model_type(), - model_name=model, - enabled=False, - ) + model_setting = ProviderModelSetting() + model_setting.tenant_id = self.tenant_id + model_setting.provider_name = self.provider.provider + model_setting.model_type = model_type.to_origin_model_type() + model_setting.model_name = model + model_setting.enabled = False db.session.add(model_setting) db.session.commit() @@ -573,13 +576,12 @@ def enable_model_load_balancing(self, model_type: ModelType, model: str) -> Prov model_setting.updated_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None) db.session.commit() else: - model_setting = ProviderModelSetting( - tenant_id=self.tenant_id, - provider_name=self.provider.provider, - model_type=model_type.to_origin_model_type(), - model_name=model, - load_balancing_enabled=True, - ) + model_setting = ProviderModelSetting() + model_setting.tenant_id = self.tenant_id + model_setting.provider_name = self.provider.provider + model_setting.model_type = model_type.to_origin_model_type() + model_setting.model_name = model + model_setting.load_balancing_enabled = True db.session.add(model_setting) db.session.commit() @@ -608,25 +610,17 @@ def disable_model_load_balancing(self, model_type: ModelType, model: str) -> Pro model_setting.updated_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None) db.session.commit() else: - model_setting = ProviderModelSetting( - tenant_id=self.tenant_id, - provider_name=self.provider.provider, - model_type=model_type.to_origin_model_type(), - model_name=model, - load_balancing_enabled=False, - ) + model_setting = ProviderModelSetting() + model_setting.tenant_id = self.tenant_id + model_setting.provider_name = self.provider.provider + model_setting.model_type = model_type.to_origin_model_type() + model_setting.model_name = model + model_setting.load_balancing_enabled = False db.session.add(model_setting) db.session.commit() return model_setting - def get_provider_instance(self) -> ModelProvider: - """ - Get provider instance. - :return: - """ - return model_provider_factory.get_provider_instance(self.provider.provider) - def get_model_type_instance(self, model_type: ModelType) -> AIModel: """ Get current model type instance. @@ -634,11 +628,19 @@ def get_model_type_instance(self, model_type: ModelType) -> AIModel: :param model_type: model type :return: """ - # Get provider instance - provider_instance = self.get_provider_instance() + model_provider_factory = ModelProviderFactory(self.tenant_id) # Get model instance of LLM - return provider_instance.get_model_instance(model_type) + return model_provider_factory.get_model_type_instance(provider=self.provider.provider, model_type=model_type) + + def get_model_schema(self, model_type: ModelType, model: str, credentials: dict) -> AIModelEntity | None: + """ + Get model schema + """ + model_provider_factory = ModelProviderFactory(self.tenant_id) + return model_provider_factory.get_model_schema( + provider=self.provider.provider, model_type=model_type, model=model, credentials=credentials + ) def switch_preferred_provider_type(self, provider_type: ProviderType) -> None: """ @@ -665,11 +667,10 @@ def switch_preferred_provider_type(self, provider_type: ProviderType) -> None: if preferred_model_provider: preferred_model_provider.preferred_provider_type = provider_type.value else: - preferred_model_provider = TenantPreferredModelProvider( - tenant_id=self.tenant_id, - provider_name=self.provider.provider, - preferred_provider_type=provider_type.value, - ) + preferred_model_provider = TenantPreferredModelProvider() + preferred_model_provider.tenant_id = self.tenant_id + preferred_model_provider.provider_name = self.provider.provider + preferred_model_provider.preferred_provider_type = provider_type.value db.session.add(preferred_model_provider) db.session.commit() @@ -734,13 +735,14 @@ def get_provider_models( :param only_active: only active models :return: """ - provider_instance = self.get_provider_instance() + model_provider_factory = ModelProviderFactory(self.tenant_id) + provider_schema = model_provider_factory.get_provider_schema(self.provider.provider) model_types = [] if model_type: model_types.append(model_type) else: - model_types = provider_instance.get_provider_schema().supported_model_types + model_types = provider_schema.supported_model_types # Group model settings by model type and model model_setting_map = defaultdict(dict) @@ -749,11 +751,11 @@ def get_provider_models( if self.using_provider_type == ProviderType.SYSTEM: provider_models = self._get_system_provider_models( - model_types=model_types, provider_instance=provider_instance, model_setting_map=model_setting_map + model_types=model_types, provider_schema=provider_schema, model_setting_map=model_setting_map ) else: provider_models = self._get_custom_provider_models( - model_types=model_types, provider_instance=provider_instance, model_setting_map=model_setting_map + model_types=model_types, provider_schema=provider_schema, model_setting_map=model_setting_map ) if only_active: @@ -764,23 +766,26 @@ def get_provider_models( def _get_system_provider_models( self, - model_types: list[ModelType], - provider_instance: ModelProvider, + model_types: Sequence[ModelType], + provider_schema: ProviderEntity, model_setting_map: dict[ModelType, dict[str, ModelSettings]], ) -> list[ModelWithProviderEntity]: """ Get system provider models. :param model_types: model types - :param provider_instance: provider instance + :param provider_schema: provider schema :param model_setting_map: model setting map :return: """ provider_models = [] for model_type in model_types: - for m in provider_instance.models(model_type): + for m in provider_schema.models: + if m.model_type != model_type: + continue + status = ModelStatus.ACTIVE - if m.model_type in model_setting_map and m.model in model_setting_map[m.model_type]: + if m.model in model_setting_map: model_setting = model_setting_map[m.model_type][m.model] if model_setting.enabled is False: status = ModelStatus.DISABLED @@ -801,7 +806,7 @@ def _get_system_provider_models( if self.provider.provider not in original_provider_configurate_methods: original_provider_configurate_methods[self.provider.provider] = [] - for configurate_method in provider_instance.get_provider_schema().configurate_methods: + for configurate_method in provider_schema.configurate_methods: original_provider_configurate_methods[self.provider.provider].append(configurate_method) should_use_custom_model = False @@ -822,14 +827,20 @@ def _get_system_provider_models( ]: # only customizable model for restrict_model in restrict_models: - copy_credentials = self.system_configuration.credentials.copy() + copy_credentials = ( + self.system_configuration.credentials.copy() + if self.system_configuration.credentials + else {} + ) if restrict_model.base_model_name: copy_credentials["base_model_name"] = restrict_model.base_model_name try: - custom_model_schema = provider_instance.get_model_instance( - restrict_model.model_type - ).get_customizable_model_schema_from_credentials(restrict_model.model, copy_credentials) + custom_model_schema = self.get_model_schema( + model_type=restrict_model.model_type, + model=restrict_model.model, + credentials=copy_credentials, + ) except Exception as ex: logger.warning(f"get custom model schema failed, {ex}") continue @@ -875,15 +886,15 @@ def _get_system_provider_models( def _get_custom_provider_models( self, - model_types: list[ModelType], - provider_instance: ModelProvider, + model_types: Sequence[ModelType], + provider_schema: ProviderEntity, model_setting_map: dict[ModelType, dict[str, ModelSettings]], ) -> list[ModelWithProviderEntity]: """ Get custom provider models. :param model_types: model types - :param provider_instance: provider instance + :param provider_schema: provider schema :param model_setting_map: model setting map :return: """ @@ -897,8 +908,10 @@ def _get_custom_provider_models( if model_type not in self.provider.supported_model_types: continue - models = provider_instance.models(model_type) - for m in models: + for m in provider_schema.models: + if m.model_type != model_type: + continue + status = ModelStatus.ACTIVE if credentials else ModelStatus.NO_CONFIGURE load_balancing_enabled = False if m.model_type in model_setting_map and m.model in model_setting_map[m.model_type]: @@ -930,10 +943,10 @@ def _get_custom_provider_models( continue try: - custom_model_schema = provider_instance.get_model_instance( - model_configuration.model_type - ).get_customizable_model_schema_from_credentials( - model_configuration.model, model_configuration.credentials + custom_model_schema = self.get_model_schema( + model_type=model_configuration.model_type, + model=model_configuration.model, + credentials=model_configuration.credentials, ) except Exception as ex: logger.warning(f"get custom model schema failed, {ex}") @@ -1043,7 +1056,7 @@ def __iter__(self): return iter(self.configurations) def values(self) -> Iterator[ProviderConfiguration]: - return self.configurations.values() + return iter(self.configurations.values()) def get(self, key, default=None): return self.configurations.get(key, default) @@ -1055,7 +1068,6 @@ class ProviderModelBundle(BaseModel): """ configuration: ProviderConfiguration - provider_instance: ModelProvider model_type_instance: AIModel # pydantic configs diff --git a/api/core/helper/moderation.py b/api/core/helper/moderation.py index b880590de28476..f3144039e31654 100644 --- a/api/core/helper/moderation.py +++ b/api/core/helper/moderation.py @@ -23,6 +23,9 @@ def check_moderation(model_config: ModelConfigWithCredentialsEntity, text: str) if using_provider_type == ProviderType.SYSTEM and provider_name in moderation_config.providers: hosting_openai_config = hosting_configuration.provider_map["openai"] + if hosting_openai_config.credentials is None: + return False + # 2000 text per chunk length = 2000 text_chunks = [text[i : i + length] for i in range(0, len(text), length)] diff --git a/api/core/model_runtime/entities/provider_entities.py b/api/core/model_runtime/entities/provider_entities.py index bfe861a97ffbf8..a6a7b67577757f 100644 --- a/api/core/model_runtime/entities/provider_entities.py +++ b/api/core/model_runtime/entities/provider_entities.py @@ -5,7 +5,7 @@ from pydantic import BaseModel, ConfigDict from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import ModelType, ProviderModel +from core.model_runtime.entities.model_entities import AIModelEntity, ModelType class ConfigurateMethod(Enum): @@ -101,7 +101,7 @@ class SimpleProviderEntity(BaseModel): icon_small: Optional[I18nObject] = None icon_large: Optional[I18nObject] = None supported_model_types: Sequence[ModelType] - models: list[ProviderModel] = [] + models: list[AIModelEntity] = [] class ProviderHelpEntity(BaseModel): @@ -127,7 +127,7 @@ class ProviderEntity(BaseModel): help: Optional[ProviderHelpEntity] = None supported_model_types: Sequence[ModelType] configurate_methods: list[ConfigurateMethod] - models: list[ProviderModel] = [] + models: list[AIModelEntity] = [] provider_credential_schema: Optional[ProviderCredentialSchema] = None model_credential_schema: Optional[ModelCredentialSchema] = None diff --git a/api/core/model_runtime/model_providers/__base/ai_model.py b/api/core/model_runtime/model_providers/__base/ai_model.py index 79a1d28ebe637e..6b04ba2efd9ca3 100644 --- a/api/core/model_runtime/model_providers/__base/ai_model.py +++ b/api/core/model_runtime/model_providers/__base/ai_model.py @@ -1,10 +1,9 @@ import decimal import os -from abc import ABC, abstractmethod from collections.abc import Mapping from typing import Optional -from pydantic import ConfigDict +from pydantic import ConfigDict, Field from core.helper.position_helper import get_position_map, sort_by_position_map from core.model_runtime.entities.common_entities import I18nObject @@ -20,34 +19,26 @@ ) from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError from core.model_runtime.model_providers.__base.tokenizers.gpt2_tokenzier import GPT2Tokenizer +from core.plugin.entities.plugin_daemon import PluginModelProviderEntity from core.tools.utils.yaml_utils import load_yaml_file -class AIModel(ABC): +class AIModel: """ Base class for all models. """ - model_type: ModelType - model_schemas: Optional[list[AIModelEntity]] = None - started_at: float = 0 + tenant_id: str = Field(description="Tenant ID") + model_type: ModelType = Field(description="Model type") + plugin_id: str = Field(description="Plugin ID") + provider_name: str = Field(description="Provider") + plugin_model_provider: PluginModelProviderEntity = Field(description="Plugin model provider") + started_at: float = Field(description="Invoke start time", default=0) # pydantic configs model_config = ConfigDict(protected_namespaces=()) - @abstractmethod - def validate_credentials(self, model: str, credentials: Mapping) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - raise NotImplementedError - @property - @abstractmethod def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: """ Map model invoke error to unified error @@ -66,20 +57,18 @@ def _transform_invoke_error(self, error: Exception) -> InvokeError: :param error: model invoke error :return: unified error """ - provider_name = self.__class__.__module__.split(".")[-3] - for invoke_error, model_errors in self._invoke_error_mapping.items(): if isinstance(error, tuple(model_errors)): if invoke_error == InvokeAuthorizationError: return invoke_error( description=( - f"[{provider_name}] Incorrect model credentials provided, please check and try again." + f"[{self.provider_name}] Incorrect model credentials provided, please check and try again." ) ) - return invoke_error(description=f"[{provider_name}] {invoke_error.description}, {str(error)}") + return invoke_error(description=f"[{self.provider_name}] {invoke_error.description}, {str(error)}") - return InvokeError(description=f"[{provider_name}] Error: {str(error)}") + return InvokeError(description=f"[{self.provider_name}] Error: {str(error)}") def get_price(self, model: str, credentials: dict, price_type: PriceType, tokens: int) -> PriceInfo: """ diff --git a/api/core/model_runtime/model_providers/__base/large_language_model.py b/api/core/model_runtime/model_providers/__base/large_language_model.py index ba88cc1f384fc5..33dbce37c4c9d2 100644 --- a/api/core/model_runtime/model_providers/__base/large_language_model.py +++ b/api/core/model_runtime/model_providers/__base/large_language_model.py @@ -1,32 +1,25 @@ import logging import os -import re import time -from abc import abstractmethod -from collections.abc import Generator, Mapping +from collections.abc import Generator from typing import Optional, Union from pydantic import ConfigDict from core.model_runtime.callbacks.base_callback import Callback from core.model_runtime.callbacks.logging_callback import LoggingCallback -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage +from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMUsage from core.model_runtime.entities.message_entities import ( AssistantPromptMessage, PromptMessage, - PromptMessageContentType, PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, ) from core.model_runtime.entities.model_entities import ( - ModelPropertyKey, ModelType, - ParameterRule, - ParameterType, PriceType, ) from core.model_runtime.model_providers.__base.ai_model import AIModel +from core.plugin.manager.model import PluginModelManager logger = logging.getLogger(__name__) @@ -71,8 +64,6 @@ def invoke( if model_parameters is None: model_parameters = {} - model_parameters = self._validate_and_filter_model_parameters(model, model_parameters, credentials) - self.started_at = time.perf_counter() callbacks = callbacks or [] @@ -94,20 +85,43 @@ def invoke( ) try: - if "response_format" in model_parameters: - result = self._code_block_mode_wrapper( + plugin_model_manager = PluginModelManager() + result = plugin_model_manager.invoke_llm( + tenant_id=self.tenant_id, + user_id=user or "unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model=model, + credentials=credentials, + model_parameters=model_parameters, + prompt_messages=prompt_messages, + tools=tools, + stop=stop, + stream=stream, + ) + + if not stream: + content = "" + content_list = [] + usage = LLMUsage.empty_usage() + system_fingerprint = None + for chunk in result: + if isinstance(chunk.delta.message.content, str): + content += chunk.delta.message.content + elif isinstance(chunk.delta.message.content, list): + content_list.extend(chunk.delta.message.content) + + usage = chunk.delta.usage or LLMUsage.empty_usage() + system_fingerprint = chunk.system_fingerprint + break + + result = LLMResult( model=model, - credentials=credentials, prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - callbacks=callbacks, + message=AssistantPromptMessage(content=content or content_list), + usage=usage, + system_fingerprint=system_fingerprint, ) - else: - result = self._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) except Exception as e: self._trigger_invoke_error_callbacks( model=model, @@ -122,6 +136,7 @@ def invoke( callbacks=callbacks, ) + # TODO raise self._transform_invoke_error(e) if stream and isinstance(result, Generator): @@ -153,244 +168,6 @@ def invoke( return result - def _code_block_mode_wrapper( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - callbacks: Optional[list[Callback]] = None, - ) -> Union[LLMResult, Generator]: - """ - Code block mode wrapper, ensure the response is a code block with output markdown quote - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :param callbacks: callbacks - :return: full response or stream response chunk generator result - """ - - block_prompts = """You should always follow the instructions and output a valid {{block}} object. -The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - - -{{instructions}} - -""" # noqa: E501 - - code_block = model_parameters.get("response_format", "") - if not code_block: - return self._invoke( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - model_parameters.pop("response_format") - stop = stop or [] - stop.extend(["\n```", "```\n"]) - block_prompts = block_prompts.replace("{{block}}", code_block) - - # check if there is a system message - if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): - # override the system message - prompt_messages[0] = SystemPromptMessage( - content=block_prompts.replace("{{instructions}}", str(prompt_messages[0].content)) - ) - else: - # insert the system message - prompt_messages.insert( - 0, - SystemPromptMessage( - content=block_prompts.replace("{{instructions}}", f"Please output a valid {code_block} object.") - ), - ) - - if len(prompt_messages) > 0 and isinstance(prompt_messages[-1], UserPromptMessage): - # add ```JSON\n to the last text message - if isinstance(prompt_messages[-1].content, str): - prompt_messages[-1].content += f"\n```{code_block}\n" - elif isinstance(prompt_messages[-1].content, list): - for i in range(len(prompt_messages[-1].content) - 1, -1, -1): - if prompt_messages[-1].content[i].type == PromptMessageContentType.TEXT: - prompt_messages[-1].content[i].data += f"\n```{code_block}\n" - break - else: - # append a user message - prompt_messages.append(UserPromptMessage(content=f"```{code_block}\n")) - - response = self._invoke( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - if isinstance(response, Generator): - first_chunk = next(response) - - def new_generator(): - yield first_chunk - yield from response - - if first_chunk.delta.message.content and first_chunk.delta.message.content.startswith("`"): - return self._code_block_mode_stream_processor_with_backtick( - model=model, prompt_messages=prompt_messages, input_generator=new_generator() - ) - else: - return self._code_block_mode_stream_processor( - model=model, prompt_messages=prompt_messages, input_generator=new_generator() - ) - - return response - - def _code_block_mode_stream_processor( - self, model: str, prompt_messages: list[PromptMessage], input_generator: Generator[LLMResultChunk, None, None] - ) -> Generator[LLMResultChunk, None, None]: - """ - Code block mode stream processor, ensure the response is a code block with output markdown quote - - :param model: model name - :param prompt_messages: prompt messages - :param input_generator: input generator - :return: output generator - """ - state = "normal" - backtick_count = 0 - for piece in input_generator: - if piece.delta.message.content: - content = piece.delta.message.content - piece.delta.message.content = "" - yield piece - piece = content - else: - yield piece - continue - new_piece: str = "" - for char in piece: - char = str(char) - if state == "normal": - if char == "`": - state = "in_backticks" - backtick_count = 1 - else: - new_piece += char - elif state == "in_backticks": - if char == "`": - backtick_count += 1 - if backtick_count == 3: - state = "skip_content" - backtick_count = 0 - else: - new_piece += "`" * backtick_count + char - state = "normal" - backtick_count = 0 - elif state == "skip_content": - if char.isspace(): - state = "normal" - - if new_piece: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=new_piece, tool_calls=[]), - ), - ) - - def _code_block_mode_stream_processor_with_backtick( - self, model: str, prompt_messages: list, input_generator: Generator[LLMResultChunk, None, None] - ) -> Generator[LLMResultChunk, None, None]: - """ - Code block mode stream processor, ensure the response is a code block with output markdown quote. - This version skips the language identifier that follows the opening triple backticks. - - :param model: model name - :param prompt_messages: prompt messages - :param input_generator: input generator - :return: output generator - """ - state = "search_start" - backtick_count = 0 - - for piece in input_generator: - if piece.delta.message.content: - content = piece.delta.message.content - # Reset content to ensure we're only processing and yielding the relevant parts - piece.delta.message.content = "" - # Yield a piece with cleared content before processing it to maintain the generator structure - yield piece - piece = content - else: - # Yield pieces without content directly - yield piece - continue - - if state == "done": - continue - - new_piece: str = "" - for char in piece: - if state == "search_start": - if char == "`": - backtick_count += 1 - if backtick_count == 3: - state = "skip_language" - backtick_count = 0 - else: - backtick_count = 0 - elif state == "skip_language": - # Skip everything until the first newline, marking the end of the language identifier - if char == "\n": - state = "in_code_block" - elif state == "in_code_block": - if char == "`": - backtick_count += 1 - if backtick_count == 3: - state = "done" - break - else: - if backtick_count > 0: - # If backticks were counted but we're still collecting content, it was a false start - new_piece += "`" * backtick_count - backtick_count = 0 - new_piece += str(char) - - elif state == "done": - break - - if new_piece: - # Only yield content collected within the code block - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=new_piece, tool_calls=[]), - ), - ) - def _invoke_result_generator( self, model: str, @@ -462,34 +239,6 @@ def _invoke_result_generator( callbacks=callbacks, ) - @abstractmethod - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - raise NotImplementedError - - @abstractmethod def get_num_tokens( self, model: str, @@ -506,41 +255,18 @@ def get_num_tokens( :param tools: tools for tool calling :return: """ - raise NotImplementedError - - def enforce_stop_tokens(self, text: str, stop: list[str]) -> str: - """Cut off the text as soon as any stop words occur.""" - return re.split("|".join(stop), text, maxsplit=1)[0] - - def get_parameter_rules(self, model: str, credentials: dict) -> list[ParameterRule]: - """ - Get parameter rules - - :param model: model name - :param credentials: model credentials - :return: parameter rules - """ - model_schema = self.get_model_schema(model, credentials) - if model_schema: - return model_schema.parameter_rules - - return [] - - def get_model_mode(self, model: str, credentials: Optional[Mapping] = None) -> LLMMode: - """ - Get model mode - - :param model: model name - :param credentials: model credentials - :return: model mode - """ - model_schema = self.get_model_schema(model, credentials) - - mode = LLMMode.CHAT - if model_schema and model_schema.model_properties.get(ModelPropertyKey.MODE): - mode = LLMMode.value_of(model_schema.model_properties[ModelPropertyKey.MODE]) - - return mode + plugin_model_manager = PluginModelManager() + return plugin_model_manager.get_llm_num_tokens( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model_type=self.model_type.value, + model=model, + credentials=credentials, + prompt_messages=prompt_messages, + tools=tools, + ) def _calc_response_usage( self, model: str, credentials: dict, prompt_tokens: int, completion_tokens: int @@ -772,98 +498,3 @@ def _trigger_invoke_error_callbacks( raise e else: logger.warning(f"Callback {callback.__class__.__name__} on_invoke_error failed with error {e}") - - def _validate_and_filter_model_parameters(self, model: str, model_parameters: dict, credentials: dict) -> dict: - """ - Validate model parameters - - :param model: model name - :param model_parameters: model parameters - :param credentials: model credentials - :return: - """ - parameter_rules = self.get_parameter_rules(model, credentials) - - # validate model parameters - filtered_model_parameters = {} - for parameter_rule in parameter_rules: - parameter_name = parameter_rule.name - parameter_value = model_parameters.get(parameter_name) - if parameter_value is None: - if parameter_rule.use_template and parameter_rule.use_template in model_parameters: - # if parameter value is None, use template value variable name instead - parameter_value = model_parameters[parameter_rule.use_template] - else: - if parameter_rule.required: - if parameter_rule.default is not None: - filtered_model_parameters[parameter_name] = parameter_rule.default - continue - else: - raise ValueError(f"Model Parameter {parameter_name} is required.") - else: - continue - - # validate parameter value type - if parameter_rule.type == ParameterType.INT: - if not isinstance(parameter_value, int): - raise ValueError(f"Model Parameter {parameter_name} should be int.") - - # validate parameter value range - if parameter_rule.min is not None and parameter_value < parameter_rule.min: - raise ValueError( - f"Model Parameter {parameter_name} should be greater than or equal to {parameter_rule.min}." - ) - - if parameter_rule.max is not None and parameter_value > parameter_rule.max: - raise ValueError( - f"Model Parameter {parameter_name} should be less than or equal to {parameter_rule.max}." - ) - elif parameter_rule.type == ParameterType.FLOAT: - if not isinstance(parameter_value, float | int): - raise ValueError(f"Model Parameter {parameter_name} should be float.") - - # validate parameter value precision - if parameter_rule.precision is not None: - if parameter_rule.precision == 0: - if parameter_value != int(parameter_value): - raise ValueError(f"Model Parameter {parameter_name} should be int.") - else: - if parameter_value != round(parameter_value, parameter_rule.precision): - raise ValueError( - f"Model Parameter {parameter_name} should be round to {parameter_rule.precision}" - f" decimal places." - ) - - # validate parameter value range - if parameter_rule.min is not None and parameter_value < parameter_rule.min: - raise ValueError( - f"Model Parameter {parameter_name} should be greater than or equal to {parameter_rule.min}." - ) - - if parameter_rule.max is not None and parameter_value > parameter_rule.max: - raise ValueError( - f"Model Parameter {parameter_name} should be less than or equal to {parameter_rule.max}." - ) - elif parameter_rule.type == ParameterType.BOOLEAN: - if not isinstance(parameter_value, bool): - raise ValueError(f"Model Parameter {parameter_name} should be bool.") - elif parameter_rule.type == ParameterType.STRING: - if not isinstance(parameter_value, str): - raise ValueError(f"Model Parameter {parameter_name} should be string.") - - # validate options - if parameter_rule.options and parameter_value not in parameter_rule.options: - raise ValueError(f"Model Parameter {parameter_name} should be one of {parameter_rule.options}.") - elif parameter_rule.type == ParameterType.TEXT: - if not isinstance(parameter_value, str): - raise ValueError(f"Model Parameter {parameter_name} should be text.") - - # validate options - if parameter_rule.options and parameter_value not in parameter_rule.options: - raise ValueError(f"Model Parameter {parameter_name} should be one of {parameter_rule.options}.") - else: - raise ValueError(f"Model Parameter {parameter_name} type {parameter_rule.type} is not supported.") - - filtered_model_parameters[parameter_name] = parameter_value - - return filtered_model_parameters diff --git a/api/core/model_runtime/model_providers/__base/text_embedding_model.py b/api/core/model_runtime/model_providers/__base/text_embedding_model.py index a948dca20d69a4..1a5c40ed516da1 100644 --- a/api/core/model_runtime/model_providers/__base/text_embedding_model.py +++ b/api/core/model_runtime/model_providers/__base/text_embedding_model.py @@ -8,6 +8,7 @@ from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult from core.model_runtime.model_providers.__base.ai_model import AIModel +from core.plugin.manager.model import PluginModelManager class TextEmbeddingModel(AIModel): @@ -66,7 +67,6 @@ def _invoke( """ raise NotImplementedError - @abstractmethod def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: """ Get number of tokens for given prompt messages @@ -76,7 +76,17 @@ def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int :param texts: texts to embed :return: """ - raise NotImplementedError + plugin_model_manager = PluginModelManager() + return plugin_model_manager.get_text_embedding_num_tokens( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model_type=self.model_type.value, + model=model, + credentials=credentials, + texts=texts, + ) def _get_context_size(self, model: str, credentials: dict) -> int: """ diff --git a/api/core/model_runtime/model_providers/__init__.py b/api/core/model_runtime/model_providers/__init__.py index 9d71013dbfa151..e69de29bb2d1d6 100644 --- a/api/core/model_runtime/model_providers/__init__.py +++ b/api/core/model_runtime/model_providers/__init__.py @@ -1,3 +0,0 @@ -from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory - -model_provider_factory = ModelProviderFactory() diff --git a/api/core/model_runtime/model_providers/anthropic/__init__.py b/api/core/model_runtime/model_providers/anthropic/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/anthropic/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/anthropic/_assets/icon_l_en.svg deleted file mode 100644 index cace17da73bd0a..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/_assets/icon_l_en.svg +++ /dev/null @@ -1,78 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/anthropic/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/anthropic/_assets/icon_s_en.svg deleted file mode 100644 index d852f04401fd94..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/_assets/icon_s_en.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - diff --git a/api/core/model_runtime/model_providers/anthropic/anthropic.py b/api/core/model_runtime/model_providers/anthropic/anthropic.py deleted file mode 100644 index 5b12f04a3e59b8..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/anthropic.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class AnthropicProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `claude-3-opus-20240229` model for validate, - model_instance.validate_credentials(model="claude-3-opus-20240229", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/anthropic/anthropic.yaml b/api/core/model_runtime/model_providers/anthropic/anthropic.yaml deleted file mode 100644 index cf41f544ef4aa3..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/anthropic.yaml +++ /dev/null @@ -1,39 +0,0 @@ -provider: anthropic -label: - en_US: Anthropic -description: - en_US: Anthropic’s powerful models, such as Claude 3. - zh_Hans: Anthropic 的强大模型，例如 Claude 3。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#F0F0EB" -help: - title: - en_US: Get your API Key from Anthropic - zh_Hans: 从 Anthropic 获取 API Key - url: - en_US: https://console.anthropic.com/account/keys -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: anthropic_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: anthropic_api_url - label: - en_US: API URL - type: text-input - required: false - placeholder: - zh_Hans: 在此输入您的 API URL - en_US: Enter your API URL diff --git a/api/core/model_runtime/model_providers/anthropic/llm/__init__.py b/api/core/model_runtime/model_providers/anthropic/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/anthropic/llm/_position.yaml b/api/core/model_runtime/model_providers/anthropic/llm/_position.yaml deleted file mode 100644 index 8394c4276a786e..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/_position.yaml +++ /dev/null @@ -1,8 +0,0 @@ -- claude-3-5-sonnet-20240620 -- claude-3-haiku-20240307 -- claude-3-opus-20240229 -- claude-3-sonnet-20240229 -- claude-2.1 -- claude-instant-1.2 -- claude-2 -- claude-instant-1 diff --git a/api/core/model_runtime/model_providers/anthropic/llm/claude-2.1.yaml b/api/core/model_runtime/model_providers/anthropic/llm/claude-2.1.yaml deleted file mode 100644 index 6707c3459402f3..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/claude-2.1.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: claude-2.1 -label: - en_US: claude-2.1 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '8.00' - output: '24.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/anthropic/llm/claude-2.yaml b/api/core/model_runtime/model_providers/anthropic/llm/claude-2.yaml deleted file mode 100644 index 1986947129462f..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/claude-2.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: claude-2 -label: - en_US: claude-2 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 100000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '8.00' - output: '24.00' - unit: '0.000001' - currency: USD -deprecated: true diff --git a/api/core/model_runtime/model_providers/anthropic/llm/claude-3-5-sonnet-20240620.yaml b/api/core/model_runtime/model_providers/anthropic/llm/claude-3-5-sonnet-20240620.yaml deleted file mode 100644 index e02c5517fe1f3c..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/claude-3-5-sonnet-20240620.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: claude-3-5-sonnet-20240620 -label: - en_US: claude-3-5-sonnet-20240620 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format -pricing: - input: '3.00' - output: '15.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/anthropic/llm/claude-3-haiku-20240307.yaml b/api/core/model_runtime/model_providers/anthropic/llm/claude-3-haiku-20240307.yaml deleted file mode 100644 index cb2af1308a0791..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/claude-3-haiku-20240307.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: claude-3-haiku-20240307 -label: - en_US: claude-3-haiku-20240307 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '0.25' - output: '1.25' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/anthropic/llm/claude-3-opus-20240229.yaml b/api/core/model_runtime/model_providers/anthropic/llm/claude-3-opus-20240229.yaml deleted file mode 100644 index 101f54c3f8ad6a..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/claude-3-opus-20240229.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: claude-3-opus-20240229 -label: - en_US: claude-3-opus-20240229 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '15.00' - output: '75.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/anthropic/llm/claude-3-sonnet-20240229.yaml b/api/core/model_runtime/model_providers/anthropic/llm/claude-3-sonnet-20240229.yaml deleted file mode 100644 index daf55553f8bea5..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/claude-3-sonnet-20240229.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: claude-3-sonnet-20240229 -label: - en_US: claude-3-sonnet-20240229 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '3.00' - output: '15.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/anthropic/llm/claude-instant-1.2.yaml b/api/core/model_runtime/model_providers/anthropic/llm/claude-instant-1.2.yaml deleted file mode 100644 index ac69bbf4d293d3..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/claude-instant-1.2.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: claude-instant-1.2 -label: - en_US: claude-instant-1.2 -model_type: llm -features: [ ] -model_properties: - mode: chat - context_size: 100000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '1.63' - output: '5.51' - unit: '0.000001' - currency: USD -deprecated: true diff --git a/api/core/model_runtime/model_providers/anthropic/llm/claude-instant-1.yaml b/api/core/model_runtime/model_providers/anthropic/llm/claude-instant-1.yaml deleted file mode 100644 index 5e76d5b1c2e74b..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/claude-instant-1.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: claude-instant-1 -label: - en_US: claude-instant-1 -model_type: llm -features: [ ] -model_properties: - mode: chat - context_size: 100000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '1.63' - output: '5.51' - unit: '0.000001' - currency: USD -deprecated: true diff --git a/api/core/model_runtime/model_providers/anthropic/llm/llm.py b/api/core/model_runtime/model_providers/anthropic/llm/llm.py deleted file mode 100644 index 46e1b415b81253..00000000000000 --- a/api/core/model_runtime/model_providers/anthropic/llm/llm.py +++ /dev/null @@ -1,624 +0,0 @@ -import base64 -import io -import json -from collections.abc import Generator -from typing import Optional, Union, cast - -import anthropic -import requests -from anthropic import Anthropic, Stream -from anthropic.types import ( - ContentBlockDeltaEvent, - Message, - MessageDeltaEvent, - MessageStartEvent, - MessageStopEvent, - MessageStreamEvent, - completion_create_params, -) -from anthropic.types.beta.tools import ToolsBetaMessage -from httpx import Timeout -from PIL import Image - -from core.model_runtime.callbacks.base_callback import Callback -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -ANTHROPIC_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. -The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - - -{{instructions}} - -""" # noqa: E501 - - -class AnthropicLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # invoke model - return self._chat_generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def _chat_generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke llm chat model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - # transform model parameters from completion api of anthropic to chat api - if "max_tokens_to_sample" in model_parameters: - model_parameters["max_tokens"] = model_parameters.pop("max_tokens_to_sample") - - # init model client - client = Anthropic(**credentials_kwargs) - - extra_model_kwargs = {} - if stop: - extra_model_kwargs["stop_sequences"] = stop - - if user: - extra_model_kwargs["metadata"] = completion_create_params.Metadata(user_id=user) - - system, prompt_message_dicts = self._convert_prompt_messages(prompt_messages) - - if system: - extra_model_kwargs["system"] = system - - # Add the new header for claude-3-5-sonnet-20240620 model - extra_headers = {} - if model == "claude-3-5-sonnet-20240620": - if model_parameters.get("max_tokens") > 4096: - extra_headers["anthropic-beta"] = "max-tokens-3-5-sonnet-2024-07-15" - - if tools: - extra_model_kwargs["tools"] = [self._transform_tool_prompt(tool) for tool in tools] - response = client.beta.tools.messages.create( - model=model, - messages=prompt_message_dicts, - stream=stream, - extra_headers=extra_headers, - **model_parameters, - **extra_model_kwargs, - ) - else: - # chat model - response = client.messages.create( - model=model, - messages=prompt_message_dicts, - stream=stream, - extra_headers=extra_headers, - **model_parameters, - **extra_model_kwargs, - ) - - if stream: - return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_chat_generate_response(model, credentials, response, prompt_messages) - - def _code_block_mode_wrapper( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - callbacks: list[Callback] = None, - ) -> Union[LLMResult, Generator]: - """ - Code block mode wrapper for invoking large language model - """ - if model_parameters.get("response_format"): - stop = stop or [] - # chat model - self._transform_chat_json_prompts( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - response_format=model_parameters["response_format"], - ) - model_parameters.pop("response_format") - - return self._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def _transform_tool_prompt(self, tool: PromptMessageTool) -> dict: - return {"name": tool.name, "description": tool.description, "input_schema": tool.parameters} - - def _transform_chat_json_prompts( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - response_format: str = "JSON", - ) -> None: - """ - Transform json prompts - """ - if "```\n" not in stop: - stop.append("```\n") - if "\n```" not in stop: - stop.append("\n```") - - # check if there is a system message - if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): - # override the system message - prompt_messages[0] = SystemPromptMessage( - content=ANTHROPIC_BLOCK_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content).replace( - "{{block}}", response_format - ) - ) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}")) - else: - # insert the system message - prompt_messages.insert( - 0, - SystemPromptMessage( - content=ANTHROPIC_BLOCK_MODE_PROMPT.replace( - "{{instructions}}", f"Please output a valid {response_format} object." - ).replace("{{block}}", response_format) - ), - ) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}")) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - prompt = self._convert_messages_to_prompt_anthropic(prompt_messages) - - client = Anthropic(api_key="") - tokens = client.count_tokens(prompt) - - tool_call_inner_prompts_tokens_map = { - "claude-3-opus-20240229": 395, - "claude-3-haiku-20240307": 264, - "claude-3-sonnet-20240229": 159, - } - - if model in tool_call_inner_prompts_tokens_map and tools: - tokens += tool_call_inner_prompts_tokens_map[model] - - return tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._chat_generate( - model=model, - credentials=credentials, - prompt_messages=[ - UserPromptMessage(content="ping"), - ], - model_parameters={ - "temperature": 0, - "max_tokens": 20, - }, - stream=False, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - response: Union[Message, ToolsBetaMessage], - prompt_messages: list[PromptMessage], - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content="", tool_calls=[]) - - for content in response.content: - if content.type == "text": - assistant_prompt_message.content += content.text - elif content.type == "tool_use": - tool_call = AssistantPromptMessage.ToolCall( - id=content.id, - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=content.name, arguments=json.dumps(content.input) - ), - ) - assistant_prompt_message.tool_calls.append(tool_call) - - # calculate num tokens - if response.usage: - # transform usage - prompt_tokens = response.usage.input_tokens - completion_tokens = response.usage.output_tokens - else: - # calculate num tokens - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - response = LLMResult( - model=response.model, prompt_messages=prompt_messages, message=assistant_prompt_message, usage=usage - ) - - return response - - def _handle_chat_generate_stream_response( - self, model: str, credentials: dict, response: Stream[MessageStreamEvent], prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm chat stream response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator - """ - full_assistant_content = "" - return_model = None - input_tokens = 0 - output_tokens = 0 - finish_reason = None - index = 0 - - tool_calls: list[AssistantPromptMessage.ToolCall] = [] - - for chunk in response: - if isinstance(chunk, MessageStartEvent): - if hasattr(chunk, "content_block"): - content_block = chunk.content_block - if isinstance(content_block, dict): - if content_block.get("type") == "tool_use": - tool_call = AssistantPromptMessage.ToolCall( - id=content_block.get("id"), - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=content_block.get("name"), arguments="" - ), - ) - tool_calls.append(tool_call) - elif hasattr(chunk, "delta"): - delta = chunk.delta - if isinstance(delta, dict) and len(tool_calls) > 0: - if delta.get("type") == "input_json_delta": - tool_calls[-1].function.arguments += delta.get("partial_json", "") - elif chunk.message: - return_model = chunk.message.model - input_tokens = chunk.message.usage.input_tokens - elif isinstance(chunk, MessageDeltaEvent): - output_tokens = chunk.usage.output_tokens - finish_reason = chunk.delta.stop_reason - elif isinstance(chunk, MessageStopEvent): - # transform usage - usage = self._calc_response_usage(model, credentials, input_tokens, output_tokens) - - # transform empty tool call arguments to {} - for tool_call in tool_calls: - if not tool_call.function.arguments: - tool_call.function.arguments = "{}" - - yield LLMResultChunk( - model=return_model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index + 1, - message=AssistantPromptMessage(content="", tool_calls=tool_calls), - finish_reason=finish_reason, - usage=usage, - ), - ) - elif isinstance(chunk, ContentBlockDeltaEvent): - chunk_text = chunk.delta.text or "" - full_assistant_content += chunk_text - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=chunk_text) - - index = chunk.index - - yield LLMResultChunk( - model=return_model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk.index, - message=assistant_prompt_message, - ), - ) - - def _to_credential_kwargs(self, credentials: dict) -> dict: - """ - Transform credentials to kwargs for model instance - - :param credentials: - :return: - """ - credentials_kwargs = { - "api_key": credentials["anthropic_api_key"], - "timeout": Timeout(315.0, read=300.0, write=10.0, connect=5.0), - "max_retries": 1, - } - - if credentials.get("anthropic_api_url"): - credentials["anthropic_api_url"] = credentials["anthropic_api_url"].rstrip("/") - credentials_kwargs["base_url"] = credentials["anthropic_api_url"] - - return credentials_kwargs - - def _convert_prompt_messages(self, prompt_messages: list[PromptMessage]) -> tuple[str, list[dict]]: - """ - Convert prompt messages to dict list and system - """ - system = "" - first_loop = True - for message in prompt_messages: - if isinstance(message, SystemPromptMessage): - message.content = message.content.strip() - if first_loop: - system = message.content - first_loop = False - else: - system += "\n" - system += message.content - - prompt_message_dicts = [] - for message in prompt_messages: - if not isinstance(message, SystemPromptMessage): - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - prompt_message_dicts.append(message_dict) - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - if not message_content.data.startswith("data:"): - # fetch image data from url - try: - image_content = requests.get(message_content.data).content - with Image.open(io.BytesIO(image_content)) as img: - mime_type = f"image/{img.format.lower()}" - base64_data = base64.b64encode(image_content).decode("utf-8") - except Exception as ex: - raise ValueError( - f"Failed to fetch image data from url {message_content.data}, {ex}" - ) - else: - data_split = message_content.data.split(";base64,") - mime_type = data_split[0].replace("data:", "") - base64_data = data_split[1] - - if mime_type not in {"image/jpeg", "image/png", "image/gif", "image/webp"}: - raise ValueError( - f"Unsupported image type {mime_type}, " - f"only support image/jpeg, image/png, image/gif, and image/webp" - ) - - sub_message_dict = { - "type": "image", - "source": {"type": "base64", "media_type": mime_type, "data": base64_data}, - } - sub_messages.append(sub_message_dict) - prompt_message_dicts.append({"role": "user", "content": sub_messages}) - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - content = [] - if message.tool_calls: - for tool_call in message.tool_calls: - content.append( - { - "type": "tool_use", - "id": tool_call.id, - "name": tool_call.function.name, - "input": json.loads(tool_call.function.arguments), - } - ) - if message.content: - content.append({"type": "text", "text": message.content}) - - if prompt_message_dicts[-1]["role"] == "assistant": - prompt_message_dicts[-1]["content"].extend(content) - else: - prompt_message_dicts.append({"role": "assistant", "content": content}) - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = { - "role": "user", - "content": [ - {"type": "tool_result", "tool_use_id": message.tool_call_id, "content": message.content} - ], - } - prompt_message_dicts.append(message_dict) - else: - raise ValueError(f"Got unknown type {message}") - - return system, prompt_message_dicts - - def _convert_one_message_to_text(self, message: PromptMessage) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt = "\n\nHuman:" - ai_prompt = "\n\nAssistant:" - content = message.content - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - if not isinstance(message.content, list): - message_text = f"{ai_prompt} {content}" - else: - message_text = "" - for sub_message in message.content: - if sub_message.type == PromptMessageContentType.TEXT: - message_text += f"{human_prompt} {sub_message.data}" - elif sub_message.type == PromptMessageContentType.IMAGE: - message_text += f"{human_prompt} [IMAGE]" - elif isinstance(message, AssistantPromptMessage): - if not isinstance(message.content, list): - message_text = f"{ai_prompt} {content}" - else: - message_text = "" - for sub_message in message.content: - if sub_message.type == PromptMessageContentType.TEXT: - message_text += f"{ai_prompt} {sub_message.data}" - elif sub_message.type == PromptMessageContentType.IMAGE: - message_text += f"{ai_prompt} [IMAGE]" - elif isinstance(message, SystemPromptMessage): - message_text = content - elif isinstance(message, ToolPromptMessage): - message_text = f"{human_prompt} {message.content}" - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - def _convert_messages_to_prompt_anthropic(self, messages: list[PromptMessage]) -> str: - """ - Format a list of messages into a full prompt for the Anthropic model - - :param messages: List of PromptMessage to combine. - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - if not messages: - return "" - - messages = messages.copy() # don't mutate the original list - if not isinstance(messages[-1], AssistantPromptMessage): - messages.append(AssistantPromptMessage(content="")) - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - # trim off the trailing ' ' that might come from the "Assistant: " - return text.rstrip() - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [anthropic.APIConnectionError, anthropic.APITimeoutError], - InvokeServerUnavailableError: [anthropic.InternalServerError], - InvokeRateLimitError: [anthropic.RateLimitError], - InvokeAuthorizationError: [anthropic.AuthenticationError, anthropic.PermissionDeniedError], - InvokeBadRequestError: [ - anthropic.BadRequestError, - anthropic.NotFoundError, - anthropic.UnprocessableEntityError, - anthropic.APIError, - ], - } diff --git a/api/core/model_runtime/model_providers/azure_ai_studio/__init__.py b/api/core/model_runtime/model_providers/azure_ai_studio/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/azure_ai_studio/_assets/icon_l_en.png 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""" - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - pass diff --git a/api/core/model_runtime/model_providers/azure_ai_studio/azure_ai_studio.yaml b/api/core/model_runtime/model_providers/azure_ai_studio/azure_ai_studio.yaml deleted file mode 100644 index 9e17ba088480db..00000000000000 --- a/api/core/model_runtime/model_providers/azure_ai_studio/azure_ai_studio.yaml +++ /dev/null @@ -1,65 +0,0 @@ -provider: azure_ai_studio -label: - zh_Hans: Azure AI Studio - en_US: Azure AI Studio -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -description: - en_US: Azure AI Studio - zh_Hans: Azure AI Studio -background: "#93c5fd" -help: - title: - en_US: How to deploy customized model on Azure AI Studio - zh_Hans: 如何在Azure AI Studio上的私有化部署的模型 - url: - en_US: https://learn.microsoft.com/en-us/azure/ai-studio/how-to/deploy-models - zh_Hans: https://learn.microsoft.com/zh-cn/azure/ai-studio/how-to/deploy-models -supported_model_types: - - llm - - rerank -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: endpoint - label: - en_US: Azure AI Studio Endpoint - type: text-input - required: true - placeholder: - zh_Hans: 请输入你的Azure AI Studio推理端点 - en_US: 'Enter your API Endpoint, eg: https://example.com' - - variable: api_key - required: true - label: - en_US: API Key - zh_Hans: API Key - type: secret-input - placeholder: - en_US: Enter your Azure AI Studio API Key - zh_Hans: 在此输入您的 Azure AI Studio API Key - show_on: - - variable: __model_type - value: llm - - variable: jwt_token - required: true - label: - en_US: JWT Token - zh_Hans: JWT令牌 - type: secret-input - placeholder: - en_US: Enter your Azure AI Studio JWT Token - zh_Hans: 在此输入您的 Azure AI Studio 推理 API Key - show_on: - - variable: __model_type - value: rerank diff --git a/api/core/model_runtime/model_providers/azure_ai_studio/llm/__init__.py b/api/core/model_runtime/model_providers/azure_ai_studio/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/azure_ai_studio/llm/llm.py b/api/core/model_runtime/model_providers/azure_ai_studio/llm/llm.py deleted file mode 100644 index 516ef8b295ef84..00000000000000 --- a/api/core/model_runtime/model_providers/azure_ai_studio/llm/llm.py +++ /dev/null @@ -1,334 +0,0 @@ -import logging -from collections.abc import Generator -from typing import Any, Optional, Union - -from azure.ai.inference import ChatCompletionsClient -from azure.ai.inference.models import StreamingChatCompletionsUpdate -from azure.core.credentials import AzureKeyCredential -from azure.core.exceptions import ( - ClientAuthenticationError, - DecodeError, - DeserializationError, - HttpResponseError, - ResourceExistsError, - ResourceModifiedError, - ResourceNotFoundError, - ResourceNotModifiedError, - SerializationError, - ServiceRequestError, - ServiceResponseError, -) - -from core.model_runtime.callbacks.base_callback import Callback -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - I18nObject, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -logger = logging.getLogger(__name__) - - -class AzureAIStudioLargeLanguageModel(LargeLanguageModel): - """ - Model class for Azure AI Studio large language model. - """ - - client: Any = None - - from azure.ai.inference.models import StreamingChatCompletionsUpdate - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - - if not self.client: - endpoint = credentials.get("endpoint") - api_key = credentials.get("api_key") - self.client = ChatCompletionsClient(endpoint=endpoint, credential=AzureKeyCredential(api_key)) - - messages = [{"role": msg.role.value, "content": msg.content} for msg in prompt_messages] - - payload = { - "messages": messages, - "max_tokens": model_parameters.get("max_tokens", 4096), - "temperature": model_parameters.get("temperature", 0), - "top_p": model_parameters.get("top_p", 1), - "stream": stream, - } - - if stop: - payload["stop"] = stop - - if tools: - payload["tools"] = [tool.model_dump() for tool in tools] - - try: - response = self.client.complete(**payload) - - if stream: - return self._handle_stream_response(response, model, prompt_messages) - else: - return self._handle_non_stream_response(response, model, prompt_messages, credentials) - except Exception as e: - raise self._transform_invoke_error(e) - - def _handle_stream_response(self, response, model: str, prompt_messages: list[PromptMessage]) -> Generator: - for chunk in response: - if isinstance(chunk, StreamingChatCompletionsUpdate): - if chunk.choices: - delta = chunk.choices[0].delta - if delta.content: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=delta.content, tool_calls=[]), - ), - ) - - def _handle_non_stream_response( - self, response, model: str, prompt_messages: list[PromptMessage], credentials: dict - ) -> LLMResult: - assistant_text = response.choices[0].message.content - assistant_prompt_message = AssistantPromptMessage(content=assistant_text) - usage = self._calc_response_usage( - model, credentials, response.usage.prompt_tokens, response.usage.completion_tokens - ) - result = LLMResult(model=model, prompt_messages=prompt_messages, message=assistant_prompt_message, usage=usage) - - if hasattr(response, "system_fingerprint"): - result.system_fingerprint = response.system_fingerprint - - return result - - def _invoke_result_generator( - self, - model: str, - result: Generator, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - callbacks: Optional[list[Callback]] = None, - ) -> Generator: - """ - Invoke result generator - - :param result: result generator - :return: result generator - """ - callbacks = callbacks or [] - prompt_message = AssistantPromptMessage(content="") - usage = None - system_fingerprint = None - real_model = model - - try: - for chunk in result: - if isinstance(chunk, dict): - content = chunk["choices"][0]["message"]["content"] - usage = chunk["usage"] - chunk = LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=content, tool_calls=[]), - ), - system_fingerprint=chunk.get("system_fingerprint"), - ) - - yield chunk - - self._trigger_new_chunk_callbacks( - chunk=chunk, - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - callbacks=callbacks, - ) - - prompt_message.content += chunk.delta.message.content - real_model = chunk.model - if hasattr(chunk.delta, "usage"): - usage = chunk.delta.usage - - if chunk.system_fingerprint: - system_fingerprint = chunk.system_fingerprint - except Exception as e: - raise self._transform_invoke_error(e) - - self._trigger_after_invoke_callbacks( - model=model, - result=LLMResult( - model=real_model, - prompt_messages=prompt_messages, - message=prompt_message, - usage=usage or LLMUsage.empty_usage(), - system_fingerprint=system_fingerprint, - ), - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - callbacks=callbacks, - ) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - # Implement token counting logic here - # Might need to use a tokenizer specific to the Azure AI Studio model - return 0 - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - endpoint = credentials.get("endpoint") - api_key = credentials.get("api_key") - client = ChatCompletionsClient(endpoint=endpoint, credential=AzureKeyCredential(api_key)) - client.get_model_info() - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [ - ServiceRequestError, - ], - InvokeServerUnavailableError: [ - ServiceResponseError, - ], - InvokeAuthorizationError: [ - ClientAuthenticationError, - ], - InvokeBadRequestError: [ - HttpResponseError, - DecodeError, - ResourceExistsError, - ResourceNotFoundError, - ResourceModifiedError, - ResourceNotModifiedError, - SerializationError, - DeserializationError, - ], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - Used to define customizable model schema - """ - rules = [ - ParameterRule( - name="temperature", - type=ParameterType.FLOAT, - use_template="temperature", - label=I18nObject(zh_Hans="温度", en_US="Temperature"), - ), - ParameterRule( - name="top_p", - type=ParameterType.FLOAT, - use_template="top_p", - label=I18nObject(zh_Hans="Top P", en_US="Top P"), - ), - ParameterRule( - name="max_tokens", - type=ParameterType.INT, - use_template="max_tokens", - min=1, - default=512, - label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"), - ), - ] - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - features=[], - model_properties={}, - parameter_rules=rules, - ) - - return entity diff --git a/api/core/model_runtime/model_providers/azure_ai_studio/rerank/__init__.py b/api/core/model_runtime/model_providers/azure_ai_studio/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/azure_ai_studio/rerank/rerank.py b/api/core/model_runtime/model_providers/azure_ai_studio/rerank/rerank.py deleted file mode 100644 index 6ed7ab277cde02..00000000000000 --- a/api/core/model_runtime/model_providers/azure_ai_studio/rerank/rerank.py +++ /dev/null @@ -1,164 +0,0 @@ -import json -import logging -import os -import ssl -import urllib.request -from typing import Optional - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - -logger = logging.getLogger(__name__) - - -class AzureRerankModel(RerankModel): - """ - Model class for Azure AI Studio rerank model. - """ - - def _allow_self_signed_https(self, allowed): - # bypass the server certificate verification on client side - if allowed and not os.environ.get("PYTHONHTTPSVERIFY", "") and getattr(ssl, "_create_unverified_context", None): - ssl._create_default_https_context = ssl._create_unverified_context - - def _azure_rerank(self, query_input: str, docs: list[str], endpoint: str, api_key: str): - # self._allow_self_signed_https(True) # Enable if using self-signed certificate - - data = {"inputs": query_input, "docs": docs} - - body = json.dumps(data).encode("utf-8") - headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"} - - req = urllib.request.Request(endpoint, body, headers) - - try: - with urllib.request.urlopen(req) as response: - result = response.read() - return json.loads(result) - except urllib.error.HTTPError as error: - logger.error(f"The request failed with status code: {error.code}") - logger.error(error.info()) - logger.error(error.read().decode("utf8", "ignore")) - raise - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n - :param user: unique user id - :return: rerank result - """ - try: - if len(docs) == 0: - return RerankResult(model=model, docs=[]) - - endpoint = credentials.get("endpoint") - api_key = credentials.get("jwt_token") - - if not endpoint or not api_key: - raise ValueError("Azure endpoint and API key must be provided in credentials") - - result = self._azure_rerank(query, docs, endpoint, api_key) - logger.info(f"Azure rerank result: {result}") - - rerank_documents = [] - for idx, (doc, score_dict) in enumerate(zip(docs, result)): - score = score_dict["score"] - rerank_document = RerankDocument(index=idx, text=doc, score=score) - - if score_threshold is None or score >= score_threshold: - rerank_documents.append(rerank_document) - - rerank_documents.sort(key=lambda x: x.score, reverse=True) - - if top_n: - rerank_documents = rerank_documents[:top_n] - - return RerankResult(model=model, docs=rerank_documents) - - except Exception as e: - logger.exception(f"Exception in Azure rerank: {e}") - raise - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke( - model=model, - credentials=credentials, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [urllib.error.URLError], - InvokeServerUnavailableError: [urllib.error.HTTPError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError, json.JSONDecodeError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.RERANK, - model_properties={}, - parameter_rules=[], - ) - - return entity diff --git a/api/core/model_runtime/model_providers/azure_openai/__init__.py b/api/core/model_runtime/model_providers/azure_openai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/azure_openai/_assets/icon_l_en.png b/api/core/model_runtime/model_providers/azure_openai/_assets/icon_l_en.png deleted file mode 100644 index 0791a67911ec40247c40bf13a2ba2d2512e013b9..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 5007 zcmY+IWmFVEyMUK2>5%RYsinI^8Wj*05KuyzrC}A8js*lMDFFciY3bMnq@+8f!KHKQ zy7=95&$-`o&dfXS%)IZ9`8DT>Hqg@`#HYmv004wqnyN+s0Gi$7S_l{Wapv>_cs~X_ zcTF=d0Dy|)-$2tcVn2G^MDsGzPzF>C({Dc}nD$D#N&rB00>SMYEC7IU^UnPUiWfcOnls2Rs=9U@?0G#O8)s!SCirDc|F0cSgHCT{^4{|&SnBiSm)LK5*NOtPk#W#|6bZ7*s1W?CZf$v@6n_=WyK zO+X#uY;A2V#3_V62ZzJ0b*wRKLPA0i>2O@T$Bt0p5Yj&EM{LpA5(ys*dob0R>8Pox zd~iZk%)P|5*gRK&DViM z9nFI^?TU_Br~3S^i;JO4`@I(mM+ktWl>a-!;CFy~jmH!_^~>EgJ?42<(0w_`-0{ki zz~^HD*GMCkZLy?nzPzv=fX+Ot@*vH_^RFhgn;5mN34-brvc6sW-NaYBcCot~e`6$9 zc73H+*RBVWPbfgaxg<$6X^A+Vt2L1VR{-o+m3zCAPgUOzqnE5T*w)&ASx~A1_J?L* zvfxM2eYaa{VS^6Tz%5BSIh5O`IU^Wi>=T0DLeQ@6Xd&L+xZl^q9!ldt8i=1YLswq{ zgR=sh>CVs_;WufLl7&Ld2w7@TopQn}z&b(Z#x-Jln3eho;dqP(`m!=%S%_$}WqQV` zTGmlRm_fQh9%EIBRz-4N1gK{$*;&A-g+Um+VWs5VEz+iu=g>@8|(eqC(F%Mi~&0DX7@zz)bL!e*jC zii-n()L58suPVM>8JUHlD2UW}X@$!XGElZao-(}LL8I;TjsABl7I=^tBX-pgGt zFwKBBC->iHNIS4dnZ6ga9-$}Li;uiWMo&`oCt}!Y9E=dmQ#r*A$eyVeXshaaR8Ur%l@ertxEitY=oa~5ktvn}nYjlG@-h#$){Vdx6#jx=3hK4IWOq*$Jk}Q~M zl1Qto*xXp2&sve|$$3Ic_v@JNDA&g&eyez#a(j_IpsZDoyVN9Y#v9c5(3qWG>+cPu zC2U+msV>;bxL=+8mbSnX$yZ4gR3VPW^WHgYh|NOGYwR)s6Gn!uVlxDR<{S8S?DP3M zFKEJIX7SIlh#bS2!lErP@xF`%x#U}0l-3aawP%f2Sy|UmX1-u>HQ-{1 zPEsLn8}1wv7d`xnfsB8HB|4@Ytgh?tKk75ubAd_K!nZvn)lz;gu;@FGaCchzCX?+< z#z~=m!Tyia78MiTYhbAjV!tsu-1NK+-rt8^r!syt3hq^q745inztj6lMT7V2`5i^O zldi6W;U(xZD$4IS)UaT&0=m=vH#Iknvf+xIUT^>zGd1;0Jjv_R{BF-wsEBx+7}HYV z2Oba%Ge_GzNdDoZzZU7>k+zw%BoA?6tu(%?=E1pI4}#Fnm)z1E@4zC|woK3Ie0-u7_3(lL+pBYN6OCj@v> z{@ih)9&@_7T;2^iJ7)|F_ydOXri6*^idb;tNPW|1u3Q{Fro}rw=gJ+m@eH>1e-Y;i z$(0SsI(IdZvLdzGun&We2Ozqnm5U?OE(8%M7TH-{Q`veg^=RhX|vEnJw2+0VamSQr{j6qg{M5*99(Zo$e+=m4VWcg z3*1!L#n)}+i<>{SlPO`uWk`jv8dGbhCbXw=9yzu&(@tkQ{H{>DDa2F|0MoGxMaCa6 zzn)O0=3*uuYa{_hHy9XH@(6+k&4q3@uky=r^8M}1rpdMQv6Qln{b9Z-aHr-D|HC^Y zbblY89IVz;@sd`ZJ0;74_QK1sH`fciZSU+suN{`*SZb7Y?OC>O7=&|$3MZyy1N8Iy zSsg2mW>nCWp|E$csWtIM(G#OnBy)?I&C9Bqr0x$eJ?=IBolI|E1L6OscOuB~T@ZSkPZB z8$Yo4G4*QH*>K*u-Z*jYTbfy+WX1|r0?PxN;13pE6KsYjS^}2x*M#G(4dpOm80w|P z))zG&pZxu$2Z(K{^9{N8sE`i#pxYt|R{W^l8$m9O9{#i`?s35MyR#1@ek=yfeZ1 zQku)vDJV?k=jW%}AJ?Jh7uXviK2>qQV%_GCbMgh+MJ{Pl;L8dJRWU}D+`q4grNC6WGmI=C$n{~>+BcZJxd-P)Zf!dU}8N6S}R zzmd*&eRkwK#wCj!0Dw8>r**JaLsx#`rI7p9%PcdA8q|`yUby)A%%h*eaMer=qQb=TiR)8 zkr{6kTiTCn6P4Sdi7zVweRr|W>1n1@{2^=No-g!@D;ne53kd*ol!oHQ2b{91I1gt&JUYWZ*I~S z2hy+?h{TY98?^W*uQaE6vTZ$esJ`#7k!<1*QEhau!)*mJWor|#yYt&Mg;wuin4HK4 z=%?b(r5q#I8msS(WO!VB_5HgMM4=V}jeV>3qLxTn-7gpARL0`=hTtB>{YckaC`fV1 z@J=ZzKbZCiokf?n*M20&$j9{RFE(kl2=x}l*{ama!~UIE&3l!erDX{RA;&lq;g(Xl{l64F04bElvPH9F3%ZM>h|{zQV!D~6W99PCITKmyK# zUdxAK&_oZp`CeNMmSW-w$~*e_x7ye8WG3ef>f8#K(yfeEXUwt~_}N-69cczx@o^3r zL%7TvG8?$xF%9{rX=s|4Ogilx)G{7tvXP6xu9YO2^LZyl&bof?KdHQA!YD9Mkj7;r z>N1U6OI;PxG4%KLEpDq$z?2?K*)jz7a;{rz4p<1gj~Yd)f_n@32DL4$s3Y!EE;dx-Q{VC&3UeqM$*L_=O$I8E==Nz1QQ~kd&aiY$ zq(f^QM#p>?A73^rQm;R%URp_lzvl3jZ%L4YZmI3H+GOuZy8k+7ASNFCetuP|`C~{-b)5}RxUaIUmTP&ZJn!I-U>?=hj$z66sbmBu;MtW?u!A^>aIe`&v|9sl3LYU!t;H~1 zqquCc)apHbU#18^4VmZrymC?N=NhP{+eFory`&qw@QkVUG6=vmFY9> zz@PMgV2BkUMb?@8cn?wxeWfuDP4e&{aCHsmM9J6kHL<&nS)P6)qz~XuQx)@o`n*7S zZ{3fL4&1MA7gZS?hM}Y(z~G@X%#6l^n#&s|2;nqpQY^>2r^zOVy)rd8lqjbgLE1b& zQ8DG}Fd*2CG6)w&HjK^`f-WyQ`a|csGWf2KK5eQ8dbE*zYL=nVG>G2i)7WMIdJ#>~ z>}3=COO901F$Zb4+ST!=2}XX1X(uQ((u#wn!V}nnIbSNMe4-c9C{Kq4JvgC5A0z#p zGd=d2xfQxfHGVraL@IL^A!efK%s>_xZD*z7=Mmf;$j;pMM`vu2!e(r+K%mIHudLal ze^OW(GHuaQ7{AL{Gkni+e&xl!K|Zv+_~bX!`&rOAFGUurFwu15ZsycaVH$9LgGlti zmYVENdtgM}A+1Zt4^>3p)o-1!$|;~MTF1-Gt*r}IAwq5o%u9X_V{~|H+0S)NS VjvA=y{3p`@T55W#70TA3{{wPWtZe`Q diff --git a/api/core/model_runtime/model_providers/azure_openai/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/azure_openai/_assets/icon_s_en.svg deleted file mode 100644 index df1f54f36ede83..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/_assets/icon_s_en.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - diff --git a/api/core/model_runtime/model_providers/azure_openai/_common.py b/api/core/model_runtime/model_providers/azure_openai/_common.py deleted file mode 100644 index 32a0269af49314..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/_common.py +++ /dev/null @@ -1,42 +0,0 @@ -import openai -from httpx import Timeout - -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.model_providers.azure_openai._constant import AZURE_OPENAI_API_VERSION - - -class _CommonAzureOpenAI: - @staticmethod - def _to_credential_kwargs(credentials: dict) -> dict: - api_version = credentials.get("openai_api_version", AZURE_OPENAI_API_VERSION) - credentials_kwargs = { - "api_key": credentials["openai_api_key"], - "azure_endpoint": credentials["openai_api_base"], - "api_version": api_version, - "timeout": Timeout(315.0, read=300.0, write=10.0, connect=5.0), - "max_retries": 1, - } - - return credentials_kwargs - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [openai.APIConnectionError, openai.APITimeoutError], - InvokeServerUnavailableError: [openai.InternalServerError], - InvokeRateLimitError: [openai.RateLimitError], - InvokeAuthorizationError: [openai.AuthenticationError, openai.PermissionDeniedError], - InvokeBadRequestError: [ - openai.BadRequestError, - openai.NotFoundError, - openai.UnprocessableEntityError, - openai.APIError, - ], - } diff --git a/api/core/model_runtime/model_providers/azure_openai/_constant.py b/api/core/model_runtime/model_providers/azure_openai/_constant.py deleted file mode 100644 index 0dada70cc5b7fa..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/_constant.py +++ /dev/null @@ -1,1262 +0,0 @@ -from pydantic import BaseModel - -from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE -from core.model_runtime.entities.llm_entities import LLMMode -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - DefaultParameterName, - FetchFrom, - I18nObject, - ModelFeature, - ModelPropertyKey, - ModelType, - ParameterRule, - PriceConfig, -) - -AZURE_OPENAI_API_VERSION = "2024-02-15-preview" - -AZURE_DEFAULT_PARAM_SEED_HELP = I18nObject( - zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，" - "您应该参考 system_fingerprint 响应参数来监视变化。", - en_US="If specified, model will make a best effort to sample deterministically," - " such that repeated requests with the same seed and parameters should return the same result." - " Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter" - " to monitor changes in the backend.", -) - - -def _get_max_tokens(default: int, min_val: int, max_val: int) -> ParameterRule: - rule = ParameterRule( - name="max_tokens", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.MAX_TOKENS], - ) - rule.default = default - rule.min = min_val - rule.max = max_val - return rule - - -class AzureBaseModel(BaseModel): - base_model_name: str - entity: AIModelEntity - - -LLM_BASE_MODELS = [ - AzureBaseModel( - base_model_name="gpt-35-turbo", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 16385, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.0005, - output=0.0015, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-35-turbo-16k", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 16385, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=16385), - ], - pricing=PriceConfig( - input=0.003, - output=0.004, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-35-turbo-0125", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 16385, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.0005, - output=0.0015, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 8192, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=8192), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.03, - output=0.06, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4-32k", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 32768, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=32768), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.06, - output=0.12, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4-0125-preview", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.01, - output=0.03, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4-1106-preview", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.01, - output=0.03, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4o-mini", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.VISION, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=16384), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.150, - output=0.600, - unit=0.000001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4o-mini-2024-07-18", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.VISION, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=16384), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object", "json_schema"], - ), - ParameterRule( - name="json_schema", - label=I18nObject(en_US="JSON Schema"), - type="text", - help=I18nObject( - zh_Hans="设置返回的json schema，llm将按照它返回", - en_US="Set a response json schema will ensure LLM to adhere it.", - ), - required=False, - ), - ], - pricing=PriceConfig( - input=0.150, - output=0.600, - unit=0.000001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4o", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.VISION, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=5.00, - output=15.00, - unit=0.000001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4o-2024-05-13", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.VISION, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=5.00, - output=15.00, - unit=0.000001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4o-2024-08-06", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.VISION, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object", "json_schema"], - ), - ParameterRule( - name="json_schema", - label=I18nObject(en_US="JSON Schema"), - type="text", - help=I18nObject( - zh_Hans="设置返回的json schema，llm将按照它返回", - en_US="Set a response json schema will ensure LLM to adhere it.", - ), - required=False, - ), - ], - pricing=PriceConfig( - input=5.00, - output=15.00, - unit=0.000001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4-turbo", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.VISION, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.01, - output=0.03, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4-turbo-2024-04-09", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ - ModelFeature.AGENT_THOUGHT, - ModelFeature.VISION, - ModelFeature.MULTI_TOOL_CALL, - ModelFeature.STREAM_TOOL_CALL, - ], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.01, - output=0.03, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-4-vision-preview", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - features=[ModelFeature.VISION], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.CHAT.value, - ModelPropertyKey.CONTEXT_SIZE: 128000, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ParameterRule( - name="seed", - label=I18nObject(zh_Hans="种子", en_US="Seed"), - type="int", - help=AZURE_DEFAULT_PARAM_SEED_HELP, - required=False, - precision=2, - min=0, - max=1, - ), - ParameterRule( - name="response_format", - label=I18nObject(zh_Hans="回复格式", en_US="response_format"), - type="string", - help=I18nObject( - zh_Hans="指定模型必须输出的格式", en_US="specifying the format that the model must output" - ), - required=False, - options=["text", "json_object"], - ), - ], - pricing=PriceConfig( - input=0.01, - output=0.03, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="gpt-35-turbo-instruct", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.COMPLETION.value, - ModelPropertyKey.CONTEXT_SIZE: 4096, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ], - pricing=PriceConfig( - input=0.0015, - output=0.002, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="text-davinci-003", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject( - en_US="fake-deployment-name-label", - ), - model_type=ModelType.LLM, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: LLMMode.COMPLETION.value, - ModelPropertyKey.CONTEXT_SIZE: 4096, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TEMPERATURE], - ), - ParameterRule( - name="top_p", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.TOP_P], - ), - ParameterRule( - name="presence_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.PRESENCE_PENALTY], - ), - ParameterRule( - name="frequency_penalty", - **PARAMETER_RULE_TEMPLATE[DefaultParameterName.FREQUENCY_PENALTY], - ), - _get_max_tokens(default=512, min_val=1, max_val=4096), - ], - pricing=PriceConfig( - input=0.02, - output=0.02, - unit=0.001, - currency="USD", - ), - ), - ), -] - -EMBEDDING_BASE_MODELS = [ - AzureBaseModel( - base_model_name="text-embedding-ada-002", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject(en_US="fake-deployment-name-label"), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TEXT_EMBEDDING, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: 8097, - ModelPropertyKey.MAX_CHUNKS: 32, - }, - pricing=PriceConfig( - input=0.0001, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="text-embedding-3-small", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject(en_US="fake-deployment-name-label"), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TEXT_EMBEDDING, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: 8191, - ModelPropertyKey.MAX_CHUNKS: 32, - }, - pricing=PriceConfig( - input=0.00002, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="text-embedding-3-large", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject(en_US="fake-deployment-name-label"), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TEXT_EMBEDDING, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: 8191, - ModelPropertyKey.MAX_CHUNKS: 32, - }, - pricing=PriceConfig( - input=0.00013, - unit=0.001, - currency="USD", - ), - ), - ), -] -SPEECH2TEXT_BASE_MODELS = [ - AzureBaseModel( - base_model_name="whisper-1", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject(en_US="fake-deployment-name-label"), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.SPEECH2TEXT, - model_properties={ - ModelPropertyKey.FILE_UPLOAD_LIMIT: 25, - ModelPropertyKey.SUPPORTED_FILE_EXTENSIONS: "flac,mp3,mp4,mpeg,mpga,m4a,ogg,wav,webm", - }, - ), - ) -] -TTS_BASE_MODELS = [ - AzureBaseModel( - base_model_name="tts-1", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject(en_US="fake-deployment-name-label"), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TTS, - model_properties={ - ModelPropertyKey.DEFAULT_VOICE: "alloy", - ModelPropertyKey.VOICES: [ - { - "mode": "alloy", - "name": "Alloy", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "echo", - "name": "Echo", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "fable", - "name": "Fable", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "onyx", - "name": "Onyx", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "nova", - "name": "Nova", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "shimmer", - "name": "Shimmer", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - ], - ModelPropertyKey.WORD_LIMIT: 120, - ModelPropertyKey.AUDIO_TYPE: "mp3", - ModelPropertyKey.MAX_WORKERS: 5, - }, - pricing=PriceConfig( - input=0.015, - unit=0.001, - currency="USD", - ), - ), - ), - AzureBaseModel( - base_model_name="tts-1-hd", - entity=AIModelEntity( - model="fake-deployment-name", - label=I18nObject(en_US="fake-deployment-name-label"), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TTS, - model_properties={ - ModelPropertyKey.DEFAULT_VOICE: "alloy", - ModelPropertyKey.VOICES: [ - { - "mode": "alloy", - "name": "Alloy", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "echo", - "name": "Echo", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "fable", - "name": "Fable", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "onyx", - "name": "Onyx", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "nova", - "name": "Nova", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - { - "mode": "shimmer", - "name": "Shimmer", - "language": ["zh-Hans", "en-US", "de-DE", "fr-FR", "es-ES", "it-IT", "th-TH", "id-ID"], - }, - ], - ModelPropertyKey.WORD_LIMIT: 120, - ModelPropertyKey.AUDIO_TYPE: "mp3", - ModelPropertyKey.MAX_WORKERS: 5, - }, - pricing=PriceConfig( - input=0.03, - unit=0.001, - currency="USD", - ), - ), - ), -] diff --git a/api/core/model_runtime/model_providers/azure_openai/azure_openai.py b/api/core/model_runtime/model_providers/azure_openai/azure_openai.py deleted file mode 100644 index 2e3c6aab0588ec..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/azure_openai.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class AzureOpenAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/azure_openai/azure_openai.yaml b/api/core/model_runtime/model_providers/azure_openai/azure_openai.yaml deleted file mode 100644 index 867f9fec420008..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/azure_openai.yaml +++ /dev/null @@ -1,227 +0,0 @@ -provider: azure_openai -label: - en_US: Azure OpenAI Service Model -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.png -background: "#E3F0FF" -help: - title: - en_US: Get your API key from Azure - zh_Hans: 从 Azure 获取 API Key - url: - en_US: https://azure.microsoft.com/en-us/products/ai-services/openai-service -supported_model_types: - - llm - - text-embedding - - speech2text - - tts -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Deployment Name - zh_Hans: 部署名称 - placeholder: - en_US: Enter your Deployment Name here, matching the Azure deployment name. - zh_Hans: 在此输入您的部署名称，与 Azure 部署名称匹配。 - credential_form_schemas: - - variable: openai_api_base - label: - en_US: API Endpoint URL - zh_Hans: API 域名 - type: text-input - required: true - placeholder: - zh_Hans: '在此输入您的 API 域名，如：https://example.com/xxx' - en_US: 'Enter your API Endpoint, eg: https://example.com/xxx' - - variable: openai_api_key - label: - en_US: API Key - zh_Hans: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API key here - - variable: openai_api_version - label: - zh_Hans: API 版本 - en_US: API Version - type: select - required: true - options: - - label: - en_US: 2024-08-01-preview - value: 2024-08-01-preview - - label: - en_US: 2024-07-01-preview - value: 2024-07-01-preview - - label: - en_US: 2024-05-01-preview - value: 2024-05-01-preview - - label: - en_US: 2024-04-01-preview - value: 2024-04-01-preview - - label: - en_US: 2024-03-01-preview - value: 2024-03-01-preview - - label: - en_US: 2024-02-15-preview - value: 2024-02-15-preview - - label: - en_US: 2023-12-01-preview - value: 2023-12-01-preview - - label: - en_US: '2024-02-01' - value: '2024-02-01' - - label: - en_US: '2024-06-01' - value: '2024-06-01' - placeholder: - zh_Hans: 在此选择您的 API 版本 - en_US: Select your API Version here - - variable: base_model_name - label: - en_US: Base Model - zh_Hans: 基础模型 - type: select - required: true - options: - - label: - en_US: gpt-35-turbo - value: gpt-35-turbo - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-35-turbo-0125 - value: gpt-35-turbo-0125 - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-35-turbo-16k - value: gpt-35-turbo-16k - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4 - value: gpt-4 - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4-32k - value: gpt-4-32k - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4o-mini - value: gpt-4o-mini - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4o-mini-2024-07-18 - value: gpt-4o-mini-2024-07-18 - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4o - value: gpt-4o - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4o-2024-05-13 - value: gpt-4o-2024-05-13 - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4o-2024-08-06 - value: gpt-4o-2024-08-06 - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4-turbo - value: gpt-4-turbo - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4-turbo-2024-04-09 - value: gpt-4-turbo-2024-04-09 - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4-0125-preview - value: gpt-4-0125-preview - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4-1106-preview - value: gpt-4-1106-preview - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-4-vision-preview - value: gpt-4-vision-preview - show_on: - - variable: __model_type - value: llm - - label: - en_US: gpt-35-turbo-instruct - value: gpt-35-turbo-instruct - show_on: - - variable: __model_type - value: llm - - label: - en_US: text-embedding-ada-002 - value: text-embedding-ada-002 - show_on: - - variable: __model_type - value: text-embedding - - label: - en_US: text-embedding-3-small - value: text-embedding-3-small - show_on: - - variable: __model_type - value: text-embedding - - label: - en_US: text-embedding-3-large - value: text-embedding-3-large - show_on: - - variable: __model_type - value: text-embedding - - label: - en_US: whisper-1 - value: whisper-1 - show_on: - - variable: __model_type - value: speech2text - - label: - en_US: tts-1 - value: tts-1 - show_on: - - variable: __model_type - value: tts - - label: - en_US: tts-1-hd - value: tts-1-hd - show_on: - - variable: __model_type - value: tts - placeholder: - zh_Hans: 在此输入您的模型版本 - en_US: Enter your model version diff --git a/api/core/model_runtime/model_providers/azure_openai/llm/__init__.py b/api/core/model_runtime/model_providers/azure_openai/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/azure_openai/llm/llm.py b/api/core/model_runtime/model_providers/azure_openai/llm/llm.py deleted file mode 100644 index f0033ea051b501..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/llm/llm.py +++ /dev/null @@ -1,665 +0,0 @@ -import copy -import json -import logging -from collections.abc import Generator, Sequence -from typing import Optional, Union, cast - -import tiktoken -from openai import AzureOpenAI, Stream -from openai.types import Completion -from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessageToolCall -from openai.types.chat.chat_completion_chunk import ChoiceDeltaToolCall - -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageFunction, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity, ModelPropertyKey -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.azure_openai._common import _CommonAzureOpenAI -from core.model_runtime.model_providers.azure_openai._constant import LLM_BASE_MODELS -from core.model_runtime.utils import helper - -logger = logging.getLogger(__name__) - - -class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - base_model_name = credentials.get("base_model_name") - if not base_model_name: - raise ValueError("Base Model Name is required") - ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model) - - if ai_model_entity and ai_model_entity.entity.model_properties.get(ModelPropertyKey.MODE) == LLMMode.CHAT.value: - # chat model - return self._chat_generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - else: - # text completion model - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - stop=stop, - stream=stream, - user=user, - ) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - base_model_name = credentials.get("base_model_name") - if not base_model_name: - raise ValueError("Base Model Name is required") - model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model) - if not model_entity: - raise ValueError(f"Base Model Name {base_model_name} is invalid") - model_mode = model_entity.entity.model_properties.get(ModelPropertyKey.MODE) - - if model_mode == LLMMode.CHAT.value: - # chat model - return self._num_tokens_from_messages(credentials, prompt_messages, tools) - else: - # text completion model, do not support tool calling - content = prompt_messages[0].content - assert isinstance(content, str) - return self._num_tokens_from_string(credentials, content) - - def validate_credentials(self, model: str, credentials: dict) -> None: - if "openai_api_base" not in credentials: - raise CredentialsValidateFailedError("Azure OpenAI API Base Endpoint is required") - - if "openai_api_key" not in credentials: - raise CredentialsValidateFailedError("Azure OpenAI API key is required") - - if "base_model_name" not in credentials: - raise CredentialsValidateFailedError("Base Model Name is required") - - base_model_name = credentials.get("base_model_name") - if not base_model_name: - raise CredentialsValidateFailedError("Base Model Name is required") - ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model) - - if not ai_model_entity: - raise CredentialsValidateFailedError(f'Base Model Name {credentials["base_model_name"]} is invalid') - - try: - client = AzureOpenAI(**self._to_credential_kwargs(credentials)) - - if ai_model_entity.entity.model_properties.get(ModelPropertyKey.MODE) == LLMMode.CHAT.value: - # chat model - client.chat.completions.create( - messages=[{"role": "user", "content": "ping"}], - model=model, - temperature=0, - max_tokens=20, - stream=False, - ) - else: - # text completion model - client.completions.create( - prompt="ping", - model=model, - temperature=0, - max_tokens=20, - stream=False, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]: - base_model_name = credentials.get("base_model_name") - if not base_model_name: - raise ValueError("Base Model Name is required") - ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model) - return ai_model_entity.entity if ai_model_entity else None - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - client = AzureOpenAI(**self._to_credential_kwargs(credentials)) - - extra_model_kwargs = {} - - if stop: - extra_model_kwargs["stop"] = stop - - if user: - extra_model_kwargs["user"] = user - - # text completion model - response = client.completions.create( - prompt=prompt_messages[0].content, model=model, stream=stream, **model_parameters, **extra_model_kwargs - ) - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_response( - self, model: str, credentials: dict, response: Completion, prompt_messages: list[PromptMessage] - ): - assistant_text = response.choices[0].text - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_text) - - # calculate num tokens - if response.usage: - # transform usage - prompt_tokens = response.usage.prompt_tokens - completion_tokens = response.usage.completion_tokens - else: - # calculate num tokens - content = prompt_messages[0].content - assert isinstance(content, str) - prompt_tokens = self._num_tokens_from_string(credentials, content) - completion_tokens = self._num_tokens_from_string(credentials, assistant_text) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=response.model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - system_fingerprint=response.system_fingerprint, - ) - - return result - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: Stream[Completion], prompt_messages: list[PromptMessage] - ) -> Generator: - full_text = "" - for chunk in response: - if len(chunk.choices) == 0: - continue - - delta = chunk.choices[0] - - if delta.finish_reason is None and (delta.text is None or delta.text == ""): - continue - - # transform assistant message to prompt message - text = delta.text or "" - assistant_prompt_message = AssistantPromptMessage(content=text) - - full_text += text - - if delta.finish_reason is not None: - # calculate num tokens - if chunk.usage: - # transform usage - prompt_tokens = chunk.usage.prompt_tokens - completion_tokens = chunk.usage.completion_tokens - else: - # calculate num tokens - content = prompt_messages[0].content - assert isinstance(content, str) - prompt_tokens = self._num_tokens_from_string(credentials, content) - completion_tokens = self._num_tokens_from_string(credentials, full_text) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - usage=usage, - ), - ) - else: - yield LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - ), - ) - - def _chat_generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - client = AzureOpenAI(**self._to_credential_kwargs(credentials)) - - response_format = model_parameters.get("response_format") - if response_format: - if response_format == "json_schema": - json_schema = model_parameters.get("json_schema") - if not json_schema: - raise ValueError("Must define JSON Schema when the response format is json_schema") - try: - schema = json.loads(json_schema) - except: - raise ValueError(f"not correct json_schema format: {json_schema}") - model_parameters.pop("json_schema") - model_parameters["response_format"] = {"type": "json_schema", "json_schema": schema} - else: - model_parameters["response_format"] = {"type": response_format} - - extra_model_kwargs = {} - - if tools: - extra_model_kwargs["tools"] = [helper.dump_model(PromptMessageFunction(function=tool)) for tool in tools] - # extra_model_kwargs['functions'] = [{ - # "name": tool.name, - # "description": tool.description, - # "parameters": tool.parameters - # } for tool in tools] - - if stop: - extra_model_kwargs["stop"] = stop - - if user: - extra_model_kwargs["user"] = user - - # chat model - messages = [self._convert_prompt_message_to_dict(m) for m in prompt_messages] - response = client.chat.completions.create( - messages=messages, - model=model, - stream=stream, - **model_parameters, - **extra_model_kwargs, - ) - - if stream: - return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages, tools) - - return self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools) - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - response: ChatCompletion, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ): - assistant_message = response.choices[0].message - assistant_message_tool_calls = assistant_message.tool_calls - - # extract tool calls from response - tool_calls = [] - self._update_tool_calls(tool_calls=tool_calls, tool_calls_response=assistant_message_tool_calls) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_message.content, tool_calls=tool_calls) - - # calculate num tokens - if response.usage: - # transform usage - prompt_tokens = response.usage.prompt_tokens - completion_tokens = response.usage.completion_tokens - else: - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(credentials, prompt_messages, tools) - completion_tokens = self._num_tokens_from_messages(credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=response.model or model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - system_fingerprint=response.system_fingerprint, - ) - - return result - - def _handle_chat_generate_stream_response( - self, - model: str, - credentials: dict, - response: Stream[ChatCompletionChunk], - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ): - index = 0 - full_assistant_content = "" - real_model = model - system_fingerprint = None - completion = "" - tool_calls = [] - for chunk in response: - if len(chunk.choices) == 0: - continue - - delta = chunk.choices[0] - # NOTE: For fix https://github.com/langgenius/dify/issues/5790 - if delta.delta is None: - continue - - # extract tool calls from response - self._update_tool_calls(tool_calls=tool_calls, tool_calls_response=delta.delta.tool_calls) - - # Handling exceptions when content filters' streaming mode is set to asynchronous modified filter - if delta.finish_reason is None and not delta.delta.content: - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=delta.delta.content or "", tool_calls=tool_calls) - - full_assistant_content += delta.delta.content or "" - - real_model = chunk.model - system_fingerprint = chunk.system_fingerprint - completion += delta.delta.content or "" - - yield LLMResultChunk( - model=real_model, - prompt_messages=prompt_messages, - system_fingerprint=system_fingerprint, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - ), - ) - - index += 1 - - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(credentials, prompt_messages, tools) - - full_assistant_prompt_message = AssistantPromptMessage(content=completion) - completion_tokens = self._num_tokens_from_messages(credentials, [full_assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=real_model, - prompt_messages=prompt_messages, - system_fingerprint=system_fingerprint, - delta=LLMResultChunkDelta( - index=index, message=AssistantPromptMessage(content=""), finish_reason="stop", usage=usage - ), - ) - - @staticmethod - def _update_tool_calls( - tool_calls: list[AssistantPromptMessage.ToolCall], - tool_calls_response: Optional[Sequence[ChatCompletionMessageToolCall | ChoiceDeltaToolCall]], - ) -> None: - if tool_calls_response: - for response_tool_call in tool_calls_response: - if isinstance(response_tool_call, ChatCompletionMessageToolCall): - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.function.name, arguments=response_tool_call.function.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call.id, type=response_tool_call.type, function=function - ) - tool_calls.append(tool_call) - elif isinstance(response_tool_call, ChoiceDeltaToolCall): - index = response_tool_call.index - if index < len(tool_calls): - tool_calls[index].id = response_tool_call.id or tool_calls[index].id - tool_calls[index].type = response_tool_call.type or tool_calls[index].type - if response_tool_call.function: - tool_calls[index].function.name = ( - response_tool_call.function.name or tool_calls[index].function.name - ) - tool_calls[index].function.arguments += response_tool_call.function.arguments or "" - else: - assert response_tool_call.id is not None - assert response_tool_call.type is not None - assert response_tool_call.function is not None - assert response_tool_call.function.name is not None - assert response_tool_call.function.arguments is not None - - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.function.name, arguments=response_tool_call.function.arguments - ) - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call.id, type=response_tool_call.type, function=function - ) - tool_calls.append(tool_call) - - @staticmethod - def _convert_prompt_message_to_dict(message: PromptMessage): - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - assert message.content is not None - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": {"url": message_content.data, "detail": message_content.detail.value}, - } - sub_messages.append(sub_message_dict) - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - # message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls: - message_dict["tool_calls"] = [helper.dump_model(tool_call) for tool_call in message.tool_calls] - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = { - "role": "tool", - "name": message.name, - "content": message.content, - "tool_call_id": message.tool_call_id, - } - else: - raise ValueError(f"Got unknown type {message}") - - if message.name: - message_dict["name"] = message.name - - return message_dict - - def _num_tokens_from_string( - self, credentials: dict, text: str, tools: Optional[list[PromptMessageTool]] = None - ) -> int: - try: - encoding = tiktoken.encoding_for_model(credentials["base_model_name"]) - except KeyError: - encoding = tiktoken.get_encoding("cl100k_base") - - num_tokens = len(encoding.encode(text)) - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - def _num_tokens_from_messages( - self, credentials: dict, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None - ) -> int: - """Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package. - - Official documentation: https://github.com/openai/openai-cookbook/blob/ - main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb""" - model = credentials["base_model_name"] - try: - encoding = tiktoken.encoding_for_model(model) - except KeyError: - logger.warning("Warning: model not found. Using cl100k_base encoding.") - model = "cl100k_base" - encoding = tiktoken.get_encoding(model) - - if model.startswith("gpt-35-turbo-0301"): - # every message follows {role/name}\n{content}\n - tokens_per_message = 4 - # if there's a name, the role is omitted - tokens_per_name = -1 - elif model.startswith("gpt-35-turbo") or model.startswith("gpt-4"): - tokens_per_message = 3 - tokens_per_name = 1 - else: - raise NotImplementedError( - f"get_num_tokens_from_messages() is not presently implemented " - f"for model {model}." - "See https://github.com/openai/openai-python/blob/main/chatml.md for " - "information on how messages are converted to tokens." - ) - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - # Cast str(value) in case the message value is not a string - # This occurs with function messages - # TODO: The current token calculation method for the image type is not implemented, - # which need to download the image and then get the resolution for calculation, - # and will increase the request delay - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - assert isinstance(tool_call, dict) - for t_key, t_value in tool_call.items(): - num_tokens += len(encoding.encode(t_key)) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += len(encoding.encode(f_key)) - num_tokens += len(encoding.encode(f_value)) - else: - num_tokens += len(encoding.encode(t_key)) - num_tokens += len(encoding.encode(t_value)) - else: - num_tokens += len(encoding.encode(str(value))) - - if key == "name": - num_tokens += tokens_per_name - - # every reply is primed with assistant - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - @staticmethod - def _num_tokens_for_tools(encoding: tiktoken.Encoding, tools: list[PromptMessageTool]) -> int: - num_tokens = 0 - for tool in tools: - num_tokens += len(encoding.encode("type")) - num_tokens += len(encoding.encode("function")) - - # calculate num tokens for function object - num_tokens += len(encoding.encode("name")) - num_tokens += len(encoding.encode(tool.name)) - num_tokens += len(encoding.encode("description")) - num_tokens += len(encoding.encode(tool.description)) - parameters = tool.parameters - num_tokens += len(encoding.encode("parameters")) - if "title" in parameters: - num_tokens += len(encoding.encode("title")) - num_tokens += len(encoding.encode(parameters["title"])) - num_tokens += len(encoding.encode("type")) - num_tokens += len(encoding.encode(parameters["type"])) - if "properties" in parameters: - num_tokens += len(encoding.encode("properties")) - for key, value in parameters["properties"].items(): - num_tokens += len(encoding.encode(key)) - for field_key, field_value in value.items(): - num_tokens += len(encoding.encode(field_key)) - if field_key == "enum": - for enum_field in field_value: - num_tokens += 3 - num_tokens += len(encoding.encode(enum_field)) - else: - num_tokens += len(encoding.encode(field_key)) - num_tokens += len(encoding.encode(str(field_value))) - if "required" in parameters: - num_tokens += len(encoding.encode("required")) - for required_field in parameters["required"]: - num_tokens += 3 - num_tokens += len(encoding.encode(required_field)) - - return num_tokens - - @staticmethod - def _get_ai_model_entity(base_model_name: str, model: str): - for ai_model_entity in LLM_BASE_MODELS: - if ai_model_entity.base_model_name == base_model_name: - ai_model_entity_copy = copy.deepcopy(ai_model_entity) - ai_model_entity_copy.entity.model = model - ai_model_entity_copy.entity.label.en_US = model - ai_model_entity_copy.entity.label.zh_Hans = model - return ai_model_entity_copy diff --git a/api/core/model_runtime/model_providers/azure_openai/speech2text/__init__.py b/api/core/model_runtime/model_providers/azure_openai/speech2text/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/azure_openai/speech2text/speech2text.py b/api/core/model_runtime/model_providers/azure_openai/speech2text/speech2text.py deleted file mode 100644 index a2b14cf3dbe6d4..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/speech2text/speech2text.py +++ /dev/null @@ -1,79 +0,0 @@ -import copy -from typing import IO, Optional - -from openai import AzureOpenAI - -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel -from core.model_runtime.model_providers.azure_openai._common import _CommonAzureOpenAI -from core.model_runtime.model_providers.azure_openai._constant import SPEECH2TEXT_BASE_MODELS, AzureBaseModel - - -class AzureOpenAISpeech2TextModel(_CommonAzureOpenAI, Speech2TextModel): - """ - Model class for OpenAI Speech to text model. - """ - - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - return self._speech2text_invoke(model, credentials, file) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - audio_file_path = self._get_demo_file_path() - - with open(audio_file_path, "rb") as audio_file: - self._speech2text_invoke(model, credentials, audio_file) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _speech2text_invoke(self, model: str, credentials: dict, file: IO[bytes]) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :return: text for given audio file - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - # init model client - client = AzureOpenAI(**credentials_kwargs) - - response = client.audio.transcriptions.create(model=model, file=file) - - return response.text - - def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]: - ai_model_entity = self._get_ai_model_entity(credentials["base_model_name"], model) - return ai_model_entity.entity - - @staticmethod - def _get_ai_model_entity(base_model_name: str, model: str) -> AzureBaseModel: - for ai_model_entity in SPEECH2TEXT_BASE_MODELS: - if ai_model_entity.base_model_name == base_model_name: - ai_model_entity_copy = copy.deepcopy(ai_model_entity) - ai_model_entity_copy.entity.model = model - ai_model_entity_copy.entity.label.en_US = model - ai_model_entity_copy.entity.label.zh_Hans = model - return ai_model_entity_copy - - return None diff --git a/api/core/model_runtime/model_providers/azure_openai/text_embedding/__init__.py b/api/core/model_runtime/model_providers/azure_openai/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/azure_openai/tts/__init__.py b/api/core/model_runtime/model_providers/azure_openai/tts/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/azure_openai/tts/tts.py b/api/core/model_runtime/model_providers/azure_openai/tts/tts.py deleted file mode 100644 index af178703a06951..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/tts/tts.py +++ /dev/null @@ -1,128 +0,0 @@ -import concurrent.futures -import copy -from typing import Optional - -from openai import AzureOpenAI - -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.errors.invoke import InvokeBadRequestError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.tts_model import TTSModel -from core.model_runtime.model_providers.azure_openai._common import _CommonAzureOpenAI -from core.model_runtime.model_providers.azure_openai._constant import TTS_BASE_MODELS, AzureBaseModel - - -class AzureOpenAIText2SpeechModel(_CommonAzureOpenAI, TTSModel): - """ - Model class for OpenAI Speech to text model. - """ - - def _invoke( - self, model: str, tenant_id: str, credentials: dict, content_text: str, voice: str, user: Optional[str] = None - ) -> any: - """ - _invoke text2speech model - - :param model: model name - :param tenant_id: user tenant id - :param credentials: model credentials - :param content_text: text content to be translated - :param voice: model timbre - :param user: unique user id - :return: text translated to audio file - """ - if not voice or voice not in [ - d["value"] for d in self.get_tts_model_voices(model=model, credentials=credentials) - ]: - voice = self._get_model_default_voice(model, credentials) - - return self._tts_invoke_streaming(model=model, credentials=credentials, content_text=content_text, voice=voice) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - validate credentials text2speech model - - :param model: model name - :param credentials: model credentials - :return: text translated to audio file - """ - try: - self._tts_invoke_streaming( - model=model, - credentials=credentials, - content_text="Hello Dify!", - voice=self._get_model_default_voice(model, credentials), - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _tts_invoke_streaming(self, model: str, credentials: dict, content_text: str, voice: str) -> any: - """ - _tts_invoke_streaming text2speech model - :param model: model name - :param credentials: model credentials - :param content_text: text content to be translated - :param voice: model timbre - :return: text translated to audio file - """ - try: - # doc: https://platform.openai.com/docs/guides/text-to-speech - credentials_kwargs = self._to_credential_kwargs(credentials) - client = AzureOpenAI(**credentials_kwargs) - # max length is 4096 characters, there is 3500 limit for each request - max_length = 3500 - if len(content_text) > max_length: - sentences = self._split_text_into_sentences(content_text, max_length=max_length) - executor = concurrent.futures.ThreadPoolExecutor(max_workers=min(3, len(sentences))) - futures = [ - executor.submit( - client.audio.speech.with_streaming_response.create, - model=model, - response_format="mp3", - input=sentences[i], - voice=voice, - ) - for i in range(len(sentences)) - ] - for future in futures: - yield from future.result().__enter__().iter_bytes(1024) # noqa:PLC2801 - - else: - response = client.audio.speech.with_streaming_response.create( - model=model, voice=voice, response_format="mp3", input=content_text.strip() - ) - - yield from response.__enter__().iter_bytes(1024) # noqa:PLC2801 - except Exception as ex: - raise InvokeBadRequestError(str(ex)) - - def _process_sentence(self, sentence: str, model: str, voice, credentials: dict): - """ - _tts_invoke openai text2speech model api - - :param model: model name - :param credentials: model credentials - :param voice: model timbre - :param sentence: text content to be translated - :return: text translated to audio file - """ - credentials_kwargs = self._to_credential_kwargs(credentials) - client = AzureOpenAI(**credentials_kwargs) - response = client.audio.speech.create(model=model, voice=voice, input=sentence.strip()) - if isinstance(response.read(), bytes): - return response.read() - - def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]: - ai_model_entity = self._get_ai_model_entity(credentials["base_model_name"], model) - return ai_model_entity.entity - - @staticmethod - def _get_ai_model_entity(base_model_name: str, model: str) -> AzureBaseModel | None: - for ai_model_entity in TTS_BASE_MODELS: - if ai_model_entity.base_model_name == base_model_name: - ai_model_entity_copy = copy.deepcopy(ai_model_entity) - ai_model_entity_copy.entity.model = model - ai_model_entity_copy.entity.label.en_US = model - ai_model_entity_copy.entity.label.zh_Hans = model - return ai_model_entity_copy - return None diff --git a/api/core/model_runtime/model_providers/baichuan/__init__.py b/api/core/model_runtime/model_providers/baichuan/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/baichuan/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/baichuan/_assets/icon_l_en.svg deleted file mode 100644 index 7ff6b5a67ad618..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/_assets/icon_l_en.svg +++ /dev/null @@ -1,19 +0,0 @@ - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/baichuan/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/baichuan/_assets/icon_s_en.svg deleted file mode 100644 index 4ddcd2672696c8..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/_assets/icon_s_en.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/baichuan/baichuan.py b/api/core/model_runtime/model_providers/baichuan/baichuan.py deleted file mode 100644 index 626fc811cfd47b..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/baichuan.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class BaichuanProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `baichuan2-turbo` model for validate, - model_instance.validate_credentials(model="baichuan2-turbo", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/baichuan/baichuan.yaml b/api/core/model_runtime/model_providers/baichuan/baichuan.yaml deleted file mode 100644 index 81e6e36215aa84..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/baichuan.yaml +++ /dev/null @@ -1,29 +0,0 @@ -provider: baichuan -label: - en_US: Baichuan -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#FFF6F2" -help: - title: - en_US: Get your API Key from BAICHUAN AI - zh_Hans: 从百川智能获取您的 API Key - url: - en_US: https://www.baichuan-ai.com -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/baichuan/llm/__init__.py b/api/core/model_runtime/model_providers/baichuan/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-53b.yaml b/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-53b.yaml deleted file mode 100644 index 8360dd5faffb00..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-53b.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: baichuan2-53b -label: - en_US: Baichuan2-53B -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 1000 - min: 1 - max: 4000 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - default: 1 - min: 1 - max: 2 - - name: with_search_enhance - label: - zh_Hans: 搜索增强 - en_US: Search Enhance - type: boolean - help: - zh_Hans: 允许模型自行进行外部搜索，以增强生成结果。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false -deprecated: true diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-turbo-192k.yaml b/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-turbo-192k.yaml deleted file mode 100644 index 0ce0265cfe5c6c..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-turbo-192k.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: baichuan2-turbo-192k -label: - en_US: Baichuan2-Turbo-192K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 192000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 8000 - min: 1 - max: 192000 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - default: 1 - min: 1 - max: 2 - - name: with_search_enhance - label: - zh_Hans: 搜索增强 - en_US: Search Enhance - type: boolean - help: - zh_Hans: 允许模型自行进行外部搜索，以增强生成结果。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false -deprecated: true diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-turbo.yaml b/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-turbo.yaml deleted file mode 100644 index ccb4ee8b92bc16..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan2-turbo.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: baichuan2-turbo -label: - en_US: Baichuan2-Turbo -model_type: llm -features: - - agent-thought - - multi-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.3 - - name: top_p - use_template: top_p - default: 0.85 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - min: 0 - max: 20 - default: 5 - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - default: 2048 - - name: with_search_enhance - label: - zh_Hans: 搜索增强 - en_US: Search Enhance - type: boolean - help: - zh_Hans: 允许模型自行进行外部搜索，以增强生成结果。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan3-turbo-128k.yaml b/api/core/model_runtime/model_providers/baichuan/llm/baichuan3-turbo-128k.yaml deleted file mode 100644 index d9cd086e82c994..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan3-turbo-128k.yaml +++ /dev/null @@ -1,53 +0,0 @@ -model: baichuan3-turbo-128k -label: - en_US: Baichuan3-Turbo-128k -model_type: llm -features: - - agent-thought - - multi-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.3 - - name: top_p - use_template: top_p - default: 0.85 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - min: 0 - max: 20 - default: 5 - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - default: 2048 - - name: res_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object - - name: with_search_enhance - label: - zh_Hans: 搜索增强 - en_US: Search Enhance - type: boolean - help: - zh_Hans: 允许模型自行进行外部搜索，以增强生成结果。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan3-turbo.yaml b/api/core/model_runtime/model_providers/baichuan/llm/baichuan3-turbo.yaml deleted file mode 100644 index 58f9b39a438a08..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan3-turbo.yaml +++ /dev/null @@ -1,53 +0,0 @@ -model: baichuan3-turbo -label: - en_US: Baichuan3-Turbo -model_type: llm -features: - - agent-thought - - multi-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.3 - - name: top_p - use_template: top_p - default: 0.85 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - min: 0 - max: 20 - default: 5 - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - default: 2048 - - name: res_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object - - name: with_search_enhance - label: - zh_Hans: 搜索增强 - en_US: Search Enhance - type: boolean - help: - zh_Hans: 允许模型自行进行外部搜索，以增强生成结果。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan4.yaml b/api/core/model_runtime/model_providers/baichuan/llm/baichuan4.yaml deleted file mode 100644 index 6a1135e165fcaf..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan4.yaml +++ /dev/null @@ -1,53 +0,0 @@ -model: baichuan4 -label: - en_US: Baichuan4 -model_type: llm -features: - - agent-thought - - multi-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.3 - - name: top_p - use_template: top_p - default: 0.85 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - min: 0 - max: 20 - default: 5 - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - default: 2048 - - name: res_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object - - name: with_search_enhance - label: - zh_Hans: 搜索增强 - en_US: Search Enhance - type: boolean - help: - zh_Hans: 允许模型自行进行外部搜索，以增强生成结果。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan_tokenizer.py b/api/core/model_runtime/model_providers/baichuan/llm/baichuan_tokenizer.py deleted file mode 100644 index a7ca28d49d636e..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan_tokenizer.py +++ /dev/null @@ -1,21 +0,0 @@ -import re - - -class BaichuanTokenizer: - @classmethod - def count_chinese_characters(cls, text: str) -> int: - return len(re.findall(r"[\u4e00-\u9fa5]", text)) - - @classmethod - def count_english_vocabularies(cls, text: str) -> int: - # remove all non-alphanumeric characters but keep spaces and other symbols like !, ., etc. - text = re.sub(r"[^a-zA-Z0-9\s]", "", text) - # count the number of words not characters - return len(text.split()) - - @classmethod - def _get_num_tokens(cls, text: str) -> int: - # tokens = number of Chinese characters + number of English words * 1.3 - # (for estimation only, subject to actual return) - # https://platform.baichuan-ai.com/docs/text-Embedding - return int(cls.count_chinese_characters(text) + cls.count_english_vocabularies(text) * 1.3) diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan_turbo.py b/api/core/model_runtime/model_providers/baichuan/llm/baichuan_turbo.py deleted file mode 100644 index d5fda73009bba9..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan_turbo.py +++ /dev/null @@ -1,144 +0,0 @@ -import json -from collections.abc import Iterator -from typing import Any, Optional, Union - -from requests import post - -from core.model_runtime.entities.message_entities import PromptMessageTool -from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import ( - BadRequestError, - InsufficientAccountBalanceError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) - - -class BaichuanModel: - api_key: str - - def __init__(self, api_key: str) -> None: - self.api_key = api_key - - @property - def _model_mapping(self) -> dict: - return { - "baichuan2-turbo": "Baichuan2-Turbo", - "baichuan3-turbo": "Baichuan3-Turbo", - "baichuan3-turbo-128k": "Baichuan3-Turbo-128k", - "baichuan4": "Baichuan4", - } - - @property - def request_headers(self) -> dict[str, Any]: - return { - "Content-Type": "application/json", - "Authorization": "Bearer " + self.api_key, - } - - def _build_parameters( - self, - model: str, - stream: bool, - messages: list[dict], - parameters: dict[str, Any], - tools: Optional[list[PromptMessageTool]] = None, - ) -> dict[str, Any]: - if model in self._model_mapping: - # the LargeLanguageModel._code_block_mode_wrapper() method will remove the response_format of parameters. - # we need to rename it to res_format to get its value - if parameters.get("res_format") == "json_object": - parameters["response_format"] = {"type": "json_object"} - - if tools or parameters.get("with_search_enhance") is True: - parameters["tools"] = [] - - # with_search_enhance is deprecated, use web_search instead - if parameters.get("with_search_enhance") is True: - parameters["tools"].append( - { - "type": "web_search", - "web_search": {"enable": True}, - } - ) - if tools: - for tool in tools: - parameters["tools"].append( - { - "type": "function", - "function": { - "name": tool.name, - "description": tool.description, - "parameters": tool.parameters, - }, - } - ) - - # turbo api accepts flat parameters - return { - "model": self._model_mapping.get(model), - "stream": stream, - "messages": messages, - **parameters, - } - else: - raise BadRequestError(f"Unknown model: {model}") - - def generate( - self, - model: str, - stream: bool, - messages: list[dict], - parameters: dict[str, Any], - timeout: int, - tools: Optional[list[PromptMessageTool]] = None, - ) -> Union[Iterator, dict]: - if model in self._model_mapping: - api_base = "https://api.baichuan-ai.com/v1/chat/completions" - else: - raise BadRequestError(f"Unknown model: {model}") - - data = self._build_parameters(model, stream, messages, parameters, tools) - - try: - response = post( - url=api_base, - headers=self.request_headers, - data=json.dumps(data), - timeout=timeout, - stream=stream, - ) - except Exception as e: - raise InternalServerError(f"Failed to invoke model: {e}") - - if response.status_code != 200: - try: - resp = response.json() - # try to parse error message - err = resp["error"]["type"] - msg = resp["error"]["message"] - except Exception as e: - raise InternalServerError(f"Failed to convert response to json: {e} with text: {response.text}") - - if err == "invalid_api_key": - raise InvalidAPIKeyError(msg) - elif err == "insufficient_quota": - raise InsufficientAccountBalanceError(msg) - elif err == "invalid_authentication": - raise InvalidAuthenticationError(msg) - elif err == "invalid_request_error": - raise BadRequestError(msg) - elif "rate" in err: - raise RateLimitReachedError(msg) - elif "internal" in err: - raise InternalServerError(msg) - elif err == "api_key_empty": - raise InvalidAPIKeyError(msg) - else: - raise InternalServerError(f"Unknown error: {err} with message: {msg}") - - if stream: - return response.iter_lines() - else: - return response.json() diff --git a/api/core/model_runtime/model_providers/baichuan/llm/baichuan_turbo_errors.py b/api/core/model_runtime/model_providers/baichuan/llm/baichuan_turbo_errors.py deleted file mode 100644 index 309b5cf413bd54..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/baichuan_turbo_errors.py +++ /dev/null @@ -1,22 +0,0 @@ -class InvalidAuthenticationError(Exception): - pass - - -class InvalidAPIKeyError(Exception): - pass - - -class RateLimitReachedError(Exception): - pass - - -class InsufficientAccountBalanceError(Exception): - pass - - -class InternalServerError(Exception): - pass - - -class BadRequestError(Exception): - pass diff --git a/api/core/model_runtime/model_providers/baichuan/llm/llm.py b/api/core/model_runtime/model_providers/baichuan/llm/llm.py deleted file mode 100644 index 91a14bf1009006..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/llm/llm.py +++ /dev/null @@ -1,296 +0,0 @@ -import json -from collections.abc import Generator, Iterator -from typing import cast - -from core.model_runtime.entities.llm_entities import ( - LLMResult, - LLMResultChunk, - LLMResultChunkDelta, -) -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.baichuan.llm.baichuan_tokenizer import BaichuanTokenizer -from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo import BaichuanModel -from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import ( - BadRequestError, - InsufficientAccountBalanceError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) - - -class BaichuanLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stream=stream, - ) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - return self._num_tokens_from_messages(prompt_messages) - - def _num_tokens_from_messages( - self, - messages: list[PromptMessage], - ) -> int: - """Calculate num tokens for baichuan model""" - - def tokens(text: str): - return BaichuanTokenizer._get_num_tokens(text) - - tokens_per_message = 3 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - num_tokens += tokens(str(value)) - num_tokens += 3 - - return num_tokens - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for Baichuan - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - raise ValueError("User message content must be str") - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls: - message_dict["tool_calls"] = [tool_call.dict() for tool_call in message.tool_calls] - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = {"role": "tool", "content": message.content, "tool_call_id": message.tool_call_id} - else: - raise ValueError(f"Unknown message type {type(message)}") - - return message_dict - - def validate_credentials(self, model: str, credentials: dict) -> None: - # ping - instance = BaichuanModel(api_key=credentials["api_key"]) - - try: - instance.generate( - model=model, - stream=False, - messages=[{"content": "ping", "role": "user"}], - parameters={ - "max_tokens": 1, - }, - timeout=60, - ) - except Exception as e: - raise CredentialsValidateFailedError(f"Invalid API key: {e}") - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stream: bool = True, - ) -> LLMResult | Generator: - instance = BaichuanModel(api_key=credentials["api_key"]) - messages = [self._convert_prompt_message_to_dict(m) for m in prompt_messages] - - # invoke model - response = instance.generate( - model=model, - stream=stream, - messages=messages, - parameters=model_parameters, - timeout=60, - tools=tools, - ) - - if stream: - return self._handle_chat_generate_stream_response(model, prompt_messages, credentials, response) - - return self._handle_chat_generate_response(model, prompt_messages, credentials, response) - - def _handle_chat_generate_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: dict, - ) -> LLMResult: - choices = response.get("choices", []) - assistant_message = AssistantPromptMessage(content="", tool_calls=[]) - if choices and choices[0]["finish_reason"] == "tool_calls": - for choice in choices: - for tool_call in choice["message"]["tool_calls"]: - tool = AssistantPromptMessage.ToolCall( - id=tool_call.get("id", ""), - type=tool_call.get("type", ""), - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=tool_call.get("function", {}).get("name", ""), - arguments=tool_call.get("function", {}).get("arguments", ""), - ), - ) - assistant_message.tool_calls.append(tool) - else: - for choice in choices: - assistant_message.content += choice["message"]["content"] - assistant_message.role = choice["message"]["role"] - - usage = response.get("usage") - if usage: - # transform usage - prompt_tokens = usage["prompt_tokens"] - completion_tokens = usage["completion_tokens"] - else: - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(prompt_messages) - completion_tokens = self._num_tokens_from_messages([assistant_message]) - - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=prompt_tokens, - completion_tokens=completion_tokens, - ) - - return LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_message, - usage=usage, - ) - - def _handle_chat_generate_stream_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: Iterator, - ) -> Generator: - for line in response: - if not line: - continue - line = line.decode("utf-8") - # remove the first `data: ` prefix - if line.startswith("data:"): - line = line[5:].strip() - try: - data = json.loads(line) - except Exception as e: - if line.strip() == "[DONE]": - return - choices = data.get("choices", []) - - stop_reason = "" - for choice in choices: - if choice.get("finish_reason"): - stop_reason = choice["finish_reason"] - - if len(choice["delta"]["content"]) == 0: - continue - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=choice["delta"]["content"], tool_calls=[]), - finish_reason=stop_reason, - ), - ) - - # if there is usage, the response is the last one, yield it and return - if "usage" in data: - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=data["usage"]["prompt_tokens"], - completion_tokens=data["usage"]["completion_tokens"], - ) - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content="", tool_calls=[]), - usage=usage, - finish_reason=stop_reason, - ), - ) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [InternalServerError], - InvokeRateLimitError: [RateLimitReachedError], - InvokeAuthorizationError: [ - InvalidAuthenticationError, - InsufficientAccountBalanceError, - InvalidAPIKeyError, - ], - InvokeBadRequestError: [BadRequestError, KeyError], - } diff --git a/api/core/model_runtime/model_providers/baichuan/text_embedding/__init__.py b/api/core/model_runtime/model_providers/baichuan/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/baichuan/text_embedding/baichuan-text-embedding.yaml b/api/core/model_runtime/model_providers/baichuan/text_embedding/baichuan-text-embedding.yaml deleted file mode 100644 index 67e5fcc47c9f58..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/text_embedding/baichuan-text-embedding.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: baichuan-text-embedding -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 16 diff --git a/api/core/model_runtime/model_providers/bedrock/__init__.py b/api/core/model_runtime/model_providers/bedrock/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/bedrock/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/bedrock/_assets/icon_l_en.svg deleted file mode 100644 index 667db50800d881..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/_assets/icon_l_en.svg +++ /dev/null @@ -1,14 +0,0 @@ - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/bedrock/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/bedrock/_assets/icon_s_en.svg deleted file mode 100644 index 6a0235af92c3cb..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/_assets/icon_s_en.svg +++ /dev/null @@ -1,15 +0,0 @@ - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/bedrock/bedrock.py b/api/core/model_runtime/model_providers/bedrock/bedrock.py deleted file mode 100644 index 1cfc1d199cbf8d..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/bedrock.py +++ /dev/null @@ -1,29 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class BedrockProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `amazon.titan-text-lite-v1` model by default for validating credentials - model_for_validation = credentials.get("model_for_validation", "amazon.titan-text-lite-v1") - model_instance.validate_credentials(model=model_for_validation, credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/bedrock/bedrock.yaml b/api/core/model_runtime/model_providers/bedrock/bedrock.yaml deleted file mode 100644 index c540ee23b31672..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/bedrock.yaml +++ /dev/null @@ -1,89 +0,0 @@ -provider: bedrock -label: - en_US: AWS -description: - en_US: AWS Bedrock's models. -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#FCFDFF" -help: - title: - en_US: Get your Access Key and Secret Access Key from AWS Console - url: - en_US: https://console.aws.amazon.com/ -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: aws_access_key_id - required: false - label: - en_US: Access Key (If not provided, credentials are obtained from the running environment.) - zh_Hans: Access Key - type: secret-input - placeholder: - en_US: Enter your Access Key - zh_Hans: 在此输入您的 Access Key - - variable: aws_secret_access_key - required: false - label: - en_US: Secret Access Key - zh_Hans: Secret Access Key - type: secret-input - placeholder: - en_US: Enter your Secret Access Key - zh_Hans: 在此输入您的 Secret Access Key - - variable: aws_region - required: true - label: - en_US: AWS Region - zh_Hans: AWS 地区 - type: select - default: us-east-1 - options: - - value: us-east-1 - label: - en_US: US East (N. Virginia) - zh_Hans: 美国东部 (弗吉尼亚北部) - - value: us-west-2 - label: - en_US: US West (Oregon) - zh_Hans: 美国西部 (俄勒冈州) - - value: ap-southeast-1 - label: - en_US: Asia Pacific (Singapore) - zh_Hans: 亚太地区 (新加坡) - - value: ap-northeast-1 - label: - en_US: Asia Pacific (Tokyo) - zh_Hans: 亚太地区 (东京) - - value: eu-central-1 - label: - en_US: Europe (Frankfurt) - zh_Hans: 欧洲 (法兰克福) - - value: eu-west-2 - label: - en_US: Eu west London (London) - zh_Hans: 欧洲西部 (伦敦) - - value: us-gov-west-1 - label: - en_US: AWS GovCloud (US-West) - zh_Hans: AWS GovCloud (US-West) - - value: ap-southeast-2 - label: - en_US: Asia Pacific (Sydney) - zh_Hans: 亚太地区 (悉尼) - - variable: model_for_validation - required: false - label: - en_US: Available Model Name - zh_Hans: 可用模型名称 - type: text-input - placeholder: - en_US: A model you have access to (e.g. amazon.titan-text-lite-v1) for validation. - zh_Hans: 为了进行验证，请输入一个您可用的模型名称 (例如：amazon.titan-text-lite-v1) diff --git a/api/core/model_runtime/model_providers/bedrock/llm/__init__.py b/api/core/model_runtime/model_providers/bedrock/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/bedrock/llm/_position.yaml b/api/core/model_runtime/model_providers/bedrock/llm/_position.yaml deleted file mode 100644 index 86c8061deefac8..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/_position.yaml +++ /dev/null @@ -1,24 +0,0 @@ -- amazon.titan-text-express-v1 -- amazon.titan-text-lite-v1 -- anthropic.claude-instant-v1 -- anthropic.claude-v1 -- anthropic.claude-v2 -- anthropic.claude-v2:1 -- anthropic.claude-3-sonnet-v1:0 -- anthropic.claude-3-haiku-v1:0 -- cohere.command-light-text-v14 -- cohere.command-text-v14 -- cohere.command-r-plus-v1.0 -- cohere.command-r-v1.0 -- meta.llama3-1-8b-instruct-v1:0 -- meta.llama3-1-70b-instruct-v1:0 -- meta.llama3-1-405b-instruct-v1:0 -- meta.llama3-8b-instruct-v1:0 -- meta.llama3-70b-instruct-v1:0 -- meta.llama2-13b-chat-v1 -- meta.llama2-70b-chat-v1 -- mistral.mistral-large-2407-v1:0 -- mistral.mistral-small-2402-v1:0 -- mistral.mistral-large-2402-v1:0 -- mistral.mixtral-8x7b-instruct-v0:1 -- mistral.mistral-7b-instruct-v0:2 diff --git a/api/core/model_runtime/model_providers/bedrock/llm/ai21.j2-mid-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/ai21.j2-mid-v1.yaml deleted file mode 100644 index 65dad02969652b..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/ai21.j2-mid-v1.yaml +++ /dev/null @@ -1,47 +0,0 @@ -model: ai21.j2-mid-v1 -label: - en_US: J2 Mid V1 -model_type: llm -model_properties: - mode: completion - context_size: 8191 -parameter_rules: - - name: temperature - use_template: temperature - - name: topP - use_template: top_p - - name: maxTokens - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 2048 - - name: count_penalty - label: - en_US: Count Penalty - required: false - type: float - default: 0 - min: 0 - max: 1 - - name: presence_penalty - label: - en_US: Presence Penalty - required: false - type: float - default: 0 - min: 0 - max: 5 - - name: frequency_penalty - label: - en_US: Frequency Penalty - required: false - type: float - default: 0 - min: 0 - max: 500 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/ai21.j2-ultra-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/ai21.j2-ultra-v1.yaml deleted file mode 100644 index b72f8064bde6d5..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/ai21.j2-ultra-v1.yaml +++ /dev/null @@ -1,47 +0,0 @@ -model: ai21.j2-ultra-v1 -label: - en_US: J2 Ultra V1 -model_type: llm -model_properties: - mode: completion - context_size: 8191 -parameter_rules: - - name: temperature - use_template: temperature - - name: topP - use_template: top_p - - name: maxTokens - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 2048 - - name: count_penalty - label: - en_US: Count Penalty - required: false - type: float - default: 0 - min: 0 - max: 1 - - name: presence_penalty - label: - en_US: Presence Penalty - required: false - type: float - default: 0 - min: 0 - max: 5 - - name: frequency_penalty - label: - en_US: Frequency Penalty - required: false - type: float - default: 0 - min: 0 - max: 500 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/amazon.titan-text-express-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/amazon.titan-text-express-v1.yaml deleted file mode 100644 index 543c16d5cd53e5..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/amazon.titan-text-express-v1.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: amazon.titan-text-express-v1 -label: - en_US: Titan Text G1 - Express -model_type: llm -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: topP - use_template: top_p - - name: maxTokenCount - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 8000 -pricing: - input: '0.0008' - output: '0.0016' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/amazon.titan-text-lite-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/amazon.titan-text-lite-v1.yaml deleted file mode 100644 index 2c6151c2390485..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/amazon.titan-text-lite-v1.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: amazon.titan-text-lite-v1 -label: - en_US: Titan Text G1 - Lite -model_type: llm -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: topP - use_template: top_p - - name: maxTokenCount - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 2048 -pricing: - input: '0.0003' - output: '0.0004' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-haiku-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-haiku-v1.yaml deleted file mode 100644 index c2d5eb64715616..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-haiku-v1.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: anthropic.claude-3-haiku-20240307-v1:0 -label: - en_US: Claude 3 Haiku -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - # docs: https://docs.anthropic.com/claude/docs/system-prompts - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. - - name: response_format - use_template: response_format -pricing: - input: '0.00025' - output: '0.00125' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-opus-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-opus-v1.yaml deleted file mode 100644 index f90fa04266187b..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-opus-v1.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: anthropic.claude-3-opus-20240229-v1:0 -label: - en_US: Claude 3 Opus -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - # docs: https://docs.anthropic.com/claude/docs/system-prompts - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. - - name: response_format - use_template: response_format -pricing: - input: '0.015' - output: '0.075' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-sonnet-v1.5.yaml b/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-sonnet-v1.5.yaml deleted file mode 100644 index dad0d6b6b6c23c..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-sonnet-v1.5.yaml +++ /dev/null @@ -1,60 +0,0 @@ -model: anthropic.claude-3-5-sonnet-20240620-v1:0 -label: - en_US: Claude 3.5 Sonnet -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. - - name: response_format - use_template: response_format -pricing: - input: '0.003' - output: '0.015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-sonnet-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-sonnet-v1.yaml deleted file mode 100644 index 962def8011b157..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-3-sonnet-v1.yaml +++ /dev/null @@ -1,60 +0,0 @@ -model: anthropic.claude-3-sonnet-20240229-v1:0 -label: - en_US: Claude 3 Sonnet -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. - - name: response_format - use_template: response_format -pricing: - input: '0.003' - output: '0.015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-instant-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-instant-v1.yaml deleted file mode 100644 index 8422f079c5e1b4..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-instant-v1.yaml +++ /dev/null @@ -1,52 +0,0 @@ -model: anthropic.claude-instant-v1 -label: - en_US: Claude Instant 1 -model_type: llm -model_properties: - mode: chat - context_size: 100000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.0008' - output: '0.0024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v1.yaml deleted file mode 100644 index 6a714b1055b2a9..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v1.yaml +++ /dev/null @@ -1,53 +0,0 @@ -model: anthropic.claude-v1 -label: - en_US: Claude 1 -model_type: llm -model_properties: - mode: chat - context_size: 100000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD -deprecated: true diff --git a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v2.1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v2.1.yaml deleted file mode 100644 index 70294e4ad3ffde..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v2.1.yaml +++ /dev/null @@ -1,54 +0,0 @@ -model: anthropic.claude-v2:1 -label: - en_US: Claude 2.1 -model_type: llm -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. - - name: response_format - use_template: response_format -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v2.yaml b/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v2.yaml deleted file mode 100644 index 0a8ea61b6df0c8..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/anthropic.claude-v2.yaml +++ /dev/null @@ -1,54 +0,0 @@ -model: anthropic.claude-v2 -label: - en_US: Claude 2 -model_type: llm -model_properties: - mode: chat - context_size: 100000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. - - name: response_format - use_template: response_format -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-light-text-v14.yaml b/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-light-text-v14.yaml deleted file mode 100644 index 74500095511f1c..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-light-text-v14.yaml +++ /dev/null @@ -1,35 +0,0 @@ -model: cohere.command-light-text-v14 -label: - en_US: Command Light Text V14 -model_type: llm -model_properties: - mode: completion - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: p - use_template: top_p - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - min: 0 - max: 500 - default: 0 - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 -pricing: - input: '0.0003' - output: '0.0006' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-r-plus-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-r-plus-v1.0.yaml deleted file mode 100644 index 3c0bb4e8d58f04..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-r-plus-v1.0.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: cohere.command-r-plus-v1:0 -label: - en_US: Command R+ -model_type: llm -features: - - tool-call - #- stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: '3' - output: '15' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-r-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-r-v1.0.yaml deleted file mode 100644 index a34f48319f2ac0..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-r-v1.0.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: cohere.command-r-v1:0 -label: - en_US: Command R -model_type: llm -features: - - tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: '0.5' - output: '1.5' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-text-v14.yaml b/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-text-v14.yaml deleted file mode 100644 index 6aea5be170c6ee..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/cohere.command-text-v14.yaml +++ /dev/null @@ -1,32 +0,0 @@ -model: cohere.command-text-v14 -label: - en_US: Command Text V14 -model_type: llm -model_properties: - mode: completion - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: p - use_template: top_p - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 -pricing: - input: '0.0015' - output: '0.0020' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-haiku-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-haiku-v1.yaml deleted file mode 100644 index 24a65ef1bb84ab..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-haiku-v1.yaml +++ /dev/null @@ -1,59 +0,0 @@ -model: eu.anthropic.claude-3-haiku-20240307-v1:0 -label: - en_US: Claude 3 Haiku(EU.Cross Region Inference) -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - # docs: https://docs.anthropic.com/claude/docs/system-prompts - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.00025' - output: '0.00125' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-sonnet-v1.5.yaml b/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-sonnet-v1.5.yaml deleted file mode 100644 index e3d25c7d8f6a68..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-sonnet-v1.5.yaml +++ /dev/null @@ -1,58 +0,0 @@ -model: eu.anthropic.claude-3-5-sonnet-20240620-v1:0 -label: - en_US: Claude 3.5 Sonnet(EU.Cross Region Inference) -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.003' - output: '0.015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-sonnet-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-sonnet-v1.yaml deleted file mode 100644 index 9a06a4ad6d5162..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/eu.anthropic.claude-3-sonnet-v1.yaml +++ /dev/null @@ -1,58 +0,0 @@ -model: eu.anthropic.claude-3-sonnet-20240229-v1:0 -label: - en_US: Claude 3 Sonnet(EU.Cross Region Inference) -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.003' - output: '0.015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/llm.py b/api/core/model_runtime/model_providers/bedrock/llm/llm.py deleted file mode 100644 index 77bab0c2945887..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/llm.py +++ /dev/null @@ -1,903 +0,0 @@ -# standard import -import base64 -import json -import logging -import mimetypes -from collections.abc import Generator -from typing import Optional, Union, cast - -# 3rd import -import boto3 -import requests -from botocore.config import Config -from botocore.exceptions import ( - ClientError, - EndpointConnectionError, - NoRegionError, - ServiceNotInRegionError, - UnknownServiceError, -) - -# local import -from core.model_runtime.callbacks.base_callback import Callback -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -logger = logging.getLogger(__name__) -ANTHROPIC_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. -The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - - -{{instructions}} - -""" # noqa: E501 - - -class BedrockLargeLanguageModel(LargeLanguageModel): - # please refer to the documentation: https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html - # TODO There is invoke issue: context limit on Cohere Model, will add them after fixed. - CONVERSE_API_ENABLED_MODEL_INFO = [ - {"prefix": "anthropic.claude-v2", "support_system_prompts": True, "support_tool_use": False}, - {"prefix": "anthropic.claude-v1", "support_system_prompts": True, "support_tool_use": False}, - {"prefix": "us.anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True}, - {"prefix": "eu.anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True}, - {"prefix": "anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True}, - {"prefix": "meta.llama", "support_system_prompts": True, "support_tool_use": False}, - {"prefix": "mistral.mistral-7b-instruct", "support_system_prompts": False, "support_tool_use": False}, - {"prefix": "mistral.mixtral-8x7b-instruct", "support_system_prompts": False, "support_tool_use": False}, - {"prefix": "mistral.mistral-large", "support_system_prompts": True, "support_tool_use": True}, - {"prefix": "mistral.mistral-small", "support_system_prompts": True, "support_tool_use": True}, - {"prefix": "cohere.command-r", "support_system_prompts": True, "support_tool_use": True}, - {"prefix": "amazon.titan", "support_system_prompts": False, "support_tool_use": False}, - ] - - @staticmethod - def _find_model_info(model_id): - for model in BedrockLargeLanguageModel.CONVERSE_API_ENABLED_MODEL_INFO: - if model_id.startswith(model["prefix"]): - return model - logger.info(f"current model id: {model_id} did not support by Converse API") - return None - - def _code_block_mode_wrapper( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - callbacks: list[Callback] = None, - ) -> Union[LLMResult, Generator]: - """ - Code block mode wrapper for invoking large language model - """ - if model_parameters.get("response_format"): - stop = stop or [] - if "```\n" not in stop: - stop.append("```\n") - if "\n```" not in stop: - stop.append("\n```") - response_format = model_parameters.pop("response_format") - format_prompt = SystemPromptMessage( - content=ANTHROPIC_BLOCK_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content).replace( - "{{block}}", response_format - ) - ) - if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): - prompt_messages[0] = format_prompt - else: - prompt_messages.insert(0, format_prompt) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}")) - return self._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - - model_info = BedrockLargeLanguageModel._find_model_info(model) - if model_info: - model_info["model"] = model - # invoke models via boto3 converse API - return self._generate_with_converse( - model_info, credentials, prompt_messages, model_parameters, stop, stream, user, tools - ) - # invoke other models via boto3 client - return self._generate(model, credentials, prompt_messages, model_parameters, stop, stream, user) - - def _generate_with_converse( - self, - model_info: dict, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - tools: Optional[list[PromptMessageTool]] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model with converse API - - :param model_info: model information - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :return: full response or stream response chunk generator result - """ - bedrock_client = boto3.client( - service_name="bedrock-runtime", - aws_access_key_id=credentials.get("aws_access_key_id"), - aws_secret_access_key=credentials.get("aws_secret_access_key"), - region_name=credentials["aws_region"], - ) - - system, prompt_message_dicts = self._convert_converse_prompt_messages(prompt_messages) - inference_config, additional_model_fields = self._convert_converse_api_model_parameters(model_parameters, stop) - - parameters = { - "modelId": model_info["model"], - "messages": prompt_message_dicts, - "inferenceConfig": inference_config, - "additionalModelRequestFields": additional_model_fields, - } - - if model_info["support_system_prompts"] and system and len(system) > 0: - parameters["system"] = system - - if model_info["support_tool_use"] and tools: - parameters["toolConfig"] = self._convert_converse_tool_config(tools=tools) - try: - if stream: - response = bedrock_client.converse_stream(**parameters) - return self._handle_converse_stream_response( - model_info["model"], credentials, response, prompt_messages - ) - else: - response = bedrock_client.converse(**parameters) - return self._handle_converse_response(model_info["model"], credentials, response, prompt_messages) - except ClientError as ex: - error_code = ex.response["Error"]["Code"] - full_error_msg = f"{error_code}: {ex.response['Error']['Message']}" - raise self._map_client_to_invoke_error(error_code, full_error_msg) - except (EndpointConnectionError, NoRegionError, ServiceNotInRegionError) as ex: - raise InvokeConnectionError(str(ex)) - - except UnknownServiceError as ex: - raise InvokeServerUnavailableError(str(ex)) - - except Exception as ex: - raise InvokeError(str(ex)) - - def _handle_converse_response( - self, model: str, credentials: dict, response: dict, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: full response chunk generator result - """ - response_content = response["output"]["message"]["content"] - # transform assistant message to prompt message - if response["stopReason"] == "tool_use": - tool_calls = [] - text, tool_use = self._extract_tool_use(response_content) - - tool_call = AssistantPromptMessage.ToolCall( - id=tool_use["toolUseId"], - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=tool_use["name"], arguments=json.dumps(tool_use["input"]) - ), - ) - tool_calls.append(tool_call) - - assistant_prompt_message = AssistantPromptMessage(content=text, tool_calls=tool_calls) - else: - assistant_prompt_message = AssistantPromptMessage(content=response_content[0]["text"]) - - # calculate num tokens - if response["usage"]: - # transform usage - prompt_tokens = response["usage"]["inputTokens"] - completion_tokens = response["usage"]["outputTokens"] - else: - # calculate num tokens - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - return result - - def _extract_tool_use(self, content: dict) -> tuple[str, dict]: - tool_use = {} - text = "" - for item in content: - if "toolUse" in item: - tool_use = item["toolUse"] - elif "text" in item: - text = item["text"] - else: - raise ValueError(f"Got unknown item: {item}") - return text, tool_use - - def _handle_converse_stream_response( - self, - model: str, - credentials: dict, - response: dict, - prompt_messages: list[PromptMessage], - ) -> Generator: - """ - Handle llm chat stream response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: full response or stream response chunk generator result - """ - - try: - full_assistant_content = "" - return_model = None - input_tokens = 0 - output_tokens = 0 - finish_reason = None - index = 0 - tool_calls: list[AssistantPromptMessage.ToolCall] = [] - tool_use = {} - - for chunk in response["stream"]: - if "messageStart" in chunk: - return_model = model - elif "messageStop" in chunk: - finish_reason = chunk["messageStop"]["stopReason"] - elif "contentBlockStart" in chunk: - tool = chunk["contentBlockStart"]["start"]["toolUse"] - tool_use["toolUseId"] = tool["toolUseId"] - tool_use["name"] = tool["name"] - elif "metadata" in chunk: - input_tokens = chunk["metadata"]["usage"]["inputTokens"] - output_tokens = chunk["metadata"]["usage"]["outputTokens"] - usage = self._calc_response_usage(model, credentials, input_tokens, output_tokens) - yield LLMResultChunk( - model=return_model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=AssistantPromptMessage(content="", tool_calls=tool_calls), - finish_reason=finish_reason, - usage=usage, - ), - ) - elif "contentBlockDelta" in chunk: - delta = chunk["contentBlockDelta"]["delta"] - if "text" in delta: - chunk_text = delta["text"] or "" - full_assistant_content += chunk_text - assistant_prompt_message = AssistantPromptMessage( - content=chunk_text or "", - ) - index = chunk["contentBlockDelta"]["contentBlockIndex"] - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index + 1, - message=assistant_prompt_message, - ), - ) - elif "toolUse" in delta: - if "input" not in tool_use: - tool_use["input"] = "" - tool_use["input"] += delta["toolUse"]["input"] - elif "contentBlockStop" in chunk: - if "input" in tool_use: - tool_call = AssistantPromptMessage.ToolCall( - id=tool_use["toolUseId"], - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=tool_use["name"], arguments=tool_use["input"] - ), - ) - tool_calls.append(tool_call) - tool_use = {} - - except Exception as ex: - raise InvokeError(str(ex)) - - def _convert_converse_api_model_parameters( - self, model_parameters: dict, stop: Optional[list[str]] = None - ) -> tuple[dict, dict]: - inference_config = {} - additional_model_fields = {} - if "max_tokens" in model_parameters: - inference_config["maxTokens"] = model_parameters["max_tokens"] - - if "temperature" in model_parameters: - inference_config["temperature"] = model_parameters["temperature"] - - if "top_p" in model_parameters: - inference_config["topP"] = model_parameters["temperature"] - - if stop: - inference_config["stopSequences"] = stop - - if "top_k" in model_parameters: - additional_model_fields["top_k"] = model_parameters["top_k"] - - return inference_config, additional_model_fields - - def _convert_converse_prompt_messages(self, prompt_messages: list[PromptMessage]) -> tuple[str, list[dict]]: - """ - Convert prompt messages to dict list and system - """ - - system = [] - prompt_message_dicts = [] - for message in prompt_messages: - if isinstance(message, SystemPromptMessage): - message.content = message.content.strip() - system.append({"text": message.content}) - else: - prompt_message_dicts.append(self._convert_prompt_message_to_dict(message)) - - return system, prompt_message_dicts - - def _convert_converse_tool_config(self, tools: Optional[list[PromptMessageTool]] = None) -> dict: - tool_config = {} - configs = [] - if tools: - for tool in tools: - configs.append( - { - "toolSpec": { - "name": tool.name, - "description": tool.description, - "inputSchema": {"json": tool.parameters}, - } - } - ) - tool_config["tools"] = configs - return tool_config - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": [{"text": message.content}]} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - if not message_content.data.startswith("data:"): - # fetch image data from url - try: - url = message_content.data - image_content = requests.get(url).content - if "?" in url: - url = url.split("?")[0] - mime_type, _ = mimetypes.guess_type(url) - base64_data = base64.b64encode(image_content).decode("utf-8") - except Exception as ex: - raise ValueError(f"Failed to fetch image data from url {message_content.data}, {ex}") - else: - data_split = message_content.data.split(";base64,") - mime_type = data_split[0].replace("data:", "") - base64_data = data_split[1] - image_content = base64.b64decode(base64_data) - - if mime_type not in {"image/jpeg", "image/png", "image/gif", "image/webp"}: - raise ValueError( - f"Unsupported image type {mime_type}, " - f"only support image/jpeg, image/png, image/gif, and image/webp" - ) - - sub_message_dict = { - "image": {"format": mime_type.replace("image/", ""), "source": {"bytes": image_content}} - } - sub_messages.append(sub_message_dict) - - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - if message.tool_calls: - message_dict = { - "role": "assistant", - "content": [ - { - "toolUse": { - "toolUseId": message.tool_calls[0].id, - "name": message.tool_calls[0].function.name, - "input": json.loads(message.tool_calls[0].function.arguments), - } - } - ], - } - else: - message_dict = {"role": "assistant", "content": [{"text": message.content}]} - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = [{"text": message.content}] - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = { - "role": "user", - "content": [ - { - "toolResult": { - "toolUseId": message.tool_call_id, - "content": [{"json": {"text": message.content}}], - } - } - ], - } - else: - raise ValueError(f"Got unknown type {message}") - return message_dict - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage] | str, - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages or message string - :param tools: tools for tool calling - :return:md = genai.GenerativeModel(model) - """ - prefix = model.split(".")[0] - model_name = model.split(".")[1] - - if isinstance(prompt_messages, str): - prompt = prompt_messages - else: - prompt = self._convert_messages_to_prompt(prompt_messages, prefix, model_name) - - return self._get_num_tokens_by_gpt2(prompt) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - required_params = {} - if "anthropic" in model: - required_params = { - "max_tokens": 32, - } - elif "ai21" in model: - # ValidationException: Malformed input request: #/temperature: expected type: Number, - # found: Null#/maxTokens: expected type: Integer, found: Null#/topP: expected type: Number, found: Null, - # please reformat your input and try again. - required_params = { - "temperature": 0.7, - "topP": 0.9, - "maxTokens": 32, - } - - try: - ping_message = UserPromptMessage(content="ping") - self._invoke( - model=model, - credentials=credentials, - prompt_messages=[ping_message], - model_parameters=required_params, - stream=False, - ) - - except ClientError as ex: - error_code = ex.response["Error"]["Code"] - full_error_msg = f"{error_code}: {ex.response['Error']['Message']}" - raise CredentialsValidateFailedError(str(self._map_client_to_invoke_error(error_code, full_error_msg))) - - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _convert_one_message_to_text( - self, message: PromptMessage, model_prefix: str, model_name: Optional[str] = None - ) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt_prefix = "" - human_prompt_postfix = "" - ai_prompt = "" - - content = message.content - - if isinstance(message, UserPromptMessage): - body = content - if isinstance(content, list): - body = "".join([c.data for c in content if c.type == PromptMessageContentType.TEXT]) - message_text = f"{human_prompt_prefix} {body} {human_prompt_postfix}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage): - message_text = content - elif isinstance(message, ToolPromptMessage): - message_text = f"{human_prompt_prefix} {message.content}" - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - def _convert_messages_to_prompt( - self, messages: list[PromptMessage], model_prefix: str, model_name: Optional[str] = None - ) -> str: - """ - Format a list of messages into a full prompt for the Anthropic, Amazon and Llama models - - :param messages: List of PromptMessage to combine. - :param model_name: specific model name.Optional,just to distinguish llama2 and llama3 - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - if not messages: - return "" - - messages = messages.copy() # don't mutate the original list - if not isinstance(messages[-1], AssistantPromptMessage): - messages.append(AssistantPromptMessage(content="")) - - text = "".join(self._convert_one_message_to_text(message, model_prefix, model_name) for message in messages) - - # trim off the trailing ' ' that might come from the "Assistant: " - return text.rstrip() - - def _create_payload( - self, - model: str, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - ): - """ - Create payload for bedrock api call depending on model provider - """ - payload = {} - model_prefix = model.split(".")[0] - model_name = model.split(".")[1] - - if model_prefix == "ai21": - payload["temperature"] = model_parameters.get("temperature") - payload["topP"] = model_parameters.get("topP") - payload["maxTokens"] = model_parameters.get("maxTokens") - payload["prompt"] = self._convert_messages_to_prompt(prompt_messages, model_prefix) - - if model_parameters.get("presencePenalty"): - payload["presencePenalty"] = {model_parameters.get("presencePenalty")} - if model_parameters.get("frequencyPenalty"): - payload["frequencyPenalty"] = {model_parameters.get("frequencyPenalty")} - if model_parameters.get("countPenalty"): - payload["countPenalty"] = {model_parameters.get("countPenalty")} - - elif model_prefix == "cohere": - payload = {**model_parameters} - payload["prompt"] = prompt_messages[0].content - payload["stream"] = stream - - else: - raise ValueError(f"Got unknown model prefix {model_prefix}") - - return payload - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: credentials kwargs - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - client_config = Config(region_name=credentials["aws_region"]) - - runtime_client = boto3.client( - service_name="bedrock-runtime", - config=client_config, - aws_access_key_id=credentials.get("aws_access_key_id"), - aws_secret_access_key=credentials.get("aws_secret_access_key"), - ) - - model_prefix = model.split(".")[0] - payload = self._create_payload(model, prompt_messages, model_parameters, stop, stream) - - # need workaround for ai21 models which doesn't support streaming - if stream and model_prefix != "ai21": - invoke = runtime_client.invoke_model_with_response_stream - else: - invoke = runtime_client.invoke_model - - try: - body_jsonstr = json.dumps(payload) - response = invoke(modelId=model, contentType="application/json", accept="*/*", body=body_jsonstr) - except ClientError as ex: - error_code = ex.response["Error"]["Code"] - full_error_msg = f"{error_code}: {ex.response['Error']['Message']}" - raise self._map_client_to_invoke_error(error_code, full_error_msg) - - except (EndpointConnectionError, NoRegionError, ServiceNotInRegionError) as ex: - raise InvokeConnectionError(str(ex)) - - except UnknownServiceError as ex: - raise InvokeServerUnavailableError(str(ex)) - - except Exception as ex: - raise InvokeError(str(ex)) - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_response( - self, model: str, credentials: dict, response: dict, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - response_body = json.loads(response.get("body").read().decode("utf-8")) - - finish_reason = response_body.get("error") - - if finish_reason is not None: - raise InvokeError(finish_reason) - - # get output text and calculate num tokens based on model / provider - model_prefix = model.split(".")[0] - - if model_prefix == "ai21": - output = response_body.get("completions")[0].get("data").get("text") - prompt_tokens = len(response_body.get("prompt").get("tokens")) - completion_tokens = len(response_body.get("completions")[0].get("data").get("tokens")) - - elif model_prefix == "cohere": - output = response_body.get("generations")[0].get("text") - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, output or "") - - else: - raise ValueError(f"Got unknown model prefix {model_prefix} when handling block response") - - # construct assistant message from output - assistant_prompt_message = AssistantPromptMessage(content=output) - - # calculate usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # construct response - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - - return result - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: dict, prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - model_prefix = model.split(".")[0] - if model_prefix == "ai21": - response_body = json.loads(response.get("body").read().decode("utf-8")) - - content = response_body.get("completions")[0].get("data").get("text") - finish_reason = response_body.get("completions")[0].get("finish_reason") - - prompt_tokens = len(response_body.get("prompt").get("tokens")) - completion_tokens = len(response_body.get("completions")[0].get("data").get("tokens")) - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, message=AssistantPromptMessage(content=content), finish_reason=finish_reason, usage=usage - ), - ) - return - - stream = response.get("body") - if not stream: - raise InvokeError("No response body") - - index = -1 - for event in stream: - chunk = event.get("chunk") - - if not chunk: - exception_name = next(iter(event)) - full_ex_msg = f"{exception_name}: {event[exception_name]['message']}" - raise self._map_client_to_invoke_error(exception_name, full_ex_msg) - - payload = json.loads(chunk.get("bytes").decode()) - - model_prefix = model.split(".")[0] - if model_prefix == "cohere": - content_delta = payload.get("text") - finish_reason = payload.get("finish_reason") - - else: - raise ValueError(f"Got unknown model prefix {model_prefix} when handling stream response") - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=content_delta or "", - ) - index += 1 - - if not finish_reason: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message), - ) - - else: - # get num tokens from metrics in last chunk - prompt_tokens = payload["amazon-bedrock-invocationMetrics"]["inputTokenCount"] - completion_tokens = payload["amazon-bedrock-invocationMetrics"]["outputTokenCount"] - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, message=assistant_prompt_message, finish_reason=finish_reason, usage=usage - ), - ) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the ermd = genai.GenerativeModel(model) error type thrown to the caller - The value is the md = genai.GenerativeModel(model) error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke emd = genai.GenerativeModel(model) error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [], - InvokeRateLimitError: [], - InvokeAuthorizationError: [], - InvokeBadRequestError: [], - } - - def _map_client_to_invoke_error(self, error_code: str, error_msg: str) -> type[InvokeError]: - """ - Map client error to invoke error - - :param error_code: error code - :param error_msg: error message - :return: invoke error - """ - - if error_code == "AccessDeniedException": - return InvokeAuthorizationError(error_msg) - elif error_code in {"ResourceNotFoundException", "ValidationException"}: - return InvokeBadRequestError(error_msg) - elif error_code in {"ThrottlingException", "ServiceQuotaExceededException"}: - return InvokeRateLimitError(error_msg) - elif error_code in { - "ModelTimeoutException", - "ModelErrorException", - "InternalServerException", - "ModelNotReadyException", - }: - return InvokeServerUnavailableError(error_msg) - elif error_code == "ModelStreamErrorException": - return InvokeConnectionError(error_msg) - - return InvokeError(error_msg) diff --git a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama2-13b-chat-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/meta.llama2-13b-chat-v1.yaml deleted file mode 100644 index a8d3704c15bd87..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama2-13b-chat-v1.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta.llama2-13b-chat-v1 -label: - en_US: Llama 2 Chat 13B -model_type: llm -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_gen_len - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 2048 -pricing: - input: '0.00075' - output: '0.00100' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama2-70b-chat-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/meta.llama2-70b-chat-v1.yaml deleted file mode 100644 index 77525e630b5ab9..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama2-70b-chat-v1.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta.llama2-70b-chat-v1 -label: - en_US: Llama 2 Chat 70B -model_type: llm -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_gen_len - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 2048 -pricing: - input: '0.00195' - output: '0.00256' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-405b-instruct-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-405b-instruct-v1.0.yaml deleted file mode 100644 index 401de65f89e044..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-405b-instruct-v1.0.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: meta.llama3-1-405b-instruct-v1:0 -label: - en_US: Llama 3.1 405B Instruct -model_type: llm -model_properties: - mode: completion - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - - name: top_p - use_template: top_p - default: 0.9 - - name: max_gen_len - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 2048 -pricing: - input: '0.00532' - output: '0.016' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-70b-instruct-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-70b-instruct-v1.0.yaml deleted file mode 100644 index 10bfa7b1d5cd42..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-70b-instruct-v1.0.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: meta.llama3-1-70b-instruct-v1:0 -label: - en_US: Llama 3.1 Instruct 70B -model_type: llm -model_properties: - mode: completion - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - - name: top_p - use_template: top_p - default: 0.9 - - name: max_gen_len - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 2048 -pricing: - input: '0.00265' - output: '0.0035' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-8b-instruct-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-8b-instruct-v1.0.yaml deleted file mode 100644 index 81cd53243f4445..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-1-8b-instruct-v1.0.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: meta.llama3-1-8b-instruct-v1:0 -label: - en_US: Llama 3.1 Instruct 8B -model_type: llm -model_properties: - mode: completion - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - - name: top_p - use_template: top_p - default: 0.9 - - name: max_gen_len - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 2048 -pricing: - input: '0.0003' - output: '0.0006' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-70b-instruct-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-70b-instruct-v1.yaml deleted file mode 100644 index 204662690e7bd4..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-70b-instruct-v1.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta.llama3-70b-instruct-v1:0 -label: - en_US: Llama 3 Instruct 70B -model_type: llm -model_properties: - mode: completion - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_gen_len - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 2048 -pricing: - input: '0.00265' - output: '0.0035' - unit: '0.00001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-8b-instruct-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-8b-instruct-v1.yaml deleted file mode 100644 index dd4f666a5f507c..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/meta.llama3-8b-instruct-v1.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta.llama3-8b-instruct-v1:0 -label: - en_US: Llama 3 Instruct 8B -model_type: llm -model_properties: - mode: completion - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_gen_len - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 2048 -pricing: - input: '0.0004' - output: '0.0006' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-7b-instruct-v0.2.yaml b/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-7b-instruct-v0.2.yaml deleted file mode 100644 index 175c14da37e230..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-7b-instruct-v0.2.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: mistral.mistral-7b-instruct-v0:2 -label: - en_US: Mistral 7B Instruct -model_type: llm -model_properties: - mode: completion - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - required: false - default: 0.5 - - name: top_p - use_template: top_p - required: false - default: 0.9 - - name: top_k - use_template: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 50 - max: 200 - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.00015' - output: '0.0002' - unit: '0.00001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-large-2402-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-large-2402-v1.0.yaml deleted file mode 100644 index 65eed5926b1e25..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-large-2402-v1.0.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: mistral.mistral-large-2402-v1:0 -label: - en_US: Mistral Large -model_type: llm -features: - - tool-call - - agent-thought -model_properties: - mode: completion - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - required: false - default: 0.7 - - name: top_p - use_template: top_p - required: false - default: 1 - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 4096 -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-large-2407-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-large-2407-v1.0.yaml deleted file mode 100644 index 19d7843a5730e9..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-large-2407-v1.0.yaml +++ /dev/null @@ -1,29 +0,0 @@ -model: mistral.mistral-large-2407-v1:0 -label: - en_US: Mistral Large 2 (24.07) -model_type: llm -features: - - tool-call -model_properties: - mode: completion - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - required: false - default: 0.7 - - name: top_p - use_template: top_p - required: false - default: 1 - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.003' - output: '0.009' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-small-2402-v1.0.yaml b/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-small-2402-v1.0.yaml deleted file mode 100644 index b97c2a94936d7b..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mistral-small-2402-v1.0.yaml +++ /dev/null @@ -1,29 +0,0 @@ -model: mistral.mistral-small-2402-v1:0 -label: - en_US: Mistral Small -model_type: llm -features: - - tool-call -model_properties: - mode: completion - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - required: false - default: 0.7 - - name: top_p - use_template: top_p - required: false - default: 1 - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 4096 -pricing: - input: '0.001' - output: '0.03' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mixtral-8x7b-instruct-v0.1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/mistral.mixtral-8x7b-instruct-v0.1.yaml deleted file mode 100644 index 03ec7eddaf2072..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/mistral.mixtral-8x7b-instruct-v0.1.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: mistral.mixtral-8x7b-instruct-v0:1 -label: - en_US: Mixtral 8X7B Instruct -model_type: llm -model_properties: - mode: completion - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - required: false - default: 0.5 - - name: top_p - use_template: top_p - required: false - default: 0.9 - - name: top_k - use_template: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 50 - max: 200 - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.00045' - output: '0.0007' - unit: '0.00001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-haiku-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-haiku-v1.yaml deleted file mode 100644 index 9247f46974dd40..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-haiku-v1.yaml +++ /dev/null @@ -1,59 +0,0 @@ -model: us.anthropic.claude-3-haiku-20240307-v1:0 -label: - en_US: Claude 3 Haiku(US.Cross Region Inference) -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - # docs: https://docs.anthropic.com/claude/docs/system-prompts - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.00025' - output: '0.00125' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-opus-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-opus-v1.yaml deleted file mode 100644 index f9854d51f03a81..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-opus-v1.yaml +++ /dev/null @@ -1,59 +0,0 @@ -model: us.anthropic.claude-3-opus-20240229-v1:0 -label: - en_US: Claude 3 Opus(US.Cross Region Inference) -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - # docs: https://docs.anthropic.com/claude/docs/system-prompts - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.015' - output: '0.075' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-sonnet-v1.5.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-sonnet-v1.5.yaml deleted file mode 100644 index fbcab2d5f3bdaf..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-sonnet-v1.5.yaml +++ /dev/null @@ -1,58 +0,0 @@ -model: us.anthropic.claude-3-5-sonnet-20240620-v1:0 -label: - en_US: Claude 3.5 Sonnet(US.Cross Region Inference) -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.003' - output: '0.015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-sonnet-v1.yaml b/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-sonnet-v1.yaml deleted file mode 100644 index 9f5a1501f0da75..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/llm/us.anthropic.claude-3-sonnet-v1.yaml +++ /dev/null @@ -1,58 +0,0 @@ -model: us.anthropic.claude-3-sonnet-20240229-v1:0 -label: - en_US: Claude 3 Sonnet(US.Cross Region Inference) -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.003' - output: '0.015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/text_embedding/__init__.py b/api/core/model_runtime/model_providers/bedrock/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/bedrock/text_embedding/_position.yaml b/api/core/model_runtime/model_providers/bedrock/text_embedding/_position.yaml deleted file mode 100644 index afbea06a3e2f19..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/text_embedding/_position.yaml +++ /dev/null @@ -1,4 +0,0 @@ -- amazon.titan-embed-text-v1 -- amazon.titan-embed-text-v2:0 -- cohere.embed-english-v3 -- cohere.embed-multilingual-v3 diff --git a/api/core/model_runtime/model_providers/bedrock/text_embedding/amazon.titan-embed-text-v1.yaml b/api/core/model_runtime/model_providers/bedrock/text_embedding/amazon.titan-embed-text-v1.yaml deleted file mode 100644 index e5a55971a19711..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/text_embedding/amazon.titan-embed-text-v1.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: amazon.titan-embed-text-v1 -model_type: text-embedding -model_properties: - context_size: 8192 -pricing: - input: '0.0001' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/text_embedding/amazon.titan-embed-text-v2.yaml b/api/core/model_runtime/model_providers/bedrock/text_embedding/amazon.titan-embed-text-v2.yaml deleted file mode 100644 index 5069efeb109a85..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/text_embedding/amazon.titan-embed-text-v2.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: amazon.titan-embed-text-v2:0 -model_type: text-embedding -model_properties: - context_size: 8192 -pricing: - input: '0.00002' - unit: '0.00001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/text_embedding/cohere.embed-english-v3.yaml b/api/core/model_runtime/model_providers/bedrock/text_embedding/cohere.embed-english-v3.yaml deleted file mode 100644 index d49aa2a99c3a95..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/text_embedding/cohere.embed-english-v3.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: cohere.embed-english-v3 -model_type: text-embedding -model_properties: - context_size: 512 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/bedrock/text_embedding/cohere.embed-multilingual-v3.yaml b/api/core/model_runtime/model_providers/bedrock/text_embedding/cohere.embed-multilingual-v3.yaml deleted file mode 100644 index 63bab59d2cea61..00000000000000 --- a/api/core/model_runtime/model_providers/bedrock/text_embedding/cohere.embed-multilingual-v3.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: cohere.embed-multilingual-v3 -model_type: text-embedding -model_properties: - context_size: 512 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/chatglm/__init__.py b/api/core/model_runtime/model_providers/chatglm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/chatglm/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/chatglm/_assets/icon_l_en.svg deleted file mode 100644 index a824d43d6f0f81..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/_assets/icon_l_en.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/chatglm/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/chatglm/_assets/icon_s_en.svg deleted file mode 100644 index 466b4fce57a4e9..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/_assets/icon_s_en.svg +++ /dev/null @@ -1,9 +0,0 @@ - - - - - - - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/chatglm/chatglm.py b/api/core/model_runtime/model_providers/chatglm/chatglm.py deleted file mode 100644 index 71d9a1532281bd..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/chatglm.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class ChatGLMProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `chatglm3-6b` model for validate, - model_instance.validate_credentials(model="chatglm3-6b", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/chatglm/chatglm.yaml b/api/core/model_runtime/model_providers/chatglm/chatglm.yaml deleted file mode 100644 index 0c1688c3502c7c..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/chatglm.yaml +++ /dev/null @@ -1,28 +0,0 @@ -provider: chatglm -label: - en_US: ChatGLM -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#F4F7FF" -help: - title: - en_US: Deploy ChatGLM to your local - zh_Hans: 部署您的本地 ChatGLM - url: - en_US: https://github.com/THUDM/ChatGLM3 -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_base - label: - en_US: API URL - type: text-input - required: true - placeholder: - zh_Hans: 在此输入您的 API URL - en_US: Enter your API URL diff --git a/api/core/model_runtime/model_providers/chatglm/llm/__init__.py b/api/core/model_runtime/model_providers/chatglm/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/chatglm/llm/chatglm2-6b-32k.yaml b/api/core/model_runtime/model_providers/chatglm/llm/chatglm2-6b-32k.yaml deleted file mode 100644 index d1075d74b5c489..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/llm/chatglm2-6b-32k.yaml +++ /dev/null @@ -1,21 +0,0 @@ -model: chatglm2-6b-32k -label: - en_US: ChatGLM2-6B-32K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 2000 - min: 1 - max: 32000 diff --git a/api/core/model_runtime/model_providers/chatglm/llm/chatglm2-6b.yaml b/api/core/model_runtime/model_providers/chatglm/llm/chatglm2-6b.yaml deleted file mode 100644 index e3cfeb9001d676..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/llm/chatglm2-6b.yaml +++ /dev/null @@ -1,21 +0,0 @@ -model: chatglm2-6b -label: - en_US: ChatGLM2-6B -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 2000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 256 - min: 1 - max: 2000 diff --git a/api/core/model_runtime/model_providers/chatglm/llm/chatglm3-6b-32k.yaml b/api/core/model_runtime/model_providers/chatglm/llm/chatglm3-6b-32k.yaml deleted file mode 100644 index 6f34743513b7bf..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/llm/chatglm3-6b-32k.yaml +++ /dev/null @@ -1,22 +0,0 @@ -model: chatglm3-6b-32k -label: - en_US: ChatGLM3-6B-32K -model_type: llm -features: - - tool-call - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 8000 - min: 1 - max: 32000 diff --git a/api/core/model_runtime/model_providers/chatglm/llm/chatglm3-6b.yaml b/api/core/model_runtime/model_providers/chatglm/llm/chatglm3-6b.yaml deleted file mode 100644 index d6d87e2e094849..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/llm/chatglm3-6b.yaml +++ /dev/null @@ -1,22 +0,0 @@ -model: chatglm3-6b -label: - en_US: ChatGLM3-6B -model_type: llm -features: - - tool-call - - agent-thought -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 256 - min: 1 - max: 8000 diff --git a/api/core/model_runtime/model_providers/chatglm/llm/llm.py b/api/core/model_runtime/model_providers/chatglm/llm/llm.py deleted file mode 100644 index b3eeb48e226e18..00000000000000 --- a/api/core/model_runtime/model_providers/chatglm/llm/llm.py +++ /dev/null @@ -1,507 +0,0 @@ -import logging -from collections.abc import Generator -from typing import Optional, cast - -from httpx import Timeout -from openai import ( - APIConnectionError, - APITimeoutError, - AuthenticationError, - ConflictError, - InternalServerError, - NotFoundError, - OpenAI, - PermissionDeniedError, - RateLimitError, - Stream, - UnprocessableEntityError, -) -from openai.types.chat import ChatCompletion, ChatCompletionChunk -from openai.types.chat.chat_completion_message import FunctionCall -from yarl import URL - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.utils import helper - -logger = logging.getLogger(__name__) - - -class ChatGLMLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # invoke model - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - return self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke( - model=model, - credentials=credentials, - prompt_messages=[ - UserPromptMessage(content="ping"), - ], - model_parameters={ - "max_tokens": 16, - }, - ) - except Exception as e: - raise CredentialsValidateFailedError(str(e)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [ - APIConnectionError, - APITimeoutError, - ], - InvokeServerUnavailableError: [ - InternalServerError, - ConflictError, - NotFoundError, - UnprocessableEntityError, - PermissionDeniedError, - ], - InvokeRateLimitError: [RateLimitError], - InvokeAuthorizationError: [AuthenticationError], - InvokeBadRequestError: [ValueError], - } - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - """ - Invoke large language model - - :param model: model name - :param credentials: credentials kwargs - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - - self._check_chatglm_parameters(model=model, model_parameters=model_parameters, tools=tools) - - kwargs = self._to_client_kwargs(credentials) - # init model client - client = OpenAI(**kwargs) - - extra_model_kwargs = {} - if stop: - extra_model_kwargs["stop"] = stop - - if user: - extra_model_kwargs["user"] = user - - if tools and len(tools) > 0: - extra_model_kwargs["functions"] = [helper.dump_model(tool) for tool in tools] - - result = client.chat.completions.create( - messages=[self._convert_prompt_message_to_dict(m) for m in prompt_messages], - model=model, - stream=stream, - **model_parameters, - **extra_model_kwargs, - ) - - if stream: - return self._handle_chat_generate_stream_response( - model=model, credentials=credentials, response=result, tools=tools, prompt_messages=prompt_messages - ) - - return self._handle_chat_generate_response( - model=model, credentials=credentials, response=result, tools=tools, prompt_messages=prompt_messages - ) - - def _check_chatglm_parameters(self, model: str, model_parameters: dict, tools: list[PromptMessageTool]) -> None: - if model.find("chatglm2") != -1 and tools is not None and len(tools) > 0: - raise InvokeBadRequestError("ChatGLM2 does not support function calling") - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for OpenAI Compatibility API - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - raise ValueError("User message content must be str") - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls and len(message.tool_calls) > 0: - message_dict["function_call"] = { - "name": message.tool_calls[0].function.name, - "arguments": message.tool_calls[0].function.arguments, - } - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - # check if last message is user message - message = cast(ToolPromptMessage, message) - message_dict = {"role": "function", "content": message.content} - else: - raise ValueError(f"Unknown message type {type(message)}") - - return message_dict - - def _extract_response_tool_calls( - self, response_function_calls: list[FunctionCall] - ) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_function_calls: - for response_tool_call in response_function_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.name, arguments=response_tool_call.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall(id=0, type="function", function=function) - tool_calls.append(tool_call) - - return tool_calls - - def _to_client_kwargs(self, credentials: dict) -> dict: - """ - Convert invoke kwargs to client kwargs - - :param stream: is stream response - :param model_name: model name - :param credentials: credentials dict - :param model_parameters: model parameters - :return: client kwargs - """ - client_kwargs = { - "timeout": Timeout(315.0, read=300.0, write=10.0, connect=5.0), - "api_key": "1", - "base_url": str(URL(credentials["api_base"]) / "v1"), - } - - return client_kwargs - - def _handle_chat_generate_stream_response( - self, - model: str, - credentials: dict, - response: Stream[ChatCompletionChunk], - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> Generator: - full_response = "" - - for chunk in response: - if len(chunk.choices) == 0: - continue - - delta = chunk.choices[0] - - if delta.finish_reason is None and (delta.delta.content is None or delta.delta.content == ""): - continue - - # check if there is a tool call in the response - function_calls = None - if delta.delta.function_call: - function_calls = [delta.delta.function_call] - - assistant_message_tool_calls = self._extract_response_tool_calls(function_calls or []) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=delta.delta.content or "", tool_calls=assistant_message_tool_calls - ) - - if delta.finish_reason is not None: - # temp_assistant_prompt_message is used to calculate usage - temp_assistant_prompt_message = AssistantPromptMessage( - content=full_response, tool_calls=assistant_message_tool_calls - ) - - prompt_tokens = self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - completion_tokens = self._num_tokens_from_messages(messages=[temp_assistant_prompt_message], tools=[]) - - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=prompt_tokens, - completion_tokens=completion_tokens, - ) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - usage=usage, - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - ), - ) - - full_response += delta.delta.content - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - response: ChatCompletion, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response - """ - if len(response.choices) == 0: - raise InvokeServerUnavailableError("Empty response") - assistant_message = response.choices[0].message - - # convert function call to tool call - function_calls = assistant_message.function_call - tool_calls = self._extract_response_tool_calls([function_calls] if function_calls else []) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_message.content, tool_calls=tool_calls) - - prompt_tokens = self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - completion_tokens = self._num_tokens_from_messages(messages=[assistant_prompt_message], tools=tools) - - usage = self._calc_response_usage( - model=model, credentials=credentials, prompt_tokens=prompt_tokens, completion_tokens=completion_tokens - ) - - response = LLMResult( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=response.system_fingerprint, - usage=usage, - message=assistant_prompt_message, - ) - - return response - - def _num_tokens_from_string(self, text: str, tools: Optional[list[PromptMessageTool]] = None) -> int: - """ - Calculate num tokens for text completion model with tiktoken package. - - :param model: model name - :param text: prompt text - :param tools: tools for tool calling - :return: number of tokens - """ - num_tokens = self._get_num_tokens_by_gpt2(text) - - if tools: - num_tokens += self._num_tokens_for_tools(tools) - - return num_tokens - - def _num_tokens_from_messages( - self, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None - ) -> int: - """Calculate num tokens for chatglm2 and chatglm3 with GPT2 tokenizer. - - it's too complex to calculate num tokens for chatglm2 and chatglm3 with ChatGLM tokenizer, - As a temporary solution we use GPT2 tokenizer instead. - - """ - - def tokens(text: str): - return self._get_num_tokens_by_gpt2(text) - - tokens_per_message = 3 - tokens_per_name = 1 - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - value = text - - if key == "function_call": - for t_key, t_value in value.items(): - num_tokens += tokens(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += tokens(f_key) - num_tokens += tokens(f_value) - else: - num_tokens += tokens(t_key) - num_tokens += tokens(t_value) - else: - num_tokens += tokens(str(value)) - - if key == "name": - num_tokens += tokens_per_name - - # every reply is primed with assistant - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(tools) - - return num_tokens - - def _num_tokens_for_tools(self, tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for tool calling - - :param encoding: encoding - :param tools: tools for tool calling - :return: number of tokens - """ - - def tokens(text: str): - return self._get_num_tokens_by_gpt2(text) - - num_tokens = 0 - for tool in tools: - # calculate num tokens for function object - num_tokens += tokens("name") - num_tokens += tokens(tool.name) - num_tokens += tokens("description") - num_tokens += tokens(tool.description) - parameters = tool.parameters - num_tokens += tokens("parameters") - num_tokens += tokens("type") - num_tokens += tokens(parameters.get("type")) - if "properties" in parameters: - num_tokens += tokens("properties") - for key, value in parameters.get("properties").items(): - num_tokens += tokens(key) - for field_key, field_value in value.items(): - num_tokens += tokens(field_key) - if field_key == "enum": - for enum_field in field_value: - num_tokens += 3 - num_tokens += tokens(enum_field) - else: - num_tokens += tokens(field_key) - num_tokens += tokens(str(field_value)) - if "required" in parameters: - num_tokens += tokens("required") - for required_field in parameters["required"]: - num_tokens += 3 - num_tokens += tokens(required_field) - - return num_tokens diff --git a/api/core/model_runtime/model_providers/cohere/__init__.py b/api/core/model_runtime/model_providers/cohere/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/cohere/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/cohere/_assets/icon_l_en.svg deleted file mode 100644 index 9c176896fe872c..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/_assets/icon_l_en.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/cohere/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/cohere/_assets/icon_s_en.svg deleted file mode 100644 index 28fe96d390245c..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/_assets/icon_s_en.svg +++ /dev/null @@ -1,16 +0,0 @@ - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/cohere/cohere.py b/api/core/model_runtime/model_providers/cohere/cohere.py deleted file mode 100644 index 8394a45fcf9ca1..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/cohere.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class CohereProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.RERANK) - - # Use `rerank-english-v2.0` model for validate, - model_instance.validate_credentials(model="rerank-english-v2.0", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/cohere/cohere.yaml b/api/core/model_runtime/model_providers/cohere/cohere.yaml deleted file mode 100644 index bd40057fe97495..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/cohere.yaml +++ /dev/null @@ -1,90 +0,0 @@ -provider: cohere -label: - zh_Hans: Cohere - en_US: Cohere -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#ECE9E3" -help: - title: - en_US: Get your API key from cohere - zh_Hans: 从 cohere 获取 API Key - url: - en_US: https://dashboard.cohere.com/api-keys -supported_model_types: - - llm - - text-embedding - - rerank -configurate_methods: - - predefined-model - - customizable-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - zh_Hans: API Key - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - show_on: [ ] - - variable: base_url - label: - zh_Hans: API Base - en_US: API Base - type: text-input - required: false - placeholder: - zh_Hans: 在此输入您的 API Base，如 https://api.cohere.ai/v1 - en_US: Enter your API Base, e.g. https://api.cohere.ai/v1 -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: mode - show_on: - - variable: __model_type - value: llm - label: - en_US: Completion mode - type: select - required: false - default: chat - placeholder: - zh_Hans: 选择对话类型 - en_US: Select completion mode - options: - - value: completion - label: - en_US: Completion - zh_Hans: 补全 - - value: chat - label: - en_US: Chat - zh_Hans: 对话 - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: base_url - label: - zh_Hans: API Base - en_US: API Base - type: text-input - required: false - placeholder: - zh_Hans: 在此输入您的 API Base，如 https://api.cohere.ai/v1 - en_US: Enter your API Base, e.g. https://api.cohere.ai/v1 diff --git a/api/core/model_runtime/model_providers/cohere/llm/__init__.py b/api/core/model_runtime/model_providers/cohere/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/cohere/llm/_position.yaml b/api/core/model_runtime/model_providers/cohere/llm/_position.yaml deleted file mode 100644 index 42d06f49a2b394..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/_position.yaml +++ /dev/null @@ -1,10 +0,0 @@ -- command-r -- command-r-plus -- command-chat -- command-light-chat -- command-nightly-chat -- command-light-nightly-chat -- command -- command-light -- command-nightly -- command-light-nightly diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-chat.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-chat.yaml deleted file mode 100644 index 5f233f35ceeeba..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-chat.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: command-chat -label: - zh_Hans: command-chat - en_US: command-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 - - name: preamble_override - label: - zh_Hans: 前导文本 - en_US: Preamble - type: string - help: - zh_Hans: 当指定时，将使用提供的前导文本替换默认的 Cohere 前导文本。 - en_US: When specified, the default Cohere preamble will be replaced with the provided one. - required: false - - name: prompt_truncation - label: - zh_Hans: 提示截断 - en_US: Prompt Truncation - type: string - help: - zh_Hans: 指定如何构造 Prompt。当 prompt_truncation 设置为 "AUTO" 时，将会丢弃一些来自聊天记录的元素，以尝试构造一个符合模型上下文长度限制的 Prompt。 - en_US: Dictates how the prompt will be constructed. With prompt_truncation set to "AUTO", some elements from chat histories will be dropped in an attempt to construct a prompt that fits within the model's context length limit. - required: true - default: 'AUTO' - options: - - 'AUTO' - - 'OFF' -pricing: - input: '1.0' - output: '2.0' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-light-chat.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-light-chat.yaml deleted file mode 100644 index b5f00487703a0d..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-light-chat.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: command-light-chat -label: - zh_Hans: command-light-chat - en_US: command-light-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 - - name: preamble_override - label: - zh_Hans: 前导文本 - en_US: Preamble - type: string - help: - zh_Hans: 当指定时，将使用提供的前导文本替换默认的 Cohere 前导文本。 - en_US: When specified, the default Cohere preamble will be replaced with the provided one. - required: false - - name: prompt_truncation - label: - zh_Hans: 提示截断 - en_US: Prompt Truncation - type: string - help: - zh_Hans: 指定如何构造 Prompt。当 prompt_truncation 设置为 "AUTO" 时，将会丢弃一些来自聊天记录的元素，以尝试构造一个符合模型上下文长度限制的 Prompt。 - en_US: Dictates how the prompt will be constructed. With prompt_truncation set to "AUTO", some elements from chat histories will be dropped in an attempt to construct a prompt that fits within the model's context length limit. - required: true - default: 'AUTO' - options: - - 'AUTO' - - 'OFF' -pricing: - input: '0.3' - output: '0.6' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-light-nightly-chat.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-light-nightly-chat.yaml deleted file mode 100644 index 1c96b24030224d..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-light-nightly-chat.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: command-light-nightly-chat -label: - zh_Hans: command-light-nightly-chat - en_US: command-light-nightly-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 - - name: preamble_override - label: - zh_Hans: 前导文本 - en_US: Preamble - type: string - help: - zh_Hans: 当指定时，将使用提供的前导文本替换默认的 Cohere 前导文本。 - en_US: When specified, the default Cohere preamble will be replaced with the provided one. - required: false - - name: prompt_truncation - label: - zh_Hans: 提示截断 - en_US: Prompt Truncation - type: string - help: - zh_Hans: 指定如何构造 Prompt。当 prompt_truncation 设置为 "AUTO" 时，将会丢弃一些来自聊天记录的元素，以尝试构造一个符合模型上下文长度限制的 Prompt。 - en_US: Dictates how the prompt will be constructed. With prompt_truncation set to "AUTO", some elements from chat histories will be dropped in an attempt to construct a prompt that fits within the model's context length limit. - required: true - default: 'AUTO' - options: - - 'AUTO' - - 'OFF' -pricing: - input: '0.3' - output: '0.6' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-light-nightly.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-light-nightly.yaml deleted file mode 100644 index 4616f766897866..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-light-nightly.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: command-light-nightly -label: - zh_Hans: command-light-nightly - en_US: command-light-nightly -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: '0.3' - output: '0.6' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-light.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-light.yaml deleted file mode 100644 index 161756b3220d28..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-light.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: command-light -label: - zh_Hans: command-light - en_US: command-light -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: '0.3' - output: '0.6' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-nightly-chat.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-nightly-chat.yaml deleted file mode 100644 index 739e09e72e9e66..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-nightly-chat.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: command-nightly-chat -label: - zh_Hans: command-nightly-chat - en_US: command-nightly-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 - - name: preamble_override - label: - zh_Hans: 前导文本 - en_US: Preamble - type: string - help: - zh_Hans: 当指定时，将使用提供的前导文本替换默认的 Cohere 前导文本。 - en_US: When specified, the default Cohere preamble will be replaced with the provided one. - required: false - - name: prompt_truncation - label: - zh_Hans: 提示截断 - en_US: Prompt Truncation - type: string - help: - zh_Hans: 指定如何构造 Prompt。当 prompt_truncation 设置为 "AUTO" 时，将会丢弃一些来自聊天记录的元素，以尝试构造一个符合模型上下文长度限制的 Prompt。 - en_US: Dictates how the prompt will be constructed. With prompt_truncation set to "AUTO", some elements from chat histories will be dropped in an attempt to construct a prompt that fits within the model's context length limit. - required: true - default: 'AUTO' - options: - - 'AUTO' - - 'OFF' -pricing: - input: '1.0' - output: '2.0' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-nightly.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-nightly.yaml deleted file mode 100644 index 1e025e40c4b453..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-nightly.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: command-nightly -label: - zh_Hans: command-nightly - en_US: command-nightly -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: '1.0' - output: '2.0' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-r-plus.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-r-plus.yaml deleted file mode 100644 index 617e6853ea6518..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-r-plus.yaml +++ /dev/null @@ -1,45 +0,0 @@ -model: command-r-plus -label: - en_US: command-r-plus -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: '3' - output: '15' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command-r.yaml b/api/core/model_runtime/model_providers/cohere/llm/command-r.yaml deleted file mode 100644 index c36680443b7a4c..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command-r.yaml +++ /dev/null @@ -1,45 +0,0 @@ -model: command-r -label: - en_US: command-r -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: '0.5' - output: '1.5' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/command.yaml b/api/core/model_runtime/model_providers/cohere/llm/command.yaml deleted file mode 100644 index 0cac7c35ea140b..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/command.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: command -label: - zh_Hans: command - en_US: command -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: '1.0' - output: '2.0' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/llm/llm.py b/api/core/model_runtime/model_providers/cohere/llm/llm.py deleted file mode 100644 index 3863ad33081962..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/llm/llm.py +++ /dev/null @@ -1,733 +0,0 @@ -import json -import logging -from collections.abc import Generator, Iterator -from typing import Optional, Union, cast - -import cohere -from cohere import ( - ChatMessage, - ChatStreamRequestToolResultsItem, - GenerateStreamedResponse, - GenerateStreamedResponse_StreamEnd, - GenerateStreamedResponse_StreamError, - GenerateStreamedResponse_TextGeneration, - Generation, - NonStreamedChatResponse, - StreamedChatResponse, - StreamedChatResponse_StreamEnd, - StreamedChatResponse_TextGeneration, - StreamedChatResponse_ToolCallsGeneration, - Tool, - ToolCall, - ToolParameterDefinitionsValue, -) -from cohere.core import RequestOptions - -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageContentType, - PromptMessageRole, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, I18nObject, ModelType -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -logger = logging.getLogger(__name__) - - -class CohereLargeLanguageModel(LargeLanguageModel): - """ - Model class for Cohere large language model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # get model mode - model_mode = self.get_model_mode(model, credentials) - - if model_mode == LLMMode.CHAT: - return self._chat_generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - else: - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - stop=stop, - stream=stream, - user=user, - ) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - # get model mode - model_mode = self.get_model_mode(model) - - try: - if model_mode == LLMMode.CHAT: - return self._num_tokens_from_messages(model, credentials, prompt_messages) - else: - return self._num_tokens_from_string(model, credentials, prompt_messages[0].content) - except Exception as e: - raise self._transform_invoke_error(e) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # get model mode - model_mode = self.get_model_mode(model) - - if model_mode == LLMMode.CHAT: - self._chat_generate( - model=model, - credentials=credentials, - prompt_messages=[UserPromptMessage(content="ping")], - model_parameters={ - "max_tokens": 20, - "temperature": 0, - }, - stream=False, - ) - else: - self._generate( - model=model, - credentials=credentials, - prompt_messages=[UserPromptMessage(content="ping")], - model_parameters={ - "max_tokens": 20, - "temperature": 0, - }, - stream=False, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke llm model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # initialize client - client = cohere.Client(credentials.get("api_key"), base_url=credentials.get("base_url")) - - if stop: - model_parameters["end_sequences"] = stop - - if stream: - response = client.generate_stream( - prompt=prompt_messages[0].content, - model=model, - **model_parameters, - request_options=RequestOptions(max_retries=0), - ) - - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - else: - response = client.generate( - prompt=prompt_messages[0].content, - model=model, - **model_parameters, - request_options=RequestOptions(max_retries=0), - ) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_response( - self, model: str, credentials: dict, response: Generation, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - assistant_text = response.generations[0].text - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_text) - - # calculate num tokens - prompt_tokens = int(response.meta.billed_units.input_tokens) - completion_tokens = int(response.meta.billed_units.output_tokens) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - response = LLMResult( - model=model, prompt_messages=prompt_messages, message=assistant_prompt_message, usage=usage - ) - - return response - - def _handle_generate_stream_response( - self, - model: str, - credentials: dict, - response: Iterator[GenerateStreamedResponse], - prompt_messages: list[PromptMessage], - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator - """ - index = 1 - full_assistant_content = "" - for chunk in response: - if isinstance(chunk, GenerateStreamedResponse_TextGeneration): - chunk = cast(GenerateStreamedResponse_TextGeneration, chunk) - text = chunk.text - - if text is None: - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=text) - - full_assistant_content += text - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - ), - ) - - index += 1 - elif isinstance(chunk, GenerateStreamedResponse_StreamEnd): - chunk = cast(GenerateStreamedResponse_StreamEnd, chunk) - - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(model, credentials, prompt_messages) - completion_tokens = self._num_tokens_from_messages( - model, credentials, [AssistantPromptMessage(content=full_assistant_content)] - ) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=AssistantPromptMessage(content=""), - finish_reason=chunk.finish_reason, - usage=usage, - ), - ) - break - elif isinstance(chunk, GenerateStreamedResponse_StreamError): - chunk = cast(GenerateStreamedResponse_StreamError, chunk) - raise InvokeBadRequestError(chunk.err) - - def _chat_generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke llm chat model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # initialize client - client = cohere.Client(credentials.get("api_key"), base_url=credentials.get("base_url")) - - if stop: - model_parameters["stop_sequences"] = stop - - if tools: - if len(tools) == 1: - raise ValueError("Cohere tool call requires at least two tools to be specified.") - - model_parameters["tools"] = self._convert_tools(tools) - - message, chat_histories, tool_results = self._convert_prompt_messages_to_message_and_chat_histories( - prompt_messages - ) - - if tool_results: - model_parameters["tool_results"] = tool_results - - # chat model - real_model = model - if self.get_model_schema(model, credentials).fetch_from == FetchFrom.PREDEFINED_MODEL: - real_model = model.removesuffix("-chat") - - if stream: - response = client.chat_stream( - message=message, - chat_history=chat_histories, - model=real_model, - **model_parameters, - request_options=RequestOptions(max_retries=0), - ) - - return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages) - else: - response = client.chat( - message=message, - chat_history=chat_histories, - model=real_model, - **model_parameters, - request_options=RequestOptions(max_retries=0), - ) - - return self._handle_chat_generate_response(model, credentials, response, prompt_messages) - - def _handle_chat_generate_response( - self, model: str, credentials: dict, response: NonStreamedChatResponse, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - assistant_text = response.text - - tool_calls = [] - if response.tool_calls: - for cohere_tool_call in response.tool_calls: - tool_call = AssistantPromptMessage.ToolCall( - id=cohere_tool_call.name, - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=cohere_tool_call.name, arguments=json.dumps(cohere_tool_call.parameters) - ), - ) - tool_calls.append(tool_call) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_text, tool_calls=tool_calls) - - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(model, credentials, prompt_messages) - completion_tokens = self._num_tokens_from_messages(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - response = LLMResult( - model=model, prompt_messages=prompt_messages, message=assistant_prompt_message, usage=usage - ) - - return response - - def _handle_chat_generate_stream_response( - self, - model: str, - credentials: dict, - response: Iterator[StreamedChatResponse], - prompt_messages: list[PromptMessage], - ) -> Generator: - """ - Handle llm chat stream response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator - """ - - def final_response( - full_text: str, - tool_calls: list[AssistantPromptMessage.ToolCall], - index: int, - finish_reason: Optional[str] = None, - ) -> LLMResultChunk: - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(model, credentials, prompt_messages) - - full_assistant_prompt_message = AssistantPromptMessage(content=full_text, tool_calls=tool_calls) - completion_tokens = self._num_tokens_from_messages(model, credentials, [full_assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - return LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=AssistantPromptMessage(content="", tool_calls=tool_calls), - finish_reason=finish_reason, - usage=usage, - ), - ) - - index = 1 - full_assistant_content = "" - tool_calls = [] - for chunk in response: - if isinstance(chunk, StreamedChatResponse_TextGeneration): - chunk = cast(StreamedChatResponse_TextGeneration, chunk) - text = chunk.text - - if text is None: - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=text) - - full_assistant_content += text - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - ), - ) - - index += 1 - elif isinstance(chunk, StreamedChatResponse_ToolCallsGeneration): - chunk = cast(StreamedChatResponse_ToolCallsGeneration, chunk) - if chunk.tool_calls: - for cohere_tool_call in chunk.tool_calls: - tool_call = AssistantPromptMessage.ToolCall( - id=cohere_tool_call.name, - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=cohere_tool_call.name, arguments=json.dumps(cohere_tool_call.parameters) - ), - ) - tool_calls.append(tool_call) - elif isinstance(chunk, StreamedChatResponse_StreamEnd): - chunk = cast(StreamedChatResponse_StreamEnd, chunk) - yield final_response(full_assistant_content, tool_calls, index, chunk.finish_reason) - index += 1 - - def _convert_prompt_messages_to_message_and_chat_histories( - self, prompt_messages: list[PromptMessage] - ) -> tuple[str, list[ChatMessage], list[ChatStreamRequestToolResultsItem]]: - """ - Convert prompt messages to message and chat histories - :param prompt_messages: prompt messages - :return: - """ - chat_histories = [] - latest_tool_call_n_outputs = [] - for prompt_message in prompt_messages: - if prompt_message.role == PromptMessageRole.ASSISTANT: - prompt_message = cast(AssistantPromptMessage, prompt_message) - if prompt_message.tool_calls: - for tool_call in prompt_message.tool_calls: - latest_tool_call_n_outputs.append( - ChatStreamRequestToolResultsItem( - call=ToolCall( - name=tool_call.function.name, parameters=json.loads(tool_call.function.arguments) - ), - outputs=[], - ) - ) - else: - cohere_prompt_message = self._convert_prompt_message_to_dict(prompt_message) - if cohere_prompt_message: - chat_histories.append(cohere_prompt_message) - elif prompt_message.role == PromptMessageRole.TOOL: - prompt_message = cast(ToolPromptMessage, prompt_message) - if latest_tool_call_n_outputs: - i = 0 - for tool_call_n_outputs in latest_tool_call_n_outputs: - if tool_call_n_outputs.call.name == prompt_message.tool_call_id: - latest_tool_call_n_outputs[i] = ChatStreamRequestToolResultsItem( - call=ToolCall( - name=tool_call_n_outputs.call.name, parameters=tool_call_n_outputs.call.parameters - ), - outputs=[{"result": prompt_message.content}], - ) - break - i += 1 - else: - cohere_prompt_message = self._convert_prompt_message_to_dict(prompt_message) - if cohere_prompt_message: - chat_histories.append(cohere_prompt_message) - - if latest_tool_call_n_outputs: - new_latest_tool_call_n_outputs = [] - for tool_call_n_outputs in latest_tool_call_n_outputs: - if tool_call_n_outputs.outputs: - new_latest_tool_call_n_outputs.append(tool_call_n_outputs) - - latest_tool_call_n_outputs = new_latest_tool_call_n_outputs - - # get latest message from chat histories and pop it - if len(chat_histories) > 0: - latest_message = chat_histories.pop() - message = latest_message.message - else: - raise ValueError("Prompt messages is empty") - - return message, chat_histories, latest_tool_call_n_outputs - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> Optional[ChatMessage]: - """ - Convert PromptMessage to dict for Cohere model - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - chat_message = ChatMessage(role="USER", message=message.content) - else: - sub_message_text = "" - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_text += message_content.data - - chat_message = ChatMessage(role="USER", message=sub_message_text) - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - if not message.content: - return None - chat_message = ChatMessage(role="CHATBOT", message=message.content) - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - chat_message = ChatMessage(role="USER", message=message.content) - elif isinstance(message, ToolPromptMessage): - return None - else: - raise ValueError(f"Got unknown type {message}") - - return chat_message - - def _convert_tools(self, tools: list[PromptMessageTool]) -> list[Tool]: - """ - Convert tools to Cohere model - """ - cohere_tools = [] - for tool in tools: - properties = tool.parameters["properties"] - required_properties = tool.parameters["required"] - - parameter_definitions = {} - for p_key, p_val in properties.items(): - required = False - if p_key in required_properties: - required = True - - desc = p_val["description"] - if "enum" in p_val: - desc += f"; Only accepts one of the following predefined options: [{', '.join(p_val['enum'])}]" - - parameter_definitions[p_key] = ToolParameterDefinitionsValue( - description=desc, type=p_val["type"], required=required - ) - - cohere_tool = Tool( - name=tool.name, description=tool.description, parameter_definitions=parameter_definitions - ) - - cohere_tools.append(cohere_tool) - - return cohere_tools - - def _num_tokens_from_string(self, model: str, credentials: dict, text: str) -> int: - """ - Calculate num tokens for text completion model. - - :param model: model name - :param credentials: credentials - :param text: prompt text - :return: number of tokens - """ - # initialize client - client = cohere.Client(credentials.get("api_key"), base_url=credentials.get("base_url")) - - response = client.tokenize(text=text, model=model) - - return len(response.tokens) - - def _num_tokens_from_messages(self, model: str, credentials: dict, messages: list[PromptMessage]) -> int: - """Calculate num tokens Cohere model.""" - calc_messages = [] - for message in messages: - cohere_message = self._convert_prompt_message_to_dict(message) - if cohere_message: - calc_messages.append(cohere_message) - message_strs = [f"{message.role}: {message.message}" for message in calc_messages] - message_str = "\n".join(message_strs) - - real_model = model - if self.get_model_schema(model, credentials).fetch_from == FetchFrom.PREDEFINED_MODEL: - real_model = model.removesuffix("-chat") - - return self._num_tokens_from_string(real_model, credentials, message_str) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - Cohere supports fine-tuning of their models. This method returns the schema of the base model - but renamed to the fine-tuned model name. - - :param model: model name - :param credentials: credentials - - :return: model schema - """ - # get model schema - models = self.predefined_models() - model_map = {model.model: model for model in models} - - mode = credentials.get("mode") - - if mode == "chat": - base_model_schema = model_map["command-light-chat"] - else: - base_model_schema = model_map["command-light"] - - base_model_schema = cast(AIModelEntity, base_model_schema) - - base_model_schema_features = base_model_schema.features or [] - base_model_schema_model_properties = base_model_schema.model_properties or {} - base_model_schema_parameters_rules = base_model_schema.parameter_rules or [] - - entity = AIModelEntity( - model=model, - label=I18nObject(zh_Hans=model, en_US=model), - model_type=ModelType.LLM, - features=list(base_model_schema_features), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties=dict(base_model_schema_model_properties.items()), - parameter_rules=list(base_model_schema_parameters_rules), - pricing=base_model_schema.pricing, - ) - - return entity - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [cohere.errors.service_unavailable_error.ServiceUnavailableError], - InvokeServerUnavailableError: [cohere.errors.internal_server_error.InternalServerError], - InvokeRateLimitError: [cohere.errors.too_many_requests_error.TooManyRequestsError], - InvokeAuthorizationError: [ - cohere.errors.unauthorized_error.UnauthorizedError, - cohere.errors.forbidden_error.ForbiddenError, - ], - InvokeBadRequestError: [ - cohere.core.api_error.ApiError, - cohere.errors.bad_request_error.BadRequestError, - cohere.errors.not_found_error.NotFoundError, - ], - } diff --git a/api/core/model_runtime/model_providers/cohere/rerank/__init__.py b/api/core/model_runtime/model_providers/cohere/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/cohere/rerank/_position.yaml b/api/core/model_runtime/model_providers/cohere/rerank/_position.yaml deleted file mode 100644 index 4dd58fc1708b0a..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/rerank/_position.yaml +++ /dev/null @@ -1,4 +0,0 @@ -- rerank-english-v2.0 -- rerank-english-v3.0 -- rerank-multilingual-v2.0 -- rerank-multilingual-v3.0 diff --git a/api/core/model_runtime/model_providers/cohere/rerank/rerank-english-v2.0.yaml b/api/core/model_runtime/model_providers/cohere/rerank/rerank-english-v2.0.yaml deleted file mode 100644 index 70b4a91a0dc7c5..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/rerank/rerank-english-v2.0.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: rerank-english-v2.0 -model_type: rerank -model_properties: - context_size: 5120 diff --git a/api/core/model_runtime/model_providers/cohere/rerank/rerank-english-v3.0.yaml b/api/core/model_runtime/model_providers/cohere/rerank/rerank-english-v3.0.yaml deleted file mode 100644 index 3779f0b6c25dd8..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/rerank/rerank-english-v3.0.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: rerank-english-v3.0 -model_type: rerank -model_properties: - context_size: 5120 diff --git a/api/core/model_runtime/model_providers/cohere/rerank/rerank-multilingual-v2.0.yaml b/api/core/model_runtime/model_providers/cohere/rerank/rerank-multilingual-v2.0.yaml deleted file mode 100644 index c9b90387cf04bc..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/rerank/rerank-multilingual-v2.0.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: rerank-multilingual-v2.0 -model_type: rerank -model_properties: - context_size: 5120 diff --git a/api/core/model_runtime/model_providers/cohere/rerank/rerank-multilingual-v3.0.yaml b/api/core/model_runtime/model_providers/cohere/rerank/rerank-multilingual-v3.0.yaml deleted file mode 100644 index 4f6690ba7685b5..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/rerank/rerank-multilingual-v3.0.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: rerank-multilingual-v3.0 -model_type: rerank -model_properties: - context_size: 5120 diff --git a/api/core/model_runtime/model_providers/cohere/rerank/rerank.py b/api/core/model_runtime/model_providers/cohere/rerank/rerank.py deleted file mode 100644 index aba8fedbc097e5..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/rerank/rerank.py +++ /dev/null @@ -1,125 +0,0 @@ -from typing import Optional - -import cohere -from cohere.core import RequestOptions - -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - - -class CohereRerankModel(RerankModel): - """ - Model class for Cohere rerank model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n - :param user: unique user id - :return: rerank result - """ - if len(docs) == 0: - return RerankResult(model=model, docs=docs) - - # initialize client - client = cohere.Client(credentials.get("api_key"), base_url=credentials.get("base_url")) - response = client.rerank( - query=query, - documents=docs, - model=model, - top_n=top_n, - return_documents=True, - request_options=RequestOptions(max_retries=0), - ) - - rerank_documents = [] - for idx, result in enumerate(response.results): - # format document - rerank_document = RerankDocument( - index=result.index, - text=result.document.text, - score=result.relevance_score, - ) - - # score threshold check - if score_threshold is not None: - if result.relevance_score >= score_threshold: - rerank_documents.append(rerank_document) - else: - rerank_documents.append(rerank_document) - - return RerankResult(model=model, docs=rerank_documents) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self.invoke( - model=model, - credentials=credentials, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [cohere.errors.service_unavailable_error.ServiceUnavailableError], - InvokeServerUnavailableError: [cohere.errors.internal_server_error.InternalServerError], - InvokeRateLimitError: [cohere.errors.too_many_requests_error.TooManyRequestsError], - InvokeAuthorizationError: [ - cohere.errors.unauthorized_error.UnauthorizedError, - cohere.errors.forbidden_error.ForbiddenError, - ], - InvokeBadRequestError: [ - cohere.core.api_error.ApiError, - cohere.errors.bad_request_error.BadRequestError, - cohere.errors.not_found_error.NotFoundError, - ], - } diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/__init__.py b/api/core/model_runtime/model_providers/cohere/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/_position.yaml b/api/core/model_runtime/model_providers/cohere/text_embedding/_position.yaml deleted file mode 100644 index 967a946f343985..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/_position.yaml +++ /dev/null @@ -1,7 +0,0 @@ -- embed-multilingual-v3.0 -- embed-multilingual-light-v3.0 -- embed-english-v3.0 -- embed-english-light-v3.0 -- embed-multilingual-v2.0 -- embed-english-v2.0 -- embed-english-light-v2.0 diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-light-v2.0.yaml b/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-light-v2.0.yaml deleted file mode 100644 index 8d2aaf17378a0c..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-light-v2.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embed-english-light-v2.0 -model_type: text-embedding -model_properties: - context_size: 1024 - max_chunks: 48 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-light-v3.0.yaml b/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-light-v3.0.yaml deleted file mode 100644 index 43b79922e33137..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-light-v3.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embed-english-light-v3.0 -model_type: text-embedding -model_properties: - context_size: 384 - max_chunks: 48 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-v2.0.yaml b/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-v2.0.yaml deleted file mode 100644 index acee82b202059a..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-v2.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embed-english-v2.0 -model_type: text-embedding -model_properties: - context_size: 4096 - max_chunks: 48 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-v3.0.yaml b/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-v3.0.yaml deleted file mode 100644 index 0ad713253e1394..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-english-v3.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embed-english-v3.0 -model_type: text-embedding -model_properties: - context_size: 1024 - max_chunks: 48 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-light-v3.0.yaml b/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-light-v3.0.yaml deleted file mode 100644 index c25306723376c8..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-light-v3.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embed-multilingual-light-v3.0 -model_type: text-embedding -model_properties: - context_size: 384 - max_chunks: 48 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-v2.0.yaml b/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-v2.0.yaml deleted file mode 100644 index 4dbc37d5e82c76..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-v2.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embed-multilingual-v2.0 -model_type: text-embedding -model_properties: - context_size: 768 - max_chunks: 48 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-v3.0.yaml b/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-v3.0.yaml deleted file mode 100644 index ec689ada1b7d68..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/embed-multilingual-v3.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embed-multilingual-v3.0 -model_type: text-embedding -model_properties: - context_size: 1024 - max_chunks: 48 -pricing: - input: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/deepseek/__init__.py b/api/core/model_runtime/model_providers/deepseek/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/deepseek/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/deepseek/_assets/icon_l_en.svg deleted file mode 100644 index 425494404f7e63..00000000000000 --- a/api/core/model_runtime/model_providers/deepseek/_assets/icon_l_en.svg +++ /dev/null @@ -1,22 +0,0 @@ - - - Created with Pixso. - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/deepseek/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/deepseek/_assets/icon_s_en.svg deleted file mode 100644 index aa854a7504c15c..00000000000000 --- a/api/core/model_runtime/model_providers/deepseek/_assets/icon_s_en.svg +++ /dev/null @@ -1,3 +0,0 @@ - - - diff --git a/api/core/model_runtime/model_providers/deepseek/deepseek.py b/api/core/model_runtime/model_providers/deepseek/deepseek.py deleted file mode 100644 index 10feef897272db..00000000000000 --- a/api/core/model_runtime/model_providers/deepseek/deepseek.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class DeepSeekProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `deepseek-chat` model for validate, - # no matter what model you pass in, text completion model or chat model - model_instance.validate_credentials(model="deepseek-chat", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/deepseek/deepseek.yaml b/api/core/model_runtime/model_providers/deepseek/deepseek.yaml deleted file mode 100644 index 16abd358d6dc70..00000000000000 --- a/api/core/model_runtime/model_providers/deepseek/deepseek.yaml +++ /dev/null @@ -1,41 +0,0 @@ -provider: deepseek -label: - en_US: deepseek - zh_Hans: 深度求索 -description: - en_US: Models provided by deepseek, such as deepseek-chat、deepseek-coder. - zh_Hans: 深度求索提供的模型，例如 deepseek-chat、deepseek-coder 。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#c0cdff" -help: - title: - en_US: Get your API Key from deepseek - zh_Hans: 从深度求索获取 API Key - url: - en_US: https://platform.deepseek.com/api_keys -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: endpoint_url - label: - zh_Hans: 自定义 API endpoint 地址 - en_US: Custom API endpoint URL - type: text-input - required: false - placeholder: - zh_Hans: Base URL, e.g. https://api.deepseek.com/v1 or https://api.deepseek.com - en_US: Base URL, e.g. https://api.deepseek.com/v1 or https://api.deepseek.com diff --git a/api/core/model_runtime/model_providers/deepseek/llm/__init__.py b/api/core/model_runtime/model_providers/deepseek/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/deepseek/llm/_position.yaml b/api/core/model_runtime/model_providers/deepseek/llm/_position.yaml deleted file mode 100644 index 43d03f2ee9598a..00000000000000 --- a/api/core/model_runtime/model_providers/deepseek/llm/_position.yaml +++ /dev/null @@ -1,2 +0,0 @@ -- deepseek-chat -- deepseek-coder diff --git a/api/core/model_runtime/model_providers/deepseek/llm/deepseek-chat.yaml b/api/core/model_runtime/model_providers/deepseek/llm/deepseek-chat.yaml deleted file mode 100644 index 4973ac8ad6981c..00000000000000 --- a/api/core/model_runtime/model_providers/deepseek/llm/deepseek-chat.yaml +++ /dev/null @@ -1,78 +0,0 @@ -model: deepseek-chat -label: - zh_Hans: deepseek-chat - en_US: deepseek-chat -model_type: llm -features: - - agent-thought - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 1 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 4096 - min: 1 - max: 8192 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 1 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. - - name: logprobs - help: - zh_Hans: 是否返回所输出 token 的对数概率。如果为 true，则在 message 的 content 中返回每个输出 token 的对数概率。 - en_US: Whether to return the log probability of the output token. If true, returns the log probability of each output token in the content of message . - type: boolean - - name: top_logprobs - type: int - default: 0 - min: 0 - max: 20 - help: - zh_Hans: 一个介于 0 到 20 之间的整数 N，指定每个输出位置返回输出概率 top N 的 token，且返回这些 token 的对数概率。指定此参数时，logprobs 必须为 true。 - en_US: An integer N between 0 and 20, specifying that each output position returns the top N tokens with output probability, and returns the logarithmic probability of these tokens. When specifying this parameter, logprobs must be true. - - name: frequency_penalty - use_template: frequency_penalty - default: 0 - min: -2.0 - max: 2.0 - help: - zh_Hans: 介于 -2.0 和 2.0 之间的数字。如果该值为正，那么新 token 会根据其在已有文本中的出现频率受到相应的惩罚，降低模型重复相同内容的可能性。 - en_US: A number between -2.0 and 2.0. If the value is positive, new tokens are penalized based on their frequency of occurrence in existing text, reducing the likelihood that the model will repeat the same content. - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '1' - output: '2' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/deepseek/llm/deepseek-coder.yaml b/api/core/model_runtime/model_providers/deepseek/llm/deepseek-coder.yaml deleted file mode 100644 index caafeadadd999e..00000000000000 --- a/api/core/model_runtime/model_providers/deepseek/llm/deepseek-coder.yaml +++ /dev/null @@ -1,28 +0,0 @@ -model: deepseek-coder -label: - zh_Hans: deepseek-coder - en_US: deepseek-coder -model_type: llm -features: - - agent-thought - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 4096 - default: 1024 diff --git a/api/core/model_runtime/model_providers/deepseek/llm/llm.py b/api/core/model_runtime/model_providers/deepseek/llm/llm.py deleted file mode 100644 index 6d0a3ee2628ea2..00000000000000 --- a/api/core/model_runtime/model_providers/deepseek/llm/llm.py +++ /dev/null @@ -1,116 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union -from urllib.parse import urlparse - -import tiktoken - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import ( - PromptMessage, - PromptMessageTool, -) -from core.model_runtime.model_providers.openai.llm.llm import OpenAILargeLanguageModel - - -class DeepSeekLargeLanguageModel(OpenAILargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials) - - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - # refactored from openai model runtime, use cl100k_base for calculate token number - def _num_tokens_from_string(self, model: str, text: str, tools: Optional[list[PromptMessageTool]] = None) -> int: - """ - Calculate num tokens for text completion model with tiktoken package. - - :param model: model name - :param text: prompt text - :param tools: tools for tool calling - :return: number of tokens - """ - encoding = tiktoken.get_encoding("cl100k_base") - num_tokens = len(encoding.encode(text)) - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - # refactored from openai model runtime, use cl100k_base for calculate token number - def _num_tokens_from_messages( - self, model: str, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None - ) -> int: - """Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package. - - Official documentation: https://github.com/openai/openai-cookbook/blob/ - main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb""" - encoding = tiktoken.get_encoding("cl100k_base") - tokens_per_message = 3 - tokens_per_name = 1 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - # Cast str(value) in case the message value is not a string - # This occurs with function messages - # TODO: The current token calculation method for the image type is not implemented, - # which need to download the image and then get the resolution for calculation, - # and will increase the request delay - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += len(encoding.encode(t_key)) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += len(encoding.encode(f_key)) - num_tokens += len(encoding.encode(f_value)) - else: - num_tokens += len(encoding.encode(t_key)) - num_tokens += len(encoding.encode(t_value)) - else: - num_tokens += len(encoding.encode(str(value))) - - if key == "name": - num_tokens += tokens_per_name - - # every reply is primed with assistant - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - @staticmethod - def _add_custom_parameters(credentials: dict) -> None: - credentials["mode"] = "chat" - credentials["openai_api_key"] = credentials["api_key"] - if "endpoint_url" not in credentials or credentials["endpoint_url"] == "": - credentials["openai_api_base"] = "https://api.deepseek.com" - else: - parsed_url = urlparse(credentials["endpoint_url"]) - credentials["openai_api_base"] = f"{parsed_url.scheme}://{parsed_url.netloc}" diff --git a/api/core/model_runtime/model_providers/fireworks/__init__.py b/api/core/model_runtime/model_providers/fireworks/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/fireworks/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/fireworks/_assets/icon_l_en.svg deleted file mode 100644 index 582605cc422cce..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/_assets/icon_l_en.svg +++ /dev/null @@ -1,3 +0,0 @@ - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/fireworks/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/fireworks/_assets/icon_s_en.svg deleted file mode 100644 index 86eeba66f9290a..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/_assets/icon_s_en.svg +++ /dev/null @@ -1,5 +0,0 @@ - - - - - diff --git a/api/core/model_runtime/model_providers/fireworks/_common.py b/api/core/model_runtime/model_providers/fireworks/_common.py deleted file mode 100644 index 378ced3a4019ba..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/_common.py +++ /dev/null @@ -1,52 +0,0 @@ -from collections.abc import Mapping - -import openai - -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) - - -class _CommonFireworks: - def _to_credential_kwargs(self, credentials: Mapping) -> dict: - """ - Transform credentials to kwargs for model instance - - :param credentials: - :return: - """ - credentials_kwargs = { - "api_key": credentials["fireworks_api_key"], - "base_url": "https://api.fireworks.ai/inference/v1", - "max_retries": 1, - } - - return credentials_kwargs - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [openai.APIConnectionError, openai.APITimeoutError], - InvokeServerUnavailableError: [openai.InternalServerError], - InvokeRateLimitError: [openai.RateLimitError], - InvokeAuthorizationError: [openai.AuthenticationError, openai.PermissionDeniedError], - InvokeBadRequestError: [ - openai.BadRequestError, - openai.NotFoundError, - openai.UnprocessableEntityError, - openai.APIError, - ], - } diff --git a/api/core/model_runtime/model_providers/fireworks/fireworks.py b/api/core/model_runtime/model_providers/fireworks/fireworks.py deleted file mode 100644 index 15f25badab994f..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/fireworks.py +++ /dev/null @@ -1,27 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class FireworksProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - model_instance.validate_credentials( - model="accounts/fireworks/models/llama-v3p1-8b-instruct", credentials=credentials - ) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/fireworks/llm/__init__.py b/api/core/model_runtime/model_providers/fireworks/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/fireworks/llm/_position.yaml b/api/core/model_runtime/model_providers/fireworks/llm/_position.yaml deleted file mode 100644 index 9f7c1af68cef72..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/_position.yaml +++ /dev/null @@ -1,16 +0,0 @@ -- llama-v3p1-405b-instruct -- llama-v3p1-70b-instruct -- llama-v3p1-8b-instruct -- llama-v3-70b-instruct -- mixtral-8x22b-instruct -- mixtral-8x7b-instruct -- firefunction-v2 -- firefunction-v1 -- gemma2-9b-it -- llama-v3-70b-instruct-hf -- llama-v3-8b-instruct -- llama-v3-8b-instruct-hf -- mixtral-8x7b-instruct-hf -- mythomax-l2-13b -- phi-3-vision-128k-instruct -- yi-large diff --git a/api/core/model_runtime/model_providers/fireworks/llm/firefunction-v1.yaml b/api/core/model_runtime/model_providers/fireworks/llm/firefunction-v1.yaml deleted file mode 100644 index f6bac12832d646..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/firefunction-v1.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/firefunction-v1 -label: - zh_Hans: Firefunction V1 - en_US: Firefunction V1 -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.5' - output: '0.5' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/firefunction-v2.yaml b/api/core/model_runtime/model_providers/fireworks/llm/firefunction-v2.yaml deleted file mode 100644 index 2979cb46d572a3..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/firefunction-v2.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/firefunction-v2 -label: - zh_Hans: Firefunction V2 - en_US: Firefunction V2 -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.9' - output: '0.9' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/gemma2-9b-it.yaml b/api/core/model_runtime/model_providers/fireworks/llm/gemma2-9b-it.yaml deleted file mode 100644 index ee41a7e2fdc3d5..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/gemma2-9b-it.yaml +++ /dev/null @@ -1,45 +0,0 @@ -model: accounts/fireworks/models/gemma2-9b-it -label: - zh_Hans: Gemma2 9B Instruct - en_US: Gemma2 9B Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.2' - output: '0.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-70b-instruct-hf.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-70b-instruct-hf.yaml deleted file mode 100644 index 2ae89b88165d12..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-70b-instruct-hf.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3-70b-instruct-hf -label: - zh_Hans: Llama3 70B Instruct(HF version) - en_US: Llama3 70B Instruct(HF version) -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.9' - output: '0.9' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-70b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-70b-instruct.yaml deleted file mode 100644 index 7c24b08ca5cca1..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-70b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3-70b-instruct -label: - zh_Hans: Llama3 70B Instruct - en_US: Llama3 70B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.9' - output: '0.9' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-8b-instruct-hf.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-8b-instruct-hf.yaml deleted file mode 100644 index 83507ef3e5276e..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-8b-instruct-hf.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3-8b-instruct-hf -label: - zh_Hans: Llama3 8B Instruct(HF version) - en_US: Llama3 8B Instruct(HF version) -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.2' - output: '0.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-8b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-8b-instruct.yaml deleted file mode 100644 index d8ac9537b80e7f..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3-8b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3-8b-instruct -label: - zh_Hans: Llama3 8B Instruct - en_US: Llama3 8B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.2' - output: '0.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-405b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-405b-instruct.yaml deleted file mode 100644 index c4ddb3e9246d4a..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-405b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3p1-405b-instruct -label: - zh_Hans: Llama3.1 405B Instruct - en_US: Llama3.1 405B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '3' - output: '3' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-70b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-70b-instruct.yaml deleted file mode 100644 index 62f84f87fa5609..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-70b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3p1-70b-instruct -label: - zh_Hans: Llama3.1 70B Instruct - en_US: Llama3.1 70B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.2' - output: '0.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-8b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-8b-instruct.yaml deleted file mode 100644 index 9bb99c91b65b0b..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p1-8b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3p1-8b-instruct -label: - zh_Hans: Llama3.1 8B Instruct - en_US: Llama3.1 8B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.2' - output: '0.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llm.py b/api/core/model_runtime/model_providers/fireworks/llm/llm.py deleted file mode 100644 index 2dcf1adba64518..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llm.py +++ /dev/null @@ -1,610 +0,0 @@ -import logging -from collections.abc import Generator -from typing import Optional, Union, cast - -from openai import OpenAI, Stream -from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessageToolCall -from openai.types.chat.chat_completion_chunk import ChoiceDeltaFunctionCall, ChoiceDeltaToolCall -from openai.types.chat.chat_completion_message import FunctionCall - -from core.model_runtime.callbacks.base_callback import Callback -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.fireworks._common import _CommonFireworks - -logger = logging.getLogger(__name__) - -FIREWORKS_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. -The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - - -{{instructions}} - -""" # noqa: E501 - - -class FireworksLargeLanguageModel(_CommonFireworks, LargeLanguageModel): - """ - Model class for Fireworks large language model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - - return self._chat_generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def _code_block_mode_wrapper( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - callbacks: Optional[list[Callback]] = None, - ) -> Union[LLMResult, Generator]: - """ - Code block mode wrapper for invoking large language model - """ - if "response_format" in model_parameters and model_parameters["response_format"] in {"JSON", "XML"}: - stop = stop or [] - self._transform_chat_json_prompts( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - response_format=model_parameters["response_format"], - ) - model_parameters.pop("response_format") - - return self._invoke( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def _transform_chat_json_prompts( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - response_format: str = "JSON", - ) -> None: - """ - Transform json prompts - """ - if stop is None: - stop = [] - if "```\n" not in stop: - stop.append("```\n") - if "\n```" not in stop: - stop.append("\n```") - - if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): - prompt_messages[0] = SystemPromptMessage( - content=FIREWORKS_BLOCK_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content).replace( - "{{block}}", response_format - ) - ) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}\n")) - else: - prompt_messages.insert( - 0, - SystemPromptMessage( - content=FIREWORKS_BLOCK_MODE_PROMPT.replace( - "{{instructions}}", f"Please output a valid {response_format} object." - ).replace("{{block}}", response_format) - ), - ) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}")) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - return self._num_tokens_from_messages(model, prompt_messages, tools) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - client.chat.completions.create( - messages=[{"role": "user", "content": "ping"}], model=model, temperature=0, max_tokens=10, stream=False - ) - except Exception as e: - raise CredentialsValidateFailedError(str(e)) - - def _chat_generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - extra_model_kwargs = {} - - if tools: - extra_model_kwargs["functions"] = [ - {"name": tool.name, "description": tool.description, "parameters": tool.parameters} for tool in tools - ] - - if stop: - extra_model_kwargs["stop"] = stop - - if user: - extra_model_kwargs["user"] = user - - # chat model - response = client.chat.completions.create( - messages=[self._convert_prompt_message_to_dict(m) for m in prompt_messages], - model=model, - stream=stream, - **model_parameters, - **extra_model_kwargs, - ) - - if stream: - return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages, tools) - return self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools) - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - response: ChatCompletion, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response - """ - assistant_message = response.choices[0].message - # assistant_message_tool_calls = assistant_message.tool_calls - assistant_message_function_call = assistant_message.function_call - - # extract tool calls from response - # tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - function_call = self._extract_response_function_call(assistant_message_function_call) - tool_calls = [function_call] if function_call else [] - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_message.content, tool_calls=tool_calls) - - # calculate num tokens - if response.usage: - # transform usage - prompt_tokens = response.usage.prompt_tokens - completion_tokens = response.usage.completion_tokens - else: - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(model, prompt_messages, tools) - completion_tokens = self._num_tokens_from_messages(model, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - response = LLMResult( - model=response.model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - system_fingerprint=response.system_fingerprint, - ) - - return response - - def _handle_chat_generate_stream_response( - self, - model: str, - credentials: dict, - response: Stream[ChatCompletionChunk], - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> Generator: - """ - Handle llm chat stream response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response chunk generator - """ - full_assistant_content = "" - delta_assistant_message_function_call_storage: Optional[ChoiceDeltaFunctionCall] = None - prompt_tokens = 0 - completion_tokens = 0 - final_tool_calls = [] - final_chunk = LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=""), - ), - ) - - for chunk in response: - if len(chunk.choices) == 0: - if chunk.usage: - # calculate num tokens - prompt_tokens = chunk.usage.prompt_tokens - completion_tokens = chunk.usage.completion_tokens - continue - - delta = chunk.choices[0] - has_finish_reason = delta.finish_reason is not None - - if ( - not has_finish_reason - and (delta.delta.content is None or delta.delta.content == "") - and delta.delta.function_call is None - ): - continue - - # assistant_message_tool_calls = delta.delta.tool_calls - assistant_message_function_call = delta.delta.function_call - - # extract tool calls from response - if delta_assistant_message_function_call_storage is not None: - # handle process of stream function call - if assistant_message_function_call: - # message has not ended ever - delta_assistant_message_function_call_storage.arguments += assistant_message_function_call.arguments - continue - else: - # message has ended - assistant_message_function_call = delta_assistant_message_function_call_storage - delta_assistant_message_function_call_storage = None - else: - if assistant_message_function_call: - # start of stream function call - delta_assistant_message_function_call_storage = assistant_message_function_call - if delta_assistant_message_function_call_storage.arguments is None: - delta_assistant_message_function_call_storage.arguments = "" - if not has_finish_reason: - continue - - # tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - function_call = self._extract_response_function_call(assistant_message_function_call) - tool_calls = [function_call] if function_call else [] - if tool_calls: - final_tool_calls.extend(tool_calls) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=delta.delta.content or "", tool_calls=tool_calls) - - full_assistant_content += delta.delta.content or "" - - if has_finish_reason: - final_chunk = LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - ), - ) - else: - yield LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - ), - ) - - if not prompt_tokens: - prompt_tokens = self._num_tokens_from_messages(model, prompt_messages, tools) - - if not completion_tokens: - full_assistant_prompt_message = AssistantPromptMessage( - content=full_assistant_content, tool_calls=final_tool_calls - ) - completion_tokens = self._num_tokens_from_messages(model, [full_assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - final_chunk.delta.usage = usage - - yield final_chunk - - def _extract_response_tool_calls( - self, response_tool_calls: list[ChatCompletionMessageToolCall | ChoiceDeltaToolCall] - ) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_tool_calls: - for response_tool_call in response_tool_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.function.name, arguments=response_tool_call.function.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call.id, type=response_tool_call.type, function=function - ) - tool_calls.append(tool_call) - - return tool_calls - - def _extract_response_function_call( - self, response_function_call: FunctionCall | ChoiceDeltaFunctionCall - ) -> AssistantPromptMessage.ToolCall: - """ - Extract function call from response - - :param response_function_call: response function call - :return: tool call - """ - tool_call = None - if response_function_call: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_function_call.name, arguments=response_function_call.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_function_call.name, type="function", function=function - ) - - return tool_call - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for Fireworks API - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": {"url": message_content.data, "detail": message_content.detail.value}, - } - sub_messages.append(sub_message_dict) - - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls: - # message_dict["tool_calls"] = [tool_call.dict() for tool_call in - # message.tool_calls] - function_call = message.tool_calls[0] - message_dict["function_call"] = { - "name": function_call.function.name, - "arguments": function_call.function.arguments, - } - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - # message_dict = { - # "role": "tool", - # "content": message.content, - # "tool_call_id": message.tool_call_id - # } - message_dict = {"role": "function", "content": message.content, "name": message.tool_call_id} - else: - raise ValueError(f"Got unknown type {message}") - - if message.name: - message_dict["name"] = message.name - - return message_dict - - def _num_tokens_from_messages( - self, - model: str, - messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - credentials: dict = None, - ) -> int: - """ - Approximate num tokens with GPT2 tokenizer. - """ - - tokens_per_message = 3 - tokens_per_name = 1 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - # Cast str(value) in case the message value is not a string - # This occurs with function messages - # TODO: The current token calculation method for the image type is not implemented, - # which need to download the image and then get the resolution for calculation, - # and will increase the request delay - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += self._get_num_tokens_by_gpt2(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += self._get_num_tokens_by_gpt2(f_key) - num_tokens += self._get_num_tokens_by_gpt2(f_value) - else: - num_tokens += self._get_num_tokens_by_gpt2(t_key) - num_tokens += self._get_num_tokens_by_gpt2(t_value) - else: - num_tokens += self._get_num_tokens_by_gpt2(str(value)) - - if key == "name": - num_tokens += tokens_per_name - - # every reply is primed with assistant - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(tools) - - return num_tokens - - def _num_tokens_for_tools(self, tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for tool calling with tiktoken package. - - :param tools: tools for tool calling - :return: number of tokens - """ - num_tokens = 0 - for tool in tools: - num_tokens += self._get_num_tokens_by_gpt2("type") - num_tokens += self._get_num_tokens_by_gpt2("function") - num_tokens += self._get_num_tokens_by_gpt2("function") - - # calculate num tokens for function object - num_tokens += self._get_num_tokens_by_gpt2("name") - num_tokens += self._get_num_tokens_by_gpt2(tool.name) - num_tokens += self._get_num_tokens_by_gpt2("description") - num_tokens += self._get_num_tokens_by_gpt2(tool.description) - parameters = tool.parameters - num_tokens += self._get_num_tokens_by_gpt2("parameters") - if "title" in parameters: - num_tokens += self._get_num_tokens_by_gpt2("title") - num_tokens += self._get_num_tokens_by_gpt2(parameters.get("title")) - num_tokens += self._get_num_tokens_by_gpt2("type") - num_tokens += self._get_num_tokens_by_gpt2(parameters.get("type")) - if "properties" in parameters: - num_tokens += self._get_num_tokens_by_gpt2("properties") - for key, value in parameters.get("properties").items(): - num_tokens += self._get_num_tokens_by_gpt2(key) - for field_key, field_value in value.items(): - num_tokens += self._get_num_tokens_by_gpt2(field_key) - if field_key == "enum": - for enum_field in field_value: - num_tokens += 3 - num_tokens += self._get_num_tokens_by_gpt2(enum_field) - else: - num_tokens += self._get_num_tokens_by_gpt2(field_key) - num_tokens += self._get_num_tokens_by_gpt2(str(field_value)) - if "required" in parameters: - num_tokens += self._get_num_tokens_by_gpt2("required") - for required_field in parameters["required"]: - num_tokens += 3 - num_tokens += self._get_num_tokens_by_gpt2(required_field) - - return num_tokens diff --git a/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x22b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x22b-instruct.yaml deleted file mode 100644 index 87d977e26cf1b2..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x22b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/mixtral-8x22b-instruct -label: - zh_Hans: Mixtral MoE 8x22B Instruct - en_US: Mixtral MoE 8x22B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 65536 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '1.2' - output: '1.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x7b-instruct-hf.yaml b/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x7b-instruct-hf.yaml deleted file mode 100644 index e3d5a90858c5ae..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x7b-instruct-hf.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/mixtral-8x7b-instruct-hf -label: - zh_Hans: Mixtral MoE 8x7B Instruct(HF version) - en_US: Mixtral MoE 8x7B Instruct(HF version) -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.5' - output: '0.5' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x7b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x7b-instruct.yaml deleted file mode 100644 index 45f632ceff2cfc..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/mixtral-8x7b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/mixtral-8x7b-instruct -label: - zh_Hans: Mixtral MoE 8x7B Instruct - en_US: Mixtral MoE 8x7B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.5' - output: '0.5' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/mythomax-l2-13b.yaml b/api/core/model_runtime/model_providers/fireworks/llm/mythomax-l2-13b.yaml deleted file mode 100644 index 9c3486ba10751b..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/mythomax-l2-13b.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/mythomax-l2-13b -label: - zh_Hans: MythoMax L2 13b - en_US: MythoMax L2 13b -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.2' - output: '0.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/phi-3-vision-128k-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/phi-3-vision-128k-instruct.yaml deleted file mode 100644 index e399f2edb1b1bd..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/phi-3-vision-128k-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/phi-3-vision-128k-instruct -label: - zh_Hans: Phi3.5 Vision Instruct - en_US: Phi3.5 Vision Instruct -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.2' - output: '0.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/yi-large.yaml b/api/core/model_runtime/model_providers/fireworks/llm/yi-large.yaml deleted file mode 100644 index bb4b6f994ec12a..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/yi-large.yaml +++ /dev/null @@ -1,45 +0,0 @@ -model: accounts/yi-01-ai/models/yi-large -label: - zh_Hans: Yi-Large - en_US: Yi-Large -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '3' - output: '3' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fishaudio/__init__.py b/api/core/model_runtime/model_providers/fishaudio/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/fishaudio/_assets/fishaudio_l_en.svg b/api/core/model_runtime/model_providers/fishaudio/_assets/fishaudio_l_en.svg deleted file mode 100644 index d6f7723bd5ca4c..00000000000000 --- a/api/core/model_runtime/model_providers/fishaudio/_assets/fishaudio_l_en.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/fishaudio/_assets/fishaudio_s_en.svg b/api/core/model_runtime/model_providers/fishaudio/_assets/fishaudio_s_en.svg deleted file mode 100644 index d6f7723bd5ca4c..00000000000000 --- a/api/core/model_runtime/model_providers/fishaudio/_assets/fishaudio_s_en.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/fishaudio/fishaudio.py b/api/core/model_runtime/model_providers/fishaudio/fishaudio.py deleted file mode 100644 index 3bc4b533e0815a..00000000000000 --- a/api/core/model_runtime/model_providers/fishaudio/fishaudio.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class FishAudioProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - For debugging purposes, this method now always passes validation. - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.TTS) - model_instance.validate_credentials(credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/fishaudio/tts/__init__.py b/api/core/model_runtime/model_providers/fishaudio/tts/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/fishaudio/tts/tts.py b/api/core/model_runtime/model_providers/fishaudio/tts/tts.py deleted file mode 100644 index 895a7a914c97de..00000000000000 --- a/api/core/model_runtime/model_providers/fishaudio/tts/tts.py +++ /dev/null @@ -1,158 +0,0 @@ -from typing import Optional - -import httpx - -from core.model_runtime.errors.invoke import InvokeBadRequestError, InvokeError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.tts_model import TTSModel - - -class FishAudioText2SpeechModel(TTSModel): - """ - Model class for Fish.audio Text to Speech model. - """ - - def get_tts_model_voices(self, model: str, credentials: dict, language: Optional[str] = None) -> list: - api_base = credentials.get("api_base", "https://api.fish.audio") - api_key = credentials.get("api_key") - use_public_models = credentials.get("use_public_models", "false") == "true" - - params = { - "self": str(not use_public_models).lower(), - "page_size": "100", - } - - if language is not None: - if "-" in language: - language = language.split("-")[0] - params["language"] = language - - results = httpx.get( - f"{api_base}/model", - headers={"Authorization": f"Bearer {api_key}"}, - params=params, - ) - - results.raise_for_status() - data = results.json() - - return [{"name": i["title"], "value": i["_id"]} for i in data["items"]] - - def _invoke( - self, - model: str, - tenant_id: str, - credentials: dict, - content_text: str, - voice: str, - user: Optional[str] = None, - ) -> any: - """ - Invoke text2speech model - - :param model: model name - :param tenant_id: user tenant id - :param credentials: model credentials - :param voice: model timbre - :param content_text: text content to be translated - :param user: unique user id - :return: generator yielding audio chunks - """ - - return self._tts_invoke_streaming( - model=model, - credentials=credentials, - content_text=content_text, - voice=voice, - ) - - def validate_credentials(self, credentials: dict, user: Optional[str] = None) -> None: - """ - Validate credentials for text2speech model - - :param credentials: model credentials - :param user: unique user id - """ - - try: - self.get_tts_model_voices( - None, - credentials={ - "api_key": credentials["api_key"], - "api_base": credentials["api_base"], - # Disable public models will trigger a 403 error if user is not logged in - "use_public_models": "false", - }, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _tts_invoke_streaming(self, model: str, credentials: dict, content_text: str, voice: str) -> any: - """ - Invoke streaming text2speech model - :param model: model name - :param credentials: model credentials - :param content_text: text content to be translated - :param voice: ID of the reference audio (if any) - :return: generator yielding audio chunks - """ - - try: - word_limit = self._get_model_word_limit(model, credentials) - if len(content_text) > word_limit: - sentences = self._split_text_into_sentences(content_text, max_length=word_limit) - else: - sentences = [content_text.strip()] - - for i in range(len(sentences)): - yield from self._tts_invoke_streaming_sentence( - credentials=credentials, content_text=sentences[i], voice=voice - ) - - except Exception as ex: - raise InvokeBadRequestError(str(ex)) - - def _tts_invoke_streaming_sentence(self, credentials: dict, content_text: str, voice: Optional[str] = None) -> any: - """ - Invoke streaming text2speech model - - :param credentials: model credentials - :param content_text: text content to be translated - :param voice: ID of the reference audio (if any) - :return: generator yielding audio chunks - """ - api_key = credentials.get("api_key") - api_url = credentials.get("api_base", "https://api.fish.audio") - latency = credentials.get("latency") - - if not api_key: - raise InvokeBadRequestError("API key is required") - - with httpx.stream( - "POST", - api_url + "/v1/tts", - json={"text": content_text, "reference_id": voice, "latency": latency}, - headers={ - "Authorization": f"Bearer {api_key}", - }, - timeout=None, - ) as response: - if response.status_code != 200: - raise InvokeBadRequestError(f"Error: {response.status_code} - {response.text}") - yield from response.iter_bytes() - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeBadRequestError: [ - httpx.HTTPStatusError, - ], - } diff --git a/api/core/model_runtime/model_providers/fishaudio/tts/tts.yaml b/api/core/model_runtime/model_providers/fishaudio/tts/tts.yaml deleted file mode 100644 index b4a446a95701c1..00000000000000 --- a/api/core/model_runtime/model_providers/fishaudio/tts/tts.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: tts-default -model_type: tts -model_properties: - word_limit: 1000 - audio_type: 'mp3' diff --git a/api/core/model_runtime/model_providers/google/__init__.py b/api/core/model_runtime/model_providers/google/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/google/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/google/_assets/icon_l_en.svg deleted file mode 100644 index bb23bffcf1c039..00000000000000 --- a/api/core/model_runtime/model_providers/google/_assets/icon_l_en.svg +++ /dev/null @@ -1,15 +0,0 @@ - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/google/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/google/_assets/icon_s_en.svg deleted file mode 100644 index c5c608cd7c603d..00000000000000 --- a/api/core/model_runtime/model_providers/google/_assets/icon_s_en.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/google/google.py b/api/core/model_runtime/model_providers/google/google.py deleted file mode 100644 index 70f56a8337b2e6..00000000000000 --- a/api/core/model_runtime/model_providers/google/google.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class GoogleProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `gemini-pro` model for validate, - model_instance.validate_credentials(model="gemini-pro", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/google/google.yaml b/api/core/model_runtime/model_providers/google/google.yaml deleted file mode 100644 index 69d4e371c462fa..00000000000000 --- a/api/core/model_runtime/model_providers/google/google.yaml +++ /dev/null @@ -1,31 +0,0 @@ -provider: google -label: - en_US: Google -description: - en_US: Google's Gemini model. - zh_Hans: 谷歌提供的 Gemini 模型. -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#FCFDFF" -help: - title: - en_US: Get your API Key from Google - zh_Hans: 从 Google 获取 API Key - url: - en_US: https://ai.google.dev/ -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: google_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/google/llm/__init__.py b/api/core/model_runtime/model_providers/google/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-8b-exp-0827.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-8b-exp-0827.yaml deleted file mode 100644 index 4e0209890a336a..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-8b-exp-0827.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-flash-8b-exp-0827 -label: - en_US: Gemini 1.5 Flash 8B 0827 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-exp-0827.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-exp-0827.yaml deleted file mode 100644 index faabc5e4d13a73..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-exp-0827.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-flash-exp-0827 -label: - en_US: Gemini 1.5 Flash 0827 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-latest.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-latest.yaml deleted file mode 100644 index a22fcca9419b91..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-latest.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-flash-latest -label: - en_US: Gemini 1.5 Flash Latest -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-exp-0801.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-exp-0801.yaml deleted file mode 100644 index 97c68f7a18d91e..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-exp-0801.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-pro-exp-0801 -label: - en_US: Gemini 1.5 Pro 0801 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 2097152 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-exp-0827.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-exp-0827.yaml deleted file mode 100644 index 860e4816a163cc..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-exp-0827.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-pro-exp-0827 -label: - en_US: Gemini 1.5 Pro 0827 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 2097152 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-latest.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-latest.yaml deleted file mode 100644 index d1bf7d269de765..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-latest.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-pro-latest -label: - en_US: Gemini 1.5 Pro Latest -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 2097152 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-pro-vision.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-pro-vision.yaml deleted file mode 100644 index 2d213d56adb9c7..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-pro-vision.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: gemini-pro-vision -label: - en_US: Gemini Pro Vision -model_type: llm -features: - - vision -model_properties: - mode: chat - context_size: 12288 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-pro.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-pro.yaml deleted file mode 100644 index e2f487c1ee9219..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-pro.yaml +++ /dev/null @@ -1,47 +0,0 @@ -model: gemini-pro -label: - en_US: Gemini Pro -model_type: llm -features: - - agent-thought - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 30720 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 2048 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/llm.py b/api/core/model_runtime/model_providers/google/llm/llm.py deleted file mode 100644 index e686ad08d9d355..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/llm.py +++ /dev/null @@ -1,443 +0,0 @@ -import base64 -import io -import json -import logging -from collections.abc import Generator -from typing import Optional, Union, cast - -import google.ai.generativelanguage as glm -import google.generativeai as genai -import requests -from google.api_core import exceptions -from google.generativeai.client import _ClientManager -from google.generativeai.types import ContentType, GenerateContentResponse -from google.generativeai.types.content_types import to_part -from PIL import Image - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -logger = logging.getLogger(__name__) - -GEMINI_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. -The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - - -{{instructions}} - -""" # noqa: E501 - - -class GoogleLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # invoke model - return self._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return:md = genai.GenerativeModel(model) - """ - prompt = self._convert_messages_to_prompt(prompt_messages) - - return self._get_num_tokens_by_gpt2(prompt) - - def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str: - """ - Format a list of messages into a full prompt for the Google model - - :param messages: List of PromptMessage to combine. - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - return text.rstrip() - - def _convert_tools_to_glm_tool(self, tools: list[PromptMessageTool]) -> glm.Tool: - """ - Convert tool messages to glm tools - - :param tools: tool messages - :return: glm tools - """ - return glm.Tool( - function_declarations=[ - glm.FunctionDeclaration( - name=tool.name, - parameters=glm.Schema( - type=glm.Type.OBJECT, - properties={ - key: { - "type_": value.get("type", "string").upper(), - "description": value.get("description", ""), - "enum": value.get("enum", []), - } - for key, value in tool.parameters.get("properties", {}).items() - }, - required=tool.parameters.get("required", []), - ), - ) - for tool in tools - ] - ) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - - try: - ping_message = SystemPromptMessage(content="ping") - self._generate(model, credentials, [ping_message], {"max_tokens_to_sample": 5}) - - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: credentials kwargs - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - config_kwargs = model_parameters.copy() - config_kwargs["max_output_tokens"] = config_kwargs.pop("max_tokens_to_sample", None) - - if stop: - config_kwargs["stop_sequences"] = stop - - google_model = genai.GenerativeModel(model_name=model) - - history = [] - - # hack for gemini-pro-vision, which currently does not support multi-turn chat - if model == "gemini-pro-vision": - last_msg = prompt_messages[-1] - content = self._format_message_to_glm_content(last_msg) - history.append(content) - else: - for msg in prompt_messages: # makes message roles strictly alternating - content = self._format_message_to_glm_content(msg) - if history and history[-1]["role"] == content["role"]: - history[-1]["parts"].extend(content["parts"]) - else: - history.append(content) - - # Create a new ClientManager with tenant's API key - new_client_manager = _ClientManager() - new_client_manager.configure(api_key=credentials["google_api_key"]) - new_custom_client = new_client_manager.make_client("generative") - - google_model._client = new_custom_client - - response = google_model.generate_content( - contents=history, - generation_config=genai.types.GenerationConfig(**config_kwargs), - stream=stream, - tools=self._convert_tools_to_glm_tool(tools) if tools else None, - request_options={"timeout": 600}, - ) - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_response( - self, model: str, credentials: dict, response: GenerateContentResponse, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=response.text) - - # calculate num tokens - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - - return result - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: GenerateContentResponse, prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - index = -1 - for chunk in response: - for part in chunk.parts: - assistant_prompt_message = AssistantPromptMessage(content="") - - if part.text: - assistant_prompt_message.content += part.text - - if part.function_call: - assistant_prompt_message.tool_calls = [ - AssistantPromptMessage.ToolCall( - id=part.function_call.name, - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=part.function_call.name, - arguments=json.dumps(dict(part.function_call.args.items())), - ), - ) - ] - - index += 1 - - if not response._done: - # transform assistant message to prompt message - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message), - ) - else: - # calculate num tokens - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - finish_reason=str(chunk.candidates[0].finish_reason), - usage=usage, - ), - ) - - def _convert_one_message_to_text(self, message: PromptMessage) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt = "\n\nuser:" - ai_prompt = "\n\nmodel:" - - content = message.content - if isinstance(content, list): - content = "".join(c.data for c in content if c.type != PromptMessageContentType.IMAGE) - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage | ToolPromptMessage): - message_text = f"{human_prompt} {content}" - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - def _format_message_to_glm_content(self, message: PromptMessage) -> ContentType: - """ - Format a single message into glm.Content for Google API - - :param message: one PromptMessage - :return: glm Content representation of message - """ - if isinstance(message, UserPromptMessage): - glm_content = {"role": "user", "parts": []} - if isinstance(message.content, str): - glm_content["parts"].append(to_part(message.content)) - else: - for c in message.content: - if c.type == PromptMessageContentType.TEXT: - glm_content["parts"].append(to_part(c.data)) - elif c.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, c) - if message_content.data.startswith("data:"): - metadata, base64_data = c.data.split(",", 1) - mime_type = metadata.split(";", 1)[0].split(":")[1] - else: - # fetch image data from url - try: - image_content = requests.get(message_content.data).content - with Image.open(io.BytesIO(image_content)) as img: - mime_type = f"image/{img.format.lower()}" - base64_data = base64.b64encode(image_content).decode("utf-8") - except Exception as ex: - raise ValueError(f"Failed to fetch image data from url {message_content.data}, {ex}") - blob = {"inline_data": {"mime_type": mime_type, "data": base64_data}} - glm_content["parts"].append(blob) - - return glm_content - elif isinstance(message, AssistantPromptMessage): - glm_content = {"role": "model", "parts": []} - if message.content: - glm_content["parts"].append(to_part(message.content)) - if message.tool_calls: - glm_content["parts"].append( - to_part( - glm.FunctionCall( - name=message.tool_calls[0].function.name, - args=json.loads(message.tool_calls[0].function.arguments), - ) - ) - ) - return glm_content - elif isinstance(message, SystemPromptMessage): - return {"role": "user", "parts": [to_part(message.content)]} - elif isinstance(message, ToolPromptMessage): - return { - "role": "function", - "parts": [ - glm.Part( - function_response=glm.FunctionResponse( - name=message.name, response={"response": message.content} - ) - ) - ], - } - else: - raise ValueError(f"Got unknown type {message}") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the ermd = genai.GenerativeModel(model) error type thrown to the caller - The value is the md = genai.GenerativeModel(model) error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke emd = genai.GenerativeModel(model) error mapping - """ - return { - InvokeConnectionError: [exceptions.RetryError], - InvokeServerUnavailableError: [ - exceptions.ServiceUnavailable, - exceptions.InternalServerError, - exceptions.BadGateway, - exceptions.GatewayTimeout, - exceptions.DeadlineExceeded, - ], - InvokeRateLimitError: [exceptions.ResourceExhausted, exceptions.TooManyRequests], - InvokeAuthorizationError: [ - exceptions.Unauthenticated, - exceptions.PermissionDenied, - exceptions.Unauthenticated, - exceptions.Forbidden, - ], - InvokeBadRequestError: [ - exceptions.BadRequest, - exceptions.InvalidArgument, - exceptions.FailedPrecondition, - exceptions.OutOfRange, - exceptions.NotFound, - exceptions.MethodNotAllowed, - exceptions.Conflict, - exceptions.AlreadyExists, - exceptions.Aborted, - exceptions.LengthRequired, - exceptions.PreconditionFailed, - exceptions.RequestRangeNotSatisfiable, - exceptions.Cancelled, - ], - } diff --git a/api/core/model_runtime/model_providers/groq/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/groq/_assets/icon_l_en.svg deleted file mode 100644 index 2505a5f493717b..00000000000000 --- a/api/core/model_runtime/model_providers/groq/_assets/icon_l_en.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/groq/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/groq/_assets/icon_s_en.svg deleted file mode 100644 index 087f37e4718b7a..00000000000000 --- a/api/core/model_runtime/model_providers/groq/_assets/icon_s_en.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - diff --git a/api/core/model_runtime/model_providers/groq/groq.py b/api/core/model_runtime/model_providers/groq/groq.py deleted file mode 100644 index d0d5ff68f8090e..00000000000000 --- a/api/core/model_runtime/model_providers/groq/groq.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class GroqProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="llama3-8b-8192", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/groq/groq.yaml b/api/core/model_runtime/model_providers/groq/groq.yaml deleted file mode 100644 index db17cc8bdd086a..00000000000000 --- a/api/core/model_runtime/model_providers/groq/groq.yaml +++ /dev/null @@ -1,32 +0,0 @@ -provider: groq -label: - zh_Hans: GroqCloud - en_US: GroqCloud -description: - en_US: GroqCloud provides access to the Groq Cloud API, which hosts models like LLama2 and Mixtral. - zh_Hans: GroqCloud 提供对 Groq Cloud API 的访问，其中托管了 LLama2 和 Mixtral 等模型。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#F5F5F4" -help: - title: - en_US: Get your API Key from GroqCloud - zh_Hans: 从 GroqCloud 获取 API Key - url: - en_US: https://console.groq.com/ -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/groq/llm/_position.yaml b/api/core/model_runtime/model_providers/groq/llm/_position.yaml deleted file mode 100644 index be115ca920df08..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/_position.yaml +++ /dev/null @@ -1,7 +0,0 @@ -- llama-3.1-405b-reasoning -- llama-3.1-70b-versatile -- llama-3.1-8b-instant -- llama3-70b-8192 -- llama3-8b-8192 -- mixtral-8x7b-32768 -- llama2-70b-4096 diff --git a/api/core/model_runtime/model_providers/groq/llm/llama-3.1-405b-reasoning.yaml b/api/core/model_runtime/model_providers/groq/llm/llama-3.1-405b-reasoning.yaml deleted file mode 100644 index 217785cea2d85f..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama-3.1-405b-reasoning.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama-3.1-405b-reasoning -label: - zh_Hans: Llama-3.1-405b-reasoning - en_US: Llama-3.1-405b-reasoning -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.05' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama-3.1-70b-versatile.yaml b/api/core/model_runtime/model_providers/groq/llm/llama-3.1-70b-versatile.yaml deleted file mode 100644 index ab5f6ab05efe31..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama-3.1-70b-versatile.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama-3.1-70b-versatile -label: - zh_Hans: Llama-3.1-70b-versatile - en_US: Llama-3.1-70b-versatile -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.05' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama-3.1-8b-instant.yaml b/api/core/model_runtime/model_providers/groq/llm/llama-3.1-8b-instant.yaml deleted file mode 100644 index a82e64532ee10d..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama-3.1-8b-instant.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama-3.1-8b-instant -label: - zh_Hans: Llama-3.1-8b-instant - en_US: Llama-3.1-8b-instant -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.05' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama2-70b-4096.yaml b/api/core/model_runtime/model_providers/groq/llm/llama2-70b-4096.yaml deleted file mode 100644 index 384912b0dd248e..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama2-70b-4096.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama2-70b-4096 -label: - zh_Hans: Llama-2-70B-4096 - en_US: Llama-2-70B-4096 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 -pricing: - input: '0.7' - output: '0.8' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama3-70b-8192.yaml b/api/core/model_runtime/model_providers/groq/llm/llama3-70b-8192.yaml deleted file mode 100644 index 91d0e307657911..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama3-70b-8192.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama3-70b-8192 -label: - zh_Hans: Llama-3-70B-8192 - en_US: Llama-3-70B-8192 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.59' - output: '0.79' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama3-8b-8192.yaml b/api/core/model_runtime/model_providers/groq/llm/llama3-8b-8192.yaml deleted file mode 100644 index b6154f761f4b40..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama3-8b-8192.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama3-8b-8192 -label: - zh_Hans: Llama-3-8B-8192 - en_US: Llama-3-8B-8192 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.05' - output: '0.08' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llm.py b/api/core/model_runtime/model_providers/groq/llm/llm.py deleted file mode 100644 index 352a7b519ee168..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llm.py +++ /dev/null @@ -1,31 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class GroqLargeLanguageModel(OAIAPICompatLargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials) - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - @staticmethod - def _add_custom_parameters(credentials: dict) -> None: - credentials["mode"] = "chat" - credentials["endpoint_url"] = "https://api.groq.com/openai/v1" diff --git a/api/core/model_runtime/model_providers/groq/llm/mixtral-8x7b-instruct-v0.1.yaml b/api/core/model_runtime/model_providers/groq/llm/mixtral-8x7b-instruct-v0.1.yaml deleted file mode 100644 index 0dc6678fa23424..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/mixtral-8x7b-instruct-v0.1.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: mixtral-8x7b-32768 -label: - zh_Hans: Mixtral-8x7b-Instruct-v0.1 - en_US: Mixtral-8x7b-Instruct-v0.1 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 20480 -pricing: - input: '0.27' - output: '0.27' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/huggingface_hub/__init__.py b/api/core/model_runtime/model_providers/huggingface_hub/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/huggingface_hub/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/huggingface_hub/_assets/icon_l_en.svg deleted file mode 100644 index 70135a08de5cc7..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_hub/_assets/icon_l_en.svg +++ /dev/null @@ -1,42 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/huggingface_hub/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/huggingface_hub/_assets/icon_s_en.svg deleted file mode 100644 index 5a444f127f88b6..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_hub/_assets/icon_s_en.svg +++ /dev/null @@ -1,19 +0,0 @@ - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/huggingface_hub/_common.py b/api/core/model_runtime/model_providers/huggingface_hub/_common.py deleted file mode 100644 index 3c4020b6eedf24..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_hub/_common.py +++ /dev/null @@ -1,9 +0,0 @@ -from huggingface_hub.utils import BadRequestError, HfHubHTTPError - -from core.model_runtime.errors.invoke import InvokeBadRequestError, InvokeError - - -class _CommonHuggingfaceHub: - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return {InvokeBadRequestError: [HfHubHTTPError, BadRequestError]} diff --git a/api/core/model_runtime/model_providers/huggingface_hub/huggingface_hub.py b/api/core/model_runtime/model_providers/huggingface_hub/huggingface_hub.py deleted file mode 100644 index 54d2a2bf399623..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_hub/huggingface_hub.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class HuggingfaceHubProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/huggingface_hub/huggingface_hub.yaml b/api/core/model_runtime/model_providers/huggingface_hub/huggingface_hub.yaml deleted file mode 100644 index 1df234cf268f4e..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_hub/huggingface_hub.yaml +++ /dev/null @@ -1,102 +0,0 @@ -provider: huggingface_hub -label: - en_US: Hugging Face Model -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#FFF8DC" -help: - title: - en_US: Get your API key from Hugging Face Hub - zh_Hans: 从 Hugging Face Hub 获取 API Key - url: - en_US: https://huggingface.co/settings/tokens -supported_model_types: - - llm - - text-embedding -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - credential_form_schemas: - - variable: huggingfacehub_api_type - label: - en_US: Endpoint Type - zh_Hans: 端点类型 - type: radio - required: true - default: hosted_inference_api - options: - - value: hosted_inference_api - label: - en_US: Hosted Inference API - - value: inference_endpoints - label: - en_US: Inference Endpoints - - variable: huggingfacehub_api_token - label: - en_US: API Token - zh_Hans: API Token - type: secret-input - required: true - placeholder: - en_US: Enter your Hugging Face Hub API Token here - zh_Hans: 在此输入您的 Hugging Face Hub API Token - - variable: huggingface_namespace - label: - en_US: 'User Name / Organization Name' - zh_Hans: '用户名 / 组织名称' - type: text-input - required: true - placeholder: - en_US: 'Enter your User Name / Organization Name here' - zh_Hans: '在此输入您的用户名 / 组织名称' - show_on: - - variable: __model_type - value: text-embedding - - variable: huggingfacehub_api_type - value: inference_endpoints - - variable: huggingfacehub_endpoint_url - label: - en_US: Endpoint URL - zh_Hans: 端点 URL - type: text-input - required: true - placeholder: - en_US: Enter your Endpoint URL here - zh_Hans: 在此输入您的端点 URL - show_on: - - variable: huggingfacehub_api_type - value: inference_endpoints - - variable: task_type - label: - en_US: Task - zh_Hans: Task - type: select - options: - - value: text2text-generation - label: - en_US: Text-to-Text Generation - show_on: - - variable: __model_type - value: llm - - value: text-generation - label: - en_US: Text Generation - zh_Hans: 文本生成 - show_on: - - variable: __model_type - value: llm - - value: feature-extraction - label: - en_US: Feature Extraction - show_on: - - variable: __model_type - value: text-embedding - show_on: - - variable: huggingfacehub_api_type - value: inference_endpoints diff --git a/api/core/model_runtime/model_providers/huggingface_hub/llm/__init__.py b/api/core/model_runtime/model_providers/huggingface_hub/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/huggingface_hub/llm/llm.py b/api/core/model_runtime/model_providers/huggingface_hub/llm/llm.py deleted file mode 100644 index 9d29237fdde573..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_hub/llm/llm.py +++ /dev/null @@ -1,313 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from huggingface_hub import InferenceClient -from huggingface_hub.hf_api import HfApi -from huggingface_hub.utils import BadRequestError - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - DefaultParameterName, - FetchFrom, - ModelPropertyKey, - ModelType, - ParameterRule, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.huggingface_hub._common import _CommonHuggingfaceHub - - -class HuggingfaceHubLargeLanguageModel(_CommonHuggingfaceHub, LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - client = InferenceClient(token=credentials["huggingfacehub_api_token"]) - - if credentials["huggingfacehub_api_type"] == "inference_endpoints": - model = credentials["huggingfacehub_endpoint_url"] - - if "baichuan" in model.lower(): - stream = False - - response = client.text_generation( - prompt=prompt_messages[0].content, - details=True, - stream=stream, - model=model, - stop_sequences=stop, - **model_parameters, - ) - - if stream: - return self._handle_generate_stream_response(model, credentials, prompt_messages, response) - - return self._handle_generate_response(model, credentials, prompt_messages, response) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - prompt = self._convert_messages_to_prompt(prompt_messages) - return self._get_num_tokens_by_gpt2(prompt) - - def validate_credentials(self, model: str, credentials: dict) -> None: - try: - if "huggingfacehub_api_type" not in credentials: - raise CredentialsValidateFailedError("Huggingface Hub Endpoint Type must be provided.") - - if credentials["huggingfacehub_api_type"] not in {"inference_endpoints", "hosted_inference_api"}: - raise CredentialsValidateFailedError("Huggingface Hub Endpoint Type is invalid.") - - if "huggingfacehub_api_token" not in credentials: - raise CredentialsValidateFailedError("Huggingface Hub Access Token must be provided.") - - if credentials["huggingfacehub_api_type"] == "inference_endpoints": - if "huggingfacehub_endpoint_url" not in credentials: - raise CredentialsValidateFailedError("Huggingface Hub Endpoint URL must be provided.") - - if "task_type" not in credentials: - raise CredentialsValidateFailedError("Huggingface Hub Task Type must be provided.") - elif credentials["huggingfacehub_api_type"] == "hosted_inference_api": - credentials["task_type"] = self._get_hosted_model_task_type( - credentials["huggingfacehub_api_token"], model - ) - - if credentials["task_type"] not in {"text2text-generation", "text-generation"}: - raise CredentialsValidateFailedError( - "Huggingface Hub Task Type must be one of text2text-generation, text-generation." - ) - - client = InferenceClient(token=credentials["huggingfacehub_api_token"]) - - if credentials["huggingfacehub_api_type"] == "inference_endpoints": - model = credentials["huggingfacehub_endpoint_url"] - - try: - client.text_generation(prompt="Who are you?", stream=True, model=model) - except BadRequestError as e: - raise CredentialsValidateFailedError( - "Only available for models running on with the `text-generation-inference`. " - "To learn more about the TGI project, please refer to https://github.com/huggingface/text-generation-inference." - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]: - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - model_properties={ModelPropertyKey.MODE: LLMMode.COMPLETION.value}, - parameter_rules=self._get_customizable_model_parameter_rules(), - ) - - return entity - - @staticmethod - def _get_customizable_model_parameter_rules() -> list[ParameterRule]: - temperature_rule_dict = PARAMETER_RULE_TEMPLATE.get(DefaultParameterName.TEMPERATURE).copy() - temperature_rule_dict["name"] = "temperature" - temperature_rule = ParameterRule(**temperature_rule_dict) - temperature_rule.default = 0.5 - - top_p_rule_dict = PARAMETER_RULE_TEMPLATE.get(DefaultParameterName.TOP_P).copy() - top_p_rule_dict["name"] = "top_p" - top_p_rule = ParameterRule(**top_p_rule_dict) - top_p_rule.default = 0.5 - - top_k_rule = ParameterRule( - name="top_k", - label={ - "en_US": "Top K", - "zh_Hans": "Top K", - }, - type="int", - help={ - "en_US": "The number of highest probability vocabulary tokens to keep for top-k-filtering.", - "zh_Hans": "保留的最高概率词汇标记的数量。", - }, - required=False, - default=2, - min=1, - max=10, - precision=0, - ) - - max_new_tokens = ParameterRule( - name="max_new_tokens", - label={ - "en_US": "Max New Tokens", - "zh_Hans": "最大新标记", - }, - type="int", - help={ - "en_US": "Maximum number of generated tokens.", - "zh_Hans": "生成的标记的最大数量。", - }, - required=False, - default=20, - min=1, - max=4096, - precision=0, - ) - - seed = ParameterRule( - name="seed", - label={ - "en_US": "Random sampling seed", - "zh_Hans": "随机采样种子", - }, - type="int", - help={ - "en_US": "Random sampling seed.", - "zh_Hans": "随机采样种子。", - }, - required=False, - precision=0, - ) - - repetition_penalty = ParameterRule( - name="repetition_penalty", - label={ - "en_US": "Repetition Penalty", - "zh_Hans": "重复惩罚", - }, - type="float", - help={ - "en_US": "The parameter for repetition penalty. 1.0 means no penalty.", - "zh_Hans": "重复惩罚的参数。1.0 表示没有惩罚。", - }, - required=False, - precision=1, - ) - - return [temperature_rule, top_k_rule, top_p_rule, max_new_tokens, seed, repetition_penalty] - - def _handle_generate_stream_response( - self, model: str, credentials: dict, prompt_messages: list[PromptMessage], response: Generator - ) -> Generator: - index = -1 - for chunk in response: - # skip special tokens - if chunk.token.special: - continue - - index += 1 - - assistant_prompt_message = AssistantPromptMessage(content=chunk.token.text) - - if chunk.details: - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - usage=usage, - finish_reason=chunk.details.finish_reason, - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - ), - ) - - def _handle_generate_response( - self, model: str, credentials: dict, prompt_messages: list[PromptMessage], response: any - ) -> LLMResult: - if isinstance(response, str): - content = response - else: - content = response.generated_text - - assistant_prompt_message = AssistantPromptMessage(content=content) - - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - return result - - @staticmethod - def _get_hosted_model_task_type(huggingfacehub_api_token: str, model_name: str): - hf_api = HfApi(token=huggingfacehub_api_token) - model_info = hf_api.model_info(repo_id=model_name) - - try: - if not model_info: - raise ValueError(f"Model {model_name} not found.") - - if "inference" in model_info.cardData and not model_info.cardData["inference"]: - raise ValueError(f"Inference API has been turned off for this model {model_name}.") - - valid_tasks = ("text2text-generation", "text-generation") - if model_info.pipeline_tag not in valid_tasks: - raise ValueError(f"Model {model_name} is not a valid task, must be one of {valid_tasks}.") - except Exception as e: - raise CredentialsValidateFailedError(f"{str(e)}") - - return model_info.pipeline_tag - - def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str: - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - return text.rstrip() - - @staticmethod - def _convert_one_message_to_text(message: PromptMessage) -> str: - human_prompt = "\n\nHuman:" - ai_prompt = "\n\nAssistant:" - content = message.content - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage): - message_text = content - else: - raise ValueError(f"Got unknown type {message}") - - return message_text diff --git a/api/core/model_runtime/model_providers/huggingface_hub/text_embedding/__init__.py b/api/core/model_runtime/model_providers/huggingface_hub/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/huggingface_tei/__init__.py b/api/core/model_runtime/model_providers/huggingface_tei/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.py b/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.py deleted file mode 100644 index 97d7e28dc646f8..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class HuggingfaceTeiProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.yaml b/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.yaml deleted file mode 100644 index f3a912d84d23d3..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.yaml +++ /dev/null @@ -1,36 +0,0 @@ -provider: huggingface_tei -label: - en_US: Text Embedding Inference -description: - en_US: A blazing fast inference solution for text embeddings models. - zh_Hans: 用于文本嵌入模型的超快速推理解决方案。 -background: "#FFF8DC" -help: - title: - en_US: How to deploy Text Embedding Inference - zh_Hans: 如何部署 Text Embedding Inference - url: - en_US: https://github.com/huggingface/text-embeddings-inference -supported_model_types: - - text-embedding - - rerank -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: server_url - label: - zh_Hans: 服务器URL - en_US: Server url - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入Text Embedding Inference的服务器地址，如 http://192.168.1.100:8080 - en_US: Enter the url of your Text Embedding Inference, e.g. http://192.168.1.100:8080 diff --git a/api/core/model_runtime/model_providers/huggingface_tei/rerank/__init__.py b/api/core/model_runtime/model_providers/huggingface_tei/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/huggingface_tei/rerank/rerank.py b/api/core/model_runtime/model_providers/huggingface_tei/rerank/rerank.py deleted file mode 100644 index 74a1dfc3ffe076..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_tei/rerank/rerank.py +++ /dev/null @@ -1,136 +0,0 @@ -from typing import Optional - -import httpx - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel -from core.model_runtime.model_providers.huggingface_tei.tei_helper import TeiHelper - - -class HuggingfaceTeiRerankModel(RerankModel): - """ - Model class for Text Embedding Inference rerank model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n - :param user: unique user id - :return: rerank result - """ - if len(docs) == 0: - return RerankResult(model=model, docs=[]) - server_url = credentials["server_url"] - - server_url = server_url.removesuffix("/") - - try: - results = TeiHelper.invoke_rerank(server_url, query, docs) - - rerank_documents = [] - for result in results: - rerank_document = RerankDocument( - index=result["index"], - text=result["text"], - score=result["score"], - ) - if score_threshold is None or result["score"] >= score_threshold: - rerank_documents.append(rerank_document) - if top_n is not None and len(rerank_documents) >= top_n: - break - - return RerankResult(model=model, docs=rerank_documents) - except httpx.HTTPStatusError as e: - raise InvokeServerUnavailableError(str(e)) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - server_url = credentials["server_url"] - extra_args = TeiHelper.get_tei_extra_parameter(server_url, model) - if extra_args.model_type != "reranker": - raise CredentialsValidateFailedError("Current model is not a rerank model") - - credentials["context_size"] = extra_args.max_input_length - - self.invoke( - model=model, - credentials=credentials, - query="Whose kasumi", - docs=[ - 'Kasumi is a girl\'s name of Japanese origin meaning "mist".', - "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music ", - "and she leads a team named PopiParty.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.RERANK, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", 512)), - }, - parameter_rules=[], - ) - - return entity diff --git a/api/core/model_runtime/model_providers/huggingface_tei/tei_helper.py b/api/core/model_runtime/model_providers/huggingface_tei/tei_helper.py deleted file mode 100644 index 81ab2492144e86..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_tei/tei_helper.py +++ /dev/null @@ -1,182 +0,0 @@ -from threading import Lock -from time import time -from typing import Optional - -import httpx -from requests.adapters import HTTPAdapter -from requests.exceptions import ConnectionError, MissingSchema, Timeout -from requests.sessions import Session -from yarl import URL - - -class TeiModelExtraParameter: - model_type: str - max_input_length: int - max_client_batch_size: int - - def __init__(self, model_type: str, max_input_length: int, max_client_batch_size: Optional[int] = None) -> None: - self.model_type = model_type - self.max_input_length = max_input_length - self.max_client_batch_size = max_client_batch_size - - -cache = {} -cache_lock = Lock() - - -class TeiHelper: - @staticmethod - def get_tei_extra_parameter(server_url: str, model_name: str) -> TeiModelExtraParameter: - TeiHelper._clean_cache() - with cache_lock: - if model_name not in cache: - cache[model_name] = { - "expires": time() + 300, - "value": TeiHelper._get_tei_extra_parameter(server_url), - } - return cache[model_name]["value"] - - @staticmethod - def _clean_cache() -> None: - try: - with cache_lock: - expired_keys = [model_uid for model_uid, model in cache.items() if model["expires"] < time()] - for model_uid in expired_keys: - del cache[model_uid] - except RuntimeError as e: - pass - - @staticmethod - def _get_tei_extra_parameter(server_url: str) -> TeiModelExtraParameter: - """ - get tei model extra parameter like model_type, max_input_length, max_batch_requests - """ - - url = str(URL(server_url) / "info") - - # this method is surrounded by a lock, and default requests may hang forever, - # so we just set a Adapter with max_retries=3 - session = Session() - session.mount("http://", HTTPAdapter(max_retries=3)) - session.mount("https://", HTTPAdapter(max_retries=3)) - - try: - response = session.get(url, timeout=10) - except (MissingSchema, ConnectionError, Timeout) as e: - raise RuntimeError(f"get tei model extra parameter failed, url: {url}, error: {e}") - if response.status_code != 200: - raise RuntimeError( - f"get tei model extra parameter failed, status code: {response.status_code}, response: {response.text}" - ) - - response_json = response.json() - - model_type = response_json.get("model_type", {}) - if len(model_type.keys()) < 1: - raise RuntimeError("model_type is empty") - model_type = list(model_type.keys())[0] - if model_type not in {"embedding", "reranker"}: - raise RuntimeError(f"invalid model_type: {model_type}") - - max_input_length = response_json.get("max_input_length", 512) - max_client_batch_size = response_json.get("max_client_batch_size", 1) - - return TeiModelExtraParameter( - model_type=model_type, max_input_length=max_input_length, max_client_batch_size=max_client_batch_size - ) - - @staticmethod - def invoke_tokenize(server_url: str, texts: list[str]) -> list[list[dict]]: - """ - Invoke tokenize endpoint - - Example response: - [ - [ - { - "id": 0, - "text": "", - "special": true, - "start": null, - "stop": null - }, - { - "id": 7704, - "text": "str", - "special": false, - "start": 0, - "stop": 3 - }, - < MORE TOKENS > - ] - ] - - :param server_url: server url - :param texts: texts to tokenize - """ - resp = httpx.post( - f"{server_url}/tokenize", - json={"inputs": texts}, - ) - resp.raise_for_status() - return resp.json() - - @staticmethod - def invoke_embeddings(server_url: str, texts: list[str]) -> dict: - """ - Invoke embeddings endpoint - - Example response: - { - "object": "list", - "data": [ - { - "object": "embedding", - "embedding": [...], - "index": 0 - } - ], - "model": "MODEL_NAME", - "usage": { - "prompt_tokens": 3, - "total_tokens": 3 - } - } - - :param server_url: server url - :param texts: texts to embed - """ - # Use OpenAI compatible API here, which has usage tracking - resp = httpx.post( - f"{server_url}/v1/embeddings", - json={"input": texts}, - ) - resp.raise_for_status() - return resp.json() - - @staticmethod - def invoke_rerank(server_url: str, query: str, docs: list[str]) -> list[dict]: - """ - Invoke rerank endpoint - - Example response: - [ - { - "index": 0, - "text": "Deep Learning is ...", - "score": 0.9950755 - } - ] - - :param server_url: server url - :param texts: texts to rerank - :param candidates: candidates to rerank - """ - params = {"query": query, "texts": docs, "return_text": True} - - response = httpx.post( - server_url + "/rerank", - json=params, - ) - response.raise_for_status() - return response.json() diff --git a/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/__init__.py b/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/hunyuan/__init__.py b/api/core/model_runtime/model_providers/hunyuan/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/hunyuan/_assets/icon_l_en.png b/api/core/model_runtime/model_providers/hunyuan/_assets/icon_l_en.png deleted file mode 100644 index 1303055ef8d1ee2b7bd127fa55c8f28a47a2ca4f..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 68638 zcmZsCRa70@7G-dUV8Jc8ySux)ySqcM5G=U6L-0Uwcb9`haCZyt)|K0%Ki<9l0S6cy zsM>q2xu>iOS5lBfg2#pb@ZkfJw3L|2hYt`Iz}Mekp@Glzhb#BM3z(~lq{xS=3H+lE zABaCliwUcF8Ju>&_^K_WzrAPamRQe0NfCcxE`|>-Eod=uitY&CSyXT(8FBEallG{4 zAE&^hT<41EII+X0RJd~8UR2PlMyhf~9K>cK?lzK>#DH^;X7k%`ynb)@WYh9O?fAaC zIte4e>N>`~;d8M5yn4?+IYvw&EcEdsBqZ4XyaXc1eAS<-jEqJA|Mr!b7#8+_UW8y- zoj?BXkN)}2DG(0U*dx&M>tg$V-UACRk``|I|NU2TLa=oR?GSIc9FyFdIHvoCqK0Bb z|G6OHO-G$H=ZUg+7e9WrJ`{P)f`~J&n1x|>6iiZn?eEcvJQSIknPD~=7JGYp^Q?oX zi8@jsvVUDUEVv}>%RC(GM9a)?Xvdi_{3V5hANbUgwb{LFI|DJ}kz8I3FxSj~4v|yc zC%n5u&n%IBHr)k{#+lsnQ+3D2!yiK6vTGLsq3$Stgo-X zX|VS}WBX-zYf};F+u8Rm@;}Rv#TOW9kT&mBl@hF+Qy)E2Y^}g%|BSY>Z~n>i3d{>> zWd_@9%~%i0vei#5mYfT5^Q*1mk<-)3;fOPS+N!kk1@e&da&$cot37MguuDbp(>>LC zd$P9@$2jgVj{@Pd;YJn`(m1DkKbj%z!>eOb>ZkVvW{a2GTa_EBe{C}tCnST6abvVA zJ!1x8((X@|^u`LgF!@?KTd`#p1iP`6nMNoyHI9&OjB!kZue)!#m=;lEe|#9s4Xj-b z{WzT^3dS4lu^XYrYK2aU?o+Zye(xkqV0IW)GFZz-_>CSHfS=}k5`!^4eWz)6t$Y76 zu5+TxL*W)GBKVvCEtv7pr}`&xbL#?|0-M;suIz9Rk^$HFcYli@j!cX^&%WAhZAnH7 zdr!Txjg(GI-yW$*6lA)%3TOnDS<^{bEs9msi-4bbco>#7<6!tjKVS-$Z4eu=L^ew~ zfz!@uLe@k@cC>!-h%tB25yG0CG} z)(8G}!nKbl6Ct1$+lG#+M^caHf%ycv!N_>?cA0S1?Q=cG|NLcOU0^7>)bS5CQN&

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z#f3M`80lT!+Ya^GVI?ahzUoy=*1mDX;fI|o#!;PKZS{62($A$WFgz{rL1ko4cSqZT zkt56QSAwV-HA;x}wx@k|SXA-jAF;99x9|8}abDpqmmlX@(%Z(QpG#XHZGqusf#qAn zXLWUVUY=K+{a-UnygU2ayOcOAIz2=Nq)#_jJy%v-^1TJK(;9qz9hmgtbn+i}pUl2$by-!z499FUgi#D*L^{Y2688K?ak1n64*_My1{cr@h>i#x3k*{HVG zrmMrD$b=a)M$J#>fTeQC(q*MBFgPu+ww8@+ZELw&6ojVo(!2-8=BA##wOkLYBpxw$J?GOA30*dmGjh9`_uXKJ!uQ1Eig1Ju%VgxJ3FFZF%9#Y48P}E zF-zGzJ-h$n*8T3V$n2zYyn6kPbve0#zaDZ(&OJ#Uq@gh+=~kvKkhZ|SEU;`_Y>a8! z*NCD}BTAlsmI!F-3&v`HtlaMoE1AXr`}f&bsw%5)3uJmeC_J?2hnMyNJhnd_OW%{W zK-vQRXMtrku`vxh8 None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `hunyuan-standard` model for validate, - model_instance.validate_credentials(model="hunyuan-standard", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/hunyuan/hunyuan.yaml b/api/core/model_runtime/model_providers/hunyuan/hunyuan.yaml deleted file mode 100644 index 812b51ddcd176a..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/hunyuan.yaml +++ /dev/null @@ -1,41 +0,0 @@ -provider: hunyuan -label: - zh_Hans: 腾讯混元 - en_US: Hunyuan -description: - en_US: Models provided by Tencent Hunyuan, such as hunyuan-standard, hunyuan-standard-256k, hunyuan-pro and hunyuan-lite. - zh_Hans: 腾讯混元提供的模型，例如 hunyuan-standard、 hunyuan-standard-256k, hunyuan-pro 和 hunyuan-lite。 -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -background: "#F6F7F7" -help: - title: - en_US: Get your API Key from Tencent Hunyuan - zh_Hans: 从腾讯混元获取 API Key - url: - en_US: https://console.cloud.tencent.com/cam/capi -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: secret_id - label: - en_US: Secret ID - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 Secret ID - en_US: Enter your Secret ID - - variable: secret_key - label: - en_US: Secret Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 Secret Key - en_US: Enter your Secret Key diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/__init__.py b/api/core/model_runtime/model_providers/hunyuan/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/_position.yaml b/api/core/model_runtime/model_providers/hunyuan/llm/_position.yaml deleted file mode 100644 index f494984443cb42..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/llm/_position.yaml +++ /dev/null @@ -1,6 +0,0 @@ -- hunyuan-lite -- hunyuan-standard -- hunyuan-standard-256k -- hunyuan-pro -- hunyuan-turbo -- hunyuan-vision diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-lite.yaml b/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-lite.yaml deleted file mode 100644 index 4f5a5dfb4858ae..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-lite.yaml +++ /dev/null @@ -1,28 +0,0 @@ -model: hunyuan-lite -label: - zh_Hans: hunyuan-lite - en_US: hunyuan-lite -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 256000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 256000 -pricing: - input: '0.00' - output: '0.00' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-pro.yaml b/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-pro.yaml deleted file mode 100644 index b173ffbe778563..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-pro.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: hunyuan-pro -label: - zh_Hans: hunyuan-pro - en_US: hunyuan-pro -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 32000 - - name: enable_enhance - label: - zh_Hans: 功能增强 - en_US: Enable Enhancement - type: boolean - help: - zh_Hans: 功能增强（如搜索）开关，关闭时将直接由主模型生成回复内容，可以降低响应时延（对于流式输出时的首字时延尤为明显）。但在少数场景里，回复效果可能会下降。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false - default: true -pricing: - input: '0.03' - output: '0.10' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-standard-256k.yaml b/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-standard-256k.yaml deleted file mode 100644 index 1f94a8623b494c..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-standard-256k.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: hunyuan-standard-256k -label: - zh_Hans: hunyuan-standard-256k - en_US: hunyuan-standard-256k -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 256000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 256000 - - name: enable_enhance - label: - zh_Hans: 功能增强 - en_US: Enable Enhancement - type: boolean - help: - zh_Hans: 功能增强（如搜索）开关，关闭时将直接由主模型生成回复内容，可以降低响应时延（对于流式输出时的首字时延尤为明显）。但在少数场景里，回复效果可能会下降。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false - default: true -pricing: - input: '0.015' - output: '0.06' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-standard.yaml b/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-standard.yaml deleted file mode 100644 index 1db25930fc7b1c..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-standard.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: hunyuan-standard -label: - zh_Hans: hunyuan-standard - en_US: hunyuan-standard -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 32000 - - name: enable_enhance - label: - zh_Hans: 功能增强 - en_US: Enable Enhancement - type: boolean - help: - zh_Hans: 功能增强（如搜索）开关，关闭时将直接由主模型生成回复内容，可以降低响应时延（对于流式输出时的首字时延尤为明显）。但在少数场景里，回复效果可能会下降。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false - default: true -pricing: - input: '0.0045' - output: '0.0005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-turbo.yaml b/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-turbo.yaml deleted file mode 100644 index 4837fed4bae563..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-turbo.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: hunyuan-turbo -label: - zh_Hans: hunyuan-turbo - en_US: hunyuan-turbo -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 32000 - - name: enable_enhance - label: - zh_Hans: 功能增强 - en_US: Enable Enhancement - type: boolean - help: - zh_Hans: 功能增强（如搜索）开关，关闭时将直接由主模型生成回复内容，可以降低响应时延（对于流式输出时的首字时延尤为明显）。但在少数场景里，回复效果可能会下降。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false - default: true -pricing: - input: '0.015' - output: '0.05' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-vision.yaml b/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-vision.yaml deleted file mode 100644 index 9edc7f4710f9a5..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/llm/hunyuan-vision.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: hunyuan-vision -label: - zh_Hans: hunyuan-vision - en_US: hunyuan-vision -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8000 - - name: enable_enhance - label: - zh_Hans: 功能增强 - en_US: Enable Enhancement - type: boolean - help: - zh_Hans: 功能增强（如搜索）开关，关闭时将直接由主模型生成回复内容，可以降低响应时延（对于流式输出时的首字时延尤为明显）。但在少数场景里，回复效果可能会下降。 - en_US: Allow the model to perform external search to enhance the generation results. - required: false - default: true -pricing: - input: '0.018' - output: '0.018' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/hunyuan/llm/llm.py b/api/core/model_runtime/model_providers/hunyuan/llm/llm.py deleted file mode 100644 index 2014de8516bc11..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/llm/llm.py +++ /dev/null @@ -1,348 +0,0 @@ -import json -import logging -from collections.abc import Generator -from typing import cast - -from tencentcloud.common import credential -from tencentcloud.common.exception import TencentCloudSDKException -from tencentcloud.common.profile.client_profile import ClientProfile -from tencentcloud.common.profile.http_profile import HttpProfile -from tencentcloud.hunyuan.v20230901 import hunyuan_client, models - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import InvokeError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -logger = logging.getLogger(__name__) - - -class HunyuanLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - client = self._setup_hunyuan_client(credentials) - request = models.ChatCompletionsRequest() - messages_dict = self._convert_prompt_messages_to_dicts(prompt_messages) - - custom_parameters = { - "Temperature": model_parameters.get("temperature", 0.0), - "TopP": model_parameters.get("top_p", 1.0), - "EnableEnhancement": model_parameters.get("enable_enhance", True), - } - - params = { - "Model": model, - "Messages": messages_dict, - "Stream": stream, - **custom_parameters, - } - # add Tools and ToolChoice - if tools and len(tools) > 0: - params["ToolChoice"] = "auto" - params["Tools"] = [ - { - "Type": "function", - "Function": { - "Name": tool.name, - "Description": tool.description, - "Parameters": json.dumps(tool.parameters), - }, - } - for tool in tools - ] - - request.from_json_string(json.dumps(params)) - response = client.ChatCompletions(request) - - if stream: - return self._handle_stream_chat_response(model, credentials, prompt_messages, response) - - return self._handle_chat_response(credentials, model, prompt_messages, response) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate credentials - """ - try: - client = self._setup_hunyuan_client(credentials) - - req = models.ChatCompletionsRequest() - params = { - "Model": model, - "Messages": [{"Role": "user", "Content": "hello"}], - "TopP": 1, - "Temperature": 0, - "Stream": False, - } - req.from_json_string(json.dumps(params)) - client.ChatCompletions(req) - except Exception as e: - raise CredentialsValidateFailedError(f"Credentials validation failed: {e}") - - def _setup_hunyuan_client(self, credentials): - secret_id = credentials["secret_id"] - secret_key = credentials["secret_key"] - cred = credential.Credential(secret_id, secret_key) - httpProfile = HttpProfile() - httpProfile.endpoint = "hunyuan.tencentcloudapi.com" - clientProfile = ClientProfile() - clientProfile.httpProfile = httpProfile - client = hunyuan_client.HunyuanClient(cred, "", clientProfile) - return client - - def _convert_prompt_messages_to_dicts(self, prompt_messages: list[PromptMessage]) -> list[dict]: - """Convert a list of PromptMessage objects to a list of dictionaries with 'Role' and 'Content' keys.""" - dict_list = [] - for message in prompt_messages: - if isinstance(message, AssistantPromptMessage): - tool_calls = message.tool_calls - if tool_calls and len(tool_calls) > 0: - dict_tool_calls = [ - { - "Id": tool_call.id, - "Type": tool_call.type, - "Function": { - "Name": tool_call.function.name, - "Arguments": tool_call.function.arguments - if (tool_call.function.arguments == "") - else "{}", - }, - } - for tool_call in tool_calls - ] - - dict_list.append( - { - "Role": message.role.value, - # fix set content = "" while tool_call request - # fix [hunyuan] None, [TencentCloudSDKException] code:InvalidParameter - # message:Messages Content and Contents not allowed empty at the same time. - "Content": " ", # message.content if (message.content is not None) else "", - "ToolCalls": dict_tool_calls, - } - ) - else: - dict_list.append({"Role": message.role.value, "Content": message.content}) - elif isinstance(message, ToolPromptMessage): - tool_execute_result = {"result": message.content} - content = json.dumps(tool_execute_result, ensure_ascii=False) - dict_list.append({"Role": message.role.value, "Content": content, "ToolCallId": message.tool_call_id}) - elif isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - dict_list.append({"Role": message.role.value, "Content": message.content}) - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"Type": "text", "Text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "Type": "image_url", - "ImageUrl": {"Url": message_content.data}, - } - sub_messages.append(sub_message_dict) - dict_list.append({"Role": message.role.value, "Contents": sub_messages}) - else: - dict_list.append({"Role": message.role.value, "Content": message.content}) - return dict_list - - def _handle_stream_chat_response(self, model, credentials, prompt_messages, resp): - tool_call = None - tool_calls = [] - - for index, event in enumerate(resp): - logging.debug("_handle_stream_chat_response, event: %s", event) - - data_str = event["data"] - data = json.loads(data_str) - - choices = data.get("Choices", []) - if not choices: - continue - choice = choices[0] - delta = choice.get("Delta", {}) - message_content = delta.get("Content", "") - finish_reason = choice.get("FinishReason", "") - - usage = data.get("Usage", {}) - prompt_tokens = usage.get("PromptTokens", 0) - completion_tokens = usage.get("CompletionTokens", 0) - - response_tool_calls = delta.get("ToolCalls") - if response_tool_calls is not None: - new_tool_calls = self._extract_response_tool_calls(response_tool_calls) - if len(new_tool_calls) > 0: - new_tool_call = new_tool_calls[0] - if tool_call is None: - tool_call = new_tool_call - elif tool_call.id != new_tool_call.id: - tool_calls.append(tool_call) - tool_call = new_tool_call - else: - tool_call.function.name += new_tool_call.function.name - tool_call.function.arguments += new_tool_call.function.arguments - if tool_call is not None and len(tool_call.function.name) > 0 and len(tool_call.function.arguments) > 0: - tool_calls.append(tool_call) - tool_call = None - - assistant_prompt_message = AssistantPromptMessage(content=message_content, tool_calls=[]) - # rewrite content = "" while tool_call to avoid show content on web page - if len(tool_calls) > 0: - assistant_prompt_message.content = "" - - # add tool_calls to assistant_prompt_message - if finish_reason == "tool_calls": - assistant_prompt_message.tool_calls = tool_calls - tool_call = None - tool_calls = [] - - if len(finish_reason) > 0: - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - delta_chunk = LLMResultChunkDelta( - index=index, - role=delta.get("Role", "assistant"), - message=assistant_prompt_message, - usage=usage, - finish_reason=finish_reason, - ) - tool_call = None - tool_calls = [] - - else: - delta_chunk = LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - ) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=delta_chunk, - ) - - def _handle_chat_response(self, credentials, model, prompt_messages, response): - usage = self._calc_response_usage( - model, credentials, response.Usage.PromptTokens, response.Usage.CompletionTokens - ) - assistant_prompt_message = AssistantPromptMessage() - assistant_prompt_message.content = response.Choices[0].Message.Content - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - - return result - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - if len(prompt_messages) == 0: - return 0 - prompt = self._convert_messages_to_prompt(prompt_messages) - return self._get_num_tokens_by_gpt2(prompt) - - def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str: - """ - Format a list of messages into a full prompt for the Anthropic model - - :param messages: List of PromptMessage to combine. - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - # trim off the trailing ' ' that might come from the "Assistant: " - return text.rstrip() - - def _convert_one_message_to_text(self, message: PromptMessage) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt = "\n\nHuman:" - ai_prompt = "\n\nAssistant:" - tool_prompt = "\n\nTool:" - content = message.content - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, ToolPromptMessage): - message_text = f"{tool_prompt} {content}" - elif isinstance(message, SystemPromptMessage): - message_text = content - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeError: [TencentCloudSDKException], - } - - def _extract_response_tool_calls(self, response_tool_calls: list[dict]) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_tool_calls: - for response_tool_call in response_tool_calls: - response_function = response_tool_call.get("Function", {}) - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_function.get("Name", ""), arguments=response_function.get("Arguments", "") - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call.get("Id", 0), type="function", function=function - ) - tool_calls.append(tool_call) - - return tool_calls diff --git a/api/core/model_runtime/model_providers/hunyuan/text_embedding/__init__.py b/api/core/model_runtime/model_providers/hunyuan/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/hunyuan/text_embedding/hunyuan-text-embedding.yaml b/api/core/model_runtime/model_providers/hunyuan/text_embedding/hunyuan-text-embedding.yaml deleted file mode 100644 index ab014e4344de97..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/text_embedding/hunyuan-text-embedding.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: hunyuan-embedding -model_type: text-embedding -model_properties: - context_size: 1024 - max_chunks: 1 diff --git a/api/core/model_runtime/model_providers/jina/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/jina/_assets/icon_l_en.svg deleted file mode 100644 index 6a241fc9ae32cf..00000000000000 --- a/api/core/model_runtime/model_providers/jina/_assets/icon_l_en.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/jina/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/jina/_assets/icon_s_en.svg deleted file mode 100644 index 2e1b00fa52e43c..00000000000000 --- a/api/core/model_runtime/model_providers/jina/_assets/icon_s_en.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - diff --git a/api/core/model_runtime/model_providers/jina/jina.py b/api/core/model_runtime/model_providers/jina/jina.py deleted file mode 100644 index 186a0a0fa7e6dc..00000000000000 --- a/api/core/model_runtime/model_providers/jina/jina.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class JinaProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.TEXT_EMBEDDING) - - # Use `jina-embeddings-v3` model for validate, - # no matter what model you pass in, text completion model or chat model - model_instance.validate_credentials(model="jina-embeddings-v3", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/jina/rerank/__init__.py b/api/core/model_runtime/model_providers/jina/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/jina/rerank/_position.yaml b/api/core/model_runtime/model_providers/jina/rerank/_position.yaml deleted file mode 100644 index c9ddaad758a539..00000000000000 --- a/api/core/model_runtime/model_providers/jina/rerank/_position.yaml +++ /dev/null @@ -1,5 +0,0 @@ -- jina-reranker-v2-base-multilingual -- jina-reranker-v1-base-en -- jina-reranker-v1-turbo-en -- jina-colbert-v1-en -- jina-reranker-v1-tiny-en diff --git a/api/core/model_runtime/model_providers/jina/rerank/jina-colbert-v1-en.yaml b/api/core/model_runtime/model_providers/jina/rerank/jina-colbert-v1-en.yaml deleted file mode 100644 index 320370f2425521..00000000000000 --- a/api/core/model_runtime/model_providers/jina/rerank/jina-colbert-v1-en.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: jina-colbert-v1-en -model_type: rerank -model_properties: - context_size: 8192 diff --git a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-base-en.yaml b/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-base-en.yaml deleted file mode 100644 index bd3f31fbd17f5f..00000000000000 --- a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-base-en.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: jina-reranker-v1-base-en -model_type: rerank -model_properties: - context_size: 8192 diff --git a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-tiny-en.yaml b/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-tiny-en.yaml deleted file mode 100644 index b81711195b3135..00000000000000 --- a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-tiny-en.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: jina-reranker-v1-tiny-en -model_type: rerank -model_properties: - context_size: 8192 diff --git a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-turbo-en.yaml b/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-turbo-en.yaml deleted file mode 100644 index d05f4bb4a2fbb7..00000000000000 --- a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v1-turbo-en.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: jina-reranker-v1-turbo-en -model_type: rerank -model_properties: - context_size: 8192 diff --git a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v2-base-multilingual.yaml b/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v2-base-multilingual.yaml deleted file mode 100644 index e6af62107eaa08..00000000000000 --- a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v2-base-multilingual.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: jina-reranker-v2-base-multilingual -model_type: rerank -model_properties: - context_size: 1024 diff --git a/api/core/model_runtime/model_providers/jina/rerank/rerank.py b/api/core/model_runtime/model_providers/jina/rerank/rerank.py deleted file mode 100644 index 79ca68914f9791..00000000000000 --- a/api/core/model_runtime/model_providers/jina/rerank/rerank.py +++ /dev/null @@ -1,125 +0,0 @@ -from typing import Optional - -import httpx - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - - -class JinaRerankModel(RerankModel): - """ - Model class for Jina rerank model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n documents to return - :param user: unique user id - :return: rerank result - """ - if len(docs) == 0: - return RerankResult(model=model, docs=[]) - - base_url = credentials.get("base_url", "https://api.jina.ai/v1") - base_url = base_url.removesuffix("/") - - try: - response = httpx.post( - base_url + "/rerank", - json={"model": model, "query": query, "documents": docs, "top_n": top_n}, - headers={"Authorization": f"Bearer {credentials.get('api_key')}"}, - ) - response.raise_for_status() - results = response.json() - - rerank_documents = [] - for result in results["results"]: - rerank_document = RerankDocument( - index=result["index"], - text=result["document"]["text"], - score=result["relevance_score"], - ) - if score_threshold is None or result["relevance_score"] >= score_threshold: - rerank_documents.append(rerank_document) - - return RerankResult(model=model, docs=rerank_documents) - except httpx.HTTPStatusError as e: - raise InvokeServerUnavailableError(str(e)) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke( - model=model, - credentials=credentials, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - """ - return { - InvokeConnectionError: [httpx.ConnectError], - InvokeServerUnavailableError: [httpx.RemoteProtocolError], - InvokeRateLimitError: [], - InvokeAuthorizationError: [httpx.HTTPStatusError], - InvokeBadRequestError: [httpx.RequestError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.RERANK, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size"))}, - ) - - return entity diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/jina-clip-v1.yaml b/api/core/model_runtime/model_providers/jina/text_embedding/jina-clip-v1.yaml deleted file mode 100644 index c06bfd7ebeb6cd..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/jina-clip-v1.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: jina-clip-v1 -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 2048 -pricing: - input: '0.001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-de.yaml b/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-de.yaml deleted file mode 100644 index 09f7023acbc67d..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-de.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: jina-embeddings-v2-base-de -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 2048 -pricing: - input: '0.001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-en.yaml b/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-en.yaml deleted file mode 100644 index a9b2cd4efb328a..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-en.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: jina-embeddings-v2-base-en -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 2048 -pricing: - input: '0.001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-zh.yaml b/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-zh.yaml deleted file mode 100644 index 2a66b4729b5fa2..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-base-zh.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: jina-embeddings-v2-base-zh -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 2048 -pricing: - input: '0.001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-small-en.yaml b/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-small-en.yaml deleted file mode 100644 index c92779d4997995..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v2-small-en.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: jina-embeddings-v2-small-en -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 2048 -pricing: - input: '0.001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v3.yaml b/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v3.yaml deleted file mode 100644 index 4e5374dc9d733d..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/jina-embeddings-v3.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: jina-embeddings-v3 -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 2048 -pricing: - input: '0.001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/jina_tokenizer.py b/api/core/model_runtime/model_providers/jina/text_embedding/jina_tokenizer.py deleted file mode 100644 index d80cbfa83d6425..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/jina_tokenizer.py +++ /dev/null @@ -1,32 +0,0 @@ -from os.path import abspath, dirname, join -from threading import Lock - -from transformers import AutoTokenizer - - -class JinaTokenizer: - _tokenizer = None - _lock = Lock() - - @classmethod - def _get_tokenizer(cls): - if cls._tokenizer is None: - with cls._lock: - if cls._tokenizer is None: - base_path = abspath(__file__) - gpt2_tokenizer_path = join(dirname(base_path), "tokenizer") - cls._tokenizer = AutoTokenizer.from_pretrained(gpt2_tokenizer_path) - return cls._tokenizer - - @classmethod - def _get_num_tokens_by_jina_base(cls, text: str) -> int: - """ - use jina tokenizer to get num tokens - """ - tokenizer = cls._get_tokenizer() - tokens = tokenizer.encode(text) - return len(tokens) - - @classmethod - def get_num_tokens(cls, text: str) -> int: - return cls._get_num_tokens_by_jina_base(text) diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/tokenizer/tokenizer.json b/api/core/model_runtime/model_providers/jina/text_embedding/tokenizer/tokenizer.json deleted file mode 100644 index 65f2b2bc19a33a..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/tokenizer/tokenizer.json +++ /dev/null @@ -1,30678 +0,0 @@ -{ - "version": "1.0", - "truncation": null, - "padding": null, - "added_tokens": [ - { - "id": 0, - "content": "[PAD]", - "single_word": false, - "lstrip": false, - "rstrip": false, - "normalized": false, - "special": true - }, - { - "id": 100, - "content": "[UNK]", - "single_word": false, - "lstrip": false, - "rstrip": false, - "normalized": false, - "special": true - }, - { - "id": 101, - "content": "[CLS]", - "single_word": false, - "lstrip": false, - "rstrip": false, - "normalized": false, - "special": true - }, - { - "id": 102, - "content": "[SEP]", - "single_word": false, - "lstrip": false, - "rstrip": false, - "normalized": false, - "special": true - }, - { - "id": 103, - "content": "[MASK]", - "single_word": false, - "lstrip": false, - "rstrip": false, - "normalized": false, - "special": true - } - ], - "normalizer": { - "type": "BertNormalizer", - "clean_text": true, - "handle_chinese_chars": true, - "strip_accents": null, - "lowercase": true - }, - "pre_tokenizer": { - "type": "BertPreTokenizer" - }, - "post_processor": { - "type": "TemplateProcessing", - "single": [ - { - "SpecialToken": { - "id": "[CLS]", - "type_id": 0 - } - }, - { - "Sequence": { - "id": "A", - "type_id": 0 - } - }, - { - "SpecialToken": { - "id": "[SEP]", - "type_id": 0 - } - } - ], - "pair": [ - { - "SpecialToken": { - "id": "[CLS]", - "type_id": 0 - } - }, - { - "Sequence": { - "id": "A", - "type_id": 0 - } - }, - { - "SpecialToken": { - "id": "[SEP]", - "type_id": 0 - } - }, - { - "Sequence": { - "id": "B", - "type_id": 1 - } - }, - { - "SpecialToken": { - "id": "[SEP]", - "type_id": 1 - } - } - ], - "special_tokens": { - "[CLS]": { - "id": "[CLS]", - "ids": [ - 101 - ], - "tokens": [ - "[CLS]" - ] - }, - "[SEP]": { - "id": "[SEP]", - "ids": [ - 102 - ], - "tokens": [ - "[SEP]" - ] - } - } - }, - "decoder": { - "type": "WordPiece", - "prefix": "##", - "cleanup": true - }, - "model": { - "type": "WordPiece", - "unk_token": "[UNK]", - "continuing_subword_prefix": "##", - "max_input_chars_per_word": 100, - "vocab": { - "[PAD]": 0, - "[unused0]": 1, - "[unused1]": 2, - "[unused2]": 3, - "[unused3]": 4, - "[unused4]": 5, 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a/api/core/model_runtime/model_providers/leptonai/leptonai.py b/api/core/model_runtime/model_providers/leptonai/leptonai.py deleted file mode 100644 index 34a55ff1924cf8..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/leptonai.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class LeptonAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="llama2-7b", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/leptonai/leptonai.yaml b/api/core/model_runtime/model_providers/leptonai/leptonai.yaml deleted file mode 100644 index a246ff5356f723..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/leptonai.yaml +++ /dev/null @@ -1,29 +0,0 @@ -provider: leptonai -label: - zh_Hans: Lepton AI - en_US: Lepton AI -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -background: "#F5F5F4" -help: - title: - en_US: Get your API Key from Lepton AI - zh_Hans: 从 Lepton AI 获取 API Key - url: - en_US: https://dashboard.lepton.ai -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/leptonai/llm/_position.yaml b/api/core/model_runtime/model_providers/leptonai/llm/_position.yaml deleted file mode 100644 index a85e8e65ba403e..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/llm/_position.yaml +++ /dev/null @@ -1,6 +0,0 @@ -- gemma-7b -- mistral-7b -- mixtral-8x7b -- llama2-7b -- llama2-13b -- llama3-70b diff --git a/api/core/model_runtime/model_providers/leptonai/llm/gemma-7b.yaml b/api/core/model_runtime/model_providers/leptonai/llm/gemma-7b.yaml deleted file mode 100644 index 2d69067a23c092..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/llm/gemma-7b.yaml +++ /dev/null @@ -1,20 +0,0 @@ -model: gemma-7b -label: - zh_Hans: gemma-7b - en_US: gemma-7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 diff --git a/api/core/model_runtime/model_providers/leptonai/llm/llama2-13b.yaml b/api/core/model_runtime/model_providers/leptonai/llm/llama2-13b.yaml deleted file mode 100644 index 307f1ea88f1b10..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/llm/llama2-13b.yaml +++ /dev/null @@ -1,20 +0,0 @@ -model: llama2-13b -label: - zh_Hans: llama2-13b - en_US: llama2-13b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 diff --git a/api/core/model_runtime/model_providers/leptonai/llm/llama2-7b.yaml b/api/core/model_runtime/model_providers/leptonai/llm/llama2-7b.yaml deleted file mode 100644 index bd471e59cd2d2d..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/llm/llama2-7b.yaml +++ /dev/null @@ -1,20 +0,0 @@ -model: llama2-7b -label: - zh_Hans: llama2-7b - en_US: llama2-7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 diff --git a/api/core/model_runtime/model_providers/leptonai/llm/llama3-70b.yaml b/api/core/model_runtime/model_providers/leptonai/llm/llama3-70b.yaml deleted file mode 100644 index 9c20eb6cdb15ca..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/llm/llama3-70b.yaml +++ /dev/null @@ -1,20 +0,0 @@ -model: llama3-70b -label: - zh_Hans: llama3-70b - en_US: llama3-70b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 diff --git a/api/core/model_runtime/model_providers/leptonai/llm/llm.py b/api/core/model_runtime/model_providers/leptonai/llm/llm.py deleted file mode 100644 index 3d69417e45da72..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/llm/llm.py +++ /dev/null @@ -1,40 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class LeptonAILargeLanguageModel(OAIAPICompatLargeLanguageModel): - MODEL_PREFIX_MAP = { - "llama2-7b": "llama2-7b", - "gemma-7b": "gemma-7b", - "mistral-7b": "mistral-7b", - "mixtral-8x7b": "mixtral-8x7b", - "llama3-70b": "llama3-70b", - "llama2-13b": "llama2-13b", - } - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials, model) - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials, model) - super().validate_credentials(model, credentials) - - @classmethod - def _add_custom_parameters(cls, credentials: dict, model: str) -> None: - credentials["mode"] = "chat" - credentials["endpoint_url"] = f"https://{cls.MODEL_PREFIX_MAP[model]}.lepton.run/api/v1" diff --git a/api/core/model_runtime/model_providers/leptonai/llm/mistral-7b.yaml b/api/core/model_runtime/model_providers/leptonai/llm/mistral-7b.yaml deleted file mode 100644 index f2b46ff91781c6..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/llm/mistral-7b.yaml +++ /dev/null @@ -1,20 +0,0 @@ -model: mistral-7b -label: - zh_Hans: mistral-7b - en_US: mistral-7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 diff --git a/api/core/model_runtime/model_providers/leptonai/llm/mixtral-8x7b.yaml b/api/core/model_runtime/model_providers/leptonai/llm/mixtral-8x7b.yaml deleted file mode 100644 index de788ac2568494..00000000000000 --- a/api/core/model_runtime/model_providers/leptonai/llm/mixtral-8x7b.yaml +++ /dev/null @@ -1,20 +0,0 @@ -model: mixtral-8x7b -label: - zh_Hans: mixtral-8x7b - en_US: mixtral-8x7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 diff --git a/api/core/model_runtime/model_providers/localai/__init__.py b/api/core/model_runtime/model_providers/localai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/localai/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/localai/_assets/icon_l_en.svg deleted file mode 100644 index 251a37fdc7e124..00000000000000 --- a/api/core/model_runtime/model_providers/localai/_assets/icon_l_en.svg +++ /dev/null @@ -1,22 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/localai/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/localai/_assets/icon_s_en.svg deleted file mode 100644 index 9dc6e6276ea166..00000000000000 --- a/api/core/model_runtime/model_providers/localai/_assets/icon_s_en.svg +++ /dev/null @@ -1,15 +0,0 @@ - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/localai/llm/__init__.py b/api/core/model_runtime/model_providers/localai/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/localai/llm/llm.py b/api/core/model_runtime/model_providers/localai/llm/llm.py deleted file mode 100644 index e7295355f627db..00000000000000 --- a/api/core/model_runtime/model_providers/localai/llm/llm.py +++ /dev/null @@ -1,674 +0,0 @@ -from collections.abc import Generator -from typing import cast - -from httpx import Timeout -from openai import ( - APIConnectionError, - APITimeoutError, - AuthenticationError, - ConflictError, - InternalServerError, - NotFoundError, - OpenAI, - PermissionDeniedError, - RateLimitError, - Stream, - UnprocessableEntityError, -) -from openai.types.chat import ChatCompletion, ChatCompletionChunk -from openai.types.chat.chat_completion_message import FunctionCall -from openai.types.completion import Completion -from yarl import URL - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.utils import helper - - -class LocalAILanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - # tools is not supported yet - return self._num_tokens_from_messages(prompt_messages, tools=tools) - - def _num_tokens_from_messages(self, messages: list[PromptMessage], tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for baichuan model - LocalAI does not supports - """ - - def tokens(text: str): - """ - We could not determine which tokenizer to use, cause the model is customized. - So we use gpt2 tokenizer to calculate the num tokens for convenience. - """ - return self._get_num_tokens_by_gpt2(text) - - tokens_per_message = 3 - tokens_per_name = 1 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += tokens(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += tokens(f_key) - num_tokens += tokens(f_value) - else: - num_tokens += tokens(t_key) - num_tokens += tokens(t_value) - if key == "function_call": - for t_key, t_value in value.items(): - num_tokens += tokens(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += tokens(f_key) - num_tokens += tokens(f_value) - else: - num_tokens += tokens(t_key) - num_tokens += tokens(t_value) - else: - num_tokens += tokens(str(value)) - - if key == "name": - num_tokens += tokens_per_name - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(tools) - - return num_tokens - - def _num_tokens_for_tools(self, tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for tool calling - - :param encoding: encoding - :param tools: tools for tool calling - :return: number of tokens - """ - - def tokens(text: str): - return self._get_num_tokens_by_gpt2(text) - - num_tokens = 0 - for tool in tools: - # calculate num tokens for function object - num_tokens += tokens("name") - num_tokens += tokens(tool.name) - num_tokens += tokens("description") - num_tokens += tokens(tool.description) - parameters = tool.parameters - num_tokens += tokens("parameters") - num_tokens += tokens("type") - num_tokens += tokens(parameters.get("type")) - if "properties" in parameters: - num_tokens += tokens("properties") - for key, value in parameters.get("properties").items(): - num_tokens += tokens(key) - for field_key, field_value in value.items(): - num_tokens += tokens(field_key) - if field_key == "enum": - for enum_field in field_value: - num_tokens += 3 - num_tokens += tokens(enum_field) - else: - num_tokens += tokens(field_key) - num_tokens += tokens(str(field_value)) - if "required" in parameters: - num_tokens += tokens("required") - for required_field in parameters["required"]: - num_tokens += 3 - num_tokens += tokens(required_field) - - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke( - model=model, - credentials=credentials, - prompt_messages=[UserPromptMessage(content="ping")], - model_parameters={ - "max_tokens": 10, - }, - stop=[], - stream=False, - ) - except Exception as ex: - raise CredentialsValidateFailedError(f"Invalid credentials {str(ex)}") - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - completion_model = None - if credentials["completion_type"] == "chat_completion": - completion_model = LLMMode.CHAT.value - elif credentials["completion_type"] == "completion": - completion_model = LLMMode.COMPLETION.value - else: - raise ValueError(f"Unknown completion type {credentials['completion_type']}") - - rules = [ - ParameterRule( - name="temperature", - type=ParameterType.FLOAT, - use_template="temperature", - label=I18nObject(zh_Hans="温度", en_US="Temperature"), - ), - ParameterRule( - name="top_p", - type=ParameterType.FLOAT, - use_template="top_p", - label=I18nObject(zh_Hans="Top P", en_US="Top P"), - ), - ParameterRule( - name="max_tokens", - type=ParameterType.INT, - use_template="max_tokens", - min=1, - max=2048, - default=512, - label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"), - ), - ] - - model_properties = ( - { - ModelPropertyKey.MODE: completion_model, - } - if completion_model - else {} - ) - - model_properties[ModelPropertyKey.CONTEXT_SIZE] = int(credentials.get("context_size", "2048")) - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - model_properties=model_properties, - parameter_rules=rules, - ) - - return entity - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - kwargs = self._to_client_kwargs(credentials) - # init model client - client = OpenAI(**kwargs) - - model_name = model - completion_type = credentials["completion_type"] - - extra_model_kwargs = { - "timeout": 60, - } - if stop: - extra_model_kwargs["stop"] = stop - - if user: - extra_model_kwargs["user"] = user - - if tools and len(tools) > 0: - extra_model_kwargs["functions"] = [helper.dump_model(tool) for tool in tools] - - if completion_type == "chat_completion": - result = client.chat.completions.create( - messages=[self._convert_prompt_message_to_dict(m) for m in prompt_messages], - model=model_name, - stream=stream, - **model_parameters, - **extra_model_kwargs, - ) - elif completion_type == "completion": - result = client.completions.create( - prompt=self._convert_prompt_message_to_completion_prompts(prompt_messages), - model=model, - stream=stream, - **model_parameters, - **extra_model_kwargs, - ) - else: - raise ValueError(f"Unknown completion type {completion_type}") - - if stream: - if completion_type == "completion": - return self._handle_completion_generate_stream_response( - model=model, credentials=credentials, response=result, tools=tools, prompt_messages=prompt_messages - ) - return self._handle_chat_generate_stream_response( - model=model, credentials=credentials, response=result, tools=tools, prompt_messages=prompt_messages - ) - - if completion_type == "completion": - return self._handle_completion_generate_response( - model=model, credentials=credentials, response=result, prompt_messages=prompt_messages - ) - return self._handle_chat_generate_response( - model=model, credentials=credentials, response=result, tools=tools, prompt_messages=prompt_messages - ) - - def _to_client_kwargs(self, credentials: dict) -> dict: - """ - Convert invoke kwargs to client kwargs - - :param credentials: credentials dict - :return: client kwargs - """ - if not credentials["server_url"].endswith("/"): - credentials["server_url"] += "/" - - client_kwargs = { - "timeout": Timeout(315.0, read=300.0, write=10.0, connect=5.0), - "api_key": "1", - "base_url": str(URL(credentials["server_url"]) / "v1"), - } - - return client_kwargs - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for OpenAI Compatibility API - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - raise ValueError("User message content must be str") - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls and len(message.tool_calls) > 0: - message_dict["function_call"] = { - "name": message.tool_calls[0].function.name, - "arguments": message.tool_calls[0].function.arguments, - } - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - # copy from core/model_runtime/model_providers/anthropic/llm/llm.py - message = cast(ToolPromptMessage, message) - message_dict = { - "role": "user", - "content": [{"type": "tool_result", "tool_use_id": message.tool_call_id, "content": message.content}], - } - else: - raise ValueError(f"Unknown message type {type(message)}") - - return message_dict - - def _convert_prompt_message_to_completion_prompts(self, messages: list[PromptMessage]) -> str: - """ - Convert PromptMessage to completion prompts - """ - prompts = "" - for message in messages: - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - prompts += f"{message.content}\n" - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - prompts += f"{message.content}\n" - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - prompts += f"{message.content}\n" - else: - raise ValueError(f"Unknown message type {type(message)}") - - return prompts - - def _handle_completion_generate_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: Completion, - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response - """ - if len(response.choices) == 0: - raise InvokeServerUnavailableError("Empty response") - - assistant_message = response.choices[0].text - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_message, tool_calls=[]) - - prompt_tokens = self._get_num_tokens_by_gpt2( - self._convert_prompt_message_to_completion_prompts(prompt_messages) - ) - completion_tokens = self._num_tokens_from_messages(messages=[assistant_prompt_message], tools=[]) - - usage = self._calc_response_usage( - model=model, credentials=credentials, prompt_tokens=prompt_tokens, completion_tokens=completion_tokens - ) - - response = LLMResult( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=response.system_fingerprint, - usage=usage, - message=assistant_prompt_message, - ) - - return response - - def _handle_chat_generate_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: ChatCompletion, - tools: list[PromptMessageTool], - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response - """ - if len(response.choices) == 0: - raise InvokeServerUnavailableError("Empty response") - - assistant_message = response.choices[0].message - - # convert function call to tool call - function_calls = assistant_message.function_call - tool_calls = self._extract_response_tool_calls([function_calls] if function_calls else []) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_message.content, tool_calls=tool_calls) - - prompt_tokens = self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - completion_tokens = self._num_tokens_from_messages(messages=[assistant_prompt_message], tools=tools) - - usage = self._calc_response_usage( - model=model, credentials=credentials, prompt_tokens=prompt_tokens, completion_tokens=completion_tokens - ) - - response = LLMResult( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=response.system_fingerprint, - usage=usage, - message=assistant_prompt_message, - ) - - return response - - def _handle_completion_generate_stream_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: Stream[Completion], - tools: list[PromptMessageTool], - ) -> Generator: - full_response = "" - - for chunk in response: - if len(chunk.choices) == 0: - continue - - delta = chunk.choices[0] - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=delta.text or "", tool_calls=[]) - - if delta.finish_reason is not None: - # temp_assistant_prompt_message is used to calculate usage - temp_assistant_prompt_message = AssistantPromptMessage(content=full_response, tool_calls=[]) - - prompt_tokens = self._get_num_tokens_by_gpt2( - self._convert_prompt_message_to_completion_prompts(prompt_messages) - ) - - completion_tokens = self._num_tokens_from_messages(messages=[temp_assistant_prompt_message], tools=[]) - - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=prompt_tokens, - completion_tokens=completion_tokens, - ) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - usage=usage, - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=0, - message=assistant_prompt_message, - ), - ) - - full_response += delta.text - - def _handle_chat_generate_stream_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: Stream[ChatCompletionChunk], - tools: list[PromptMessageTool], - ) -> Generator: - full_response = "" - - for chunk in response: - if len(chunk.choices) == 0: - continue - - delta = chunk.choices[0] - - if delta.finish_reason is None and (delta.delta.content is None or delta.delta.content == ""): - continue - - # check if there is a tool call in the response - function_calls = None - if delta.delta.function_call: - function_calls = [delta.delta.function_call] - - assistant_message_tool_calls = self._extract_response_tool_calls(function_calls or []) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=delta.delta.content or "", tool_calls=assistant_message_tool_calls - ) - - if delta.finish_reason is not None: - # temp_assistant_prompt_message is used to calculate usage - temp_assistant_prompt_message = AssistantPromptMessage( - content=full_response, tool_calls=assistant_message_tool_calls - ) - - prompt_tokens = self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - completion_tokens = self._num_tokens_from_messages(messages=[temp_assistant_prompt_message], tools=[]) - - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=prompt_tokens, - completion_tokens=completion_tokens, - ) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - usage=usage, - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - ), - ) - - full_response += delta.delta.content - - def _extract_response_tool_calls( - self, response_function_calls: list[FunctionCall] - ) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_function_calls: - for response_tool_call in response_function_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.name, arguments=response_tool_call.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall(id=0, type="function", function=function) - tool_calls.append(tool_call) - - return tool_calls - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [ - APIConnectionError, - APITimeoutError, - ], - InvokeServerUnavailableError: [ - InternalServerError, - ConflictError, - NotFoundError, - UnprocessableEntityError, - PermissionDeniedError, - ], - InvokeRateLimitError: [RateLimitError], - InvokeAuthorizationError: [AuthenticationError], - InvokeBadRequestError: [ValueError], - } diff --git a/api/core/model_runtime/model_providers/localai/localai.py b/api/core/model_runtime/model_providers/localai/localai.py deleted file mode 100644 index 4ff898052b380d..00000000000000 --- a/api/core/model_runtime/model_providers/localai/localai.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class LocalAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/localai/localai.yaml b/api/core/model_runtime/model_providers/localai/localai.yaml deleted file mode 100644 index 864dd7a30c3a6f..00000000000000 --- a/api/core/model_runtime/model_providers/localai/localai.yaml +++ /dev/null @@ -1,72 +0,0 @@ -provider: localai -label: - en_US: LocalAI -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#F3F4F6" -help: - title: - en_US: How to deploy LocalAI - zh_Hans: 如何部署 LocalAI - url: - en_US: https://github.com/go-skynet/LocalAI -supported_model_types: - - llm - - text-embedding - - rerank - - speech2text -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: completion_type - show_on: - - variable: __model_type - value: llm - label: - en_US: Completion type - type: select - required: false - default: chat_completion - placeholder: - zh_Hans: 选择对话类型 - en_US: Select completion type - options: - - value: completion - label: - en_US: Completion - zh_Hans: 补全 - - value: chat_completion - label: - en_US: ChatCompletion - zh_Hans: 对话 - - variable: server_url - label: - zh_Hans: 服务器URL - en_US: Server url - type: text-input - required: true - placeholder: - zh_Hans: 在此输入LocalAI的服务器地址，如 http://192.168.1.100:8080 - en_US: Enter the url of your LocalAI, e.g. http://192.168.1.100:8080 - - variable: context_size - show_on: - - variable: __model_type - value: llm - label: - zh_Hans: 上下文大小 - en_US: Context size - placeholder: - zh_Hans: 输入上下文大小 - en_US: Enter context size - required: false - type: text-input diff --git a/api/core/model_runtime/model_providers/localai/rerank/__init__.py b/api/core/model_runtime/model_providers/localai/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/localai/rerank/rerank.py b/api/core/model_runtime/model_providers/localai/rerank/rerank.py deleted file mode 100644 index 2b0f53bc19e8ec..00000000000000 --- a/api/core/model_runtime/model_providers/localai/rerank/rerank.py +++ /dev/null @@ -1,134 +0,0 @@ -from json import dumps -from typing import Optional - -import httpx -from requests import post -from yarl import URL - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - - -class LocalaiRerankModel(RerankModel): - """ - LocalAI rerank model API is compatible with Jina rerank model API. So just copy the JinaRerankModel class code here. - """ - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n documents to return - :param user: unique user id - :return: rerank result - """ - if len(docs) == 0: - return RerankResult(model=model, docs=[]) - - server_url = credentials["server_url"] - model_name = model - - if not server_url: - raise CredentialsValidateFailedError("server_url is required") - if not model_name: - raise CredentialsValidateFailedError("model_name is required") - - url = server_url - headers = {"Authorization": f"Bearer {credentials.get('api_key')}", "Content-Type": "application/json"} - - data = {"model": model_name, "query": query, "documents": docs, "top_n": top_n} - - try: - response = post(str(URL(url) / "rerank"), headers=headers, data=dumps(data), timeout=10) - response.raise_for_status() - results = response.json() - - rerank_documents = [] - for result in results["results"]: - rerank_document = RerankDocument( - index=result["index"], - text=result["document"]["text"], - score=result["relevance_score"], - ) - if score_threshold is None or result["relevance_score"] >= score_threshold: - rerank_documents.append(rerank_document) - - return RerankResult(model=model, docs=rerank_documents) - except httpx.HTTPStatusError as e: - raise InvokeServerUnavailableError(str(e)) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke( - model=model, - credentials=credentials, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - """ - return { - InvokeConnectionError: [httpx.ConnectError], - InvokeServerUnavailableError: [httpx.RemoteProtocolError], - InvokeRateLimitError: [], - InvokeAuthorizationError: [httpx.HTTPStatusError], - InvokeBadRequestError: [httpx.RequestError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.RERANK, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={}, - ) - - return entity diff --git a/api/core/model_runtime/model_providers/localai/speech2text/__init__.py b/api/core/model_runtime/model_providers/localai/speech2text/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/localai/speech2text/speech2text.py b/api/core/model_runtime/model_providers/localai/speech2text/speech2text.py deleted file mode 100644 index 4b9d0f5bfefd33..00000000000000 --- a/api/core/model_runtime/model_providers/localai/speech2text/speech2text.py +++ /dev/null @@ -1,89 +0,0 @@ -from typing import IO, Optional - -from requests import Request, Session -from yarl import URL - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel - - -class LocalAISpeech2text(Speech2TextModel): - """ - Model class for Local AI Text to speech model. - """ - - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - - url = str(URL(credentials["server_url"]) / "v1/audio/transcriptions") - data = {"model": model} - files = {"file": file} - - session = Session() - request = Request("POST", url, data=data, files=files) - prepared_request = session.prepare_request(request) - response = session.send(prepared_request) - - if "error" in response.json(): - raise InvokeServerUnavailableError("Empty response") - - return response.json()["text"] - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - audio_file_path = self._get_demo_file_path() - - with open(audio_file_path, "rb") as audio_file: - self._invoke(model, credentials, audio_file) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.SPEECH2TEXT, - model_properties={}, - parameter_rules=[], - ) - - return entity diff --git a/api/core/model_runtime/model_providers/localai/text_embedding/__init__.py b/api/core/model_runtime/model_providers/localai/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/minimax/__init__.py b/api/core/model_runtime/model_providers/minimax/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/minimax/_assets/icon_l_en.png b/api/core/model_runtime/model_providers/minimax/_assets/icon_l_en.png deleted file mode 100644 index 5066b525f99c3f36d2f96b3b905aaead8cb263ef..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 5767 zcmV;27I^82P)4ihG1%Y>eBeXACCiemV`emGcfXhK^^C@{4j)LiurJe 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a/api/core/model_runtime/model_providers/minimax/llm/__init__.py b/api/core/model_runtime/model_providers/minimax/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/minimax/llm/abab5-chat.yaml b/api/core/model_runtime/model_providers/minimax/llm/abab5-chat.yaml deleted file mode 100644 index 2c1f79e2b77052..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/abab5-chat.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: abab5-chat -label: - en_US: Abab5-Chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 6144 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 6144 - min: 1 - max: 6144 - - name: mask_sensitive_info - type: boolean - default: true - label: - zh_Hans: 隐私保护 - en_US: Moderate - help: - zh_Hans: 对输出中易涉及隐私问题的文本信息进行打码，目前包括但不限于邮箱、域名、链接、证件号、家庭住址等，默认true，即开启打码 - en_US: Mask the sensitive info of the generated content, such as email/domain/link/address/phone/id.. - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0.015' - output: '0.015' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/minimax/llm/abab5.5-chat.yaml b/api/core/model_runtime/model_providers/minimax/llm/abab5.5-chat.yaml deleted file mode 100644 index 6d29be0d0e8708..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/abab5.5-chat.yaml +++ /dev/null @@ -1,53 +0,0 @@ -model: abab5.5-chat -label: - en_US: Abab5.5-Chat -model_type: llm -features: - - agent-thought - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.01 - max: 1 - default: 0.9 - - name: top_p - use_template: top_p - min: 0.01 - max: 1 - default: 0.95 - - name: max_tokens - use_template: max_tokens - required: true - default: 6144 - min: 1 - max: 16384 - - name: mask_sensitive_info - type: boolean - default: true - label: - zh_Hans: 隐私保护 - en_US: Moderate - help: - zh_Hans: 对输出中易涉及隐私问题的文本信息进行打码，目前包括但不限于邮箱、域名、链接、证件号、家庭住址等，默认true，即开启打码 - en_US: Mask the sensitive info of the generated content, such as email/domain/link/address/phone/id.. - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: plugin_web_search - required: false - default: false - type: boolean - label: - en_US: Enable Web Search - zh_Hans: 开启网页搜索 -pricing: - input: '0.015' - output: '0.015' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/minimax/llm/abab5.5s-chat.yaml b/api/core/model_runtime/model_providers/minimax/llm/abab5.5s-chat.yaml deleted file mode 100644 index aa42bb57395d68..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/abab5.5s-chat.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: abab5.5s-chat -label: - en_US: Abab5.5s-Chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.01 - max: 1 - default: 0.9 - - name: top_p - use_template: top_p - min: 0.01 - max: 1 - default: 0.95 - - name: max_tokens - use_template: max_tokens - required: true - default: 3072 - min: 1 - max: 8192 - - name: mask_sensitive_info - type: boolean - default: true - label: - zh_Hans: 隐私保护 - en_US: Moderate - help: - zh_Hans: 对输出中易涉及隐私问题的文本信息进行打码，目前包括但不限于邮箱、域名、链接、证件号、家庭住址等，默认true，即开启打码 - en_US: Mask the sensitive info of the generated content, such as email/domain/link/address/phone/id.. - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0.005' - output: '0.005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/minimax/llm/abab6-chat.yaml b/api/core/model_runtime/model_providers/minimax/llm/abab6-chat.yaml deleted file mode 100644 index 9188b6b53fa08c..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/abab6-chat.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: abab6-chat -label: - en_US: Abab6-Chat -model_type: llm -features: - - agent-thought - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.01 - max: 1 - default: 0.1 - - name: top_p - use_template: top_p - min: 0.01 - max: 1 - default: 0.9 - - name: max_tokens - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 32768 - - name: mask_sensitive_info - type: boolean - default: true - label: - zh_Hans: 隐私保护 - en_US: Moderate - help: - zh_Hans: 对输出中易涉及隐私问题的文本信息进行打码，目前包括但不限于邮箱、域名、链接、证件号、家庭住址等，默认true，即开启打码 - en_US: Mask the sensitive info of the generated content, such as email/domain/link/address/phone/id.. - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0.1' - output: '0.1' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/minimax/llm/abab6.5-chat.yaml b/api/core/model_runtime/model_providers/minimax/llm/abab6.5-chat.yaml deleted file mode 100644 index 5d717d5f8ccd9d..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/abab6.5-chat.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: abab6.5-chat -label: - en_US: Abab6.5-Chat -model_type: llm -features: - - agent-thought - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.01 - max: 1 - default: 0.1 - - name: top_p - use_template: top_p - min: 0.01 - max: 1 - default: 0.95 - - name: max_tokens - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 8192 - - name: mask_sensitive_info - type: boolean - default: true - label: - zh_Hans: 隐私保护 - en_US: Moderate - help: - zh_Hans: 对输出中易涉及隐私问题的文本信息进行打码，目前包括但不限于邮箱、域名、链接、证件号、家庭住址等，默认true，即开启打码 - en_US: Mask the sensitive info of the generated content, such as email/domain/link/address/phone/id.. - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0.03' - output: '0.03' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/minimax/llm/abab6.5s-chat.yaml b/api/core/model_runtime/model_providers/minimax/llm/abab6.5s-chat.yaml deleted file mode 100644 index 4631fe67e44cb7..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/abab6.5s-chat.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: abab6.5s-chat -label: - en_US: Abab6.5s-Chat -model_type: llm -features: - - agent-thought - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 245760 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.01 - max: 1 - default: 0.1 - - name: top_p - use_template: top_p - min: 0.01 - max: 1 - default: 0.95 - - name: max_tokens - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 245760 - - name: mask_sensitive_info - type: boolean - default: true - label: - zh_Hans: 隐私保护 - en_US: Moderate - help: - zh_Hans: 对输出中易涉及隐私问题的文本信息进行打码，目前包括但不限于邮箱、域名、链接、证件号、家庭住址等，默认true，即开启打码 - en_US: Mask the sensitive info of the generated content, such as email/domain/link/address/phone/id.. - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0.01' - output: '0.01' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/minimax/llm/chat_completion.py b/api/core/model_runtime/model_providers/minimax/llm/chat_completion.py deleted file mode 100644 index 88cc0e8e0f32d0..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/chat_completion.py +++ /dev/null @@ -1,166 +0,0 @@ -from collections.abc import Generator -from json import dumps, loads -from typing import Any, Union - -from requests import Response, post - -from core.model_runtime.model_providers.minimax.llm.errors import ( - BadRequestError, - InsufficientAccountBalanceError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) -from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage - - -class MinimaxChatCompletion: - """ - Minimax Chat Completion API - """ - - def generate( - self, - model: str, - api_key: str, - group_id: str, - prompt_messages: list[MinimaxMessage], - model_parameters: dict, - tools: list[dict[str, Any]], - stop: list[str] | None, - stream: bool, - user: str, - ) -> Union[MinimaxMessage, Generator[MinimaxMessage, None, None]]: - """ - generate chat completion - """ - if not api_key or not group_id: - raise InvalidAPIKeyError("Invalid API key or group ID") - - url = f"https://api.minimax.chat/v1/text/chatcompletion?GroupId={group_id}" - - extra_kwargs = {} - - if "max_tokens" in model_parameters and type(model_parameters["max_tokens"]) == int: - extra_kwargs["tokens_to_generate"] = model_parameters["max_tokens"] - - if "temperature" in model_parameters and type(model_parameters["temperature"]) == float: - extra_kwargs["temperature"] = model_parameters["temperature"] - - if "top_p" in model_parameters and type(model_parameters["top_p"]) == float: - extra_kwargs["top_p"] = model_parameters["top_p"] - - prompt = "你是一个什么都懂的专家" - - role_meta = {"user_name": "我", "bot_name": "专家"} - - # check if there is a system message - if len(prompt_messages) == 0: - raise BadRequestError("At least one message is required") - - if prompt_messages[0].role == MinimaxMessage.Role.SYSTEM.value: - if prompt_messages[0].content: - prompt = prompt_messages[0].content - prompt_messages = prompt_messages[1:] - - # check if there is a user message - if len(prompt_messages) == 0: - raise BadRequestError("At least one user message is required") - - messages = [ - { - "sender_type": message.role, - "text": message.content, - } - for message in prompt_messages - ] - - headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"} - - body = { - "model": model, - "messages": messages, - "prompt": prompt, - "role_meta": role_meta, - "stream": stream, - **extra_kwargs, - } - - try: - response = post(url=url, data=dumps(body), headers=headers, stream=stream, timeout=(10, 300)) - except Exception as e: - raise InternalServerError(e) - - if response.status_code != 200: - raise InternalServerError(response.text) - - if stream: - return self._handle_stream_chat_generate_response(response) - return self._handle_chat_generate_response(response) - - def _handle_error(self, code: int, msg: str): - if code in {1000, 1001, 1013, 1027}: - raise InternalServerError(msg) - elif code in {1002, 1039}: - raise RateLimitReachedError(msg) - elif code == 1004: - raise InvalidAuthenticationError(msg) - elif code == 1008: - raise InsufficientAccountBalanceError(msg) - elif code == 2013: - raise BadRequestError(msg) - else: - raise InternalServerError(msg) - - def _handle_chat_generate_response(self, response: Response) -> MinimaxMessage: - """ - handle chat generate response - """ - response = response.json() - if "base_resp" in response and response["base_resp"]["status_code"] != 0: - code = response["base_resp"]["status_code"] - msg = response["base_resp"]["status_msg"] - self._handle_error(code, msg) - - message = MinimaxMessage(content=response["reply"], role=MinimaxMessage.Role.ASSISTANT.value) - message.usage = { - "prompt_tokens": 0, - "completion_tokens": response["usage"]["total_tokens"], - "total_tokens": response["usage"]["total_tokens"], - } - message.stop_reason = response["choices"][0]["finish_reason"] - return message - - def _handle_stream_chat_generate_response(self, response: Response) -> Generator[MinimaxMessage, None, None]: - """ - handle stream chat generate response - """ - for line in response.iter_lines(): - if not line: - continue - line: str = line.decode("utf-8") - if line.startswith("data: "): - line = line[6:].strip() - data = loads(line) - - if "base_resp" in data and data["base_resp"]["status_code"] != 0: - code = data["base_resp"]["status_code"] - msg = data["base_resp"]["status_msg"] - self._handle_error(code, msg) - - if data["reply"]: - total_tokens = data["usage"]["total_tokens"] - message = MinimaxMessage(role=MinimaxMessage.Role.ASSISTANT.value, content="") - message.usage = {"prompt_tokens": 0, "completion_tokens": total_tokens, "total_tokens": total_tokens} - message.stop_reason = data["choices"][0]["finish_reason"] - yield message - return - - choices = data.get("choices", []) - if len(choices) == 0: - continue - - for choice in choices: - message = choice["delta"] - yield MinimaxMessage(content=message, role=MinimaxMessage.Role.ASSISTANT.value) diff --git a/api/core/model_runtime/model_providers/minimax/llm/chat_completion_pro.py b/api/core/model_runtime/model_providers/minimax/llm/chat_completion_pro.py deleted file mode 100644 index 8b8fdbb6bdf558..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/chat_completion_pro.py +++ /dev/null @@ -1,191 +0,0 @@ -from collections.abc import Generator -from json import dumps, loads -from typing import Any, Union - -from requests import Response, post - -from core.model_runtime.model_providers.minimax.llm.errors import ( - BadRequestError, - InsufficientAccountBalanceError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) -from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage - - -class MinimaxChatCompletionPro: - """ - Minimax Chat Completion Pro API, supports function calling - however, we do not have enough time and energy to implement it, but the parameters are reserved - """ - - def generate( - self, - model: str, - api_key: str, - group_id: str, - prompt_messages: list[MinimaxMessage], - model_parameters: dict, - tools: list[dict[str, Any]], - stop: list[str] | None, - stream: bool, - user: str, - ) -> Union[MinimaxMessage, Generator[MinimaxMessage, None, None]]: - """ - generate chat completion - """ - if not api_key or not group_id: - raise InvalidAPIKeyError("Invalid API key or group ID") - - url = f"https://api.minimax.chat/v1/text/chatcompletion_pro?GroupId={group_id}" - - extra_kwargs = {} - - if "max_tokens" in model_parameters and type(model_parameters["max_tokens"]) == int: - extra_kwargs["tokens_to_generate"] = model_parameters["max_tokens"] - - if "temperature" in model_parameters and type(model_parameters["temperature"]) == float: - extra_kwargs["temperature"] = model_parameters["temperature"] - - if "top_p" in model_parameters and type(model_parameters["top_p"]) == float: - extra_kwargs["top_p"] = model_parameters["top_p"] - - if "mask_sensitive_info" in model_parameters and type(model_parameters["mask_sensitive_info"]) == bool: - extra_kwargs["mask_sensitive_info"] = model_parameters["mask_sensitive_info"] - - if model_parameters.get("plugin_web_search"): - extra_kwargs["plugins"] = ["plugin_web_search"] - - bot_setting = {"bot_name": "专家", "content": "你是一个什么都懂的专家"} - - reply_constraints = {"sender_type": "BOT", "sender_name": "专家"} - - # check if there is a system message - if len(prompt_messages) == 0: - raise BadRequestError("At least one message is required") - - if prompt_messages[0].role == MinimaxMessage.Role.SYSTEM.value: - if prompt_messages[0].content: - bot_setting["content"] = prompt_messages[0].content - prompt_messages = prompt_messages[1:] - - # check if there is a user message - if len(prompt_messages) == 0: - raise BadRequestError("At least one user message is required") - - messages = [message.to_dict() for message in prompt_messages] - - headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"} - - body = { - "model": model, - "messages": messages, - "bot_setting": [bot_setting], - "reply_constraints": reply_constraints, - "stream": stream, - **extra_kwargs, - } - - if tools: - body["functions"] = tools - body["function_call"] = {"type": "auto"} - - try: - response = post(url=url, data=dumps(body), headers=headers, stream=stream, timeout=(10, 300)) - except Exception as e: - raise InternalServerError(e) - - if response.status_code != 200: - raise InternalServerError(response.text) - - if stream: - return self._handle_stream_chat_generate_response(response) - return self._handle_chat_generate_response(response) - - def _handle_error(self, code: int, msg: str): - if code in {1000, 1001, 1013, 1027}: - raise InternalServerError(msg) - elif code in {1002, 1039}: - raise RateLimitReachedError(msg) - elif code == 1004: - raise InvalidAuthenticationError(msg) - elif code == 1008: - raise InsufficientAccountBalanceError(msg) - elif code == 2013: - raise BadRequestError(msg) - else: - raise InternalServerError(msg) - - def _handle_chat_generate_response(self, response: Response) -> MinimaxMessage: - """ - handle chat generate response - """ - response = response.json() - if "base_resp" in response and response["base_resp"]["status_code"] != 0: - code = response["base_resp"]["status_code"] - msg = response["base_resp"]["status_msg"] - self._handle_error(code, msg) - - message = MinimaxMessage(content=response["reply"], role=MinimaxMessage.Role.ASSISTANT.value) - message.usage = { - "prompt_tokens": 0, - "completion_tokens": response["usage"]["total_tokens"], - "total_tokens": response["usage"]["total_tokens"], - } - message.stop_reason = response["choices"][0]["finish_reason"] - return message - - def _handle_stream_chat_generate_response(self, response: Response) -> Generator[MinimaxMessage, None, None]: - """ - handle stream chat generate response - """ - for line in response.iter_lines(): - if not line: - continue - line: str = line.decode("utf-8") - if line.startswith("data: "): - line = line[6:].strip() - data = loads(line) - - if "base_resp" in data and data["base_resp"]["status_code"] != 0: - code = data["base_resp"]["status_code"] - msg = data["base_resp"]["status_msg"] - self._handle_error(code, msg) - - # final chunk - if data["reply"] or data.get("usage"): - total_tokens = data["usage"]["total_tokens"] - minimax_message = MinimaxMessage(role=MinimaxMessage.Role.ASSISTANT.value, content="") - minimax_message.usage = { - "prompt_tokens": 0, - "completion_tokens": total_tokens, - "total_tokens": total_tokens, - } - minimax_message.stop_reason = data["choices"][0]["finish_reason"] - - choices = data.get("choices", []) - if len(choices) > 0: - for choice in choices: - message = choice["messages"][0] - # append function_call message - if "function_call" in message: - function_call_message = MinimaxMessage(content="", role=MinimaxMessage.Role.ASSISTANT.value) - function_call_message.function_call = message["function_call"] - yield function_call_message - - yield minimax_message - return - - # partial chunk - choices = data.get("choices", []) - if len(choices) == 0: - continue - - for choice in choices: - message = choice["messages"][0] - # append text message - if "text" in message: - minimax_message = MinimaxMessage(content=message["text"], role=MinimaxMessage.Role.ASSISTANT.value) - yield minimax_message diff --git a/api/core/model_runtime/model_providers/minimax/llm/errors.py b/api/core/model_runtime/model_providers/minimax/llm/errors.py deleted file mode 100644 index 309b5cf413bd54..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/errors.py +++ /dev/null @@ -1,22 +0,0 @@ -class InvalidAuthenticationError(Exception): - pass - - -class InvalidAPIKeyError(Exception): - pass - - -class RateLimitReachedError(Exception): - pass - - -class InsufficientAccountBalanceError(Exception): - pass - - -class InternalServerError(Exception): - pass - - -class BadRequestError(Exception): - pass diff --git a/api/core/model_runtime/model_providers/minimax/llm/llm.py b/api/core/model_runtime/model_providers/minimax/llm/llm.py deleted file mode 100644 index 4250c40cfb94b1..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/llm.py +++ /dev/null @@ -1,271 +0,0 @@ -from collections.abc import Generator - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.minimax.llm.chat_completion import MinimaxChatCompletion -from core.model_runtime.model_providers.minimax.llm.chat_completion_pro import MinimaxChatCompletionPro -from core.model_runtime.model_providers.minimax.llm.errors import ( - BadRequestError, - InsufficientAccountBalanceError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) -from core.model_runtime.model_providers.minimax.llm.types import MinimaxMessage - - -class MinimaxLargeLanguageModel(LargeLanguageModel): - model_apis = { - "abab6.5s-chat": MinimaxChatCompletionPro, - "abab6.5-chat": MinimaxChatCompletionPro, - "abab6-chat": MinimaxChatCompletionPro, - "abab5.5s-chat": MinimaxChatCompletionPro, - "abab5.5-chat": MinimaxChatCompletionPro, - "abab5-chat": MinimaxChatCompletion, - } - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - return self._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate credentials for Baichuan model - """ - if model not in self.model_apis: - raise CredentialsValidateFailedError(f"Invalid model: {model}") - - if not credentials.get("minimax_api_key"): - raise CredentialsValidateFailedError("Invalid API key") - - if not credentials.get("minimax_group_id"): - raise CredentialsValidateFailedError("Invalid group ID") - - # ping - instance = MinimaxChatCompletionPro() - try: - instance.generate( - model=model, - api_key=credentials["minimax_api_key"], - group_id=credentials["minimax_group_id"], - prompt_messages=[MinimaxMessage(content="ping", role="USER")], - model_parameters={}, - tools=[], - stop=[], - stream=False, - user="", - ) - except (InvalidAuthenticationError, InsufficientAccountBalanceError) as e: - raise CredentialsValidateFailedError(f"Invalid API key: {e}") - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - return self._num_tokens_from_messages(prompt_messages, tools) - - def _num_tokens_from_messages(self, messages: list[PromptMessage], tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for minimax model - - not like ChatGLM, Minimax has a special prompt structure, we could not find a proper way - to calculate the num tokens, so we use str() to convert the prompt to string - - Minimax does not provide their own tokenizer of adab5.5 and abab5 model - therefore, we use gpt2 tokenizer instead - """ - messages_dict = [self._convert_prompt_message_to_minimax_message(m).to_dict() for m in messages] - return self._get_num_tokens_by_gpt2(str(messages_dict)) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - """ - use MinimaxChatCompletionPro as the type of client, anyway, MinimaxChatCompletion has the same interface - """ - client: MinimaxChatCompletionPro = self.model_apis[model]() - - if tools: - tools = [ - {"name": tool.name, "description": tool.description, "parameters": tool.parameters} for tool in tools - ] - - response = client.generate( - model=model, - api_key=credentials["minimax_api_key"], - group_id=credentials["minimax_group_id"], - prompt_messages=[self._convert_prompt_message_to_minimax_message(message) for message in prompt_messages], - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - if stream: - return self._handle_chat_generate_stream_response( - model=model, prompt_messages=prompt_messages, credentials=credentials, response=response - ) - return self._handle_chat_generate_response( - model=model, prompt_messages=prompt_messages, credentials=credentials, response=response - ) - - def _convert_prompt_message_to_minimax_message(self, prompt_message: PromptMessage) -> MinimaxMessage: - """ - convert PromptMessage to MinimaxMessage so that we can use MinimaxChatCompletionPro interface - """ - if isinstance(prompt_message, SystemPromptMessage): - return MinimaxMessage(role=MinimaxMessage.Role.SYSTEM.value, content=prompt_message.content) - elif isinstance(prompt_message, UserPromptMessage): - return MinimaxMessage(role=MinimaxMessage.Role.USER.value, content=prompt_message.content) - elif isinstance(prompt_message, AssistantPromptMessage): - if prompt_message.tool_calls: - message = MinimaxMessage(role=MinimaxMessage.Role.ASSISTANT.value, content="") - message.function_call = { - "name": prompt_message.tool_calls[0].function.name, - "arguments": prompt_message.tool_calls[0].function.arguments, - } - return message - return MinimaxMessage(role=MinimaxMessage.Role.ASSISTANT.value, content=prompt_message.content) - elif isinstance(prompt_message, ToolPromptMessage): - return MinimaxMessage(role=MinimaxMessage.Role.FUNCTION.value, content=prompt_message.content) - else: - raise NotImplementedError(f"Prompt message type {type(prompt_message)} is not supported") - - def _handle_chat_generate_response( - self, model: str, prompt_messages: list[PromptMessage], credentials: dict, response: MinimaxMessage - ) -> LLMResult: - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=response.usage["prompt_tokens"], - completion_tokens=response.usage["completion_tokens"], - ) - return LLMResult( - model=model, - prompt_messages=prompt_messages, - message=AssistantPromptMessage( - content=response.content, - tool_calls=[], - ), - usage=usage, - ) - - def _handle_chat_generate_stream_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: Generator[MinimaxMessage, None, None], - ) -> Generator[LLMResultChunk, None, None]: - for message in response: - if message.usage: - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=message.usage["prompt_tokens"], - completion_tokens=message.usage["completion_tokens"], - ) - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=message.content, tool_calls=[]), - usage=usage, - finish_reason=message.stop_reason or None, - ), - ) - elif message.function_call: - if "name" not in message.function_call or "arguments" not in message.function_call: - continue - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage( - content="", - tool_calls=[ - AssistantPromptMessage.ToolCall( - id="", - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=message.function_call["name"], arguments=message.function_call["arguments"] - ), - ) - ], - ), - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=message.content, tool_calls=[]), - finish_reason=message.stop_reason or None, - ), - ) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [InternalServerError], - InvokeRateLimitError: [RateLimitReachedError], - InvokeAuthorizationError: [ - InvalidAuthenticationError, - InsufficientAccountBalanceError, - InvalidAPIKeyError, - ], - InvokeBadRequestError: [BadRequestError, KeyError], - } diff --git a/api/core/model_runtime/model_providers/minimax/llm/types.py b/api/core/model_runtime/model_providers/minimax/llm/types.py deleted file mode 100644 index 88ebe5e2e00e7a..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/llm/types.py +++ /dev/null @@ -1,30 +0,0 @@ -from enum import Enum -from typing import Any - - -class MinimaxMessage: - class Role(Enum): - USER = "USER" - ASSISTANT = "BOT" - SYSTEM = "SYSTEM" - FUNCTION = "FUNCTION" - - role: str = Role.USER.value - content: str - usage: dict[str, int] = None - stop_reason: str = "" - function_call: dict[str, Any] = None - - def to_dict(self) -> dict[str, Any]: - if self.function_call and self.role == MinimaxMessage.Role.ASSISTANT.value: - return {"sender_type": "BOT", "sender_name": "专家", "text": "", "function_call": self.function_call} - - return { - "sender_type": self.role, - "sender_name": "我" if self.role == "USER" else "专家", - "text": self.content, - } - - def __init__(self, content: str, role: str = "USER") -> None: - self.content = content - self.role = role diff --git a/api/core/model_runtime/model_providers/minimax/minimax.py b/api/core/model_runtime/model_providers/minimax/minimax.py deleted file mode 100644 index 5a761903a1eb12..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/minimax.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class MinimaxProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `abab5.5-chat` model for validate, - model_instance.validate_credentials(model="abab5.5-chat", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise CredentialsValidateFailedError(f"{ex}") diff --git a/api/core/model_runtime/model_providers/minimax/minimax.yaml b/api/core/model_runtime/model_providers/minimax/minimax.yaml deleted file mode 100644 index 0a97ff9bb98758..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/minimax.yaml +++ /dev/null @@ -1,37 +0,0 @@ -provider: minimax -label: - en_US: Minimax -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -background: "#FFEFEF" -help: - title: - en_US: Get your API Key from Minimax - zh_Hans: 从 Minimax 获取您的 API Key - url: - en_US: https://api.minimax.chat/user-center/basic-information/interface-key -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: minimax_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: minimax_group_id - label: - en_US: Group ID - type: text-input - required: true - placeholder: - zh_Hans: 在此输入您的 Group ID - en_US: Enter your group ID diff --git a/api/core/model_runtime/model_providers/minimax/text_embedding/__init__.py b/api/core/model_runtime/model_providers/minimax/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/minimax/text_embedding/embo-01.yaml b/api/core/model_runtime/model_providers/minimax/text_embedding/embo-01.yaml deleted file mode 100644 index 33546eafd3f54e..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/text_embedding/embo-01.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embo-01 -model_type: text-embedding -model_properties: - context_size: 4096 - max_chunks: 1 -pricing: - input: '0.0005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/mistralai/__init__.py b/api/core/model_runtime/model_providers/mistralai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git 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zKB(hKE4<*mIltVs^ggG1b~H0?N+ zmEe{A2kJHcj(hLc+Qt!s+S`n7lCGOFDx5iTS^ugQ<=uMlPoUW1=xWrYZ5>iX*eL|b z%Lx;A)v0>(9mIMbDJN42)R0c7pcD{t?OTbx&VtVY3?w+SR`UOROKj?Ki=EpTNL4B6 z{UB(I;9@DE8B1o`=E3$b%vxPIblwtlN&EfkUDX5;P}Z*b7edg`JnjP0d4CZfuNOA2 zJ+ckc^PW2iD!^U-VVBmG|CEQX@`=z4(r?_O4mw|eJ{unCAs7hB!ng{<6uvF|* diff --git a/api/core/model_runtime/model_providers/mistralai/llm/_position.yaml b/api/core/model_runtime/model_providers/mistralai/llm/_position.yaml deleted file mode 100644 index bdb06b7fff6376..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/_position.yaml +++ /dev/null @@ -1,11 +0,0 @@ -- pixtral-12b-2409 -- codestral-latest -- mistral-embed -- open-mistral-nemo -- open-codestral-mamba -- open-mistral-7b -- open-mixtral-8x7b -- open-mixtral-8x22b -- mistral-small-latest -- mistral-medium-latest -- mistral-large-latest diff --git a/api/core/model_runtime/model_providers/mistralai/llm/codestral-latest.yaml b/api/core/model_runtime/model_providers/mistralai/llm/codestral-latest.yaml deleted file mode 100644 index 5f1260233fe97b..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/codestral-latest.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: codestral-latest -label: - zh_Hans: codestral-latest - en_US: codestral-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 4096 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/llm.py b/api/core/model_runtime/model_providers/mistralai/llm/llm.py deleted file mode 100644 index da60bd7661d597..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/llm.py +++ /dev/null @@ -1,36 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class MistralAILargeLanguageModel(OAIAPICompatLargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials) - - # mistral dose not support user/stop arguments - stop = [] - user = None - - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - @staticmethod - def _add_custom_parameters(credentials: dict) -> None: - credentials["mode"] = "chat" - credentials["endpoint_url"] = "https://api.mistral.ai/v1" diff --git a/api/core/model_runtime/model_providers/mistralai/llm/mistral-embed.yaml b/api/core/model_runtime/model_providers/mistralai/llm/mistral-embed.yaml deleted file mode 100644 index d759103d08a944..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/mistral-embed.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: mistral-embed -label: - zh_Hans: mistral-embed - en_US: mistral-embed -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/mistral-large-latest.yaml b/api/core/model_runtime/model_providers/mistralai/llm/mistral-large-latest.yaml deleted file mode 100644 index a0d07a2bf801bf..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/mistral-large-latest.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: mistral-large-latest -label: - zh_Hans: mistral-large-latest - en_US: mistral-large-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8000 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/mistral-medium-latest.yaml b/api/core/model_runtime/model_providers/mistralai/llm/mistral-medium-latest.yaml deleted file mode 100644 index 7c7440894c0c9c..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/mistral-medium-latest.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: mistral-medium-latest -label: - zh_Hans: mistral-medium-latest - en_US: mistral-medium-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8000 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.0027' - output: '0.0081' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/mistral-small-latest.yaml b/api/core/model_runtime/model_providers/mistralai/llm/mistral-small-latest.yaml deleted file mode 100644 index 865e6102262196..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/mistral-small-latest.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: mistral-small-latest -label: - zh_Hans: mistral-small-latest - en_US: mistral-small-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8000 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/open-codestral-mamba.yaml b/api/core/model_runtime/model_providers/mistralai/llm/open-codestral-mamba.yaml deleted file mode 100644 index d7ffb9ea020848..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/open-codestral-mamba.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: open-codestral-mamba -label: - zh_Hans: open-codestral-mamba - en_US: open-codestral-mamba -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 256000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 16384 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/open-mistral-7b.yaml b/api/core/model_runtime/model_providers/mistralai/llm/open-mistral-7b.yaml deleted file mode 100644 index ac2922695999c0..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/open-mistral-7b.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: open-mistral-7b -label: - zh_Hans: open-mistral-7b - en_US: open-mistral-7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 2048 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.00025' - output: '0.00025' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/open-mistral-nemo.yaml b/api/core/model_runtime/model_providers/mistralai/llm/open-mistral-nemo.yaml deleted file mode 100644 index dcda4fbce7e82c..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/open-mistral-nemo.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: open-mistral-nemo -label: - zh_Hans: open-mistral-nemo - en_US: open-mistral-nemo -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8192 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/open-mixtral-8x22b.yaml b/api/core/model_runtime/model_providers/mistralai/llm/open-mixtral-8x22b.yaml deleted file mode 100644 index 325fafd497300e..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/open-mixtral-8x22b.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: open-mixtral-8x22b -label: - zh_Hans: open-mixtral-8x22b - en_US: open-mixtral-8x22b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 64000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8000 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/open-mixtral-8x7b.yaml b/api/core/model_runtime/model_providers/mistralai/llm/open-mixtral-8x7b.yaml deleted file mode 100644 index d217e5e7e98c42..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/open-mixtral-8x7b.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: open-mixtral-8x7b -label: - zh_Hans: open-mixtral-8x7b - en_US: open-mixtral-8x7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8000 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.0007' - output: '0.0007' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/llm/pixtral-12b-2409.yaml b/api/core/model_runtime/model_providers/mistralai/llm/pixtral-12b-2409.yaml deleted file mode 100644 index 0b002b49cac8e0..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/llm/pixtral-12b-2409.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: pixtral-12b-2409 -label: - zh_Hans: pixtral-12b-2409 - en_US: pixtral-12b-2409 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8192 - - name: safe_prompt - default: false - type: boolean - help: - en_US: Whether to inject a safety prompt before all conversations. - zh_Hans: 是否开启提示词审查 - label: - en_US: SafePrompt - zh_Hans: 提示词审查 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: RandomSeed - zh_Hans: 随机数种子 - default: 0 - min: 0 - max: 2147483647 -pricing: - input: '0.008' - output: '0.024' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mistralai/mistralai.py b/api/core/model_runtime/model_providers/mistralai/mistralai.py deleted file mode 100644 index 7f9db8da1c1ddf..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/mistralai.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class MistralAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="open-mistral-7b", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/mistralai/mistralai.yaml b/api/core/model_runtime/model_providers/mistralai/mistralai.yaml deleted file mode 100644 index c9b4226ea6e573..00000000000000 --- a/api/core/model_runtime/model_providers/mistralai/mistralai.yaml +++ /dev/null @@ -1,31 +0,0 @@ -provider: mistralai -label: - en_US: MistralAI -description: - en_US: Models provided by MistralAI, such as open-mistral-7b and mistral-large-latest. - zh_Hans: MistralAI 提供的模型，例如 open-mistral-7b 和 mistral-large-latest。 -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -background: "#FFFFFF" -help: - title: - en_US: Get your API Key from MistralAI - zh_Hans: 从 MistralAI 获取 API Key - url: - en_US: https://console.mistral.ai/api-keys/ -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/mixedbread/__init__.py b/api/core/model_runtime/model_providers/mixedbread/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/mixedbread/_assets/icon_l_en.png b/api/core/model_runtime/model_providers/mixedbread/_assets/icon_l_en.png deleted file mode 100644 index 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zM3OwagBT{3J?b8`b5@-TMR=mFi`)k~mYA^+?yGigabY(g1?<^1qkIn%Dw7AwRitNk zG;4C&R_^0I%?u3GtHgaQPeWZ8-#rHMCMIyX&u5| z-5TKK{>Xn~_6eESUKSP@z2a>)3(k2aKU87L`9mquTnc-JC#`|z{Pjd&yAkO%5BNwJ z@JOPwTFINN64LB|9FAcaT^7a_Y5qBRm^R}IwCP+(ojpijp|m!h{>kCHJaHs4-hjaWH#zqgnD6&U?{7o9wb^9EzqW0SVY|4j% zYs5XPgKHDoPgg9YCw5x=C1=4$6))O(MCGna4M>Sxjy= z0vV@C5q|R0`o^HR3KBZ3f+Eci*S*@iV$6xLq$i#Am9;eNHbCmqt6a-T#5HZnnneaw zS;zg;L6Qbp;eD@D()yJt1)%eORcv*M+`>bHGD=`?NFXZ*16C~eDd%P&e;ceex_@@k z@fZnb;b)j*tBR@g=*S(&Rh%}PKr!eGI^FiC>U2&P)==h%6vD>IioI)jI&n`uCW6~UH z?3Ror16b{?Dv@XvA0)9PhXOk;Oj&`M5&Qx43djohe`+})z None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.TEXT_EMBEDDING) - - # Use `mxbai-embed-large-v1` model for validate, - model_instance.validate_credentials(model="mxbai-embed-large-v1", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/mixedbread/mixedbread.yaml b/api/core/model_runtime/model_providers/mixedbread/mixedbread.yaml deleted file mode 100644 index 2f43aea6ade2c6..00000000000000 --- a/api/core/model_runtime/model_providers/mixedbread/mixedbread.yaml +++ /dev/null @@ -1,31 +0,0 @@ -provider: mixedbread -label: - en_US: MixedBread -description: - en_US: Embedding and Rerank Model Supported -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -background: "#EFFDFD" -help: - title: - en_US: Get your API key from MixedBread AI - zh_Hans: 从 MixedBread 获取 API Key - url: - en_US: https://www.mixedbread.ai/ -supported_model_types: - - text-embedding - - rerank -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/mixedbread/rerank/__init__.py b/api/core/model_runtime/model_providers/mixedbread/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/mixedbread/rerank/mxbai-rerank-large-v1-en.yaml b/api/core/model_runtime/model_providers/mixedbread/rerank/mxbai-rerank-large-v1-en.yaml deleted file mode 100644 index beda2199537450..00000000000000 --- a/api/core/model_runtime/model_providers/mixedbread/rerank/mxbai-rerank-large-v1-en.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: mxbai-rerank-large-v1 -model_type: rerank -model_properties: - context_size: 512 diff --git a/api/core/model_runtime/model_providers/mixedbread/rerank/rerank.py b/api/core/model_runtime/model_providers/mixedbread/rerank/rerank.py deleted file mode 100644 index bf3c12fd86dc35..00000000000000 --- a/api/core/model_runtime/model_providers/mixedbread/rerank/rerank.py +++ /dev/null @@ -1,125 +0,0 @@ -from typing import Optional - -import httpx - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - - -class MixedBreadRerankModel(RerankModel): - """ - Model class for MixedBread rerank model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n documents to return - :param user: unique user id - :return: rerank result - """ - if len(docs) == 0: - return RerankResult(model=model, docs=[]) - - base_url = credentials.get("base_url", "https://api.mixedbread.ai/v1") - base_url = base_url.removesuffix("/") - - try: - response = httpx.post( - base_url + "/reranking", - json={"model": model, "query": query, "input": docs, "top_k": top_n, "return_input": True}, - headers={"Authorization": f"Bearer {credentials.get('api_key')}", "Content-Type": "application/json"}, - ) - response.raise_for_status() - results = response.json() - - rerank_documents = [] - for result in results["data"]: - rerank_document = RerankDocument( - index=result["index"], - text=result["input"], - score=result["score"], - ) - if score_threshold is None or result["score"] >= score_threshold: - rerank_documents.append(rerank_document) - - return RerankResult(model=model, docs=rerank_documents) - except httpx.HTTPStatusError as e: - raise InvokeServerUnavailableError(str(e)) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke( - model=model, - credentials=credentials, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - """ - return { - InvokeConnectionError: [httpx.ConnectError], - InvokeServerUnavailableError: [httpx.RemoteProtocolError], - InvokeRateLimitError: [], - InvokeAuthorizationError: [httpx.HTTPStatusError], - InvokeBadRequestError: [httpx.RequestError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.RERANK, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", "512"))}, - ) - - return entity diff --git a/api/core/model_runtime/model_providers/mixedbread/text_embedding/__init__.py b/api/core/model_runtime/model_providers/mixedbread/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/mixedbread/text_embedding/mxbai-embed-2d-large-v1-en.yaml b/api/core/model_runtime/model_providers/mixedbread/text_embedding/mxbai-embed-2d-large-v1-en.yaml deleted file mode 100644 index 0c3c863d06b89a..00000000000000 --- a/api/core/model_runtime/model_providers/mixedbread/text_embedding/mxbai-embed-2d-large-v1-en.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: mxbai-embed-2d-large-v1 -model_type: text-embedding -model_properties: - context_size: 512 -pricing: - input: '0.0001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/mixedbread/text_embedding/mxbai-embed-large-v1-en.yaml b/api/core/model_runtime/model_providers/mixedbread/text_embedding/mxbai-embed-large-v1-en.yaml deleted file mode 100644 index 0c5cda2a72a99e..00000000000000 --- a/api/core/model_runtime/model_providers/mixedbread/text_embedding/mxbai-embed-large-v1-en.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: mxbai-embed-large-v1 -model_type: text-embedding -model_properties: - context_size: 512 -pricing: - input: '0.0001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/model_provider_factory.py b/api/core/model_runtime/model_providers/model_provider_factory.py index e2d17e32575920..1370676f0e1d85 100644 --- a/api/core/model_runtime/model_providers/model_provider_factory.py +++ b/api/core/model_runtime/model_providers/model_provider_factory.py @@ -3,61 +3,116 @@ from collections.abc import Sequence from typing import Optional -from pydantic import BaseModel, ConfigDict +from pydantic import BaseModel -from core.helper.module_import_helper import load_single_subclass_from_source from core.helper.position_helper import get_provider_position_map, sort_to_dict_by_position_map -from core.model_runtime.entities.model_entities import ModelType +from core.model_runtime.entities.model_entities import AIModelEntity, ModelType from core.model_runtime.entities.provider_entities import ProviderConfig, ProviderEntity, SimpleProviderEntity -from core.model_runtime.model_providers.__base.model_provider import ModelProvider +from core.model_runtime.model_providers.__base.ai_model import AIModel +from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel +from core.model_runtime.model_providers.__base.moderation_model import ModerationModel +from core.model_runtime.model_providers.__base.rerank_model import RerankModel +from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel +from core.model_runtime.model_providers.__base.text2img_model import Text2ImageModel +from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel +from core.model_runtime.model_providers.__base.tts_model import TTSModel from core.model_runtime.schema_validators.model_credential_schema_validator import ModelCredentialSchemaValidator from core.model_runtime.schema_validators.provider_credential_schema_validator import ProviderCredentialSchemaValidator +from core.plugin.entities.plugin_daemon import PluginModelProviderEntity +from core.plugin.manager.asset import PluginAssetManager +from core.plugin.manager.model import PluginModelManager logger = logging.getLogger(__name__) class ModelProviderExtension(BaseModel): - model_config = ConfigDict(arbitrary_types_allowed=True) - - provider_instance: ModelProvider - name: str + plugin_model_provider_entity: PluginModelProviderEntity position: Optional[int] = None class ModelProviderFactory: - model_provider_extensions: Optional[dict[str, ModelProviderExtension]] = None + provider_position_map: dict[str, int] = {} + + def __init__(self, tenant_id: str) -> None: + self.tenant_id = tenant_id + self.plugin_model_manager = PluginModelManager() - def __init__(self) -> None: - # for cache in memory - self.get_providers() + if not self.provider_position_map: + # get the path of current classes + current_path = os.path.abspath(__file__) + model_providers_path = os.path.dirname(current_path) + + # get _position.yaml file path + self.provider_position_map = get_provider_position_map(model_providers_path) def get_providers(self) -> Sequence[ProviderEntity]: """ Get all providers :return: list of providers """ - # scan all providers - model_provider_extensions = self._get_model_provider_map() + # Fetch plugin model providers + plugin_providers = self.get_plugin_model_providers() - # traverse all model_provider_extensions - providers = [] - for model_provider_extension in model_provider_extensions.values(): - # get model_provider instance - model_provider_instance = model_provider_extension.provider_instance + # Convert PluginModelProviderEntity to ModelProviderExtension + model_provider_extensions = [] + for provider in plugin_providers: + model_provider_extensions.append(ModelProviderExtension(plugin_model_provider_entity=provider)) - # get provider schema - provider_schema = model_provider_instance.get_provider_schema() + sorted_extensions = sort_to_dict_by_position_map( + position_map=self.provider_position_map, + data=model_provider_extensions, + name_func=lambda x: x.plugin_model_provider_entity.declaration.provider, + ) - for model_type in provider_schema.supported_model_types: - # get predefined models for given model type - models = model_provider_instance.models(model_type) - if models: - provider_schema.models.extend(models) + return [extension.plugin_model_provider_entity.declaration for extension in sorted_extensions.values()] - providers.append(provider_schema) + def get_plugin_model_providers(self) -> Sequence[PluginModelProviderEntity]: + """ + Get all plugin model providers + :return: list of plugin model providers + """ + # Fetch plugin model providers + plugin_providers = self.plugin_model_manager.fetch_model_providers(self.tenant_id) - # return providers - return providers + for provider in plugin_providers: + provider.declaration.provider = provider.plugin_id + "/" + provider.declaration.provider + + return plugin_providers + + def get_provider_schema(self, provider: str) -> ProviderEntity: + """ + Get provider schema + :param provider: provider name + :return: provider schema + """ + plugin_model_provider_entity = self.get_plugin_model_provider(provider=provider) + return plugin_model_provider_entity.declaration + + def get_plugin_model_provider(self, provider: str) -> PluginModelProviderEntity: + """ + Get plugin model provider + :param provider: provider name + :return: provider schema + """ + # fetch plugin model providers + plugin_model_provider_entities = self.get_plugin_model_providers() + + plugin_id, provider_name = self.get_plugin_id_and_provider_name_from_provider(provider) + + # get the provider + plugin_model_provider_entity = next( + ( + p + for p in plugin_model_provider_entities + if p.declaration.provider == provider_name and (plugin_id and p.plugin_id == plugin_id) + ), + None, + ) + + if not plugin_model_provider_entity: + raise ValueError(f"Invalid provider: {provider}") + + return plugin_model_provider_entity def provider_credentials_validate(self, *, provider: str, credentials: dict) -> dict: """ @@ -67,15 +122,11 @@ def provider_credentials_validate(self, *, provider: str, credentials: dict) -> :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. :return: """ - # get the provider instance - model_provider_instance = self.get_provider_instance(provider) - - # get provider schema - provider_schema = model_provider_instance.get_provider_schema() + # fetch plugin model provider + plugin_model_provider_entity = self.get_plugin_model_provider(provider=provider) # get provider_credential_schema and validate credentials according to the rules - provider_credential_schema = provider_schema.provider_credential_schema - + provider_credential_schema = plugin_model_provider_entity.declaration.provider_credential_schema if not provider_credential_schema: raise ValueError(f"Provider {provider} does not have provider_credential_schema") @@ -84,7 +135,13 @@ def provider_credentials_validate(self, *, provider: str, credentials: dict) -> filtered_credentials = validator.validate_and_filter(credentials) # validate the credentials, raise exception if validation failed - model_provider_instance.validate_provider_credentials(filtered_credentials) + self.plugin_model_manager.validate_provider_credentials( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=plugin_model_provider_entity.plugin_id, + provider=provider, + credentials=filtered_credentials, + ) return filtered_credentials @@ -100,15 +157,11 @@ def model_credentials_validate( :param credentials: model credentials, credentials form defined in `model_credential_schema`. :return: """ - # get the provider instance - model_provider_instance = self.get_provider_instance(provider) - - # get provider schema - provider_schema = model_provider_instance.get_provider_schema() + # fetch plugin model provider + plugin_model_provider_entity = self.get_plugin_model_provider(provider=provider) # get model_credential_schema and validate credentials according to the rules - model_credential_schema = provider_schema.model_credential_schema - + model_credential_schema = plugin_model_provider_entity.declaration.model_credential_schema if not model_credential_schema: raise ValueError(f"Provider {provider} does not have model_credential_schema") @@ -116,14 +169,38 @@ def model_credentials_validate( validator = ModelCredentialSchemaValidator(model_type, model_credential_schema) filtered_credentials = validator.validate_and_filter(credentials) - # get model instance of the model type - model_instance = model_provider_instance.get_model_instance(model_type) - # call validate_credentials method of model type to validate credentials, raise exception if validation failed - model_instance.validate_credentials(model, filtered_credentials) + self.plugin_model_manager.validate_model_credentials( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=plugin_model_provider_entity.plugin_id, + provider=provider, + model_type=model_type.value, + model=model, + credentials=filtered_credentials, + ) return filtered_credentials + def get_model_schema( + self, *, provider: str, model_type: ModelType, model: str, credentials: dict + ) -> AIModelEntity | None: + """ + Get model schema + """ + plugin_id, provider_name = self.get_plugin_id_and_provider_name_from_provider(provider) + model_schema = self.plugin_model_manager.get_model_schema( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=plugin_id, + provider=provider_name, + model_type=model_type.value, + model=model, + credentials=credentials, + ) + + return model_schema + def get_models( self, *, @@ -142,7 +219,7 @@ def get_models( provider_configs = provider_configs or [] # scan all providers - model_provider_extensions = self._get_model_provider_map() + plugin_model_provider_entities = self.get_plugin_model_providers() # convert provider_configs to dict provider_credentials_dict = {} @@ -151,16 +228,13 @@ def get_models( # traverse all model_provider_extensions providers = [] - for name, model_provider_extension in model_provider_extensions.items(): + for plugin_model_provider_entity in plugin_model_provider_entities: # filter by provider if provider is present - if provider and name != provider: + if provider and plugin_model_provider_entity.declaration.provider != provider: continue - # get model_provider instance - model_provider_instance = model_provider_extension.provider_instance - # get provider schema - provider_schema = model_provider_instance.get_provider_schema() + provider_schema = plugin_model_provider_entity.declaration model_types = provider_schema.supported_model_types if model_type: @@ -170,13 +244,11 @@ def get_models( model_types = [model_type] all_model_type_models = [] - for model_type in model_types: - # get predefined models for given model type - models = model_provider_instance.models( - model_type=model_type, - ) + for model_schema in provider_schema.models: + if model_schema.model_type != model_type: + continue - all_model_type_models.extend(models) + all_model_type_models.append(model_schema) simple_provider_schema = provider_schema.to_simple_provider() simple_provider_schema.models.extend(all_model_type_models) @@ -185,95 +257,82 @@ def get_models( return providers - def get_provider_instance(self, provider: str) -> ModelProvider: + def get_model_type_instance(self, provider: str, model_type: ModelType) -> AIModel: """ - Get provider instance by provider name + Get model type instance by provider name and model type :param provider: provider name - :return: provider instance + :param model_type: model type + :return: model type instance """ - # scan all providers - model_provider_extensions = self._get_model_provider_map() - - # get the provider extension - model_provider_extension = model_provider_extensions.get(provider) - if not model_provider_extension: - raise Exception(f"Invalid provider: {provider}") - - # get the provider instance - model_provider_instance = model_provider_extension.provider_instance - - return model_provider_instance - - def _get_model_provider_map(self) -> dict[str, ModelProviderExtension]: + plugin_id, provider_name = self.get_plugin_id_and_provider_name_from_provider(provider) + init_params = { + "tenant_id": self.tenant_id, + "plugin_id": plugin_id, + "provider_name": provider_name, + "plugin_model_provider": self.get_plugin_model_provider(provider), + } + + if model_type == ModelType.LLM: + return LargeLanguageModel(**init_params) + elif model_type == ModelType.TEXT_EMBEDDING: + return TextEmbeddingModel(**init_params) + elif model_type == ModelType.RERANK: + return RerankModel(**init_params) + elif model_type == ModelType.SPEECH2TEXT: + return Speech2TextModel(**init_params) + elif model_type == ModelType.MODERATION: + return ModerationModel(**init_params) + elif model_type == ModelType.TTS: + return TTSModel(**init_params) + elif model_type == ModelType.TEXT2IMG: + return Text2ImageModel(**init_params) + + def get_provider_icon(self, provider: str, icon_type: str, lang: str) -> bytes: """ - Retrieves the model provider map. - - This method retrieves the model provider map, which is a dictionary containing the model provider names as keys - and instances of `ModelProviderExtension` as values. The model provider map is used to store information about - available model providers. - - Returns: - A dictionary containing the model provider map. - - Raises: - None. + Get provider icon + :param provider: provider name + :param icon_type: icon type (icon_small or icon_large) + :param lang: language (zh_Hans or en_US) + :return: provider icon """ - if self.model_provider_extensions: - return self.model_provider_extensions - - # get the path of current classes - current_path = os.path.abspath(__file__) - model_providers_path = os.path.dirname(current_path) - - # get all folders path under model_providers_path that do not start with __ - model_provider_dir_paths = [ - os.path.join(model_providers_path, model_provider_dir) - for model_provider_dir in os.listdir(model_providers_path) - if not model_provider_dir.startswith("__") - and os.path.isdir(os.path.join(model_providers_path, model_provider_dir)) - ] - - # get _position.yaml file path - position_map = get_provider_position_map(model_providers_path) - - # traverse all model_provider_dir_paths - model_providers: list[ModelProviderExtension] = [] - for model_provider_dir_path in model_provider_dir_paths: - # get model_provider dir name - model_provider_name = os.path.basename(model_provider_dir_path) - - file_names = os.listdir(model_provider_dir_path) - - if (model_provider_name + ".py") not in file_names: - logger.warning(f"Missing {model_provider_name}.py file in {model_provider_dir_path}, Skip.") - continue - - # Dynamic loading {model_provider_name}.py file and find the subclass of ModelProvider - py_path = os.path.join(model_provider_dir_path, model_provider_name + ".py") - model_provider_class = load_single_subclass_from_source( - module_name=f"core.model_runtime.model_providers.{model_provider_name}.{model_provider_name}", - script_path=py_path, - parent_type=ModelProvider, - ) - - if not model_provider_class: - logger.warning(f"Missing Model Provider Class that extends ModelProvider in {py_path}, Skip.") - continue - - if f"{model_provider_name}.yaml" not in file_names: - logger.warning(f"Missing {model_provider_name}.yaml file in {model_provider_dir_path}, Skip.") - continue - - model_providers.append( - ModelProviderExtension( - name=model_provider_name, - provider_instance=model_provider_class(), - position=position_map.get(model_provider_name), - ) - ) - - sorted_extensions = sort_to_dict_by_position_map(position_map, model_providers, lambda x: x.name) - - self.model_provider_extensions = sorted_extensions - - return sorted_extensions + # get the provider schema + provider_schema = self.get_provider_schema(provider) + + if icon_type.lower() == "icon_small": + if not provider_schema.icon_small: + raise ValueError(f"Provider {provider} does not have small icon.") + + if lang.lower() == "zh_hans": + file_name = provider_schema.icon_small.zh_Hans + else: + file_name = provider_schema.icon_small.en_US + else: + if not provider_schema.icon_large: + raise ValueError(f"Provider {provider} does not have large icon.") + + if lang.lower() == "zh_hans": + file_name = provider_schema.icon_large.zh_Hans + else: + file_name = provider_schema.icon_large.en_US + + if not file_name: + raise ValueError(f"Provider {provider} does not have icon.") + + # get icon bytes from plugin asset manager + plugin_asset_manager = PluginAssetManager() + return plugin_asset_manager.fetch_asset(tenant_id=self.tenant_id, id=file_name) + + def get_plugin_id_and_provider_name_from_provider(self, provider: str) -> tuple[str, str]: + """ + Get plugin id and provider name from provider name + :param provider: provider name + :return: plugin id and provider name + """ + plugin_id = "langgenius" + provider_name = provider + if "/" in provider: + # get the plugin_id before provider + plugin_id = "/".join(provider.split("/")[:-1]) + provider_name = provider.split("/")[-1] + + return plugin_id, provider_name diff --git 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b/api/core/model_runtime/model_providers/moonshot/llm/_position.yaml deleted file mode 100644 index 1810ec61d68e89..00000000000000 --- a/api/core/model_runtime/model_providers/moonshot/llm/_position.yaml +++ /dev/null @@ -1,3 +0,0 @@ -- moonshot-v1-8k -- moonshot-v1-32k -- moonshot-v1-128k diff --git a/api/core/model_runtime/model_providers/moonshot/llm/llm.py b/api/core/model_runtime/model_providers/moonshot/llm/llm.py deleted file mode 100644 index 3ea46c2967e19c..00000000000000 --- a/api/core/model_runtime/model_providers/moonshot/llm/llm.py +++ /dev/null @@ -1,327 +0,0 @@ -import json -from collections.abc import Generator -from typing import Optional, Union, cast - -import requests - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContent, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelFeature, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class MoonshotLargeLanguageModel(OAIAPICompatLargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials) - self._add_function_call(model, credentials) - user = user[:32] if user else None - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - return AIModelEntity( - model=model, - label=I18nObject(en_US=model, zh_Hans=model), - model_type=ModelType.LLM, - features=[ModelFeature.TOOL_CALL, ModelFeature.MULTI_TOOL_CALL, ModelFeature.STREAM_TOOL_CALL] - if credentials.get("function_calling_type") == "tool_call" - else [], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", 4096)), - ModelPropertyKey.MODE: LLMMode.CHAT.value, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - use_template="temperature", - label=I18nObject(en_US="Temperature", zh_Hans="温度"), - type=ParameterType.FLOAT, - ), - ParameterRule( - name="max_tokens", - use_template="max_tokens", - default=512, - min=1, - max=int(credentials.get("max_tokens", 4096)), - label=I18nObject(en_US="Max Tokens", zh_Hans="最大标记"), - type=ParameterType.INT, - ), - ParameterRule( - name="top_p", - use_template="top_p", - label=I18nObject(en_US="Top P", zh_Hans="Top P"), - type=ParameterType.FLOAT, - ), - ], - ) - - def _add_custom_parameters(self, credentials: dict) -> None: - credentials["mode"] = "chat" - if "endpoint_url" not in credentials or credentials["endpoint_url"] == "": - credentials["endpoint_url"] = "https://api.moonshot.cn/v1" - - def _add_function_call(self, model: str, credentials: dict) -> None: - model_schema = self.get_model_schema(model, credentials) - if model_schema and {ModelFeature.TOOL_CALL, ModelFeature.MULTI_TOOL_CALL}.intersection( - model_schema.features or [] - ): - credentials["function_calling_type"] = "tool_call" - - def _convert_prompt_message_to_dict(self, message: PromptMessage, credentials: Optional[dict] = None) -> dict: - """ - Convert PromptMessage to dict for OpenAI API format - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(PromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": {"url": message_content.data, "detail": message_content.detail.value}, - } - sub_messages.append(sub_message_dict) - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls: - message_dict["tool_calls"] = [] - for function_call in message.tool_calls: - message_dict["tool_calls"].append( - { - "id": function_call.id, - "type": function_call.type, - "function": { - "name": function_call.function.name, - "arguments": function_call.function.arguments, - }, - } - ) - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = {"role": "tool", "content": message.content, "tool_call_id": message.tool_call_id} - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - else: - raise ValueError(f"Got unknown type {message}") - - if message.name: - message_dict["name"] = message.name - - return message_dict - - def _extract_response_tool_calls(self, response_tool_calls: list[dict]) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_tool_calls: - for response_tool_call in response_tool_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call["function"]["name"] - if response_tool_call.get("function", {}).get("name") - else "", - arguments=response_tool_call["function"]["arguments"] - if response_tool_call.get("function", {}).get("arguments") - else "", - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call["id"] if response_tool_call.get("id") else "", - type=response_tool_call["type"] if response_tool_call.get("type") else "", - function=function, - ) - tool_calls.append(tool_call) - - return tool_calls - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: requests.Response, prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param credentials: model credentials - :param response: streamed response - :param prompt_messages: prompt messages - :return: llm response chunk generator - """ - full_assistant_content = "" - chunk_index = 0 - - def create_final_llm_result_chunk( - index: int, message: AssistantPromptMessage, finish_reason: str - ) -> LLMResultChunk: - # calculate num tokens - prompt_tokens = self._num_tokens_from_string(model, prompt_messages[0].content) - completion_tokens = self._num_tokens_from_string(model, full_assistant_content) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - return LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=message, finish_reason=finish_reason, usage=usage), - ) - - tools_calls: list[AssistantPromptMessage.ToolCall] = [] - finish_reason = "Unknown" - - def increase_tool_call(new_tool_calls: list[AssistantPromptMessage.ToolCall]): - def get_tool_call(tool_name: str): - if not tool_name: - return tools_calls[-1] - - tool_call = next((tool_call for tool_call in tools_calls if tool_call.function.name == tool_name), None) - if tool_call is None: - tool_call = AssistantPromptMessage.ToolCall( - id="", - type="", - function=AssistantPromptMessage.ToolCall.ToolCallFunction(name=tool_name, arguments=""), - ) - tools_calls.append(tool_call) - - return tool_call - - for new_tool_call in new_tool_calls: - # get tool call - tool_call = get_tool_call(new_tool_call.function.name) - # update tool call - if new_tool_call.id: - tool_call.id = new_tool_call.id - if new_tool_call.type: - tool_call.type = new_tool_call.type - if new_tool_call.function.name: - tool_call.function.name = new_tool_call.function.name - if new_tool_call.function.arguments: - tool_call.function.arguments += new_tool_call.function.arguments - - for chunk in response.iter_lines(decode_unicode=True, delimiter="\n\n"): - if chunk: - # ignore sse comments - if chunk.startswith(":"): - continue - decoded_chunk = chunk.strip().lstrip("data: ").lstrip() - chunk_json = None - try: - chunk_json = json.loads(decoded_chunk) - # stream ended - except json.JSONDecodeError as e: - yield create_final_llm_result_chunk( - index=chunk_index + 1, - message=AssistantPromptMessage(content=""), - finish_reason="Non-JSON encountered.", - ) - break - if not chunk_json or len(chunk_json["choices"]) == 0: - continue - - choice = chunk_json["choices"][0] - finish_reason = chunk_json["choices"][0].get("finish_reason") - chunk_index += 1 - - if "delta" in choice: - delta = choice["delta"] - delta_content = delta.get("content") - - assistant_message_tool_calls = delta.get("tool_calls", None) - # assistant_message_function_call = delta.delta.function_call - - # extract tool calls from response - if assistant_message_tool_calls: - tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - increase_tool_call(tool_calls) - - if delta_content is None or delta_content == "": - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=delta_content, tool_calls=tool_calls if assistant_message_tool_calls else [] - ) - - full_assistant_content += delta_content - elif "text" in choice: - choice_text = choice.get("text", "") - if choice_text == "": - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=choice_text) - full_assistant_content += choice_text - else: - continue - - # check payload indicator for completion - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk_index, - message=assistant_prompt_message, - ), - ) - - chunk_index += 1 - - if tools_calls: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk_index, - message=AssistantPromptMessage(tool_calls=tools_calls, content=""), - ), - ) - - yield create_final_llm_result_chunk( - index=chunk_index, message=AssistantPromptMessage(content=""), finish_reason=finish_reason - ) diff --git a/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-128k.yaml b/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-128k.yaml deleted file mode 100644 index 59c0915ee9b610..00000000000000 --- a/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-128k.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: moonshot-v1-128k -label: - zh_Hans: moonshot-v1-128k - en_US: moonshot-v1-128k -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 128000 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.06' - output: '0.06' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-32k.yaml b/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-32k.yaml deleted file mode 100644 index 724f2aa5a29f96..00000000000000 --- a/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-32k.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: moonshot-v1-32k -label: - zh_Hans: moonshot-v1-32k - en_US: moonshot-v1-32k -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 32000 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.024' - output: '0.024' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-8k.yaml b/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-8k.yaml deleted file mode 100644 index 5872295bfad1ef..00000000000000 --- a/api/core/model_runtime/model_providers/moonshot/llm/moonshot-v1-8k.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: moonshot-v1-8k -label: - zh_Hans: moonshot-v1-8k - en_US: moonshot-v1-8k -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.012' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/moonshot/moonshot.py b/api/core/model_runtime/model_providers/moonshot/moonshot.py deleted file mode 100644 index 4995e235f54c69..00000000000000 --- a/api/core/model_runtime/model_providers/moonshot/moonshot.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class MoonshotProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="moonshot-v1-8k", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/moonshot/moonshot.yaml b/api/core/model_runtime/model_providers/moonshot/moonshot.yaml deleted file mode 100644 index 41e9c2e8086e83..00000000000000 --- a/api/core/model_runtime/model_providers/moonshot/moonshot.yaml +++ /dev/null @@ -1,89 +0,0 @@ -provider: moonshot -label: - zh_Hans: 月之暗面 - en_US: Moonshot -description: - en_US: Models provided by Moonshot, such as moonshot-v1-8k, moonshot-v1-32k, and moonshot-v1-128k. - zh_Hans: Moonshot 提供的模型，例如 moonshot-v1-8k、moonshot-v1-32k 和 moonshot-v1-128k。 -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -background: "#FFFFFF" -help: - title: - en_US: Get your API Key from Moonshot - zh_Hans: 从 Moonshot 获取 API Key - url: - en_US: https://platform.moonshot.cn/console/api-keys -supported_model_types: - - llm -configurate_methods: - - predefined-model - - customizable-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: endpoint_url - label: - en_US: API Base - type: text-input - required: false - placeholder: - zh_Hans: Base URL, 如：https://api.moonshot.cn/v1 - en_US: Base URL, e.g. https://api.moonshot.cn/v1 -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - type: text-input - default: '4096' - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: max_tokens - label: - zh_Hans: 最大 token 上限 - en_US: Upper bound for max tokens - default: '4096' - type: text-input - - variable: function_calling_type - label: - en_US: Function calling - type: select - required: false - default: no_call - options: - - value: no_call - label: - en_US: Not supported - zh_Hans: 不支持 - - value: tool_call - label: - en_US: Tool Call - zh_Hans: Tool Call diff --git a/api/core/model_runtime/model_providers/nomic/__init__.py b/api/core/model_runtime/model_providers/nomic/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/nomic/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/nomic/_assets/icon_l_en.svg deleted file mode 100644 index 6c4a1058ab9c70..00000000000000 --- a/api/core/model_runtime/model_providers/nomic/_assets/icon_l_en.svg +++ /dev/null @@ -1,13 +0,0 @@ - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/nomic/_assets/icon_s_en.png b/api/core/model_runtime/model_providers/nomic/_assets/icon_s_en.png deleted file mode 100644 index 3eba3b82bc1e3fcb6b27cd9038786e19b7c2adcf..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 25814 zcmce8c{o*H`?qc#G9K{_ZDQ;ou+Q{u_24=Hr{Y2>&m?^_GR7 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-from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) - - -class _CommonNomic: - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError, InvokeBadRequestError], - } diff --git a/api/core/model_runtime/model_providers/nomic/nomic.py b/api/core/model_runtime/model_providers/nomic/nomic.py deleted file mode 100644 index d4e5da2e98ec97..00000000000000 --- a/api/core/model_runtime/model_providers/nomic/nomic.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class NomicAtlasProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.TEXT_EMBEDDING) - model_instance.validate_credentials(model="nomic-embed-text-v1.5", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/nomic/nomic.yaml b/api/core/model_runtime/model_providers/nomic/nomic.yaml deleted file mode 100644 index 60dcf1facb475d..00000000000000 --- a/api/core/model_runtime/model_providers/nomic/nomic.yaml +++ /dev/null @@ -1,29 +0,0 @@ -provider: nomic -label: - zh_Hans: Nomic Atlas - en_US: Nomic Atlas -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.svg -background: "#EFF1FE" -help: - title: - en_US: Get your API key from Nomic Atlas - zh_Hans: 从Nomic Atlas获取 API Key - url: - en_US: https://atlas.nomic.ai/data -supported_model_types: - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: nomic_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/nomic/text_embedding/__init__.py b/api/core/model_runtime/model_providers/nomic/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/nomic/text_embedding/nomic-embed-text-v1.5.yaml b/api/core/model_runtime/model_providers/nomic/text_embedding/nomic-embed-text-v1.5.yaml deleted file mode 100644 index 111452df579f8f..00000000000000 --- a/api/core/model_runtime/model_providers/nomic/text_embedding/nomic-embed-text-v1.5.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: nomic-embed-text-v1.5 -model_type: text-embedding -model_properties: - context_size: 8192 -pricing: - input: "0.1" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/nomic/text_embedding/nomic-embed-text-v1.yaml b/api/core/model_runtime/model_providers/nomic/text_embedding/nomic-embed-text-v1.yaml deleted file mode 100644 index ac59f106ed2928..00000000000000 --- a/api/core/model_runtime/model_providers/nomic/text_embedding/nomic-embed-text-v1.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: nomic-embed-text-v1 -model_type: text-embedding -model_properties: - context_size: 8192 -pricing: - input: "0.1" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/novita/_assets/icon_l_en.svg deleted file mode 100644 index 5c92cdbc6d8466..00000000000000 --- a/api/core/model_runtime/model_providers/novita/_assets/icon_l_en.svg +++ /dev/null @@ -1,19 +0,0 @@ - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/novita/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/novita/_assets/icon_s_en.svg deleted file mode 100644 index 798c1d63485221..00000000000000 --- a/api/core/model_runtime/model_providers/novita/_assets/icon_s_en.svg +++ /dev/null @@ -1,10 +0,0 @@ - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/novita/llm/Nous-Hermes-2-Mixtral-8x7B-DPO.yaml b/api/core/model_runtime/model_providers/novita/llm/Nous-Hermes-2-Mixtral-8x7B-DPO.yaml deleted file mode 100644 index 7ff30458e2ff0e..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/Nous-Hermes-2-Mixtral-8x7B-DPO.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: Nous-Hermes-2-Mixtral-8x7B-DPO -label: - zh_Hans: Nous-Hermes-2-Mixtral-8x7B-DPO - en_US: Nous-Hermes-2-Mixtral-8x7B-DPO -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0027' - output: '0.0027' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/airoboros-l2-70b.yaml b/api/core/model_runtime/model_providers/novita/llm/airoboros-l2-70b.yaml deleted file mode 100644 index b5994184613141..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/airoboros-l2-70b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: jondurbin/airoboros-l2-70b -label: - zh_Hans: jondurbin/airoboros-l2-70b - en_US: jondurbin/airoboros-l2-70b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.005' - output: '0.005' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/dolphin-mixtral-8x22b.yaml b/api/core/model_runtime/model_providers/novita/llm/dolphin-mixtral-8x22b.yaml deleted file mode 100644 index 72a181f5d37193..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/dolphin-mixtral-8x22b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: cognitivecomputations/dolphin-mixtral-8x22b -label: - zh_Hans: cognitivecomputations/dolphin-mixtral-8x22b - en_US: cognitivecomputations/dolphin-mixtral-8x22b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.009' - output: '0.009' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/gemma-2-9b-it.yaml b/api/core/model_runtime/model_providers/novita/llm/gemma-2-9b-it.yaml deleted file mode 100644 index d1749bc882bfea..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/gemma-2-9b-it.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: google/gemma-2-9b-it -label: - zh_Hans: google/gemma-2-9b-it - en_US: google/gemma-2-9b-it -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0008' - output: '0.0008' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/hermes-2-pro-llama-3-8b.yaml b/api/core/model_runtime/model_providers/novita/llm/hermes-2-pro-llama-3-8b.yaml deleted file mode 100644 index 8b3228e56a6726..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/hermes-2-pro-llama-3-8b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: nousresearch/hermes-2-pro-llama-3-8b -label: - zh_Hans: nousresearch/hermes-2-pro-llama-3-8b - en_US: nousresearch/hermes-2-pro-llama-3-8b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0014' - output: '0.0014' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/l3-70b-euryale-v2.1.yaml b/api/core/model_runtime/model_providers/novita/llm/l3-70b-euryale-v2.1.yaml deleted file mode 100644 index 5e27941c529e8f..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/l3-70b-euryale-v2.1.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: sao10k/l3-70b-euryale-v2.1 -label: - zh_Hans: sao10k/l3-70b-euryale-v2.1 - en_US: sao10k/l3-70b-euryale-v2.1 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0148' - output: '0.0148' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/llama-3-70b-instruct.yaml b/api/core/model_runtime/model_providers/novita/llm/llama-3-70b-instruct.yaml deleted file mode 100644 index 39709e10639b69..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/llama-3-70b-instruct.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: meta-llama/llama-3-70b-instruct -label: - zh_Hans: meta-llama/llama-3-70b-instruct - en_US: meta-llama/llama-3-70b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0051' - output: '0.0074' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/llama-3-8b-instruct.yaml b/api/core/model_runtime/model_providers/novita/llm/llama-3-8b-instruct.yaml deleted file mode 100644 index 9b5e5df4d071fe..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/llama-3-8b-instruct.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: meta-llama/llama-3-8b-instruct -label: - zh_Hans: meta-llama/llama-3-8b-instruct - en_US: meta-llama/llama-3-8b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.00063' - output: '0.00063' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/llama-3.1-405b-instruct.yaml b/api/core/model_runtime/model_providers/novita/llm/llama-3.1-405b-instruct.yaml deleted file mode 100644 index c5a45271ae94aa..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/llama-3.1-405b-instruct.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: meta-llama/llama-3.1-405b-instruct -label: - zh_Hans: meta-llama/llama-3.1-405b-instruct - en_US: meta-llama/llama-3.1-405b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.03' - output: '0.05' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/llama-3.1-70b-instruct.yaml b/api/core/model_runtime/model_providers/novita/llm/llama-3.1-70b-instruct.yaml deleted file mode 100644 index 3a5c29c40fd7c7..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/llama-3.1-70b-instruct.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: meta-llama/llama-3.1-70b-instruct -label: - zh_Hans: meta-llama/llama-3.1-70b-instruct - en_US: meta-llama/llama-3.1-70b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0055' - output: '0.0076' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/llama-3.1-8b-instruct.yaml b/api/core/model_runtime/model_providers/novita/llm/llama-3.1-8b-instruct.yaml deleted file mode 100644 index e6ef772a3f0784..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/llama-3.1-8b-instruct.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: meta-llama/llama-3.1-8b-instruct -label: - zh_Hans: meta-llama/llama-3.1-8b-instruct - en_US: meta-llama/llama-3.1-8b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.001' - output: '0.001' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/llm.py b/api/core/model_runtime/model_providers/novita/llm/llm.py deleted file mode 100644 index 23367ed1b4309e..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/llm.py +++ /dev/null @@ -1,69 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class NovitaLargeLanguageModel(OAIAPICompatLargeLanguageModel): - def _update_endpoint_url(self, credentials: dict): - credentials["endpoint_url"] = "https://api.novita.ai/v3/openai" - credentials["extra_headers"] = {"X-Novita-Source": "dify.ai"} - return credentials - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - return super()._invoke(model, cred_with_endpoint, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - self._add_custom_parameters(credentials, model) - return super().validate_credentials(model, cred_with_endpoint) - - @classmethod - def _add_custom_parameters(cls, credentials: dict, model: str) -> None: - credentials["mode"] = "chat" - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - return super()._generate( - model, cred_with_endpoint, prompt_messages, model_parameters, tools, stop, stream, user - ) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - - return super().get_customizable_model_schema(model, cred_with_endpoint) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - - return super().get_num_tokens(model, cred_with_endpoint, prompt_messages, tools) diff --git a/api/core/model_runtime/model_providers/novita/llm/lzlv_70b.yaml b/api/core/model_runtime/model_providers/novita/llm/lzlv_70b.yaml deleted file mode 100644 index 0cc68a8c45082d..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/lzlv_70b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: lzlv_70b -label: - zh_Hans: lzlv_70b - en_US: lzlv_70b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0058' - output: '0.0078' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/midnight-rose-70b.yaml b/api/core/model_runtime/model_providers/novita/llm/midnight-rose-70b.yaml deleted file mode 100644 index 19876bee17ab4d..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/midnight-rose-70b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: sophosympatheia/midnight-rose-70b -label: - zh_Hans: sophosympatheia/midnight-rose-70b - en_US: sophosympatheia/midnight-rose-70b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.008' - output: '0.008' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/mistral-7b-instruct.yaml b/api/core/model_runtime/model_providers/novita/llm/mistral-7b-instruct.yaml deleted file mode 100644 index 6fba47bcf09731..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/mistral-7b-instruct.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: mistralai/mistral-7b-instruct -label: - zh_Hans: mistralai/mistral-7b-instruct - en_US: mistralai/mistral-7b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.00059' - output: '0.00059' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/mythomax-l2-13b.yaml b/api/core/model_runtime/model_providers/novita/llm/mythomax-l2-13b.yaml deleted file mode 100644 index 7e4ac3ffe02d0f..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/mythomax-l2-13b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: gryphe/mythomax-l2-13b -label: - zh_Hans: gryphe/mythomax-l2-13b - en_US: gryphe/mythomax-l2-13b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.00119' - output: '0.00119' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/nous-hermes-llama2-13b.yaml b/api/core/model_runtime/model_providers/novita/llm/nous-hermes-llama2-13b.yaml deleted file mode 100644 index 75671c414c7424..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/nous-hermes-llama2-13b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: nousresearch/nous-hermes-llama2-13b -label: - zh_Hans: nousresearch/nous-hermes-llama2-13b - en_US: nousresearch/nous-hermes-llama2-13b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0017' - output: '0.0017' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/openhermes-2.5-mistral-7b.yaml b/api/core/model_runtime/model_providers/novita/llm/openhermes-2.5-mistral-7b.yaml deleted file mode 100644 index 8b0deba4f7889e..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/openhermes-2.5-mistral-7b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: teknium/openhermes-2.5-mistral-7b -label: - zh_Hans: teknium/openhermes-2.5-mistral-7b - en_US: teknium/openhermes-2.5-mistral-7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0017' - output: '0.0017' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/llm/wizardlm-2-8x22b.yaml b/api/core/model_runtime/model_providers/novita/llm/wizardlm-2-8x22b.yaml deleted file mode 100644 index ef42568e8f627c..00000000000000 --- a/api/core/model_runtime/model_providers/novita/llm/wizardlm-2-8x22b.yaml +++ /dev/null @@ -1,41 +0,0 @@ -model: microsoft/wizardlm-2-8x22b -label: - zh_Hans: microsoft/wizardlm-2-8x22b - en_US: microsoft/wizardlm-2-8x22b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 65535 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 2 - default: 1 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 512 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 -pricing: - input: '0.0064' - output: '0.0064' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/novita/novita.py b/api/core/model_runtime/model_providers/novita/novita.py deleted file mode 100644 index 76a75b01e27e01..00000000000000 --- a/api/core/model_runtime/model_providers/novita/novita.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class NovitaProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `meta-llama/llama-3-8b-instruct` model for validate, - # no matter what model you pass in, text completion model or chat model - model_instance.validate_credentials(model="meta-llama/llama-3-8b-instruct", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/novita/novita.yaml b/api/core/model_runtime/model_providers/novita/novita.yaml deleted file mode 100644 index f6341979891e65..00000000000000 --- a/api/core/model_runtime/model_providers/novita/novita.yaml +++ /dev/null @@ -1,31 +0,0 @@ -provider: novita -label: - en_US: novita.ai -description: - en_US: An LLM API that matches various application scenarios with high cost-effectiveness. - zh_Hans: 适配多种海外应用场景的高性价比 LLM API -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#eadeff" -help: - title: - en_US: Get your API key from novita.ai - zh_Hans: 从 novita.ai 获取 API Key - url: - en_US: https://novita.ai/settings#key-management?utm_source=dify&utm_medium=ch&utm_campaign=api -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - required: true - label: - en_US: API Key - type: secret-input - placeholder: - zh_Hans: 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a/api/core/model_runtime/model_providers/nvidia/llm/_position.yaml b/api/core/model_runtime/model_providers/nvidia/llm/_position.yaml deleted file mode 100644 index ad01d430d61c79..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/_position.yaml +++ /dev/null @@ -1,17 +0,0 @@ -- google/gemma-7b -- google/codegemma-7b -- google/recurrentgemma-2b -- meta/llama2-70b -- meta/llama-3.1-8b-instruct -- meta/llama-3.1-70b-instruct -- meta/llama-3.1-405b-instruct -- meta/llama3-8b-instruct -- meta/llama3-70b-instruct -- mistralai/mistral-large -- mistralai/mixtral-8x7b-instruct-v0.1 -- mistralai/mixtral-8x22b-instruct-v0.1 -- nvidia/nemotron-4-340b-instruct -- microsoft/phi-3-medium-128k-instruct -- microsoft/phi-3-mini-128k-instruct -- fuyu-8b -- snowflake/arctic diff --git a/api/core/model_runtime/model_providers/nvidia/llm/arctic.yaml b/api/core/model_runtime/model_providers/nvidia/llm/arctic.yaml deleted file mode 100644 index 7f53ae58e695a9..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/arctic.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: snowflake/arctic -label: - zh_Hans: snowflake/arctic - en_US: snowflake/arctic -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/codegemma-7b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/codegemma-7b.yaml deleted file mode 100644 index 57446224a8a811..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/codegemma-7b.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: google/codegemma-7b -label: - zh_Hans: google/codegemma-7b - en_US: google/codegemma-7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/fuyu-8b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/fuyu-8b.yaml deleted file mode 100644 index 6ae524c6d80913..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/fuyu-8b.yaml +++ /dev/null @@ -1,27 +0,0 @@ -model: fuyu-8b -label: - zh_Hans: fuyu-8b - en_US: fuyu-8b -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 16000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.2 - min: 0.1 - max: 1 - - name: top_p - use_template: top_p - default: 0.7 - min: 0.1 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/gemma-7b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/gemma-7b.yaml deleted file mode 100644 index 794b820bf42175..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/gemma-7b.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: google/gemma-7b -label: - zh_Hans: google/gemma-7b - en_US: google/gemma-7b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-405b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-405b.yaml deleted file mode 100644 index 5472de99027643..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-405b.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: meta/llama-3.1-405b-instruct -label: - zh_Hans: meta/llama-3.1-405b-instruct - en_US: meta/llama-3.1-405b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 4096 - default: 1024 - - name: frequency_penalt - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-70b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-70b.yaml deleted file mode 100644 index 16af0554a1ef41..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-70b.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: meta/llama-3.1-70b-instruct -label: - zh_Hans: meta/llama-3.1-70b-instruct - en_US: meta/llama-3.1-70b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 4096 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-8b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-8b.yaml deleted file mode 100644 index f2d43dc30edf89..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/llama-3.1-8b.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: meta/llama-3.1-8b-instruct -label: - zh_Hans: meta/llama-3.1-8b-instruct - en_US: meta/llama-3.1-8b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 4096 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/llama2-70b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/llama2-70b.yaml deleted file mode 100644 index 9fba816b7fd21d..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/llama2-70b.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: meta/llama2-70b -label: - zh_Hans: meta/llama2-70b - en_US: meta/llama2-70b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/llama3-70b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/llama3-70b.yaml deleted file mode 100644 index 4d591d42265825..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/llama3-70b.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: meta/llama3-70b-instruct -label: - zh_Hans: meta/llama3-70b-instruct - en_US: meta/llama3-70b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/llama3-8b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/llama3-8b.yaml deleted file mode 100644 index 01395666745b69..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/llama3-8b.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: meta/llama3-8b-instruct -label: - zh_Hans: meta/llama3-8b-instruct - en_US: meta/llama3-8b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/llm.py b/api/core/model_runtime/model_providers/nvidia/llm/llm.py deleted file mode 100644 index 1c98c6be6ca72d..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/llm.py +++ /dev/null @@ -1,247 +0,0 @@ -import json -from collections.abc import Generator -from typing import Optional, Union - -import requests -from yarl import URL - -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult -from core.model_runtime.entities.message_entities import ( - PromptMessage, - PromptMessageContentType, - PromptMessageFunction, - PromptMessageTool, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import InvokeError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel -from core.model_runtime.utils import helper - - -class NVIDIALargeLanguageModel(OAIAPICompatLargeLanguageModel): - MODEL_SUFFIX_MAP = { - "fuyu-8b": "vlm/adept/fuyu-8b", - "mistralai/mistral-large": "", - "mistralai/mixtral-8x7b-instruct-v0.1": "", - "mistralai/mixtral-8x22b-instruct-v0.1": "", - "google/gemma-7b": "", - "google/codegemma-7b": "", - "snowflake/arctic": "", - "meta/llama2-70b": "", - "meta/llama3-8b-instruct": "", - "meta/llama3-70b-instruct": "", - "meta/llama-3.1-8b-instruct": "", - "meta/llama-3.1-70b-instruct": "", - "meta/llama-3.1-405b-instruct": "", - "google/recurrentgemma-2b": "", - "nvidia/nemotron-4-340b-instruct": "", - "microsoft/phi-3-medium-128k-instruct": "", - "microsoft/phi-3-mini-128k-instruct": "", - } - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials, model) - prompt_messages = self._transform_prompt_messages(prompt_messages) - stop = [] - user = None - - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def _transform_prompt_messages(self, prompt_messages: list[PromptMessage]) -> list[PromptMessage]: - """ - Handle Image transform - """ - for i, p in enumerate(prompt_messages): - if isinstance(p, UserPromptMessage) and isinstance(p.content, list): - content = p.content - content_text = "" - for prompt_content in content: - if prompt_content.type == PromptMessageContentType.TEXT: - content_text += prompt_content.data - else: - content_text += f' ' - - prompt_message = UserPromptMessage(content=content_text) - prompt_messages[i] = prompt_message - return prompt_messages - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials, model) - self._validate_credentials(model, credentials) - - def _add_custom_parameters(self, credentials: dict, model: str) -> None: - credentials["mode"] = "chat" - - if self.MODEL_SUFFIX_MAP[model]: - credentials["server_url"] = f"https://ai.api.nvidia.com/v1/{self.MODEL_SUFFIX_MAP[model]}" - credentials.pop("endpoint_url") - else: - credentials["endpoint_url"] = "https://integrate.api.nvidia.com/v1" - - credentials["stream_mode_delimiter"] = "\n" - - def _validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials using requests to ensure compatibility with all providers following - OpenAI's API standard. - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - headers = {"Content-Type": "application/json"} - - api_key = credentials.get("api_key") - if api_key: - headers["Authorization"] = f"Bearer {api_key}" - - endpoint_url = credentials.get("endpoint_url") - if endpoint_url and not endpoint_url.endswith("/"): - endpoint_url += "/" - server_url = credentials.get("server_url") - - # prepare the payload for a simple ping to the model - data = {"model": model, "max_tokens": 5} - - completion_type = LLMMode.value_of(credentials["mode"]) - - if completion_type is LLMMode.CHAT: - data["messages"] = [ - {"role": "user", "content": "ping"}, - ] - if "endpoint_url" in credentials: - endpoint_url = str(URL(endpoint_url) / "chat" / "completions") - elif "server_url" in credentials: - endpoint_url = server_url - elif completion_type is LLMMode.COMPLETION: - data["prompt"] = "ping" - if "endpoint_url" in credentials: - endpoint_url = str(URL(endpoint_url) / "completions") - elif "server_url" in credentials: - endpoint_url = server_url - else: - raise ValueError("Unsupported completion type for model configuration.") - - # send a post request to validate the credentials - response = requests.post(endpoint_url, headers=headers, json=data, timeout=(10, 300)) - - if response.status_code != 200: - raise CredentialsValidateFailedError( - f"Credentials validation failed with status code {response.status_code}" - ) - - try: - json_result = response.json() - except json.JSONDecodeError as e: - raise CredentialsValidateFailedError("Credentials validation failed: JSON decode error") - except CredentialsValidateFailedError: - raise - except Exception as ex: - raise CredentialsValidateFailedError(f"An error occurred during credentials validation: {str(ex)}") - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke llm completion model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - headers = { - "Content-Type": "application/json", - "Accept-Charset": "utf-8", - } - - api_key = credentials.get("api_key") - if api_key: - headers["Authorization"] = f"Bearer {api_key}" - - if stream: - headers["Accept"] = "text/event-stream" - - endpoint_url = credentials.get("endpoint_url") - if endpoint_url and not endpoint_url.endswith("/"): - endpoint_url += "/" - server_url = credentials.get("server_url") - - data = {"model": model, "stream": stream, **model_parameters} - - completion_type = LLMMode.value_of(credentials["mode"]) - - if completion_type is LLMMode.CHAT: - if "endpoint_url" in credentials: - endpoint_url = str(URL(endpoint_url) / "chat" / "completions") - elif "server_url" in credentials: - endpoint_url = server_url - data["messages"] = [self._convert_prompt_message_to_dict(m, credentials) for m in prompt_messages] - elif completion_type is LLMMode.COMPLETION: - data["prompt"] = "ping" - if "endpoint_url" in credentials: - endpoint_url = str(URL(endpoint_url) / "completions") - elif "server_url" in credentials: - endpoint_url = server_url - else: - raise ValueError("Unsupported completion type for model configuration.") - - # annotate tools with names, descriptions, etc. - function_calling_type = credentials.get("function_calling_type", "no_call") - formatted_tools = [] - if tools: - if function_calling_type == "function_call": - data["functions"] = [ - {"name": tool.name, "description": tool.description, "parameters": tool.parameters} - for tool in tools - ] - elif function_calling_type == "tool_call": - data["tool_choice"] = "auto" - - for tool in tools: - formatted_tools.append(helper.dump_model(PromptMessageFunction(function=tool))) - - data["tools"] = formatted_tools - - if stop: - data["stop"] = stop - - if user: - data["user"] = user - - response = requests.post(endpoint_url, headers=headers, json=data, timeout=(10, 300), stream=stream) - - if response.encoding is None or response.encoding == "ISO-8859-1": - response.encoding = "utf-8" - - if not response.ok: - raise InvokeError(f"API request failed with status code {response.status_code}: {response.text}") - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) diff --git a/api/core/model_runtime/model_providers/nvidia/llm/mistral-large.yaml b/api/core/model_runtime/model_providers/nvidia/llm/mistral-large.yaml deleted file mode 100644 index 3e14d221417178..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/mistral-large.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: mistralai/mistral-large -label: - zh_Hans: mistralai/mistral-large - en_US: mistralai/mistral-large -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/mistralai_mixtral-8x7b-instruct-v0.1.yaml b/api/core/model_runtime/model_providers/nvidia/llm/mistralai_mixtral-8x7b-instruct-v0.1.yaml deleted file mode 100644 index d2c4dc5d934a23..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/mistralai_mixtral-8x7b-instruct-v0.1.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: mistralai/mixtral-8x7b-instruct-v0.1 -label: - zh_Hans: mistralai/mixtral-8x7b-instruct-v0.1 - en_US: mistralai/mixtral-8x7b-instruct-v0.1 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/mixtral-8x22b-instruct-v0.1.yaml b/api/core/model_runtime/model_providers/nvidia/llm/mixtral-8x22b-instruct-v0.1.yaml deleted file mode 100644 index 05500c03362f0e..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/mixtral-8x22b-instruct-v0.1.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: mistralai/mixtral-8x22b-instruct-v0.1 -label: - zh_Hans: mistralai/mixtral-8x22b-instruct-v0.1 - en_US: mistralai/mixtral-8x22b-instruct-v0.1 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 64000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/nemotron-4-340b-instruct.yaml b/api/core/model_runtime/model_providers/nvidia/llm/nemotron-4-340b-instruct.yaml deleted file mode 100644 index e5537cd2fd9dc8..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/nemotron-4-340b-instruct.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: nvidia/nemotron-4-340b-instruct -label: - zh_Hans: nvidia/nemotron-4-340b-instruct - en_US: nvidia/nemotron-4-340b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 4096 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/phi-3-medium-128k-instruct.yaml b/api/core/model_runtime/model_providers/nvidia/llm/phi-3-medium-128k-instruct.yaml deleted file mode 100644 index 0c5538d1350613..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/phi-3-medium-128k-instruct.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: microsoft/phi-3-medium-128k-instruct -label: - zh_Hans: microsoft/phi-3-medium-128k-instruct - en_US: microsoft/phi-3-medium-128k-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 4096 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/phi-3-mini-128k-instruct.yaml b/api/core/model_runtime/model_providers/nvidia/llm/phi-3-mini-128k-instruct.yaml deleted file mode 100644 index 1eb1c51d01157c..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/phi-3-mini-128k-instruct.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: microsoft/phi-3-mini-128k-instruct -label: - zh_Hans: microsoft/phi-3-mini-128k-instruct - en_US: microsoft/phi-3-mini-128k-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 4096 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/nvidia/llm/recurrentgemma-2b.yaml b/api/core/model_runtime/model_providers/nvidia/llm/recurrentgemma-2b.yaml deleted file mode 100644 index 73fcce39305347..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/llm/recurrentgemma-2b.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: google/recurrentgemma-2b -label: - zh_Hans: google/recurrentgemma-2b - en_US: google/recurrentgemma-2b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 2048 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.2 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 0.7 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 1024 - default: 1024 - - name: random_seed - type: int - help: - en_US: The seed to use for random sampling. If set, different calls will generate deterministic results. - zh_Hans: 当开启随机数种子以后，你可以通过指定一个固定的种子来使得回答结果更加稳定 - label: - en_US: Seed - zh_Hans: 种子 - default: 0 - min: 0 - max: 2147483647 diff --git a/api/core/model_runtime/model_providers/nvidia/nvidia.py b/api/core/model_runtime/model_providers/nvidia/nvidia.py deleted file mode 100644 index 058fa003462585..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/nvidia.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class MistralAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="mistralai/mixtral-8x7b-instruct-v0.1", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/nvidia/nvidia.yaml b/api/core/model_runtime/model_providers/nvidia/nvidia.yaml deleted file mode 100644 index ce894a3372b757..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/nvidia.yaml +++ /dev/null @@ -1,33 +0,0 @@ -provider: nvidia -label: - en_US: API Catalog -description: - en_US: API Catalog - zh_Hans: API Catalog -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.png -background: "#FFFFFF" -help: - title: - en_US: Get your API Key from NVIDIA - zh_Hans: 从 NVIDIA 获取 API Key - url: - en_US: https://build.nvidia.com/explore/discover -supported_model_types: - - llm - - text-embedding - - rerank -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/nvidia/rerank/__init__.py b/api/core/model_runtime/model_providers/nvidia/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/nvidia/rerank/rerank-qa-mistral-4b.yaml b/api/core/model_runtime/model_providers/nvidia/rerank/rerank-qa-mistral-4b.yaml deleted file mode 100644 index 461f4e1cbe47a4..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/rerank/rerank-qa-mistral-4b.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: nv-rerank-qa-mistral-4b:1 -model_type: rerank -model_properties: - context_size: 512 diff --git a/api/core/model_runtime/model_providers/nvidia/rerank/rerank.py b/api/core/model_runtime/model_providers/nvidia/rerank/rerank.py deleted file mode 100644 index fabebc67ab0eeb..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/rerank/rerank.py +++ /dev/null @@ -1,121 +0,0 @@ -from math import exp -from typing import Optional - -import requests - -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - - -class NvidiaRerankModel(RerankModel): - """ - Model class for NVIDIA rerank model. - """ - - def _sigmoid(self, logit: float) -> float: - return 1 / (1 + exp(-logit)) - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n documents to return - :param user: unique user id - :return: rerank result - """ - if len(docs) == 0: - return RerankResult(model=model, docs=[]) - - try: - invoke_url = "https://ai.api.nvidia.com/v1/retrieval/nvidia/reranking" - - headers = { - "Authorization": f"Bearer {credentials.get('api_key')}", - "Accept": "application/json", - } - payload = { - "model": model, - "query": {"text": query}, - "passages": [{"text": doc} for doc in docs], - } - session = requests.Session() - response = session.post(invoke_url, headers=headers, json=payload) - response.raise_for_status() - results = response.json() - - rerank_documents = [] - for result in results["rankings"]: - index = result["index"] - logit = result["logit"] - rerank_document = RerankDocument( - index=index, - text=docs[index], - score=self._sigmoid(logit), - ) - - rerank_documents.append(rerank_document) - if rerank_documents: - rerank_documents = sorted(rerank_documents, key=lambda x: x.score, reverse=True) - if top_n: - rerank_documents = rerank_documents[:top_n] - return RerankResult(model=model, docs=rerank_documents) - except requests.HTTPError as e: - raise InvokeServerUnavailableError(str(e)) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke( - model=model, - credentials=credentials, - query="What is the GPU memory bandwidth of H100 SXM?", - docs=[ - "Example doc 1", - "Example doc 2", - "Example doc 3", - ], - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - """ - return { - InvokeConnectionError: [requests.ConnectionError], - InvokeServerUnavailableError: [requests.HTTPError], - InvokeRateLimitError: [], - InvokeAuthorizationError: [requests.HTTPError], - InvokeBadRequestError: [requests.RequestException], - } diff --git a/api/core/model_runtime/model_providers/nvidia/text_embedding/__init__.py b/api/core/model_runtime/model_providers/nvidia/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/nvidia/text_embedding/embed-qa-4.yaml b/api/core/model_runtime/model_providers/nvidia/text_embedding/embed-qa-4.yaml deleted file mode 100644 index a9b5e25c3c695e..00000000000000 --- 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a/api/core/model_runtime/model_providers/nvidia_nim/llm/__init__.py b/api/core/model_runtime/model_providers/nvidia_nim/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/nvidia_nim/llm/llm.py b/api/core/model_runtime/model_providers/nvidia_nim/llm/llm.py deleted file mode 100644 index 6ff380bdd99c8b..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia_nim/llm/llm.py +++ /dev/null @@ -1,13 +0,0 @@ -import logging - -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - -logger = logging.getLogger(__name__) - - -class NVIDIANIMProvider(OAIAPICompatLargeLanguageModel): - """ - Model class for NVIDIA NIM large language model. - """ - - pass diff --git a/api/core/model_runtime/model_providers/nvidia_nim/nvidia_nim.py b/api/core/model_runtime/model_providers/nvidia_nim/nvidia_nim.py deleted file mode 100644 index ad890ada22abc8..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia_nim/nvidia_nim.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class NVIDIANIMProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/nvidia_nim/nvidia_nim.yaml b/api/core/model_runtime/model_providers/nvidia_nim/nvidia_nim.yaml deleted file mode 100644 index 0e892665d7e114..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia_nim/nvidia_nim.yaml +++ /dev/null @@ -1,79 +0,0 @@ -provider: nvidia_nim -label: - en_US: NVIDIA NIM -description: - en_US: NVIDIA NIM, a set of easy-to-use inference microservices. - zh_Hans: NVIDIA NIM，一组易于使用的模型推理微服务。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.png -background: "#EFFDFD" -help: - title: - en_US: Learn more about NVIDIA NIM - zh_Hans: 了解 NVIDIA NIM 更多信息 - url: - en_US: https://www.nvidia.com/en-us/ai/ -supported_model_types: - - llm -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter full model name - zh_Hans: 输入模型全称 - credential_form_schemas: - - variable: endpoint_url - label: - zh_Hans: API endpoint URL - en_US: API endpoint URL - type: text-input - required: true - placeholder: - zh_Hans: Base URL, e.g. http://192.168.1.100:8000/v1 - en_US: Base URL, e.g. http://192.168.1.100:8000/v1 - - variable: mode - show_on: - - variable: __model_type - value: llm - label: - en_US: Completion mode - type: select - required: false - default: chat - placeholder: - zh_Hans: 选择对话类型 - en_US: Select completion mode - options: - - value: completion - label: - en_US: Completion - zh_Hans: 补全 - - value: chat - label: - en_US: Chat - zh_Hans: 对话 - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - type: text-input - default: '4096' - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: max_tokens_to_sample - label: - zh_Hans: 最大 token 上限 - en_US: Upper bound for max tokens - show_on: - - variable: __model_type - value: llm - default: '4096' - type: text-input diff --git a/api/core/model_runtime/model_providers/oci/__init__.py b/api/core/model_runtime/model_providers/oci/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/oci/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/oci/_assets/icon_l_en.svg deleted file mode 100644 index 0981dfcff28c78..00000000000000 --- a/api/core/model_runtime/model_providers/oci/_assets/icon_l_en.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/oci/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/oci/_assets/icon_s_en.svg deleted file mode 100644 index 0981dfcff28c78..00000000000000 --- a/api/core/model_runtime/model_providers/oci/_assets/icon_s_en.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/oci/llm/cohere.command-r-16k.yaml b/api/core/model_runtime/model_providers/oci/llm/cohere.command-r-16k.yaml deleted file mode 100644 index eb60cbcd90f5cd..00000000000000 --- a/api/core/model_runtime/model_providers/oci/llm/cohere.command-r-16k.yaml +++ /dev/null @@ -1,52 +0,0 @@ -model: cohere.command-r-16k -label: - en_US: cohere.command-r-16k v1.2 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - default: 1 - max: 1.0 - - name: topP - use_template: top_p - default: 0.75 - min: 0 - max: 1 - - name: topK - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presencePenalty - use_template: presence_penalty - min: 0 - max: 1 - default: 0 - - name: frequencyPenalty - use_template: frequency_penalty - min: 0 - max: 1 - default: 0 - - name: maxTokens - use_template: max_tokens - default: 600 - max: 4000 -pricing: - input: '0.004' - output: '0.004' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/oci/llm/cohere.command-r-plus.yaml b/api/core/model_runtime/model_providers/oci/llm/cohere.command-r-plus.yaml deleted file mode 100644 index df31b0d0df355d..00000000000000 --- a/api/core/model_runtime/model_providers/oci/llm/cohere.command-r-plus.yaml +++ /dev/null @@ -1,52 +0,0 @@ -model: cohere.command-r-plus -label: - en_US: cohere.command-r-plus v1.2 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - default: 1 - max: 1.0 - - name: topP - use_template: top_p - default: 0.75 - min: 0 - max: 1 - - name: topK - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presencePenalty - use_template: presence_penalty - min: 0 - max: 1 - default: 0 - - name: frequencyPenalty - use_template: frequency_penalty - min: 0 - max: 1 - default: 0 - - name: maxTokens - use_template: max_tokens - default: 600 - max: 4000 -pricing: - input: '0.0219' - output: '0.0219' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/oci/llm/llm.py b/api/core/model_runtime/model_providers/oci/llm/llm.py deleted file mode 100644 index 1e1fc5b3ea89aa..00000000000000 --- a/api/core/model_runtime/model_providers/oci/llm/llm.py +++ /dev/null @@ -1,469 +0,0 @@ -import base64 -import copy -import json -import logging -from collections.abc import Generator -from typing import Optional, Union - -import oci -from oci.generative_ai_inference.models.base_chat_response import BaseChatResponse - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -logger = logging.getLogger(__name__) - -request_template = { - "compartmentId": "", - "servingMode": {"modelId": "cohere.command-r-plus", "servingType": "ON_DEMAND"}, - "chatRequest": { - "apiFormat": "COHERE", - # "preambleOverride": "You are a helpful assistant.", - # "message": "Hello!", - # "chatHistory": [], - "maxTokens": 600, - "isStream": False, - "frequencyPenalty": 0, - "presencePenalty": 0, - "temperature": 1, - "topP": 0.75, - }, -} -oci_config_template = { - "user": "", - "fingerprint": "", - "tenancy": "", - "region": "", - "compartment_id": "", - "key_content": "", -} - - -class OCILargeLanguageModel(LargeLanguageModel): - # https://docs.oracle.com/en-us/iaas/Content/generative-ai/pretrained-models.htm - _supported_models = { - "meta.llama-3-70b-instruct": { - "system": True, - "multimodal": False, - "tool_call": False, - "stream_tool_call": False, - }, - "cohere.command-r-16k": { - "system": True, - "multimodal": False, - "tool_call": True, - "stream_tool_call": False, - }, - "cohere.command-r-plus": { - "system": True, - "multimodal": False, - "tool_call": True, - "stream_tool_call": False, - }, - } - - def _is_tool_call_supported(self, model_id: str, stream: bool = False) -> bool: - feature = self._supported_models.get(model_id) - if not feature: - return False - return feature["stream_tool_call"] if stream else feature["tool_call"] - - def _is_multimodal_supported(self, model_id: str) -> bool: - feature = self._supported_models.get(model_id) - if not feature: - return False - return feature["multimodal"] - - def _is_system_prompt_supported(self, model_id: str) -> bool: - feature = self._supported_models.get(model_id) - if not feature: - return False - return feature["system"] - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # print("model"+"*"*20) - # print(model) - # print("credentials"+"*"*20) - # print(credentials) - # print("model_parameters"+"*"*20) - # print(model_parameters) - # print("prompt_messages"+"*"*200) - # print(prompt_messages) - # print("tools"+"*"*20) - # print(tools) - - # invoke model - return self._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return:md = genai.GenerativeModel(model) - """ - prompt = self._convert_messages_to_prompt(prompt_messages) - - return self._get_num_tokens_by_gpt2(prompt) - - def get_num_characters( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return:md = genai.GenerativeModel(model) - """ - prompt = self._convert_messages_to_prompt(prompt_messages) - - return len(prompt) - - def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str: - """ - :param messages: List of PromptMessage to combine. - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - return text.rstrip() - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - # Setup basic variables - # Auth Config - try: - ping_message = SystemPromptMessage(content="ping") - self._generate(model, credentials, [ping_message], {"maxTokens": 5}) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: credentials kwargs - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # config_kwargs = model_parameters.copy() - # config_kwargs['max_output_tokens'] = config_kwargs.pop('max_tokens_to_sample', None) - # if stop: - # config_kwargs["stop_sequences"] = stop - - # initialize client - # ref: https://docs.oracle.com/en-us/iaas/api/#/en/generative-ai-inference/20231130/ChatResult/Chat - oci_config = copy.deepcopy(oci_config_template) - if "oci_config_content" in credentials: - oci_config_content = base64.b64decode(credentials.get("oci_config_content")).decode("utf-8") - config_items = oci_config_content.split("/") - if len(config_items) != 5: - raise CredentialsValidateFailedError( - "oci_config_content should be base64.b64encode(" - "'user_ocid/fingerprint/tenancy_ocid/region/compartment_ocid'.encode('utf-8'))" - ) - oci_config["user"] = config_items[0] - oci_config["fingerprint"] = config_items[1] - oci_config["tenancy"] = config_items[2] - oci_config["region"] = config_items[3] - oci_config["compartment_id"] = config_items[4] - else: - raise CredentialsValidateFailedError("need to set oci_config_content in credentials ") - if "oci_key_content" in credentials: - oci_key_content = base64.b64decode(credentials.get("oci_key_content")).decode("utf-8") - oci_config["key_content"] = oci_key_content.encode(encoding="utf-8") - else: - raise CredentialsValidateFailedError("need to set oci_config_content in credentials ") - - # oci_config = oci.config.from_file('~/.oci/config', credentials.get('oci_api_profile')) - compartment_id = oci_config["compartment_id"] - client = oci.generative_ai_inference.GenerativeAiInferenceClient(config=oci_config) - # call embedding model - request_args = copy.deepcopy(request_template) - request_args["compartmentId"] = compartment_id - request_args["servingMode"]["modelId"] = model - - chat_history = [] - system_prompts = [] - # if "meta.llama" in model: - # request_args["chatRequest"]["apiFormat"] = "GENERIC" - request_args["chatRequest"]["maxTokens"] = model_parameters.pop("maxTokens", 600) - request_args["chatRequest"].update(model_parameters) - frequency_penalty = model_parameters.get("frequencyPenalty", 0) - presence_penalty = model_parameters.get("presencePenalty", 0) - if frequency_penalty > 0 and presence_penalty > 0: - raise InvokeBadRequestError("Cannot set both frequency penalty and presence penalty") - - # for msg in prompt_messages: # makes message roles strictly alternating - # content = self._format_message_to_glm_content(msg) - # if history and history[-1]["role"] == content["role"]: - # history[-1]["parts"].extend(content["parts"]) - # else: - # history.append(content) - - # temporary not implement the tool call function - valid_value = self._is_tool_call_supported(model, stream) - if tools is not None and len(tools) > 0: - if not valid_value: - raise InvokeBadRequestError("Does not support function calling") - if model.startswith("cohere"): - # print("run cohere " * 10) - for message in prompt_messages[:-1]: - text = "" - if isinstance(message.content, str): - text = message.content - if isinstance(message, UserPromptMessage): - chat_history.append({"role": "USER", "message": text}) - else: - chat_history.append({"role": "CHATBOT", "message": text}) - if isinstance(message, SystemPromptMessage): - if isinstance(message.content, str): - system_prompts.append(message.content) - args = { - "apiFormat": "COHERE", - "preambleOverride": " ".join(system_prompts), - "message": prompt_messages[-1].content, - "chatHistory": chat_history, - } - request_args["chatRequest"].update(args) - elif model.startswith("meta"): - # print("run meta " * 10) - meta_messages = [] - for message in prompt_messages: - text = message.content - meta_messages.append({"role": message.role.name, "content": [{"type": "TEXT", "text": text}]}) - args = {"apiFormat": "GENERIC", "messages": meta_messages, "numGenerations": 1, "topK": -1} - request_args["chatRequest"].update(args) - - if stream: - request_args["chatRequest"]["isStream"] = True - # print("final request" + "|" * 20) - # print(request_args) - response = client.chat(request_args) - # print(vars(response)) - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_response( - self, model: str, credentials: dict, response: BaseChatResponse, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=response.data.chat_response.text) - - # calculate num tokens - prompt_tokens = self.get_num_characters(model, credentials, prompt_messages) - completion_tokens = self.get_num_characters(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - - return result - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: BaseChatResponse, prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - index = -1 - events = response.data.events() - for stream in events: - chunk = json.loads(stream.data) - # print(chunk) - # chunk: {'apiFormat': 'COHERE', 'text': 'Hello'} - - # for chunk in response: - # for part in chunk.parts: - # if part.function_call: - # assistant_prompt_message.tool_calls = [ - # AssistantPromptMessage.ToolCall( - # id=part.function_call.name, - # type='function', - # function=AssistantPromptMessage.ToolCall.ToolCallFunction( - # name=part.function_call.name, - # arguments=json.dumps(dict(part.function_call.args.items())) - # ) - # ) - # ] - - if "finishReason" not in chunk: - assistant_prompt_message = AssistantPromptMessage(content="") - if model.startswith("cohere"): - if chunk["text"]: - assistant_prompt_message.content += chunk["text"] - elif model.startswith("meta"): - assistant_prompt_message.content += chunk["message"]["content"][0]["text"] - index += 1 - # transform assistant message to prompt message - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message), - ) - else: - # calculate num tokens - prompt_tokens = self.get_num_characters(model, credentials, prompt_messages) - completion_tokens = self.get_num_characters(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - finish_reason=str(chunk["finishReason"]), - usage=usage, - ), - ) - - def _convert_one_message_to_text(self, message: PromptMessage) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt = "\n\nuser:" - ai_prompt = "\n\nmodel:" - - content = message.content - if isinstance(content, list): - content = "".join(c.data for c in content if c.type != PromptMessageContentType.IMAGE) - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage | ToolPromptMessage): - message_text = f"{human_prompt} {content}" - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [], - InvokeRateLimitError: [], - InvokeAuthorizationError: [], - InvokeBadRequestError: [], - } diff --git a/api/core/model_runtime/model_providers/oci/llm/meta.llama-3-70b-instruct.yaml b/api/core/model_runtime/model_providers/oci/llm/meta.llama-3-70b-instruct.yaml deleted file mode 100644 index dd5be107c07570..00000000000000 --- a/api/core/model_runtime/model_providers/oci/llm/meta.llama-3-70b-instruct.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: meta.llama-3-70b-instruct -label: - zh_Hans: meta.llama-3-70b-instruct - en_US: meta.llama-3-70b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - default: 1 - max: 2.0 - - name: topP - use_template: top_p - default: 0.75 - min: 0 - max: 1 - - name: topK - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presencePenalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 - - name: frequencyPenalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: maxTokens - use_template: max_tokens - default: 600 - max: 8000 -pricing: - input: '0.015' - output: '0.015' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/oci/oci.py b/api/core/model_runtime/model_providers/oci/oci.py deleted file mode 100644 index e182d2d0439d77..00000000000000 --- a/api/core/model_runtime/model_providers/oci/oci.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class OCIGENAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `cohere.command-r-plus` model for validate, - model_instance.validate_credentials(model="cohere.command-r-plus", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/oci/oci.yaml b/api/core/model_runtime/model_providers/oci/oci.yaml deleted file mode 100644 index f2f23e18f12073..00000000000000 --- a/api/core/model_runtime/model_providers/oci/oci.yaml +++ /dev/null @@ -1,42 +0,0 @@ -provider: oci -label: - en_US: OCIGenerativeAI -description: - en_US: Models provided by OCI, such as Cohere Command R and Cohere Command R+. - zh_Hans: OCI 提供的模型，例如 Cohere Command R 和 Cohere Command R+。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#FFFFFF" -help: - title: - en_US: Get your API Key from OCI - zh_Hans: 从 OCI 获取 API Key - url: - en_US: https://docs.cloud.oracle.com/Content/API/Concepts/sdkconfig.htm -supported_model_types: - - llm - - text-embedding - #- rerank -configurate_methods: - - predefined-model - #- customizable-model -provider_credential_schema: - credential_form_schemas: - - variable: oci_config_content - label: - en_US: oci api key config file's content - type: text-input - required: true - placeholder: - zh_Hans: 在此输入您的 oci api key config 文件的内容(base64.b64encode("user_ocid/fingerprint/tenancy_ocid/region/compartment_ocid".encode('utf-8')) ) - en_US: Enter your oci api key config file's content(base64.b64encode("user_ocid/fingerprint/tenancy_ocid/region/compartment_ocid".encode('utf-8')) ) - - variable: oci_key_content - label: - en_US: oci api key file's content - type: text-input - required: true - placeholder: - zh_Hans: 在此输入您的 oci api key 文件的内容(base64.b64encode("pem file content".encode('utf-8'))) - en_US: Enter your oci api key file's content(base64.b64encode("pem file content".encode('utf-8'))) diff --git a/api/core/model_runtime/model_providers/oci/text_embedding/__init__.py b/api/core/model_runtime/model_providers/oci/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/oci/text_embedding/_position.yaml b/api/core/model_runtime/model_providers/oci/text_embedding/_position.yaml deleted file mode 100644 index 149f1e3797850f..00000000000000 --- a/api/core/model_runtime/model_providers/oci/text_embedding/_position.yaml +++ /dev/null @@ -1,5 +0,0 @@ -- cohere.embed-english-light-v2.0 -- cohere.embed-english-light-v3.0 -- cohere.embed-english-v3.0 -- cohere.embed-multilingual-light-v3.0 -- cohere.embed-multilingual-v3.0 diff --git a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-light-v2.0.yaml b/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-light-v2.0.yaml deleted file mode 100644 index 259d5b45b7a2f1..00000000000000 --- a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-light-v2.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: cohere.embed-english-light-v2.0 -model_type: text-embedding -model_properties: - context_size: 1024 - max_chunks: 48 -pricing: - input: '0.001' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-light-v3.0.yaml b/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-light-v3.0.yaml deleted file mode 100644 index 065e7474c0bb97..00000000000000 --- a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-light-v3.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: cohere.embed-english-light-v3.0 -model_type: text-embedding -model_properties: - context_size: 384 - max_chunks: 48 -pricing: - input: '0.001' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-v3.0.yaml b/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-v3.0.yaml deleted file mode 100644 index 3e2deea16a1d0b..00000000000000 --- a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-english-v3.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: cohere.embed-english-v3.0 -model_type: text-embedding -model_properties: - context_size: 1024 - max_chunks: 48 -pricing: - input: '0.001' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-multilingual-light-v3.0.yaml b/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-multilingual-light-v3.0.yaml deleted file mode 100644 index 0d2b892c64290e..00000000000000 --- a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-multilingual-light-v3.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: cohere.embed-multilingual-light-v3.0 -model_type: text-embedding -model_properties: - context_size: 384 - max_chunks: 48 -pricing: - input: '0.001' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-multilingual-v3.0.yaml b/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-multilingual-v3.0.yaml deleted file mode 100644 index 9ebe260b32875b..00000000000000 --- a/api/core/model_runtime/model_providers/oci/text_embedding/cohere.embed-multilingual-v3.0.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: cohere.embed-multilingual-v3.0 -model_type: text-embedding -model_properties: - context_size: 1024 - max_chunks: 48 -pricing: - input: '0.001' - unit: '0.0001' - currency: USD diff --git a/api/core/model_runtime/model_providers/ollama/__init__.py b/api/core/model_runtime/model_providers/ollama/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/ollama/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/ollama/_assets/icon_l_en.svg deleted file mode 100644 index 39d8a1ece60a10..00000000000000 --- a/api/core/model_runtime/model_providers/ollama/_assets/icon_l_en.svg +++ /dev/null @@ -1,15 +0,0 @@ - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/ollama/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/ollama/_assets/icon_s_en.svg deleted file mode 100644 index f8482a96b99cbc..00000000000000 --- a/api/core/model_runtime/model_providers/ollama/_assets/icon_s_en.svg +++ /dev/null @@ -1,15 +0,0 @@ - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/ollama/llm/__init__.py b/api/core/model_runtime/model_providers/ollama/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/ollama/llm/llm.py b/api/core/model_runtime/model_providers/ollama/llm/llm.py deleted file mode 100644 index a7ea53e0e99c5f..00000000000000 --- a/api/core/model_runtime/model_providers/ollama/llm/llm.py +++ /dev/null @@ -1,726 +0,0 @@ -import json -import logging -import re -from collections.abc import Generator -from decimal import Decimal -from typing import Optional, Union, cast -from urllib.parse import urljoin - -import requests - -from core.model_runtime.entities.llm_entities import ( - LLMMode, - LLMResult, - LLMResultChunk, - LLMResultChunkDelta, -) -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - DefaultParameterName, - FetchFrom, - I18nObject, - ModelFeature, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, - PriceConfig, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import ( - LargeLanguageModel, -) - -logger = logging.getLogger(__name__) - - -class OllamaLargeLanguageModel(LargeLanguageModel): - """ - Model class for Ollama large language model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - stop=stop, - stream=stream, - user=user, - ) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - # get model mode - model_mode = self.get_model_mode(model, credentials) - - if model_mode == LLMMode.CHAT: - # chat model - return self._num_tokens_from_messages(prompt_messages) - else: - first_prompt_message = prompt_messages[0] - if isinstance(first_prompt_message.content, str): - text = first_prompt_message.content - else: - text = "" - for message_content in first_prompt_message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - text = message_content.data - break - return self._get_num_tokens_by_gpt2(text) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._generate( - model=model, - credentials=credentials, - prompt_messages=[UserPromptMessage(content="ping")], - model_parameters={"num_predict": 5}, - stream=False, - ) - except InvokeError as ex: - raise CredentialsValidateFailedError(f"An error occurred during credentials validation: {ex.description}") - except Exception as ex: - raise CredentialsValidateFailedError(f"An error occurred during credentials validation: {str(ex)}") - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke llm completion model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - headers = {"Content-Type": "application/json"} - - endpoint_url = credentials["base_url"] - if not endpoint_url.endswith("/"): - endpoint_url += "/" - - # prepare the payload for a simple ping to the model - data = {"model": model, "stream": stream} - - if "format" in model_parameters: - data["format"] = model_parameters["format"] - del model_parameters["format"] - - if "keep_alive" in model_parameters: - data["keep_alive"] = model_parameters["keep_alive"] - del model_parameters["keep_alive"] - - data["options"] = model_parameters or {} - - if stop: - data["options"]["stop"] = stop - - completion_type = LLMMode.value_of(credentials["mode"]) - - if completion_type is LLMMode.CHAT: - endpoint_url = urljoin(endpoint_url, "api/chat") - data["messages"] = [self._convert_prompt_message_to_dict(m) for m in prompt_messages] - else: - endpoint_url = urljoin(endpoint_url, "api/generate") - first_prompt_message = prompt_messages[0] - if isinstance(first_prompt_message, UserPromptMessage): - first_prompt_message = cast(UserPromptMessage, first_prompt_message) - if isinstance(first_prompt_message.content, str): - data["prompt"] = first_prompt_message.content - else: - text = "" - images = [] - for message_content in first_prompt_message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - text = message_content.data - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - image_data = re.sub( - r"^data:image\/[a-zA-Z]+;base64,", - "", - message_content.data, - ) - images.append(image_data) - - data["prompt"] = text - data["images"] = images - - # send a post request to validate the credentials - response = requests.post(endpoint_url, headers=headers, json=data, timeout=(10, 300), stream=stream) - - response.encoding = "utf-8" - if response.status_code != 200: - raise InvokeError(f"API request failed with status code {response.status_code}: {response.text}") - - if stream: - return self._handle_generate_stream_response(model, credentials, completion_type, response, prompt_messages) - - return self._handle_generate_response(model, credentials, completion_type, response, prompt_messages) - - def _handle_generate_response( - self, - model: str, - credentials: dict, - completion_type: LLMMode, - response: requests.Response, - prompt_messages: list[PromptMessage], - ) -> LLMResult: - """ - Handle llm completion response - - :param model: model name - :param credentials: model credentials - :param completion_type: completion type - :param response: response - :param prompt_messages: prompt messages - :return: llm result - """ - response_json = response.json() - - if completion_type is LLMMode.CHAT: - message = response_json.get("message", {}) - response_content = message.get("content", "") - else: - response_content = response_json["response"] - - assistant_message = AssistantPromptMessage(content=response_content) - - if "prompt_eval_count" in response_json and "eval_count" in response_json: - # transform usage - prompt_tokens = response_json["prompt_eval_count"] - completion_tokens = response_json["eval_count"] - else: - # calculate num tokens - prompt_tokens = self._get_num_tokens_by_gpt2(prompt_messages[0].content) - completion_tokens = self._get_num_tokens_by_gpt2(assistant_message.content) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=response_json["model"], - prompt_messages=prompt_messages, - message=assistant_message, - usage=usage, - ) - - return result - - def _handle_generate_stream_response( - self, - model: str, - credentials: dict, - completion_type: LLMMode, - response: requests.Response, - prompt_messages: list[PromptMessage], - ) -> Generator: - """ - Handle llm completion stream response - - :param model: model name - :param credentials: model credentials - :param completion_type: completion type - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - full_text = "" - chunk_index = 0 - - def create_final_llm_result_chunk( - index: int, message: AssistantPromptMessage, finish_reason: str - ) -> LLMResultChunk: - # calculate num tokens - prompt_tokens = self._get_num_tokens_by_gpt2(prompt_messages[0].content) - completion_tokens = self._get_num_tokens_by_gpt2(full_text) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - return LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=message, - finish_reason=finish_reason, - usage=usage, - ), - ) - - for chunk in response.iter_lines(decode_unicode=True, delimiter="\n"): - if not chunk: - continue - - try: - chunk_json = json.loads(chunk) - # stream ended - except json.JSONDecodeError as e: - yield create_final_llm_result_chunk( - index=chunk_index, - message=AssistantPromptMessage(content=""), - finish_reason="Non-JSON encountered.", - ) - - chunk_index += 1 - break - - if completion_type is LLMMode.CHAT: - if not chunk_json: - continue - - if "message" not in chunk_json: - text = "" - else: - text = chunk_json.get("message").get("content", "") - else: - if not chunk_json: - continue - - # transform assistant message to prompt message - text = chunk_json["response"] - - assistant_prompt_message = AssistantPromptMessage(content=text) - - full_text += text - - if chunk_json["done"]: - # calculate num tokens - if "prompt_eval_count" in chunk_json: - prompt_tokens = chunk_json["prompt_eval_count"] - else: - prompt_message_content = prompt_messages[0].content - if isinstance(prompt_message_content, str): - prompt_tokens = self._get_num_tokens_by_gpt2(prompt_message_content) - else: - content_text = "" - for message_content in prompt_message_content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - content_text += message_content.data - prompt_tokens = self._get_num_tokens_by_gpt2(content_text) - - completion_tokens = chunk_json.get("eval_count", self._get_num_tokens_by_gpt2(full_text)) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=chunk_json["model"], - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk_index, - message=assistant_prompt_message, - finish_reason="stop", - usage=usage, - ), - ) - else: - yield LLMResultChunk( - model=chunk_json["model"], - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk_index, - message=assistant_prompt_message, - ), - ) - - chunk_index += 1 - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for Ollama API - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - text = "" - images = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - text = message_content.data - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - image_data = re.sub(r"^data:image\/[a-zA-Z]+;base64,", "", message_content.data) - images.append(image_data) - - message_dict = {"role": "user", "content": text, "images": images} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - else: - raise ValueError(f"Got unknown type {message}") - - return message_dict - - def _num_tokens_from_messages(self, messages: list[PromptMessage]) -> int: - """ - Calculate num tokens. - - :param messages: messages - """ - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - for key, value in message.items(): - num_tokens += self._get_num_tokens_by_gpt2(str(key)) - num_tokens += self._get_num_tokens_by_gpt2(str(value)) - - return num_tokens - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - Get customizable model schema. - - :param model: model name - :param credentials: credentials - - :return: model schema - """ - extras = {} - - if "vision_support" in credentials and credentials["vision_support"] == "true": - extras["features"] = [ModelFeature.VISION] - - entity = AIModelEntity( - model=model, - label=I18nObject(zh_Hans=model, en_US=model), - model_type=ModelType.LLM, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.MODE: credentials.get("mode"), - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", 4096)), - }, - parameter_rules=[ - ParameterRule( - name=DefaultParameterName.TEMPERATURE.value, - use_template=DefaultParameterName.TEMPERATURE.value, - label=I18nObject(en_US="Temperature", zh_Hans="温度"), - type=ParameterType.FLOAT, - help=I18nObject( - en_US="The temperature of the model. " - "Increasing the temperature will make the model answer " - "more creatively. (Default: 0.8)", - zh_Hans="模型的温度。增加温度将使模型的回答更具创造性。（默认值：0.8）", - ), - default=0.1, - min=0, - max=1, - ), - ParameterRule( - name=DefaultParameterName.TOP_P.value, - use_template=DefaultParameterName.TOP_P.value, - label=I18nObject(en_US="Top P", zh_Hans="Top P"), - type=ParameterType.FLOAT, - help=I18nObject( - en_US="Works together with top-k. A higher value (e.g., 0.95) will lead to " - "more diverse text, while a lower value (e.g., 0.5) will generate more " - "focused and conservative text. (Default: 0.9)", - zh_Hans="与top-k一起工作。较高的值（例如，0.95）会导致生成更多样化的文本，而较低的值（例如，0.5）会生成更专注和保守的文本。（默认值：0.9）", - ), - default=0.9, - min=0, - max=1, - ), - ParameterRule( - name="top_k", - label=I18nObject(en_US="Top K", zh_Hans="Top K"), - type=ParameterType.INT, - help=I18nObject( - en_US="Reduces the probability of generating nonsense. " - "A higher value (e.g. 100) will give more diverse answers, " - "while a lower value (e.g. 10) will be more conservative. (Default: 40)", - zh_Hans="减少生成无意义内容的可能性。较高的值（例如100）将提供更多样化的答案，而较低的值（例如10）将更为保守。（默认值：40）", - ), - min=1, - max=100, - ), - ParameterRule( - name="repeat_penalty", - label=I18nObject(en_US="Repeat Penalty"), - type=ParameterType.FLOAT, - help=I18nObject( - en_US="Sets how strongly to penalize repetitions. " - "A higher value (e.g., 1.5) will penalize repetitions more strongly, " - "while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)", - zh_Hans="设置对重复内容的惩罚强度。一个较高的值（例如，1.5）会更强地惩罚重复内容，而一个较低的值（例如，0.9）则会相对宽容。（默认值：1.1）", - ), - min=-2, - max=2, - ), - ParameterRule( - name="num_predict", - use_template="max_tokens", - label=I18nObject(en_US="Num Predict", zh_Hans="最大令牌数预测"), - type=ParameterType.INT, - help=I18nObject( - en_US="Maximum number of tokens to predict when generating text. " - "(Default: 128, -1 = infinite generation, -2 = fill context)", - zh_Hans="生成文本时预测的最大令牌数。（默认值：128，-1 = 无限生成，-2 = 填充上下文）", - ), - default=(512 if int(credentials.get("max_tokens", 4096)) >= 768 else 128), - min=-2, - max=int(credentials.get("max_tokens", 4096)), - ), - ParameterRule( - name="mirostat", - label=I18nObject(en_US="Mirostat sampling", zh_Hans="Mirostat 采样"), - type=ParameterType.INT, - help=I18nObject( - en_US="Enable Mirostat sampling for controlling perplexity. " - "(default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)", - zh_Hans="启用 Mirostat 采样以控制困惑度。" - "（默认值：0，0 = 禁用，1 = Mirostat，2 = Mirostat 2.0）", - ), - min=0, - max=2, - ), - ParameterRule( - name="mirostat_eta", - label=I18nObject(en_US="Mirostat Eta", zh_Hans="学习率"), - type=ParameterType.FLOAT, - help=I18nObject( - en_US="Influences how quickly the algorithm responds to feedback from " - "the generated text. A lower learning rate will result in slower adjustments, " - "while a higher learning rate will make the algorithm more responsive. " - "(Default: 0.1)", - zh_Hans="影响算法对生成文本反馈响应的速度。较低的学习率会导致调整速度变慢，而较高的学习率会使得算法更加灵敏。（默认值：0.1）", - ), - precision=1, - ), - ParameterRule( - name="mirostat_tau", - label=I18nObject(en_US="Mirostat Tau", zh_Hans="文本连贯度"), - type=ParameterType.FLOAT, - help=I18nObject( - en_US="Controls the balance between coherence and diversity of the output. " - "A lower value will result in more focused and coherent text. (Default: 5.0)", - zh_Hans="控制输出的连贯性和多样性之间的平衡。较低的值会导致更专注和连贯的文本。（默认值：5.0）", - ), - precision=1, - ), - ParameterRule( - name="num_ctx", - label=I18nObject(en_US="Size of context window", zh_Hans="上下文窗口大小"), - type=ParameterType.INT, - help=I18nObject( - en_US="Sets the size of the context window used to generate the next token. (Default: 2048)", - zh_Hans="设置用于生成下一个标记的上下文窗口大小。（默认值：2048）", - ), - default=2048, - min=1, - ), - ParameterRule( - name="num_gpu", - label=I18nObject(en_US="GPU Layers", zh_Hans="GPU 层数"), - type=ParameterType.INT, - help=I18nObject( - en_US="The number of layers to offload to the GPU(s). " - "On macOS it defaults to 1 to enable metal support, 0 to disable." - "As long as a model fits into one gpu it stays in one. " - "It does not set the number of GPU(s). ", - zh_Hans="加载到 GPU 的层数。在 macOS 上，默认为 1 以启用 Metal 支持，设置为 0 则禁用。" - "只要模型适合一个 GPU，它就保留在其中。它不设置 GPU 的数量。", - ), - min=-1, - default=1, - ), - ParameterRule( - name="num_thread", - label=I18nObject(en_US="Num Thread", zh_Hans="线程数"), - type=ParameterType.INT, - help=I18nObject( - en_US="Sets the number of threads to use during computation. " - "By default, Ollama will detect this for optimal performance. " - "It is recommended to set this value to the number of physical CPU cores " - "your system has (as opposed to the logical number of cores).", - zh_Hans="设置计算过程中使用的线程数。默认情况下，Ollama会检测以获得最佳性能。建议将此值设置为系统拥有的物理CPU核心数（而不是逻辑核心数）。", - ), - min=1, - ), - ParameterRule( - name="repeat_last_n", - label=I18nObject(en_US="Repeat last N", zh_Hans="回溯内容"), - type=ParameterType.INT, - help=I18nObject( - en_US="Sets how far back for the model to look back to prevent repetition. " - "(Default: 64, 0 = disabled, -1 = num_ctx)", - zh_Hans="设置模型回溯多远的内容以防止重复。（默认值：64，0 = 禁用，-1 = num_ctx）", - ), - min=-1, - ), - ParameterRule( - name="tfs_z", - label=I18nObject(en_US="TFS Z", zh_Hans="减少标记影响"), - type=ParameterType.FLOAT, - help=I18nObject( - en_US="Tail free sampling is used to reduce the impact of less probable tokens " - "from the output. A higher value (e.g., 2.0) will reduce the impact more, " - "while a value of 1.0 disables this setting. (default: 1)", - zh_Hans="用于减少输出中不太可能的标记的影响。较高的值（例如，2.0）会更多地减少这种影响，而1.0的值则会禁用此设置。（默认值：1）", - ), - precision=1, - ), - ParameterRule( - name="seed", - label=I18nObject(en_US="Seed", zh_Hans="随机数种子"), - type=ParameterType.INT, - help=I18nObject( - en_US="Sets the random number seed to use for generation. Setting this to " - "a specific number will make the model generate the same text for " - "the same prompt. (Default: 0)", - zh_Hans="设置用于生成的随机数种子。将此设置为特定数字将使模型对相同的提示生成相同的文本。（默认值：0）", - ), - ), - ParameterRule( - name="keep_alive", - label=I18nObject(en_US="Keep Alive", zh_Hans="模型存活时间"), - type=ParameterType.STRING, - help=I18nObject( - en_US="Sets how long the model is kept in memory after generating a response. " - "This must be a duration string with a unit (e.g., '10m' for 10 minutes or '24h' for 24 hours)." - " A negative number keeps the model loaded indefinitely, and '0' unloads the model" - " immediately after generating a response." - " Valid time units are 's','m','h'. (Default: 5m)", - zh_Hans="设置模型在生成响应后在内存中保留的时间。" - "这必须是一个带有单位的持续时间字符串（例如，'10m' 表示10分钟，'24h' 表示24小时）。" - "负数表示无限期地保留模型，'0'表示在生成响应后立即卸载模型。" - "有效的时间单位有 's'（秒）、'm'（分钟）、'h'（小时）。（默认值：5m）", - ), - ), - ParameterRule( - name="format", - label=I18nObject(en_US="Format", zh_Hans="返回格式"), - type=ParameterType.STRING, - help=I18nObject( - en_US="the format to return a response in. Currently the only accepted value is json.", - zh_Hans="返回响应的格式。目前唯一接受的值是json。", - ), - options=["json"], - ), - ], - pricing=PriceConfig( - input=Decimal(credentials.get("input_price", 0)), - output=Decimal(credentials.get("output_price", 0)), - unit=Decimal(credentials.get("unit", 0)), - currency=credentials.get("currency", "USD"), - ), - **extras, - ) - - return entity - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeAuthorizationError: [ - requests.exceptions.InvalidHeader, # Missing or Invalid API Key - ], - InvokeBadRequestError: [ - requests.exceptions.HTTPError, # Invalid Endpoint URL or model name - requests.exceptions.InvalidURL, # Misconfigured request or other API error - ], - InvokeRateLimitError: [ - requests.exceptions.RetryError # Too many requests sent in a short period of time - ], - InvokeServerUnavailableError: [ - requests.exceptions.ConnectionError, # Engine Overloaded - requests.exceptions.HTTPError, # Server Error - ], - InvokeConnectionError: [ - requests.exceptions.ConnectTimeout, # Timeout - requests.exceptions.ReadTimeout, # Timeout - ], - } diff --git a/api/core/model_runtime/model_providers/ollama/ollama.py b/api/core/model_runtime/model_providers/ollama/ollama.py deleted file mode 100644 index 115280193a5ed6..00000000000000 --- a/api/core/model_runtime/model_providers/ollama/ollama.py +++ /dev/null @@ -1,16 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class OpenAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - pass diff --git a/api/core/model_runtime/model_providers/ollama/ollama.yaml b/api/core/model_runtime/model_providers/ollama/ollama.yaml deleted file mode 100644 index 33747753bd9f67..00000000000000 --- a/api/core/model_runtime/model_providers/ollama/ollama.yaml +++ /dev/null @@ -1,98 +0,0 @@ -provider: ollama -label: - en_US: Ollama -icon_large: - en_US: icon_l_en.svg -icon_small: - en_US: icon_s_en.svg -background: "#F9FAFB" -help: - title: - en_US: How to integrate with Ollama - zh_Hans: 如何集成 Ollama - url: - en_US: https://docs.dify.ai/tutorials/model-configuration/ollama -supported_model_types: - - llm - - text-embedding -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: base_url - label: - zh_Hans: 基础 URL - en_US: Base URL - type: text-input - required: true - placeholder: - zh_Hans: Ollama server 的基础 URL，例如 http://192.168.1.100:11434 - en_US: Base url of Ollama server, e.g. http://192.168.1.100:11434 - - variable: mode - show_on: - - variable: __model_type - value: llm - label: - zh_Hans: 模型类型 - en_US: Completion mode - type: select - required: true - default: chat - placeholder: - zh_Hans: 选择对话类型 - en_US: Select completion mode - options: - - value: completion - label: - en_US: Completion - zh_Hans: 补全 - - value: chat - label: - en_US: Chat - zh_Hans: 对话 - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - type: text-input - default: '4096' - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: max_tokens - label: - zh_Hans: 最大 token 上限 - en_US: Upper bound for max tokens - show_on: - - variable: __model_type - value: llm - default: '4096' - type: text-input - required: true - - variable: vision_support - label: - zh_Hans: 是否支持 Vision - en_US: Vision support - show_on: - - variable: __model_type - value: llm - default: 'false' - type: radio - required: false - options: - - value: 'true' - label: - en_US: 'Yes' - zh_Hans: 是 - - value: 'false' - label: - en_US: 'No' - zh_Hans: 否 diff --git a/api/core/model_runtime/model_providers/ollama/text_embedding/__init__.py b/api/core/model_runtime/model_providers/ollama/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai/__init__.py b/api/core/model_runtime/model_providers/openai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/openai/_assets/icon_l_en.svg deleted file mode 100644 index dae73f58d71908..00000000000000 --- a/api/core/model_runtime/model_providers/openai/_assets/icon_l_en.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/openai/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/openai/_assets/icon_s_en.svg deleted file mode 100644 index 70686f9b3b58aa..00000000000000 --- a/api/core/model_runtime/model_providers/openai/_assets/icon_s_en.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - diff --git a/api/core/model_runtime/model_providers/openai/_common.py b/api/core/model_runtime/model_providers/openai/_common.py deleted file mode 100644 index 2181bb4f08fd8f..00000000000000 --- a/api/core/model_runtime/model_providers/openai/_common.py +++ /dev/null @@ -1,60 +0,0 @@ -from collections.abc import Mapping - -import openai -from httpx import Timeout - -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) - - -class _CommonOpenAI: - def _to_credential_kwargs(self, credentials: Mapping) -> dict: - """ - Transform credentials to kwargs for model instance - - :param credentials: - :return: - """ - credentials_kwargs = { - "api_key": credentials["openai_api_key"], - "timeout": Timeout(315.0, read=300.0, write=10.0, connect=5.0), - "max_retries": 1, - } - - if credentials.get("openai_api_base"): - openai_api_base = credentials["openai_api_base"].rstrip("/") - credentials_kwargs["base_url"] = openai_api_base + "/v1" - - if "openai_organization" in credentials: - credentials_kwargs["organization"] = credentials["openai_organization"] - - return credentials_kwargs - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [openai.APIConnectionError, openai.APITimeoutError], - InvokeServerUnavailableError: [openai.InternalServerError], - InvokeRateLimitError: [openai.RateLimitError], - InvokeAuthorizationError: [openai.AuthenticationError, openai.PermissionDeniedError], - InvokeBadRequestError: [ - openai.BadRequestError, - openai.NotFoundError, - openai.UnprocessableEntityError, - openai.APIError, - ], - } diff --git a/api/core/model_runtime/model_providers/openai/llm/__init__.py b/api/core/model_runtime/model_providers/openai/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai/llm/_position.yaml b/api/core/model_runtime/model_providers/openai/llm/_position.yaml deleted file mode 100644 index 7501bc1164dc43..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/_position.yaml +++ /dev/null @@ -1,26 +0,0 @@ -- gpt-4 -- gpt-4o -- gpt-4o-2024-05-13 -- gpt-4o-2024-08-06 -- chatgpt-4o-latest -- gpt-4o-mini -- gpt-4o-mini-2024-07-18 -- o1-preview -- o1-preview-2024-09-12 -- o1-mini -- o1-mini-2024-09-12 -- gpt-4-turbo -- gpt-4-turbo-2024-04-09 -- gpt-4-turbo-preview -- gpt-4-32k -- gpt-4-1106-preview -- gpt-4-0125-preview -- gpt-4-vision-preview -- gpt-3.5-turbo -- gpt-3.5-turbo-16k -- gpt-3.5-turbo-16k-0613 -- gpt-3.5-turbo-0125 -- gpt-3.5-turbo-1106 -- gpt-3.5-turbo-0613 -- gpt-3.5-turbo-instruct -- text-davinci-003 diff --git a/api/core/model_runtime/model_providers/openai/llm/chatgpt-4o-latest.yaml b/api/core/model_runtime/model_providers/openai/llm/chatgpt-4o-latest.yaml deleted file mode 100644 index b47449a49abc2e..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/chatgpt-4o-latest.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: chatgpt-4o-latest -label: - zh_Hans: chatgpt-4o-latest - en_US: chatgpt-4o-latest -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 16384 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '2.50' - output: '10.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-0125.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-0125.yaml deleted file mode 100644 index ffa725ec40f4f5..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-0125.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: gpt-3.5-turbo-0125 -label: - zh_Hans: gpt-3.5-turbo-0125 - en_US: gpt-3.5-turbo-0125 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 16385 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.0005' - output: '0.0015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-0613.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-0613.yaml deleted file mode 100644 index a1ad07d7129568..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-0613.yaml +++ /dev/null @@ -1,34 +0,0 @@ -model: gpt-3.5-turbo-0613 -label: - zh_Hans: gpt-3.5-turbo-0613 - en_US: gpt-3.5-turbo-0613 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '0.0015' - output: '0.002' - unit: '0.001' - currency: USD -deprecated: true diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-1106.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-1106.yaml deleted file mode 100644 index 21150fc3a6df61..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-1106.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: gpt-3.5-turbo-1106 -label: - zh_Hans: gpt-3.5-turbo-1106 - en_US: gpt-3.5-turbo-1106 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 16385 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.001' - output: '0.002' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-16k-0613.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-16k-0613.yaml deleted file mode 100644 index 4e302792842415..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-16k-0613.yaml +++ /dev/null @@ -1,34 +0,0 @@ -model: gpt-3.5-turbo-16k-0613 -label: - zh_Hans: gpt-3.5-turbo-16k-0613 - en_US: gpt-3.5-turbo-16k-0613 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 16385 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 16385 - - name: response_format - use_template: response_format -pricing: - input: '0.003' - output: '0.004' - unit: '0.001' - currency: USD -deprecated: true diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-16k.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-16k.yaml deleted file mode 100644 index 3684c1945c7d29..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-16k.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: gpt-3.5-turbo-16k -label: - zh_Hans: gpt-3.5-turbo-16k - en_US: gpt-3.5-turbo-16k -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 16385 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 16385 - - name: response_format - use_template: response_format -pricing: - input: '0.003' - output: '0.004' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-instruct.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-instruct.yaml deleted file mode 100644 index ad831539e09d1a..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: gpt-3.5-turbo-instruct -label: - zh_Hans: gpt-3.5-turbo-instruct - en_US: gpt-3.5-turbo-instruct -model_type: llm -features: [ ] -model_properties: - mode: completion - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: '0.0015' - output: '0.002' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo.yaml deleted file mode 100644 index d3a8ee535a9d16..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-3.5-turbo.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: gpt-3.5-turbo -label: - zh_Hans: gpt-3.5-turbo - en_US: gpt-3.5-turbo -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 16385 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.0005' - output: '0.0015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4-0125-preview.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4-0125-preview.yaml deleted file mode 100644 index ac4ec5840bd771..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4-0125-preview.yaml +++ /dev/null @@ -1,56 +0,0 @@ -model: gpt-4-0125-preview -label: - zh_Hans: gpt-4-0125-preview - en_US: gpt-4-0125-preview -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.01' - output: '0.03' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4-1106-preview.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4-1106-preview.yaml deleted file mode 100644 index d7752397701f9a..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4-1106-preview.yaml +++ /dev/null @@ -1,56 +0,0 @@ -model: gpt-4-1106-preview -label: - zh_Hans: gpt-4-1106-preview - en_US: gpt-4-1106-preview -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.01' - output: '0.03' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4-32k.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4-32k.yaml deleted file mode 100644 index 8358425e6d2909..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4-32k.yaml +++ /dev/null @@ -1,56 +0,0 @@ -model: gpt-4-32k -label: - zh_Hans: gpt-4-32k - en_US: gpt-4-32k -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 32768 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.06' - output: '0.12' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo-2024-04-09.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo-2024-04-09.yaml deleted file mode 100644 index 0234499164abf4..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo-2024-04-09.yaml +++ /dev/null @@ -1,57 +0,0 @@ -model: gpt-4-turbo-2024-04-09 -label: - zh_Hans: gpt-4-turbo-2024-04-09 - en_US: gpt-4-turbo-2024-04-09 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.01' - output: '0.03' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo-preview.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo-preview.yaml deleted file mode 100644 index 8d29cf0c04a1df..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo-preview.yaml +++ /dev/null @@ -1,56 +0,0 @@ -model: gpt-4-turbo-preview -label: - zh_Hans: gpt-4-turbo-preview - en_US: gpt-4-turbo-preview -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.01' - output: '0.03' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo.yaml deleted file mode 100644 index b25ff6a81269fa..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4-turbo.yaml +++ /dev/null @@ -1,57 +0,0 @@ -model: gpt-4-turbo -label: - zh_Hans: gpt-4-turbo - en_US: gpt-4-turbo -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.01' - output: '0.03' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4-vision-preview.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4-vision-preview.yaml deleted file mode 100644 index 07037c66438dd2..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4-vision-preview.yaml +++ /dev/null @@ -1,54 +0,0 @@ -model: gpt-4-vision-preview -label: - zh_Hans: gpt-4-vision-preview - en_US: gpt-4-vision-preview -model_type: llm -features: - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.01' - output: '0.03' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4.yaml deleted file mode 100644 index f7b5138b7df366..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4.yaml +++ /dev/null @@ -1,56 +0,0 @@ -model: gpt-4 -label: - zh_Hans: gpt-4 - en_US: gpt-4 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '0.03' - output: '0.06' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-05-13.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-05-13.yaml deleted file mode 100644 index b630d6f63075c2..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-05-13.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: gpt-4o-2024-05-13 -label: - zh_Hans: gpt-4o-2024-05-13 - en_US: gpt-4o-2024-05-13 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '5.00' - output: '15.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-08-06.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-08-06.yaml deleted file mode 100644 index 73b7f6970076c0..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-08-06.yaml +++ /dev/null @@ -1,47 +0,0 @@ -model: gpt-4o-2024-08-06 -label: - zh_Hans: gpt-4o-2024-08-06 - en_US: gpt-4o-2024-08-06 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 16384 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object - - json_schema - - name: json_schema - use_template: json_schema -pricing: - input: '2.50' - output: '10.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-mini-2024-07-18.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4o-mini-2024-07-18.yaml deleted file mode 100644 index df38270f79b1c3..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-mini-2024-07-18.yaml +++ /dev/null @@ -1,47 +0,0 @@ -model: gpt-4o-mini-2024-07-18 -label: - zh_Hans: gpt-4o-mini-2024-07-18 - en_US: gpt-4o-mini-2024-07-18 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 16384 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object - - json_schema - - name: json_schema - use_template: json_schema -pricing: - input: '0.15' - output: '0.60' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-mini.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4o-mini.yaml deleted file mode 100644 index 5e3c94fbe255c0..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-mini.yaml +++ /dev/null @@ -1,47 +0,0 @@ -model: gpt-4o-mini -label: - zh_Hans: gpt-4o-mini - en_US: gpt-4o-mini -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 16384 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object - - json_schema - - name: json_schema - use_template: json_schema -pricing: - input: '0.15' - output: '0.60' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/gpt-4o.yaml b/api/core/model_runtime/model_providers/openai/llm/gpt-4o.yaml deleted file mode 100644 index 3090a9e090c2c5..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/gpt-4o.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: gpt-4o -label: - zh_Hans: gpt-4o - en_US: gpt-4o -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '5.00' - output: '15.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/llm.py b/api/core/model_runtime/model_providers/openai/llm/llm.py deleted file mode 100644 index d42fce528a8f30..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/llm.py +++ /dev/null @@ -1,1182 +0,0 @@ -import json -import logging -from collections.abc import Generator -from typing import Optional, Union, cast - -import tiktoken -from openai import OpenAI, Stream -from openai.types import Completion -from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessageToolCall -from openai.types.chat.chat_completion_chunk import ChoiceDeltaFunctionCall, ChoiceDeltaToolCall -from openai.types.chat.chat_completion_message import FunctionCall - -from core.model_runtime.callbacks.base_callback import Callback -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, I18nObject, ModelType, PriceConfig -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.openai._common import _CommonOpenAI - -logger = logging.getLogger(__name__) - -OPENAI_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. -The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - - -{{instructions}} - -""" # noqa: E501 - - -class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel): - """ - Model class for OpenAI large language model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # handle fine tune remote models - base_model = model - if model.startswith("ft:"): - base_model = model.split(":")[1] - - # get model mode - model_mode = self.get_model_mode(base_model, credentials) - - if model_mode == LLMMode.CHAT: - # chat model - return self._chat_generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - else: - # text completion model - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - stop=stop, - stream=stream, - user=user, - ) - - def _code_block_mode_wrapper( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - callbacks: list[Callback] = None, - ) -> Union[LLMResult, Generator]: - """ - Code block mode wrapper for invoking large language model - """ - # handle fine tune remote models - base_model = model - if model.startswith("ft:"): - base_model = model.split(":")[1] - - # get model mode - model_mode = self.get_model_mode(base_model, credentials) - - # transform response format - if "response_format" in model_parameters and model_parameters["response_format"] in {"JSON", "XML"}: - stop = stop or [] - if model_mode == LLMMode.CHAT: - # chat model - self._transform_chat_json_prompts( - model=base_model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - response_format=model_parameters["response_format"], - ) - else: - self._transform_completion_json_prompts( - model=base_model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - response_format=model_parameters["response_format"], - ) - model_parameters.pop("response_format") - - return self._invoke( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def _transform_chat_json_prompts( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - response_format: str = "JSON", - ) -> None: - """ - Transform json prompts - """ - if "```\n" not in stop: - stop.append("```\n") - if "\n```" not in stop: - stop.append("\n```") - - # check if there is a system message - if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): - # override the system message - prompt_messages[0] = SystemPromptMessage( - content=OPENAI_BLOCK_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content).replace( - "{{block}}", response_format - ) - ) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}\n")) - else: - # insert the system message - prompt_messages.insert( - 0, - SystemPromptMessage( - content=OPENAI_BLOCK_MODE_PROMPT.replace( - "{{instructions}}", f"Please output a valid {response_format} object." - ).replace("{{block}}", response_format) - ), - ) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}")) - - def _transform_completion_json_prompts( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - response_format: str = "JSON", - ) -> None: - """ - Transform json prompts - """ - if "```\n" not in stop: - stop.append("```\n") - if "\n```" not in stop: - stop.append("\n```") - - # override the last user message - user_message = None - for i in range(len(prompt_messages) - 1, -1, -1): - if isinstance(prompt_messages[i], UserPromptMessage): - user_message = prompt_messages[i] - break - - if user_message: - if prompt_messages[i].content[-11:] == "Assistant: ": - # now we are in the chat app, remove the last assistant message - prompt_messages[i].content = prompt_messages[i].content[:-11] - prompt_messages[i] = UserPromptMessage( - content=OPENAI_BLOCK_MODE_PROMPT.replace("{{instructions}}", user_message.content).replace( - "{{block}}", response_format - ) - ) - prompt_messages[i].content += f"Assistant:\n```{response_format}\n" - else: - prompt_messages[i] = UserPromptMessage( - content=OPENAI_BLOCK_MODE_PROMPT.replace("{{instructions}}", user_message.content).replace( - "{{block}}", response_format - ) - ) - prompt_messages[i].content += f"\n```{response_format}\n" - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - # handle fine tune remote models - if model.startswith("ft:"): - base_model = model.split(":")[1] - else: - base_model = model - - # get model mode - model_mode = self.get_model_mode(model) - - if model_mode == LLMMode.CHAT: - # chat model - return self._num_tokens_from_messages(base_model, prompt_messages, tools) - else: - # text completion model, do not support tool calling - return self._num_tokens_from_string(base_model, prompt_messages[0].content) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - # handle fine tune remote models - base_model = model - # fine-tuned model name likes ft:gpt-3.5-turbo-0613:personal::xxxxx - if model.startswith("ft:"): - base_model = model.split(":")[1] - - # check if model exists - remote_models = self.remote_models(credentials) - remote_model_map = {model.model: model for model in remote_models} - if model not in remote_model_map: - raise CredentialsValidateFailedError(f"Fine-tuned model {model} not found") - - # get model mode - model_mode = self.get_model_mode(base_model, credentials) - - if model_mode == LLMMode.CHAT: - # chat model - client.chat.completions.create( - messages=[{"role": "user", "content": "ping"}], - model=model, - temperature=0, - max_tokens=20, - stream=False, - ) - else: - # text completion model - client.completions.create( - prompt="ping", - model=model, - temperature=0, - max_tokens=20, - stream=False, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def remote_models(self, credentials: dict) -> list[AIModelEntity]: - """ - Return remote models if credentials are provided. - - :param credentials: provider credentials - :return: - """ - # get predefined models - predefined_models = self.predefined_models() - predefined_models_map = {model.model: model for model in predefined_models} - - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - # get all remote models - remote_models = client.models.list() - - fine_tune_models = [model for model in remote_models if model.id.startswith("ft:")] - - ai_model_entities = [] - for model in fine_tune_models: - base_model = model.id.split(":")[1] - - base_model_schema = None - for predefined_model_name, predefined_model in predefined_models_map.items(): - if predefined_model_name in base_model: - base_model_schema = predefined_model - - if not base_model_schema: - continue - - ai_model_entity = AIModelEntity( - model=model.id, - label=I18nObject(zh_Hans=model.id, en_US=model.id), - model_type=ModelType.LLM, - features=base_model_schema.features, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties=base_model_schema.model_properties, - parameter_rules=base_model_schema.parameter_rules, - pricing=PriceConfig(input=0.003, output=0.006, unit=0.001, currency="USD"), - ) - - ai_model_entities.append(ai_model_entity) - - return ai_model_entities - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke llm completion model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - # init model client - client = OpenAI(**credentials_kwargs) - - extra_model_kwargs = {} - - if stop: - extra_model_kwargs["stop"] = stop - - if user: - extra_model_kwargs["user"] = user - - if stream: - extra_model_kwargs["stream_options"] = {"include_usage": True} - - # text completion model - response = client.completions.create( - prompt=prompt_messages[0].content, model=model, stream=stream, **model_parameters, **extra_model_kwargs - ) - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_response( - self, model: str, credentials: dict, response: Completion, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm completion response - - :param model: model name - :param credentials: model credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm result - """ - assistant_text = response.choices[0].text - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_text) - - # calculate num tokens - if response.usage: - # transform usage - prompt_tokens = response.usage.prompt_tokens - completion_tokens = response.usage.completion_tokens - else: - # calculate num tokens - prompt_tokens = self._num_tokens_from_string(model, prompt_messages[0].content) - completion_tokens = self._num_tokens_from_string(model, assistant_text) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=response.model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - system_fingerprint=response.system_fingerprint, - ) - - return result - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: Stream[Completion], prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm completion stream response - - :param model: model name - :param credentials: model credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - full_text = "" - prompt_tokens = 0 - completion_tokens = 0 - - final_chunk = LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=""), - ), - ) - - for chunk in response: - if len(chunk.choices) == 0: - if chunk.usage: - # calculate num tokens - prompt_tokens = chunk.usage.prompt_tokens - completion_tokens = chunk.usage.completion_tokens - continue - - delta = chunk.choices[0] - - if delta.finish_reason is None and (delta.text is None or delta.text == ""): - continue - - # transform assistant message to prompt message - text = delta.text or "" - assistant_prompt_message = AssistantPromptMessage(content=text) - - full_text += text - - if delta.finish_reason is not None: - final_chunk = LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - ), - ) - else: - yield LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - ), - ) - - if not prompt_tokens: - prompt_tokens = self._num_tokens_from_string(model, prompt_messages[0].content) - - if not completion_tokens: - completion_tokens = self._num_tokens_from_string(model, full_text) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - final_chunk.delta.usage = usage - - yield final_chunk - - def _chat_generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke llm chat model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - # init model client - client = OpenAI(**credentials_kwargs) - - response_format = model_parameters.get("response_format") - if response_format: - if response_format == "json_schema": - json_schema = model_parameters.get("json_schema") - if not json_schema: - raise ValueError("Must define JSON Schema when the response format is json_schema") - try: - schema = json.loads(json_schema) - except: - raise ValueError(f"not correct json_schema format: {json_schema}") - model_parameters.pop("json_schema") - model_parameters["response_format"] = {"type": "json_schema", "json_schema": schema} - else: - model_parameters["response_format"] = {"type": response_format} - - extra_model_kwargs = {} - - if tools: - # extra_model_kwargs['tools'] = [helper.dump_model(PromptMessageFunction(function=tool)) for tool in tools] - extra_model_kwargs["functions"] = [ - {"name": tool.name, "description": tool.description, "parameters": tool.parameters} for tool in tools - ] - - if stop: - extra_model_kwargs["stop"] = stop - - if user: - extra_model_kwargs["user"] = user - - if stream: - extra_model_kwargs["stream_options"] = {"include_usage": True} - - # clear illegal prompt messages - prompt_messages = self._clear_illegal_prompt_messages(model, prompt_messages) - - block_as_stream = False - if model.startswith("o1"): - if stream: - block_as_stream = True - stream = False - - if "stream_options" in extra_model_kwargs: - del extra_model_kwargs["stream_options"] - - if "stop" in extra_model_kwargs: - del extra_model_kwargs["stop"] - - # chat model - response = client.chat.completions.create( - messages=[self._convert_prompt_message_to_dict(m) for m in prompt_messages], - model=model, - stream=stream, - **model_parameters, - **extra_model_kwargs, - ) - - if stream: - return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages, tools) - - block_result = self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools) - - if block_as_stream: - return self._handle_chat_block_as_stream_response(block_result, prompt_messages, stop) - - return block_result - - def _handle_chat_block_as_stream_response( - self, - block_result: LLMResult, - prompt_messages: list[PromptMessage], - stop: Optional[list[str]] = None, - ) -> Generator[LLMResultChunk, None, None]: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :param stop: stop words - :return: llm response chunk generator - """ - text = block_result.message.content - text = cast(str, text) - - if stop: - text = self.enforce_stop_tokens(text, stop) - - yield LLMResultChunk( - model=block_result.model, - prompt_messages=prompt_messages, - system_fingerprint=block_result.system_fingerprint, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=text), - finish_reason="stop", - usage=block_result.usage, - ), - ) - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - response: ChatCompletion, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response - """ - assistant_message = response.choices[0].message - # assistant_message_tool_calls = assistant_message.tool_calls - assistant_message_function_call = assistant_message.function_call - - # extract tool calls from response - # tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - function_call = self._extract_response_function_call(assistant_message_function_call) - tool_calls = [function_call] if function_call else [] - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_message.content, tool_calls=tool_calls) - - # calculate num tokens - if response.usage: - # transform usage - prompt_tokens = response.usage.prompt_tokens - completion_tokens = response.usage.completion_tokens - else: - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(model, prompt_messages, tools) - completion_tokens = self._num_tokens_from_messages(model, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - response = LLMResult( - model=response.model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - system_fingerprint=response.system_fingerprint, - ) - - return response - - def _handle_chat_generate_stream_response( - self, - model: str, - credentials: dict, - response: Stream[ChatCompletionChunk], - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> Generator: - """ - Handle llm chat stream response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response chunk generator - """ - full_assistant_content = "" - delta_assistant_message_function_call_storage: ChoiceDeltaFunctionCall = None - prompt_tokens = 0 - completion_tokens = 0 - final_tool_calls = [] - final_chunk = LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=""), - ), - ) - - for chunk in response: - if len(chunk.choices) == 0: - if chunk.usage: - # calculate num tokens - prompt_tokens = chunk.usage.prompt_tokens - completion_tokens = chunk.usage.completion_tokens - continue - - delta = chunk.choices[0] - has_finish_reason = delta.finish_reason is not None - - if ( - not has_finish_reason - and (delta.delta.content is None or delta.delta.content == "") - and delta.delta.function_call is None - ): - continue - - # assistant_message_tool_calls = delta.delta.tool_calls - assistant_message_function_call = delta.delta.function_call - - # extract tool calls from response - if delta_assistant_message_function_call_storage is not None: - # handle process of stream function call - if assistant_message_function_call: - # message has not ended ever - delta_assistant_message_function_call_storage.arguments += assistant_message_function_call.arguments - continue - else: - # message has ended - assistant_message_function_call = delta_assistant_message_function_call_storage - delta_assistant_message_function_call_storage = None - else: - if assistant_message_function_call: - # start of stream function call - delta_assistant_message_function_call_storage = assistant_message_function_call - if delta_assistant_message_function_call_storage.arguments is None: - delta_assistant_message_function_call_storage.arguments = "" - if not has_finish_reason: - continue - - # tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - function_call = self._extract_response_function_call(assistant_message_function_call) - tool_calls = [function_call] if function_call else [] - if tool_calls: - final_tool_calls.extend(tool_calls) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=delta.delta.content or "", tool_calls=tool_calls) - - full_assistant_content += delta.delta.content or "" - - if has_finish_reason: - final_chunk = LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - ), - ) - else: - yield LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - ), - ) - - if not prompt_tokens: - prompt_tokens = self._num_tokens_from_messages(model, prompt_messages, tools) - - if not completion_tokens: - full_assistant_prompt_message = AssistantPromptMessage( - content=full_assistant_content, tool_calls=final_tool_calls - ) - completion_tokens = self._num_tokens_from_messages(model, [full_assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - final_chunk.delta.usage = usage - - yield final_chunk - - def _extract_response_tool_calls( - self, response_tool_calls: list[ChatCompletionMessageToolCall | ChoiceDeltaToolCall] - ) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_tool_calls: - for response_tool_call in response_tool_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.function.name, arguments=response_tool_call.function.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call.id, type=response_tool_call.type, function=function - ) - tool_calls.append(tool_call) - - return tool_calls - - def _extract_response_function_call( - self, response_function_call: FunctionCall | ChoiceDeltaFunctionCall - ) -> AssistantPromptMessage.ToolCall: - """ - Extract function call from response - - :param response_function_call: response function call - :return: tool call - """ - tool_call = None - if response_function_call: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_function_call.name, arguments=response_function_call.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_function_call.name, type="function", function=function - ) - - return tool_call - - def _clear_illegal_prompt_messages(self, model: str, prompt_messages: list[PromptMessage]) -> list[PromptMessage]: - """ - Clear illegal prompt messages for OpenAI API - - :param model: model name - :param prompt_messages: prompt messages - :return: cleaned prompt messages - """ - checklist = ["gpt-4-turbo", "gpt-4-turbo-2024-04-09"] - - if model in checklist: - # count how many user messages are there - user_message_count = len([m for m in prompt_messages if isinstance(m, UserPromptMessage)]) - if user_message_count > 1: - for prompt_message in prompt_messages: - if isinstance(prompt_message, UserPromptMessage): - if isinstance(prompt_message.content, list): - prompt_message.content = "\n".join( - [ - item.data - if item.type == PromptMessageContentType.TEXT - else "[IMAGE]" - if item.type == PromptMessageContentType.IMAGE - else "" - for item in prompt_message.content - ] - ) - - if model.startswith("o1"): - system_message_count = len([m for m in prompt_messages if isinstance(m, SystemPromptMessage)]) - if system_message_count > 0: - new_prompt_messages = [] - for prompt_message in prompt_messages: - if isinstance(prompt_message, SystemPromptMessage): - prompt_message = UserPromptMessage( - content=prompt_message.content, - name=prompt_message.name, - ) - - new_prompt_messages.append(prompt_message) - prompt_messages = new_prompt_messages - - return prompt_messages - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for OpenAI API - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": {"url": message_content.data, "detail": message_content.detail.value}, - } - sub_messages.append(sub_message_dict) - - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls: - # message_dict["tool_calls"] = [tool_call.dict() for tool_call in - # message.tool_calls] - function_call = message.tool_calls[0] - message_dict["function_call"] = { - "name": function_call.function.name, - "arguments": function_call.function.arguments, - } - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - # message_dict = { - # "role": "tool", - # "content": message.content, - # "tool_call_id": message.tool_call_id - # } - message_dict = {"role": "function", "content": message.content, "name": message.tool_call_id} - else: - raise ValueError(f"Got unknown type {message}") - - if message.name: - message_dict["name"] = message.name - - return message_dict - - def _num_tokens_from_string(self, model: str, text: str, tools: Optional[list[PromptMessageTool]] = None) -> int: - """ - Calculate num tokens for text completion model with tiktoken package. - - :param model: model name - :param text: prompt text - :param tools: tools for tool calling - :return: number of tokens - """ - try: - encoding = tiktoken.encoding_for_model(model) - except KeyError: - encoding = tiktoken.get_encoding("cl100k_base") - - num_tokens = len(encoding.encode(text)) - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - def _num_tokens_from_messages( - self, model: str, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None - ) -> int: - """Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package. - - Official documentation: https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb""" - if model.startswith("ft:"): - model = model.split(":")[1] - - # Currently, we can use gpt4o to calculate chatgpt-4o-latest's token. - if model == "chatgpt-4o-latest" or model.startswith("o1"): - model = "gpt-4o" - - try: - encoding = tiktoken.encoding_for_model(model) - except KeyError: - logger.warning("Warning: model not found. Using cl100k_base encoding.") - model = "cl100k_base" - encoding = tiktoken.get_encoding(model) - - if model.startswith("gpt-3.5-turbo-0301"): - # every message follows {role/name}\n{content}\n - tokens_per_message = 4 - # if there's a name, the role is omitted - tokens_per_name = -1 - elif model.startswith("gpt-3.5-turbo") or model.startswith("gpt-4") or model.startswith("o1"): - tokens_per_message = 3 - tokens_per_name = 1 - else: - raise NotImplementedError( - f"get_num_tokens_from_messages() is not presently implemented " - f"for model {model}." - "See https://platform.openai.com/docs/advanced-usage/managing-tokens for " - "information on how messages are converted to tokens." - ) - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - # Cast str(value) in case the message value is not a string - # This occurs with function messages - # TODO: The current token calculation method for the image type is not implemented, - # which need to download the image and then get the resolution for calculation, - # and will increase the request delay - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += len(encoding.encode(t_key)) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += len(encoding.encode(f_key)) - num_tokens += len(encoding.encode(f_value)) - else: - num_tokens += len(encoding.encode(t_key)) - num_tokens += len(encoding.encode(t_value)) - else: - num_tokens += len(encoding.encode(str(value))) - - if key == "name": - num_tokens += tokens_per_name - - # every reply is primed with assistant - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - def _num_tokens_for_tools(self, encoding: tiktoken.Encoding, tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for tool calling with tiktoken package. - - :param encoding: encoding - :param tools: tools for tool calling - :return: number of tokens - """ - num_tokens = 0 - for tool in tools: - num_tokens += len(encoding.encode("type")) - num_tokens += len(encoding.encode("function")) - - # calculate num tokens for function object - num_tokens += len(encoding.encode("name")) - num_tokens += len(encoding.encode(tool.name)) - num_tokens += len(encoding.encode("description")) - num_tokens += len(encoding.encode(tool.description)) - parameters = tool.parameters - num_tokens += len(encoding.encode("parameters")) - if "title" in parameters: - num_tokens += len(encoding.encode("title")) - num_tokens += len(encoding.encode(parameters.get("title"))) - num_tokens += len(encoding.encode("type")) - num_tokens += len(encoding.encode(parameters.get("type"))) - if "properties" in parameters: - num_tokens += len(encoding.encode("properties")) - for key, value in parameters.get("properties").items(): - num_tokens += len(encoding.encode(key)) - for field_key, field_value in value.items(): - num_tokens += len(encoding.encode(field_key)) - if field_key == "enum": - for enum_field in field_value: - num_tokens += 3 - num_tokens += len(encoding.encode(enum_field)) - else: - num_tokens += len(encoding.encode(field_key)) - num_tokens += len(encoding.encode(str(field_value))) - if "required" in parameters: - num_tokens += len(encoding.encode("required")) - for required_field in parameters["required"]: - num_tokens += 3 - num_tokens += len(encoding.encode(required_field)) - - return num_tokens - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - OpenAI supports fine-tuning of their models. This method returns the schema of the base model - but renamed to the fine-tuned model name. - - :param model: model name - :param credentials: credentials - - :return: model schema - """ - if not model.startswith("ft:"): - base_model = model - else: - # get base_model - base_model = model.split(":")[1] - - # get model schema - models = self.predefined_models() - model_map = {model.model: model for model in models} - if base_model not in model_map: - raise ValueError(f"Base model {base_model} not found") - - base_model_schema = model_map[base_model] - - base_model_schema_features = base_model_schema.features or [] - base_model_schema_model_properties = base_model_schema.model_properties or {} - base_model_schema_parameters_rules = base_model_schema.parameter_rules or [] - - entity = AIModelEntity( - model=model, - label=I18nObject(zh_Hans=model, en_US=model), - model_type=ModelType.LLM, - features=list(base_model_schema_features), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties=dict(base_model_schema_model_properties.items()), - parameter_rules=list(base_model_schema_parameters_rules), - pricing=base_model_schema.pricing, - ) - - return entity diff --git a/api/core/model_runtime/model_providers/openai/llm/o1-mini-2024-09-12.yaml b/api/core/model_runtime/model_providers/openai/llm/o1-mini-2024-09-12.yaml deleted file mode 100644 index 0ade7f8ded9d4b..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/o1-mini-2024-09-12.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: o1-mini-2024-09-12 -label: - zh_Hans: o1-mini-2024-09-12 - en_US: o1-mini-2024-09-12 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - default: 65536 - min: 1 - max: 65536 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: response_format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '3.00' - output: '12.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/o1-mini.yaml b/api/core/model_runtime/model_providers/openai/llm/o1-mini.yaml deleted file mode 100644 index 60816c5d1e4d93..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/o1-mini.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: o1-mini -label: - zh_Hans: o1-mini - en_US: o1-mini -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - default: 65536 - min: 1 - max: 65536 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: response_format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '3.00' - output: '12.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/o1-preview-2024-09-12.yaml b/api/core/model_runtime/model_providers/openai/llm/o1-preview-2024-09-12.yaml deleted file mode 100644 index c9da96f611bc91..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/o1-preview-2024-09-12.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: o1-preview-2024-09-12 -label: - zh_Hans: o1-preview-2024-09-12 - en_US: o1-preview-2024-09-12 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - default: 32768 - min: 1 - max: 32768 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: response_format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '15.00' - output: '60.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/o1-preview.yaml b/api/core/model_runtime/model_providers/openai/llm/o1-preview.yaml deleted file mode 100644 index c83874b76582e8..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/o1-preview.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: o1-preview -label: - zh_Hans: o1-preview - en_US: o1-preview -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - default: 32768 - min: 1 - max: 32768 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: response_format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '15.00' - output: '60.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/llm/text-davinci-003.yaml b/api/core/model_runtime/model_providers/openai/llm/text-davinci-003.yaml deleted file mode 100644 index 76b5d848753da5..00000000000000 --- a/api/core/model_runtime/model_providers/openai/llm/text-davinci-003.yaml +++ /dev/null @@ -1,29 +0,0 @@ -model: text-davinci-003 -label: - zh_Hans: text-davinci-003 - en_US: text-davinci-003 -model_type: llm -features: [ ] -model_properties: - mode: completion - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 -pricing: - input: '0.001' - output: '0.002' - unit: '0.001' - currency: USD -deprecated: true diff --git a/api/core/model_runtime/model_providers/openai/moderation/moderation.py b/api/core/model_runtime/model_providers/openai/moderation/moderation.py index 619044d808cdf6..a83248c0c25b41 100644 --- a/api/core/model_runtime/model_providers/openai/moderation/moderation.py +++ b/api/core/model_runtime/model_providers/openai/moderation/moderation.py @@ -1,15 +1,25 @@ +from collections.abc import Mapping from typing import Optional +import openai +from httpx import Timeout from openai import OpenAI from openai.types import ModerationCreateResponse from core.model_runtime.entities.model_entities import ModelPropertyKey +from core.model_runtime.errors.invoke import ( + InvokeAuthorizationError, + InvokeBadRequestError, + InvokeConnectionError, + InvokeError, + InvokeRateLimitError, + InvokeServerUnavailableError, +) from core.model_runtime.errors.validate import CredentialsValidateFailedError from core.model_runtime.model_providers.__base.moderation_model import ModerationModel -from core.model_runtime.model_providers.openai._common import _CommonOpenAI -class OpenAIModerationModel(_CommonOpenAI, ModerationModel): +class OpenAIModerationModel(ModerationModel): """ Model class for OpenAI text moderation model. """ @@ -111,3 +121,48 @@ def _get_max_chunks(self, model: str, credentials: dict) -> int: return model_schema.model_properties[ModelPropertyKey.MAX_CHUNKS] return 1 + + def _to_credential_kwargs(self, credentials: Mapping) -> dict: + """ + Transform credentials to kwargs for model instance + + :param credentials: + :return: + """ + credentials_kwargs = { + "api_key": credentials["openai_api_key"], + "timeout": Timeout(315.0, read=300.0, write=10.0, connect=5.0), + "max_retries": 1, + } + + if credentials.get("openai_api_base"): + openai_api_base = credentials["openai_api_base"].rstrip("/") + credentials_kwargs["base_url"] = openai_api_base + "/v1" + + if "openai_organization" in credentials: + credentials_kwargs["organization"] = credentials["openai_organization"] + + return credentials_kwargs + + @property + def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: + """ + Map model invoke error to unified error + The key is the error type thrown to the caller + The value is the error type thrown by the model, + which needs to be converted into a unified error type for the caller. + + :return: Invoke error mapping + """ + return { + InvokeConnectionError: [openai.APIConnectionError, openai.APITimeoutError], + InvokeServerUnavailableError: [openai.InternalServerError], + InvokeRateLimitError: [openai.RateLimitError], + InvokeAuthorizationError: [openai.AuthenticationError, openai.PermissionDeniedError], + InvokeBadRequestError: [ + openai.BadRequestError, + openai.NotFoundError, + openai.UnprocessableEntityError, + openai.APIError, + ], + } diff --git a/api/core/model_runtime/model_providers/openai/moderation/text-moderation-stable.yaml b/api/core/model_runtime/model_providers/openai/moderation/text-moderation-stable.yaml deleted file mode 100644 index 5ca180916782d9..00000000000000 --- a/api/core/model_runtime/model_providers/openai/moderation/text-moderation-stable.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: text-moderation-stable -model_type: moderation -model_properties: - max_chunks: 32 - max_characters_per_chunk: 2000 diff --git a/api/core/model_runtime/model_providers/openai/openai.py b/api/core/model_runtime/model_providers/openai/openai.py deleted file mode 100644 index 175d7db73c46d4..00000000000000 --- a/api/core/model_runtime/model_providers/openai/openai.py +++ /dev/null @@ -1,29 +0,0 @@ -import logging -from collections.abc import Mapping - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class OpenAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: Mapping) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `gpt-3.5-turbo` model for validate, - # no matter what model you pass in, text completion model or chat model - model_instance.validate_credentials(model="gpt-3.5-turbo", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/openai/openai.yaml b/api/core/model_runtime/model_providers/openai/openai.yaml deleted file mode 100644 index b4dc8fd4f2dfad..00000000000000 --- a/api/core/model_runtime/model_providers/openai/openai.yaml +++ /dev/null @@ -1,89 +0,0 @@ -provider: openai -label: - en_US: OpenAI -description: - en_US: Models provided by OpenAI, such as GPT-3.5-Turbo and GPT-4. - zh_Hans: OpenAI 提供的模型，例如 GPT-3.5-Turbo 和 GPT-4。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#E5E7EB" -help: - title: - en_US: Get your API Key from OpenAI - zh_Hans: 从 OpenAI 获取 API Key - url: - en_US: https://platform.openai.com/account/api-keys -supported_model_types: - - llm - - text-embedding - - speech2text - - moderation - - tts -configurate_methods: - - predefined-model - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: openai_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: openai_organization - label: - zh_Hans: 组织 ID - en_US: Organization - type: text-input - required: false - placeholder: - zh_Hans: 在此输入您的组织 ID - en_US: Enter your Organization ID - - variable: openai_api_base - label: - zh_Hans: API Base - en_US: API Base - type: text-input - required: false - placeholder: - zh_Hans: 在此输入您的 API Base - en_US: Enter your API Base -provider_credential_schema: - credential_form_schemas: - - variable: openai_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: openai_organization - label: - zh_Hans: 组织 ID - en_US: Organization - type: text-input - required: false - placeholder: - zh_Hans: 在此输入您的组织 ID - en_US: Enter your Organization ID - - variable: openai_api_base - label: - zh_Hans: API Base - en_US: API Base - type: text-input - required: false - placeholder: - zh_Hans: 在此输入您的 API Base, 如：https://api.openai.com - en_US: Enter your API Base, e.g. https://api.openai.com diff --git a/api/core/model_runtime/model_providers/openai/speech2text/__init__.py b/api/core/model_runtime/model_providers/openai/speech2text/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai/speech2text/speech2text.py b/api/core/model_runtime/model_providers/openai/speech2text/speech2text.py deleted file mode 100644 index 18f97e45f33bd8..00000000000000 --- a/api/core/model_runtime/model_providers/openai/speech2text/speech2text.py +++ /dev/null @@ -1,60 +0,0 @@ -from typing import IO, Optional - -from openai import OpenAI - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel -from core.model_runtime.model_providers.openai._common import _CommonOpenAI - - -class OpenAISpeech2TextModel(_CommonOpenAI, Speech2TextModel): - """ - Model class for OpenAI Speech to text model. - """ - - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - return self._speech2text_invoke(model, credentials, file) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - audio_file_path = self._get_demo_file_path() - - with open(audio_file_path, "rb") as audio_file: - self._speech2text_invoke(model, credentials, audio_file) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _speech2text_invoke(self, model: str, credentials: dict, file: IO[bytes]) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :return: text for given audio file - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - # init model client - client = OpenAI(**credentials_kwargs) - - response = client.audio.transcriptions.create(model=model, file=file) - - return response.text diff --git a/api/core/model_runtime/model_providers/openai/speech2text/whisper-1.yaml b/api/core/model_runtime/model_providers/openai/speech2text/whisper-1.yaml deleted file mode 100644 index 6c14c766192d6b..00000000000000 --- a/api/core/model_runtime/model_providers/openai/speech2text/whisper-1.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: whisper-1 -model_type: speech2text -model_properties: - file_upload_limit: 25 - supported_file_extensions: flac,mp3,mp4,mpeg,mpga,m4a,ogg,wav,webm diff --git a/api/core/model_runtime/model_providers/openai/text_embedding/__init__.py b/api/core/model_runtime/model_providers/openai/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-3-large.yaml b/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-3-large.yaml deleted file mode 100644 index 9489170fdea0b4..00000000000000 --- a/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-3-large.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: text-embedding-3-large -model_type: text-embedding -model_properties: - context_size: 8191 - max_chunks: 32 -pricing: - input: '0.00013' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-3-small.yaml b/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-3-small.yaml deleted file mode 100644 index 586ba2b28f9041..00000000000000 --- a/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-3-small.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: text-embedding-3-small -model_type: text-embedding -model_properties: - context_size: 8191 - max_chunks: 32 -pricing: - input: '0.00002' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-ada-002.yaml b/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-ada-002.yaml deleted file mode 100644 index ef1c49b017dc34..00000000000000 --- a/api/core/model_runtime/model_providers/openai/text_embedding/text-embedding-ada-002.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: text-embedding-ada-002 -model_type: text-embedding -model_properties: - context_size: 8097 - max_chunks: 32 -pricing: - input: '0.0001' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/tts/__init__.py b/api/core/model_runtime/model_providers/openai/tts/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai/tts/tts-1-hd.yaml b/api/core/model_runtime/model_providers/openai/tts/tts-1-hd.yaml deleted file mode 100644 index 449c131f9d10f9..00000000000000 --- a/api/core/model_runtime/model_providers/openai/tts/tts-1-hd.yaml +++ /dev/null @@ -1,31 +0,0 @@ -model: tts-1-hd -model_type: tts -model_properties: - default_voice: 'alloy' - voices: - - mode: 'alloy' - name: 'Alloy' - language: [ 'zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID' ] - - mode: 'echo' - name: 'Echo' - language: [ 'zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID' ] - - mode: 'fable' - name: 'Fable' - language: [ 'zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID' ] - - mode: 'onyx' - name: 'Onyx' - language: [ 'zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID' ] - - mode: 'nova' - name: 'Nova' - language: [ 'zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID' ] - - mode: 'shimmer' - name: 'Shimmer' - language: [ 'zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID' ] - word_limit: 3500 - audio_type: 'mp3' - max_workers: 5 -pricing: - input: '0.03' - output: '0' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/tts/tts-1.yaml b/api/core/model_runtime/model_providers/openai/tts/tts-1.yaml deleted file mode 100644 index 83969fb2f7a129..00000000000000 --- a/api/core/model_runtime/model_providers/openai/tts/tts-1.yaml +++ /dev/null @@ -1,31 +0,0 @@ -model: tts-1 -model_type: tts -model_properties: - default_voice: 'alloy' - voices: - - mode: 'alloy' - name: 'Alloy' - language: ['zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID'] - - mode: 'echo' - name: 'Echo' - language: ['zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID'] - - mode: 'fable' - name: 'Fable' - language: ['zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID'] - - mode: 'onyx' - name: 'Onyx' - language: ['zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID'] - - mode: 'nova' - name: 'Nova' - language: ['zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID'] - - mode: 'shimmer' - name: 'Shimmer' - language: ['zh-Hans', 'en-US', 'de-DE', 'fr-FR', 'es-ES', 'it-IT', 'th-TH', 'id-ID'] - word_limit: 3500 - audio_type: 'mp3' - max_workers: 5 -pricing: - input: '0.015' - output: '0' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openai/tts/tts.py b/api/core/model_runtime/model_providers/openai/tts/tts.py deleted file mode 100644 index a14c91639b88fc..00000000000000 --- a/api/core/model_runtime/model_providers/openai/tts/tts.py +++ /dev/null @@ -1,118 +0,0 @@ -import concurrent.futures -from typing import Optional - -from openai import OpenAI - -from core.model_runtime.errors.invoke import InvokeBadRequestError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.tts_model import TTSModel -from core.model_runtime.model_providers.openai._common import _CommonOpenAI - - -class OpenAIText2SpeechModel(_CommonOpenAI, TTSModel): - """ - Model class for OpenAI Speech to text model. - """ - - def _invoke( - self, model: str, tenant_id: str, credentials: dict, content_text: str, voice: str, user: Optional[str] = None - ) -> any: - """ - _invoke text2speech model - - :param model: model name - :param tenant_id: user tenant id - :param credentials: model credentials - :param content_text: text content to be translated - :param voice: model timbre - :param user: unique user id - :return: text translated to audio file - """ - - if not voice or voice not in [ - d["value"] for d in self.get_tts_model_voices(model=model, credentials=credentials) - ]: - voice = self._get_model_default_voice(model, credentials) - # if streaming: - return self._tts_invoke_streaming(model=model, credentials=credentials, content_text=content_text, voice=voice) - - def validate_credentials(self, model: str, credentials: dict, user: Optional[str] = None) -> None: - """ - validate credentials text2speech model - - :param model: model name - :param credentials: model credentials - :param user: unique user id - :return: text translated to audio file - """ - try: - self._tts_invoke_streaming( - model=model, - credentials=credentials, - content_text="Hello Dify!", - voice=self._get_model_default_voice(model, credentials), - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _tts_invoke_streaming(self, model: str, credentials: dict, content_text: str, voice: str) -> any: - """ - _tts_invoke_streaming text2speech model - - :param model: model name - :param credentials: model credentials - :param content_text: text content to be translated - :param voice: model timbre - :return: text translated to audio file - """ - try: - # doc: https://platform.openai.com/docs/guides/text-to-speech - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - model_support_voice = [ - x.get("value") for x in self.get_tts_model_voices(model=model, credentials=credentials) - ] - if not voice or voice not in model_support_voice: - voice = self._get_model_default_voice(model, credentials) - word_limit = self._get_model_word_limit(model, credentials) - if len(content_text) > word_limit: - sentences = self._split_text_into_sentences(content_text, max_length=word_limit) - executor = concurrent.futures.ThreadPoolExecutor(max_workers=min(3, len(sentences))) - futures = [ - executor.submit( - client.audio.speech.with_streaming_response.create, - model=model, - response_format="mp3", - input=sentences[i], - voice=voice, - ) - for i in range(len(sentences)) - ] - for future in futures: - yield from future.result().__enter__().iter_bytes(1024) # noqa:PLC2801 - - else: - response = client.audio.speech.with_streaming_response.create( - model=model, voice=voice, response_format="mp3", input=content_text.strip() - ) - - yield from response.__enter__().iter_bytes(1024) # noqa:PLC2801 - except Exception as ex: - raise InvokeBadRequestError(str(ex)) - - def _process_sentence(self, sentence: str, model: str, voice, credentials: dict): - """ - _tts_invoke openai text2speech model api - - :param model: model name - :param credentials: model credentials - :param voice: model timbre - :param sentence: text content to be translated - :return: text translated to audio file - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - response = client.audio.speech.create(model=model, voice=voice, input=sentence.strip()) - if isinstance(response.read(), bytes): - return response.read() diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/__init__.py b/api/core/model_runtime/model_providers/openai_api_compatible/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/_common.py b/api/core/model_runtime/model_providers/openai_api_compatible/_common.py deleted file mode 100644 index 1234e44f80c40c..00000000000000 --- a/api/core/model_runtime/model_providers/openai_api_compatible/_common.py +++ /dev/null @@ -1,43 +0,0 @@ -import requests - -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) - - -class _CommonOaiApiCompat: - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeAuthorizationError: [ - requests.exceptions.InvalidHeader, # Missing or Invalid API Key - ], - InvokeBadRequestError: [ - requests.exceptions.HTTPError, # Invalid Endpoint URL or model name - requests.exceptions.InvalidURL, # Misconfigured request or other API error - ], - InvokeRateLimitError: [ - requests.exceptions.RetryError # Too many requests sent in a short period of time - ], - InvokeServerUnavailableError: [ - requests.exceptions.ConnectionError, # Engine Overloaded - requests.exceptions.HTTPError, # Server Error - ], - InvokeConnectionError: [ - requests.exceptions.ConnectTimeout, # Timeout - requests.exceptions.ReadTimeout, # Timeout - ], - } diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/llm/__init__.py b/api/core/model_runtime/model_providers/openai_api_compatible/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/llm/llm.py b/api/core/model_runtime/model_providers/openai_api_compatible/llm/llm.py deleted file mode 100644 index c2ffe653c8b70a..00000000000000 --- a/api/core/model_runtime/model_providers/openai_api_compatible/llm/llm.py +++ /dev/null @@ -1,828 +0,0 @@ -import json -import logging -from collections.abc import Generator -from decimal import Decimal -from typing import Optional, Union, cast -from urllib.parse import urljoin - -import requests - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContent, - PromptMessageContentType, - PromptMessageFunction, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - DefaultParameterName, - FetchFrom, - ModelFeature, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, - PriceConfig, -) -from core.model_runtime.errors.invoke import InvokeError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.openai_api_compatible._common import _CommonOaiApiCompat -from core.model_runtime.utils import helper - -logger = logging.getLogger(__name__) - - -class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel): - """ - Model class for OpenAI large language model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - - # text completion model - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: - :param credentials: - :param prompt_messages: - :param tools: tools for tool calling - :return: - """ - return self._num_tokens_from_messages(model, prompt_messages, tools, credentials) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials using requests to ensure compatibility with all providers following - OpenAI's API standard. - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - headers = {"Content-Type": "application/json"} - - api_key = credentials.get("api_key") - if api_key: - headers["Authorization"] = f"Bearer {api_key}" - - endpoint_url = credentials["endpoint_url"] - if not endpoint_url.endswith("/"): - endpoint_url += "/" - - # prepare the payload for a simple ping to the model - data = {"model": model, "max_tokens": 5} - - completion_type = LLMMode.value_of(credentials["mode"]) - - if completion_type is LLMMode.CHAT: - data["messages"] = [ - {"role": "user", "content": "ping"}, - ] - endpoint_url = urljoin(endpoint_url, "chat/completions") - elif completion_type is LLMMode.COMPLETION: - data["prompt"] = "ping" - endpoint_url = urljoin(endpoint_url, "completions") - else: - raise ValueError("Unsupported completion type for model configuration.") - - # send a post request to validate the credentials - response = requests.post(endpoint_url, headers=headers, json=data, timeout=(10, 300)) - - if response.status_code != 200: - raise CredentialsValidateFailedError( - f"Credentials validation failed with status code {response.status_code}" - ) - - try: - json_result = response.json() - except json.JSONDecodeError as e: - raise CredentialsValidateFailedError("Credentials validation failed: JSON decode error") - - if completion_type is LLMMode.CHAT and json_result.get("object", "") == "": - json_result["object"] = "chat.completion" - elif completion_type is LLMMode.COMPLETION and json_result.get("object", "") == "": - json_result["object"] = "text_completion" - - if completion_type is LLMMode.CHAT and ( - "object" not in json_result or json_result["object"] != "chat.completion" - ): - raise CredentialsValidateFailedError( - "Credentials validation failed: invalid response object, must be 'chat.completion'" - ) - elif completion_type is LLMMode.COMPLETION and ( - "object" not in json_result or json_result["object"] != "text_completion" - ): - raise CredentialsValidateFailedError( - "Credentials validation failed: invalid response object, must be 'text_completion'" - ) - except CredentialsValidateFailedError: - raise - except Exception as ex: - raise CredentialsValidateFailedError(f"An error occurred during credentials validation: {str(ex)}") - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - features = [] - - function_calling_type = credentials.get("function_calling_type", "no_call") - if function_calling_type == "function_call": - features.append(ModelFeature.TOOL_CALL) - elif function_calling_type == "tool_call": - features.append(ModelFeature.MULTI_TOOL_CALL) - - stream_function_calling = credentials.get("stream_function_calling", "supported") - if stream_function_calling == "supported": - features.append(ModelFeature.STREAM_TOOL_CALL) - - vision_support = credentials.get("vision_support", "not_support") - if vision_support == "support": - features.append(ModelFeature.VISION) - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.LLM, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - features=features, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", "4096")), - ModelPropertyKey.MODE: credentials.get("mode"), - }, - parameter_rules=[ - ParameterRule( - name=DefaultParameterName.TEMPERATURE.value, - label=I18nObject(en_US="Temperature", zh_Hans="温度"), - help=I18nObject( - en_US="Kernel sampling threshold. Used to determine the randomness of the results." - "The higher the value, the stronger the randomness." - "The higher the possibility of getting different answers to the same question.", - zh_Hans="核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。", - ), - type=ParameterType.FLOAT, - default=float(credentials.get("temperature", 0.7)), - min=0, - max=2, - precision=2, - ), - ParameterRule( - name=DefaultParameterName.TOP_P.value, - label=I18nObject(en_US="Top P", zh_Hans="Top P"), - help=I18nObject( - en_US="The probability threshold of the nucleus sampling method during the generation process." - "The larger the value is, the higher the randomness of generation will be." - "The smaller the value is, the higher the certainty of generation will be.", - zh_Hans="生成过程中核采样方法概率阈值。取值越大，生成的随机性越高；取值越小，生成的确定性越高。", - ), - type=ParameterType.FLOAT, - default=float(credentials.get("top_p", 1)), - min=0, - max=1, - precision=2, - ), - ParameterRule( - name=DefaultParameterName.FREQUENCY_PENALTY.value, - label=I18nObject(en_US="Frequency Penalty", zh_Hans="频率惩罚"), - help=I18nObject( - en_US="For controlling the repetition rate of words used by the model." - "Increasing this can reduce the repetition of the same words in the model's output.", - zh_Hans="用于控制模型已使用字词的重复率。 提高此项可以降低模型在输出中重复相同字词的重复度。", - ), - type=ParameterType.FLOAT, - default=float(credentials.get("frequency_penalty", 0)), - min=-2, - max=2, - ), - ParameterRule( - name=DefaultParameterName.PRESENCE_PENALTY.value, - label=I18nObject(en_US="Presence Penalty", zh_Hans="存在惩罚"), - help=I18nObject( - en_US="Used to control the repetition rate when generating models." - "Increasing this can reduce the repetition rate of model generation.", - zh_Hans="用于控制模型生成时的重复度。提高此项可以降低模型生成的重复度。", - ), - type=ParameterType.FLOAT, - default=float(credentials.get("presence_penalty", 0)), - min=-2, - max=2, - ), - ParameterRule( - name=DefaultParameterName.MAX_TOKENS.value, - label=I18nObject(en_US="Max Tokens", zh_Hans="最大标记"), - help=I18nObject( - en_US="Maximum length of tokens for the model response.", zh_Hans="模型回答的tokens的最大长度。" - ), - type=ParameterType.INT, - default=512, - min=1, - max=int(credentials.get("max_tokens_to_sample", 4096)), - ), - ], - pricing=PriceConfig( - input=Decimal(credentials.get("input_price", 0)), - output=Decimal(credentials.get("output_price", 0)), - unit=Decimal(credentials.get("unit", 0)), - currency=credentials.get("currency", "USD"), - ), - ) - - if credentials["mode"] == "chat": - entity.model_properties[ModelPropertyKey.MODE] = LLMMode.CHAT.value - elif credentials["mode"] == "completion": - entity.model_properties[ModelPropertyKey.MODE] = LLMMode.COMPLETION.value - else: - raise ValueError(f"Unknown completion type {credentials['completion_type']}") - - return entity - - # validate_credentials method has been rewritten to use the requests library for compatibility with all providers - # following OpenAI's API standard. - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke llm completion model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - headers = { - "Content-Type": "application/json", - "Accept-Charset": "utf-8", - } - extra_headers = credentials.get("extra_headers") - if extra_headers is not None: - headers = { - **headers, - **extra_headers, - } - - api_key = credentials.get("api_key") - if api_key: - headers["Authorization"] = f"Bearer {api_key}" - - endpoint_url = credentials["endpoint_url"] - if not endpoint_url.endswith("/"): - endpoint_url += "/" - - data = {"model": model, "stream": stream, **model_parameters} - - completion_type = LLMMode.value_of(credentials["mode"]) - - if completion_type is LLMMode.CHAT: - endpoint_url = urljoin(endpoint_url, "chat/completions") - data["messages"] = [self._convert_prompt_message_to_dict(m, credentials) for m in prompt_messages] - elif completion_type is LLMMode.COMPLETION: - endpoint_url = urljoin(endpoint_url, "completions") - data["prompt"] = prompt_messages[0].content - else: - raise ValueError("Unsupported completion type for model configuration.") - - # annotate tools with names, descriptions, etc. - function_calling_type = credentials.get("function_calling_type", "no_call") - formatted_tools = [] - if tools: - if function_calling_type == "function_call": - data["functions"] = [ - {"name": tool.name, "description": tool.description, "parameters": tool.parameters} - for tool in tools - ] - elif function_calling_type == "tool_call": - data["tool_choice"] = "auto" - - for tool in tools: - formatted_tools.append(helper.dump_model(PromptMessageFunction(function=tool))) - - data["tools"] = formatted_tools - - if stop: - data["stop"] = stop - - if user: - data["user"] = user - - response = requests.post(endpoint_url, headers=headers, json=data, timeout=(10, 300), stream=stream) - - if response.encoding is None or response.encoding == "ISO-8859-1": - response.encoding = "utf-8" - - if response.status_code != 200: - raise InvokeError(f"API request failed with status code {response.status_code}: {response.text}") - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: requests.Response, prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param credentials: model credentials - :param response: streamed response - :param prompt_messages: prompt messages - :return: llm response chunk generator - """ - full_assistant_content = "" - chunk_index = 0 - - def create_final_llm_result_chunk( - index: int, message: AssistantPromptMessage, finish_reason: str - ) -> LLMResultChunk: - # calculate num tokens - prompt_tokens = self._num_tokens_from_string(model, prompt_messages[0].content) - completion_tokens = self._num_tokens_from_string(model, full_assistant_content) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - return LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=message, finish_reason=finish_reason, usage=usage), - ) - - # delimiter for stream response, need unicode_escape - import codecs - - delimiter = credentials.get("stream_mode_delimiter", "\n\n") - delimiter = codecs.decode(delimiter, "unicode_escape") - - tools_calls: list[AssistantPromptMessage.ToolCall] = [] - - def increase_tool_call(new_tool_calls: list[AssistantPromptMessage.ToolCall]): - def get_tool_call(tool_call_id: str): - if not tool_call_id: - return tools_calls[-1] - - tool_call = next((tool_call for tool_call in tools_calls if tool_call.id == tool_call_id), None) - if tool_call is None: - tool_call = AssistantPromptMessage.ToolCall( - id=tool_call_id, - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction(name="", arguments=""), - ) - tools_calls.append(tool_call) - - return tool_call - - for new_tool_call in new_tool_calls: - # get tool call - tool_call = get_tool_call(new_tool_call.function.name) - # update tool call - if new_tool_call.id: - tool_call.id = new_tool_call.id - if new_tool_call.type: - tool_call.type = new_tool_call.type - if new_tool_call.function.name: - tool_call.function.name = new_tool_call.function.name - if new_tool_call.function.arguments: - tool_call.function.arguments += new_tool_call.function.arguments - - finish_reason = None # The default value of finish_reason is None - - for chunk in response.iter_lines(decode_unicode=True, delimiter=delimiter): - chunk = chunk.strip() - if chunk: - # ignore sse comments - if chunk.startswith(":"): - continue - decoded_chunk = chunk.strip().lstrip("data: ").lstrip() - if decoded_chunk == "[DONE]": # Some provider returns "data: [DONE]" - continue - - try: - chunk_json = json.loads(decoded_chunk) - # stream ended - except json.JSONDecodeError as e: - yield create_final_llm_result_chunk( - index=chunk_index + 1, - message=AssistantPromptMessage(content=""), - finish_reason="Non-JSON encountered.", - ) - break - if not chunk_json or len(chunk_json["choices"]) == 0: - continue - - choice = chunk_json["choices"][0] - finish_reason = chunk_json["choices"][0].get("finish_reason") - chunk_index += 1 - - if "delta" in choice: - delta = choice["delta"] - delta_content = delta.get("content") - - assistant_message_tool_calls = None - - if "tool_calls" in delta and credentials.get("function_calling_type", "no_call") == "tool_call": - assistant_message_tool_calls = delta.get("tool_calls", None) - elif ( - "function_call" in delta - and credentials.get("function_calling_type", "no_call") == "function_call" - ): - assistant_message_tool_calls = [ - {"id": "tool_call_id", "type": "function", "function": delta.get("function_call", {})} - ] - - # assistant_message_function_call = delta.delta.function_call - - # extract tool calls from response - if assistant_message_tool_calls: - tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - increase_tool_call(tool_calls) - - if delta_content is None or delta_content == "": - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=delta_content, - ) - - # reset tool calls - tool_calls = [] - full_assistant_content += delta_content - elif "text" in choice: - choice_text = choice.get("text", "") - if choice_text == "": - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=choice_text) - full_assistant_content += choice_text - else: - continue - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk_index, - message=assistant_prompt_message, - ), - ) - - chunk_index += 1 - - if tools_calls: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk_index, - message=AssistantPromptMessage(tool_calls=tools_calls, content=""), - ), - ) - - yield create_final_llm_result_chunk( - index=chunk_index, message=AssistantPromptMessage(content=""), finish_reason=finish_reason - ) - - def _handle_generate_response( - self, model: str, credentials: dict, response: requests.Response, prompt_messages: list[PromptMessage] - ) -> LLMResult: - response_json = response.json() - - completion_type = LLMMode.value_of(credentials["mode"]) - - output = response_json["choices"][0] - - response_content = "" - tool_calls = None - function_calling_type = credentials.get("function_calling_type", "no_call") - if completion_type is LLMMode.CHAT: - response_content = output.get("message", {})["content"] - if function_calling_type == "tool_call": - tool_calls = output.get("message", {}).get("tool_calls") - elif function_calling_type == "function_call": - tool_calls = output.get("message", {}).get("function_call") - - elif completion_type is LLMMode.COMPLETION: - response_content = output["text"] - - assistant_message = AssistantPromptMessage(content=response_content, tool_calls=[]) - - if tool_calls: - if function_calling_type == "tool_call": - assistant_message.tool_calls = self._extract_response_tool_calls(tool_calls) - elif function_calling_type == "function_call": - assistant_message.tool_calls = [self._extract_response_function_call(tool_calls)] - - usage = response_json.get("usage") - if usage: - # transform usage - prompt_tokens = usage["prompt_tokens"] - completion_tokens = usage["completion_tokens"] - else: - # calculate num tokens - prompt_tokens = self._num_tokens_from_string(model, prompt_messages[0].content) - completion_tokens = self._num_tokens_from_string(model, assistant_message.content) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=response_json["model"], - prompt_messages=prompt_messages, - message=assistant_message, - usage=usage, - ) - - return result - - def _convert_prompt_message_to_dict(self, message: PromptMessage, credentials: Optional[dict] = None) -> dict: - """ - Convert PromptMessage to dict for OpenAI API format - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(PromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": {"url": message_content.data, "detail": message_content.detail.value}, - } - sub_messages.append(sub_message_dict) - - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls: - function_calling_type = credentials.get("function_calling_type", "no_call") - if function_calling_type == "tool_call": - message_dict["tool_calls"] = [tool_call.dict() for tool_call in message.tool_calls] - elif function_calling_type == "function_call": - function_call = message.tool_calls[0] - message_dict["function_call"] = { - "name": function_call.function.name, - "arguments": function_call.function.arguments, - } - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - function_calling_type = credentials.get("function_calling_type", "no_call") - if function_calling_type == "tool_call": - message_dict = {"role": "tool", "content": message.content, "tool_call_id": message.tool_call_id} - elif function_calling_type == "function_call": - message_dict = {"role": "function", "content": message.content, "name": message.tool_call_id} - else: - raise ValueError(f"Got unknown type {message}") - - if message.name and message_dict.get("role", "") != "tool": - message_dict["name"] = message.name - - return message_dict - - def _num_tokens_from_string( - self, model: str, text: Union[str, list[PromptMessageContent]], tools: Optional[list[PromptMessageTool]] = None - ) -> int: - """ - Approximate num tokens for model with gpt2 tokenizer. - - :param model: model name - :param text: prompt text - :param tools: tools for tool calling - :return: number of tokens - """ - if isinstance(text, str): - full_text = text - else: - full_text = "" - for message_content in text: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(PromptMessageContent, message_content) - full_text += message_content.data - - num_tokens = self._get_num_tokens_by_gpt2(full_text) - - if tools: - num_tokens += self._num_tokens_for_tools(tools) - - return num_tokens - - def _num_tokens_from_messages( - self, - model: str, - messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - credentials: dict = None, - ) -> int: - """ - Approximate num tokens with GPT2 tokenizer. - """ - - tokens_per_message = 3 - tokens_per_name = 1 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m, credentials) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - # Cast str(value) in case the message value is not a string - # This occurs with function messages - # TODO: The current token calculation method for the image type is not implemented, - # which need to download the image and then get the resolution for calculation, - # and will increase the request delay - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += self._get_num_tokens_by_gpt2(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += self._get_num_tokens_by_gpt2(f_key) - num_tokens += self._get_num_tokens_by_gpt2(f_value) - else: - num_tokens += self._get_num_tokens_by_gpt2(t_key) - num_tokens += self._get_num_tokens_by_gpt2(t_value) - else: - num_tokens += self._get_num_tokens_by_gpt2(str(value)) - - if key == "name": - num_tokens += tokens_per_name - - # every reply is primed with assistant - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(tools) - - return num_tokens - - def _num_tokens_for_tools(self, tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for tool calling with tiktoken package. - - :param tools: tools for tool calling - :return: number of tokens - """ - num_tokens = 0 - for tool in tools: - num_tokens += self._get_num_tokens_by_gpt2("type") - num_tokens += self._get_num_tokens_by_gpt2("function") - num_tokens += self._get_num_tokens_by_gpt2("function") - - # calculate num tokens for function object - num_tokens += self._get_num_tokens_by_gpt2("name") - num_tokens += self._get_num_tokens_by_gpt2(tool.name) - num_tokens += self._get_num_tokens_by_gpt2("description") - num_tokens += self._get_num_tokens_by_gpt2(tool.description) - parameters = tool.parameters - num_tokens += self._get_num_tokens_by_gpt2("parameters") - if "title" in parameters: - num_tokens += self._get_num_tokens_by_gpt2("title") - num_tokens += self._get_num_tokens_by_gpt2(parameters.get("title")) - num_tokens += self._get_num_tokens_by_gpt2("type") - num_tokens += self._get_num_tokens_by_gpt2(parameters.get("type")) - if "properties" in parameters: - num_tokens += self._get_num_tokens_by_gpt2("properties") - for key, value in parameters.get("properties").items(): - num_tokens += self._get_num_tokens_by_gpt2(key) - for field_key, field_value in value.items(): - num_tokens += self._get_num_tokens_by_gpt2(field_key) - if field_key == "enum": - for enum_field in field_value: - num_tokens += 3 - num_tokens += self._get_num_tokens_by_gpt2(enum_field) - else: - num_tokens += self._get_num_tokens_by_gpt2(field_key) - num_tokens += self._get_num_tokens_by_gpt2(str(field_value)) - if "required" in parameters: - num_tokens += self._get_num_tokens_by_gpt2("required") - for required_field in parameters["required"]: - num_tokens += 3 - num_tokens += self._get_num_tokens_by_gpt2(required_field) - - return num_tokens - - def _extract_response_tool_calls(self, response_tool_calls: list[dict]) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_tool_calls: - for response_tool_call in response_tool_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.get("function", {}).get("name", ""), - arguments=response_tool_call.get("function", {}).get("arguments", ""), - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call.get("id", ""), type=response_tool_call.get("type", ""), function=function - ) - tool_calls.append(tool_call) - - return tool_calls - - def _extract_response_function_call(self, response_function_call) -> AssistantPromptMessage.ToolCall: - """ - Extract function call from response - - :param response_function_call: response function call - :return: tool call - """ - tool_call = None - if response_function_call: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_function_call.get("name", ""), arguments=response_function_call.get("arguments", "") - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_function_call.get("id", ""), type="function", function=function - ) - - return tool_call diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.py b/api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.py deleted file mode 100644 index ca6f1852872fed..00000000000000 --- a/api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class OAICompatProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.yaml b/api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.yaml deleted file mode 100644 index 88c76fe16ef733..00000000000000 --- a/api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.yaml +++ /dev/null @@ -1,162 +0,0 @@ -provider: openai_api_compatible -label: - en_US: OpenAI-API-compatible -description: - en_US: Model providers compatible with OpenAI's API standard, such as LM Studio. - zh_Hans: 兼容 OpenAI API 的模型供应商，例如 LM Studio 。 -supported_model_types: - - llm - - text-embedding - - speech2text -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter full model name - zh_Hans: 输入模型全称 - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: false - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: endpoint_url - label: - zh_Hans: API endpoint URL - en_US: API endpoint URL - type: text-input - required: true - placeholder: - zh_Hans: Base URL, e.g. https://api.openai.com/v1 - en_US: Base URL, e.g. https://api.openai.com/v1 - - variable: mode - show_on: - - variable: __model_type - value: llm - label: - en_US: Completion mode - type: select - required: false - default: chat - placeholder: - zh_Hans: 选择对话类型 - en_US: Select completion mode - options: - - value: completion - label: - en_US: Completion - zh_Hans: 补全 - - value: chat - label: - en_US: Chat - zh_Hans: 对话 - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - show_on: - - variable: __model_type - value: llm - type: text-input - default: '4096' - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - show_on: - - variable: __model_type - value: text-embedding - type: text-input - default: '4096' - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: max_tokens_to_sample - label: - zh_Hans: 最大 token 上限 - en_US: Upper bound for max tokens - show_on: - - variable: __model_type - value: llm - default: '4096' - type: text-input - - variable: function_calling_type - show_on: - - variable: __model_type - value: llm - label: - en_US: Function calling - type: select - required: false - default: no_call - options: - - value: function_call - label: - en_US: Function Call - zh_Hans: Function Call - - value: tool_call - label: - en_US: Tool Call - zh_Hans: Tool Call - - value: no_call - label: - en_US: Not Support - zh_Hans: 不支持 - - variable: stream_function_calling - show_on: - - variable: __model_type - value: llm - label: - en_US: Stream function calling - type: select - required: false - default: not_supported - options: - - value: supported - label: - en_US: Support - zh_Hans: 支持 - - value: not_supported - label: - en_US: Not Support - zh_Hans: 不支持 - - variable: vision_support - show_on: - - variable: __model_type - value: llm - label: - zh_Hans: Vision 支持 - en_US: Vision Support - type: select - required: false - default: no_support - options: - - value: support - label: - en_US: Support - zh_Hans: 支持 - - value: no_support - label: - en_US: Not Support - zh_Hans: 不支持 - - variable: stream_mode_delimiter - label: - zh_Hans: 流模式返回结果的分隔符 - en_US: Delimiter for streaming results - show_on: - - variable: __model_type - value: llm - default: '\n\n' - type: text-input diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/speech2text/__init__.py b/api/core/model_runtime/model_providers/openai_api_compatible/speech2text/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/speech2text/speech2text.py b/api/core/model_runtime/model_providers/openai_api_compatible/speech2text/speech2text.py deleted file mode 100644 index 405096578cdd5d..00000000000000 --- a/api/core/model_runtime/model_providers/openai_api_compatible/speech2text/speech2text.py +++ /dev/null @@ -1,61 +0,0 @@ -from typing import IO, Optional -from urllib.parse import urljoin - -import requests - -from core.model_runtime.errors.invoke import InvokeBadRequestError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel -from core.model_runtime.model_providers.openai_api_compatible._common import _CommonOaiApiCompat - - -class OAICompatSpeech2TextModel(_CommonOaiApiCompat, Speech2TextModel): - """ - Model class for OpenAI Compatible Speech to text model. - """ - - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - headers = {} - - api_key = credentials.get("api_key") - if api_key: - headers["Authorization"] = f"Bearer {api_key}" - - endpoint_url = credentials.get("endpoint_url") - if not endpoint_url.endswith("/"): - endpoint_url += "/" - endpoint_url = urljoin(endpoint_url, "audio/transcriptions") - - payload = {"model": model} - files = [("file", file)] - response = requests.post(endpoint_url, headers=headers, data=payload, files=files) - - if response.status_code != 200: - raise InvokeBadRequestError(response.text) - response_data = response.json() - return response_data["text"] - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - audio_file_path = self._get_demo_file_path() - - with open(audio_file_path, "rb") as audio_file: - self._invoke(model, credentials, audio_file) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/text_embedding/__init__.py b/api/core/model_runtime/model_providers/openai_api_compatible/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openllm/__init__.py b/api/core/model_runtime/model_providers/openllm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openllm/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/openllm/_assets/icon_l_en.svg deleted file mode 100644 index 59bb57992ca511..00000000000000 --- a/api/core/model_runtime/model_providers/openllm/_assets/icon_l_en.svg +++ /dev/null @@ -1,19 +0,0 @@ - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/openllm/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/openllm/_assets/icon_s_en.svg deleted file mode 100644 index d25d627020c26d..00000000000000 --- a/api/core/model_runtime/model_providers/openllm/_assets/icon_s_en.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/openllm/llm/__init__.py b/api/core/model_runtime/model_providers/openllm/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openllm/llm/llm.py b/api/core/model_runtime/model_providers/openllm/llm/llm.py deleted file mode 100644 index 34b4de796206dd..00000000000000 --- a/api/core/model_runtime/model_providers/openllm/llm/llm.py +++ /dev/null @@ -1,264 +0,0 @@ -from collections.abc import Generator - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.openllm.llm.openllm_generate import OpenLLMGenerate, OpenLLMGenerateMessage -from core.model_runtime.model_providers.openllm.llm.openllm_generate_errors import ( - BadRequestError, - InsufficientAccountBalanceError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) - - -class OpenLLMLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - return self._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate credentials for Baichuan model - """ - if not credentials.get("server_url"): - raise CredentialsValidateFailedError("Invalid server URL") - - # ping - instance = OpenLLMGenerate() - try: - instance.generate( - server_url=credentials["server_url"], - model_name=model, - prompt_messages=[OpenLLMGenerateMessage(content="ping\nAnswer: ", role="user")], - model_parameters={ - "max_tokens": 64, - "temperature": 0.8, - "top_p": 0.9, - "top_k": 15, - }, - stream=False, - user="", - stop=[], - ) - except InvalidAuthenticationError as e: - raise CredentialsValidateFailedError(f"Invalid API key: {e}") - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - return self._num_tokens_from_messages(prompt_messages, tools) - - def _num_tokens_from_messages(self, messages: list[PromptMessage], tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for OpenLLM model - it's a generate model, so we just join them by spe - """ - messages = ",".join([message.content for message in messages]) - return self._get_num_tokens_by_gpt2(messages) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - client = OpenLLMGenerate() - response = client.generate( - model_name=model, - server_url=credentials["server_url"], - prompt_messages=[self._convert_prompt_message_to_openllm_message(message) for message in prompt_messages], - model_parameters=model_parameters, - stop=stop, - stream=stream, - user=user, - ) - - if stream: - return self._handle_chat_generate_stream_response( - model=model, prompt_messages=prompt_messages, credentials=credentials, response=response - ) - return self._handle_chat_generate_response( - model=model, prompt_messages=prompt_messages, credentials=credentials, response=response - ) - - def _convert_prompt_message_to_openllm_message(self, prompt_message: PromptMessage) -> OpenLLMGenerateMessage: - """ - convert PromptMessage to OpenLLMGenerateMessage so that we can use OpenLLMGenerateMessage interface - """ - if isinstance(prompt_message, UserPromptMessage): - return OpenLLMGenerateMessage(role=OpenLLMGenerateMessage.Role.USER.value, content=prompt_message.content) - elif isinstance(prompt_message, AssistantPromptMessage): - return OpenLLMGenerateMessage( - role=OpenLLMGenerateMessage.Role.ASSISTANT.value, content=prompt_message.content - ) - else: - raise NotImplementedError(f"Prompt message type {type(prompt_message)} is not supported") - - def _handle_chat_generate_response( - self, model: str, prompt_messages: list[PromptMessage], credentials: dict, response: OpenLLMGenerateMessage - ) -> LLMResult: - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=response.usage["prompt_tokens"], - completion_tokens=response.usage["completion_tokens"], - ) - return LLMResult( - model=model, - prompt_messages=prompt_messages, - message=AssistantPromptMessage( - content=response.content, - tool_calls=[], - ), - usage=usage, - ) - - def _handle_chat_generate_stream_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: Generator[OpenLLMGenerateMessage, None, None], - ) -> Generator[LLMResultChunk, None, None]: - for message in response: - if message.usage: - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=message.usage["prompt_tokens"], - completion_tokens=message.usage["completion_tokens"], - ) - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=message.content, tool_calls=[]), - usage=usage, - finish_reason=message.stop_reason or None, - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=message.content, tool_calls=[]), - finish_reason=message.stop_reason or None, - ), - ) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - rules = [ - ParameterRule( - name="temperature", - type=ParameterType.FLOAT, - use_template="temperature", - label=I18nObject(zh_Hans="温度", en_US="Temperature"), - ), - ParameterRule( - name="top_p", - type=ParameterType.FLOAT, - use_template="top_p", - label=I18nObject(zh_Hans="Top P", en_US="Top P"), - ), - ParameterRule( - name="top_k", - type=ParameterType.INT, - use_template="top_k", - min=1, - default=1, - label=I18nObject(zh_Hans="Top K", en_US="Top K"), - ), - ParameterRule( - name="max_tokens", - type=ParameterType.INT, - use_template="max_tokens", - min=1, - default=512, - label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"), - ), - ] - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - model_properties={ - ModelPropertyKey.MODE: LLMMode.COMPLETION.value, - }, - parameter_rules=rules, - ) - - return entity - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [InternalServerError], - InvokeRateLimitError: [RateLimitReachedError], - InvokeAuthorizationError: [ - InvalidAuthenticationError, - InsufficientAccountBalanceError, - InvalidAPIKeyError, - ], - InvokeBadRequestError: [BadRequestError, KeyError], - } diff --git a/api/core/model_runtime/model_providers/openllm/llm/openllm_generate.py b/api/core/model_runtime/model_providers/openllm/llm/openllm_generate.py deleted file mode 100644 index 351dcced153750..00000000000000 --- a/api/core/model_runtime/model_providers/openllm/llm/openllm_generate.py +++ /dev/null @@ -1,198 +0,0 @@ -from collections.abc import Generator -from enum import Enum -from json import dumps, loads -from typing import Any, Union - -from requests import Response, post -from requests.exceptions import ConnectionError, InvalidSchema, MissingSchema - -from core.model_runtime.model_providers.openllm.llm.openllm_generate_errors import ( - BadRequestError, - InternalServerError, - InvalidAuthenticationError, -) - - -class OpenLLMGenerateMessage: - class Role(Enum): - USER = "user" - ASSISTANT = "assistant" - - role: str = Role.USER.value - content: str - usage: dict[str, int] = None - stop_reason: str = "" - - def to_dict(self) -> dict[str, Any]: - return { - "role": self.role, - "content": self.content, - } - - def __init__(self, content: str, role: str = "user") -> None: - self.content = content - self.role = role - - -class OpenLLMGenerate: - def generate( - self, - server_url: str, - model_name: str, - stream: bool, - model_parameters: dict[str, Any], - stop: list[str], - prompt_messages: list[OpenLLMGenerateMessage], - user: str, - ) -> Union[Generator[OpenLLMGenerateMessage, None, None], OpenLLMGenerateMessage]: - if not server_url: - raise InvalidAuthenticationError("Invalid server URL") - - default_llm_config = { - "max_new_tokens": 128, - "min_length": 0, - "early_stopping": False, - "num_beams": 1, - "num_beam_groups": 1, - "use_cache": True, - "temperature": 0.75, - "top_k": 15, - "top_p": 0.9, - "typical_p": 1, - "epsilon_cutoff": 0, - "eta_cutoff": 0, - "diversity_penalty": 0, - "repetition_penalty": 1, - "encoder_repetition_penalty": 1, - "length_penalty": 1, - "no_repeat_ngram_size": 0, - "renormalize_logits": False, - "remove_invalid_values": False, - "num_return_sequences": 1, - "output_attentions": False, - "output_hidden_states": False, - "output_scores": False, - "encoder_no_repeat_ngram_size": 0, - "n": 1, - "presence_penalty": 0, - "frequency_penalty": 0, - "use_beam_search": False, - "ignore_eos": False, - "skip_special_tokens": True, - } - - if "max_tokens" in model_parameters and type(model_parameters["max_tokens"]) == int: - default_llm_config["max_new_tokens"] = model_parameters["max_tokens"] - - if "temperature" in model_parameters and type(model_parameters["temperature"]) == float: - default_llm_config["temperature"] = model_parameters["temperature"] - - if "top_p" in model_parameters and type(model_parameters["top_p"]) == float: - default_llm_config["top_p"] = model_parameters["top_p"] - - if "top_k" in model_parameters and type(model_parameters["top_k"]) == int: - default_llm_config["top_k"] = model_parameters["top_k"] - - if "use_cache" in model_parameters and type(model_parameters["use_cache"]) == bool: - default_llm_config["use_cache"] = model_parameters["use_cache"] - - headers = {"Content-Type": "application/json", "accept": "application/json"} - - if stream: - url = f"{server_url}/v1/generate_stream" - timeout = 10 - else: - url = f"{server_url}/v1/generate" - timeout = 120 - - data = { - "stop": stop or [], - "prompt": "\n".join([message.content for message in prompt_messages]), - "llm_config": default_llm_config, - } - - try: - response = post(url=url, data=dumps(data), timeout=timeout, stream=stream, headers=headers) - except (ConnectionError, InvalidSchema, MissingSchema) as e: - # cloud not connect to the server - raise InvalidAuthenticationError(f"Invalid server URL: {e}") - - if not response.ok: - resp = response.json() - msg = resp["msg"] - if response.status_code == 400: - raise BadRequestError(msg) - elif response.status_code == 404: - raise InvalidAuthenticationError(msg) - elif response.status_code == 500: - raise InternalServerError(msg) - else: - raise InternalServerError(msg) - - if stream: - return self._handle_chat_stream_generate_response(response) - return self._handle_chat_generate_response(response) - - def _handle_chat_generate_response(self, response: Response) -> OpenLLMGenerateMessage: - try: - data = response.json() - except Exception as e: - raise InternalServerError(f"Failed to convert response to json: {e} with text: {response.text}") - - message = data["outputs"][0] - text = message["text"] - token_ids = message["token_ids"] - prompt_token_ids = data["prompt_token_ids"] - stop_reason = message["finish_reason"] - - message = OpenLLMGenerateMessage(content=text, role=OpenLLMGenerateMessage.Role.ASSISTANT.value) - message.stop_reason = stop_reason - message.usage = { - "prompt_tokens": len(prompt_token_ids), - "completion_tokens": len(token_ids), - "total_tokens": len(prompt_token_ids) + len(token_ids), - } - - return message - - def _handle_chat_stream_generate_response( - self, response: Response - ) -> Generator[OpenLLMGenerateMessage, None, None]: - completion_usage = 0 - - for line in response.iter_lines(): - if not line: - continue - - line: str = line.decode("utf-8") - if line.startswith("data: "): - line = line[6:].strip() - - if line == "[DONE]": - return - - try: - data = loads(line) - except Exception as e: - raise InternalServerError(f"Failed to convert response to json: {e} with text: {line}") - - output = data["outputs"] - - for choice in output: - text = choice["text"] - token_ids = choice["token_ids"] - - completion_usage += len(token_ids) - message = OpenLLMGenerateMessage(content=text, role=OpenLLMGenerateMessage.Role.ASSISTANT.value) - - if choice.get("finish_reason"): - finish_reason = choice["finish_reason"] - prompt_token_ids = data["prompt_token_ids"] - message.stop_reason = finish_reason - message.usage = { - "prompt_tokens": len(prompt_token_ids), - "completion_tokens": completion_usage, - "total_tokens": completion_usage + len(prompt_token_ids), - } - - yield message diff --git a/api/core/model_runtime/model_providers/openllm/llm/openllm_generate_errors.py b/api/core/model_runtime/model_providers/openllm/llm/openllm_generate_errors.py deleted file mode 100644 index 309b5cf413bd54..00000000000000 --- a/api/core/model_runtime/model_providers/openllm/llm/openllm_generate_errors.py +++ /dev/null @@ -1,22 +0,0 @@ -class InvalidAuthenticationError(Exception): - pass - - -class InvalidAPIKeyError(Exception): - pass - - -class RateLimitReachedError(Exception): - pass - - -class InsufficientAccountBalanceError(Exception): - pass - - -class InternalServerError(Exception): - pass - - -class BadRequestError(Exception): - pass diff --git a/api/core/model_runtime/model_providers/openllm/openllm.py b/api/core/model_runtime/model_providers/openllm/openllm.py deleted file mode 100644 index 80148021446944..00000000000000 --- a/api/core/model_runtime/model_providers/openllm/openllm.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class OpenLLMProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/openllm/openllm.yaml b/api/core/model_runtime/model_providers/openllm/openllm.yaml deleted file mode 100644 index fef52695e3eeed..00000000000000 --- a/api/core/model_runtime/model_providers/openllm/openllm.yaml +++ /dev/null @@ -1,37 +0,0 @@ -provider: openllm -label: - en_US: OpenLLM -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#F9FAFB" -help: - title: - en_US: How to deploy OpenLLM - zh_Hans: 如何部署 OpenLLM - url: - en_US: https://github.com/bentoml/OpenLLM -supported_model_types: - - llm - - text-embedding -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: server_url - label: - zh_Hans: 服务器URL - en_US: Server url - type: text-input - required: true - placeholder: - zh_Hans: 在此输入OpenLLM的服务器地址，如 http://192.168.1.100:3000 - en_US: Enter the url of your OpenLLM, e.g. http://192.168.1.100:3000 diff --git a/api/core/model_runtime/model_providers/openllm/text_embedding/__init__.py b/api/core/model_runtime/model_providers/openllm/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openrouter/__init__.py b/api/core/model_runtime/model_providers/openrouter/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openrouter/_assets/openrouter.svg b/api/core/model_runtime/model_providers/openrouter/_assets/openrouter.svg deleted file mode 100644 index 2e9590d923b8ef..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/_assets/openrouter.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/openrouter/_assets/openrouter_square.svg b/api/core/model_runtime/model_providers/openrouter/_assets/openrouter_square.svg deleted file mode 100644 index ed81fc041fc3e2..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/_assets/openrouter_square.svg +++ /dev/null @@ -1,10 +0,0 @@ - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/openrouter/llm/__init__.py b/api/core/model_runtime/model_providers/openrouter/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/openrouter/llm/_position.yaml b/api/core/model_runtime/model_providers/openrouter/llm/_position.yaml deleted file mode 100644 index d9497b76b894c4..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/_position.yaml +++ /dev/null @@ -1,27 +0,0 @@ -- openai/o1-preview -- openai/o1-mini -- openai/gpt-4o -- openai/gpt-4o-mini -- openai/gpt-4 -- openai/gpt-4-32k -- openai/gpt-3.5-turbo -- anthropic/claude-3.5-sonnet -- anthropic/claude-3-haiku -- anthropic/claude-3-opus -- anthropic/claude-3-sonnet -- google/gemini-pro-1.5 -- google/gemini-flash-1.5 -- google/gemini-pro -- cohere/command-r-plus -- cohere/command-r -- meta-llama/llama-3.1-405b-instruct -- meta-llama/llama-3.1-70b-instruct -- meta-llama/llama-3.1-8b-instruct -- meta-llama/llama-3-70b-instruct -- meta-llama/llama-3-8b-instruct -- mistralai/mixtral-8x22b-instruct -- mistralai/mixtral-8x7b-instruct -- mistralai/mistral-7b-instruct -- qwen/qwen-2-72b-instruct -- deepseek/deepseek-chat -- deepseek/deepseek-coder diff --git a/api/core/model_runtime/model_providers/openrouter/llm/claude-3-5-sonnet.yaml b/api/core/model_runtime/model_providers/openrouter/llm/claude-3-5-sonnet.yaml deleted file mode 100644 index 40558854e2a7bd..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/claude-3-5-sonnet.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: anthropic/claude-3.5-sonnet -label: - en_US: claude-3.5-sonnet -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: "3.00" - output: "15.00" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/claude-3-haiku.yaml b/api/core/model_runtime/model_providers/openrouter/llm/claude-3-haiku.yaml deleted file mode 100644 index ce17d4123e5c13..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/claude-3-haiku.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: anthropic/claude-3-haiku -label: - en_US: claude-3-haiku -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: "0.25" - output: "1.25" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/claude-3-opus.yaml b/api/core/model_runtime/model_providers/openrouter/llm/claude-3-opus.yaml deleted file mode 100644 index 68a92219eb0e52..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/claude-3-opus.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: anthropic/claude-3-opus -label: - en_US: claude-3-opus -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: "15.00" - output: "75.00" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/claude-3-sonnet.yaml b/api/core/model_runtime/model_providers/openrouter/llm/claude-3-sonnet.yaml deleted file mode 100644 index ede88459ca0ccc..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/claude-3-sonnet.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: anthropic/claude-3-sonnet -label: - en_US: claude-3-sonnet -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 4096 - min: 1 - max: 4096 - - name: response_format - use_template: response_format -pricing: - input: "3.00" - output: "15.00" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/command-r-plus.yaml b/api/core/model_runtime/model_providers/openrouter/llm/command-r-plus.yaml deleted file mode 100644 index a23eb269d1084b..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/command-r-plus.yaml +++ /dev/null @@ -1,45 +0,0 @@ -model: cohere/command-r-plus -label: - en_US: command-r-plus -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: top_p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: "3" - output: "15" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/command-r.yaml b/api/core/model_runtime/model_providers/openrouter/llm/command-r.yaml deleted file mode 100644 index 7165bf29b0c22c..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/command-r.yaml +++ /dev/null @@ -1,45 +0,0 @@ -model: cohere/command-r -label: - en_US: command-r -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - max: 5.0 - - name: top_p - use_template: top_p - default: 0.75 - min: 0.01 - max: 0.99 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - default: 0 - min: 0 - max: 500 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 1024 - max: 4096 -pricing: - input: "0.5" - output: "1.5" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/deepseek-chat.yaml b/api/core/model_runtime/model_providers/openrouter/llm/deepseek-chat.yaml deleted file mode 100644 index 7a1dea69503daa..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/deepseek-chat.yaml +++ /dev/null @@ -1,50 +0,0 @@ -model: deepseek/deepseek-chat -label: - en_US: deepseek-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 1 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 1 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. - - name: frequency_penalty - use_template: frequency_penalty - default: 0 - min: -2.0 - max: 2.0 - help: - zh_Hans: 介于 -2.0 和 2.0 之间的数字。如果该值为正，那么新 token 会根据其在已有文本中的出现频率受到相应的惩罚，降低模型重复相同内容的可能性。 - en_US: A number between -2.0 and 2.0. If the value is positive, new tokens are penalized based on their frequency of occurrence in existing text, reducing the likelihood that the model will repeat the same content. -pricing: - input: "0.14" - output: "0.28" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/deepseek-coder.yaml b/api/core/model_runtime/model_providers/openrouter/llm/deepseek-coder.yaml deleted file mode 100644 index c05f4769b83354..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/deepseek-coder.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: deepseek/deepseek-coder -label: - en_US: deepseek-coder -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 4096 - default: 1024 -pricing: - input: "0.14" - output: "0.28" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gemini-1.5-flash.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gemini-1.5-flash.yaml deleted file mode 100644 index 0b2f329b28ea49..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gemini-1.5-flash.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: google/gemini-flash-1.5 -label: - en_US: gemini-flash-1.5 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format -pricing: - input: "0.25" - output: "0.75" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gemini-1.5-pro.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gemini-1.5-pro.yaml deleted file mode 100644 index 679ce9bdcd443f..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gemini-1.5-pro.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: google/gemini-pro-1.5 -label: - en_US: gemini-pro-1.5 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format -pricing: - input: "2.5" - output: "7.5" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gemini-pro.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gemini-pro.yaml deleted file mode 100644 index 9f5d96c5b82e64..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gemini-pro.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: google/gemini-pro -label: - en_US: gemini-pro -model_type: llm -features: - - agent-thought - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 30720 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 2048 - - name: response_format - use_template: response_format -pricing: - input: "0.125" - output: "0.375" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gpt-3.5-turbo.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gpt-3.5-turbo.yaml deleted file mode 100644 index 186c1cc6636049..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gpt-3.5-turbo.yaml +++ /dev/null @@ -1,42 +0,0 @@ -model: openai/gpt-3.5-turbo -label: - en_US: gpt-3.5-turbo -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 16385 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: "0.5" - output: "1.5" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4-32k.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gpt-4-32k.yaml deleted file mode 100644 index 8c2989b300076d..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4-32k.yaml +++ /dev/null @@ -1,57 +0,0 @@ -model: openai/gpt-4-32k -label: - en_US: gpt-4-32k -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 32768 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: - 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: - If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: "60" - output: "120" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gpt-4.yaml deleted file mode 100644 index ef19d4f6f0dba4..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4.yaml +++ /dev/null @@ -1,57 +0,0 @@ -model: openai/gpt-4 -label: - en_US: gpt-4 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: - 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: - If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: "30" - output: "60" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o-2024-08-06.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o-2024-08-06.yaml deleted file mode 100644 index 0be325f55bdc90..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o-2024-08-06.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: gpt-4o-2024-08-06 -label: - zh_Hans: gpt-4o-2024-08-06 - en_US: gpt-4o-2024-08-06 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 16384 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: '2.50' - output: '10.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o-mini.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o-mini.yaml deleted file mode 100644 index 3b1d95643d22aa..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o-mini.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: openai/gpt-4o-mini -label: - en_US: gpt-4o-mini -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 16384 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: "0.15" - output: "0.60" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o.yaml b/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o.yaml deleted file mode 100644 index a8c97efdd64b12..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/gpt-4o.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: openai/gpt-4o -label: - en_US: gpt-4o -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call - - vision -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: Response Format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: "5.00" - output: "15.00" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/llama-3-70b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/llama-3-70b-instruct.yaml deleted file mode 100644 index b91c39e729eda3..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/llama-3-70b-instruct.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta-llama/llama-3-70b-instruct -label: - en_US: llama-3-70b-instruct -model_type: llm -model_properties: - mode: completion - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 2048 -pricing: - input: "0.59" - output: "0.79" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/llama-3-8b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/llama-3-8b-instruct.yaml deleted file mode 100644 index 84b2c7fac2c0f0..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/llama-3-8b-instruct.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta-llama/llama-3-8b-instruct -label: - en_US: llama-3-8b-instruct -model_type: llm -model_properties: - mode: completion - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 2048 -pricing: - input: "0.07" - output: "0.07" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-405b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-405b-instruct.yaml deleted file mode 100644 index a489ce1b5ad384..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-405b-instruct.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta-llama/llama-3.1-405b-instruct -label: - en_US: llama-3.1-405b-instruct -model_type: llm -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 131072 -pricing: - input: "2.7" - output: "2.7" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-70b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-70b-instruct.yaml deleted file mode 100644 index 12037411b100bd..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-70b-instruct.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta-llama/llama-3.1-70b-instruct -label: - en_US: llama-3.1-70b-instruct -model_type: llm -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 131072 -pricing: - input: "0.52" - output: "0.75" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-8b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-8b-instruct.yaml deleted file mode 100644 index 6f06493f293f9d..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/llama-3.1-8b-instruct.yaml +++ /dev/null @@ -1,23 +0,0 @@ -model: meta-llama/llama-3.1-8b-instruct -label: - en_US: llama-3.1-8b-instruct -model_type: llm -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 512 - min: 1 - max: 131072 -pricing: - input: "0.06" - output: "0.06" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/llm.py b/api/core/model_runtime/model_providers/openrouter/llm/llm.py deleted file mode 100644 index 736ab8e7a8f6ce..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/llm.py +++ /dev/null @@ -1,106 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class OpenRouterLargeLanguageModel(OAIAPICompatLargeLanguageModel): - def _update_credential(self, model: str, credentials: dict): - credentials["endpoint_url"] = "https://openrouter.ai/api/v1" - credentials["mode"] = self.get_model_mode(model).value - credentials["function_calling_type"] = "tool_call" - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._update_credential(model, credentials) - - return self._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._update_credential(model, credentials) - - return super().validate_credentials(model, credentials) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._update_credential(model, credentials) - - block_as_stream = False - if model.startswith("openai/o1"): - block_as_stream = True - stop = None - - # invoke block as stream - if stream and block_as_stream: - return self._generate_block_as_stream( - model, credentials, prompt_messages, model_parameters, tools, stop, user - ) - else: - return super()._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def _generate_block_as_stream( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - user: Optional[str] = None, - ) -> Generator: - resp: LLMResult = super()._generate( - model, credentials, prompt_messages, model_parameters, tools, stop, False, user - ) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=resp.message, - usage=self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=resp.usage.prompt_tokens, - completion_tokens=resp.usage.completion_tokens, - ), - finish_reason="stop", - ), - ) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - self._update_credential(model, credentials) - - return super().get_customizable_model_schema(model, credentials) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - self._update_credential(model, credentials) - - return super().get_num_tokens(model, credentials, prompt_messages, tools) diff --git a/api/core/model_runtime/model_providers/openrouter/llm/mistral-7b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/mistral-7b-instruct.yaml deleted file mode 100644 index 012dfc55ce18a8..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/mistral-7b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: mistralai/mistral-7b-instruct -label: - en_US: mistral-7b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 2048 -pricing: - input: "0.07" - output: "0.07" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/mixtral-8x22b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/mixtral-8x22b-instruct.yaml deleted file mode 100644 index f4eb4e45d95cb2..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/mixtral-8x22b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: mistralai/mixtral-8x22b-instruct -label: - en_US: mixtral-8x22b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 64000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8000 -pricing: - input: "0.65" - output: "0.65" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/mixtral-8x7b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/mixtral-8x7b-instruct.yaml deleted file mode 100644 index 7871e1f7a05c17..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/mixtral-8x7b-instruct.yaml +++ /dev/null @@ -1,31 +0,0 @@ -model: mistralai/mixtral-8x7b-instruct -label: - zh_Hans: mixtral-8x7b-instruct - en_US: mixtral-8x7b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.7 - min: 0 - max: 1 - - name: top_p - use_template: top_p - default: 1 - min: 0 - max: 1 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8000 -pricing: - input: "0.24" - output: "0.24" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/o1-mini.yaml b/api/core/model_runtime/model_providers/openrouter/llm/o1-mini.yaml deleted file mode 100644 index 85a918ff5e0ed5..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/o1-mini.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: openai/o1-mini -label: - en_US: o1-mini -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 65536 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: response_format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: "3.00" - output: "12.00" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/o1-preview.yaml b/api/core/model_runtime/model_providers/openrouter/llm/o1-preview.yaml deleted file mode 100644 index 74b0a511bed270..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/o1-preview.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: openai/o1-preview -label: - en_US: o1-preview -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 32768 - - name: response_format - label: - zh_Hans: 回复格式 - en_US: response_format - type: string - help: - zh_Hans: 指定模型必须输出的格式 - en_US: specifying the format that the model must output - required: false - options: - - text - - json_object -pricing: - input: "15.00" - output: "60.00" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/llm/qwen2-72b-instruct.yaml b/api/core/model_runtime/model_providers/openrouter/llm/qwen2-72b-instruct.yaml deleted file mode 100644 index 7b75fcb0c986a3..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/llm/qwen2-72b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: qwen/qwen-2-72b-instruct -label: - en_US: qwen-2-72b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: "0.59" - output: "0.79" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/openrouter/openrouter.py b/api/core/model_runtime/model_providers/openrouter/openrouter.py deleted file mode 100644 index 2e59ab50598b8b..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/openrouter.py +++ /dev/null @@ -1,20 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class OpenRouterProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="openai/gpt-3.5-turbo", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/openrouter/openrouter.yaml b/api/core/model_runtime/model_providers/openrouter/openrouter.yaml deleted file mode 100644 index f7536609ec5193..00000000000000 --- a/api/core/model_runtime/model_providers/openrouter/openrouter.yaml +++ /dev/null @@ -1,105 +0,0 @@ -provider: openrouter -label: - en_US: OpenRouter -icon_small: - en_US: openrouter_square.svg -icon_large: - en_US: openrouter.svg -background: "#F1EFED" -help: - title: - en_US: Get your API key from openrouter.ai - zh_Hans: 从 openrouter.ai 获取 API Key - url: - en_US: https://openrouter.ai/keys -supported_model_types: - - llm -configurate_methods: - - predefined-model - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter full model name - zh_Hans: 输入模型全称 - credential_form_schemas: - - variable: api_key - required: true - label: - en_US: API Key - type: secret-input - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: mode - show_on: - - variable: __model_type - value: llm - label: - en_US: Completion mode - type: select - required: false - default: chat - placeholder: - zh_Hans: 选择对话类型 - en_US: Select completion mode - options: - - value: completion - label: - en_US: Completion - zh_Hans: 补全 - - value: chat - label: - en_US: Chat - zh_Hans: 对话 - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - type: text-input - default: "4096" - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: max_tokens_to_sample - label: - zh_Hans: 最大 token 上限 - en_US: Upper bound for max tokens - show_on: - - variable: __model_type - value: llm - default: "4096" - type: text-input - - variable: vision_support - show_on: - - variable: __model_type - value: llm - label: - zh_Hans: 是否支持 Vision - en_US: Vision Support - type: radio - required: false - default: "no_support" - options: - - value: "support" - label: - en_US: "Yes" - zh_Hans: 是 - - value: "no_support" - label: - en_US: "No" - zh_Hans: 否 -provider_credential_schema: - credential_form_schemas: - - variable: api_key - required: true - label: - en_US: API Key - type: secret-input - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/perfxcloud/__init__.py b/api/core/model_runtime/model_providers/perfxcloud/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/perfxcloud/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/perfxcloud/_assets/icon_l_en.svg deleted file mode 100644 index 060d9de3a95c30..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/_assets/icon_l_en.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - diff --git a/api/core/model_runtime/model_providers/perfxcloud/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/perfxcloud/_assets/icon_s_en.svg deleted file mode 100644 index be0c2eeb1ccc48..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/_assets/icon_s_en.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Llama3-Chinese_v2.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Llama3-Chinese_v2.yaml deleted file mode 100644 index bf91468fcf56bf..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Llama3-Chinese_v2.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: Llama3-Chinese_v2 -label: - en_US: Llama3-Chinese_v2 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3-70B-Instruct-GPTQ-Int4.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3-70B-Instruct-GPTQ-Int4.yaml deleted file mode 100644 index 781b837e8eceea..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3-70B-Instruct-GPTQ-Int4.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: Meta-Llama-3-70B-Instruct-GPTQ-Int4 -label: - en_US: Meta-Llama-3-70B-Instruct-GPTQ-Int4 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 1024 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3-8B-Instruct.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3-8B-Instruct.yaml deleted file mode 100644 index 67210e9020fe6a..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3-8B-Instruct.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: Meta-Llama-3-8B-Instruct -label: - en_US: Meta-Llama-3-8B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3.1-405B-Instruct-AWQ-INT4.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3.1-405B-Instruct-AWQ-INT4.yaml deleted file mode 100644 index 482632ff0673d2..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3.1-405B-Instruct-AWQ-INT4.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: Meta-Llama-3.1-405B-Instruct-AWQ-INT4 -label: - en_US: Meta-Llama-3.1-405B-Instruct-AWQ-INT4 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 410960 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3.1-8B-Instruct.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3.1-8B-Instruct.yaml deleted file mode 100644 index bbab46344c3a12..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3.1-8B-Instruct.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Meta-Llama-3.1-8B-Instruct -label: - en_US: Meta-Llama-3.1-8B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.1 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen-14B-Chat-Int4.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen-14B-Chat-Int4.yaml deleted file mode 100644 index ec6d9bcc149fdf..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen-14B-Chat-Int4.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: Qwen-14B-Chat-Int4 -label: - en_US: Qwen-14B-Chat-Int4 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-110B-Chat-GPTQ-Int4.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-110B-Chat-GPTQ-Int4.yaml deleted file mode 100644 index b561a53039a78e..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-110B-Chat-GPTQ-Int4.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: Qwen1.5-110B-Chat-GPTQ-Int4 -label: - en_US: Qwen1.5-110B-Chat-GPTQ-Int4 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 128 - min: 1 - max: 256 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-72B-Chat-GPTQ-Int4.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-72B-Chat-GPTQ-Int4.yaml deleted file mode 100644 index ddb6fd977c5a56..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-72B-Chat-GPTQ-Int4.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: Qwen1.5-72B-Chat-GPTQ-Int4 -label: - en_US: Qwen1.5-72B-Chat-GPTQ-Int4 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 2048 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-7B.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-7B.yaml deleted file mode 100644 index 024c79dbcfd76c..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-7B.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: Qwen1.5-7B -label: - en_US: Qwen1.5-7B -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct-AWQ-int4.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct-AWQ-int4.yaml deleted file mode 100644 index 94f661f40d5c90..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct-AWQ-int4.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Qwen2-72B-Instruct-AWQ-int4 -label: - en_US: Qwen2-72B-Instruct-AWQ-int4 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct-GPTQ-Int4.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct-GPTQ-Int4.yaml deleted file mode 100644 index a06f8d5ab18f4c..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct-GPTQ-Int4.yaml +++ /dev/null @@ -1,64 +0,0 @@ -model: Qwen2-72B-Instruct-GPTQ-Int4 -label: - en_US: Qwen2-72B-Instruct-GPTQ-Int4 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 2048 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.7 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct.yaml deleted file mode 100644 index cea6560295267a..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Qwen2-72B-Instruct -label: - en_US: Qwen2-72B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-7B-Instruct.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-7B-Instruct.yaml deleted file mode 100644 index 4369411399e72a..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-7B-Instruct.yaml +++ /dev/null @@ -1,63 +0,0 @@ -model: Qwen2-7B-Instruct -label: - en_US: Qwen2-7B-Instruct -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: completion - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-7B.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-7B.yaml deleted file mode 100644 index d549ecd227dfb8..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-7B.yaml +++ /dev/null @@ -1,64 +0,0 @@ -model: Qwen2-7B -label: - en_US: Qwen2-7B -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: completion - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2.5-72B-Instruct.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2.5-72B-Instruct.yaml deleted file mode 100644 index 15cbf01f1f66da..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2.5-72B-Instruct.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Qwen2.5-72B-Instruct -label: - en_US: Qwen2.5-72B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 30720 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2.5-7B-Instruct.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2.5-7B-Instruct.yaml deleted file mode 100644 index dadc8f8f3275e5..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2.5-7B-Instruct.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Qwen2.5-7B-Instruct -label: - en_US: Qwen2.5-7B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Reflection-Llama-3.1-70B.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Reflection-Llama-3.1-70B.yaml deleted file mode 100644 index 649be20b48abef..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Reflection-Llama-3.1-70B.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Reflection-Llama-3.1-70B -label: - en_US: Reflection-Llama-3.1-70B -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 10240 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-1_5-9B-Chat-16K.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-1_5-9B-Chat-16K.yaml deleted file mode 100644 index 92eae6804f61fa..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-1_5-9B-Chat-16K.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Yi-1_5-9B-Chat-16K -label: - en_US: Yi-1_5-9B-Chat-16K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-Coder-1.5B-Chat.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-Coder-1.5B-Chat.yaml deleted file mode 100644 index 0e21ce148c39bd..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-Coder-1.5B-Chat.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Yi-Coder-1.5B-Chat -label: - en_US: Yi-Coder-1.5B-Chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 20480 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-Coder-9B-Chat.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-Coder-9B-Chat.yaml deleted file mode 100644 index 23b0841ce4ed65..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/Yi-Coder-9B-Chat.yaml +++ /dev/null @@ -1,61 +0,0 @@ -model: Yi-Coder-9B-Chat -label: - en_US: Yi-Coder-9B-Chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 20480 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/__init__.py b/api/core/model_runtime/model_providers/perfxcloud/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/_position.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/_position.yaml deleted file mode 100644 index 37bf400f1e3475..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/_position.yaml +++ /dev/null @@ -1,24 +0,0 @@ -- Qwen2.5-72B-Instruct -- Qwen2.5-7B-Instruct -- Yi-Coder-1.5B-Chat -- Yi-Coder-9B-Chat -- Qwen2-72B-Instruct-AWQ-int4 -- Yi-1_5-9B-Chat-16K -- Qwen2-7B-Instruct -- Reflection-Llama-3.1-70B -- Qwen2-72B-Instruct -- Meta-Llama-3.1-8B-Instruct - -- Meta-Llama-3.1-405B-Instruct-AWQ-INT4 -- Meta-Llama-3-70B-Instruct-GPTQ-Int4 -- chatglm3-6b -- Meta-Llama-3-8B-Instruct -- Llama3-Chinese_v2 -- deepseek-v2-lite-chat -- Qwen2-72B-Instruct-GPTQ-Int4 -- Qwen2-7B -- Qwen-14B-Chat-Int4 -- Qwen1.5-72B-Chat-GPTQ-Int4 -- Qwen1.5-7B -- Qwen1.5-110B-Chat-GPTQ-Int4 -- deepseek-v2-chat diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/chatglm3-6b.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/chatglm3-6b.yaml deleted file mode 100644 index 75d80f784a71f5..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/chatglm3-6b.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: chatglm3-6b -label: - en_US: chatglm3-6b -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/deepseek-v2-chat.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/deepseek-v2-chat.yaml deleted file mode 100644 index fa9a7b7175e9dc..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/deepseek-v2-chat.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: deepseek-v2-chat -label: - en_US: deepseek-v2-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/deepseek-v2-lite-chat.yaml b/api/core/model_runtime/model_providers/perfxcloud/llm/deepseek-v2-lite-chat.yaml deleted file mode 100644 index 75a26d25051aea..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/deepseek-v2-lite-chat.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: deepseek-v2-lite-chat -label: - en_US: deepseek-v2-lite-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 2048 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.5 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 600 - min: 1 - max: 1248 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. -pricing: - input: "0.000" - output: "0.000" - unit: "0.000" - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/perfxcloud/llm/llm.py b/api/core/model_runtime/model_providers/perfxcloud/llm/llm.py deleted file mode 100644 index 89cac665aa5a08..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/llm/llm.py +++ /dev/null @@ -1,116 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union -from urllib.parse import urlparse - -import tiktoken - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import ( - PromptMessage, - PromptMessageTool, -) -from core.model_runtime.model_providers.openai.llm.llm import OpenAILargeLanguageModel - - -class PerfXCloudLargeLanguageModel(OpenAILargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials) - - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - # refactored from openai model runtime, use cl100k_base for calculate token number - def _num_tokens_from_string(self, model: str, text: str, tools: Optional[list[PromptMessageTool]] = None) -> int: - """ - Calculate num tokens for text completion model with tiktoken package. - - :param model: model name - :param text: prompt text - :param tools: tools for tool calling - :return: number of tokens - """ - encoding = tiktoken.get_encoding("cl100k_base") - num_tokens = len(encoding.encode(text)) - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - # refactored from openai model runtime, use cl100k_base for calculate token number - def _num_tokens_from_messages( - self, model: str, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None - ) -> int: - """Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package. - - Official documentation: https://github.com/openai/openai-cookbook/blob/ - main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb""" - encoding = tiktoken.get_encoding("cl100k_base") - tokens_per_message = 3 - tokens_per_name = 1 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - # Cast str(value) in case the message value is not a string - # This occurs with function messages - # TODO: The current token calculation method for the image type is not implemented, - # which need to download the image and then get the resolution for calculation, - # and will increase the request delay - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += len(encoding.encode(t_key)) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += len(encoding.encode(f_key)) - num_tokens += len(encoding.encode(f_value)) - else: - num_tokens += len(encoding.encode(t_key)) - num_tokens += len(encoding.encode(t_value)) - else: - num_tokens += len(encoding.encode(str(value))) - - if key == "name": - num_tokens += tokens_per_name - - # every reply is primed with assistant - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - @staticmethod - def _add_custom_parameters(credentials: dict) -> None: - credentials["mode"] = "chat" - credentials["openai_api_key"] = credentials["api_key"] - if "endpoint_url" not in credentials or credentials["endpoint_url"] == "": - credentials["openai_api_base"] = "https://cloud.perfxlab.cn" - else: - parsed_url = urlparse(credentials["endpoint_url"]) - credentials["openai_api_base"] = f"{parsed_url.scheme}://{parsed_url.netloc}" diff --git a/api/core/model_runtime/model_providers/perfxcloud/perfxcloud.py b/api/core/model_runtime/model_providers/perfxcloud/perfxcloud.py deleted file mode 100644 index 9a4ead031d018c..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/perfxcloud.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class PerfXCloudProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/perfxcloud/perfxcloud.yaml b/api/core/model_runtime/model_providers/perfxcloud/perfxcloud.yaml deleted file mode 100644 index 10ee691ebd0609..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/perfxcloud.yaml +++ /dev/null @@ -1,42 +0,0 @@ -provider: perfxcloud -label: - en_US: PerfXCloud - zh_Hans: PerfXCloud -description: - en_US: PerfXCloud (Pengfeng Technology) is an AI development and deployment platform tailored for developers and enterprises, providing reasoning capabilities for multiple models. - zh_Hans: PerfXCloud（澎峰科技）为开发者和企业量身打造的AI开发和部署平台，提供多种模型的的推理能力。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#e3f0ff" -help: - title: - en_US: Get your API Key from PerfXCloud - zh_Hans: 从 PerfXCloud 获取 API Key - url: - en_US: https://cloud.perfxlab.cn/panel/token -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: endpoint_url - label: - zh_Hans: 自定义 API endpoint 地址 - en_US: Custom API endpoint URL - type: text-input - required: false - placeholder: - zh_Hans: Base URL, e.g. https://cloud.perfxlab.cn/v1 - en_US: Base URL, e.g. https://cloud.perfxlab.cn/v1 diff --git a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-large-en-v1.5.yaml b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-large-en-v1.5.yaml deleted file mode 100644 index 5756fb3d149d4c..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-large-en-v1.5.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: BAAI/bge-large-en-v1.5 -model_type: text-embedding -model_properties: - context_size: 32768 diff --git a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-large-zh-v1.5.yaml b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-large-zh-v1.5.yaml deleted file mode 100644 index 4204ab2860248b..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-large-zh-v1.5.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: BAAI/bge-large-zh-v1.5 -model_type: text-embedding -model_properties: - context_size: 32768 diff --git a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-m3.yaml b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-m3.yaml deleted file mode 100644 index 55488e56885d10..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-m3.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: BAAI/bge-m3 -model_type: text-embedding -model_properties: - context_size: 32768 diff --git a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/__init__.py b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/gte-Qwen2-7B-instruct.yaml b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/gte-Qwen2-7B-instruct.yaml deleted file mode 100644 index 03db0d8bce8500..00000000000000 --- a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/gte-Qwen2-7B-instruct.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: gte-Qwen2-7B-instruct -model_type: text-embedding -model_properties: - context_size: 2048 diff --git a/api/core/model_runtime/model_providers/replicate/__init__.py b/api/core/model_runtime/model_providers/replicate/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/replicate/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/replicate/_assets/icon_l_en.svg deleted file mode 100644 index 63c09470d54059..00000000000000 --- a/api/core/model_runtime/model_providers/replicate/_assets/icon_l_en.svg +++ /dev/null @@ -1,13 +0,0 @@ - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/replicate/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/replicate/_assets/icon_s_en.svg deleted file mode 100644 index 527316edb6f738..00000000000000 --- a/api/core/model_runtime/model_providers/replicate/_assets/icon_s_en.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - diff --git a/api/core/model_runtime/model_providers/replicate/_common.py b/api/core/model_runtime/model_providers/replicate/_common.py deleted file mode 100644 index 915f6e0eefcd08..00000000000000 --- a/api/core/model_runtime/model_providers/replicate/_common.py +++ /dev/null @@ -1,9 +0,0 @@ -from replicate.exceptions import ModelError, ReplicateError - -from core.model_runtime.errors.invoke import InvokeBadRequestError, InvokeError - - -class _CommonReplicate: - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return {InvokeBadRequestError: [ReplicateError, ModelError]} diff --git a/api/core/model_runtime/model_providers/replicate/llm/__init__.py b/api/core/model_runtime/model_providers/replicate/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/replicate/llm/llm.py b/api/core/model_runtime/model_providers/replicate/llm/llm.py deleted file mode 100644 index 3641b35dc02a39..00000000000000 --- a/api/core/model_runtime/model_providers/replicate/llm/llm.py +++ /dev/null @@ -1,305 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from replicate import Client as ReplicateClient -from replicate.exceptions import ReplicateError -from replicate.prediction import Prediction - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageRole, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - ParameterRule, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.replicate._common import _CommonReplicate - - -class ReplicateLargeLanguageModel(_CommonReplicate, LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - model_version = "" - if "model_version" in credentials: - model_version = credentials["model_version"] - - client = ReplicateClient(api_token=credentials["replicate_api_token"], timeout=30) - model_info = client.models.get(model) - - if model_version: - model_info_version = model_info.versions.get(model_version) - else: - model_info_version = model_info.latest_version - - inputs = {**model_parameters} - - if prompt_messages[0].role == PromptMessageRole.SYSTEM: - if "system_prompt" in model_info_version.openapi_schema["components"]["schemas"]["Input"]["properties"]: - inputs["system_prompt"] = prompt_messages[0].content - inputs["prompt"] = prompt_messages[1].content - else: - inputs["prompt"] = prompt_messages[0].content - - prediction = client.predictions.create(version=model_info_version, input=inputs) - - if stream: - return self._handle_generate_stream_response(model, credentials, prediction, stop, prompt_messages) - return self._handle_generate_response(model, credentials, prediction, stop, prompt_messages) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - prompt = self._convert_messages_to_prompt(prompt_messages) - return self._get_num_tokens_by_gpt2(prompt) - - def validate_credentials(self, model: str, credentials: dict) -> None: - if "replicate_api_token" not in credentials: - raise CredentialsValidateFailedError("Replicate Access Token must be provided.") - - model_version = "" - if "model_version" in credentials: - model_version = credentials["model_version"] - - if model.count("/") != 1: - raise CredentialsValidateFailedError( - "Replicate Model Name must be provided, format: {user_name}/{model_name}" - ) - - try: - client = ReplicateClient(api_token=credentials["replicate_api_token"], timeout=30) - model_info = client.models.get(model) - - if model_version: - model_info_version = model_info.versions.get(model_version) - else: - model_info_version = model_info.latest_version - - self._check_text_generation_model(model_info_version, model, model_version, model_info.description) - except ReplicateError as e: - raise CredentialsValidateFailedError( - f"Model {model}:{model_version} not exists, cause: {e.__class__.__name__}:{str(e)}" - ) - except Exception as e: - raise CredentialsValidateFailedError(str(e)) - - @staticmethod - def _check_text_generation_model(model_info_version, model_name, version, description): - if "language model" in description.lower(): - return - - if ( - "temperature" not in model_info_version.openapi_schema["components"]["schemas"]["Input"]["properties"] - or "top_p" not in model_info_version.openapi_schema["components"]["schemas"]["Input"]["properties"] - or "top_k" not in model_info_version.openapi_schema["components"]["schemas"]["Input"]["properties"] - ): - raise CredentialsValidateFailedError(f"Model {model_name}:{version} is not a Text Generation model.") - - def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]: - model_type = LLMMode.CHAT if model.endswith("-chat") else LLMMode.COMPLETION - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - model_properties={ModelPropertyKey.MODE: model_type.value}, - parameter_rules=self._get_customizable_model_parameter_rules(model, credentials), - ) - - return entity - - @classmethod - def _get_customizable_model_parameter_rules(cls, model: str, credentials: dict) -> list[ParameterRule]: - model_version = "" - if "model_version" in credentials: - model_version = credentials["model_version"] - - client = ReplicateClient(api_token=credentials["replicate_api_token"], timeout=30) - model_info = client.models.get(model) - - if model_version: - model_info_version = model_info.versions.get(model_version) - else: - model_info_version = model_info.latest_version - - parameter_rules = [] - - input_properties = sorted( - model_info_version.openapi_schema["components"]["schemas"]["Input"]["properties"].items(), - key=lambda item: item[1].get("x-order", 0), - ) - - for key, value in input_properties: - if key not in {"system_prompt", "prompt"} and "stop" not in key: - value_type = value.get("type") - - if not value_type: - continue - - param_type = cls._get_parameter_type(value_type) - - rule = ParameterRule( - name=key, - label={"en_US": value["title"]}, - type=param_type, - help={ - "en_US": value.get("description"), - }, - required=False, - default=value.get("default"), - min=value.get("minimum"), - max=value.get("maximum"), - ) - parameter_rules.append(rule) - - return parameter_rules - - def _handle_generate_stream_response( - self, - model: str, - credentials: dict, - prediction: Prediction, - stop: list[str], - prompt_messages: list[PromptMessage], - ) -> Generator: - index = -1 - current_completion: str = "" - stop_condition_reached = False - - prediction_output_length = 10000 - is_prediction_output_finished = False - - for output in prediction.output_iterator(): - current_completion += output - - if not is_prediction_output_finished and prediction.status == "succeeded": - prediction_output_length = len(prediction.output) - 1 - is_prediction_output_finished = True - - if stop: - for s in stop: - if s in current_completion: - prediction.cancel() - stop_index = current_completion.find(s) - current_completion = current_completion[:stop_index] - stop_condition_reached = True - break - - if stop_condition_reached: - break - - index += 1 - - assistant_prompt_message = AssistantPromptMessage(content=output or "") - - if index < prediction_output_length: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message), - ) - else: - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message, usage=usage), - ) - - def _handle_generate_response( - self, - model: str, - credentials: dict, - prediction: Prediction, - stop: list[str], - prompt_messages: list[PromptMessage], - ) -> LLMResult: - current_completion: str = "" - stop_condition_reached = False - for output in prediction.output_iterator(): - current_completion += output - - if stop: - for s in stop: - if s in current_completion: - prediction.cancel() - stop_index = current_completion.find(s) - current_completion = current_completion[:stop_index] - stop_condition_reached = True - break - - if stop_condition_reached: - break - - assistant_prompt_message = AssistantPromptMessage(content=current_completion) - - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - - return result - - @classmethod - def _get_parameter_type(cls, param_type: str) -> str: - type_mapping = {"integer": "int", "number": "float", "boolean": "boolean", "string": "string"} - return type_mapping.get(param_type) - - def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str: - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - return text.rstrip() - - @staticmethod - def _convert_one_message_to_text(message: PromptMessage) -> str: - human_prompt = "\n\nHuman:" - ai_prompt = "\n\nAssistant:" - content = message.content - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage): - message_text = content - else: - raise ValueError(f"Got unknown type {message}") - - return message_text diff --git a/api/core/model_runtime/model_providers/replicate/replicate.py b/api/core/model_runtime/model_providers/replicate/replicate.py deleted file mode 100644 index ca137579c96f2c..00000000000000 --- a/api/core/model_runtime/model_providers/replicate/replicate.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class ReplicateProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/replicate/replicate.yaml b/api/core/model_runtime/model_providers/replicate/replicate.yaml deleted file mode 100644 index 9cad6d4f0df595..00000000000000 --- a/api/core/model_runtime/model_providers/replicate/replicate.yaml +++ /dev/null @@ -1,41 +0,0 @@ -provider: replicate -label: - en_US: Replicate -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#E5E7EB" -help: - title: - en_US: Get your API Key from Replicate - zh_Hans: 从 Replicate 获取 API Key - url: - en_US: https://replicate.com/account/api-tokens -supported_model_types: - - llm - - text-embedding -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - credential_form_schemas: - - variable: replicate_api_token - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 Replicate API Key - en_US: Enter your Replicate API Key - - variable: model_version - label: - en_US: Model Version - type: text-input - required: false - placeholder: - zh_Hans: 在此输入您的模型版本，默认为最新版本 - en_US: Enter your model version, default to the latest version diff --git a/api/core/model_runtime/model_providers/replicate/text_embedding/__init__.py b/api/core/model_runtime/model_providers/replicate/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/sagemaker/__init__.py b/api/core/model_runtime/model_providers/sagemaker/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/sagemaker/_assets/icon_l_en.png b/api/core/model_runtime/model_providers/sagemaker/_assets/icon_l_en.png deleted file mode 100644 index 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zvgh61uFt|VP5JI*ef0PMNRN^cQk<8~EFrJ?LwXdYJh{-CTJF+|zzo_coWCzb-LqA! zlMf8cPTh!bdYUW85Zvs0kd1P6f)e;;3loVZzD?D4#y+3IAjJDE*625BtSI}hos9=X z(LBjqgdnr;Zr(Cd#3HSa&Kn|^Fe#nSi2*2q!Zz{!>cCppGm*<{47Fb;!3jVz!$b%S zSv@zh#qM{vdxyWSre+qlwqBwz{ezR<|1SJRsyJSQU;JECaEVIu5-cwf3H#B0(e2Ow OOmb4nk~QL{VgCa)i~r65 diff --git a/api/core/model_runtime/model_providers/sagemaker/llm/__init__.py b/api/core/model_runtime/model_providers/sagemaker/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/sagemaker/rerank/__init__.py b/api/core/model_runtime/model_providers/sagemaker/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/sagemaker/rerank/rerank.py b/api/core/model_runtime/model_providers/sagemaker/rerank/rerank.py deleted file mode 100644 index 959dff6a21c6d5..00000000000000 --- a/api/core/model_runtime/model_providers/sagemaker/rerank/rerank.py +++ /dev/null @@ -1,173 +0,0 @@ -import json -import logging -import operator -from typing import Any, Optional - -import boto3 - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - -logger = logging.getLogger(__name__) - - -class SageMakerRerankModel(RerankModel): - """ - Model class for SageMaker rerank model. - """ - - sagemaker_client: Any = None - - def _sagemaker_rerank(self, query_input: str, docs: list[str], rerank_endpoint: str): - inputs = [query_input] * len(docs) - response_model = self.sagemaker_client.invoke_endpoint( - EndpointName=rerank_endpoint, - Body=json.dumps({"inputs": inputs, "docs": docs}), - ContentType="application/json", - ) - json_str = response_model["Body"].read().decode("utf8") - json_obj = json.loads(json_str) - scores = json_obj["scores"] - return scores if isinstance(scores, list) else [scores] - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n - :param user: unique user id - :return: rerank result - """ - line = 0 - try: - if len(docs) == 0: - return RerankResult(model=model, docs=docs) - - line = 1 - if not self.sagemaker_client: - access_key = credentials.get("aws_access_key_id") - secret_key = credentials.get("aws_secret_access_key") - aws_region = credentials.get("aws_region") - if aws_region: - if access_key and secret_key: - self.sagemaker_client = boto3.client( - "sagemaker-runtime", - aws_access_key_id=access_key, - aws_secret_access_key=secret_key, - region_name=aws_region, - ) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime", region_name=aws_region) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime") - - line = 2 - - sagemaker_endpoint = credentials.get("sagemaker_endpoint") - candidate_docs = [] - - scores = self._sagemaker_rerank(query, docs, sagemaker_endpoint) - for idx in range(len(scores)): - candidate_docs.append({"content": docs[idx], "score": scores[idx]}) - - sorted(candidate_docs, key=operator.itemgetter("score"), reverse=True) - - line = 3 - rerank_documents = [] - for idx, result in enumerate(candidate_docs): - rerank_document = RerankDocument( - index=idx, text=result.get("content"), score=result.get("score", -100.0) - ) - - if score_threshold is not None: - if rerank_document.score >= score_threshold: - rerank_documents.append(rerank_document) - else: - rerank_documents.append(rerank_document) - - return RerankResult(model=model, docs=rerank_documents) - - except Exception as e: - logger.exception(f"Exception {e}, line : {line}") - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke( - model=model, - credentials=credentials, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.RERANK, - model_properties={}, - parameter_rules=[], - ) - - return entity diff --git a/api/core/model_runtime/model_providers/sagemaker/sagemaker.py b/api/core/model_runtime/model_providers/sagemaker/sagemaker.py deleted file mode 100644 index 042155b1522fef..00000000000000 --- a/api/core/model_runtime/model_providers/sagemaker/sagemaker.py +++ /dev/null @@ -1,41 +0,0 @@ -import logging -import uuid -from typing import IO, Any - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class SageMakerProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - pass - - -def buffer_to_s3(s3_client: Any, file: IO[bytes], bucket: str, s3_prefix: str) -> str: - """ - return s3_uri of this file - """ - s3_key = f"{s3_prefix}{uuid.uuid4()}.mp3" - s3_client.put_object(Body=file.read(), Bucket=bucket, Key=s3_key, ContentType="audio/mp3") - return s3_key - - -def generate_presigned_url(s3_client: Any, file: IO[bytes], bucket_name: str, s3_prefix: str, expiration=600) -> str: - object_key = buffer_to_s3(s3_client, file, bucket_name, s3_prefix) - try: - response = s3_client.generate_presigned_url( - "get_object", Params={"Bucket": bucket_name, "Key": object_key}, ExpiresIn=expiration - ) - except Exception as e: - print(f"Error generating presigned URL: {e}") - return None - - return response diff --git a/api/core/model_runtime/model_providers/sagemaker/sagemaker.yaml b/api/core/model_runtime/model_providers/sagemaker/sagemaker.yaml deleted file mode 100644 index 87cd50f50cbb85..00000000000000 --- a/api/core/model_runtime/model_providers/sagemaker/sagemaker.yaml +++ /dev/null @@ -1,193 +0,0 @@ -provider: sagemaker -label: - zh_Hans: Sagemaker - en_US: Sagemaker -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -description: - en_US: Customized model on Sagemaker - zh_Hans: Sagemaker上的私有化部署的模型 -background: "#ECE9E3" -help: - title: - en_US: How to deploy customized model on Sagemaker - zh_Hans: 如何在Sagemaker上的私有化部署的模型 - url: - en_US: https://github.com/aws-samples/dify-aws-tool/blob/main/README.md#how-to-deploy-sagemaker-endpoint - zh_Hans: https://github.com/aws-samples/dify-aws-tool/blob/main/README_ZH.md#%E5%A6%82%E4%BD%95%E9%83%A8%E7%BD%B2sagemaker%E6%8E%A8%E7%90%86%E7%AB%AF%E7%82%B9 -supported_model_types: - - llm - - text-embedding - - rerank - - speech2text - - tts -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: mode - show_on: - - variable: __model_type - value: llm - label: - en_US: Completion mode - type: select - required: false - default: chat - placeholder: - zh_Hans: 选择对话类型 - en_US: Select completion mode - options: - - value: chat - label: - en_US: Chat - zh_Hans: Chat - - variable: sagemaker_endpoint - label: - en_US: sagemaker endpoint - type: text-input - required: true - placeholder: - zh_Hans: 请输出你的Sagemaker推理端点 - en_US: Enter your Sagemaker Inference endpoint - - variable: audio_s3_cache_bucket - show_on: - - variable: __model_type - value: speech2text - label: - zh_Hans: 音频缓存桶(s3 bucket) - en_US: audio cache bucket(s3 bucket) - type: text-input - required: true - placeholder: - zh_Hans: sagemaker-us-east-1-******207838 - en_US: sagemaker-us-east-1-*******7838 - - variable: audio_model_type - show_on: - - variable: __model_type - value: tts - label: - en_US: Audio model type - type: select - required: true - placeholder: - zh_Hans: 语音模型类型 - en_US: Audio model type - options: - - value: PresetVoice - label: - en_US: preset voice - zh_Hans: 内置音色 - - value: CloneVoice - label: - en_US: clone voice - zh_Hans: 克隆音色 - - value: CloneVoice_CrossLingual - label: - en_US: crosslingual clone voice - zh_Hans: 跨语种克隆音色 - - value: InstructVoice - label: - en_US: Instruct voice - zh_Hans: 文字指令音色 - - variable: prompt_audio - show_on: - - variable: __model_type - value: tts - label: - en_US: Mock Audio Source - type: text-input - required: false - placeholder: - zh_Hans: 被模仿的音色音频 - en_US: source audio to be mocked - - variable: prompt_text - show_on: - - variable: __model_type - value: tts - label: - en_US: Prompt Audio Text - type: text-input - required: false - placeholder: - zh_Hans: 模仿音色的对应文本 - en_US: text for the mocked source audio - - variable: instruct_text - show_on: - - variable: __model_type - value: tts - label: - en_US: instruct text for speaker - type: text-input - required: false - - variable: aws_access_key_id - required: false - label: - en_US: Access Key (If not provided, credentials are obtained from the running environment.) - zh_Hans: Access Key (如果未提供，凭证将从运行环境中获取。) - type: secret-input - placeholder: - en_US: Enter your Access Key - zh_Hans: 在此输入您的 Access Key - - variable: aws_secret_access_key - required: false - label: - en_US: Secret Access Key - zh_Hans: Secret Access Key - type: secret-input - placeholder: - en_US: Enter your Secret Access Key - zh_Hans: 在此输入您的 Secret Access Key - - variable: aws_region - required: false - label: - en_US: AWS Region - zh_Hans: AWS 地区 - type: select - default: us-east-1 - options: - - value: us-east-1 - label: - en_US: US East (N. Virginia) - zh_Hans: 美国东部 (弗吉尼亚北部) - - value: us-west-2 - label: - en_US: US West (Oregon) - zh_Hans: 美国西部 (俄勒冈州) - - value: ap-southeast-1 - label: - en_US: Asia Pacific (Singapore) - zh_Hans: 亚太地区 (新加坡) - - value: ap-northeast-1 - label: - en_US: Asia Pacific (Tokyo) - zh_Hans: 亚太地区 (东京) - - value: eu-central-1 - label: - en_US: Europe (Frankfurt) - zh_Hans: 欧洲 (法兰克福) - - value: us-gov-west-1 - label: - en_US: AWS GovCloud (US-West) - zh_Hans: AWS GovCloud (US-West) - - value: ap-southeast-2 - label: - en_US: Asia Pacific (Sydney) - zh_Hans: 亚太地区 (悉尼) - - value: cn-north-1 - label: - en_US: AWS Beijing (cn-north-1) - zh_Hans: 中国北京 (cn-north-1) - - value: cn-northwest-1 - label: - en_US: AWS Ningxia (cn-northwest-1) - zh_Hans: 中国宁夏 (cn-northwest-1) diff --git a/api/core/model_runtime/model_providers/sagemaker/speech2text/__init__.py b/api/core/model_runtime/model_providers/sagemaker/speech2text/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/sagemaker/speech2text/speech2text.py b/api/core/model_runtime/model_providers/sagemaker/speech2text/speech2text.py deleted file mode 100644 index 6aa8c9995f68b4..00000000000000 --- a/api/core/model_runtime/model_providers/sagemaker/speech2text/speech2text.py +++ /dev/null @@ -1,125 +0,0 @@ -import json -import logging -from typing import IO, Any, Optional - -import boto3 - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel -from core.model_runtime.model_providers.sagemaker.sagemaker import generate_presigned_url - -logger = logging.getLogger(__name__) - - -class SageMakerSpeech2TextModel(Speech2TextModel): - """ - Model class for Xinference speech to text model. - """ - - sagemaker_client: Any = None - s3_client: Any = None - - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - asr_text = None - - try: - if not self.sagemaker_client: - access_key = credentials.get("aws_access_key_id") - secret_key = credentials.get("aws_secret_access_key") - aws_region = credentials.get("aws_region") - if aws_region: - if access_key and secret_key: - self.sagemaker_client = boto3.client( - "sagemaker-runtime", - aws_access_key_id=access_key, - aws_secret_access_key=secret_key, - region_name=aws_region, - ) - self.s3_client = boto3.client( - "s3", aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name=aws_region - ) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime", region_name=aws_region) - self.s3_client = boto3.client("s3", region_name=aws_region) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime") - self.s3_client = boto3.client("s3") - - s3_prefix = "dify/speech2text/" - sagemaker_endpoint = credentials.get("sagemaker_endpoint") - bucket = credentials.get("audio_s3_cache_bucket") - - s3_presign_url = generate_presigned_url(self.s3_client, file, bucket, s3_prefix) - payload = {"audio_s3_presign_uri": s3_presign_url} - - response_model = self.sagemaker_client.invoke_endpoint( - EndpointName=sagemaker_endpoint, Body=json.dumps(payload), ContentType="application/json" - ) - json_str = response_model["Body"].read().decode("utf8") - json_obj = json.loads(json_str) - asr_text = json_obj["text"] - except Exception as e: - logger.exception(f"Exception {e}, line : {line}") - - return asr_text - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - pass - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.SPEECH2TEXT, - model_properties={}, - parameter_rules=[], - ) - - return entity diff --git a/api/core/model_runtime/model_providers/sagemaker/text_embedding/__init__.py b/api/core/model_runtime/model_providers/sagemaker/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/sagemaker/tts/__init__.py b/api/core/model_runtime/model_providers/sagemaker/tts/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/sagemaker/tts/tts.py b/api/core/model_runtime/model_providers/sagemaker/tts/tts.py deleted file mode 100644 index a22bd6dd6ef4f8..00000000000000 --- a/api/core/model_runtime/model_providers/sagemaker/tts/tts.py +++ /dev/null @@ -1,275 +0,0 @@ -import concurrent.futures -import copy -import json -import logging -from enum import Enum -from typing import Any, Optional - -import boto3 -import requests - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.model_providers.__base.tts_model import TTSModel - -logger = logging.getLogger(__name__) - - -class TTSModelType(Enum): - PresetVoice = "PresetVoice" - CloneVoice = "CloneVoice" - CloneVoice_CrossLingual = "CloneVoice_CrossLingual" - InstructVoice = "InstructVoice" - - -class SageMakerText2SpeechModel(TTSModel): - sagemaker_client: Any = None - s3_client: Any = None - comprehend_client: Any = None - - def __init__(self): - # preset voices, need support custom voice - self.model_voices = { - "__default": { - "all": [ - {"name": "Default", "value": "default"}, - ] - }, - "CosyVoice": { - "zh-Hans": [ - {"name": "中文男", "value": "中文男"}, - {"name": "中文女", "value": "中文女"}, - {"name": "粤语女", "value": "粤语女"}, - ], - "zh-Hant": [ - {"name": "中文男", "value": "中文男"}, - {"name": "中文女", "value": "中文女"}, - {"name": "粤语女", "value": "粤语女"}, - ], - "en-US": [ - {"name": "英文男", "value": "英文男"}, - {"name": "英文女", "value": "英文女"}, - ], - "ja-JP": [ - {"name": "日语男", "value": "日语男"}, - ], - "ko-KR": [ - {"name": "韩语女", "value": "韩语女"}, - ], - }, - } - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - pass - - def _detect_lang_code(self, content: str, map_dict: dict = None): - map_dict = {"zh": "<|zh|>", "en": "<|en|>", "ja": "<|jp|>", "zh-TW": "<|yue|>", "ko": "<|ko|>"} - - response = self.comprehend_client.detect_dominant_language(Text=content) - language_code = response["Languages"][0]["LanguageCode"] - - return map_dict.get(language_code, "<|zh|>") - - def _build_tts_payload( - self, - model_type: str, - content_text: str, - model_role: str, - prompt_text: str, - prompt_audio: str, - instruct_text: str, - ): - if model_type == TTSModelType.PresetVoice.value and model_role: - return {"tts_text": content_text, "role": model_role} - if model_type == TTSModelType.CloneVoice.value and prompt_text and prompt_audio: - return {"tts_text": content_text, "prompt_text": prompt_text, "prompt_audio": prompt_audio} - if model_type == TTSModelType.CloneVoice_CrossLingual.value and prompt_audio: - lang_tag = self._detect_lang_code(content_text) - return {"tts_text": f"{content_text}", "prompt_audio": prompt_audio, "lang_tag": lang_tag} - if model_type == TTSModelType.InstructVoice.value and instruct_text and model_role: - return {"tts_text": content_text, "role": model_role, "instruct_text": instruct_text} - - raise RuntimeError(f"Invalid params for {model_type}") - - def _invoke( - self, model: str, tenant_id: str, credentials: dict, content_text: str, voice: str, user: Optional[str] = None - ): - """ - _invoke text2speech model - - :param model: model name - :param tenant_id: user tenant id - :param credentials: model credentials - :param voice: model timbre - :param content_text: text content to be translated - :param user: unique user id - :return: text translated to audio file - """ - if not self.sagemaker_client: - access_key = credentials.get("aws_access_key_id") - secret_key = credentials.get("aws_secret_access_key") - aws_region = credentials.get("aws_region") - if aws_region: - if access_key and secret_key: - self.sagemaker_client = boto3.client( - "sagemaker-runtime", - aws_access_key_id=access_key, - aws_secret_access_key=secret_key, - region_name=aws_region, - ) - self.s3_client = boto3.client( - "s3", aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name=aws_region - ) - self.comprehend_client = boto3.client( - "comprehend", - aws_access_key_id=access_key, - aws_secret_access_key=secret_key, - region_name=aws_region, - ) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime", region_name=aws_region) - self.s3_client = boto3.client("s3", region_name=aws_region) - self.comprehend_client = boto3.client("comprehend", region_name=aws_region) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime") - self.s3_client = boto3.client("s3") - self.comprehend_client = boto3.client("comprehend") - - model_type = credentials.get("audio_model_type", "PresetVoice") - prompt_text = credentials.get("prompt_text") - prompt_audio = credentials.get("prompt_audio") - instruct_text = credentials.get("instruct_text") - sagemaker_endpoint = credentials.get("sagemaker_endpoint") - payload = self._build_tts_payload(model_type, content_text, voice, prompt_text, prompt_audio, instruct_text) - - return self._tts_invoke_streaming(model_type, payload, sagemaker_endpoint) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TTS, - model_properties={}, - parameter_rules=[], - ) - - return entity - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError], - } - - def _get_model_default_voice(self, model: str, credentials: dict) -> any: - return "" - - def _get_model_word_limit(self, model: str, credentials: dict) -> int: - return 15 - - def _get_model_audio_type(self, model: str, credentials: dict) -> str: - return "mp3" - - def _get_model_workers_limit(self, model: str, credentials: dict) -> int: - return 5 - - def get_tts_model_voices(self, model: str, credentials: dict, language: Optional[str] = None) -> list: - audio_model_name = "CosyVoice" - for key, voices in self.model_voices.items(): - if key in audio_model_name: - if language and language in voices: - return voices[language] - elif "all" in voices: - return voices["all"] - - return self.model_voices["__default"]["all"] - - def _invoke_sagemaker(self, payload: dict, endpoint: str): - response_model = self.sagemaker_client.invoke_endpoint( - EndpointName=endpoint, - Body=json.dumps(payload), - ContentType="application/json", - ) - json_str = response_model["Body"].read().decode("utf8") - json_obj = json.loads(json_str) - return json_obj - - def _tts_invoke_streaming(self, model_type: str, payload: dict, sagemaker_endpoint: str) -> any: - """ - _tts_invoke_streaming text2speech model - - :param model: model name - :param credentials: model credentials - :param content_text: text content to be translated - :param voice: model timbre - :return: text translated to audio file - """ - try: - lang_tag = "" - if model_type == TTSModelType.CloneVoice_CrossLingual.value: - lang_tag = payload.pop("lang_tag") - - word_limit = self._get_model_word_limit(model="", credentials={}) - content_text = payload.get("tts_text") - if len(content_text) > word_limit: - split_sentences = self._split_text_into_sentences(content_text, max_length=word_limit) - sentences = [f"{lang_tag}{s}" for s in split_sentences if len(s)] - len_sent = len(sentences) - executor = concurrent.futures.ThreadPoolExecutor(max_workers=min(4, len_sent)) - payloads = [copy.deepcopy(payload) for i in range(len_sent)] - for idx in range(len_sent): - payloads[idx]["tts_text"] = sentences[idx] - - futures = [ - executor.submit( - self._invoke_sagemaker, - payload=payload, - endpoint=sagemaker_endpoint, - ) - for payload in payloads - ] - - for future in futures: - resp = future.result() - audio_bytes = requests.get(resp.get("s3_presign_url")).content - for i in range(0, len(audio_bytes), 1024): - yield audio_bytes[i : i + 1024] - else: - resp = self._invoke_sagemaker(payload, sagemaker_endpoint) - audio_bytes = requests.get(resp.get("s3_presign_url")).content - - for i in range(0, len(audio_bytes), 1024): - yield audio_bytes[i : i + 1024] - except Exception as ex: - raise InvokeBadRequestError(str(ex)) diff --git a/api/core/model_runtime/model_providers/siliconflow/_assets/siliconflow.svg b/api/core/model_runtime/model_providers/siliconflow/_assets/siliconflow.svg deleted file mode 100644 index 16e406f030225b..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/_assets/siliconflow.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/siliconflow/_assets/siliconflow_square.svg b/api/core/model_runtime/model_providers/siliconflow/_assets/siliconflow_square.svg deleted file mode 100644 index ad6b384f7acd21..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/_assets/siliconflow_square.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/deepdeek-coder-v2-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/deepdeek-coder-v2-instruct.yaml deleted file mode 100644 index d4431179e5656d..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/deepdeek-coder-v2-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: deepseek-ai/DeepSeek-Coder-V2-Instruct -label: - en_US: deepseek-ai/DeepSeek-Coder-V2-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1.33' - output: '1.33' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/deepseek-v2-chat.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/deepseek-v2-chat.yaml deleted file mode 100644 index caa6508b5ed2a2..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/deepseek-v2-chat.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: deepseek-ai/DeepSeek-V2-Chat -label: - en_US: deepseek-ai/DeepSeek-V2-Chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1.33' - output: '1.33' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/deepseek-v2.5.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/deepseek-v2.5.yaml deleted file mode 100644 index 1c8e15ae52afa7..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/deepseek-v2.5.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: deepseek-ai/DeepSeek-V2.5 -label: - en_US: deepseek-ai/DeepSeek-V2.5 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1.33' - output: '1.33' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-27b-it.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-27b-it.yaml deleted file mode 100644 index 2840e3dcf4b113..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-27b-it.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: google/gemma-2-27b-it -label: - en_US: google/gemma-2-27b-it -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8196 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1.26' - output: '1.26' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-9b-it.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-9b-it.yaml deleted file mode 100644 index d7e19b46f6d6f2..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-9b-it.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: google/gemma-2-9b-it -label: - en_US: google/gemma-2-9b-it -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8196 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/glm4-9b-chat.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/glm4-9b-chat.yaml deleted file mode 100644 index 9b32a024774d06..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/glm4-9b-chat.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: THUDM/glm-4-9b-chat -label: - en_US: THUDM/glm-4-9b-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-7b-chat.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-7b-chat.yaml deleted file mode 100644 index 73ad4480aa2968..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-7b-chat.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: internlm/internlm2_5-7b-chat -label: - en_US: internlm/internlm2_5-7b-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/llm.py b/api/core/model_runtime/model_providers/siliconflow/llm/llm.py deleted file mode 100644 index c1868b6ad02b83..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/llm.py +++ /dev/null @@ -1,31 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class SiliconflowLargeLanguageModel(OAIAPICompatLargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials) - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - @classmethod - def _add_custom_parameters(cls, credentials: dict) -> None: - credentials["mode"] = "chat" - credentials["endpoint_url"] = "https://api.siliconflow.cn/v1" diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-70b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-70b-instruct.yaml deleted file mode 100644 index 9993d781ac8959..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-70b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: meta-llama/Meta-Llama-3-70B-Instruct -label: - en_US: meta-llama/Meta-Llama-3-70B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '4.13' - output: '4.13' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-8b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-8b-instruct.yaml deleted file mode 100644 index 60e3764789e1f5..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-8b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: meta-llama/Meta-Llama-3-8B-Instruct -label: - en_US: meta-llama/Meta-Llama-3-8B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-405b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-405b-instruct.yaml deleted file mode 100644 index f992660aa2e66f..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-405b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: meta-llama/Meta-Llama-3.1-405B-Instruct -label: - en_US: meta-llama/Meta-Llama-3.1-405B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '21' - output: '21' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-70b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-70b-instruct.yaml deleted file mode 100644 index 1c69d63a400219..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-70b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: meta-llama/Meta-Llama-3.1-70B-Instruct -label: - en_US: meta-llama/Meta-Llama-3.1-70B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '4.13' - output: '4.13' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-8b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-8b-instruct.yaml deleted file mode 100644 index a97002a5ca3658..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-8b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: meta-llama/Meta-Llama-3.1-8B-Instruct -label: - en_US: meta-llama/Meta-Llama-3.1-8B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/mistral-7b-instruct-v0.2.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/mistral-7b-instruct-v0.2.yaml deleted file mode 100644 index 89fb153ba09ac9..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/mistral-7b-instruct-v0.2.yaml +++ /dev/null @@ -1,31 +0,0 @@ -model: mistralai/Mistral-7B-Instruct-v0.2 -label: - en_US: mistralai/Mistral-7B-Instruct-v0.2 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/mistral-8x7b-instruct-v0.1.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/mistral-8x7b-instruct-v0.1.yaml deleted file mode 100644 index 2785e7496fb060..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/mistral-8x7b-instruct-v0.1.yaml +++ /dev/null @@ -1,31 +0,0 @@ -model: mistralai/Mixtral-8x7B-Instruct-v0.1 -label: - en_US: mistralai/Mixtral-8x7B-Instruct-v0.1 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1.26' - output: '1.26' - unit: '0.000001' - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-1.5b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-1.5b-instruct.yaml deleted file mode 100644 index f6c976af8e7b6e..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-1.5b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: Qwen/Qwen2-1.5B-Instruct -label: - en_US: Qwen/Qwen2-1.5B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-57b-a14b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-57b-a14b-instruct.yaml deleted file mode 100644 index a996e919ea9f27..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-57b-a14b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: Qwen/Qwen2-57B-A14B-Instruct -label: - en_US: Qwen/Qwen2-57B-A14B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1.26' - output: '1.26' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-72b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-72b-instruct.yaml deleted file mode 100644 index a6e2c22dac87c0..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-72b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: Qwen/Qwen2-72B-Instruct -label: - en_US: Qwen/Qwen2-72B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '4.13' - output: '4.13' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-7b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-7b-instruct.yaml deleted file mode 100644 index d8bea5e12927e7..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-7b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: Qwen/Qwen2-7B-Instruct -label: - en_US: Qwen/Qwen2-7B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-14b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-14b-instruct.yaml deleted file mode 100644 index 02a401464bb8c0..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-14b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: Qwen/Qwen2.5-14B-Instruct -label: - en_US: Qwen/Qwen2.5-14B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 8192 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0.7' - output: '0.7' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-32b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-32b-instruct.yaml deleted file mode 100644 index d084617e7d7366..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-32b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: Qwen/Qwen2.5-32B-Instruct -label: - en_US: Qwen/Qwen2.5-32B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 8192 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1.26' - output: '1.26' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-72b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-72b-instruct.yaml deleted file mode 100644 index dfbad2494cdf74..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-72b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: Qwen/Qwen2.5-72B-Instruct -label: - en_US: Qwen/Qwen2.5-72B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 8192 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '4.13' - output: '4.13' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-7b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-7b-instruct.yaml deleted file mode 100644 index cdc8ffc4d21041..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-7b-instruct.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: Qwen/Qwen2.5-7B-Instruct -label: - en_US: Qwen/Qwen2.5-7B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 8192 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-34b-chat.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-34b-chat.yaml deleted file mode 100644 index 864ba46f1adfdf..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-34b-chat.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: 01-ai/Yi-1.5-34B-Chat -label: - en_US: 01-ai/Yi-1.5-34B-Chat-16K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1.26' - output: '1.26' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-6b-chat.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-6b-chat.yaml deleted file mode 100644 index fe4c8b4b3e0350..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-6b-chat.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: 01-ai/Yi-1.5-6B-Chat -label: - en_US: 01-ai/Yi-1.5-6B-Chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-9b-chat.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-9b-chat.yaml deleted file mode 100644 index c61f0dc53fe6ec..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-9b-chat.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: 01-ai/Yi-1.5-9B-Chat-16K -label: - en_US: 01-ai/Yi-1.5-9B-Chat-16K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/rerank/__init__.py b/api/core/model_runtime/model_providers/siliconflow/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/siliconflow/rerank/bce-reranker-base_v1.yaml b/api/core/model_runtime/model_providers/siliconflow/rerank/bce-reranker-base_v1.yaml deleted file mode 100644 index ff3635bfeb1273..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/rerank/bce-reranker-base_v1.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: netease-youdao/bce-reranker-base_v1 -model_type: rerank -model_properties: - context_size: 512 diff --git a/api/core/model_runtime/model_providers/siliconflow/rerank/bge-reranker-v2-m3.yaml b/api/core/model_runtime/model_providers/siliconflow/rerank/bge-reranker-v2-m3.yaml deleted file mode 100644 index 807f531b084892..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/rerank/bge-reranker-v2-m3.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: BAAI/bge-reranker-v2-m3 -model_type: rerank -model_properties: - context_size: 8192 diff --git a/api/core/model_runtime/model_providers/siliconflow/rerank/rerank.py b/api/core/model_runtime/model_providers/siliconflow/rerank/rerank.py deleted file mode 100644 index 58b033d28aa90e..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/rerank/rerank.py +++ /dev/null @@ -1,85 +0,0 @@ -from typing import Optional - -import httpx - -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - - -class SiliconflowRerankModel(RerankModel): - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - if len(docs) == 0: - return RerankResult(model=model, docs=[]) - - base_url = credentials.get("base_url", "https://api.siliconflow.cn/v1") - base_url = base_url.removesuffix("/") - try: - response = httpx.post( - base_url + "/rerank", - json={"model": model, "query": query, "documents": docs, "top_n": top_n, "return_documents": True}, - headers={"Authorization": f"Bearer {credentials.get('api_key')}"}, - ) - response.raise_for_status() - results = response.json() - - rerank_documents = [] - for result in results["results"]: - rerank_document = RerankDocument( - index=result["index"], - text=result["document"]["text"], - score=result["relevance_score"], - ) - if score_threshold is None or result["relevance_score"] >= score_threshold: - rerank_documents.append(rerank_document) - - return RerankResult(model=model, docs=rerank_documents) - except httpx.HTTPStatusError as e: - raise InvokeServerUnavailableError(str(e)) - - def validate_credentials(self, model: str, credentials: dict) -> None: - try: - self._invoke( - model=model, - credentials=credentials, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - """ - return { - InvokeConnectionError: [httpx.ConnectError], - InvokeServerUnavailableError: [httpx.RemoteProtocolError], - InvokeRateLimitError: [], - InvokeAuthorizationError: [httpx.HTTPStatusError], - InvokeBadRequestError: [httpx.RequestError], - } diff --git a/api/core/model_runtime/model_providers/siliconflow/siliconflow.py b/api/core/model_runtime/model_providers/siliconflow/siliconflow.py deleted file mode 100644 index e121ab8c7e4e2f..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/siliconflow.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class SiliconflowProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="deepseek-ai/DeepSeek-V2-Chat", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/siliconflow/siliconflow.yaml b/api/core/model_runtime/model_providers/siliconflow/siliconflow.yaml deleted file mode 100644 index c46a891604c480..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/siliconflow.yaml +++ /dev/null @@ -1,32 +0,0 @@ -provider: siliconflow -label: - zh_Hans: 硅基流动 - en_US: SiliconFlow -icon_small: - en_US: siliconflow_square.svg -icon_large: - en_US: siliconflow.svg -background: "#ffecff" -help: - title: - en_US: Get your API Key from SiliconFlow - zh_Hans: 从 SiliconFlow 获取 API Key - url: - en_US: https://cloud.siliconflow.cn/account/ak -supported_model_types: - - llm - - text-embedding - - rerank - - speech2text -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/siliconflow/speech2text/__init__.py b/api/core/model_runtime/model_providers/siliconflow/speech2text/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/siliconflow/speech2text/sense-voice-small.yaml b/api/core/model_runtime/model_providers/siliconflow/speech2text/sense-voice-small.yaml deleted file mode 100644 index deceaf60f4f017..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/speech2text/sense-voice-small.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: iic/SenseVoiceSmall -model_type: speech2text -model_properties: - file_upload_limit: 1 - supported_file_extensions: mp3,wav diff --git a/api/core/model_runtime/model_providers/siliconflow/speech2text/speech2text.py b/api/core/model_runtime/model_providers/siliconflow/speech2text/speech2text.py deleted file mode 100644 index 8d1932863e09d9..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/speech2text/speech2text.py +++ /dev/null @@ -1,30 +0,0 @@ -from typing import IO, Optional - -from core.model_runtime.model_providers.openai_api_compatible.speech2text.speech2text import OAICompatSpeech2TextModel - - -class SiliconflowSpeech2TextModel(OAICompatSpeech2TextModel): - """ - Model class for Siliconflow Speech to text model. - """ - - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - self._add_custom_parameters(credentials) - return super()._invoke(model, credentials, file) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - return super().validate_credentials(model, credentials) - - @classmethod - def _add_custom_parameters(cls, credentials: dict) -> None: - credentials["endpoint_url"] = "https://api.siliconflow.cn/v1" diff --git a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bce-embedding-base-v1.yaml b/api/core/model_runtime/model_providers/siliconflow/text_embedding/bce-embedding-base-v1.yaml deleted file mode 100644 index 710fbc04f6ad12..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bce-embedding-base-v1.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: netease-youdao/bce-embedding-base_v1 -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 1 diff --git a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-en-v1.5.yaml b/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-en-v1.5.yaml deleted file mode 100644 index 84f69b41a08c13..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-en-v1.5.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: BAAI/bge-large-en-v1.5 -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 1 diff --git a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-zh-v1.5.yaml b/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-zh-v1.5.yaml deleted file mode 100644 index 5248375d0b507e..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-zh-v1.5.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: BAAI/bge-large-zh-v1.5 -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 1 diff --git a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-m3.yaml b/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-m3.yaml deleted file mode 100644 index f0b12dd420ab2b..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-m3.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: BAAI/bge-m3 -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 1 diff --git a/api/core/model_runtime/model_providers/spark/__init__.py b/api/core/model_runtime/model_providers/spark/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/spark/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/spark/_assets/icon_l_en.svg deleted file mode 100644 index 521c68cae52a78..00000000000000 --- a/api/core/model_runtime/model_providers/spark/_assets/icon_l_en.svg +++ /dev/null @@ -1,24 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/spark/_assets/icon_l_zh.svg b/api/core/model_runtime/model_providers/spark/_assets/icon_l_zh.svg deleted file mode 100644 index 71d85216aaa691..00000000000000 --- a/api/core/model_runtime/model_providers/spark/_assets/icon_l_zh.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/spark/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/spark/_assets/icon_s_en.svg deleted file mode 100644 index ef0a9131a48e43..00000000000000 --- a/api/core/model_runtime/model_providers/spark/_assets/icon_s_en.svg +++ /dev/null @@ -1,5 +0,0 @@ - - - - - diff --git a/api/core/model_runtime/model_providers/spark/llm/__init__.py b/api/core/model_runtime/model_providers/spark/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/spark/llm/_client.py b/api/core/model_runtime/model_providers/spark/llm/_client.py deleted file mode 100644 index 48911f657a52e3..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/_client.py +++ /dev/null @@ -1,163 +0,0 @@ -import base64 -import hashlib -import hmac -import json -import queue -import ssl -from datetime import datetime -from time import mktime -from typing import Optional -from urllib.parse import urlencode, urlparse -from wsgiref.handlers import format_date_time - -import websocket - - -class SparkLLMClient: - def __init__(self, model: str, app_id: str, api_key: str, api_secret: str, api_domain: Optional[str] = None): - domain = "spark-api.xf-yun.com" - endpoint = "chat" - if api_domain: - domain = api_domain - - model_api_configs = { - "spark-lite": {"version": "v1.1", "chat_domain": "general"}, - "spark-pro": {"version": "v3.1", "chat_domain": "generalv3"}, - "spark-pro-128k": {"version": "pro-128k", "chat_domain": "pro-128k"}, - "spark-max": {"version": "v3.5", "chat_domain": "generalv3.5"}, - "spark-max-32k": {"version": "max-32k", "chat_domain": "max-32k"}, - "spark-4.0-ultra": {"version": "v4.0", "chat_domain": "4.0Ultra"}, - } - - api_version = model_api_configs[model]["version"] - - self.chat_domain = model_api_configs[model]["chat_domain"] - - if model in ["spark-pro-128k", "spark-max-32k"]: - self.api_base = f"wss://{domain}/{endpoint}/{api_version}" - else: - self.api_base = f"wss://{domain}/{api_version}/{endpoint}" - - self.app_id = app_id - self.ws_url = self.create_url( - urlparse(self.api_base).netloc, urlparse(self.api_base).path, self.api_base, api_key, api_secret - ) - - self.queue = queue.Queue() - self.blocking_message = "" - - def create_url(self, host: str, path: str, api_base: str, api_key: str, api_secret: str) -> str: - # generate timestamp by RFC1123 - now = datetime.now() - date = format_date_time(mktime(now.timetuple())) - - signature_origin = "host: " + host + "\n" - signature_origin += "date: " + date + "\n" - signature_origin += "GET " + path + " HTTP/1.1" - - # encrypt using hmac-sha256 - signature_sha = hmac.new( - api_secret.encode("utf-8"), signature_origin.encode("utf-8"), digestmod=hashlib.sha256 - ).digest() - - signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding="utf-8") - - authorization_origin = ( - f'api_key="{api_key}", algorithm="hmac-sha256", headers="host date request-line",' - f' signature="{signature_sha_base64}"' - ) - - authorization = base64.b64encode(authorization_origin.encode("utf-8")).decode(encoding="utf-8") - - v = {"authorization": authorization, "date": date, "host": host} - # generate url - url = api_base + "?" + urlencode(v) - return url - - def run(self, messages: list, user_id: str, model_kwargs: Optional[dict] = None, streaming: bool = False): - websocket.enableTrace(False) - ws = websocket.WebSocketApp( - self.ws_url, - on_message=self.on_message, - on_error=self.on_error, - on_close=self.on_close, - on_open=self.on_open, - ) - ws.messages = messages - ws.user_id = user_id - ws.model_kwargs = model_kwargs - ws.streaming = streaming - ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE}) - - def on_error(self, ws, error): - self.queue.put({"status_code": error.status_code, "error": error.resp_body.decode("utf-8")}) - ws.close() - - def on_close(self, ws, close_status_code, close_reason): - self.queue.put({"done": True}) - - def on_open(self, ws): - self.blocking_message = "" - data = json.dumps(self.gen_params(messages=ws.messages, user_id=ws.user_id, model_kwargs=ws.model_kwargs)) - ws.send(data) - - def on_message(self, ws, message): - data = json.loads(message) - code = data["header"]["code"] - if code != 0: - self.queue.put({"status_code": 400, "error": f"Code: {code}, Error: {data['header']['message']}"}) - ws.close() - else: - choices = data["payload"]["choices"] - status = choices["status"] - content = choices["text"][0]["content"] - if ws.streaming: - self.queue.put({"data": content}) - else: - self.blocking_message += content - - if status == 2: - if not ws.streaming: - self.queue.put({"data": self.blocking_message}) - ws.close() - - def gen_params(self, messages: list, user_id: str, model_kwargs: Optional[dict] = None) -> dict: - data = { - "header": { - "app_id": self.app_id, - # resolve this error message => $.header.uid' length must be less or equal than 32 - "uid": user_id[:32] if user_id else None, - }, - "parameter": {"chat": {"domain": self.chat_domain}}, - "payload": {"message": {"text": messages}}, - } - - if model_kwargs: - data["parameter"]["chat"].update(model_kwargs) - - return data - - def subscribe(self): - while True: - content = self.queue.get() - if "error" in content: - if content["status_code"] == 401: - raise SparkError( - "[Spark] The credentials you provided are incorrect. " - "Please double-check and fill them in again." - ) - elif content["status_code"] == 403: - raise SparkError( - "[Spark] Sorry, the credentials you provided are access denied. " - "Please try again after obtaining the necessary permissions." - ) - else: - raise SparkError(f"[Spark] code: {content['status_code']}, error: {content['error']}") - - if "data" not in content: - break - yield content - - -class SparkError(Exception): - pass diff --git a/api/core/model_runtime/model_providers/spark/llm/_position.yaml b/api/core/model_runtime/model_providers/spark/llm/_position.yaml deleted file mode 100644 index 73f39cb1197b48..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/_position.yaml +++ /dev/null @@ -1,11 +0,0 @@ -- spark-max-32k -- spark-4.0-ultra -- spark-max -- spark-pro-128k -- spark-pro -- spark-lite -- spark-4 -- spark-3.5 -- spark-3 -- spark-1.5 -- spark-2 diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-1.5.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-1.5.yaml deleted file mode 100644 index fcd65c24e0f60c..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-1.5.yaml +++ /dev/null @@ -1,34 +0,0 @@ -model: spark-1.5 -deprecated: true -label: - en_US: Spark V1.5 -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: 模型回答的tokens的最大长度。 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-2.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-2.yaml deleted file mode 100644 index 2db6805a2e2af0..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-2.yaml +++ /dev/null @@ -1,34 +0,0 @@ -model: spark-2 -deprecated: true -label: - en_US: Spark V2.0 -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 2048 - min: 1 - max: 8192 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: 模型回答的tokens的最大长度。 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-3.5.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-3.5.yaml deleted file mode 100644 index 86617a53d0d4fb..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-3.5.yaml +++ /dev/null @@ -1,34 +0,0 @@ -model: spark-3.5 -deprecated: true -label: - en_US: Spark V3.5 -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 2048 - min: 1 - max: 8192 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: 模型回答的tokens的最大长度。 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-3.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-3.yaml deleted file mode 100644 index 9f296c684db78d..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-3.yaml +++ /dev/null @@ -1,34 +0,0 @@ -model: spark-3 -deprecated: true -label: - en_US: Spark V3.0 -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 2048 - min: 1 - max: 8192 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: 模型回答的tokens的最大长度。 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-4.0-ultra.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-4.0-ultra.yaml deleted file mode 100644 index bbf85764f1c8c1..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-4.0-ultra.yaml +++ /dev/null @@ -1,42 +0,0 @@ -model: spark-4.0-ultra -label: - en_US: Spark 4.0 Ultra -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 1 - max: 8192 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: Maximum length of tokens for the model response. - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false - - name: show_ref_label - label: - zh_Hans: 联网检索 - en_US: web search - type: boolean - default: false - help: - zh_Hans: 该参数仅4.0 Ultra版本支持，当设置为true时，如果输入内容触发联网检索插件，会先返回检索信源列表，然后再返回星火回复结果，否则仅返回星火回复结果 - en_US: The parameter is only supported in the 4.0 Ultra version. When set to true, if the input triggers the online search plugin, it will first return a list of search sources and then return the Spark response. Otherwise, it will only return the Spark response. diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-4.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-4.yaml deleted file mode 100644 index 4b5529e81c0602..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-4.yaml +++ /dev/null @@ -1,34 +0,0 @@ -model: spark-4 -deprecated: true -label: - en_US: Spark V4.0 -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 1 - max: 8192 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: 模型回答的tokens的最大长度。 - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-lite.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-lite.yaml deleted file mode 100644 index 1f6141a816b8e1..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-lite.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: spark-lite -label: - en_US: Spark Lite -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: Maximum length of tokens for the model response. - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-max-32k.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-max-32k.yaml deleted file mode 100644 index 1a1ab6844c69c5..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-max-32k.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: spark-max-32k -label: - en_US: Spark Max-32K -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 1 - max: 8192 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: Maximum length of tokens for the model response. - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-max.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-max.yaml deleted file mode 100644 index 71eb2b86d36ac4..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-max.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: spark-max -label: - en_US: Spark Max -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 1 - max: 8192 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: Maximum length of tokens for the model response. - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-pro-128k.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-pro-128k.yaml deleted file mode 100644 index da1fead6da940d..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-pro-128k.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: spark-pro-128k -label: - en_US: Spark Pro-128K -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: Maximum length of tokens for the model response. - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/llm/spark-pro.yaml b/api/core/model_runtime/model_providers/spark/llm/spark-pro.yaml deleted file mode 100644 index 9ee479f15b0504..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/spark-pro.yaml +++ /dev/null @@ -1,33 +0,0 @@ -model: spark-pro -label: - en_US: Spark Pro -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.5 - help: - zh_Hans: 核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。 - en_US: Kernel sampling threshold. Used to determine the randomness of the results. The higher the value, the stronger the randomness, that is, the higher the possibility of getting different answers to the same question. - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 1 - max: 8192 - help: - zh_Hans: 模型回答的tokens的最大长度。 - en_US: Maximum length of tokens for the model response. - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - default: 4 - min: 1 - max: 6 - help: - zh_Hans: 从 k 个候选中随机选择一个（非等概率）。 - en_US: Randomly select one from k candidates (non-equal probability). - required: false diff --git a/api/core/model_runtime/model_providers/spark/spark.py b/api/core/model_runtime/model_providers/spark/spark.py deleted file mode 100644 index b3695e0501cd8a..00000000000000 --- a/api/core/model_runtime/model_providers/spark/spark.py +++ /dev/null @@ -1,18 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class SparkProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - # ignore credentials validation because every model has their own spark quota pool - pass diff --git a/api/core/model_runtime/model_providers/spark/spark.yaml b/api/core/model_runtime/model_providers/spark/spark.yaml deleted file mode 100644 index 3b07b30f2472be..00000000000000 --- a/api/core/model_runtime/model_providers/spark/spark.yaml +++ /dev/null @@ -1,46 +0,0 @@ -provider: spark -label: - zh_Hans: 讯飞星火 - en_US: iFLYTEK SPARK -icon_small: - en_US: icon_s_en.svg -icon_large: - zh_Hans: icon_l_zh.svg - en_US: icon_l_en.svg -background: "#EBF8FF" -help: - title: - en_US: Get your API key from iFLYTEK SPARK - zh_Hans: 从讯飞星火获取 API Keys - url: - en_US: https://www.xfyun.cn/solutions/xinghuoAPI -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: app_id - label: - en_US: APPID - type: text-input - required: true - placeholder: - zh_Hans: 在此输入您的 APPID - en_US: Enter your APPID - - variable: api_secret - label: - en_US: APISecret - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 APISecret - en_US: Enter your APISecret - - variable: api_key - label: - en_US: APIKey - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 APIKey - en_US: Enter your APIKey diff --git a/api/core/model_runtime/model_providers/stepfun/__init__.py b/api/core/model_runtime/model_providers/stepfun/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/stepfun/_assets/icon_l_en.png b/api/core/model_runtime/model_providers/stepfun/_assets/icon_l_en.png deleted file mode 100644 index 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self._add_function_call(model, credentials) - user = user[:32] if user else None - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - return AIModelEntity( - model=model, - label=I18nObject(en_US=model, zh_Hans=model), - model_type=ModelType.LLM, - features=[ModelFeature.TOOL_CALL, ModelFeature.MULTI_TOOL_CALL, ModelFeature.STREAM_TOOL_CALL] - if credentials.get("function_calling_type") == "tool_call" - else [], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", 8000)), - ModelPropertyKey.MODE: LLMMode.CHAT.value, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - use_template="temperature", - label=I18nObject(en_US="Temperature", zh_Hans="温度"), - type=ParameterType.FLOAT, - ), - ParameterRule( - name="max_tokens", - use_template="max_tokens", - default=512, - min=1, - max=int(credentials.get("max_tokens", 1024)), - label=I18nObject(en_US="Max Tokens", zh_Hans="最大标记"), - type=ParameterType.INT, - ), - ParameterRule( - name="top_p", - use_template="top_p", - label=I18nObject(en_US="Top P", zh_Hans="Top P"), - type=ParameterType.FLOAT, - ), - ], - ) - - def _add_custom_parameters(self, credentials: dict) -> None: - credentials["mode"] = "chat" - credentials["endpoint_url"] = "https://api.stepfun.com/v1" - - def _add_function_call(self, model: str, credentials: dict) -> None: - model_schema = self.get_model_schema(model, credentials) - if model_schema and {ModelFeature.TOOL_CALL, ModelFeature.MULTI_TOOL_CALL}.intersection( - model_schema.features or [] - ): - credentials["function_calling_type"] = "tool_call" - - def _convert_prompt_message_to_dict(self, message: PromptMessage, credentials: Optional[dict] = None) -> dict: - """ - Convert PromptMessage to dict for OpenAI API format - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(PromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": { - "url": message_content.data, - }, - } - sub_messages.append(sub_message_dict) - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls: - message_dict["tool_calls"] = [] - for function_call in message.tool_calls: - message_dict["tool_calls"].append( - { - "id": function_call.id, - "type": function_call.type, - "function": { - "name": function_call.function.name, - "arguments": function_call.function.arguments, - }, - } - ) - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = {"role": "tool", "content": message.content, "tool_call_id": message.tool_call_id} - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - else: - raise ValueError(f"Got unknown type {message}") - - if message.name: - message_dict["name"] = message.name - - return message_dict - - def _extract_response_tool_calls(self, response_tool_calls: list[dict]) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_tool_calls: - for response_tool_call in response_tool_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call["function"]["name"] - if response_tool_call.get("function", {}).get("name") - else "", - arguments=response_tool_call["function"]["arguments"] - if response_tool_call.get("function", {}).get("arguments") - else "", - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call["id"] if response_tool_call.get("id") else "", - type=response_tool_call["type"] if response_tool_call.get("type") else "", - function=function, - ) - tool_calls.append(tool_call) - - return tool_calls - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: requests.Response, prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param credentials: model credentials - :param response: streamed response - :param prompt_messages: prompt messages - :return: llm response chunk generator - """ - full_assistant_content = "" - chunk_index = 0 - - def create_final_llm_result_chunk( - index: int, message: AssistantPromptMessage, finish_reason: str - ) -> LLMResultChunk: - # calculate num tokens - prompt_tokens = self._num_tokens_from_string(model, prompt_messages[0].content) - completion_tokens = self._num_tokens_from_string(model, full_assistant_content) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - return LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=message, finish_reason=finish_reason, usage=usage), - ) - - tools_calls: list[AssistantPromptMessage.ToolCall] = [] - finish_reason = "Unknown" - - def increase_tool_call(new_tool_calls: list[AssistantPromptMessage.ToolCall]): - def get_tool_call(tool_name: str): - if not tool_name: - return tools_calls[-1] - - tool_call = next((tool_call for tool_call in tools_calls if tool_call.function.name == tool_name), None) - if tool_call is None: - tool_call = AssistantPromptMessage.ToolCall( - id="", - type="", - function=AssistantPromptMessage.ToolCall.ToolCallFunction(name=tool_name, arguments=""), - ) - tools_calls.append(tool_call) - - return tool_call - - for new_tool_call in new_tool_calls: - # get tool call - tool_call = get_tool_call(new_tool_call.function.name) - # update tool call - if new_tool_call.id: - tool_call.id = new_tool_call.id - if new_tool_call.type: - tool_call.type = new_tool_call.type - if new_tool_call.function.name: - tool_call.function.name = new_tool_call.function.name - if new_tool_call.function.arguments: - tool_call.function.arguments += new_tool_call.function.arguments - - for chunk in response.iter_lines(decode_unicode=True, delimiter="\n\n"): - if chunk: - # ignore sse comments - if chunk.startswith(":"): - continue - decoded_chunk = chunk.strip().lstrip("data: ").lstrip() - chunk_json = None - try: - chunk_json = json.loads(decoded_chunk) - # stream ended - except json.JSONDecodeError as e: - yield create_final_llm_result_chunk( - index=chunk_index + 1, - message=AssistantPromptMessage(content=""), - finish_reason="Non-JSON encountered.", - ) - break - if not chunk_json or len(chunk_json["choices"]) == 0: - continue - - choice = chunk_json["choices"][0] - finish_reason = chunk_json["choices"][0].get("finish_reason") - chunk_index += 1 - - if "delta" in choice: - delta = choice["delta"] - delta_content = delta.get("content") - - assistant_message_tool_calls = delta.get("tool_calls", None) - # assistant_message_function_call = delta.delta.function_call - - # extract tool calls from response - if assistant_message_tool_calls: - tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - increase_tool_call(tool_calls) - - if delta_content is None or delta_content == "": - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=delta_content, tool_calls=tool_calls if assistant_message_tool_calls else [] - ) - - full_assistant_content += delta_content - elif "text" in choice: - choice_text = choice.get("text", "") - if choice_text == "": - continue - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=choice_text) - full_assistant_content += choice_text - else: - continue - - # check payload indicator for completion - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk_index, - message=assistant_prompt_message, - ), - ) - - chunk_index += 1 - - if tools_calls: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=chunk_index, - message=AssistantPromptMessage(tool_calls=tools_calls, content=""), - ), - ) - - yield create_final_llm_result_chunk( - index=chunk_index, message=AssistantPromptMessage(content=""), finish_reason=finish_reason - ) diff --git a/api/core/model_runtime/model_providers/stepfun/llm/step-1-128k.yaml b/api/core/model_runtime/model_providers/stepfun/llm/step-1-128k.yaml deleted file mode 100644 index 13f7b7fd264aa8..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/llm/step-1-128k.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: step-1-128k -label: - zh_Hans: step-1-128k - en_US: step-1-128k -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 128000 -pricing: - input: '0.04' - output: '0.20' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/stepfun/llm/step-1-256k.yaml b/api/core/model_runtime/model_providers/stepfun/llm/step-1-256k.yaml deleted file mode 100644 index f80ec9851c451d..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/llm/step-1-256k.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: step-1-256k -label: - zh_Hans: step-1-256k - en_US: step-1-256k -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 256000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 256000 -pricing: - input: '0.095' - output: '0.300' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/stepfun/llm/step-1-32k.yaml b/api/core/model_runtime/model_providers/stepfun/llm/step-1-32k.yaml deleted file mode 100644 index 96132d14a8251f..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/llm/step-1-32k.yaml +++ /dev/null @@ -1,28 +0,0 @@ -model: step-1-32k -label: - zh_Hans: step-1-32k - en_US: step-1-32k -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 32000 -pricing: - input: '0.015' - output: '0.070' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/stepfun/llm/step-1-8k.yaml b/api/core/model_runtime/model_providers/stepfun/llm/step-1-8k.yaml deleted file mode 100644 index 4a4ba8d17825d3..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/llm/step-1-8k.yaml +++ /dev/null @@ -1,28 +0,0 @@ -model: step-1-8k -label: - zh_Hans: step-1-8k - en_US: step-1-8k -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8000 -pricing: - input: '0.005' - output: '0.020' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/stepfun/llm/step-1-flash.yaml b/api/core/model_runtime/model_providers/stepfun/llm/step-1-flash.yaml deleted file mode 100644 index afb880f2a40bbc..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/llm/step-1-flash.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: step-1-flash -label: - zh_Hans: step-1-flash - en_US: step-1-flash -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8000 -pricing: - input: '0.001' - output: '0.004' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/stepfun/llm/step-1v-32k.yaml b/api/core/model_runtime/model_providers/stepfun/llm/step-1v-32k.yaml deleted file mode 100644 index 08d6ad245d2dd6..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/llm/step-1v-32k.yaml +++ /dev/null @@ -1,28 +0,0 @@ -model: step-1v-32k -label: - zh_Hans: step-1v-32k - en_US: step-1v-32k -model_type: llm -features: - - vision - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 32000 -pricing: - input: '0.015' - output: '0.070' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/stepfun/llm/step-1v-8k.yaml b/api/core/model_runtime/model_providers/stepfun/llm/step-1v-8k.yaml deleted file mode 100644 index 843d14d9c67e80..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/llm/step-1v-8k.yaml +++ /dev/null @@ -1,28 +0,0 @@ -model: step-1v-8k -label: - zh_Hans: step-1v-8k - en_US: step-1v-8k -model_type: llm -features: - - vision - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.005' - output: '0.020' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/stepfun/llm/step-2-16k.yaml b/api/core/model_runtime/model_providers/stepfun/llm/step-2-16k.yaml deleted file mode 100644 index 6f2dabbfb0e308..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/llm/step-2-16k.yaml +++ /dev/null @@ -1,28 +0,0 @@ -model: step-2-16k -label: - zh_Hans: step-2-16k - en_US: step-2-16k -model_type: llm -features: - - agent-thought - - tool-call - - multi-tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 16000 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 16000 -pricing: - input: '0.038' - output: '0.120' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/stepfun/stepfun.py b/api/core/model_runtime/model_providers/stepfun/stepfun.py deleted file mode 100644 index e1c41a91537cd1..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/stepfun.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class StepfunProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="step-1-8k", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/stepfun/stepfun.yaml b/api/core/model_runtime/model_providers/stepfun/stepfun.yaml deleted file mode 100644 index ccc8455adcf3ca..00000000000000 --- a/api/core/model_runtime/model_providers/stepfun/stepfun.yaml +++ /dev/null @@ -1,81 +0,0 @@ -provider: stepfun -label: - zh_Hans: 阶跃星辰 - en_US: Stepfun -description: - en_US: Models provided by stepfun, such as step-1-8k, step-1-32k、step-1v-8k、step-1v-32k, step-1-128k and step-1-256k - zh_Hans: 阶跃星辰提供的模型，例如 step-1-8k、step-1-32k、step-1v-8k、step-1v-32k、step-1-128k 和 step-1-256k。 -icon_small: - en_US: icon_s_en.png -icon_large: - en_US: icon_l_en.png -background: "#FFFFFF" -help: - title: - en_US: Get your API Key from stepfun - zh_Hans: 从 stepfun 获取 API Key - url: - en_US: https://platform.stepfun.com/interface-key -supported_model_types: - - llm -configurate_methods: - - predefined-model - - customizable-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - type: text-input - default: '8192' - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: max_tokens - label: - zh_Hans: 最大 token 上限 - en_US: Upper bound for max tokens - default: '8192' - type: text-input - - variable: function_calling_type - label: - en_US: Function calling - type: select - required: false - default: no_call - options: - - value: no_call - label: - en_US: Not supported - zh_Hans: 不支持 - - value: tool_call - label: - en_US: Tool Call - zh_Hans: Tool Call diff --git a/api/core/model_runtime/model_providers/tencent/__init__.py b/api/core/model_runtime/model_providers/tencent/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/tencent/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/tencent/_assets/icon_l_en.svg deleted file mode 100644 index 63c7c8f988a904..00000000000000 --- a/api/core/model_runtime/model_providers/tencent/_assets/icon_l_en.svg +++ /dev/null @@ -1,13 +0,0 @@ - - - - - tencent-cloud - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/tencent/_assets/icon_l_zh.svg b/api/core/model_runtime/model_providers/tencent/_assets/icon_l_zh.svg deleted file mode 100644 index 63c7c8f988a904..00000000000000 --- a/api/core/model_runtime/model_providers/tencent/_assets/icon_l_zh.svg +++ /dev/null @@ -1,13 +0,0 @@ - - - - - tencent-cloud - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/tencent/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/tencent/_assets/icon_s_en.svg deleted file mode 100644 index a3299b920198d2..00000000000000 --- a/api/core/model_runtime/model_providers/tencent/_assets/icon_s_en.svg +++ /dev/null @@ -1,11 +0,0 @@ - - - - - tencent-cloud - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/tencent/speech2text/__init__.py b/api/core/model_runtime/model_providers/tencent/speech2text/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/tencent/speech2text/flash_recognizer.py b/api/core/model_runtime/model_providers/tencent/speech2text/flash_recognizer.py deleted file mode 100644 index c3c21793e8eb39..00000000000000 --- a/api/core/model_runtime/model_providers/tencent/speech2text/flash_recognizer.py +++ /dev/null @@ -1,164 +0,0 @@ -import base64 -import hashlib -import hmac -import operator -import time - -import requests - - -class Credential: - def __init__(self, secret_id, secret_key): - self.secret_id = secret_id - self.secret_key = secret_key - - -class FlashRecognitionRequest: - def __init__(self, voice_format="mp3", engine_type="16k_zh"): - self.engine_type = engine_type - self.speaker_diarization = 0 - self.hotword_id = "" - self.customization_id = "" - self.filter_dirty = 0 - self.filter_modal = 0 - self.filter_punc = 0 - self.convert_num_mode = 1 - self.word_info = 0 - self.voice_format = voice_format - self.first_channel_only = 1 - self.reinforce_hotword = 0 - self.sentence_max_length = 0 - - def set_first_channel_only(self, first_channel_only): - self.first_channel_only = first_channel_only - - def set_speaker_diarization(self, speaker_diarization): - self.speaker_diarization = speaker_diarization - - def set_filter_dirty(self, filter_dirty): - self.filter_dirty = filter_dirty - - def set_filter_modal(self, filter_modal): - self.filter_modal = filter_modal - - def set_filter_punc(self, filter_punc): - self.filter_punc = filter_punc - - def set_convert_num_mode(self, convert_num_mode): - self.convert_num_mode = convert_num_mode - - def set_word_info(self, word_info): - self.word_info = word_info - - def set_hotword_id(self, hotword_id): - self.hotword_id = hotword_id - - def set_customization_id(self, customization_id): - self.customization_id = customization_id - - def set_voice_format(self, voice_format): - self.voice_format = voice_format - - def set_sentence_max_length(self, sentence_max_length): - self.sentence_max_length = sentence_max_length - - def set_reinforce_hotword(self, reinforce_hotword): - self.reinforce_hotword = reinforce_hotword - - -class FlashRecognizer: - """ - response: - request_id string - status Integer - message String - audio_duration Integer - flash_result Result Array - - Result: - text String - channel_id Integer - sentence_list Sentence Array - - Sentence: - text String - start_time Integer - end_time Integer - speaker_id Integer - word_list Word Array - - Word: - word String - start_time Integer - end_time Integer - stable_flag： Integer - """ - - def __init__(self, appid, credential): - self.credential = credential - self.appid = appid - - def _format_sign_string(self, param): - signstr = "POSTasr.cloud.tencent.com/asr/flash/v1/" - for t in param: - if "appid" in t: - signstr += str(t[1]) - break - signstr += "?" - for x in param: - tmp = x - if "appid" in x: - continue - for t in tmp: - signstr += str(t) - signstr += "=" - signstr = signstr[:-1] - signstr += "&" - signstr = signstr[:-1] - return signstr - - def _build_header(self): - header = {"Host": "asr.cloud.tencent.com"} - return header - - def _sign(self, signstr, secret_key): - hmacstr = hmac.new(secret_key.encode("utf-8"), signstr.encode("utf-8"), hashlib.sha1).digest() - s = base64.b64encode(hmacstr) - s = s.decode("utf-8") - return s - - def _build_req_with_signature(self, secret_key, params, header): - query = sorted(params.items(), key=operator.itemgetter(0)) - signstr = self._format_sign_string(query) - signature = self._sign(signstr, secret_key) - header["Authorization"] = signature - req_url = "https://" - req_url += signstr[4::] - return req_url - - def _create_query_arr(self, req): - return { - "appid": self.appid, - "secretid": self.credential.secret_id, - "timestamp": str(int(time.time())), - "engine_type": req.engine_type, - "voice_format": req.voice_format, - "speaker_diarization": req.speaker_diarization, - "hotword_id": req.hotword_id, - "customization_id": req.customization_id, - "filter_dirty": req.filter_dirty, - "filter_modal": req.filter_modal, - "filter_punc": req.filter_punc, - "convert_num_mode": req.convert_num_mode, - "word_info": req.word_info, - "first_channel_only": req.first_channel_only, - "reinforce_hotword": req.reinforce_hotword, - "sentence_max_length": req.sentence_max_length, - } - - def recognize(self, req, data): - header = self._build_header() - query_arr = self._create_query_arr(req) - req_url = self._build_req_with_signature(self.credential.secret_key, query_arr, header) - r = requests.post(req_url, headers=header, data=data) - return r.text diff --git a/api/core/model_runtime/model_providers/tencent/speech2text/speech2text.py b/api/core/model_runtime/model_providers/tencent/speech2text/speech2text.py deleted file mode 100644 index 5b427663ca85b0..00000000000000 --- a/api/core/model_runtime/model_providers/tencent/speech2text/speech2text.py +++ /dev/null @@ -1,86 +0,0 @@ -import json -from typing import IO, Optional - -import requests - -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeConnectionError, - InvokeError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel -from core.model_runtime.model_providers.tencent.speech2text.flash_recognizer import ( - Credential, - FlashRecognitionRequest, - FlashRecognizer, -) - - -class TencentSpeech2TextModel(Speech2TextModel): - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - return self._speech2text_invoke(model, credentials, file) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - audio_file_path = self._get_demo_file_path() - - with open(audio_file_path, "rb") as audio_file: - self._speech2text_invoke(model, credentials, audio_file) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _speech2text_invoke(self, model: str, credentials: dict, file: IO[bytes]) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :return: text for given audio file - """ - app_id = credentials["app_id"] - secret_id = credentials["secret_id"] - secret_key = credentials["secret_key"] - voice_format = file.voice_format if hasattr(file, "voice_format") else "mp3" - tencent_voice_recognizer = FlashRecognizer(app_id, Credential(secret_id, secret_key)) - resp = tencent_voice_recognizer.recognize(FlashRecognitionRequest(voice_format), file) - resp = json.loads(resp) - code = resp["code"] - message = resp["message"] - if code == 4002: - raise CredentialsValidateFailedError(str(message)) - elif code != 0: - return f"Tencent ASR Recognition failed with code {code} and message {message}" - return "\n".join(item["text"] for item in resp["flash_result"]) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [requests.exceptions.ConnectionError], - InvokeAuthorizationError: [CredentialsValidateFailedError], - } diff --git a/api/core/model_runtime/model_providers/tencent/speech2text/tencent.yaml b/api/core/model_runtime/model_providers/tencent/speech2text/tencent.yaml deleted file mode 100644 index 618d19ac7c3b38..00000000000000 --- a/api/core/model_runtime/model_providers/tencent/speech2text/tencent.yaml +++ /dev/null @@ -1,5 +0,0 @@ -model: tencent -model_type: speech2text -model_properties: - file_upload_limit: 25 - supported_file_extensions: flac,mp3,mp4,mpeg,mpga,m4a,ogg,wav,webm diff --git a/api/core/model_runtime/model_providers/tencent/tencent.py b/api/core/model_runtime/model_providers/tencent/tencent.py deleted file mode 100644 index 79c6f577b8d5ef..00000000000000 --- a/api/core/model_runtime/model_providers/tencent/tencent.py +++ /dev/null @@ -1,26 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class TencentProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.SPEECH2TEXT) - model_instance.validate_credentials(model="tencent", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/tencent/tencent.yaml b/api/core/model_runtime/model_providers/tencent/tencent.yaml deleted file mode 100644 index 7d8d5a186684be..00000000000000 --- a/api/core/model_runtime/model_providers/tencent/tencent.yaml +++ /dev/null @@ -1,49 +0,0 @@ -provider: tencent -label: - zh_Hans: 腾讯云 - en_US: Tencent -icon_small: - en_US: icon_s_en.svg -icon_large: - zh_Hans: icon_l_zh.svg - en_US: icon_l_en.svg -background: "#E5E7EB" -help: - title: - en_US: Get your API key from Tencent AI - zh_Hans: 从腾讯云获取 API Key - url: - en_US: https://cloud.tencent.com/product/asr -supported_model_types: - - speech2text -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: app_id - label: - zh_Hans: APPID - en_US: APPID - type: text-input - required: true - placeholder: - zh_Hans: 在此输入您的腾讯语音识别服务的 APPID - en_US: Enter the APPID of your Tencent Cloud ASR service - - variable: secret_id - label: - zh_Hans: SecretId - en_US: SecretId - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的腾讯语音识别服务的 SecretId - en_US: Enter the SecretId of your Tencent Cloud ASR service - - variable: secret_key - label: - zh_Hans: SecretKey - en_US: SecretKey - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的腾讯语音识别服务的 SecretKey - en_US: Enter the SecretKey of your Tencent Cloud ASR service diff --git a/api/core/model_runtime/model_providers/togetherai/__init__.py b/api/core/model_runtime/model_providers/togetherai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/togetherai/_assets/togetherai.svg b/api/core/model_runtime/model_providers/togetherai/_assets/togetherai.svg deleted file mode 100644 index e9d918b15e1abd..00000000000000 --- a/api/core/model_runtime/model_providers/togetherai/_assets/togetherai.svg +++ /dev/null @@ -1,13 +0,0 @@ - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/togetherai/_assets/togetherai_square.svg b/api/core/model_runtime/model_providers/togetherai/_assets/togetherai_square.svg deleted file mode 100644 index 16bae5235f5de0..00000000000000 --- a/api/core/model_runtime/model_providers/togetherai/_assets/togetherai_square.svg +++ /dev/null @@ -1,19 +0,0 @@ - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/togetherai/llm/__init__.py b/api/core/model_runtime/model_providers/togetherai/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/togetherai/llm/llm.py b/api/core/model_runtime/model_providers/togetherai/llm/llm.py deleted file mode 100644 index b96d43979ef54a..00000000000000 --- a/api/core/model_runtime/model_providers/togetherai/llm/llm.py +++ /dev/null @@ -1,170 +0,0 @@ -from collections.abc import Generator -from decimal import Decimal -from typing import Optional, Union - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult -from core.model_runtime.entities.message_entities import ( - PromptMessage, - PromptMessageTool, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - DefaultParameterName, - FetchFrom, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, - PriceConfig, -) -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class TogetherAILargeLanguageModel(OAIAPICompatLargeLanguageModel): - def _update_endpoint_url(self, credentials: dict): - credentials["endpoint_url"] = "https://api.together.xyz/v1" - return credentials - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - - return super()._invoke(model, cred_with_endpoint, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - - return super().validate_credentials(model, cred_with_endpoint) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - - return super()._generate( - model, cred_with_endpoint, prompt_messages, model_parameters, tools, stop, stream, user - ) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - REPETITION_PENALTY = "repetition_penalty" - TOP_K = "top_k" - features = [] - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.LLM, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - features=features, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(cred_with_endpoint.get("context_size", "4096")), - ModelPropertyKey.MODE: cred_with_endpoint.get("mode"), - }, - parameter_rules=[ - ParameterRule( - name=DefaultParameterName.TEMPERATURE.value, - label=I18nObject(en_US="Temperature"), - type=ParameterType.FLOAT, - default=float(cred_with_endpoint.get("temperature", 0.7)), - min=0, - max=2, - precision=2, - ), - ParameterRule( - name=DefaultParameterName.TOP_P.value, - label=I18nObject(en_US="Top P"), - type=ParameterType.FLOAT, - default=float(cred_with_endpoint.get("top_p", 1)), - min=0, - max=1, - precision=2, - ), - ParameterRule( - name=TOP_K, - label=I18nObject(en_US="Top K"), - type=ParameterType.INT, - default=int(cred_with_endpoint.get("top_k", 50)), - min=-2147483647, - max=2147483647, - precision=0, - ), - ParameterRule( - name=REPETITION_PENALTY, - label=I18nObject(en_US="Repetition Penalty"), - type=ParameterType.FLOAT, - default=float(cred_with_endpoint.get("repetition_penalty", 1)), - min=-3.4, - max=3.4, - precision=1, - ), - ParameterRule( - name=DefaultParameterName.MAX_TOKENS.value, - label=I18nObject(en_US="Max Tokens"), - type=ParameterType.INT, - default=512, - min=1, - max=int(cred_with_endpoint.get("max_tokens_to_sample", 4096)), - ), - ParameterRule( - name=DefaultParameterName.FREQUENCY_PENALTY.value, - label=I18nObject(en_US="Frequency Penalty"), - type=ParameterType.FLOAT, - default=float(credentials.get("frequency_penalty", 0)), - min=-2, - max=2, - ), - ParameterRule( - name=DefaultParameterName.PRESENCE_PENALTY.value, - label=I18nObject(en_US="Presence Penalty"), - type=ParameterType.FLOAT, - default=float(credentials.get("presence_penalty", 0)), - min=-2, - max=2, - ), - ], - pricing=PriceConfig( - input=Decimal(cred_with_endpoint.get("input_price", 0)), - output=Decimal(cred_with_endpoint.get("output_price", 0)), - unit=Decimal(cred_with_endpoint.get("unit", 0)), - currency=cred_with_endpoint.get("currency", "USD"), - ), - ) - - if cred_with_endpoint["mode"] == "chat": - entity.model_properties[ModelPropertyKey.MODE] = LLMMode.CHAT.value - elif cred_with_endpoint["mode"] == "completion": - entity.model_properties[ModelPropertyKey.MODE] = LLMMode.COMPLETION.value - else: - raise ValueError(f"Unknown completion type {cred_with_endpoint['completion_type']}") - - return entity - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - cred_with_endpoint = self._update_endpoint_url(credentials=credentials) - - return super().get_num_tokens(model, cred_with_endpoint, prompt_messages, tools) diff --git a/api/core/model_runtime/model_providers/togetherai/togetherai.py b/api/core/model_runtime/model_providers/togetherai/togetherai.py deleted file mode 100644 index aa4100a7c9b4d8..00000000000000 --- a/api/core/model_runtime/model_providers/togetherai/togetherai.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class TogetherAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/togetherai/togetherai.yaml b/api/core/model_runtime/model_providers/togetherai/togetherai.yaml deleted file mode 100644 index e69471b15def73..00000000000000 --- a/api/core/model_runtime/model_providers/togetherai/togetherai.yaml +++ /dev/null @@ -1,75 +0,0 @@ -provider: togetherai -label: - en_US: together.ai -icon_small: - en_US: togetherai_square.svg -icon_large: - en_US: togetherai.svg -background: "#F1EFED" -help: - title: - en_US: Get your API key from together.ai - zh_Hans: 从 together.ai 获取 API Key - url: - en_US: https://api.together.xyz/ -supported_model_types: - - llm -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter full model name - zh_Hans: 输入模型全称 - credential_form_schemas: - - variable: api_key - required: true - label: - en_US: API Key - type: secret-input - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: mode - show_on: - - variable: __model_type - value: llm - label: - en_US: Completion mode - type: select - required: false - default: chat - placeholder: - zh_Hans: 选择对话类型 - en_US: Select completion mode - options: - - value: completion - label: - en_US: Completion - zh_Hans: 补全 - - value: chat - label: - en_US: Chat - zh_Hans: 对话 - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - type: text-input - default: '4096' - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: max_tokens_to_sample - label: - zh_Hans: 最大 token 上限 - en_US: Upper bound for max tokens - show_on: - - variable: __model_type - value: llm - default: '4096' - type: text-input diff --git a/api/core/model_runtime/model_providers/tongyi/__init__.py b/api/core/model_runtime/model_providers/tongyi/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/tongyi/_assets/icon_l_en.png b/api/core/model_runtime/model_providers/tongyi/_assets/icon_l_en.png deleted file mode 100644 index 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file mode 100644 index 8a50c7aa05f38c..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/_common.py +++ /dev/null @@ -1,55 +0,0 @@ -from dashscope.common.error import ( - AuthenticationError, - InvalidParameter, - RequestFailure, - ServiceUnavailableError, - UnsupportedHTTPMethod, - UnsupportedModel, -) - -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) - - -class _CommonTongyi: - @staticmethod - def _to_credential_kwargs(credentials: dict) -> dict: - credentials_kwargs = { - "dashscope_api_key": credentials["dashscope_api_key"], - } - - return credentials_kwargs - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [ - RequestFailure, - ], - InvokeServerUnavailableError: [ - ServiceUnavailableError, - ], - InvokeRateLimitError: [], - InvokeAuthorizationError: [ - AuthenticationError, - ], - InvokeBadRequestError: [ - InvalidParameter, - UnsupportedModel, - UnsupportedHTTPMethod, - ], - } diff --git a/api/core/model_runtime/model_providers/tongyi/llm/__init__.py b/api/core/model_runtime/model_providers/tongyi/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/tongyi/llm/_position.yaml b/api/core/model_runtime/model_providers/tongyi/llm/_position.yaml deleted file mode 100644 index 8ce336d60cb396..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/_position.yaml +++ /dev/null @@ -1,51 +0,0 @@ -- qwen-vl-max-0809 -- qwen-vl-max-0201 -- qwen-vl-max -- qwen-max-latest -- qwen-max-1201 -- qwen-max-0919 -- qwen-max-0428 -- qwen-max-0403 -- qwen-max-0107 -- qwen-max -- qwen-max-longcontext -- qwen-plus-latest -- qwen-plus-0919 -- qwen-plus-0806 -- qwen-plus-0723 -- qwen-plus-0624 -- qwen-plus-0206 -- qwen-plus-chat -- qwen-plus -- qwen-vl-plus-0809 -- qwen-vl-plus-0201 -- qwen-vl-plus -- qwen-turbo-latest -- qwen-turbo-0919 -- qwen-turbo-0624 -- qwen-turbo-0206 -- qwen-turbo-chat -- qwen-turbo -- qwen2.5-72b-instruct -- qwen2.5-32b-instruct -- qwen2.5-14b-instruct -- qwen2.5-7b-instruct -- qwen2.5-3b-instruct -- qwen2.5-1.5b-instruct -- qwen2.5-0.5b-instruct -- qwen2.5-coder-7b-instruct -- qwen2-math-72b-instruct -- qwen2-math-7b-instruct -- qwen2-math-1.5b-instruct -- qwen-long -- qwen-math-plus-latest -- qwen-math-plus-0919 -- qwen-math-plus-0816 -- qwen-math-plus -- qwen-math-turbo-latest -- qwen-math-turbo-0919 -- qwen-math-turbo -- qwen-coder-turbo-latest -- qwen-coder-turbo-0919 -- qwen-coder-turbo -- farui-plus diff --git a/api/core/model_runtime/model_providers/tongyi/llm/farui-plus.yaml b/api/core/model_runtime/model_providers/tongyi/llm/farui-plus.yaml deleted file mode 100644 index 34a57d1fc0c9a5..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/farui-plus.yaml +++ /dev/null @@ -1,77 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: farui-plus -label: - en_US: farui-plus -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 12288 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.02' - output: '0.02' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/llm.py b/api/core/model_runtime/model_providers/tongyi/llm/llm.py deleted file mode 100644 index 3e3585b30ae33d..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/llm.py +++ /dev/null @@ -1,593 +0,0 @@ -import base64 -import os -import tempfile -import uuid -from collections.abc import Generator -from http import HTTPStatus -from pathlib import Path -from typing import Optional, Union, cast - -from dashscope import Generation, MultiModalConversation, get_tokenizer -from dashscope.api_entities.dashscope_response import GenerationResponse -from dashscope.common.error import ( - AuthenticationError, - InvalidParameter, - RequestFailure, - ServiceUnavailableError, - UnsupportedHTTPMethod, - UnsupportedModel, -) - -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - I18nObject, - ModelFeature, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - - -class TongyiLargeLanguageModel(LargeLanguageModel): - tokenizers = {} - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # invoke model without code wrapper - return self._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - # Check if the model was added via get_customizable_model_schema - if self.get_customizable_model_schema(model, credentials) is not None: - # For custom models, tokens are not calculated. - return 0 - - if model in {"qwen-turbo-chat", "qwen-plus-chat"}: - model = model.replace("-chat", "") - if model == "farui-plus": - model = "qwen-farui-plus" - - if model in self.tokenizers: - tokenizer = self.tokenizers[model] - else: - tokenizer = get_tokenizer(model) - self.tokenizers[model] = tokenizer - - # convert string to token ids - tokens = tokenizer.encode(self._convert_messages_to_prompt(prompt_messages)) - - return len(tokens) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._generate( - model=model, - credentials=credentials, - prompt_messages=[ - UserPromptMessage(content="ping"), - ], - model_parameters={ - "temperature": 0.5, - }, - stream=False, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - mode = self.get_model_mode(model, credentials) - - if model in {"qwen-turbo-chat", "qwen-plus-chat"}: - model = model.replace("-chat", "") - - extra_model_kwargs = {} - if tools: - extra_model_kwargs["tools"] = self._convert_tools(tools) - - if stop: - extra_model_kwargs["stop"] = stop - - params = { - "model": model, - **model_parameters, - **credentials_kwargs, - **extra_model_kwargs, - } - - model_schema = self.get_model_schema(model, credentials) - if ModelFeature.VISION in (model_schema.features or []): - params["messages"] = self._convert_prompt_messages_to_tongyi_messages(prompt_messages, rich_content=True) - - response = MultiModalConversation.call(**params, stream=stream) - else: - # nothing different between chat model and completion model in tongyi - params["messages"] = self._convert_prompt_messages_to_tongyi_messages(prompt_messages) - response = Generation.call(**params, result_format="message", stream=stream) - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_response( - self, model: str, credentials: dict, response: GenerationResponse, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - if response.status_code not in {200, HTTPStatus.OK}: - raise ServiceUnavailableError(response.message) - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=response.output.choices[0].message.content, - ) - - # transform usage - usage = self._calc_response_usage(model, credentials, response.usage.input_tokens, response.usage.output_tokens) - - # transform response - result = LLMResult( - model=model, - message=assistant_prompt_message, - prompt_messages=prompt_messages, - usage=usage, - ) - - return result - - def _handle_generate_stream_response( - self, - model: str, - credentials: dict, - responses: Generator[GenerationResponse, None, None], - prompt_messages: list[PromptMessage], - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param credentials: credentials - :param responses: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - full_text = "" - tool_calls = [] - for index, response in enumerate(responses): - if response.status_code not in {200, HTTPStatus.OK}: - raise ServiceUnavailableError( - f"Failed to invoke model {model}, status code: {response.status_code}, " - f"message: {response.message}" - ) - - resp_finish_reason = response.output.choices[0].finish_reason - - if resp_finish_reason is not None and resp_finish_reason != "null": - resp_content = response.output.choices[0].message.content - - assistant_prompt_message = AssistantPromptMessage( - content="", - ) - - if "tool_calls" in response.output.choices[0].message: - tool_calls = response.output.choices[0].message["tool_calls"] - elif resp_content: - # special for qwen-vl - if isinstance(resp_content, list): - resp_content = resp_content[0]["text"] - - # transform assistant message to prompt message - assistant_prompt_message.content = resp_content.replace(full_text, "", 1) - - full_text = resp_content - - if tool_calls: - message_tool_calls = [] - for tool_call_obj in tool_calls: - message_tool_call = AssistantPromptMessage.ToolCall( - id=tool_call_obj["function"]["name"], - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=tool_call_obj["function"]["name"], arguments=tool_call_obj["function"]["arguments"] - ), - ) - message_tool_calls.append(message_tool_call) - - assistant_prompt_message.tool_calls = message_tool_calls - - # transform usage - usage = response.usage - usage = self._calc_response_usage(model, credentials, usage.input_tokens, usage.output_tokens) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, message=assistant_prompt_message, finish_reason=resp_finish_reason, usage=usage - ), - ) - else: - resp_content = response.output.choices[0].message.content - if not resp_content: - if "tool_calls" in response.output.choices[0].message: - tool_calls = response.output.choices[0].message["tool_calls"] - continue - - # special for qwen-vl - if isinstance(resp_content, list): - resp_content = resp_content[0]["text"] - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=resp_content.replace(full_text, "", 1), - ) - - full_text = resp_content - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message), - ) - - def _to_credential_kwargs(self, credentials: dict) -> dict: - """ - Transform credentials to kwargs for model instance - - :param credentials: - :return: - """ - credentials_kwargs = { - "api_key": credentials["dashscope_api_key"], - } - - return credentials_kwargs - - def _convert_one_message_to_text(self, message: PromptMessage) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt = "\n\nHuman:" - ai_prompt = "\n\nAssistant:" - content = message.content - - if isinstance(message, UserPromptMessage): - if isinstance(content, str): - message_text = f"{human_prompt} {content}" - else: - message_text = "" - for sub_message in content: - if sub_message.type == PromptMessageContentType.TEXT: - message_text = f"{human_prompt} {sub_message.data}" - break - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage | ToolPromptMessage): - message_text = content - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str: - """ - Format a list of messages into a full prompt for the Anthropic model - - :param messages: List of PromptMessage to combine. - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - # trim off the trailing ' ' that might come from the "Assistant: " - return text.rstrip() - - def _convert_prompt_messages_to_tongyi_messages( - self, prompt_messages: list[PromptMessage], rich_content: bool = False - ) -> list[dict]: - """ - Convert prompt messages to tongyi messages - - :param prompt_messages: prompt messages - :return: tongyi messages - """ - tongyi_messages = [] - for prompt_message in prompt_messages: - if isinstance(prompt_message, SystemPromptMessage): - tongyi_messages.append( - { - "role": "system", - "content": prompt_message.content if not rich_content else [{"text": prompt_message.content}], - } - ) - elif isinstance(prompt_message, UserPromptMessage): - if isinstance(prompt_message.content, str): - tongyi_messages.append( - { - "role": "user", - "content": prompt_message.content - if not rich_content - else [{"text": prompt_message.content}], - } - ) - else: - sub_messages = [] - for message_content in prompt_message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - - image_url = message_content.data - if message_content.data.startswith("data:"): - # convert image base64 data to file in /tmp - image_url = self._save_base64_image_to_file(message_content.data) - - sub_message_dict = {"image": image_url} - sub_messages.append(sub_message_dict) - - # resort sub_messages to ensure text is always at last - sub_messages = sorted(sub_messages, key=lambda x: "text" in x) - - tongyi_messages.append({"role": "user", "content": sub_messages}) - elif isinstance(prompt_message, AssistantPromptMessage): - content = prompt_message.content - if not content: - content = " " - message = {"role": "assistant", "content": content if not rich_content else [{"text": content}]} - if prompt_message.tool_calls: - message["tool_calls"] = [tool_call.model_dump() for tool_call in prompt_message.tool_calls] - tongyi_messages.append(message) - elif isinstance(prompt_message, ToolPromptMessage): - tongyi_messages.append( - {"role": "tool", "content": prompt_message.content, "name": prompt_message.tool_call_id} - ) - else: - raise ValueError(f"Got unknown type {prompt_message}") - - return tongyi_messages - - def _save_base64_image_to_file(self, base64_image: str) -> str: - """ - Save base64 image to file - 'data:{upload_file.mime_type};base64,{encoded_string}' - - :param base64_image: base64 image data - :return: image file path - """ - # get mime type and encoded string - mime_type, encoded_string = base64_image.split(",")[0].split(";")[0].split(":")[1], base64_image.split(",")[1] - - # save image to file - temp_dir = tempfile.gettempdir() - - file_path = os.path.join(temp_dir, f"{uuid.uuid4()}.{mime_type.split('/')[1]}") - - Path(file_path).write_bytes(base64.b64decode(encoded_string)) - - return f"file://{file_path}" - - def _convert_tools(self, tools: list[PromptMessageTool]) -> list[dict]: - """ - Convert tools - """ - tool_definitions = [] - for tool in tools: - properties = tool.parameters["properties"] - required_properties = tool.parameters["required"] - - properties_definitions = {} - for p_key, p_val in properties.items(): - desc = p_val["description"] - if "enum" in p_val: - desc += f"; Only accepts one of the following predefined options: [{', '.join(p_val['enum'])}]" - - properties_definitions[p_key] = { - "description": desc, - "type": p_val["type"], - } - - tool_definition = { - "type": "function", - "function": { - "name": tool.name, - "description": tool.description, - "parameters": properties_definitions, - "required": required_properties, - }, - } - - tool_definitions.append(tool_definition) - - return tool_definitions - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [ - RequestFailure, - ], - InvokeServerUnavailableError: [ - ServiceUnavailableError, - ], - InvokeRateLimitError: [], - InvokeAuthorizationError: [ - AuthenticationError, - ], - InvokeBadRequestError: [ - InvalidParameter, - UnsupportedModel, - UnsupportedHTTPMethod, - ], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - Architecture for defining customizable models - - :param model: model name - :param credentials: model credentials - :return: AIModelEntity or None - """ - return AIModelEntity( - model=model, - label=I18nObject(en_US=model, zh_Hans=model), - model_type=ModelType.LLM, - features=[ModelFeature.TOOL_CALL, ModelFeature.MULTI_TOOL_CALL, ModelFeature.STREAM_TOOL_CALL] - if credentials.get("function_calling_type") == "tool_call" - else [], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", 8000)), - ModelPropertyKey.MODE: LLMMode.CHAT.value, - }, - parameter_rules=[ - ParameterRule( - name="temperature", - use_template="temperature", - label=I18nObject(en_US="Temperature", zh_Hans="温度"), - type=ParameterType.FLOAT, - ), - ParameterRule( - name="max_tokens", - use_template="max_tokens", - default=512, - min=1, - max=int(credentials.get("max_tokens", 1024)), - label=I18nObject(en_US="Max Tokens", zh_Hans="最大标记"), - type=ParameterType.INT, - ), - ParameterRule( - name="top_p", - use_template="top_p", - label=I18nObject(en_US="Top P", zh_Hans="Top P"), - type=ParameterType.FLOAT, - ), - ParameterRule( - name="top_k", - use_template="top_k", - label=I18nObject(en_US="Top K", zh_Hans="Top K"), - type=ParameterType.FLOAT, - ), - ParameterRule( - name="frequency_penalty", - use_template="frequency_penalty", - label=I18nObject(en_US="Frequency Penalty", zh_Hans="重复惩罚"), - type=ParameterType.FLOAT, - ), - ], - ) diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo-0919.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo-0919.yaml deleted file mode 100644 index 64a3f331336bc0..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo-0919.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-coder-turbo-0919 -label: - en_US: qwen-coder-turbo-0919 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo-latest.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo-latest.yaml deleted file mode 100644 index a4c93f7047ff58..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo-latest.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-coder-turbo-latest -label: - en_US: qwen-coder-turbo-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo.yaml deleted file mode 100644 index ff68faed80810b..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-coder-turbo.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-coder-turbo -label: - en_US: qwen-coder-turbo -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-long.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-long.yaml deleted file mode 100644 index c3dbb3616fb961..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-long.yaml +++ /dev/null @@ -1,77 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-long -label: - en_US: qwen-long -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 10000000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 6000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.0005' - output: '0.002' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-0816.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-0816.yaml deleted file mode 100644 index 42fe1f68623bc4..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-0816.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-math-plus-0816 -label: - en_US: qwen-math-plus-0816 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 3072 - min: 1 - max: 3072 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-0919.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-0919.yaml deleted file mode 100644 index 9b6567b8cda4d7..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-0919.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-math-plus-0919 -label: - en_US: qwen-math-plus-0919 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 3072 - min: 1 - max: 3072 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-latest.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-latest.yaml deleted file mode 100644 index b2a2393b365fcb..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus-latest.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-math-plus-latest -label: - en_US: qwen-math-plus-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 3072 - min: 1 - max: 3072 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus.yaml deleted file mode 100644 index 63f4b7ff0a0879..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-plus.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-math-plus -label: - en_US: qwen-math-plus -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 3072 - min: 1 - max: 3072 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo-0919.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo-0919.yaml deleted file mode 100644 index 4da90eec3eddfd..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo-0919.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-math-turbo-0919 -label: - en_US: qwen-math-turbo-0919 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 3072 - min: 1 - max: 3072 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo-latest.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo-latest.yaml deleted file mode 100644 index d29f8851dd3909..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo-latest.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-math-turbo-latest -label: - en_US: qwen-math-turbo-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 3072 - min: 1 - max: 3072 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo.yaml deleted file mode 100644 index 2a8f7f725e9366..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-math-turbo.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-math-turbo -label: - en_US: qwen-math-turbo -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 3072 - min: 1 - max: 3072 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0107.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0107.yaml deleted file mode 100644 index ef1841b5173bc5..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0107.yaml +++ /dev/null @@ -1,78 +0,0 @@ -# this model corresponds to qwen-max, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#cf6cc4aa2aokf) -model: qwen-max-0107 -label: - en_US: qwen-max-0107 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.04' - output: '0.12' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0403.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0403.yaml deleted file mode 100644 index a2ea5df130f379..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0403.yaml +++ /dev/null @@ -1,78 +0,0 @@ -# this model corresponds to qwen-max-0403, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#cf6cc4aa2aokf) -model: qwen-max-0403 -label: - en_US: qwen-max-0403 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.04' - output: '0.12' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0428.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0428.yaml deleted file mode 100644 index a467665f118a68..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0428.yaml +++ /dev/null @@ -1,78 +0,0 @@ -# this model corresponds to qwen-max-0428, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#cf6cc4aa2aokf) -model: qwen-max-0428 -label: - en_US: qwen-max-0428 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.04' - output: '0.12' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0919.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0919.yaml deleted file mode 100644 index 78661eaea065f2..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-0919.yaml +++ /dev/null @@ -1,78 +0,0 @@ -# this model corresponds to qwen-max-0919, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#cf6cc4aa2aokf) -model: qwen-max-0919 -label: - en_US: qwen-max-0919 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.02' - output: '0.06' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-1201.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-1201.yaml deleted file mode 100644 index 6f4674576b4426..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-1201.yaml +++ /dev/null @@ -1,78 +0,0 @@ -# this model corresponds to qwen-max, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#cf6cc4aa2aokf) -model: qwen-max-1201 -label: - en_US: qwen-max-1201 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.04' - output: '0.12' - unit: '0.001' - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-latest.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-latest.yaml deleted file mode 100644 index 8b5f0054733455..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-latest.yaml +++ /dev/null @@ -1,78 +0,0 @@ -# this model corresponds to qwen-max, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#cf6cc4aa2aokf) -model: qwen-max-latest -label: - en_US: qwen-max-latest -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.02' - output: '0.06' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-longcontext.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-longcontext.yaml deleted file mode 100644 index 098494ff95012d..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max-longcontext.yaml +++ /dev/null @@ -1,78 +0,0 @@ -# this model corresponds to qwen-max, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#cf6cc4aa2aokf) -model: qwen-max-longcontext -label: - en_US: qwen-max-longcontext -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8000 - min: 1 - max: 8000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.04' - output: '0.12' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-max.yaml deleted file mode 100644 index 9d0d3f8db39c23..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-max.yaml +++ /dev/null @@ -1,87 +0,0 @@ -# this model corresponds to qwen-max, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#cf6cc4aa2aokf) -model: qwen-max -label: - en_US: qwen-max -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: enable_search - type: boolean - default: false - label: - zh_Hans: 联网搜索 - en_US: Web Search - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. - - name: response_format - use_template: response_format -pricing: - input: '0.02' - output: '0.06' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0206.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0206.yaml deleted file mode 100644 index 0b1a6f81df80c0..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0206.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-plus-0206, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#bb0ffee88bwnk) -model: qwen-plus-0206 -label: - en_US: qwen-plus-0206 -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8000 - min: 1 - max: 8000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0624.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0624.yaml deleted file mode 100644 index 7706005bb535cd..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0624.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-plus-0624, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#bb0ffee88bwnk) -model: qwen-plus-0624 -label: - en_US: qwen-plus-0624 -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8000 - min: 1 - max: 8000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0723.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0723.yaml deleted file mode 100644 index 348276fc08f98c..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0723.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-plus-0723, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#bb0ffee88bwnk) -model: qwen-plus-0723 -label: - en_US: qwen-plus-0723 -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8000 - min: 1 - max: 8000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0806.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0806.yaml deleted file mode 100644 index 29f125135eaa3f..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0806.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-plus-0806, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#bb0ffee88bwnk) -model: qwen-plus-0806 -label: - en_US: qwen-plus-0806 -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0919.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0919.yaml deleted file mode 100644 index 905fa1e1028bbf..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-0919.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-plus-0919, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#bb0ffee88bwnk) -model: qwen-plus-0919 -label: - en_US: qwen-plus-0919 -model_type: llm -features: - - agent-thought -model_properties: - mode: completion - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.0008' - output: '0.002' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-chat.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-chat.yaml deleted file mode 100644 index c7a3549727ce8e..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-chat.yaml +++ /dev/null @@ -1,79 +0,0 @@ -# this model corresponds to qwen-plus, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#bb0ffee88bwnk) -model: qwen-plus-chat -label: - en_US: qwen-plus-chat -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-latest.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-latest.yaml deleted file mode 100644 index 608f52c2964ea3..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus-latest.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-plus-latest, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#bb0ffee88bwnk) -model: qwen-plus-latest -label: - en_US: qwen-plus-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.0008' - output: '0.002' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus.yaml deleted file mode 100644 index 9089e57255bb70..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-plus.yaml +++ /dev/null @@ -1,87 +0,0 @@ -# this model corresponds to qwen-plus, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#bb0ffee88bwnk) -model: qwen-plus -label: - en_US: qwen-plus -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: enable_search - type: boolean - default: false - label: - zh_Hans: 联网搜索 - en_US: Web Search - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. - - name: response_format - use_template: response_format -pricing: - input: '0.0008' - output: '0.002' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0206.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0206.yaml deleted file mode 100644 index 7ee0d44f2f2834..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0206.yaml +++ /dev/null @@ -1,77 +0,0 @@ -# this model corresponds to qwen-turbo-0206, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#ff492e2c10lub) - -model: qwen-turbo-0206 -label: - en_US: qwen-turbo-0206 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0624.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0624.yaml deleted file mode 100644 index 20a3f7eb6460f3..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0624.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-turbo-0624, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#ff492e2c10lub) -model: qwen-turbo-0624 -label: - en_US: qwen-turbo-0624 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0919.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0919.yaml deleted file mode 100644 index ba73dec3631fb5..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-0919.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-turbo-0919, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#ff492e2c10lub) -model: qwen-turbo-0919 -label: - en_US: qwen-turbo-0919 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.0003' - output: '0.0006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-chat.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-chat.yaml deleted file mode 100644 index d785b7fe857878..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-chat.yaml +++ /dev/null @@ -1,79 +0,0 @@ -# this model corresponds to qwen-turbo, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#ff492e2c10lub) -model: qwen-turbo-chat -label: - en_US: qwen-turbo-chat -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 1500 - min: 1 - max: 1500 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-latest.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-latest.yaml deleted file mode 100644 index fe38a4283c2d1e..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo-latest.yaml +++ /dev/null @@ -1,76 +0,0 @@ -# this model corresponds to qwen-turbo-latest, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#ff492e2c10lub) -model: qwen-turbo-latest -label: - en_US: qwen-turbo-latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.0006' - output: '0.0003' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo.yaml deleted file mode 100644 index 215c9ec5fc96aa..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-turbo.yaml +++ /dev/null @@ -1,87 +0,0 @@ -# this model corresponds to qwen-turbo, for more details -# please refer to (https://help.aliyun.com/zh/model-studio/getting-started/models#ff492e2c10lub) -model: qwen-turbo -label: - en_US: qwen-turbo -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: enable_search - type: boolean - default: false - label: - zh_Hans: 联网搜索 - en_US: Web Search - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. - - name: response_format - use_template: response_format -pricing: - input: '0.0006' - output: '0.0003' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max-0201.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max-0201.yaml deleted file mode 100644 index d80168ffc3fb55..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max-0201.yaml +++ /dev/null @@ -1,49 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-vl-max-0201 -label: - en_US: qwen-vl-max-0201 -model_type: llm -features: - - vision - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: response_format - use_template: response_format -pricing: - input: '0.02' - output: '0.02' - unit: '0.001' - currency: RMB -deprecated: true diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max-0809.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max-0809.yaml deleted file mode 100644 index 50e10226a5f5c4..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max-0809.yaml +++ /dev/null @@ -1,79 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-vl-max-0809 -label: - en_US: qwen-vl-max-0809 -model_type: llm -features: - - vision - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: max_tokens - required: false - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: response_format - use_template: response_format - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.02' - output: '0.02' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max.yaml deleted file mode 100644 index 21b127f56c47d9..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-max.yaml +++ /dev/null @@ -1,79 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-vl-max -label: - en_US: qwen-vl-max -model_type: llm -features: - - vision - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: max_tokens - required: false - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: response_format - use_template: response_format - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.02' - output: '0.02' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus-0201.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus-0201.yaml deleted file mode 100644 index 03cb039d15a7dd..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus-0201.yaml +++ /dev/null @@ -1,79 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-vl-plus-0201 -label: - en_US: qwen-vl-plus-0201 -model_type: llm -features: - - vision - - agent-thought -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: max_tokens - required: false - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: response_format - use_template: response_format - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.02' - output: '0.02' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus-0809.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus-0809.yaml deleted file mode 100644 index 67b2b2ebddc616..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus-0809.yaml +++ /dev/null @@ -1,79 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-vl-plus-0809 -label: - en_US: qwen-vl-plus-0809 -model_type: llm -features: - - vision - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: max_tokens - required: false - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: response_format - use_template: response_format - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.008' - output: '0.008' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus.yaml deleted file mode 100644 index f55764c6c05500..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen-vl-plus.yaml +++ /dev/null @@ -1,79 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen-vl-plus -label: - en_US: qwen-vl-plus -model_type: llm -features: - - vision - - agent-thought -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: max_tokens - required: false - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: response_format - use_template: response_format - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.008' - output: '0.008' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-1.5b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-1.5b-instruct.yaml deleted file mode 100644 index ea157f42ded914..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-1.5b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2-math-1.5b-instruct -label: - en_US: qwen2-math-1.5b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-72b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-72b-instruct.yaml deleted file mode 100644 index 37052a923317d9..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-72b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2-math-72b-instruct -label: - en_US: qwen2-math-72b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-7b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-7b-instruct.yaml deleted file mode 100644 index e182f1c27f7ea9..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2-math-7b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2-math-7b-instruct -label: - en_US: qwen2-math-7b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-0.5b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-0.5b-instruct.yaml deleted file mode 100644 index 9e75ccc1f210d9..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-0.5b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-0.5b-instruct -label: - en_US: qwen2.5-0.5b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.000' - output: '0.000' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-1.5b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-1.5b-instruct.yaml deleted file mode 100644 index 67c9d312432af7..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-1.5b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-1.5b-instruct -label: - en_US: qwen2.5-1.5b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.000' - output: '0.000' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-14b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-14b-instruct.yaml deleted file mode 100644 index 2a38be921cf3fd..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-14b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-14b-instruct -label: - en_US: qwen2.5-14b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.002' - output: '0.006' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-32b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-32b-instruct.yaml deleted file mode 100644 index e6e4fbf97808be..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-32b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-32b-instruct -label: - en_US: qwen2.5-32b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.0035' - output: '0.007' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-3b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-3b-instruct.yaml deleted file mode 100644 index 8f250379a788ab..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-3b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-3b-instruct -label: - en_US: qwen2.5-3b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.000' - output: '0.000' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-72b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-72b-instruct.yaml deleted file mode 100644 index bb3cdd6141f1ea..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-72b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-72b-instruct -label: - en_US: qwen2.5-72b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.004' - output: '0.012' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-7b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-7b-instruct.yaml deleted file mode 100644 index fdcd3d42757edb..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-7b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-7b-instruct -label: - en_US: qwen2.5-7b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.001' - output: '0.002' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-coder-7b-instruct.yaml b/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-coder-7b-instruct.yaml deleted file mode 100644 index 7ebeec395393c7..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/llm/qwen2.5-coder-7b-instruct.yaml +++ /dev/null @@ -1,75 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models -model: qwen2.5-coder-7b-instruct -label: - en_US: qwen2.5-coder-7b-instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0.001' - output: '0.002' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/text_embedding/__init__.py b/api/core/model_runtime/model_providers/tongyi/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v1.yaml b/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v1.yaml deleted file mode 100644 index 52e35d8b50afd8..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v1.yaml +++ /dev/null @@ -1,10 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models#3383780daf8hw -model: text-embedding-v1 -model_type: text-embedding -model_properties: - context_size: 2048 - max_chunks: 25 -pricing: - input: "0.0007" - unit: "0.001" - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v2.yaml b/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v2.yaml deleted file mode 100644 index 5bb6a8f4243d53..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v2.yaml +++ /dev/null @@ -1,10 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models#3383780daf8hw -model: text-embedding-v2 -model_type: text-embedding -model_properties: - context_size: 2048 - max_chunks: 25 -pricing: - input: "0.0007" - unit: "0.001" - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v3.yaml b/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v3.yaml deleted file mode 100644 index d8af0e2b63565d..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/text_embedding/text-embedding-v3.yaml +++ /dev/null @@ -1,10 +0,0 @@ -# for more details, please refer to https://help.aliyun.com/zh/model-studio/getting-started/models#3383780daf8hw -model: text-embedding-v3 -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 25 -pricing: - input: "0.0007" - unit: "0.001" - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/tongyi.py b/api/core/model_runtime/model_providers/tongyi/tongyi.py deleted file mode 100644 index a084512de9a885..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/tongyi.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class TongyiProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `qwen-turbo` model for validate, - model_instance.validate_credentials(model="qwen-turbo", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/tongyi/tongyi.yaml b/api/core/model_runtime/model_providers/tongyi/tongyi.yaml deleted file mode 100644 index 1a09c20fd93f61..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/tongyi.yaml +++ /dev/null @@ -1,87 +0,0 @@ -provider: tongyi -label: - zh_Hans: 通义千问 - en_US: TONGYI -icon_small: - en_US: icon_s_en.png -icon_large: - zh_Hans: icon_l_zh.png - en_US: icon_l_en.png -background: "#EFF1FE" -help: - title: - en_US: Get your API key from AliCloud - zh_Hans: 从阿里云百炼获取 API Key - url: - en_US: https://bailian.console.aliyun.com/?apiKey=1#/api-key -supported_model_types: - - llm - - tts - - text-embedding -configurate_methods: - - predefined-model - - customizable-model -provider_credential_schema: - credential_form_schemas: - - variable: dashscope_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: dashscope_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: context_size - label: - zh_Hans: 模型上下文长度 - en_US: Model context size - required: true - type: text-input - default: '4096' - placeholder: - zh_Hans: 在此输入您的模型上下文长度 - en_US: Enter your Model context size - - variable: max_tokens - label: - zh_Hans: 最大 token 上限 - en_US: Upper bound for max tokens - default: '4096' - type: text-input - show_on: - - variable: __model_type - value: llm - - variable: function_calling_type - label: - en_US: Function calling - type: select - required: false - default: no_call - options: - - value: no_call - label: - en_US: Not Support - zh_Hans: 不支持 - - value: function_call - label: - en_US: Support - zh_Hans: 支持 - show_on: - - variable: __model_type - value: llm diff --git a/api/core/model_runtime/model_providers/tongyi/tts/__init__.py b/api/core/model_runtime/model_providers/tongyi/tts/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/tongyi/tts/tts-1.yaml b/api/core/model_runtime/model_providers/tongyi/tts/tts-1.yaml deleted file mode 100644 index 4eaa0ff3612bf2..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/tts/tts-1.yaml +++ /dev/null @@ -1,139 +0,0 @@ -model: tts-1 -model_type: tts -model_properties: - default_voice: 'sambert-zhiru-v1' - voices: - - mode: "sambert-zhinan-v1" - name: "知楠（广告男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiqi-v1" - name: "知琪（温柔女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhichu-v1" - name: "知厨（新闻播报）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhide-v1" - name: "知德（新闻男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhijia-v1" - name: "知佳（标准女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiru-v1" - name: "知茹（新闻女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiqian-v1" - name: "知倩（配音解说、新闻播报）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhixiang-v1" - name: "知祥（配音解说）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiwei-v1" - name: "知薇（萝莉女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhihao-v1" - name: "知浩（咨询男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhijing-v1" - name: "知婧（严厉女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiming-v1" - name: "知茗（诙谐男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhimo-v1" - name: "知墨（情感男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhina-v1" - name: "知娜（浙普女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhishu-v1" - name: "知树（资讯男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhistella-v1" - name: "知莎（知性女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiting-v1" - name: "知婷（电台女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhixiao-v1" - name: "知笑（资讯女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiya-v1" - name: "知雅（严厉女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiye-v1" - name: "知晔（青年男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiying-v1" - name: "知颖（软萌童声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhiyuan-v1" - name: "知媛（知心姐姐）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhigui-v1" - name: "知柜（直播女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhishuo-v1" - name: "知硕（自然男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhimiao-emo-v1" - name: "知妙（多种情感女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhimao-v1" - name: "知猫（直播女声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhilun-v1" - name: "知伦（悬疑解说）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhifei-v1" - name: "知飞（激昂解说）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-zhida-v1" - name: "知达（标准男声）" - language: [ "zh-Hans", "en-US" ] - - mode: "sambert-camila-v1" - name: "Camila（西班牙语女声）" - language: [ "es-ES" ] - - mode: "sambert-perla-v1" - name: "Perla（意大利语女声）" - language: [ "it-IT" ] - - mode: "sambert-indah-v1" - name: "Indah（印尼语女声）" - language: [ "id-ID" ] - - mode: "sambert-clara-v1" - name: "Clara（法语女声）" - language: [ "fr-FR" ] - - mode: "sambert-hanna-v1" - name: "Hanna（德语女声）" - language: [ "de-DE" ] - - mode: "sambert-beth-v1" - name: "Beth（咨询女声）" - language: [ "en-US" ] - - mode: "sambert-betty-v1" - name: "Betty（客服女声）" - language: [ "en-US" ] - - mode: "sambert-cally-v1" - name: "Cally（自然女声）" - language: [ "en-US" ] - - mode: "sambert-cindy-v1" - name: "Cindy（对话女声）" - language: [ "en-US" ] - - mode: "sambert-eva-v1" - name: "Eva（陪伴女声）" - language: [ "en-US" ] - - mode: "sambert-donna-v1" - name: "Donna（教育女声）" - language: [ "en-US" ] - - mode: "sambert-brian-v1" - name: "Brian（客服男声）" - language: [ "en-US" ] - - mode: "sambert-waan-v1" - name: "Waan（泰语女声）" - language: [ "th-TH" ] - word_limit: 7000 - audio_type: 'mp3' - max_workers: 5 -pricing: - input: '1' - output: '0' - unit: '0.0001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/tongyi/tts/tts.py b/api/core/model_runtime/model_providers/tongyi/tts/tts.py deleted file mode 100644 index 48a38897a87e9e..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/tts/tts.py +++ /dev/null @@ -1,152 +0,0 @@ -import threading -from queue import Queue -from typing import Optional - -import dashscope -from dashscope import SpeechSynthesizer -from dashscope.api_entities.dashscope_response import SpeechSynthesisResponse -from dashscope.audio.tts import ResultCallback, SpeechSynthesisResult - -from core.model_runtime.errors.invoke import InvokeBadRequestError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.tts_model import TTSModel -from core.model_runtime.model_providers.tongyi._common import _CommonTongyi - - -class TongyiText2SpeechModel(_CommonTongyi, TTSModel): - """ - Model class for Tongyi Speech to text model. - """ - - def _invoke( - self, model: str, tenant_id: str, credentials: dict, content_text: str, voice: str, user: Optional[str] = None - ) -> any: - """ - _invoke text2speech model - - :param model: model name - :param tenant_id: user tenant id - :param credentials: model credentials - :param voice: model timbre - :param content_text: text content to be translated - :param user: unique user id - :return: text translated to audio file - """ - if not voice or voice not in [ - d["value"] for d in self.get_tts_model_voices(model=model, credentials=credentials) - ]: - voice = self._get_model_default_voice(model, credentials) - - return self._tts_invoke_streaming(model=model, credentials=credentials, content_text=content_text, voice=voice) - - def validate_credentials(self, model: str, credentials: dict, user: Optional[str] = None) -> None: - """ - validate credentials text2speech model - - :param model: model name - :param credentials: model credentials - :param user: unique user id - :return: text translated to audio file - """ - try: - self._tts_invoke_streaming( - model=model, - credentials=credentials, - content_text="Hello Dify!", - voice=self._get_model_default_voice(model, credentials), - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _tts_invoke_streaming(self, model: str, credentials: dict, content_text: str, voice: str) -> any: - """ - _tts_invoke_streaming text2speech model - - :param model: model name - :param credentials: model credentials - :param voice: model timbre - :param content_text: text content to be translated - :return: text translated to audio file - """ - word_limit = self._get_model_word_limit(model, credentials) - audio_type = self._get_model_audio_type(model, credentials) - try: - audio_queue: Queue = Queue() - callback = Callback(queue=audio_queue) - - def invoke_remote(content, v, api_key, cb, at, wl): - if len(content) < word_limit: - sentences = [content] - else: - sentences = list(self._split_text_into_sentences(org_text=content, max_length=wl)) - for sentence in sentences: - SpeechSynthesizer.call( - model=v, - sample_rate=16000, - api_key=api_key, - text=sentence.strip(), - callback=cb, - format=at, - word_timestamp_enabled=True, - phoneme_timestamp_enabled=True, - ) - - threading.Thread( - target=invoke_remote, - args=(content_text, voice, credentials.get("dashscope_api_key"), callback, audio_type, word_limit), - ).start() - - while True: - audio = audio_queue.get() - if audio is None: - break - yield audio - - except Exception as ex: - raise InvokeBadRequestError(str(ex)) - - @staticmethod - def _process_sentence(sentence: str, credentials: dict, voice: str, audio_type: str): - """ - _tts_invoke Tongyi text2speech model api - - :param credentials: model credentials - :param sentence: text content to be translated - :param voice: model timbre - :param audio_type: audio file type - :return: text translated to audio file - """ - response = dashscope.audio.tts.SpeechSynthesizer.call( - model=voice, - sample_rate=48000, - api_key=credentials.get("dashscope_api_key"), - text=sentence.strip(), - format=audio_type, - ) - if isinstance(response.get_audio_data(), bytes): - return response.get_audio_data() - - -class Callback(ResultCallback): - def __init__(self, queue: Queue): - self._queue = queue - - def on_open(self): - pass - - def on_complete(self): - self._queue.put(None) - self._queue.task_done() - - def on_error(self, response: SpeechSynthesisResponse): - self._queue.put(None) - self._queue.task_done() - - def on_close(self): - self._queue.put(None) - self._queue.task_done() - - def on_event(self, result: SpeechSynthesisResult): - ad = result.get_audio_frame() - if ad: - self._queue.put(ad) diff --git a/api/core/model_runtime/model_providers/triton_inference_server/__init__.py b/api/core/model_runtime/model_providers/triton_inference_server/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git 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ziX_pO|Fl10P`%g_7oDxc2fxA&NB0KK-}dX^`d7F5(B$M_3g0(4mQEW2jCn9M`$#fG z9!^eq`MLb{mt7jVERuO{@f{8;Z6Io}urx2_Vk7`qFxu}xR&z6Jt9r@tHbo`Tp>6C- z%hsyXLR~v+o0)rUnECA(-iC6~*!BYTn-`o!Mgz$EN@Zd?fszFo%3S`H*Ku5FPsV|p z!M|_868`^Mx)35d6sz#yj{4~X;-U$!UJisX7TW9fqUv@k8dWCt8%~>%FnsS(8G&Gfe`J*Ewi>TnqE`gYuG@>QBS7tu9?na*bz#-3eN8Ec!iU-XldX6 z^0PbCs8G$rCARSMz1qi}So^kr$~NO$uNu!NH0=)Kp;6^J_w!Wv9WS`pFXs&F+?)I; zlr4h(fzfjXOBNqm@(^#7JN)DrrlE!z$Zw-5-to(hnFCp3dvj+u(ydpxquC&+ULnX9 zs%TRXGN%IF4ri6mNE~32-=)m3*2uf1VrUnI%F`S)J7q@5efw^`=)pBbp#={3O&H5# zY?td@VU;aoAu;o4&bLIRzc8k;$m?9@1AbtvSTTjBCu$rnkvJUTr@vRGi&843=QtJ- zG(2%T#UA3iXuK{C*BZfvx~hGI`F&;?SCl@G&h|r#@&@j6|DlhIYXJEE{-d)1;KBdV zc@5Aj{-YB(g8jJHTwG`UzueLJLvtSgv7!<1LQ54;1^tH?xuU!QrRc}be*palqu - - diff --git a/api/core/model_runtime/model_providers/triton_inference_server/llm/__init__.py b/api/core/model_runtime/model_providers/triton_inference_server/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/triton_inference_server/llm/llm.py b/api/core/model_runtime/model_providers/triton_inference_server/llm/llm.py deleted file mode 100644 index cf7e3f14be03ad..00000000000000 --- a/api/core/model_runtime/model_providers/triton_inference_server/llm/llm.py +++ /dev/null @@ -1,280 +0,0 @@ -from collections.abc import Generator - -from httpx import Response, post -from yarl import URL - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - - -class TritonInferenceAILargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - """ - invoke LLM - - see `core.model_runtime.model_providers.__base.large_language_model.LargeLanguageModel._invoke` - """ - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - validate credentials - """ - if "server_url" not in credentials: - raise CredentialsValidateFailedError("server_url is required in credentials") - - try: - self._invoke( - model=model, - credentials=credentials, - prompt_messages=[UserPromptMessage(content="ping")], - model_parameters={}, - stream=False, - ) - except InvokeError as ex: - raise CredentialsValidateFailedError(f"An error occurred during connection: {str(ex)}") - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - """ - get number of tokens - - cause TritonInference LLM is a customized model, we could net detect which tokenizer to use - so we just take the GPT2 tokenizer as default - """ - return self._get_num_tokens_by_gpt2(self._convert_prompt_message_to_text(prompt_messages)) - - def _convert_prompt_message_to_text(self, message: list[PromptMessage]) -> str: - """ - convert prompt message to text - """ - text = "" - for item in message: - if isinstance(item, UserPromptMessage): - text += f"User: {item.content}" - elif isinstance(item, SystemPromptMessage): - text += f"System: {item.content}" - elif isinstance(item, AssistantPromptMessage): - text += f"Assistant: {item.content}" - else: - raise NotImplementedError(f"PromptMessage type {type(item)} is not supported") - return text - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - rules = [ - ParameterRule( - name="temperature", - type=ParameterType.FLOAT, - use_template="temperature", - label=I18nObject(zh_Hans="温度", en_US="Temperature"), - ), - ParameterRule( - name="top_p", - type=ParameterType.FLOAT, - use_template="top_p", - label=I18nObject(zh_Hans="Top P", en_US="Top P"), - ), - ParameterRule( - name="max_tokens", - type=ParameterType.INT, - use_template="max_tokens", - min=1, - max=int(credentials.get("context_length", 2048)), - default=min(512, int(credentials.get("context_length", 2048))), - label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"), - ), - ] - - completion_type = None - - if "completion_type" in credentials: - if credentials["completion_type"] == "chat": - completion_type = LLMMode.CHAT.value - elif credentials["completion_type"] == "completion": - completion_type = LLMMode.COMPLETION.value - else: - raise ValueError(f'completion_type {credentials["completion_type"]} is not supported') - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - parameter_rules=rules, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - model_properties={ - ModelPropertyKey.MODE: completion_type, - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_length", 2048)), - }, - ) - - return entity - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - """ - generate text from LLM - """ - if "server_url" not in credentials: - raise CredentialsValidateFailedError("server_url is required in credentials") - - if "stream" in credentials and not bool(credentials["stream"]) and stream: - raise ValueError(f"stream is not supported by model {model}") - - try: - parameters = {} - if "temperature" in model_parameters: - parameters["temperature"] = model_parameters["temperature"] - if "top_p" in model_parameters: - parameters["top_p"] = model_parameters["top_p"] - if "top_k" in model_parameters: - parameters["top_k"] = model_parameters["top_k"] - if "presence_penalty" in model_parameters: - parameters["presence_penalty"] = model_parameters["presence_penalty"] - if "frequency_penalty" in model_parameters: - parameters["frequency_penalty"] = model_parameters["frequency_penalty"] - - response = post( - str(URL(credentials["server_url"]) / "v2" / "models" / model / "generate"), - json={ - "text_input": self._convert_prompt_message_to_text(prompt_messages), - "max_tokens": model_parameters.get("max_tokens", 512), - "parameters": {"stream": False, **parameters}, - }, - timeout=(10, 120), - ) - response.raise_for_status() - if response.status_code != 200: - raise InvokeBadRequestError(f"Invoke failed with status code {response.status_code}, {response.text}") - - if stream: - return self._handle_chat_stream_response( - model=model, credentials=credentials, prompt_messages=prompt_messages, tools=tools, resp=response - ) - return self._handle_chat_generate_response( - model=model, credentials=credentials, prompt_messages=prompt_messages, tools=tools, resp=response - ) - except Exception as ex: - raise InvokeConnectionError(f"An error occurred during connection: {str(ex)}") - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool], - resp: Response, - ) -> LLMResult: - """ - handle normal chat generate response - """ - text = resp.json()["text_output"] - - usage = LLMUsage.empty_usage() - usage.prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - usage.completion_tokens = self._get_num_tokens_by_gpt2(text) - - return LLMResult( - model=model, prompt_messages=prompt_messages, message=AssistantPromptMessage(content=text), usage=usage - ) - - def _handle_chat_stream_response( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool], - resp: Response, - ) -> Generator: - """ - handle normal chat generate response - """ - text = resp.json()["text_output"] - - usage = LLMUsage.empty_usage() - usage.prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - usage.completion_tokens = self._get_num_tokens_by_gpt2(text) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=0, message=AssistantPromptMessage(content=text), usage=usage), - ) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [], - InvokeRateLimitError: [], - InvokeAuthorizationError: [], - InvokeBadRequestError: [ValueError], - } diff --git a/api/core/model_runtime/model_providers/triton_inference_server/triton_inference_server.py b/api/core/model_runtime/model_providers/triton_inference_server/triton_inference_server.py deleted file mode 100644 index d85f7c82e7db71..00000000000000 --- a/api/core/model_runtime/model_providers/triton_inference_server/triton_inference_server.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class XinferenceAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/triton_inference_server/triton_inference_server.yaml b/api/core/model_runtime/model_providers/triton_inference_server/triton_inference_server.yaml deleted file mode 100644 index 218678b8835519..00000000000000 --- a/api/core/model_runtime/model_providers/triton_inference_server/triton_inference_server.yaml +++ /dev/null @@ -1,84 +0,0 @@ -provider: triton_inference_server -label: - en_US: Triton Inference Server -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.png -background: "#EFFDFD" -help: - title: - en_US: How to deploy Triton Inference Server - zh_Hans: 如何部署 Triton Inference Server - url: - en_US: https://github.com/triton-inference-server/server -supported_model_types: - - llm -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: server_url - label: - zh_Hans: 服务器URL - en_US: Server url - type: text-input - required: true - placeholder: - zh_Hans: 在此输入 Triton Inference Server 的服务器地址，如 http://192.168.1.100:8000 - en_US: Enter the url of your Triton Inference Server, e.g. http://192.168.1.100:8000 - - variable: context_size - label: - zh_Hans: 上下文大小 - en_US: Context size - type: text-input - required: true - placeholder: - zh_Hans: 在此输入您的上下文大小 - en_US: Enter the context size - default: '2048' - - variable: completion_type - label: - zh_Hans: 补全类型 - en_US: Model type - type: select - required: true - default: chat - placeholder: - zh_Hans: 在此输入您的补全类型 - en_US: Enter the completion type - options: - - label: - zh_Hans: 补全模型 - en_US: Completion model - value: completion - - label: - zh_Hans: 对话模型 - en_US: Chat model - value: chat - - variable: stream - label: - zh_Hans: 流式输出 - en_US: Stream output - type: select - required: true - default: 'true' - placeholder: - zh_Hans: 是否支持流式输出 - en_US: Whether to support stream output - options: - - label: - zh_Hans: 是 - en_US: 'Yes' - value: 'true' - - label: - zh_Hans: 否 - en_US: 'No' - value: 'false' diff --git a/api/core/model_runtime/model_providers/upstage/__init__.py b/api/core/model_runtime/model_providers/upstage/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/upstage/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/upstage/_assets/icon_l_en.svg deleted file mode 100644 index 0761f85ba64958..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/_assets/icon_l_en.svg +++ /dev/null @@ -1,14 +0,0 @@ - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/upstage/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/upstage/_assets/icon_s_en.svg deleted file mode 100644 index 44ef12b7303098..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/_assets/icon_s_en.svg +++ /dev/null @@ -1,3 +0,0 @@ - - - diff --git a/api/core/model_runtime/model_providers/upstage/_common.py b/api/core/model_runtime/model_providers/upstage/_common.py deleted file mode 100644 index 47ebaccd84ab8a..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/_common.py +++ /dev/null @@ -1,54 +0,0 @@ -from collections.abc import Mapping - -import openai -from httpx import Timeout - -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) - - -class _CommonUpstage: - def _to_credential_kwargs(self, credentials: Mapping) -> dict: - """ - Transform credentials to kwargs for model instance - - :param credentials: - :return: - """ - credentials_kwargs = { - "api_key": credentials["upstage_api_key"], - "base_url": "https://api.upstage.ai/v1/solar", - "timeout": Timeout(315.0, read=300.0, write=20.0, connect=10.0), - "max_retries": 1, - } - - return credentials_kwargs - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [openai.APIConnectionError, openai.APITimeoutError], - InvokeServerUnavailableError: [openai.InternalServerError], - InvokeRateLimitError: [openai.RateLimitError], - InvokeAuthorizationError: [openai.AuthenticationError, openai.PermissionDeniedError], - InvokeBadRequestError: [ - openai.BadRequestError, - openai.NotFoundError, - openai.UnprocessableEntityError, - openai.APIError, - ], - } diff --git a/api/core/model_runtime/model_providers/upstage/llm/__init__.py b/api/core/model_runtime/model_providers/upstage/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/upstage/llm/_position.yaml b/api/core/model_runtime/model_providers/upstage/llm/_position.yaml deleted file mode 100644 index 7992843dcb1d1d..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/llm/_position.yaml +++ /dev/null @@ -1 +0,0 @@ -- solar-1-mini-chat diff --git a/api/core/model_runtime/model_providers/upstage/llm/llm.py b/api/core/model_runtime/model_providers/upstage/llm/llm.py deleted file mode 100644 index a18ee906248a49..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/llm/llm.py +++ /dev/null @@ -1,603 +0,0 @@ -import logging -from collections.abc import Generator -from typing import Optional, Union, cast - -from openai import OpenAI, Stream -from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessageToolCall -from openai.types.chat.chat_completion_chunk import ChoiceDeltaFunctionCall, ChoiceDeltaToolCall -from openai.types.chat.chat_completion_message import FunctionCall -from tokenizers import Tokenizer - -from core.model_runtime.callbacks.base_callback import Callback -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.upstage._common import _CommonUpstage - -logger = logging.getLogger(__name__) - -UPSTAGE_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. -The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - - -{{instructions}} - -""" # noqa: E501 - - -class UpstageLargeLanguageModel(_CommonUpstage, LargeLanguageModel): - """ - Model class for Upstage large language model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - - return self._chat_generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def _code_block_mode_wrapper( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - callbacks: Optional[list[Callback]] = None, - ) -> Union[LLMResult, Generator]: - """ - Code block mode wrapper for invoking large language model - """ - if "response_format" in model_parameters and model_parameters["response_format"] in {"JSON", "XML"}: - stop = stop or [] - self._transform_chat_json_prompts( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - response_format=model_parameters["response_format"], - ) - model_parameters.pop("response_format") - - return self._invoke( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def _transform_chat_json_prompts( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - response_format: str = "JSON", - ) -> None: - """ - Transform json prompts - """ - if stop is None: - stop = [] - if "```\n" not in stop: - stop.append("```\n") - if "\n```" not in stop: - stop.append("\n```") - - if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): - prompt_messages[0] = SystemPromptMessage( - content=UPSTAGE_BLOCK_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content).replace( - "{{block}}", response_format - ) - ) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}\n")) - else: - prompt_messages.insert( - 0, - SystemPromptMessage( - content=UPSTAGE_BLOCK_MODE_PROMPT.replace( - "{{instructions}}", f"Please output a valid {response_format} object." - ).replace("{{block}}", response_format) - ), - ) - prompt_messages.append(AssistantPromptMessage(content=f"\n```{response_format}")) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - return self._num_tokens_from_messages(model, prompt_messages, tools) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - client.chat.completions.create( - messages=[{"role": "user", "content": "ping"}], model=model, temperature=0, max_tokens=10, stream=False - ) - except Exception as e: - raise CredentialsValidateFailedError(str(e)) - - def _chat_generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - extra_model_kwargs = {} - - if tools: - extra_model_kwargs["functions"] = [ - {"name": tool.name, "description": tool.description, "parameters": tool.parameters} for tool in tools - ] - - if stop: - extra_model_kwargs["stop"] = stop - - if user: - extra_model_kwargs["user"] = user - - # chat model - response = client.chat.completions.create( - messages=[self._convert_prompt_message_to_dict(m) for m in prompt_messages], - model=model, - stream=stream, - **model_parameters, - **extra_model_kwargs, - ) - - if stream: - return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages, tools) - return self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools) - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - response: ChatCompletion, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response - """ - assistant_message = response.choices[0].message - # assistant_message_tool_calls = assistant_message.tool_calls - assistant_message_function_call = assistant_message.function_call - - # extract tool calls from response - # tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - function_call = self._extract_response_function_call(assistant_message_function_call) - tool_calls = [function_call] if function_call else [] - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_message.content, tool_calls=tool_calls) - - # calculate num tokens - if response.usage: - # transform usage - prompt_tokens = response.usage.prompt_tokens - completion_tokens = response.usage.completion_tokens - else: - # calculate num tokens - prompt_tokens = self._num_tokens_from_messages(model, prompt_messages, tools) - completion_tokens = self._num_tokens_from_messages(model, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - response = LLMResult( - model=response.model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - system_fingerprint=response.system_fingerprint, - ) - - return response - - def _handle_chat_generate_stream_response( - self, - model: str, - credentials: dict, - response: Stream[ChatCompletionChunk], - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> Generator: - """ - Handle llm chat stream response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: llm response chunk generator - """ - full_assistant_content = "" - delta_assistant_message_function_call_storage: Optional[ChoiceDeltaFunctionCall] = None - prompt_tokens = 0 - completion_tokens = 0 - final_tool_calls = [] - final_chunk = LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=""), - ), - ) - - for chunk in response: - if len(chunk.choices) == 0: - if chunk.usage: - # calculate num tokens - prompt_tokens = chunk.usage.prompt_tokens - completion_tokens = chunk.usage.completion_tokens - continue - - delta = chunk.choices[0] - has_finish_reason = delta.finish_reason is not None - - if ( - not has_finish_reason - and (delta.delta.content is None or delta.delta.content == "") - and delta.delta.function_call is None - ): - continue - - # assistant_message_tool_calls = delta.delta.tool_calls - assistant_message_function_call = delta.delta.function_call - - # extract tool calls from response - if delta_assistant_message_function_call_storage is not None: - # handle process of stream function call - if assistant_message_function_call: - # message has not ended ever - delta_assistant_message_function_call_storage.arguments += assistant_message_function_call.arguments - continue - else: - # message has ended - assistant_message_function_call = delta_assistant_message_function_call_storage - delta_assistant_message_function_call_storage = None - else: - if assistant_message_function_call: - # start of stream function call - delta_assistant_message_function_call_storage = assistant_message_function_call - if delta_assistant_message_function_call_storage.arguments is None: - delta_assistant_message_function_call_storage.arguments = "" - if not has_finish_reason: - continue - - # tool_calls = self._extract_response_tool_calls(assistant_message_tool_calls) - function_call = self._extract_response_function_call(assistant_message_function_call) - tool_calls = [function_call] if function_call else [] - if tool_calls: - final_tool_calls.extend(tool_calls) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=delta.delta.content or "", tool_calls=tool_calls) - - full_assistant_content += delta.delta.content or "" - - if has_finish_reason: - final_chunk = LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - ), - ) - else: - yield LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - ), - ) - - if not prompt_tokens: - prompt_tokens = self._num_tokens_from_messages(model, prompt_messages, tools) - - if not completion_tokens: - full_assistant_prompt_message = AssistantPromptMessage( - content=full_assistant_content, tool_calls=final_tool_calls - ) - completion_tokens = self._num_tokens_from_messages(model, [full_assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - final_chunk.delta.usage = usage - - yield final_chunk - - def _extract_response_tool_calls( - self, response_tool_calls: list[ChatCompletionMessageToolCall | ChoiceDeltaToolCall] - ) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_tool_calls: - for response_tool_call in response_tool_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.function.name, arguments=response_tool_call.function.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call.id, type=response_tool_call.type, function=function - ) - tool_calls.append(tool_call) - - return tool_calls - - def _extract_response_function_call( - self, response_function_call: FunctionCall | ChoiceDeltaFunctionCall - ) -> AssistantPromptMessage.ToolCall: - """ - Extract function call from response - - :param response_function_call: response function call - :return: tool call - """ - tool_call = None - if response_function_call: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_function_call.name, arguments=response_function_call.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_function_call.name, type="function", function=function - ) - - return tool_call - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for Upstage API - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": {"url": message_content.data, "detail": message_content.detail.value}, - } - sub_messages.append(sub_message_dict) - - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls: - # message_dict["tool_calls"] = [tool_call.dict() for tool_call in - # message.tool_calls] - function_call = message.tool_calls[0] - message_dict["function_call"] = { - "name": function_call.function.name, - "arguments": function_call.function.arguments, - } - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - # message_dict = { - # "role": "tool", - # "content": message.content, - # "tool_call_id": message.tool_call_id - # } - message_dict = {"role": "function", "content": message.content, "name": message.tool_call_id} - else: - raise ValueError(f"Got unknown type {message}") - - if message.name: - message_dict["name"] = message.name - - return message_dict - - def _get_tokenizer(self) -> Tokenizer: - return Tokenizer.from_pretrained("upstage/solar-1-mini-tokenizer") - - def _num_tokens_from_messages( - self, model: str, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None - ) -> int: - """ - Calculate num tokens for solar with Huggingface Solar tokenizer. - Solar tokenizer is opened in huggingface https://huggingface.co/upstage/solar-1-mini-tokenizer - """ - tokenizer = self._get_tokenizer() - tokens_per_message = 5 # <|im_start|>{role}\n{message}<|im_end|> - tokens_prefix = 1 # <|startoftext|> - tokens_suffix = 3 # <|im_start|>assistant\n - - num_tokens = 0 - num_tokens += tokens_prefix - - messages_dict = [self._convert_prompt_message_to_dict(message) for message in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += len(tokenizer.encode(t_key, add_special_tokens=False)) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += len(tokenizer.encode(f_key, add_special_tokens=False)) - num_tokens += len(tokenizer.encode(f_value, add_special_tokens=False)) - else: - num_tokens += len(tokenizer.encode(t_key, add_special_tokens=False)) - num_tokens += len(tokenizer.encode(t_value, add_special_tokens=False)) - else: - num_tokens += len(tokenizer.encode(str(value), add_special_tokens=False)) - num_tokens += tokens_suffix - - if tools: - num_tokens += self._num_tokens_for_tools(tokenizer, tools) - - return num_tokens - - def _num_tokens_for_tools(self, tokenizer: Tokenizer, tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for tool calling with upstage tokenizer. - - :param tokenizer: huggingface tokenizer - :param tools: tools for tool calling - :return: number of tokens - """ - num_tokens = 0 - for tool in tools: - num_tokens += len(tokenizer.encode("type")) - num_tokens += len(tokenizer.encode("function")) - - # calculate num tokens for function object - num_tokens += len(tokenizer.encode("name")) - num_tokens += len(tokenizer.encode(tool.name)) - num_tokens += len(tokenizer.encode("description")) - num_tokens += len(tokenizer.encode(tool.description)) - parameters = tool.parameters - num_tokens += len(tokenizer.encode("parameters")) - if "title" in parameters: - num_tokens += len(tokenizer.encode("title")) - num_tokens += len(tokenizer.encode(parameters.get("title"))) - num_tokens += len(tokenizer.encode("type")) - num_tokens += len(tokenizer.encode(parameters.get("type"))) - if "properties" in parameters: - num_tokens += len(tokenizer.encode("properties")) - for key, value in parameters.get("properties").items(): - num_tokens += len(tokenizer.encode(key)) - for field_key, field_value in value.items(): - num_tokens += len(tokenizer.encode(field_key)) - if field_key == "enum": - for enum_field in field_value: - num_tokens += 3 - num_tokens += len(tokenizer.encode(enum_field)) - else: - num_tokens += len(tokenizer.encode(field_key)) - num_tokens += len(tokenizer.encode(str(field_value))) - if "required" in parameters: - num_tokens += len(tokenizer.encode("required")) - for required_field in parameters["required"]: - num_tokens += 3 - num_tokens += len(tokenizer.encode(required_field)) - - return num_tokens diff --git a/api/core/model_runtime/model_providers/upstage/llm/solar-1-mini-chat.yaml b/api/core/model_runtime/model_providers/upstage/llm/solar-1-mini-chat.yaml deleted file mode 100644 index 787ac83f8ad92d..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/llm/solar-1-mini-chat.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: solar-1-mini-chat -label: - zh_Hans: solar-1-mini-chat - en_US: solar-1-mini-chat - ko_KR: solar-1-mini-chat -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 32768 - - name: seed - label: - zh_Hans: 种子 - en_US: Seed - type: int - help: - zh_Hans: - 如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint - 响应参数来监视变化。 - en_US: - If specified, model will make a best effort to sample deterministically, - such that repeated requests with the same seed and parameters should return - the same result. Determinism is not guaranteed, and you should refer to the - system_fingerprint response parameter to monitor changes in the backend. - required: false -pricing: - input: "0.5" - output: "0.5" - unit: "0.000001" - currency: USD diff --git a/api/core/model_runtime/model_providers/upstage/text_embedding/__init__.py b/api/core/model_runtime/model_providers/upstage/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/upstage/text_embedding/solar-embedding-1-large-passage.yaml b/api/core/model_runtime/model_providers/upstage/text_embedding/solar-embedding-1-large-passage.yaml deleted file mode 100644 index d838a5bbb1bbfd..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/text_embedding/solar-embedding-1-large-passage.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: solar-embedding-1-large-passage -model_type: text-embedding -model_properties: - context_size: 4000 - max_chunks: 32 -pricing: - input: '0.1' - unit: '0.000001' - currency: 'USD' diff --git a/api/core/model_runtime/model_providers/upstage/text_embedding/solar-embedding-1-large-query.yaml b/api/core/model_runtime/model_providers/upstage/text_embedding/solar-embedding-1-large-query.yaml deleted file mode 100644 index c77645cffdd8f4..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/text_embedding/solar-embedding-1-large-query.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: solar-embedding-1-large-query -model_type: text-embedding -model_properties: - context_size: 4000 - max_chunks: 32 -pricing: - input: '0.1' - unit: '0.000001' - currency: 'USD' diff --git a/api/core/model_runtime/model_providers/upstage/upstage.py b/api/core/model_runtime/model_providers/upstage/upstage.py deleted file mode 100644 index e45d4aae19eb6c..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/upstage.py +++ /dev/null @@ -1,27 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class UpstageProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials from defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="solar-1-mini-chat", credentials=credentials) - except CredentialsValidateFailedError as e: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise e - except Exception as e: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise e diff --git a/api/core/model_runtime/model_providers/upstage/upstage.yaml b/api/core/model_runtime/model_providers/upstage/upstage.yaml deleted file mode 100644 index 837667cfa9b41f..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/upstage.yaml +++ /dev/null @@ -1,49 +0,0 @@ -provider: upstage -label: - en_US: Upstage -description: - en_US: Models provided by Upstage, such as Solar-1-mini-chat. - zh_Hans: Upstage 提供的模型，例如 Solar-1-mini-chat. -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#FFFFF" -help: - title: - en_US: Get your API Key from Upstage - zh_Hans: 从 Upstage 获取 API Key - url: - en_US: https://console.upstage.ai/api-keys -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: upstage_api_key - label: - en_US: 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a/api/core/model_runtime/model_providers/vertex_ai/_common.py +++ /dev/null @@ -1,15 +0,0 @@ -from core.model_runtime.errors.invoke import InvokeError - - -class _CommonVertexAi: - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - pass diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/__init__.py b/api/core/model_runtime/model_providers/vertex_ai/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-haiku.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-haiku.yaml deleted file mode 100644 index 5613348695dc20..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-haiku.yaml +++ /dev/null @@ -1,56 +0,0 @@ -model: claude-3-haiku@20240307 -label: - en_US: Claude 3 Haiku -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - # docs: https://docs.anthropic.com/claude/docs/system-prompts - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.00025' - output: '0.00125' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-opus.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-opus.yaml deleted file mode 100644 index ab084636b5dec7..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-opus.yaml +++ /dev/null @@ -1,56 +0,0 @@ -model: claude-3-opus@20240229 -label: - en_US: Claude 3 Opus -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - # docs: https://docs.anthropic.com/claude/docs/system-prompts - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.015' - output: '0.075' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-sonnet.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-sonnet.yaml deleted file mode 100644 index 0be0113ffd98cf..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3-sonnet.yaml +++ /dev/null @@ -1,55 +0,0 @@ -model: claude-3-sonnet@20240229 -label: - en_US: Claude 3 Sonnet -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.003' - output: '0.015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3.5-sonnet.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3.5-sonnet.yaml deleted file mode 100644 index c64384e6a2f153..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/anthropic.claude-3.5-sonnet.yaml +++ /dev/null @@ -1,55 +0,0 @@ -model: claude-3-5-sonnet@20240620 -label: - en_US: Claude 3.5 Sonnet -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: max_tokens - use_template: max_tokens - required: true - type: int - default: 4096 - min: 1 - max: 4096 - help: - zh_Hans: 停止前生成的最大令牌数。请注意，Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。 - en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter. - - name: temperature - use_template: temperature - required: false - type: float - default: 1 - min: 0.0 - max: 1.0 - help: - zh_Hans: 生成内容的随机性。 - en_US: The amount of randomness injected into the response. - - name: top_p - required: false - type: float - default: 0.999 - min: 0.000 - max: 1.000 - help: - zh_Hans: 在核采样中，Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布，并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p，但不能同时更改两者。 - en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both. - - name: top_k - required: false - type: int - default: 0 - min: 0 - # tip docs from aws has error, max value is 500 - max: 500 - help: - zh_Hans: 对于每个后续标记，仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。 - en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses. -pricing: - input: '0.003' - output: '0.015' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.0-pro-vision.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.0-pro-vision.yaml deleted file mode 100644 index ebb276b8af18f5..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.0-pro-vision.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: gemini-1.0-pro-vision-001 -label: - en_US: Gemini 1.0 Pro Vision -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - en_US: Top k - type: int - help: - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_output_tokens - use_template: max_tokens - required: true - default: 2048 - min: 1 - max: 2048 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.0-pro.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.0-pro.yaml deleted file mode 100644 index c325973846f5f8..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.0-pro.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: gemini-1.0-pro-002 -label: - en_US: Gemini 1.0 Pro -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32760 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - en_US: Top k - type: int - help: - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_output_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/text_embedding/__init__.py b/api/core/model_runtime/model_providers/vertex_ai/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text-embedding-004.yaml b/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text-embedding-004.yaml deleted file mode 100644 index 32db6faf89940f..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text-embedding-004.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: text-embedding-004 -model_type: text-embedding -model_properties: - context_size: 2048 -pricing: - input: '0.00013' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text-multilingual-embedding-002.yaml b/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text-multilingual-embedding-002.yaml deleted file mode 100644 index 2ec0eea9f21b78..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text-multilingual-embedding-002.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: text-multilingual-embedding-002 -model_type: text-embedding -model_properties: - context_size: 2048 -pricing: - input: '0.00013' - unit: '0.001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/vertex_ai.py b/api/core/model_runtime/model_providers/vertex_ai/vertex_ai.py deleted file mode 100644 index 466a86fd36a181..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/vertex_ai.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class VertexAiProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `gemini-1.0-pro-002` model for validate, - model_instance.validate_credentials(model="gemini-1.0-pro-002", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/vertex_ai/vertex_ai.yaml b/api/core/model_runtime/model_providers/vertex_ai/vertex_ai.yaml deleted file mode 100644 index 27a4d03fe2975b..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/vertex_ai.yaml +++ /dev/null @@ -1,43 +0,0 @@ -provider: vertex_ai -label: - en_US: Vertex AI | Google Cloud Platform -description: - en_US: Vertex AI in Google Cloud Platform. -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.png -background: "#FCFDFF" -help: - title: - en_US: Get your Access Details from Google - url: - en_US: https://cloud.google.com/vertex-ai/ -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: vertex_project_id - label: - en_US: Project ID - type: text-input - required: true - placeholder: - en_US: Enter your Google Cloud Project ID - - variable: vertex_location - label: - en_US: Location - type: text-input - required: true - placeholder: - en_US: Enter your Google Cloud Location - - variable: vertex_service_account_key - label: - en_US: Service Account Key (Leave blank if you use Application Default Credentials) - type: secret-input - required: false - placeholder: - en_US: Enter your Google Cloud Service Account Key in base64 format diff --git a/api/core/model_runtime/model_providers/volcengine_maas/__init__.py b/api/core/model_runtime/model_providers/volcengine_maas/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_l_en.svg deleted file mode 100644 index 616e90916b2810..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_l_en.svg +++ /dev/null @@ -1,23 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_l_zh.svg b/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_l_zh.svg deleted file mode 100644 index 24b92195bd5522..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_l_zh.svg +++ /dev/null @@ -1,39 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_s_en.svg deleted file mode 100644 index e6454a89b7ccdf..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/_assets/icon_s_en.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/volcengine_maas/client.py b/api/core/model_runtime/model_providers/volcengine_maas/client.py deleted file mode 100644 index cfe21e4b9f4617..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/client.py +++ /dev/null @@ -1,216 +0,0 @@ -import re -from collections.abc import Generator -from typing import Optional, cast - -from volcenginesdkarkruntime import Ark -from volcenginesdkarkruntime.types.chat import ( - ChatCompletion, - ChatCompletionAssistantMessageParam, - ChatCompletionChunk, - ChatCompletionContentPartImageParam, - ChatCompletionContentPartTextParam, - ChatCompletionMessageParam, - ChatCompletionMessageToolCallParam, - ChatCompletionSystemMessageParam, - ChatCompletionToolMessageParam, - ChatCompletionToolParam, - ChatCompletionUserMessageParam, -) -from volcenginesdkarkruntime.types.chat.chat_completion_content_part_image_param import ImageURL -from volcenginesdkarkruntime.types.chat.chat_completion_message_tool_call_param import Function -from volcenginesdkarkruntime.types.create_embedding_response import CreateEmbeddingResponse -from volcenginesdkarkruntime.types.shared_params import FunctionDefinition - -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) - -DEFAULT_V2_ENDPOINT = "maas-api.ml-platform-cn-beijing.volces.com" -DEFAULT_V3_ENDPOINT = "https://ark.cn-beijing.volces.com/api/v3" - - -class ArkClientV3: - endpoint_id: Optional[str] = None - ark: Optional[Ark] = None - - def __init__(self, *args, **kwargs): - self.ark = Ark(*args, **kwargs) - self.endpoint_id = None - - @staticmethod - def is_legacy(credentials: dict) -> bool: - # match default v2 endpoint - if ArkClientV3.is_compatible_with_legacy(credentials): - return False - # match default v3 endpoint - if credentials.get("api_endpoint_host") == DEFAULT_V3_ENDPOINT: - return False - # only v3 support api_key - if credentials.get("auth_method") == "api_key": - return False - # these cases are considered as sdk v2 - # - modified default v2 endpoint - # - modified default v3 endpoint and auth without api_key - return True - - @staticmethod - def is_compatible_with_legacy(credentials: dict) -> bool: - endpoint = credentials.get("api_endpoint_host") - return endpoint == DEFAULT_V2_ENDPOINT - - @classmethod - def from_credentials(cls, credentials): - """Initialize the client using the credentials provided.""" - args = { - "base_url": credentials["api_endpoint_host"], - "region": credentials["volc_region"], - } - if credentials.get("auth_method") == "api_key": - args = { - **args, - "api_key": credentials["volc_api_key"], - } - else: - args = { - **args, - "ak": credentials["volc_access_key_id"], - "sk": credentials["volc_secret_access_key"], - } - - if cls.is_compatible_with_legacy(credentials): - args = {**args, "base_url": DEFAULT_V3_ENDPOINT} - - client = ArkClientV3(**args) - client.endpoint_id = credentials["endpoint_id"] - return client - - @staticmethod - def convert_prompt_message(message: PromptMessage) -> ChatCompletionMessageParam: - """Converts a PromptMessage to a ChatCompletionMessageParam""" - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - content = message.content - else: - content = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - content.append( - ChatCompletionContentPartTextParam( - text=message_content.text, - type="text", - ) - ) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - image_data = re.sub(r"^data:image\/[a-zA-Z]+;base64,", "", message_content.data) - content.append( - ChatCompletionContentPartImageParam( - image_url=ImageURL( - url=image_data, - detail=message_content.detail.value, - ), - type="image_url", - ) - ) - message_dict = ChatCompletionUserMessageParam(role="user", content=content) - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = ChatCompletionAssistantMessageParam( - content=message.content, - role="assistant", - tool_calls=None - if not message.tool_calls - else [ - ChatCompletionMessageToolCallParam( - id=call.id, - function=Function(name=call.function.name, arguments=call.function.arguments), - type="function", - ) - for call in message.tool_calls - ], - ) - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = ChatCompletionSystemMessageParam(content=message.content, role="system") - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = ChatCompletionToolMessageParam( - content=message.content, role="tool", tool_call_id=message.tool_call_id - ) - else: - raise ValueError(f"Got unknown PromptMessage type {message}") - - return message_dict - - @staticmethod - def _convert_tool_prompt(message: PromptMessageTool) -> ChatCompletionToolParam: - return ChatCompletionToolParam( - type="function", - function=FunctionDefinition( - name=message.name, - description=message.description, - parameters=message.parameters, - ), - ) - - def chat( - self, - messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - frequency_penalty: Optional[float] = None, - max_tokens: Optional[int] = None, - presence_penalty: Optional[float] = None, - top_p: Optional[float] = None, - temperature: Optional[float] = None, - ) -> ChatCompletion: - """Block chat""" - return self.ark.chat.completions.create( - model=self.endpoint_id, - messages=[self.convert_prompt_message(message) for message in messages], - tools=[self._convert_tool_prompt(tool) for tool in tools] if tools else None, - stop=stop, - frequency_penalty=frequency_penalty, - max_tokens=max_tokens, - presence_penalty=presence_penalty, - top_p=top_p, - temperature=temperature, - ) - - def stream_chat( - self, - messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - frequency_penalty: Optional[float] = None, - max_tokens: Optional[int] = None, - presence_penalty: Optional[float] = None, - top_p: Optional[float] = None, - temperature: Optional[float] = None, - ) -> Generator[ChatCompletionChunk]: - """Stream chat""" - chunks = self.ark.chat.completions.create( - stream=True, - model=self.endpoint_id, - messages=[self.convert_prompt_message(message) for message in messages], - tools=[self._convert_tool_prompt(tool) for tool in tools] if tools else None, - stop=stop, - frequency_penalty=frequency_penalty, - max_tokens=max_tokens, - presence_penalty=presence_penalty, - top_p=top_p, - temperature=temperature, - stream_options={"include_usage": True}, - ) - yield from chunks - - def embeddings(self, texts: list[str]) -> CreateEmbeddingResponse: - return self.ark.embeddings.create(model=self.endpoint_id, input=texts) diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/__init__.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/client.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/client.py deleted file mode 100644 index 266f1216f82b29..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/client.py +++ /dev/null @@ -1,123 +0,0 @@ -import re -from collections.abc import Callable, Generator -from typing import cast - -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.model_providers.volcengine_maas.legacy.errors import wrap_error -from core.model_runtime.model_providers.volcengine_maas.legacy.volc_sdk import ChatRole, MaasError, MaasService - - -class MaaSClient(MaasService): - def __init__(self, host: str, region: str): - self.endpoint_id = None - super().__init__(host, region) - - def set_endpoint_id(self, endpoint_id: str): - self.endpoint_id = endpoint_id - - @classmethod - def from_credential(cls, credentials: dict) -> "MaaSClient": - host = credentials["api_endpoint_host"] - region = credentials["volc_region"] - ak = credentials["volc_access_key_id"] - sk = credentials["volc_secret_access_key"] - endpoint_id = credentials["endpoint_id"] - - client = cls(host, region) - client.set_endpoint_id(endpoint_id) - client.set_ak(ak) - client.set_sk(sk) - return client - - def chat(self, params: dict, messages: list[PromptMessage], stream=False, **extra_model_kwargs) -> Generator | dict: - req = { - "parameters": params, - "messages": [self.convert_prompt_message_to_maas_message(prompt) for prompt in messages], - **extra_model_kwargs, - } - if not stream: - return super().chat( - self.endpoint_id, - req, - ) - return super().stream_chat( - self.endpoint_id, - req, - ) - - def embeddings(self, texts: list[str]) -> dict: - req = {"input": texts} - return super().embeddings(self.endpoint_id, req) - - @staticmethod - def convert_prompt_message_to_maas_message(message: PromptMessage) -> dict: - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": ChatRole.USER, "content": message.content} - else: - content = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - raise ValueError("Content object type only support image_url") - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - image_data = re.sub(r"^data:image\/[a-zA-Z]+;base64,", "", message_content.data) - content.append( - { - "type": "image_url", - "image_url": { - "url": "", - "image_bytes": image_data, - "detail": message_content.detail, - }, - } - ) - - message_dict = {"role": ChatRole.USER, "content": content} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": ChatRole.ASSISTANT, "content": message.content} - if message.tool_calls: - message_dict["tool_calls"] = [ - {"name": call.function.name, "arguments": call.function.arguments} for call in message.tool_calls - ] - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": ChatRole.SYSTEM, "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = {"role": ChatRole.FUNCTION, "content": message.content, "name": message.tool_call_id} - else: - raise ValueError(f"Got unknown PromptMessage type {message}") - - return message_dict - - @staticmethod - def wrap_exception(fn: Callable[[], dict | Generator]) -> dict | Generator: - try: - resp = fn() - except MaasError as e: - raise wrap_error(e) - - return resp - - @staticmethod - def transform_tool_prompt_to_maas_config(tool: PromptMessageTool): - return { - "type": "function", - "function": { - "name": tool.name, - "description": tool.description, - "parameters": tool.parameters, - }, - } diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/errors.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/errors.py deleted file mode 100644 index 91dbe21a616195..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/errors.py +++ /dev/null @@ -1,156 +0,0 @@ -from core.model_runtime.model_providers.volcengine_maas.legacy.volc_sdk import MaasError - - -class ClientSDKRequestError(MaasError): - pass - - -class SignatureDoesNotMatchError(MaasError): - pass - - -class RequestTimeoutError(MaasError): - pass - - -class ServiceConnectionTimeoutError(MaasError): - pass - - -class MissingAuthenticationHeaderError(MaasError): - pass - - -class AuthenticationHeaderIsInvalidError(MaasError): - pass - - -class InternalServiceError(MaasError): - pass - - -class MissingParameterError(MaasError): - pass - - -class InvalidParameterError(MaasError): - pass - - -class AuthenticationExpireError(MaasError): - pass - - -class EndpointIsInvalidError(MaasError): - pass - - -class EndpointIsNotEnableError(MaasError): - pass - - -class ModelNotSupportStreamModeError(MaasError): - pass - - -class ReqTextExistRiskError(MaasError): - pass - - -class RespTextExistRiskError(MaasError): - pass - - -class EndpointRateLimitExceededError(MaasError): - pass - - -class ServiceConnectionRefusedError(MaasError): - pass - - -class ServiceConnectionClosedError(MaasError): - pass - - -class UnauthorizedUserForEndpointError(MaasError): - pass - - -class InvalidEndpointWithNoURLError(MaasError): - pass - - -class EndpointAccountRpmRateLimitExceededError(MaasError): - pass - - -class EndpointAccountTpmRateLimitExceededError(MaasError): - pass - - -class ServiceResourceWaitQueueFullError(MaasError): - pass - - -class EndpointIsPendingError(MaasError): - pass - - -class ServiceNotOpenError(MaasError): - pass - - -AuthErrors = { - "SignatureDoesNotMatch": SignatureDoesNotMatchError, - "MissingAuthenticationHeader": MissingAuthenticationHeaderError, - "AuthenticationHeaderIsInvalid": AuthenticationHeaderIsInvalidError, - "AuthenticationExpire": AuthenticationExpireError, - "UnauthorizedUserForEndpoint": UnauthorizedUserForEndpointError, -} - -BadRequestErrors = { - "MissingParameter": MissingParameterError, - "InvalidParameter": InvalidParameterError, - "EndpointIsInvalid": EndpointIsInvalidError, - "EndpointIsNotEnable": EndpointIsNotEnableError, - "ModelNotSupportStreamMode": ModelNotSupportStreamModeError, - "ReqTextExistRisk": ReqTextExistRiskError, - "RespTextExistRisk": RespTextExistRiskError, - "InvalidEndpointWithNoURL": InvalidEndpointWithNoURLError, - "ServiceNotOpen": ServiceNotOpenError, -} - -RateLimitErrors = { - "EndpointRateLimitExceeded": EndpointRateLimitExceededError, - "EndpointAccountRpmRateLimitExceeded": EndpointAccountRpmRateLimitExceededError, - "EndpointAccountTpmRateLimitExceeded": EndpointAccountTpmRateLimitExceededError, -} - -ServerUnavailableErrors = { - "InternalServiceError": InternalServiceError, - "EndpointIsPending": EndpointIsPendingError, - "ServiceResourceWaitQueueFull": ServiceResourceWaitQueueFullError, -} - -ConnectionErrors = { - "ClientSDKRequestError": ClientSDKRequestError, - "RequestTimeout": RequestTimeoutError, - "ServiceConnectionTimeout": ServiceConnectionTimeoutError, - "ServiceConnectionRefused": ServiceConnectionRefusedError, - "ServiceConnectionClosed": ServiceConnectionClosedError, -} - -ErrorCodeMap = { - **AuthErrors, - **BadRequestErrors, - **RateLimitErrors, - **ServerUnavailableErrors, - **ConnectionErrors, -} - - -def wrap_error(e: MaasError) -> Exception: - if ErrorCodeMap.get(e.code): - return ErrorCodeMap.get(e.code)(e.code_n, e.code, e.message, e.req_id) - return e diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/__init__.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/__init__.py deleted file mode 100644 index 8b3eb157be5cfe..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from .common import ChatRole -from .maas import MaasError, MaasService - -__all__ = ["MaasService", "ChatRole", "MaasError"] diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/__init__.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/__init__.py deleted file mode 100644 index 8b137891791fe9..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/__init__.py +++ /dev/null @@ -1 +0,0 @@ - diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/auth.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/auth.py deleted file mode 100644 index c22bf8e76de36a..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/auth.py +++ /dev/null @@ -1,159 +0,0 @@ -# coding : utf-8 -import datetime -from itertools import starmap - -import pytz - -from .util import Util - - -class MetaData: - def __init__(self): - self.algorithm = "" - self.credential_scope = "" - self.signed_headers = "" - self.date = "" - self.region = "" - self.service = "" - - def set_date(self, date): - self.date = date - - def set_service(self, service): - self.service = service - - def set_region(self, region): - self.region = region - - def set_algorithm(self, algorithm): - self.algorithm = algorithm - - def set_credential_scope(self, credential_scope): - self.credential_scope = credential_scope - - def set_signed_headers(self, signed_headers): - self.signed_headers = signed_headers - - -class SignResult: - def __init__(self): - self.xdate = "" - self.xCredential = "" - self.xAlgorithm = "" - self.xSignedHeaders = "" - self.xSignedQueries = "" - self.xSignature = "" - self.xContextSha256 = "" - self.xSecurityToken = "" - - self.authorization = "" - - def __str__(self): - return "\n".join(list(starmap("{}:{}".format, self.__dict__.items()))) - - -class Credentials: - def __init__(self, ak, sk, service, region, session_token=""): - self.ak = ak - self.sk = sk - self.service = service - self.region = region - self.session_token = session_token - - def set_ak(self, ak): - self.ak = ak - - def set_sk(self, sk): - self.sk = sk - - def set_session_token(self, session_token): - self.session_token = session_token - - -class Signer: - @staticmethod - def sign(request, credentials): - if request.path == "": - request.path = "/" - if request.method != "GET" and "Content-Type" not in request.headers: - request.headers["Content-Type"] = "application/x-www-form-urlencoded; charset=utf-8" - - format_date = Signer.get_current_format_date() - request.headers["X-Date"] = format_date - if credentials.session_token != "": - request.headers["X-Security-Token"] = credentials.session_token - - md = MetaData() - md.set_algorithm("HMAC-SHA256") - md.set_service(credentials.service) - md.set_region(credentials.region) - md.set_date(format_date[:8]) - - hashed_canon_req = Signer.hashed_canonical_request_v4(request, md) - md.set_credential_scope("/".join([md.date, md.region, md.service, "request"])) - - signing_str = "\n".join([md.algorithm, format_date, md.credential_scope, hashed_canon_req]) - signing_key = Signer.get_signing_secret_key_v4(credentials.sk, md.date, md.region, md.service) - sign = Util.to_hex(Util.hmac_sha256(signing_key, signing_str)) - request.headers["Authorization"] = Signer.build_auth_header_v4(sign, md, credentials) - - @staticmethod - def hashed_canonical_request_v4(request, meta): - body_hash = Util.sha256(request.body) - request.headers["X-Content-Sha256"] = body_hash - - signed_headers = {} - for key in request.headers: - if key in {"Content-Type", "Content-Md5", "Host"} or key.startswith("X-"): - signed_headers[key.lower()] = request.headers[key] - - if "host" in signed_headers: - v = signed_headers["host"] - if v.find(":") != -1: - split = v.split(":") - port = split[1] - if str(port) == "80" or str(port) == "443": - signed_headers["host"] = split[0] - - signed_str = "" - for key in sorted(signed_headers.keys()): - signed_str += key + ":" + signed_headers[key] + "\n" - - meta.set_signed_headers(";".join(sorted(signed_headers.keys()))) - - canonical_request = "\n".join( - [ - request.method, - Util.norm_uri(request.path), - Util.norm_query(request.query), - signed_str, - meta.signed_headers, - body_hash, - ] - ) - - return Util.sha256(canonical_request) - - @staticmethod - def get_signing_secret_key_v4(sk, date, region, service): - date = Util.hmac_sha256(bytes(sk, encoding="utf-8"), date) - region = Util.hmac_sha256(date, region) - service = Util.hmac_sha256(region, service) - return Util.hmac_sha256(service, "request") - - @staticmethod - def build_auth_header_v4(signature, meta, credentials): - credential = credentials.ak + "/" + meta.credential_scope - return ( - meta.algorithm - + " Credential=" - + credential - + ", SignedHeaders=" - + meta.signed_headers - + ", Signature=" - + signature - ) - - @staticmethod - def get_current_format_date(): - return datetime.datetime.now(tz=pytz.timezone("UTC")).strftime("%Y%m%dT%H%M%SZ") diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/service.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/service.py deleted file mode 100644 index 33c41f3eb331a3..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/service.py +++ /dev/null @@ -1,216 +0,0 @@ -import json -from collections import OrderedDict -from urllib.parse import urlencode - -import requests - -from .auth import Signer - -VERSION = "v1.0.137" - - -class Service: - def __init__(self, service_info, api_info): - self.service_info = service_info - self.api_info = api_info - self.session = requests.session() - - def set_ak(self, ak): - self.service_info.credentials.set_ak(ak) - - def set_sk(self, sk): - self.service_info.credentials.set_sk(sk) - - def set_session_token(self, session_token): - self.service_info.credentials.set_session_token(session_token) - - def set_host(self, host): - self.service_info.host = host - - def set_scheme(self, scheme): - self.service_info.scheme = scheme - - def get(self, api, params, doseq=0): - if api not in self.api_info: - raise Exception("no such api") - api_info = self.api_info[api] - - r = self.prepare_request(api_info, params, doseq) - - Signer.sign(r, self.service_info.credentials) - - url = r.build(doseq) - resp = self.session.get( - url, headers=r.headers, timeout=(self.service_info.connection_timeout, self.service_info.socket_timeout) - ) - if resp.status_code == 200: - return resp.text - else: - raise Exception(resp.text) - - def post(self, api, params, form): - if api not in self.api_info: - raise Exception("no such api") - api_info = self.api_info[api] - r = self.prepare_request(api_info, params) - r.headers["Content-Type"] = "application/x-www-form-urlencoded" - r.form = self.merge(api_info.form, form) - r.body = urlencode(r.form, True) - Signer.sign(r, self.service_info.credentials) - - url = r.build() - - resp = self.session.post( - url, - headers=r.headers, - data=r.form, - timeout=(self.service_info.connection_timeout, self.service_info.socket_timeout), - ) - if resp.status_code == 200: - return resp.text - else: - raise Exception(resp.text) - - def json(self, api, params, body): - if api not in self.api_info: - raise Exception("no such api") - api_info = self.api_info[api] - r = self.prepare_request(api_info, params) - r.headers["Content-Type"] = "application/json" - r.body = body - - Signer.sign(r, self.service_info.credentials) - - url = r.build() - resp = self.session.post( - url, - headers=r.headers, - data=r.body, - timeout=(self.service_info.connection_timeout, self.service_info.socket_timeout), - ) - if resp.status_code == 200: - return json.dumps(resp.json()) - else: - raise Exception(resp.text.encode("utf-8")) - - def put(self, url, file_path, headers): - with open(file_path, "rb") as f: - resp = self.session.put(url, headers=headers, data=f) - if resp.status_code == 200: - return True, resp.text.encode("utf-8") - else: - return False, resp.text.encode("utf-8") - - def put_data(self, url, data, headers): - resp = self.session.put(url, headers=headers, data=data) - if resp.status_code == 200: - return True, resp.text.encode("utf-8") - else: - return False, resp.text.encode("utf-8") - - def prepare_request(self, api_info, params, doseq=0): - for key in params: - if type(params[key]) == int or type(params[key]) == float or type(params[key]) == bool: - params[key] = str(params[key]) - elif type(params[key]) == list: - if not doseq: - params[key] = ",".join(params[key]) - - connection_timeout = self.service_info.connection_timeout - socket_timeout = self.service_info.socket_timeout - - r = Request() - r.set_schema(self.service_info.scheme) - r.set_method(api_info.method) - r.set_connection_timeout(connection_timeout) - r.set_socket_timeout(socket_timeout) - - headers = self.merge(api_info.header, self.service_info.header) - headers["Host"] = self.service_info.host - headers["User-Agent"] = "volc-sdk-python/" + VERSION - r.set_headers(headers) - - query = self.merge(api_info.query, params) - r.set_query(query) - - r.set_host(self.service_info.host) - r.set_path(api_info.path) - - return r - - @staticmethod - def merge(param1, param2): - od = OrderedDict() - for key in param1: - od[key] = param1[key] - - for key in param2: - od[key] = param2[key] - - return od - - -class Request: - def __init__(self): - self.schema = "" - self.method = "" - self.host = "" - self.path = "" - self.headers = OrderedDict() - self.query = OrderedDict() - self.body = "" - self.form = {} - self.connection_timeout = 0 - self.socket_timeout = 0 - - def set_schema(self, schema): - self.schema = schema - - def set_method(self, method): - self.method = method - - def set_host(self, host): - self.host = host - - def set_path(self, path): - self.path = path - - def set_headers(self, headers): - self.headers = headers - - def set_query(self, query): - self.query = query - - def set_body(self, body): - self.body = body - - def set_connection_timeout(self, connection_timeout): - self.connection_timeout = connection_timeout - - def set_socket_timeout(self, socket_timeout): - self.socket_timeout = socket_timeout - - def build(self, doseq=0): - return self.schema + "://" + self.host + self.path + "?" + urlencode(self.query, doseq) - - -class ServiceInfo: - def __init__(self, host, header, credentials, connection_timeout, socket_timeout, scheme="http"): - self.host = host - self.header = header - self.credentials = credentials - self.connection_timeout = connection_timeout - self.socket_timeout = socket_timeout - self.scheme = scheme - - -class ApiInfo: - def __init__(self, method, path, query, form, header): - self.method = method - self.path = path - self.query = query - self.form = form - self.header = header - - def __str__(self): - return "method: " + self.method + ", path: " + self.path diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/util.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/util.py deleted file mode 100644 index 178d63714e9cf1..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/base/util.py +++ /dev/null @@ -1,44 +0,0 @@ -import hashlib -import hmac -import operator -from functools import reduce -from urllib.parse import quote - - -class Util: - @staticmethod - def norm_uri(path): - return quote(path).replace("%2F", "/").replace("+", "%20") - - @staticmethod - def norm_query(params): - query = "" - for key in sorted(params.keys()): - if type(params[key]) == list: - for k in params[key]: - query = query + quote(key, safe="-_.~") + "=" + quote(k, safe="-_.~") + "&" - else: - query = query + quote(key, safe="-_.~") + "=" + quote(params[key], safe="-_.~") + "&" - query = query[:-1] - return query.replace("+", "%20") - - @staticmethod - def hmac_sha256(key, content): - return hmac.new(key, bytes(content, encoding="utf-8"), hashlib.sha256).digest() - - @staticmethod - def sha256(content): - if isinstance(content, str) is True: - return hashlib.sha256(content.encode("utf-8")).hexdigest() - else: - return hashlib.sha256(content).hexdigest() - - @staticmethod - def to_hex(content): - lst = [] - for ch in content: - hv = hex(ch).replace("0x", "") - if len(hv) == 1: - hv = "0" + hv - lst.append(hv) - return reduce(operator.add, lst) diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/common.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/common.py deleted file mode 100644 index 3825fd65741ef5..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/common.py +++ /dev/null @@ -1,77 +0,0 @@ -import json -import random -from datetime import datetime - - -class ChatRole: - USER = "user" - ASSISTANT = "assistant" - SYSTEM = "system" - FUNCTION = "function" - - -class _Dict(dict): - __setattr__ = dict.__setitem__ - __getattr__ = dict.__getitem__ - - def __missing__(self, key): - return None - - -def dict_to_object(dict_obj): - # 支持嵌套类型 - if isinstance(dict_obj, list): - insts = [] - for i in dict_obj: - insts.append(dict_to_object(i)) - return insts - - if isinstance(dict_obj, dict): - inst = _Dict() - for k, v in dict_obj.items(): - inst[k] = dict_to_object(v) - return inst - - return dict_obj - - -def json_to_object(json_str, req_id=None): - obj = dict_to_object(json.loads(json_str)) - if obj and isinstance(obj, dict) and req_id: - obj["req_id"] = req_id - return obj - - -def gen_req_id(): - return datetime.now().strftime("%Y%m%d%H%M%S") + format(random.randint(0, 2**64 - 1), "020X") - - -class SSEDecoder: - def __init__(self, source): - self.source = source - - def _read(self): - data = b"" - for chunk in self.source: - for line in chunk.splitlines(True): - data += line - if data.endswith((b"\r\r", b"\n\n", b"\r\n\r\n")): - yield data - data = b"" - if data: - yield data - - def next(self): - for chunk in self._read(): - for line in chunk.splitlines(): - # skip comment - if line.startswith(b":"): - continue - - if b":" in line: - field, value = line.split(b":", 1) - else: - field, value = line, b"" - - if field == b"data" and len(value) > 0: - yield value diff --git a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/maas.py b/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/maas.py deleted file mode 100644 index a3836685f1fbf4..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/legacy/volc_sdk/maas.py +++ /dev/null @@ -1,198 +0,0 @@ -import copy -import json -from collections.abc import Iterator - -from .base.auth import Credentials, Signer -from .base.service import ApiInfo, Service, ServiceInfo -from .common import SSEDecoder, dict_to_object, gen_req_id, json_to_object - - -class MaasService(Service): - def __init__(self, host, region, connection_timeout=60, socket_timeout=60): - service_info = self.get_service_info(host, region, connection_timeout, socket_timeout) - self._apikey = None - api_info = self.get_api_info() - super().__init__(service_info, api_info) - - def set_apikey(self, apikey): - self._apikey = apikey - - @staticmethod - def get_service_info(host, region, connection_timeout, socket_timeout): - service_info = ServiceInfo( - host, - {"Accept": "application/json"}, - Credentials("", "", "ml_maas", region), - connection_timeout, - socket_timeout, - "https", - ) - return service_info - - @staticmethod - def get_api_info(): - api_info = { - "chat": ApiInfo("POST", "/api/v2/endpoint/{endpoint_id}/chat", {}, {}, {}), - "embeddings": ApiInfo("POST", "/api/v2/endpoint/{endpoint_id}/embeddings", {}, {}, {}), - } - return api_info - - def chat(self, endpoint_id, req): - req["stream"] = False - return self._request(endpoint_id, "chat", req) - - def stream_chat(self, endpoint_id, req): - req_id = gen_req_id() - self._validate("chat", req_id) - apikey = self._apikey - - try: - req["stream"] = True - res = self._call(endpoint_id, "chat", req_id, {}, json.dumps(req).encode("utf-8"), apikey, stream=True) - - decoder = SSEDecoder(res) - - def iter_fn(): - for data in decoder.next(): - if data == b"[DONE]": - return - - try: - res = json_to_object(str(data, encoding="utf-8"), req_id=req_id) - except Exception: - raise - - if res.error is not None and res.error.code_n != 0: - raise MaasError( - res.error.code_n, - res.error.code, - res.error.message, - req_id, - ) - yield res - - return iter_fn() - except MaasError: - raise - except Exception as e: - raise new_client_sdk_request_error(str(e)) - - def embeddings(self, endpoint_id, req): - return self._request(endpoint_id, "embeddings", req) - - def _request(self, endpoint_id, api, req, params={}): - req_id = gen_req_id() - - self._validate(api, req_id) - - apikey = self._apikey - - try: - res = self._call(endpoint_id, api, req_id, params, json.dumps(req).encode("utf-8"), apikey) - resp = dict_to_object(res.json()) - if resp and isinstance(resp, dict): - resp["req_id"] = req_id - return resp - - except MaasError as e: - raise e - except Exception as e: - raise new_client_sdk_request_error(str(e), req_id) - - def _validate(self, api, req_id): - credentials_exist = ( - self.service_info.credentials is not None - and self.service_info.credentials.sk is not None - and self.service_info.credentials.ak is not None - ) - - if not self._apikey and not credentials_exist: - raise new_client_sdk_request_error("no valid credential", req_id) - - if api not in self.api_info: - raise new_client_sdk_request_error("no such api", req_id) - - def _call(self, endpoint_id, api, req_id, params, body, apikey=None, stream=False): - api_info = copy.deepcopy(self.api_info[api]) - api_info.path = api_info.path.format(endpoint_id=endpoint_id) - - r = self.prepare_request(api_info, params) - r.headers["x-tt-logid"] = req_id - r.headers["Content-Type"] = "application/json" - r.body = body - - if apikey is None: - Signer.sign(r, self.service_info.credentials) - elif apikey is not None: - r.headers["Authorization"] = "Bearer " + apikey - - url = r.build() - res = self.session.post( - url, - headers=r.headers, - data=r.body, - timeout=( - self.service_info.connection_timeout, - self.service_info.socket_timeout, - ), - stream=stream, - ) - - if res.status_code != 200: - raw = res.text.encode() - res.close() - try: - resp = json_to_object(str(raw, encoding="utf-8"), req_id=req_id) - except Exception: - raise new_client_sdk_request_error(raw, req_id) - - if resp.error: - raise MaasError(resp.error.code_n, resp.error.code, resp.error.message, req_id) - else: - raise new_client_sdk_request_error(resp, req_id) - - return res - - -class MaasError(Exception): - def __init__(self, code_n, code, message, req_id): - self.code_n = code_n - self.code = code - self.message = message - self.req_id = req_id - - def __str__(self): - return ( - "Detailed exception information is listed below.\n" - + "req_id: {}\n" - + "code_n: {}\n" - + "code: {}\n" - + "message: {}" - ).format(self.req_id, self.code_n, self.code, self.message) - - -def new_client_sdk_request_error(raw, req_id=""): - return MaasError(1709701, "ClientSDKRequestError", "MaaS SDK request error: {}".format(raw), req_id) - - -class BinaryResponseContent: - def __init__(self, response, request_id) -> None: - self.response = response - self.request_id = request_id - - def stream_to_file(self, file: str) -> None: - is_first = True - error_bytes = b"" - with open(file, mode="wb") as f: - for data in self.response: - if len(error_bytes) > 0 or (is_first and '"error":' in str(data)): - error_bytes += data - else: - f.write(data) - - if len(error_bytes) > 0: - resp = json_to_object(str(error_bytes, encoding="utf-8"), req_id=self.request_id) - raise MaasError(resp.error.code_n, resp.error.code, resp.error.message, self.request_id) - - def iter_bytes(self) -> Iterator[bytes]: - yield from self.response diff --git a/api/core/model_runtime/model_providers/volcengine_maas/llm/__init__.py b/api/core/model_runtime/model_providers/volcengine_maas/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/volcengine_maas/llm/llm.py b/api/core/model_runtime/model_providers/volcengine_maas/llm/llm.py deleted file mode 100644 index dec6c9d789c135..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/llm/llm.py +++ /dev/null @@ -1,388 +0,0 @@ -import logging -from collections.abc import Generator - -from volcenginesdkarkruntime.types.chat import ChatCompletion, ChatCompletionChunk - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.volcengine_maas.client import ArkClientV3 -from core.model_runtime.model_providers.volcengine_maas.legacy.client import MaaSClient -from core.model_runtime.model_providers.volcengine_maas.legacy.errors import ( - AuthErrors, - BadRequestErrors, - ConnectionErrors, - MaasError, - RateLimitErrors, - ServerUnavailableErrors, -) -from core.model_runtime.model_providers.volcengine_maas.llm.models import ( - get_model_config, - get_v2_req_params, - get_v3_req_params, -) - -logger = logging.getLogger(__name__) - - -class VolcengineMaaSLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - if ArkClientV3.is_legacy(credentials): - return self._generate_v2(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - return self._generate_v3(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate credentials - """ - if ArkClientV3.is_legacy(credentials): - return self._validate_credentials_v2(credentials) - return self._validate_credentials_v3(credentials) - - @staticmethod - def _validate_credentials_v2(credentials: dict) -> None: - client = MaaSClient.from_credential(credentials) - try: - client.chat( - { - "max_new_tokens": 16, - "temperature": 0.7, - "top_p": 0.9, - "top_k": 15, - }, - [UserPromptMessage(content="ping\nAnswer: ")], - ) - except MaasError as e: - raise CredentialsValidateFailedError(e.message) - - @staticmethod - def _validate_credentials_v3(credentials: dict) -> None: - client = ArkClientV3.from_credentials(credentials) - try: - client.chat( - max_tokens=16, - temperature=0.7, - top_p=0.9, - messages=[UserPromptMessage(content="ping\nAnswer: ")], - ) - except Exception as e: - raise CredentialsValidateFailedError(e) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - if ArkClientV3.is_legacy(credentials): - return self._get_num_tokens_v2(prompt_messages) - return self._get_num_tokens_v3(prompt_messages) - - def _get_num_tokens_v2(self, messages: list[PromptMessage]) -> int: - if len(messages) == 0: - return 0 - num_tokens = 0 - messages_dict = [MaaSClient.convert_prompt_message_to_maas_message(m) for m in messages] - for message in messages_dict: - for key, value in message.items(): - num_tokens += self._get_num_tokens_by_gpt2(str(key)) - num_tokens += self._get_num_tokens_by_gpt2(str(value)) - - return num_tokens - - def _get_num_tokens_v3(self, messages: list[PromptMessage]) -> int: - if len(messages) == 0: - return 0 - num_tokens = 0 - messages_dict = [ArkClientV3.convert_prompt_message(m) for m in messages] - for message in messages_dict: - for key, value in message.items(): - num_tokens += self._get_num_tokens_by_gpt2(str(key)) - num_tokens += self._get_num_tokens_by_gpt2(str(value)) - - return num_tokens - - def _generate_v2( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - client = MaaSClient.from_credential(credentials) - req_params = get_v2_req_params(credentials, model_parameters, stop) - extra_model_kwargs = {} - if tools: - extra_model_kwargs["tools"] = [MaaSClient.transform_tool_prompt_to_maas_config(tool) for tool in tools] - resp = MaaSClient.wrap_exception(lambda: client.chat(req_params, prompt_messages, stream, **extra_model_kwargs)) - - def _handle_stream_chat_response() -> Generator: - for index, r in enumerate(resp): - choices = r["choices"] - if not choices: - continue - choice = choices[0] - message = choice["message"] - usage = None - if r.get("usage"): - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=r["usage"]["prompt_tokens"], - completion_tokens=r["usage"]["completion_tokens"], - ) - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=AssistantPromptMessage(content=message["content"] or "", tool_calls=[]), - usage=usage, - finish_reason=choice.get("finish_reason"), - ), - ) - - def _handle_chat_response() -> LLMResult: - choices = resp["choices"] - if not choices: - raise ValueError("No choices found") - - choice = choices[0] - message = choice["message"] - - # parse tool calls - tool_calls = [] - if message["tool_calls"]: - for call in message["tool_calls"]: - tool_call = AssistantPromptMessage.ToolCall( - id=call["function"]["name"], - type=call["type"], - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=call["function"]["name"], arguments=call["function"]["arguments"] - ), - ) - tool_calls.append(tool_call) - - usage = resp["usage"] - return LLMResult( - model=model, - prompt_messages=prompt_messages, - message=AssistantPromptMessage( - content=message["content"] or "", - tool_calls=tool_calls, - ), - usage=self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=usage["prompt_tokens"], - completion_tokens=usage["completion_tokens"], - ), - ) - - if not stream: - return _handle_chat_response() - return _handle_stream_chat_response() - - def _generate_v3( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - client = ArkClientV3.from_credentials(credentials) - req_params = get_v3_req_params(credentials, model_parameters, stop) - if tools: - req_params["tools"] = tools - - def _handle_stream_chat_response(chunks: Generator[ChatCompletionChunk]) -> Generator: - for chunk in chunks: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage( - content=chunk.choices[0].delta.content if chunk.choices else "", tool_calls=[] - ), - usage=self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=chunk.usage.prompt_tokens, - completion_tokens=chunk.usage.completion_tokens, - ) - if chunk.usage - else None, - finish_reason=chunk.choices[0].finish_reason if chunk.choices else None, - ), - ) - - def _handle_chat_response(resp: ChatCompletion) -> LLMResult: - choice = resp.choices[0] - message = choice.message - # parse tool calls - tool_calls = [] - if message.tool_calls: - for call in message.tool_calls: - tool_call = AssistantPromptMessage.ToolCall( - id=call.id, - type=call.type, - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=call.function.name, arguments=call.function.arguments - ), - ) - tool_calls.append(tool_call) - - usage = resp.usage - return LLMResult( - model=model, - prompt_messages=prompt_messages, - message=AssistantPromptMessage( - content=message.content or "", - tool_calls=tool_calls, - ), - usage=self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=usage.prompt_tokens, - completion_tokens=usage.completion_tokens, - ), - ) - - if not stream: - resp = client.chat(prompt_messages, **req_params) - return _handle_chat_response(resp) - - chunks = client.stream_chat(prompt_messages, **req_params) - return _handle_stream_chat_response(chunks) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - model_config = get_model_config(credentials) - - rules = [ - ParameterRule( - name="temperature", - type=ParameterType.FLOAT, - use_template="temperature", - label=I18nObject(zh_Hans="温度", en_US="Temperature"), - ), - ParameterRule( - name="top_p", - type=ParameterType.FLOAT, - use_template="top_p", - label=I18nObject(zh_Hans="Top P", en_US="Top P"), - ), - ParameterRule( - name="top_k", type=ParameterType.INT, min=1, default=1, label=I18nObject(zh_Hans="Top K", en_US="Top K") - ), - ParameterRule( - name="presence_penalty", - type=ParameterType.FLOAT, - use_template="presence_penalty", - label=I18nObject( - en_US="Presence Penalty", - zh_Hans="存在惩罚", - ), - min=-2.0, - max=2.0, - ), - ParameterRule( - name="frequency_penalty", - type=ParameterType.FLOAT, - use_template="frequency_penalty", - label=I18nObject( - en_US="Frequency Penalty", - zh_Hans="频率惩罚", - ), - min=-2.0, - max=2.0, - ), - ParameterRule( - name="max_tokens", - type=ParameterType.INT, - use_template="max_tokens", - min=1, - max=model_config.properties.max_tokens, - default=512, - label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"), - ), - ] - - model_properties = {} - model_properties[ModelPropertyKey.CONTEXT_SIZE] = model_config.properties.context_size - model_properties[ModelPropertyKey.MODE] = model_config.properties.mode.value - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - model_properties=model_properties, - parameter_rules=rules, - features=model_config.features, - ) - - return entity - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: ConnectionErrors.values(), - InvokeServerUnavailableError: ServerUnavailableErrors.values(), - InvokeRateLimitError: RateLimitErrors.values(), - InvokeAuthorizationError: AuthErrors.values(), - InvokeBadRequestError: BadRequestErrors.values(), - } diff --git a/api/core/model_runtime/model_providers/volcengine_maas/llm/models.py b/api/core/model_runtime/model_providers/volcengine_maas/llm/models.py deleted file mode 100644 index d8be14b0247698..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/llm/models.py +++ /dev/null @@ -1,142 +0,0 @@ -from pydantic import BaseModel - -from core.model_runtime.entities.llm_entities import LLMMode -from core.model_runtime.entities.model_entities import ModelFeature - - -class ModelProperties(BaseModel): - context_size: int - max_tokens: int - mode: LLMMode - - -class ModelConfig(BaseModel): - properties: ModelProperties - features: list[ModelFeature] - - -configs: dict[str, ModelConfig] = { - "Doubao-pro-4k": ModelConfig( - properties=ModelProperties(context_size=4096, max_tokens=4096, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "Doubao-lite-4k": ModelConfig( - properties=ModelProperties(context_size=4096, max_tokens=4096, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "Doubao-pro-32k": ModelConfig( - properties=ModelProperties(context_size=32768, max_tokens=4096, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "Doubao-lite-32k": ModelConfig( - properties=ModelProperties(context_size=32768, max_tokens=4096, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "Doubao-pro-128k": ModelConfig( - properties=ModelProperties(context_size=131072, max_tokens=4096, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "Doubao-lite-128k": ModelConfig( - properties=ModelProperties(context_size=131072, max_tokens=4096, mode=LLMMode.CHAT), features=[] - ), - "Skylark2-pro-4k": ModelConfig( - properties=ModelProperties(context_size=4096, max_tokens=4096, mode=LLMMode.CHAT), features=[] - ), - "Llama3-8B": ModelConfig( - properties=ModelProperties(context_size=8192, max_tokens=8192, mode=LLMMode.CHAT), features=[] - ), - "Llama3-70B": ModelConfig( - properties=ModelProperties(context_size=8192, max_tokens=8192, mode=LLMMode.CHAT), features=[] - ), - "Moonshot-v1-8k": ModelConfig( - properties=ModelProperties(context_size=8192, max_tokens=4096, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "Moonshot-v1-32k": ModelConfig( - properties=ModelProperties(context_size=32768, max_tokens=16384, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "Moonshot-v1-128k": ModelConfig( - properties=ModelProperties(context_size=131072, max_tokens=65536, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "GLM3-130B": ModelConfig( - properties=ModelProperties(context_size=8192, max_tokens=4096, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "GLM3-130B-Fin": ModelConfig( - properties=ModelProperties(context_size=8192, max_tokens=4096, mode=LLMMode.CHAT), - features=[ModelFeature.TOOL_CALL], - ), - "Mistral-7B": ModelConfig( - properties=ModelProperties(context_size=8192, max_tokens=2048, mode=LLMMode.CHAT), features=[] - ), -} - - -def get_model_config(credentials: dict) -> ModelConfig: - base_model = credentials.get("base_model_name", "") - model_configs = configs.get(base_model) - if not model_configs: - return ModelConfig( - properties=ModelProperties( - context_size=int(credentials.get("context_size", 0)), - max_tokens=int(credentials.get("max_tokens", 0)), - mode=LLMMode.value_of(credentials.get("mode", "chat")), - ), - features=[], - ) - return model_configs - - -def get_v2_req_params(credentials: dict, model_parameters: dict, stop: list[str] | None = None): - req_params = {} - # predefined properties - model_configs = get_model_config(credentials) - if model_configs: - req_params["max_prompt_tokens"] = model_configs.properties.context_size - req_params["max_new_tokens"] = model_configs.properties.max_tokens - - # model parameters - if model_parameters.get("max_tokens"): - req_params["max_new_tokens"] = model_parameters.get("max_tokens") - if model_parameters.get("temperature"): - req_params["temperature"] = model_parameters.get("temperature") - if model_parameters.get("top_p"): - req_params["top_p"] = model_parameters.get("top_p") - if model_parameters.get("top_k"): - req_params["top_k"] = model_parameters.get("top_k") - if model_parameters.get("presence_penalty"): - req_params["presence_penalty"] = model_parameters.get("presence_penalty") - if model_parameters.get("frequency_penalty"): - req_params["frequency_penalty"] = model_parameters.get("frequency_penalty") - - if stop: - req_params["stop"] = stop - - return req_params - - -def get_v3_req_params(credentials: dict, model_parameters: dict, stop: list[str] | None = None): - req_params = {} - # predefined properties - model_configs = get_model_config(credentials) - if model_configs: - req_params["max_tokens"] = model_configs.properties.max_tokens - - # model parameters - if model_parameters.get("max_tokens"): - req_params["max_tokens"] = model_parameters.get("max_tokens") - if model_parameters.get("temperature"): - req_params["temperature"] = model_parameters.get("temperature") - if model_parameters.get("top_p"): - req_params["top_p"] = model_parameters.get("top_p") - if model_parameters.get("presence_penalty"): - req_params["presence_penalty"] = model_parameters.get("presence_penalty") - if model_parameters.get("frequency_penalty"): - req_params["frequency_penalty"] = model_parameters.get("frequency_penalty") - - if stop: - req_params["stop"] = stop - - return req_params diff --git a/api/core/model_runtime/model_providers/volcengine_maas/text_embedding/__init__.py b/api/core/model_runtime/model_providers/volcengine_maas/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/volcengine_maas/text_embedding/models.py b/api/core/model_runtime/model_providers/volcengine_maas/text_embedding/models.py deleted file mode 100644 index ce4f0c3ab1960e..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/text_embedding/models.py +++ /dev/null @@ -1,28 +0,0 @@ -from pydantic import BaseModel - - -class ModelProperties(BaseModel): - context_size: int - max_chunks: int - - -class ModelConfig(BaseModel): - properties: ModelProperties - - -ModelConfigs = { - "Doubao-embedding": ModelConfig(properties=ModelProperties(context_size=4096, max_chunks=32)), -} - - -def get_model_config(credentials: dict) -> ModelConfig: - base_model = credentials.get("base_model_name", "") - model_configs = ModelConfigs.get(base_model) - if not model_configs: - return ModelConfig( - properties=ModelProperties( - context_size=int(credentials.get("context_size", 0)), - max_chunks=int(credentials.get("max_chunks", 0)), - ) - ) - return model_configs diff --git a/api/core/model_runtime/model_providers/volcengine_maas/volcengine_maas.py b/api/core/model_runtime/model_providers/volcengine_maas/volcengine_maas.py deleted file mode 100644 index 10f9be2d08e70d..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/volcengine_maas.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class VolcengineMaaSProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/volcengine_maas/volcengine_maas.yaml b/api/core/model_runtime/model_providers/volcengine_maas/volcengine_maas.yaml deleted file mode 100644 index 13e00da76fb149..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/volcengine_maas.yaml +++ /dev/null @@ -1,266 +0,0 @@ -provider: volcengine_maas -label: - en_US: Volcengine -description: - en_US: Volcengine Ark models. - zh_Hans: 火山方舟提供的模型，例如 Doubao-pro-4k、Doubao-pro-32k 和 Doubao-pro-128k。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg - zh_Hans: icon_l_zh.svg -background: "#F9FAFB" -help: - title: - en_US: Get your Access Key and Secret Access Key from Volcengine Console - zh_Hans: 从火山引擎控制台获取您的 Access Key 和 Secret Access Key - url: - en_US: https://console.volcengine.com/iam/keymanage/ -supported_model_types: - - llm - - text-embedding -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your Model Name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: auth_method - required: true - label: - en_US: Authentication Method - zh_Hans: 鉴权方式 - type: select - default: aksk - options: - - label: - en_US: API Key - value: api_key - - label: - en_US: Access Key / Secret Access Key - value: aksk - placeholder: - en_US: Enter your Authentication Method - zh_Hans: 选择鉴权方式 - - variable: volc_access_key_id - required: true - show_on: - - variable: auth_method - value: aksk - label: - en_US: Access Key - zh_Hans: Access Key - type: secret-input - placeholder: - en_US: Enter your Access Key - zh_Hans: 输入您的 Access Key - - variable: volc_secret_access_key - required: true - show_on: - - variable: auth_method - value: aksk - label: - en_US: Secret Access Key - zh_Hans: Secret Access Key - type: secret-input - placeholder: - en_US: Enter your Secret Access Key - zh_Hans: 输入您的 Secret Access Key - - variable: volc_api_key - required: true - show_on: - - variable: auth_method - value: api_key - label: - en_US: API Key - type: secret-input - placeholder: - en_US: Enter your API Key - zh_Hans: 输入您的 API Key - - variable: volc_region - required: true - label: - en_US: Volcengine Region - zh_Hans: 火山引擎地域 - type: text-input - default: cn-beijing - placeholder: - en_US: Enter Volcengine Region - zh_Hans: 输入火山引擎地域 - - variable: api_endpoint_host - required: true - label: - en_US: API Endpoint Host - zh_Hans: API Endpoint Host - type: text-input - default: https://ark.cn-beijing.volces.com/api/v3 - placeholder: - en_US: Enter your API Endpoint Host - zh_Hans: 输入 API Endpoint Host - - variable: endpoint_id - required: true - label: - en_US: Endpoint ID - zh_Hans: Endpoint ID - type: text-input - placeholder: - en_US: Enter your Endpoint ID - zh_Hans: 输入您的 Endpoint ID - - variable: base_model_name - label: - en_US: Base Model - zh_Hans: 基础模型 - type: select - required: true - options: - - label: - en_US: Doubao-pro-4k - value: Doubao-pro-4k - show_on: - - variable: __model_type - value: llm - - label: - en_US: Doubao-lite-4k - value: Doubao-lite-4k - show_on: - - variable: __model_type - value: llm - - label: - en_US: Doubao-pro-32k - value: Doubao-pro-32k - show_on: - - variable: __model_type - value: llm - - label: - en_US: Doubao-lite-32k - value: Doubao-lite-32k - show_on: - - variable: __model_type - value: llm - - label: - en_US: Doubao-pro-128k - value: Doubao-pro-128k - show_on: - - variable: __model_type - value: llm - - label: - en_US: Doubao-lite-128k - value: Doubao-lite-128k - show_on: - - variable: __model_type - value: llm - - label: - en_US: Llama3-8B - value: Llama3-8B - show_on: - - variable: __model_type - value: llm - - label: - en_US: Llama3-70B - value: Llama3-70B - show_on: - - variable: __model_type - value: llm - - label: - en_US: Moonshot-v1-8k - value: Moonshot-v1-8k - show_on: - - variable: __model_type - value: llm - - label: - en_US: Moonshot-v1-32k - value: Moonshot-v1-32k - show_on: - - variable: __model_type - value: llm - - label: - en_US: Moonshot-v1-128k - value: Moonshot-v1-128k - show_on: - - variable: __model_type - value: llm - - label: - en_US: GLM3-130B - value: GLM3-130B - show_on: - - variable: __model_type - value: llm - - label: - en_US: GLM3-130B-Fin - value: GLM3-130B-Fin - show_on: - - variable: __model_type - value: llm - - label: - en_US: Mistral-7B - value: Mistral-7B - show_on: - - variable: __model_type - value: llm - - label: - en_US: Doubao-embedding - value: Doubao-embedding - show_on: - - variable: __model_type - value: text-embedding - - label: - en_US: Custom - zh_Hans: 自定义 - value: Custom - - variable: mode - required: true - show_on: - - variable: __model_type - value: llm - - variable: base_model_name - value: Custom - label: - zh_Hans: 模型类型 - en_US: Completion Mode - type: select - default: chat - placeholder: - zh_Hans: 选择对话类型 - en_US: Select Completion Mode - options: - - value: completion - label: - en_US: Completion - zh_Hans: 补全 - - value: chat - label: - en_US: Chat - zh_Hans: 对话 - - variable: context_size - required: true - show_on: - - variable: base_model_name - value: Custom - label: - zh_Hans: 模型上下文长度 - en_US: Model Context Size - type: text-input - default: "4096" - placeholder: - zh_Hans: 输入您的模型上下文长度 - en_US: Enter your Model Context Size - - variable: max_tokens - required: true - show_on: - - variable: __model_type - value: llm - - variable: base_model_name - value: Custom - label: - zh_Hans: 最大 token 上限 - en_US: Upper Bound for Max Tokens - default: "4096" - type: text-input - placeholder: - zh_Hans: 输入您的模型最大 token 上限 - en_US: Enter your model Upper Bound for Max Tokens diff --git a/api/core/model_runtime/model_providers/wenxin/__init__.py b/api/core/model_runtime/model_providers/wenxin/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/wenxin/_assets/icon_l_en.png 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a/api/core/model_runtime/model_providers/wenxin/_common.py b/api/core/model_runtime/model_providers/wenxin/_common.py deleted file mode 100644 index d72d1bd83a7e25..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/_common.py +++ /dev/null @@ -1,194 +0,0 @@ -from datetime import datetime, timedelta -from threading import Lock - -from requests import post - -from core.model_runtime.model_providers.wenxin.wenxin_errors import ( - BadRequestError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) - -baidu_access_tokens: dict[str, "BaiduAccessToken"] = {} -baidu_access_tokens_lock = Lock() - - -class BaiduAccessToken: - api_key: str - access_token: str - expires: datetime - - def __init__(self, api_key: str) -> None: - self.api_key = api_key - self.access_token = "" - self.expires = datetime.now() + timedelta(days=3) - - @staticmethod - def _get_access_token(api_key: str, secret_key: str) -> str: - """ - request access token from Baidu - """ - try: - response = post( - url=f"https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={api_key}&client_secret={secret_key}", - headers={"Content-Type": "application/json", "Accept": "application/json"}, - ) - except Exception as e: - raise InvalidAuthenticationError(f"Failed to get access token from Baidu: {e}") - - resp = response.json() - if "error" in resp: - if resp["error"] == "invalid_client": - raise InvalidAPIKeyError(f'Invalid API key or secret key: {resp["error_description"]}') - elif resp["error"] == "unknown_error": - raise InternalServerError(f'Internal server error: {resp["error_description"]}') - elif resp["error"] == "invalid_request": - raise BadRequestError(f'Bad request: {resp["error_description"]}') - elif resp["error"] == "rate_limit_exceeded": - raise RateLimitReachedError(f'Rate limit reached: {resp["error_description"]}') - else: - raise Exception(f'Unknown error: {resp["error_description"]}') - - return resp["access_token"] - - @staticmethod - def get_access_token(api_key: str, secret_key: str) -> "BaiduAccessToken": - """ - LLM from Baidu requires access token to invoke the API. - however, we have api_key and secret_key, and access token is valid for 30 days. - so we can cache the access token for 3 days. (avoid memory leak) - - it may be more efficient to use a ticker to refresh access token, but it will cause - more complexity, so we just refresh access tokens when get_access_token is called. - """ - - # loop up cache, remove expired access token - baidu_access_tokens_lock.acquire() - now = datetime.now() - for key in list(baidu_access_tokens.keys()): - token = baidu_access_tokens[key] - if token.expires < now: - baidu_access_tokens.pop(key) - - if api_key not in baidu_access_tokens: - # if access token not in cache, request it - token = BaiduAccessToken(api_key) - baidu_access_tokens[api_key] = token - try: - # try to get access token - token_str = BaiduAccessToken._get_access_token(api_key, secret_key) - finally: - # release it to enhance performance - # btw, _get_access_token will raise exception if failed, release lock here to avoid deadlock - baidu_access_tokens_lock.release() - token.access_token = token_str - token.expires = now + timedelta(days=3) - return token - else: - # if access token in cache, return it - token = baidu_access_tokens[api_key] - baidu_access_tokens_lock.release() - return token - - -class _CommonWenxin: - api_bases = { - "ernie-bot": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-4k-0205", - "ernie-bot-4": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro", - "ernie-bot-8k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions", - "ernie-bot-turbo": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/eb-instant", - "ernie-3.5-8k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions", - "ernie-3.5-8k-0205": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-8k-0205", - "ernie-3.5-8k-1222": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-8k-1222", - "ernie-3.5-4k-0205": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-4k-0205", - "ernie-3.5-128k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-128k", - "ernie-4.0-8k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro", - "ernie-4.0-8k-latest": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro", - "ernie-speed-8k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie_speed", - "ernie-speed-128k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-speed-128k", - "ernie-speed-appbuilder": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ai_apaas", - "ernie-lite-8k-0922": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/eb-instant", - "ernie-lite-8k-0308": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-lite-8k", - "ernie-character-8k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-char-8k", - "ernie-character-8k-0321": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-char-8k", - "ernie-4.0-turbo-8k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k", - "ernie-4.0-turbo-8k-preview": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k-preview", - "yi_34b_chat": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/yi_34b_chat", - "embedding-v1": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/embedding-v1", - "bge-large-en": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/bge_large_en", - "bge-large-zh": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/bge_large_zh", - "tao-8k": "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/tao_8k", - } - - function_calling_supports = [ - "ernie-bot", - "ernie-bot-8k", - "ernie-3.5-8k", - "ernie-3.5-8k-0205", - "ernie-3.5-8k-1222", - "ernie-3.5-4k-0205", - "ernie-3.5-128k", - "ernie-4.0-8k", - "ernie-4.0-turbo-8k", - "ernie-4.0-turbo-8k-preview", - "yi_34b_chat", - ] - - api_key: str = "" - secret_key: str = "" - - def __init__(self, api_key: str, secret_key: str): - self.api_key = api_key - self.secret_key = secret_key - - @staticmethod - def _to_credential_kwargs(credentials: dict) -> dict: - credentials_kwargs = {"api_key": credentials["api_key"], "secret_key": credentials["secret_key"]} - return credentials_kwargs - - def _handle_error(self, code: int, msg: str): - error_map = { - 1: InternalServerError, - 2: InternalServerError, - 3: BadRequestError, - 4: RateLimitReachedError, - 6: InvalidAuthenticationError, - 13: InvalidAPIKeyError, - 14: InvalidAPIKeyError, - 15: InvalidAPIKeyError, - 17: RateLimitReachedError, - 18: RateLimitReachedError, - 19: RateLimitReachedError, - 100: InvalidAPIKeyError, - 111: InvalidAPIKeyError, - 200: InternalServerError, - 336000: InternalServerError, - 336001: BadRequestError, - 336002: BadRequestError, - 336003: BadRequestError, - 336004: InvalidAuthenticationError, - 336005: InvalidAPIKeyError, - 336006: BadRequestError, - 336007: BadRequestError, - 336008: BadRequestError, - 336100: InternalServerError, - 336101: BadRequestError, - 336102: BadRequestError, - 336103: BadRequestError, - 336104: BadRequestError, - 336105: BadRequestError, - 336200: InternalServerError, - 336303: BadRequestError, - 337006: BadRequestError, - } - - if code in error_map: - raise error_map[code](msg) - else: - raise InternalServerError(f"Unknown error: {msg}") - - def _get_access_token(self) -> str: - token = BaiduAccessToken.get_access_token(self.api_key, self.secret_key) - return token.access_token diff --git a/api/core/model_runtime/model_providers/wenxin/llm/__init__.py b/api/core/model_runtime/model_providers/wenxin/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-128k.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-128k.yaml deleted file mode 100644 index b1b1ba1f69a0fb..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-128k.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: ernie-3.5-128k -label: - en_US: Ernie-3.5-128K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 2 - max: 4096 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-4k-0205.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-4k-0205.yaml deleted file mode 100644 index 1e8cf96440e71e..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-4k-0205.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: ernie-3.5-4k-0205 -label: - en_US: Ernie-3.5-4k-0205 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k-0205.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k-0205.yaml deleted file mode 100644 index b308abcb323f3d..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k-0205.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: ernie-3.5-8k-0205 -label: - en_US: Ernie-3.5-8K-0205 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k-1222.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k-1222.yaml deleted file mode 100644 index c43588cfe11ea7..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k-1222.yaml +++ /dev/null @@ -1,38 +0,0 @@ -model: ernie-3.5-8k-1222 -label: - en_US: Ernie-3.5-8K-1222 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k.yaml deleted file mode 100644 index 145844a4fffe85..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-3.5-8k.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: ernie-3.5-8k -label: - en_US: Ernie-3.5-8K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-8k-latest.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-8k-latest.yaml deleted file mode 100644 index d23ae0dc48c12f..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-8k-latest.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: ernie-4.0-8k-latest -label: - en_US: Ernie-4.0-8K-Latest -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-8k.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-8k.yaml deleted file mode 100644 index 9ebb5c8c4fe36b..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-8k.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: ernie-4.0-8k -label: - en_US: Ernie-4.0-8K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-turbo-8k-preview.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-turbo-8k-preview.yaml deleted file mode 100644 index 16df54022021b1..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-turbo-8k-preview.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: ernie-4.0-turbo-8k-preview -label: - en_US: Ernie-4.0-turbo-8k-preview -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-turbo-8k.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-turbo-8k.yaml deleted file mode 100644 index 2887a510d05157..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-4.0-turbo-8k.yaml +++ /dev/null @@ -1,40 +0,0 @@ -model: ernie-4.0-turbo-8k -label: - en_US: Ernie-4.0-turbo-8K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-4.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-4.yaml deleted file mode 100644 index f352787aecb279..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-4.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: ernie-bot-4 -label: - en_US: Ernie Bot 4 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4800 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 256 - min: 1 - max: 4800 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-8k.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-8k.yaml deleted file mode 100644 index fa4b7dd800c11b..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-8k.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: ernie-bot-8k -label: - en_US: Ernie Bot 8k -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 1024 - min: 1 - max: 8000 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-turbo.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-turbo.yaml deleted file mode 100644 index c94aa2db88646a..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot-turbo.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: ernie-bot-turbo -label: - en_US: Ernie Bot Turbo -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 11200 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 1024 - min: 1 - max: 11200 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: response_format - use_template: response_format -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot.yaml deleted file mode 100644 index 13985b74831e0d..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-bot.yaml +++ /dev/null @@ -1,39 +0,0 @@ -model: ernie-bot -label: - en_US: Ernie Bot -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4800 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.8 - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - required: true - default: 256 - min: 1 - max: 4800 - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: disable_search - label: - zh_Hans: 禁用搜索 - en_US: Disable Search - type: boolean - help: - zh_Hans: 禁用模型自行进行外部搜索。 - en_US: Disable the model to perform external search. - required: false - - name: response_format - use_template: response_format -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-character-8k-0321.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-character-8k-0321.yaml deleted file mode 100644 index 74451ff9e356e6..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-character-8k-0321.yaml +++ /dev/null @@ -1,31 +0,0 @@ -model: ernie-character-8k-0321 -label: - en_US: ERNIE-Character-8K-0321 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.95 - - name: top_p - use_template: top_p - min: 0 - max: 1.0 - default: 0.7 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 1024 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-character-8k.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-character-8k.yaml deleted file mode 100644 index 4b11b3e895be9f..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-character-8k.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: ernie-character-8k-0321 -label: - en_US: ERNIE-Character-8K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.95 - - name: top_p - use_template: top_p - min: 0 - max: 1.0 - default: 0.7 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 1024 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-lite-8k-0308.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-lite-8k-0308.yaml deleted file mode 100644 index 97ecb03f87b623..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-lite-8k-0308.yaml +++ /dev/null @@ -1,31 +0,0 @@ -model: ernie-lite-8k-0308 -label: - en_US: ERNIE-Lite-8K-0308 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.95 - - name: top_p - use_template: top_p - min: 0 - max: 1.0 - default: 0.7 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-lite-8k-0922.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-lite-8k-0922.yaml deleted file mode 100644 index 7410ce51df00ef..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-lite-8k-0922.yaml +++ /dev/null @@ -1,31 +0,0 @@ -model: ernie-lite-8k-0922 -label: - en_US: ERNIE-Lite-8K-0922 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.95 - - name: top_p - use_template: top_p - min: 0 - max: 1.0 - default: 0.7 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 1024 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 -deprecated: true diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-128k.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-128k.yaml deleted file mode 100644 index 331639624ccbbb..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-128k.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: ernie-speed-128k -label: - en_US: ERNIE-Speed-128K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 128000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.95 - - name: top_p - use_template: top_p - min: 0 - max: 1.0 - default: 0.7 - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 2 - max: 4096 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-8k.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-8k.yaml deleted file mode 100644 index 304c6d1f7ed8de..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-8k.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: ernie-speed-8k -label: - en_US: ERNIE-Speed-8K -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.95 - - name: top_p - use_template: top_p - min: 0 - max: 1.0 - default: 0.7 - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 2 - max: 2048 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-appbuilder.yaml b/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-appbuilder.yaml deleted file mode 100644 index c254ae02604c7b..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie-speed-appbuilder.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: ernie-speed-appbuilder -label: - en_US: ERNIE-Speed-AppBuilder -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.95 - - name: top_p - use_template: top_p - min: 0 - max: 1.0 - default: 0.7 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 diff --git a/api/core/model_runtime/model_providers/wenxin/llm/ernie_bot.py b/api/core/model_runtime/model_providers/wenxin/llm/ernie_bot.py deleted file mode 100644 index 07b970f8104c8f..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/ernie_bot.py +++ /dev/null @@ -1,245 +0,0 @@ -from collections.abc import Generator -from enum import Enum -from json import dumps, loads -from typing import Any, Union - -from requests import Response, post - -from core.model_runtime.entities.message_entities import PromptMessageTool -from core.model_runtime.model_providers.wenxin._common import _CommonWenxin -from core.model_runtime.model_providers.wenxin.wenxin_errors import ( - BadRequestError, - InternalServerError, -) - - -class ErnieMessage: - class Role(Enum): - USER = "user" - ASSISTANT = "assistant" - FUNCTION = "function" - SYSTEM = "system" - - role: str = Role.USER.value - content: str - usage: dict[str, int] = None - stop_reason: str = "" - - def to_dict(self) -> dict[str, Any]: - return { - "role": self.role, - "content": self.content, - } - - def __init__(self, content: str, role: str = "user") -> None: - self.content = content - self.role = role - - -class ErnieBotModel(_CommonWenxin): - def generate( - self, - model: str, - stream: bool, - messages: list[ErnieMessage], - parameters: dict[str, Any], - timeout: int, - tools: list[PromptMessageTool], - stop: list[str], - user: str, - ) -> Union[Generator[ErnieMessage, None, None], ErnieMessage]: - # check parameters - self._check_parameters(model, parameters, tools, stop) - - # get access token - access_token = self._get_access_token() - - # generate request body - url = f"{self.api_bases[model]}?access_token={access_token}" - - # clone messages - messages_cloned = self._copy_messages(messages=messages) - - # build body - body = self._build_request_body( - model, messages=messages_cloned, stream=stream, parameters=parameters, tools=tools, stop=stop, user=user - ) - headers = { - "Content-Type": "application/json", - } - - resp = post(url=url, data=dumps(body), headers=headers, stream=stream) - - if resp.status_code != 200: - raise InternalServerError(f"Failed to invoke ernie bot: {resp.text}") - - if stream: - return self._handle_chat_stream_generate_response(resp) - return self._handle_chat_generate_response(resp) - - def _copy_messages(self, messages: list[ErnieMessage]) -> list[ErnieMessage]: - return [ErnieMessage(message.content, message.role) for message in messages] - - def _check_parameters( - self, model: str, parameters: dict[str, Any], tools: list[PromptMessageTool], stop: list[str] - ) -> None: - if model not in self.api_bases: - raise BadRequestError(f"Invalid model: {model}") - - # if model not in self.function_calling_supports and tools is not None and len(tools) > 0: - # raise BadRequestError(f'Model {model} does not support calling function.') - # ErnieBot supports function calling, however, there is lots of limitations. - # such as, the messages should be ordered as user by assistant or function... - # so, we just disable function calling for now. - - if tools is not None and len(tools) > 0: - raise BadRequestError("function calling is not supported yet.") - - if stop is not None: - if len(stop) > 4: - raise BadRequestError("stop list should not exceed 4 items.") - - for s in stop: - if len(s) > 20: - raise BadRequestError("stop item should not exceed 20 characters.") - - def _build_request_body( - self, - model: str, - messages: list[ErnieMessage], - stream: bool, - parameters: dict[str, Any], - tools: list[PromptMessageTool], - stop: list[str], - user: str, - ) -> dict[str, Any]: - # if model in self.function_calling_supports: - # return self._build_function_calling_request_body(model, messages, parameters, tools, stop, user) - return self._build_chat_request_body(model, messages, stream, parameters, stop, user) - - def _build_function_calling_request_body( - self, - model: str, - messages: list[ErnieMessage], - stream: bool, - parameters: dict[str, Any], - tools: list[PromptMessageTool], - stop: list[str], - user: str, - ) -> dict[str, Any]: - if len(messages) % 2 == 0: - raise BadRequestError("The number of messages should be odd.") - if messages[0].role == "function": - raise BadRequestError("The first message should be user message.") - - """ - TODO: implement function calling - """ - - def _build_chat_request_body( - self, - model: str, - messages: list[ErnieMessage], - stream: bool, - parameters: dict[str, Any], - stop: list[str], - user: str, - ) -> dict[str, Any]: - if len(messages) == 0: - raise BadRequestError("The number of messages should not be zero.") - - # check if the first element is system, shift it - system_message = "" - if messages[0].role == "system": - message = messages.pop(0) - system_message = message.content - - if len(messages) % 2 == 0: - raise BadRequestError("The number of messages should be odd.") - if messages[0].role != "user": - raise BadRequestError("The first message should be user message.") - body = { - "messages": [message.to_dict() for message in messages], - "stream": stream, - "stop": stop, - "user_id": user, - **parameters, - } - - if "max_tokens" in parameters and type(parameters["max_tokens"]) == int: - body["max_output_tokens"] = parameters["max_tokens"] - - if "presence_penalty" in parameters and type(parameters["presence_penalty"]) == float: - body["penalty_score"] = parameters["presence_penalty"] - - if system_message: - body["system"] = system_message - - return body - - def _handle_chat_generate_response(self, response: Response) -> ErnieMessage: - data = response.json() - if "error_code" in data: - code = data["error_code"] - msg = data["error_msg"] - # raise error - self._handle_error(code, msg) - - result = data["result"] - usage = data["usage"] - - message = ErnieMessage(content=result, role="assistant") - message.usage = { - "prompt_tokens": usage["prompt_tokens"], - "completion_tokens": usage["completion_tokens"], - "total_tokens": usage["total_tokens"], - } - - return message - - def _handle_chat_stream_generate_response(self, response: Response) -> Generator[ErnieMessage, None, None]: - for line in response.iter_lines(): - if len(line) == 0: - continue - line = line.decode("utf-8") - if line[0] == "{": - try: - data = loads(line) - if "error_code" in data: - code = data["error_code"] - msg = data["error_msg"] - # raise error - self._handle_error(code, msg) - except Exception as e: - raise InternalServerError(f"Failed to parse response: {e}") - - if line.startswith("data:"): - line = line[5:].strip() - else: - continue - - if not line: - continue - try: - data = loads(line) - except Exception as e: - raise InternalServerError(f"Failed to parse response: {e}") - - result = data["result"] - is_end = data["is_end"] - - if is_end: - usage = data["usage"] - finish_reason = data.get("finish_reason", None) - message = ErnieMessage(content=result, role="assistant") - message.usage = { - "prompt_tokens": usage["prompt_tokens"], - "completion_tokens": usage["completion_tokens"], - "total_tokens": usage["total_tokens"], - } - message.stop_reason = finish_reason - - yield message - else: - message = ErnieMessage(content=result, role="assistant") - yield message diff --git a/api/core/model_runtime/model_providers/wenxin/llm/llm.py b/api/core/model_runtime/model_providers/wenxin/llm/llm.py deleted file mode 100644 index f7c160b6b47b79..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/llm.py +++ /dev/null @@ -1,316 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union, cast - -from core.model_runtime.callbacks.base_callback import Callback -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.wenxin._common import BaiduAccessToken -from core.model_runtime.model_providers.wenxin.llm.ernie_bot import ErnieBotModel, ErnieMessage -from core.model_runtime.model_providers.wenxin.wenxin_errors import invoke_error_mapping - -ERNIE_BOT_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object. -The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - - -{{instructions}} - - -You should also complete the text started with ``` but not tell ``` directly. -""" # noqa: E501 - - -class ErnieBotLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ) - - def _code_block_mode_wrapper( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - callbacks: list[Callback] = None, - ) -> Union[LLMResult, Generator]: - """ - Code block mode wrapper for invoking large language model - """ - if "response_format" in model_parameters and model_parameters["response_format"] in {"JSON", "XML"}: - response_format = model_parameters["response_format"] - stop = stop or [] - self._transform_json_prompts( - model, credentials, prompt_messages, model_parameters, tools, stop, stream, user, response_format - ) - model_parameters.pop("response_format") - if stream: - return self._code_block_mode_stream_processor( - model=model, - prompt_messages=prompt_messages, - input_generator=self._invoke( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - ), - ) - - return self._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def _transform_json_prompts( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - response_format: str = "JSON", - ) -> None: - """ - Transform json prompts to model prompts - """ - - # check if there is a system message - if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): - # override the system message - prompt_messages[0] = SystemPromptMessage( - content=ERNIE_BOT_BLOCK_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content).replace( - "{{block}}", response_format - ) - ) - else: - # insert the system message - prompt_messages.insert( - 0, - SystemPromptMessage( - content=ERNIE_BOT_BLOCK_MODE_PROMPT.replace( - "{{instructions}}", f"Please output a valid {response_format} object." - ).replace("{{block}}", response_format) - ), - ) - - if len(prompt_messages) > 0 and isinstance(prompt_messages[-1], UserPromptMessage): - # add ```JSON\n to the last message - prompt_messages[-1].content += "\n```JSON\n{\n" - else: - # append a user message - prompt_messages.append(UserPromptMessage(content="```JSON\n{\n")) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - # tools is not supported yet - return self._num_tokens_from_messages(prompt_messages) - - def _num_tokens_from_messages( - self, - messages: list[PromptMessage], - ) -> int: - """Calculate num tokens for baichuan model""" - - def tokens(text: str): - return self._get_num_tokens_by_gpt2(text) - - tokens_per_message = 3 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - num_tokens += tokens(str(value)) - num_tokens += 3 - - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - api_key = credentials["api_key"] - secret_key = credentials["secret_key"] - try: - BaiduAccessToken.get_access_token(api_key, secret_key) - except Exception as e: - raise CredentialsValidateFailedError(f"Credentials validation failed: {e}") - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - instance = ErnieBotModel( - api_key=credentials["api_key"], - secret_key=credentials["secret_key"], - ) - - user = user or "ErnieBotDefault" - - # convert prompt messages to baichuan messages - messages = [ - ErnieMessage( - content=message.content - if isinstance(message.content, str) - else "".join([content.data for content in message.content]), - role=message.role.value, - ) - for message in prompt_messages - ] - - # invoke model - response = instance.generate( - model=model, - stream=stream, - messages=messages, - parameters=model_parameters, - timeout=60, - tools=tools, - stop=stop, - user=user, - ) - - if stream: - return self._handle_chat_generate_stream_response(model, prompt_messages, credentials, response) - else: - return self._handle_chat_generate_response(model, prompt_messages, credentials, response) - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for Baichuan - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - raise ValueError("User message content must be str") - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - else: - raise ValueError(f"Unknown message type {type(message)}") - - return message_dict - - def _handle_chat_generate_response( - self, model: str, prompt_messages: list[PromptMessage], credentials: dict, response: ErnieMessage - ) -> LLMResult: - # convert baichuan message to llm result - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=response.usage["prompt_tokens"], - completion_tokens=response.usage["completion_tokens"], - ) - return LLMResult( - model=model, - prompt_messages=prompt_messages, - message=AssistantPromptMessage(content=response.content, tool_calls=[]), - usage=usage, - ) - - def _handle_chat_generate_stream_response( - self, - model: str, - prompt_messages: list[PromptMessage], - credentials: dict, - response: Generator[ErnieMessage, None, None], - ) -> Generator: - for message in response: - if message.usage: - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=message.usage["prompt_tokens"], - completion_tokens=message.usage["completion_tokens"], - ) - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=message.content, tool_calls=[]), - usage=usage, - finish_reason=message.stop_reason or None, - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=0, - message=AssistantPromptMessage(content=message.content, tool_calls=[]), - finish_reason=message.stop_reason or None, - ), - ) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return invoke_error_mapping() diff --git a/api/core/model_runtime/model_providers/wenxin/llm/yi_34b_chat.yaml b/api/core/model_runtime/model_providers/wenxin/llm/yi_34b_chat.yaml deleted file mode 100644 index 0b247fbd223dac..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/llm/yi_34b_chat.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: yi_34b_chat -label: - en_US: yi_34b_chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32000 -parameter_rules: - - name: temperature - use_template: temperature - min: 0.1 - max: 1.0 - default: 0.95 - - name: top_p - use_template: top_p - min: 0 - max: 1.0 - default: 0.7 - - name: max_tokens - use_template: max_tokens - default: 4096 - min: 2 - max: 4096 - - name: presence_penalty - use_template: presence_penalty - default: 1.0 - min: 1.0 - max: 2.0 diff --git a/api/core/model_runtime/model_providers/wenxin/text_embedding/__init__.py b/api/core/model_runtime/model_providers/wenxin/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/wenxin/text_embedding/bge-large-en.yaml b/api/core/model_runtime/model_providers/wenxin/text_embedding/bge-large-en.yaml deleted file mode 100644 index 74fadb7f9de60f..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/text_embedding/bge-large-en.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: bge-large-en -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 16 -pricing: - input: '0.0005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/wenxin/text_embedding/bge-large-zh.yaml b/api/core/model_runtime/model_providers/wenxin/text_embedding/bge-large-zh.yaml deleted file mode 100644 index d4af27ec389a66..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/text_embedding/bge-large-zh.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: bge-large-zh -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 16 -pricing: - input: '0.0005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/wenxin/text_embedding/embedding-v1.yaml b/api/core/model_runtime/model_providers/wenxin/text_embedding/embedding-v1.yaml deleted file mode 100644 index eda48d965533e5..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/text_embedding/embedding-v1.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: embedding-v1 -model_type: text-embedding -model_properties: - context_size: 384 - max_chunks: 16 -pricing: - input: '0.0005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/wenxin/text_embedding/tao-8k.yaml b/api/core/model_runtime/model_providers/wenxin/text_embedding/tao-8k.yaml deleted file mode 100644 index e28f253eb6b861..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/text_embedding/tao-8k.yaml +++ /dev/null @@ -1,9 +0,0 @@ -model: tao-8k -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 1 -pricing: - input: '0.0005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/wenxin/wenxin.py b/api/core/model_runtime/model_providers/wenxin/wenxin.py deleted file mode 100644 index 895af20bc8541d..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/wenxin.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class WenxinProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `ernie-bot` model for validate, - model_instance.validate_credentials(model="ernie-bot", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/wenxin/wenxin.yaml b/api/core/model_runtime/model_providers/wenxin/wenxin.yaml deleted file mode 100644 index 6a6b38e6a1b7ab..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/wenxin.yaml +++ /dev/null @@ -1,40 +0,0 @@ -provider: wenxin -label: - en_US: WenXin - zh_Hans: 文心一言 -icon_small: - en_US: icon_s_en.png - zh_Hans: icon_s_en.png -icon_large: - en_US: icon_l_en.png - zh_Hans: icon_l_zh.png -background: "#E8F5FE" -help: - title: - en_US: Get your API Key from WenXin - zh_Hans: 从文心一言获取您的 API Key - url: - en_US: https://cloud.baidu.com/wenxin.html -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: secret_key - label: - en_US: Secret Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 Secret Key - en_US: Enter your Secret Key diff --git a/api/core/model_runtime/model_providers/wenxin/wenxin_errors.py b/api/core/model_runtime/model_providers/wenxin/wenxin_errors.py deleted file mode 100644 index bd074e047717ac..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/wenxin_errors.py +++ /dev/null @@ -1,54 +0,0 @@ -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) - - -def invoke_error_mapping() -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [InternalServerError], - InvokeRateLimitError: [RateLimitReachedError], - InvokeAuthorizationError: [ - InvalidAuthenticationError, - InsufficientAccountBalanceError, - InvalidAPIKeyError, - ], - InvokeBadRequestError: [BadRequestError, KeyError], - } - - -class InvalidAuthenticationError(Exception): - pass - - -class InvalidAPIKeyError(Exception): - pass - - -class RateLimitReachedError(Exception): - pass - - -class InsufficientAccountBalanceError(Exception): - pass - - -class InternalServerError(Exception): - pass - - -class BadRequestError(Exception): - pass diff --git a/api/core/model_runtime/model_providers/xinference/__init__.py b/api/core/model_runtime/model_providers/xinference/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/xinference/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/xinference/_assets/icon_l_en.svg deleted file mode 100644 index 8109176543385c..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/_assets/icon_l_en.svg +++ /dev/null @@ -1,42 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/xinference/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/xinference/_assets/icon_s_en.svg deleted file mode 100644 index f5c5f75ea817ff..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/_assets/icon_s_en.svg +++ /dev/null @@ -1,24 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/api/core/model_runtime/model_providers/xinference/llm/__init__.py b/api/core/model_runtime/model_providers/xinference/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/xinference/llm/llm.py b/api/core/model_runtime/model_providers/xinference/llm/llm.py deleted file mode 100644 index 286640079b02a9..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/llm/llm.py +++ /dev/null @@ -1,816 +0,0 @@ -from collections.abc import Generator, Iterator -from typing import cast - -from openai import ( - APIConnectionError, - APITimeoutError, - AuthenticationError, - ConflictError, - InternalServerError, - NotFoundError, - OpenAI, - PermissionDeniedError, - RateLimitError, - UnprocessableEntityError, -) -from openai.types.chat import ChatCompletion, ChatCompletionChunk, ChatCompletionMessageToolCall -from openai.types.chat.chat_completion_chunk import ChoiceDeltaFunctionCall, ChoiceDeltaToolCall -from openai.types.chat.chat_completion_message import FunctionCall -from openai.types.completion import Completion -from xinference_client.client.restful.restful_client import ( - Client, - RESTfulChatModelHandle, - RESTfulGenerateModelHandle, -) - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContent, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - DefaultParameterName, - FetchFrom, - ModelFeature, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.xinference.xinference_helper import ( - XinferenceHelper, - XinferenceModelExtraParameter, -) -from core.model_runtime.utils import helper - - -class XinferenceAILargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - """ - invoke LLM - - see `core.model_runtime.model_providers.__base.large_language_model.LargeLanguageModel._invoke` - """ - if "temperature" in model_parameters: - if model_parameters["temperature"] < 0.01: - model_parameters["temperature"] = 0.01 - elif model_parameters["temperature"] > 1.0: - model_parameters["temperature"] = 0.99 - - return self._generate( - model=model, - credentials=credentials, - prompt_messages=prompt_messages, - model_parameters=model_parameters, - tools=tools, - stop=stop, - stream=stream, - user=user, - extra_model_kwargs=XinferenceHelper.get_xinference_extra_parameter( - server_url=credentials["server_url"], - model_uid=credentials["model_uid"], - api_key=credentials.get("api_key"), - ), - ) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - validate credentials - - credentials should be like: - { - 'model_type': 'text-generation', - 'server_url': 'server url', - 'model_uid': 'model uid', - } - """ - try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: - raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") - - extra_param = XinferenceHelper.get_xinference_extra_parameter( - server_url=credentials["server_url"], - model_uid=credentials["model_uid"], - api_key=credentials.get("api_key"), - ) - if "completion_type" not in credentials: - if "chat" in extra_param.model_ability: - credentials["completion_type"] = "chat" - elif "generate" in extra_param.model_ability: - credentials["completion_type"] = "completion" - else: - raise ValueError( - f"xinference model ability {extra_param.model_ability} is not supported," - f" check if you have the right model type" - ) - - if extra_param.support_function_call: - credentials["support_function_call"] = True - - if extra_param.support_vision: - credentials["support_vision"] = True - - if extra_param.context_length: - credentials["context_length"] = extra_param.context_length - - except RuntimeError as e: - raise CredentialsValidateFailedError(f"Xinference credentials validate failed: {e}") - except KeyError as e: - raise CredentialsValidateFailedError(f"Xinference credentials validate failed: {e}") - except Exception as e: - raise e - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool] | None = None, - ) -> int: - """ - get number of tokens - - cause XinferenceAI LLM is a customized model, we could net detect which tokenizer to use - so we just take the GPT2 tokenizer as default - """ - return self._num_tokens_from_messages(prompt_messages, tools) - - def _num_tokens_from_messages( - self, messages: list[PromptMessage], tools: list[PromptMessageTool], is_completion_model: bool = False - ) -> int: - def tokens(text: str): - return self._get_num_tokens_by_gpt2(text) - - if is_completion_model: - return sum(tokens(str(message.content)) for message in messages) - - tokens_per_message = 3 - tokens_per_name = 1 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += tokens(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += tokens(f_key) - num_tokens += tokens(f_value) - else: - num_tokens += tokens(t_key) - num_tokens += tokens(t_value) - if key == "function_call": - for t_key, t_value in value.items(): - num_tokens += tokens(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += tokens(f_key) - num_tokens += tokens(f_value) - else: - num_tokens += tokens(t_key) - num_tokens += tokens(t_value) - else: - num_tokens += tokens(str(value)) - - if key == "name": - num_tokens += tokens_per_name - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(tools) - - return num_tokens - - def _num_tokens_for_tools(self, tools: list[PromptMessageTool]) -> int: - """ - Calculate num tokens for tool calling - - :param encoding: encoding - :param tools: tools for tool calling - :return: number of tokens - """ - - def tokens(text: str): - return self._get_num_tokens_by_gpt2(text) - - num_tokens = 0 - for tool in tools: - # calculate num tokens for function object - num_tokens += tokens("name") - num_tokens += tokens(tool.name) - num_tokens += tokens("description") - num_tokens += tokens(tool.description) - parameters = tool.parameters - num_tokens += tokens("parameters") - num_tokens += tokens("type") - num_tokens += tokens(parameters.get("type")) - if "properties" in parameters: - num_tokens += tokens("properties") - for key, value in parameters.get("properties").items(): - num_tokens += tokens(key) - for field_key, field_value in value.items(): - num_tokens += tokens(field_key) - if field_key == "enum": - for enum_field in field_value: - num_tokens += 3 - num_tokens += tokens(enum_field) - else: - num_tokens += tokens(field_key) - num_tokens += tokens(str(field_value)) - if "required" in parameters: - num_tokens += tokens("required") - for required_field in parameters["required"]: - num_tokens += 3 - num_tokens += tokens(required_field) - - return num_tokens - - def _convert_prompt_message_to_text(self, message: list[PromptMessage]) -> str: - """ - convert prompt message to text - """ - text = "" - for item in message: - if isinstance(item, UserPromptMessage | SystemPromptMessage | AssistantPromptMessage): - text += item.content - else: - raise NotImplementedError(f"PromptMessage type {type(item)} is not supported") - return text - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for OpenAI Compatibility API - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(PromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": {"url": message_content.data, "detail": message_content.detail.value}, - } - sub_messages.append(sub_message_dict) - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls and len(message.tool_calls) > 0: - message_dict["function_call"] = { - "name": message.tool_calls[0].function.name, - "arguments": message.tool_calls[0].function.arguments, - } - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = {"tool_call_id": message.tool_call_id, "role": "tool", "content": message.content} - else: - raise ValueError(f"Unknown message type {type(message)}") - - return message_dict - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - rules = [ - ParameterRule( - name="temperature", - type=ParameterType.FLOAT, - use_template="temperature", - label=I18nObject(zh_Hans="温度", en_US="Temperature"), - ), - ParameterRule( - name="top_p", - type=ParameterType.FLOAT, - use_template="top_p", - label=I18nObject(zh_Hans="Top P", en_US="Top P"), - ), - ParameterRule( - name="max_tokens", - type=ParameterType.INT, - use_template="max_tokens", - min=1, - max=credentials.get("context_length", 2048), - default=512, - label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"), - ), - ParameterRule( - name=DefaultParameterName.PRESENCE_PENALTY, - use_template=DefaultParameterName.PRESENCE_PENALTY, - type=ParameterType.FLOAT, - label=I18nObject( - en_US="Presence Penalty", - zh_Hans="存在惩罚", - ), - required=False, - help=I18nObject( - en_US="Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they " - "appear in the text so far, increasing the model's likelihood to talk about new topics.", - zh_Hans="介于 -2.0 和 2.0 之间的数字。正值会根据新词是否已出现在文本中对其进行惩罚，" - "从而增加模型谈论新话题的可能性。", - ), - default=0.0, - min=-2.0, - max=2.0, - precision=2, - ), - ParameterRule( - name=DefaultParameterName.FREQUENCY_PENALTY, - use_template=DefaultParameterName.FREQUENCY_PENALTY, - type=ParameterType.FLOAT, - label=I18nObject( - en_US="Frequency Penalty", - zh_Hans="频率惩罚", - ), - required=False, - help=I18nObject( - en_US="Number between -2.0 and 2.0. Positive values penalize new tokens based on their " - "existing frequency in the text so far, decreasing the model's likelihood to repeat the " - "same line verbatim.", - zh_Hans="介于 -2.0 和 2.0 之间的数字。正值会根据新词在文本中的现有频率对其进行惩罚，" - "从而降低模型逐字重复相同内容的可能性。", - ), - default=0.0, - min=-2.0, - max=2.0, - precision=2, - ), - ] - - completion_type = None - - if "completion_type" in credentials: - if credentials["completion_type"] == "chat": - completion_type = LLMMode.CHAT.value - elif credentials["completion_type"] == "completion": - completion_type = LLMMode.COMPLETION.value - else: - raise ValueError(f'completion_type {credentials["completion_type"]} is not supported') - else: - extra_args = XinferenceHelper.get_xinference_extra_parameter( - server_url=credentials["server_url"], - model_uid=credentials["model_uid"], - api_key=credentials.get("api_key"), - ) - - if "chat" in extra_args.model_ability: - completion_type = LLMMode.CHAT.value - elif "generate" in extra_args.model_ability: - completion_type = LLMMode.COMPLETION.value - else: - raise ValueError(f"xinference model ability {extra_args.model_ability} is not supported") - - features = [] - - support_function_call = credentials.get("support_function_call", False) - if support_function_call: - features.append(ModelFeature.TOOL_CALL) - - support_vision = credentials.get("support_vision", False) - if support_vision: - features.append(ModelFeature.VISION) - - context_length = credentials.get("context_length", 2048) - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - features=features, - model_properties={ModelPropertyKey.MODE: completion_type, ModelPropertyKey.CONTEXT_SIZE: context_length}, - parameter_rules=rules, - ) - - return entity - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - extra_model_kwargs: XinferenceModelExtraParameter, - tools: list[PromptMessageTool] | None = None, - stop: list[str] | None = None, - stream: bool = True, - user: str | None = None, - ) -> LLMResult | Generator: - """ - generate text from LLM - - see `core.model_runtime.model_providers.__base.large_language_model.LargeLanguageModel._generate` - - extra_model_kwargs can be got by `XinferenceHelper.get_xinference_extra_parameter` - """ - if "server_url" not in credentials: - raise CredentialsValidateFailedError("server_url is required in credentials") - - credentials["server_url"] = credentials["server_url"].removesuffix("/") - - api_key = credentials.get("api_key") or "abc" - - client = OpenAI( - base_url=f'{credentials["server_url"]}/v1', - api_key=api_key, - max_retries=3, - timeout=60, - ) - - xinference_client = Client( - base_url=credentials["server_url"], - api_key=credentials.get("api_key"), - ) - - xinference_model = xinference_client.get_model(credentials["model_uid"]) - - generate_config = { - "temperature": model_parameters.get("temperature", 1.0), - "top_p": model_parameters.get("top_p", 0.7), - "max_tokens": model_parameters.get("max_tokens", 512), - "presence_penalty": model_parameters.get("presence_penalty", 0.0), - "frequency_penalty": model_parameters.get("frequency_penalty", 0.0), - } - - if stop: - generate_config["stop"] = stop - - if tools and len(tools) > 0: - generate_config["tools"] = [{"type": "function", "function": helper.dump_model(tool)} for tool in tools] - vision = credentials.get("support_vision", False) - if isinstance(xinference_model, RESTfulChatModelHandle): - resp = client.chat.completions.create( - model=credentials["model_uid"], - messages=[self._convert_prompt_message_to_dict(message) for message in prompt_messages], - stream=stream, - user=user, - **generate_config, - ) - if stream: - if tools and len(tools) > 0: - raise InvokeBadRequestError("xinference tool calls does not support stream mode") - return self._handle_chat_stream_response( - model=model, credentials=credentials, prompt_messages=prompt_messages, tools=tools, resp=resp - ) - return self._handle_chat_generate_response( - model=model, credentials=credentials, prompt_messages=prompt_messages, tools=tools, resp=resp - ) - elif isinstance(xinference_model, RESTfulGenerateModelHandle): - resp = client.completions.create( - model=credentials["model_uid"], - prompt=self._convert_prompt_message_to_text(prompt_messages), - stream=stream, - user=user, - **generate_config, - ) - if stream: - return self._handle_completion_stream_response( - model=model, credentials=credentials, prompt_messages=prompt_messages, tools=tools, resp=resp - ) - return self._handle_completion_generate_response( - model=model, credentials=credentials, prompt_messages=prompt_messages, tools=tools, resp=resp - ) - else: - raise NotImplementedError(f"xinference model handle type {type(xinference_model)} is not supported") - - def _extract_response_tool_calls( - self, response_tool_calls: list[ChatCompletionMessageToolCall | ChoiceDeltaToolCall] - ) -> list[AssistantPromptMessage.ToolCall]: - """ - Extract tool calls from response - - :param response_tool_calls: response tool calls - :return: list of tool calls - """ - tool_calls = [] - if response_tool_calls: - for response_tool_call in response_tool_calls: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_tool_call.function.name, arguments=response_tool_call.function.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_tool_call.id, type=response_tool_call.type, function=function - ) - tool_calls.append(tool_call) - - return tool_calls - - def _extract_response_function_call( - self, response_function_call: FunctionCall | ChoiceDeltaFunctionCall - ) -> AssistantPromptMessage.ToolCall: - """ - Extract function call from response - - :param response_function_call: response function call - :return: tool call - """ - tool_call = None - if response_function_call: - function = AssistantPromptMessage.ToolCall.ToolCallFunction( - name=response_function_call.name, arguments=response_function_call.arguments - ) - - tool_call = AssistantPromptMessage.ToolCall( - id=response_function_call.name, type="function", function=function - ) - - return tool_call - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool], - resp: ChatCompletion, - ) -> LLMResult: - """ - handle normal chat generate response - """ - if len(resp.choices) == 0: - raise InvokeServerUnavailableError("Empty response") - - assistant_message = resp.choices[0].message - - # convert tool call to assistant message tool call - tool_calls = assistant_message.tool_calls - assistant_prompt_message_tool_calls = self._extract_response_tool_calls(tool_calls or []) - function_call = assistant_message.function_call - if function_call: - assistant_prompt_message_tool_calls += [self._extract_response_function_call(function_call)] - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=assistant_message.content, tool_calls=assistant_prompt_message_tool_calls - ) - - prompt_tokens = self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - completion_tokens = self._num_tokens_from_messages(messages=[assistant_prompt_message], tools=tools) - - usage = self._calc_response_usage( - model=model, credentials=credentials, prompt_tokens=prompt_tokens, completion_tokens=completion_tokens - ) - - response = LLMResult( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=resp.system_fingerprint, - usage=usage, - message=assistant_prompt_message, - ) - - return response - - def _handle_chat_stream_response( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool], - resp: Iterator[ChatCompletionChunk], - ) -> Generator: - """ - handle stream chat generate response - """ - full_response = "" - - for chunk in resp: - if len(chunk.choices) == 0: - continue - - delta = chunk.choices[0] - - if delta.finish_reason is None and (delta.delta.content is None or delta.delta.content == ""): - continue - - # check if there is a tool call in the response - function_call = None - tool_calls = [] - if delta.delta.tool_calls: - tool_calls += delta.delta.tool_calls - if delta.delta.function_call: - function_call = delta.delta.function_call - - assistant_message_tool_calls = self._extract_response_tool_calls(tool_calls) - if function_call: - assistant_message_tool_calls += [self._extract_response_function_call(function_call)] - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=delta.delta.content or "", tool_calls=assistant_message_tool_calls - ) - - if delta.finish_reason is not None: - # temp_assistant_prompt_message is used to calculate usage - temp_assistant_prompt_message = AssistantPromptMessage( - content=full_response, tool_calls=assistant_message_tool_calls - ) - - prompt_tokens = self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - completion_tokens = self._num_tokens_from_messages(messages=[temp_assistant_prompt_message], tools=[]) - - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=prompt_tokens, - completion_tokens=completion_tokens, - ) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=0, message=assistant_prompt_message, finish_reason=delta.finish_reason, usage=usage - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=0, - message=assistant_prompt_message, - ), - ) - - full_response += delta.delta.content - - def _handle_completion_generate_response( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool], - resp: Completion, - ) -> LLMResult: - """ - handle normal completion generate response - """ - if len(resp.choices) == 0: - raise InvokeServerUnavailableError("Empty response") - - assistant_message = resp.choices[0].text - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=assistant_message, tool_calls=[]) - - prompt_tokens = self._get_num_tokens_by_gpt2(self._convert_prompt_message_to_text(prompt_messages)) - completion_tokens = self._num_tokens_from_messages( - messages=[assistant_prompt_message], tools=[], is_completion_model=True - ) - usage = self._calc_response_usage( - model=model, credentials=credentials, prompt_tokens=prompt_tokens, completion_tokens=completion_tokens - ) - - response = LLMResult( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=resp.system_fingerprint, - usage=usage, - message=assistant_prompt_message, - ) - - return response - - def _handle_completion_stream_response( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool], - resp: Iterator[Completion], - ) -> Generator: - """ - handle stream completion generate response - """ - full_response = "" - - for chunk in resp: - if len(chunk.choices) == 0: - continue - - delta = chunk.choices[0] - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=delta.text or "", tool_calls=[]) - - if delta.finish_reason is not None: - # temp_assistant_prompt_message is used to calculate usage - temp_assistant_prompt_message = AssistantPromptMessage(content=full_response, tool_calls=[]) - - prompt_tokens = self._get_num_tokens_by_gpt2(self._convert_prompt_message_to_text(prompt_messages)) - completion_tokens = self._num_tokens_from_messages( - messages=[temp_assistant_prompt_message], tools=[], is_completion_model=True - ) - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=prompt_tokens, - completion_tokens=completion_tokens, - ) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=0, message=assistant_prompt_message, finish_reason=delta.finish_reason, usage=usage - ), - ) - else: - if delta.text is None or delta.text == "": - continue - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=chunk.system_fingerprint, - delta=LLMResultChunkDelta( - index=0, - message=assistant_prompt_message, - ), - ) - - full_response += delta.text - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [ - APIConnectionError, - APITimeoutError, - ], - InvokeServerUnavailableError: [ - InternalServerError, - ConflictError, - NotFoundError, - UnprocessableEntityError, - PermissionDeniedError, - ], - InvokeRateLimitError: [RateLimitError], - InvokeAuthorizationError: [AuthenticationError], - InvokeBadRequestError: [ValueError], - } diff --git a/api/core/model_runtime/model_providers/xinference/rerank/__init__.py b/api/core/model_runtime/model_providers/xinference/rerank/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/xinference/rerank/rerank.py b/api/core/model_runtime/model_providers/xinference/rerank/rerank.py deleted file mode 100644 index 8f18bc42d2339d..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/rerank/rerank.py +++ /dev/null @@ -1,189 +0,0 @@ -from typing import Optional - -from xinference_client.client.restful.restful_client import Client, RESTfulRerankModelHandle - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.rerank_model import RerankModel - - -class XinferenceRerankModel(RerankModel): - """ - Model class for Xinference rerank model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n - :param user: unique user id - :return: rerank result - """ - if len(docs) == 0: - return RerankResult(model=model, docs=[]) - - server_url = credentials["server_url"] - model_uid = credentials["model_uid"] - api_key = credentials.get("api_key") - server_url = server_url.removesuffix("/") - auth_headers = {"Authorization": f"Bearer {api_key}"} if api_key else {} - - params = {"documents": docs, "query": query, "top_n": top_n, "return_documents": True} - try: - handle = RESTfulRerankModelHandle(model_uid, server_url, auth_headers) - response = handle.rerank(**params) - except RuntimeError as e: - if "rerank hasn't support extra parameter" not in str(e): - raise InvokeServerUnavailableError(str(e)) - - # compatible xinference server between v0.10.1 - v0.12.1, not support 'return_len' - handle = RESTfulRerankModelHandleWithoutExtraParameter(model_uid, server_url, auth_headers) - response = handle.rerank(**params) - - rerank_documents = [] - for idx, result in enumerate(response["results"]): - # format document - index = result["index"] - page_content = result["document"] if isinstance(result["document"], str) else result["document"]["text"] - rerank_document = RerankDocument( - index=index, - text=page_content, - score=result["relevance_score"], - ) - - # score threshold check - if score_threshold is not None: - if result["relevance_score"] >= score_threshold: - rerank_documents.append(rerank_document) - else: - rerank_documents.append(rerank_document) - - return RerankResult(model=model, docs=rerank_documents) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: - raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") - - credentials["server_url"] = credentials["server_url"].removesuffix("/") - - # initialize client - client = Client( - base_url=credentials["server_url"], - api_key=credentials.get("api_key"), - ) - - xinference_client = client.get_model(model_uid=credentials["model_uid"]) - - if not isinstance(xinference_client, RESTfulRerankModelHandle): - raise InvokeBadRequestError( - "please check model type, the model you want to invoke is not a rerank model" - ) - - self.invoke( - model=model, - credentials=credentials, - query="Whose kasumi", - docs=[ - 'Kasumi is a girl\'s name of Japanese origin meaning "mist".', - "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music ", - "and she leads a team named PopiParty.", - ], - score_threshold=0.8, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.RERANK, - model_properties={}, - parameter_rules=[], - ) - - return entity - - -class RESTfulRerankModelHandleWithoutExtraParameter(RESTfulRerankModelHandle): - def rerank( - self, - documents: list[str], - query: str, - top_n: Optional[int] = None, - max_chunks_per_doc: Optional[int] = None, - return_documents: Optional[bool] = None, - **kwargs, - ): - url = f"{self._base_url}/v1/rerank" - request_body = { - "model": self._model_uid, - "documents": documents, - "query": query, - "top_n": top_n, - "max_chunks_per_doc": max_chunks_per_doc, - "return_documents": return_documents, - } - - import requests - - response = requests.post(url, json=request_body, headers=self.auth_headers) - if response.status_code != 200: - raise InvokeServerUnavailableError(f"Failed to rerank documents, detail: {response.json()['detail']}") - response_data = response.json() - return response_data diff --git a/api/core/model_runtime/model_providers/xinference/speech2text/__init__.py b/api/core/model_runtime/model_providers/xinference/speech2text/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/xinference/speech2text/speech2text.py b/api/core/model_runtime/model_providers/xinference/speech2text/speech2text.py deleted file mode 100644 index a6c5b8a0a571e9..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/speech2text/speech2text.py +++ /dev/null @@ -1,144 +0,0 @@ -from typing import IO, Optional - -from xinference_client.client.restful.restful_client import Client, RESTfulAudioModelHandle - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel - - -class XinferenceSpeech2TextModel(Speech2TextModel): - """ - Model class for Xinference speech to text model. - """ - - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - return self._speech2text_invoke(model, credentials, file) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: - raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") - - credentials["server_url"] = credentials["server_url"].removesuffix("/") - - # initialize client - client = Client( - base_url=credentials["server_url"], - api_key=credentials.get("api_key"), - ) - - xinference_client = client.get_model(model_uid=credentials["model_uid"]) - - if not isinstance(xinference_client, RESTfulAudioModelHandle): - raise InvokeBadRequestError( - "please check model type, the model you want to invoke is not a audio model" - ) - - audio_file_path = self._get_demo_file_path() - - with open(audio_file_path, "rb") as audio_file: - self.invoke(model, credentials, audio_file) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError], - } - - def _speech2text_invoke( - self, - model: str, - credentials: dict, - file: IO[bytes], - language: Optional[str] = None, - prompt: Optional[str] = None, - response_format: Optional[str] = "json", - temperature: Optional[float] = 0, - ) -> str: - """ - Invoke speech2text model - - :param model: model name - :param credentials: model credentials - :param file: The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, - mpga, m4a, ogg, wav, or webm. - :param language: The language of the input audio. Supplying the input language in ISO-639-1 - :param prompt: An optional text to guide the model's style or continue a previous audio segment. - The prompt should match the audio language. - :param response_format: The format of the transcript output, in one of these options: json, text, srt, - verbose_json, or vtt. - :param temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more - random,while lower values like 0.2 will make it more focused and deterministic.If set to 0, the model will use - log probability to automatically increase the temperature until certain thresholds are hit. - :return: text for given audio file - """ - server_url = credentials["server_url"] - model_uid = credentials["model_uid"] - api_key = credentials.get("api_key") - server_url = server_url.removesuffix("/") - auth_headers = {"Authorization": f"Bearer {api_key}"} if api_key else {} - - try: - handle = RESTfulAudioModelHandle(model_uid, server_url, auth_headers) - response = handle.transcriptions( - audio=file, language=language, prompt=prompt, response_format=response_format, temperature=temperature - ) - except RuntimeError as e: - raise InvokeServerUnavailableError(str(e)) - - return response["text"] - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.SPEECH2TEXT, - model_properties={}, - parameter_rules=[], - ) - - return entity diff --git a/api/core/model_runtime/model_providers/xinference/text_embedding/__init__.py b/api/core/model_runtime/model_providers/xinference/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/xinference/tts/__init__.py b/api/core/model_runtime/model_providers/xinference/tts/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/xinference/tts/tts.py b/api/core/model_runtime/model_providers/xinference/tts/tts.py deleted file mode 100644 index 81dbe397d2f10c..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/tts/tts.py +++ /dev/null @@ -1,228 +0,0 @@ -import concurrent.futures -from typing import Optional - -from xinference_client.client.restful.restful_client import RESTfulAudioModelHandle - -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.tts_model import TTSModel -from core.model_runtime.model_providers.xinference.xinference_helper import XinferenceHelper - - -class XinferenceText2SpeechModel(TTSModel): - def __init__(self): - # preset voices, need support custom voice - self.model_voices = { - "__default": { - "all": [ - {"name": "Default", "value": "default"}, - ] - }, - "ChatTTS": { - "all": [ - {"name": "Alloy", "value": "alloy"}, - {"name": "Echo", "value": "echo"}, - {"name": "Fable", "value": "fable"}, - {"name": "Onyx", "value": "onyx"}, - {"name": "Nova", "value": "nova"}, - {"name": "Shimmer", "value": "shimmer"}, - ] - }, - "CosyVoice": { - "zh-Hans": [ - {"name": "中文男", "value": "中文男"}, - {"name": "中文女", "value": "中文女"}, - {"name": "粤语女", "value": "粤语女"}, - ], - "zh-Hant": [ - {"name": "中文男", "value": "中文男"}, - {"name": "中文女", "value": "中文女"}, - {"name": "粤语女", "value": "粤语女"}, - ], - "en-US": [ - {"name": "英文男", "value": "英文男"}, - {"name": "英文女", "value": "英文女"}, - ], - "ja-JP": [ - {"name": "日语男", "value": "日语男"}, - ], - "ko-KR": [ - {"name": "韩语女", "value": "韩语女"}, - ], - }, - } - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: - raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") - - credentials["server_url"] = credentials["server_url"].removesuffix("/") - - extra_param = XinferenceHelper.get_xinference_extra_parameter( - server_url=credentials["server_url"], - model_uid=credentials["model_uid"], - api_key=credentials.get("api_key"), - ) - - if "text-to-audio" not in extra_param.model_ability: - raise InvokeBadRequestError( - "please check model type, the model you want to invoke is not a text-to-audio model" - ) - - if extra_param.model_family and extra_param.model_family in self.model_voices: - credentials["audio_model_name"] = extra_param.model_family - else: - credentials["audio_model_name"] = "__default" - - self._tts_invoke_streaming( - model=model, - credentials=credentials, - content_text="Hello Dify!", - voice=self._get_model_default_voice(model, credentials), - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _invoke( - self, model: str, tenant_id: str, credentials: dict, content_text: str, voice: str, user: Optional[str] = None - ): - """ - _invoke text2speech model - - :param model: model name - :param tenant_id: user tenant id - :param credentials: model credentials - :param voice: model timbre - :param content_text: text content to be translated - :param user: unique user id - :return: text translated to audio file - """ - return self._tts_invoke_streaming(model, credentials, content_text, voice) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TTS, - model_properties={}, - parameter_rules=[], - ) - - return entity - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError], - } - - def get_tts_model_voices(self, model: str, credentials: dict, language: Optional[str] = None) -> list: - audio_model_name = credentials.get("audio_model_name", "__default") - for key, voices in self.model_voices.items(): - if key in audio_model_name: - if language and language in voices: - return voices[language] - elif "all" in voices: - return voices["all"] - else: - all_voices = [] - for lang, lang_voices in voices.items(): - all_voices.extend(lang_voices) - return all_voices - - return self.model_voices["__default"]["all"] - - def _get_model_default_voice(self, model: str, credentials: dict) -> any: - return "" - - def _get_model_word_limit(self, model: str, credentials: dict) -> int: - return 3500 - - def _get_model_audio_type(self, model: str, credentials: dict) -> str: - return "mp3" - - def _get_model_workers_limit(self, model: str, credentials: dict) -> int: - return 5 - - def _tts_invoke_streaming(self, model: str, credentials: dict, content_text: str, voice: str) -> any: - """ - _tts_invoke_streaming text2speech model - - :param model: model name - :param credentials: model credentials - :param content_text: text content to be translated - :param voice: model timbre - :return: text translated to audio file - """ - credentials["server_url"] = credentials["server_url"].removesuffix("/") - - try: - api_key = credentials.get("api_key") - auth_headers = {"Authorization": f"Bearer {api_key}"} if api_key else {} - handle = RESTfulAudioModelHandle( - credentials["model_uid"], credentials["server_url"], auth_headers=auth_headers - ) - - model_support_voice = [ - x.get("value") for x in self.get_tts_model_voices(model=model, credentials=credentials) - ] - if not voice or voice not in model_support_voice: - voice = self._get_model_default_voice(model, credentials) - word_limit = self._get_model_word_limit(model, credentials) - if len(content_text) > word_limit: - sentences = self._split_text_into_sentences(content_text, max_length=word_limit) - executor = concurrent.futures.ThreadPoolExecutor(max_workers=min(3, len(sentences))) - futures = [ - executor.submit( - handle.speech, input=sentences[i], voice=voice, response_format="mp3", speed=1.0, stream=True - ) - for i in range(len(sentences)) - ] - - for future in futures: - response = future.result() - for chunk in response: - yield chunk - else: - response = handle.speech( - input=content_text.strip(), voice=voice, response_format="mp3", speed=1.0, stream=True - ) - - for chunk in response: - yield chunk - except Exception as ex: - raise InvokeBadRequestError(str(ex)) diff --git a/api/core/model_runtime/model_providers/xinference/xinference.py b/api/core/model_runtime/model_providers/xinference/xinference.py deleted file mode 100644 index d85f7c82e7db71..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/xinference.py +++ /dev/null @@ -1,10 +0,0 @@ -import logging - -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class XinferenceAIProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - pass diff --git a/api/core/model_runtime/model_providers/xinference/xinference.yaml b/api/core/model_runtime/model_providers/xinference/xinference.yaml deleted file mode 100644 index be9073c1cab1f4..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/xinference.yaml +++ /dev/null @@ -1,58 +0,0 @@ -provider: xinference -label: - en_US: Xorbits Inference -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#FAF5FF" -help: - title: - en_US: How to deploy Xinference - zh_Hans: 如何部署 Xinference - url: - en_US: https://github.com/xorbitsai/inference -supported_model_types: - - llm - - text-embedding - - rerank - - speech2text - - tts -configurate_methods: - - customizable-model -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: server_url - label: - zh_Hans: 服务器URL - en_US: Server url - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入Xinference的服务器地址，如 http://192.168.1.100:9997 - en_US: Enter the url of your Xinference, e.g. http://192.168.1.100:9997 - - variable: model_uid - label: - zh_Hans: 模型UID - en_US: Model uid - type: text-input - required: true - placeholder: - zh_Hans: 在此输入您的Model UID - en_US: Enter the model uid - - variable: api_key - label: - zh_Hans: API密钥 - en_US: API key - type: secret-input - required: false - placeholder: - zh_Hans: 在此输入您的API密钥 - en_US: Enter the api key diff --git a/api/core/model_runtime/model_providers/xinference/xinference_helper.py b/api/core/model_runtime/model_providers/xinference/xinference_helper.py deleted file mode 100644 index 619ee1492a9272..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/xinference_helper.py +++ /dev/null @@ -1,134 +0,0 @@ -from threading import Lock -from time import time -from typing import Optional - -from requests.adapters import HTTPAdapter -from requests.exceptions import ConnectionError, MissingSchema, Timeout -from requests.sessions import Session -from yarl import URL - - -class XinferenceModelExtraParameter: - model_format: str - model_handle_type: str - model_ability: list[str] - max_tokens: int = 512 - context_length: int = 2048 - support_function_call: bool = False - support_vision: bool = False - model_family: Optional[str] - - def __init__( - self, - model_format: str, - model_handle_type: str, - model_ability: list[str], - support_function_call: bool, - support_vision: bool, - max_tokens: int, - context_length: int, - model_family: Optional[str], - ) -> None: - self.model_format = model_format - self.model_handle_type = model_handle_type - self.model_ability = model_ability - self.support_function_call = support_function_call - self.support_vision = support_vision - self.max_tokens = max_tokens - self.context_length = context_length - self.model_family = model_family - - -cache = {} -cache_lock = Lock() - - -class XinferenceHelper: - @staticmethod - def get_xinference_extra_parameter(server_url: str, model_uid: str, api_key: str) -> XinferenceModelExtraParameter: - XinferenceHelper._clean_cache() - with cache_lock: - if model_uid not in cache: - cache[model_uid] = { - "expires": time() + 300, - "value": XinferenceHelper._get_xinference_extra_parameter(server_url, model_uid, api_key), - } - return cache[model_uid]["value"] - - @staticmethod - def _clean_cache() -> None: - try: - with cache_lock: - expired_keys = [model_uid for model_uid, model in cache.items() if model["expires"] < time()] - for model_uid in expired_keys: - del cache[model_uid] - except RuntimeError as e: - pass - - @staticmethod - def _get_xinference_extra_parameter(server_url: str, model_uid: str, api_key: str) -> XinferenceModelExtraParameter: - """ - get xinference model extra parameter like model_format and model_handle_type - """ - - if not model_uid or not model_uid.strip() or not server_url or not server_url.strip(): - raise RuntimeError("model_uid is empty") - - url = str(URL(server_url) / "v1" / "models" / model_uid) - - # this method is surrounded by a lock, and default requests may hang forever, - # so we just set a Adapter with max_retries=3 - session = Session() - session.mount("http://", HTTPAdapter(max_retries=3)) - session.mount("https://", HTTPAdapter(max_retries=3)) - headers = {"Authorization": f"Bearer {api_key}"} if api_key else {} - - try: - response = session.get(url, headers=headers, timeout=10) - except (MissingSchema, ConnectionError, Timeout) as e: - raise RuntimeError(f"get xinference model extra parameter failed, url: {url}, error: {e}") - if response.status_code != 200: - raise RuntimeError( - f"get xinference model extra parameter failed, status code: {response.status_code}," - f" response: {response.text}" - ) - - response_json = response.json() - - model_format = response_json.get("model_format", "ggmlv3") - model_ability = response_json.get("model_ability", []) - model_family = response_json.get("model_family", None) - - if response_json.get("model_type") == "embedding": - model_handle_type = "embedding" - elif response_json.get("model_type") == "audio": - model_handle_type = "audio" - if model_family and model_family in {"ChatTTS", "CosyVoice", "FishAudio"}: - model_ability.append("text-to-audio") - else: - model_ability.append("audio-to-text") - elif model_format == "ggmlv3" and "chatglm" in response_json["model_name"]: - model_handle_type = "chatglm" - elif "generate" in model_ability: - model_handle_type = "generate" - elif "chat" in model_ability: - model_handle_type = "chat" - else: - raise NotImplementedError("xinference model handle type is not supported") - - support_function_call = "tools" in model_ability - support_vision = "vision" in model_ability - max_tokens = response_json.get("max_tokens", 512) - - context_length = response_json.get("context_length", 2048) - - return XinferenceModelExtraParameter( - model_format=model_format, - model_handle_type=model_handle_type, - model_ability=model_ability, - support_function_call=support_function_call, - support_vision=support_vision, - max_tokens=max_tokens, - context_length=context_length, - model_family=model_family, - ) diff --git a/api/core/model_runtime/model_providers/yi/__init__.py b/api/core/model_runtime/model_providers/yi/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/yi/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/yi/_assets/icon_l_en.svg deleted file mode 100644 index 9ce3baddaa94ed..00000000000000 --- a/api/core/model_runtime/model_providers/yi/_assets/icon_l_en.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - - - - - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/yi/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/yi/_assets/icon_s_en.svg deleted file mode 100644 index eb0395a21c5dd8..00000000000000 --- a/api/core/model_runtime/model_providers/yi/_assets/icon_s_en.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - \ No newline at end of file diff --git a/api/core/model_runtime/model_providers/yi/llm/__init__.py b/api/core/model_runtime/model_providers/yi/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/yi/llm/_position.yaml b/api/core/model_runtime/model_providers/yi/llm/_position.yaml deleted file mode 100644 index e876893b414985..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/_position.yaml +++ /dev/null @@ -1,9 +0,0 @@ -- yi-34b-chat-0205 -- yi-34b-chat-200k -- yi-vl-plus -- yi-large -- yi-medium -- yi-vision -- yi-medium-200k -- yi-spark -- yi-large-turbo diff --git a/api/core/model_runtime/model_providers/yi/llm/llm.py b/api/core/model_runtime/model_providers/yi/llm/llm.py deleted file mode 100644 index 5ab7fd126e3082..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/llm.py +++ /dev/null @@ -1,127 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union -from urllib.parse import urlparse - -import tiktoken - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import ( - PromptMessage, - PromptMessageTool, - SystemPromptMessage, -) -from core.model_runtime.model_providers.openai.llm.llm import OpenAILargeLanguageModel - - -class YiLargeLanguageModel(OpenAILargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials) - - # yi-vl-plus not support system prompt yet. - if model == "yi-vl-plus": - prompt_message_except_system: list[PromptMessage] = [] - for message in prompt_messages: - if not isinstance(message, SystemPromptMessage): - prompt_message_except_system.append(message) - return super()._invoke( - model, credentials, prompt_message_except_system, model_parameters, tools, stop, stream - ) - - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - # refactored from openai model runtime, use cl100k_base for calculate token number - def _num_tokens_from_string(self, model: str, text: str, tools: Optional[list[PromptMessageTool]] = None) -> int: - """ - Calculate num tokens for text completion model with tiktoken package. - - :param model: model name - :param text: prompt text - :param tools: tools for tool calling - :return: number of tokens - """ - encoding = tiktoken.get_encoding("cl100k_base") - num_tokens = len(encoding.encode(text)) - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - # refactored from openai model runtime, use cl100k_base for calculate token number - def _num_tokens_from_messages( - self, model: str, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None - ) -> int: - """Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package. - - Official documentation: https://github.com/openai/openai-cookbook/blob/ - main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb""" - encoding = tiktoken.get_encoding("cl100k_base") - tokens_per_message = 3 - tokens_per_name = 1 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - # Cast str(value) in case the message value is not a string - # This occurs with function messages - # TODO: The current token calculation method for the image type is not implemented, - # which need to download the image and then get the resolution for calculation, - # and will increase the request delay - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += len(encoding.encode(t_key)) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += len(encoding.encode(f_key)) - num_tokens += len(encoding.encode(f_value)) - else: - num_tokens += len(encoding.encode(t_key)) - num_tokens += len(encoding.encode(t_value)) - else: - num_tokens += len(encoding.encode(str(value))) - - if key == "name": - num_tokens += tokens_per_name - - # every reply is primed with assistant - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(encoding, tools) - - return num_tokens - - @staticmethod - def _add_custom_parameters(credentials: dict) -> None: - credentials["mode"] = "chat" - credentials["openai_api_key"] = credentials["api_key"] - if "endpoint_url" not in credentials or credentials["endpoint_url"] == "": - credentials["openai_api_base"] = "https://api.lingyiwanwu.com" - else: - parsed_url = urlparse(credentials["endpoint_url"]) - credentials["openai_api_base"] = f"{parsed_url.scheme}://{parsed_url.netloc}" diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-34b-chat-0205.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-34b-chat-0205.yaml deleted file mode 100644 index ea3d8f5dcee376..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-34b-chat-0205.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: yi-34b-chat-0205 -label: - zh_Hans: yi-34b-chat-0205 - en_US: yi-34b-chat-0205 -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4000 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '2.5' - output: '2.5' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-34b-chat-200k.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-34b-chat-200k.yaml deleted file mode 100644 index d91f984d7f006f..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-34b-chat-200k.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: yi-34b-chat-200k -label: - zh_Hans: yi-34b-chat-200k - en_US: yi-34b-chat-200k -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 200000 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.6 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 4096 - min: 1 - max: 199950 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.9 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '12' - output: '12' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-large-turbo.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-large-turbo.yaml deleted file mode 100644 index 1d00eca2cafebb..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-large-turbo.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: yi-large-turbo -label: - zh_Hans: yi-large-turbo - en_US: yi-large-turbo -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 1024 - min: 1 - max: 16384 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.9 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '12' - output: '12' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-large.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-large.yaml deleted file mode 100644 index 347f511280b9ad..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-large.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: yi-large -label: - zh_Hans: yi-large - en_US: yi-large -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 1024 - min: 1 - max: 16384 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.9 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '20' - output: '20' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-medium-200k.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-medium-200k.yaml deleted file mode 100644 index e8ddbcba97b415..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-medium-200k.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: yi-medium-200k -label: - zh_Hans: yi-medium-200k - en_US: yi-medium-200k -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 204800 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 1024 - min: 1 - max: 204800 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.9 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '12' - output: '12' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-medium.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-medium.yaml deleted file mode 100644 index 4f0244d1f5e7b7..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-medium.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: yi-medium -label: - zh_Hans: yi-medium - en_US: yi-medium -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 1024 - min: 1 - max: 16384 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.9 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '2.5' - output: '2.5' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-spark.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-spark.yaml deleted file mode 100644 index e28e9fd8c09e82..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-spark.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: yi-spark -label: - zh_Hans: yi-spark - en_US: yi-spark -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 16384 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 1024 - min: 1 - max: 16384 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.9 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '1' - output: '1' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-vision.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-vision.yaml deleted file mode 100644 index bce34f58364f24..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-vision.yaml +++ /dev/null @@ -1,44 +0,0 @@ -model: yi-vision -label: - zh_Hans: yi-vision - en_US: yi-vision -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 1024 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.9 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '6' - output: '6' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/llm/yi-vl-plus.yaml b/api/core/model_runtime/model_providers/yi/llm/yi-vl-plus.yaml deleted file mode 100644 index 461c68583fe669..00000000000000 --- a/api/core/model_runtime/model_providers/yi/llm/yi-vl-plus.yaml +++ /dev/null @@ -1,43 +0,0 @@ -model: yi-vl-plus -label: - zh_Hans: yi-vl-plus - en_US: yi-vl-plus -model_type: llm -features: - - vision -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。 - en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is. - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4000 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.01 - max: 1.00 - help: - zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。 - en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature. -pricing: - input: '6' - output: '6' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/yi/yi.py b/api/core/model_runtime/model_providers/yi/yi.py deleted file mode 100644 index 9599acb22b505a..00000000000000 --- a/api/core/model_runtime/model_providers/yi/yi.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class YiProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `yi-34b-chat-0205` model for validate, - # no matter what model you pass in, text completion model or chat model - model_instance.validate_credentials(model="yi-34b-chat-0205", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/yi/yi.yaml b/api/core/model_runtime/model_providers/yi/yi.yaml deleted file mode 100644 index de741afb10990c..00000000000000 --- a/api/core/model_runtime/model_providers/yi/yi.yaml +++ /dev/null @@ -1,41 +0,0 @@ -provider: yi -label: - en_US: 01.AI - zh_Hans: 零一万物 -description: - en_US: Models provided by 01.AI, such as yi-34b-chat and yi-vl-plus. - zh_Hans: 零一万物提供的模型，例如 yi-34b-chat 和 yi-vl-plus。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#E9F1EC" -help: - title: - en_US: Get your API Key from 01.ai - zh_Hans: 从零一万物获取 API Key - url: - en_US: https://platform.lingyiwanwu.com/apikeys -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: endpoint_url - label: - zh_Hans: 自定义 API endpoint 地址 - en_US: Custom API endpoint URL - type: text-input - required: false - placeholder: - zh_Hans: Base URL, e.g. https://api.lingyiwanwu.com/v1 - en_US: Base URL, e.g. https://api.lingyiwanwu.com/v1 diff --git a/api/core/model_runtime/model_providers/zhinao/__init__.py b/api/core/model_runtime/model_providers/zhinao/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/zhinao/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/zhinao/_assets/icon_l_en.svg deleted file mode 100644 index b22b8694419bc7..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/_assets/icon_l_en.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - diff --git a/api/core/model_runtime/model_providers/zhinao/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/zhinao/_assets/icon_s_en.svg deleted file mode 100644 index 8fe72b7d0928e6..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/_assets/icon_s_en.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - diff --git a/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo-responsibility-8k.yaml b/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo-responsibility-8k.yaml deleted file mode 100644 index f420df0001b3a2..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo-responsibility-8k.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: 360gpt-turbo-responsibility-8k -label: - zh_Hans: 360gpt-turbo-responsibility-8k - en_US: 360gpt-turbo-responsibility-8k -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 8192 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 8192 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo.yaml b/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo.yaml deleted file mode 100644 index a2658fbe4f5c0e..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: 360gpt-turbo -label: - zh_Hans: 360gpt-turbo - en_US: 360gpt-turbo -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 2048 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/zhinao/llm/360gpt2-pro.yaml b/api/core/model_runtime/model_providers/zhinao/llm/360gpt2-pro.yaml deleted file mode 100644 index 00c81eb1daaffb..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/llm/360gpt2-pro.yaml +++ /dev/null @@ -1,36 +0,0 @@ -model: 360gpt2-pro -label: - zh_Hans: 360gpt2-pro - en_US: 360gpt2-pro -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 2048 -parameter_rules: - - name: temperature - use_template: temperature - min: 0 - max: 1 - default: 0.5 - - name: top_p - use_template: top_p - min: 0 - max: 1 - default: 1 - - name: max_tokens - use_template: max_tokens - min: 1 - max: 2048 - default: 1024 - - name: frequency_penalty - use_template: frequency_penalty - min: -2 - max: 2 - default: 0 - - name: presence_penalty - use_template: presence_penalty - min: -2 - max: 2 - default: 0 diff --git a/api/core/model_runtime/model_providers/zhinao/llm/__init__.py b/api/core/model_runtime/model_providers/zhinao/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/zhinao/llm/_position.yaml b/api/core/model_runtime/model_providers/zhinao/llm/_position.yaml deleted file mode 100644 index ab8dbf51821c0a..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/llm/_position.yaml +++ /dev/null @@ -1,3 +0,0 @@ -- 360gpt2-pro -- 360gpt-turbo -- 360gpt-turbo-responsibility-8k diff --git a/api/core/model_runtime/model_providers/zhinao/llm/llm.py b/api/core/model_runtime/model_providers/zhinao/llm/llm.py deleted file mode 100644 index befc3de021e1f2..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/llm/llm.py +++ /dev/null @@ -1,31 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult -from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - - -class ZhinaoLargeLanguageModel(OAIAPICompatLargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - self._add_custom_parameters(credentials) - return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream) - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - @classmethod - def _add_custom_parameters(cls, credentials: dict) -> None: - credentials["mode"] = "chat" - credentials["endpoint_url"] = "https://api.360.cn/v1" diff --git a/api/core/model_runtime/model_providers/zhinao/zhinao.py b/api/core/model_runtime/model_providers/zhinao/zhinao.py deleted file mode 100644 index 2a263292f98f14..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/zhinao.py +++ /dev/null @@ -1,28 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class ZhinaoProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - # Use `360gpt-turbo` model for validate, - # no matter what model you pass in, text completion model or chat model - model_instance.validate_credentials(model="360gpt-turbo", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/zhinao/zhinao.yaml b/api/core/model_runtime/model_providers/zhinao/zhinao.yaml deleted file mode 100644 index c5cb142c47d4c3..00000000000000 --- a/api/core/model_runtime/model_providers/zhinao/zhinao.yaml +++ /dev/null @@ -1,32 +0,0 @@ -provider: zhinao -label: - en_US: 360 AI - zh_Hans: 360 智脑 -description: - en_US: Models provided by 360 AI. - zh_Hans: 360 智脑提供的模型。 -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#e3f0ff" -help: - title: - en_US: Get your API Key from 360 AI. - zh_Hans: 从360 智脑获取 API Key - url: - en_US: https://ai.360.com/platform/keys -supported_model_types: - - llm -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/zhipuai/__init__.py b/api/core/model_runtime/model_providers/zhipuai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/zhipuai/_assets/icon_l_en.svg b/api/core/model_runtime/model_providers/zhipuai/_assets/icon_l_en.svg deleted file mode 100644 index d32499917d3c72..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/_assets/icon_l_en.svg +++ /dev/null @@ -1,6 +0,0 @@ - - - - - - diff --git a/api/core/model_runtime/model_providers/zhipuai/_assets/icon_l_zh.svg b/api/core/model_runtime/model_providers/zhipuai/_assets/icon_l_zh.svg deleted file mode 100644 index 067ea2c4272ee8..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/_assets/icon_l_zh.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - diff --git a/api/core/model_runtime/model_providers/zhipuai/_assets/icon_s_en.svg b/api/core/model_runtime/model_providers/zhipuai/_assets/icon_s_en.svg deleted file mode 100644 index 016f97ddab8dab..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/_assets/icon_s_en.svg +++ /dev/null @@ -1,8 +0,0 @@ - - - - - - - - diff --git a/api/core/model_runtime/model_providers/zhipuai/_common.py b/api/core/model_runtime/model_providers/zhipuai/_common.py deleted file mode 100644 index fa95232f717d78..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/_common.py +++ /dev/null @@ -1,41 +0,0 @@ -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) - - -class _CommonZhipuaiAI: - def _to_credential_kwargs(self, credentials: dict) -> dict: - """ - Transform credentials to kwargs for model instance - - :param credentials: - :return: - """ - credentials_kwargs = { - "api_key": credentials["api_key"] if "api_key" in credentials else credentials.get("zhipuai_api_key"), - } - - return credentials_kwargs - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [], - InvokeRateLimitError: [], - InvokeAuthorizationError: [], - InvokeBadRequestError: [], - } diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/__init__.py b/api/core/model_runtime/model_providers/zhipuai/llm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_lite.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_lite.yaml deleted file mode 100644 index 9778de1a2eeaa0..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_lite.yaml +++ /dev/null @@ -1,22 +0,0 @@ -model: chatglm_lite -label: - en_US: chatglm_lite -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.9 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. -deprecated: true diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_lite_32k.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_lite_32k.yaml deleted file mode 100644 index 7836d964c64cf9..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_lite_32k.yaml +++ /dev/null @@ -1,22 +0,0 @@ -model: chatglm_lite_32k -label: - en_US: chatglm_lite_32k -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.9 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. -deprecated: true diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_pro.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_pro.yaml deleted file mode 100644 index b3d53c812bd8fd..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_pro.yaml +++ /dev/null @@ -1,22 +0,0 @@ -model: chatglm_pro -label: - en_US: chatglm_pro -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.9 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. -deprecated: true diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_std.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_std.yaml deleted file mode 100644 index 7d8b9520a0ee47..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_std.yaml +++ /dev/null @@ -1,22 +0,0 @@ -model: chatglm_std -label: - en_US: chatglm_std -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.9 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. -deprecated: true diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_turbo.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_turbo.yaml deleted file mode 100644 index fcd5c5ef640206..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/chatglm_turbo.yaml +++ /dev/null @@ -1,51 +0,0 @@ -model: chatglm_turbo -label: - en_US: chatglm_turbo -model_type: llm -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: return_type - label: - zh_Hans: 回复类型 - en_US: Return Type - type: string - help: - zh_Hans: 用于控制每次返回内容的类型，空或者没有此字段时默认按照 json_string 返回，json_string 返回标准的 JSON 字符串，text 返回原始的文本内容。 - en_US: Used to control the type of content returned each time. When it is empty or does not have this field, it will be returned as json_string by default. json_string returns a standard JSON string, and text returns the original text content. - required: false - options: - - text - - json_string diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-0520.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-0520.yaml deleted file mode 100644 index 7fcf6922023fbf..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-0520.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: glm-4-0520 -label: - en_US: glm-4-0520 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 4095 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.1' - output: '0.1' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-air.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-air.yaml deleted file mode 100644 index fcd7c7768c7179..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-air.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: glm-4-air -label: - en_US: glm-4-air -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 4095 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.001' - output: '0.001' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-airx.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-airx.yaml deleted file mode 100644 index c9ae5abf196360..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-airx.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: glm-4-airx -label: - en_US: glm-4-airx -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 4095 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.01' - output: '0.01' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-flash.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-flash.yaml deleted file mode 100644 index 98c4f72c7237f7..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-flash.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: glm-4-flash -label: - en_US: glm-4-flash -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 4095 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0' - output: '0' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm_3_turbo.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm_3_turbo.yaml deleted file mode 100644 index 0b5391ce2f83fd..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm_3_turbo.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: glm-3-turbo -label: - en_US: glm-3-turbo -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 8192 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.001' - output: '0.001' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm_4.yaml deleted file mode 100644 index 62f453fb775b9b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: glm-4 -label: - en_US: glm-4 -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 4095 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.1' - output: '0.1' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml deleted file mode 100644 index 350b080c3fc11b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml +++ /dev/null @@ -1,65 +0,0 @@ -model: glm-4-long -label: - en_US: glm-4-long -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat - context_size: 10240 -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - min: 0.0 - max: 1.0 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 4095 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.001' - output: '0.001' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_plus.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_plus.yaml deleted file mode 100644 index 2d7ebd71cf26e1..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_plus.yaml +++ /dev/null @@ -1,62 +0,0 @@ -model: glm-4-plus -label: - en_US: glm-4-plus -model_type: llm -features: - - multi-tool-call - - agent-thought - - stream-tool-call -model_properties: - mode: chat -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.7 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 4095 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.05' - output: '0.05' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4v.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm_4v.yaml deleted file mode 100644 index 3a1120ff375c19..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4v.yaml +++ /dev/null @@ -1,60 +0,0 @@ -model: glm-4v -label: - en_US: glm-4v -model_type: llm -model_properties: - mode: chat -features: - - vision -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.6 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.05' - output: '0.05' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4v_plus.yaml b/api/core/model_runtime/model_providers/zhipuai/llm/glm_4v_plus.yaml deleted file mode 100644 index 14b9623e5a8c44..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4v_plus.yaml +++ /dev/null @@ -1,60 +0,0 @@ -model: glm-4v-plus -label: - en_US: glm-4v-plus -model_type: llm -model_properties: - mode: chat -features: - - vision -parameter_rules: - - name: temperature - use_template: temperature - default: 0.95 - min: 0.0 - max: 1.0 - help: - zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: top_p - use_template: top_p - default: 0.6 - help: - zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。 - en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time. - - name: do_sample - label: - zh_Hans: 采样策略 - en_US: Sampling strategy - type: boolean - help: - zh_Hans: do_sample 为 true 时启用采样策略，do_sample 为 false 时采样策略 temperature、top_p 将不生效。默认值为 true。 - en_US: When `do_sample` is set to true, the sampling strategy is enabled. When `do_sample` is set to false, the sampling strategies such as `temperature` and `top_p` will not take effect. The default value is true. - default: true - - name: stream - label: - zh_Hans: 流处理 - en_US: Event Stream - type: boolean - help: - zh_Hans: 使用同步调用时，此参数应当设置为 fasle 或者省略。表示模型生成完所有内容后一次性返回所有内容。默认值为 false。如果设置为 true，模型将通过标准 Event Stream ，逐块返回模型生成内容。Event Stream 结束时会返回一条data：[DONE]消息。注意：在模型流式输出生成内容的过程中，我们会分批对模型生成内容进行检测，当检测到违法及不良信息时，API会返回错误码（1301）。开发者识别到错误码（1301），应及时采取（清屏、重启对话）等措施删除生成内容，并确保不将含有违法及不良信息的内容传递给模型继续生成，避免其造成负面影响。 - en_US: When using synchronous invocation, this parameter should be set to false or omitted. It indicates that the model will return all the generated content at once after the generation is complete. The default value is false. If set to true, the model will return the generated content in chunks via the standard Event Stream. A data：[DONE] message will be sent at the end of the Event Stream.Note：During the model's streaming output process, we will batch check the generated content. If illegal or harmful information is detected, the API will return an error code (1301). Developers who identify error code (1301) should promptly take actions such as clearing the screen or restarting the conversation to delete the generated content. They should also ensure that no illegal or harmful content is passed back to the model for continued generation to avoid negative impacts. - default: false - - name: max_tokens - use_template: max_tokens - default: 1024 - min: 1 - max: 1024 - - name: web_search - type: boolean - label: - zh_Hans: 联网搜索 - en_US: Web Search - default: false - help: - zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。 - en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic. -pricing: - input: '0.01' - output: '0.01' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/llm/llm.py b/api/core/model_runtime/model_providers/zhipuai/llm/llm.py deleted file mode 100644 index ea331701abb78a..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/llm/llm.py +++ /dev/null @@ -1,486 +0,0 @@ -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageContent, - PromptMessageContentType, - PromptMessageRole, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.zhipuai._common import _CommonZhipuaiAI -from core.model_runtime.model_providers.zhipuai.zhipuai_sdk._client import ZhipuAI -from core.model_runtime.model_providers.zhipuai.zhipuai_sdk.types.chat.chat_completion import Completion -from core.model_runtime.model_providers.zhipuai.zhipuai_sdk.types.chat.chat_completion_chunk import ChatCompletionChunk -from core.model_runtime.utils import helper - -GLM_JSON_MODE_PROMPT = """You should always follow the instructions and output a valid JSON object. -The structure of the JSON object you can found in the instructions, use {"answer": "$your_answer"} as the default structure -if you are not sure about the structure. - -And you should always end the block with a "```" to indicate the end of the JSON object. - - -{{instructions}} - - -```JSON""" # noqa: E501 - - -class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - # invoke model - # stop = stop or [] - # self._transform_json_prompts(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - return self._generate(model, credentials_kwargs, prompt_messages, model_parameters, tools, stop, stream, user) - - # def _transform_json_prompts(self, model: str, credentials: dict, - # prompt_messages: list[PromptMessage], model_parameters: dict, - # tools: list[PromptMessageTool] | None = None, stop: list[str] | None = None, - # stream: bool = True, user: str | None = None) \ - # -> None: - # """ - # Transform json prompts to model prompts - # """ - # if "}\n\n" not in stop: - # stop.append("}\n\n") - - # # check if there is a system message - # if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage): - # # override the system message - # prompt_messages[0] = SystemPromptMessage( - # content=GLM_JSON_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content) - # ) - # else: - # # insert the system message - # prompt_messages.insert(0, SystemPromptMessage( - # content=GLM_JSON_MODE_PROMPT.replace("{{instructions}}", "Please output a valid JSON object.") - # )) - # # check if the last message is a user message - # if len(prompt_messages) > 0 and isinstance(prompt_messages[-1], UserPromptMessage): - # # add ```JSON\n to the last message - # prompt_messages[-1].content += "\n```JSON\n" - # else: - # # append a user message - # prompt_messages.append(UserPromptMessage( - # content="```JSON\n" - # )) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - prompt = self._convert_messages_to_prompt(prompt_messages, tools) - - return self._get_num_tokens_by_gpt2(prompt) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - self._generate( - model=model, - credentials_kwargs=credentials_kwargs, - prompt_messages=[ - UserPromptMessage(content="ping"), - ], - model_parameters={ - "temperature": 0.5, - }, - tools=[], - stream=False, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _generate( - self, - model: str, - credentials_kwargs: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials_kwargs: credentials kwargs - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - extra_model_kwargs = {} - # request to glm-4v-plus with stop words will always response "finish_reason":"network_error" - if stop and model != "glm-4v-plus": - extra_model_kwargs["stop"] = stop - - client = ZhipuAI(api_key=credentials_kwargs["api_key"]) - - if len(prompt_messages) == 0: - raise ValueError("At least one message is required") - - if prompt_messages[0].role == PromptMessageRole.SYSTEM: - if not prompt_messages[0].content: - prompt_messages = prompt_messages[1:] - - # resolve zhipuai model not support system message and user message, assistant message must be in sequence - new_prompt_messages: list[PromptMessage] = [] - for prompt_message in prompt_messages: - copy_prompt_message = prompt_message.copy() - if copy_prompt_message.role in {PromptMessageRole.USER, PromptMessageRole.SYSTEM, PromptMessageRole.TOOL}: - if isinstance(copy_prompt_message.content, list): - # check if model is 'glm-4v' - if model not in {"glm-4v", "glm-4v-plus"}: - # not support list message - continue - # get image and - if not isinstance(copy_prompt_message, UserPromptMessage): - # not support system message - continue - new_prompt_messages.append(copy_prompt_message) - - if not isinstance(copy_prompt_message.content, str): - # not support image message - continue - - if ( - new_prompt_messages - and new_prompt_messages[-1].role == PromptMessageRole.USER - and copy_prompt_message.role == PromptMessageRole.USER - ): - new_prompt_messages[-1].content += "\n\n" + copy_prompt_message.content - else: - if copy_prompt_message.role in {PromptMessageRole.USER, PromptMessageRole.TOOL}: - new_prompt_messages.append(copy_prompt_message) - elif copy_prompt_message.role == PromptMessageRole.SYSTEM: - new_prompt_message = SystemPromptMessage(content=copy_prompt_message.content) - new_prompt_messages.append(new_prompt_message) - else: - new_prompt_message = UserPromptMessage(content=copy_prompt_message.content) - new_prompt_messages.append(new_prompt_message) - else: - if new_prompt_messages and new_prompt_messages[-1].role == PromptMessageRole.ASSISTANT: - new_prompt_messages[-1].content += "\n\n" + copy_prompt_message.content - else: - new_prompt_messages.append(copy_prompt_message) - - if model in {"glm-4v", "glm-4v-plus"}: - params = self._construct_glm_4v_parameter(model, new_prompt_messages, model_parameters) - else: - params = {"model": model, "messages": [], **model_parameters} - # glm model - if not model.startswith("chatglm"): - for prompt_message in new_prompt_messages: - if prompt_message.role == PromptMessageRole.TOOL: - params["messages"].append( - { - "role": "tool", - "content": prompt_message.content, - "tool_call_id": prompt_message.tool_call_id, - } - ) - elif isinstance(prompt_message, AssistantPromptMessage): - if prompt_message.tool_calls: - params["messages"].append( - { - "role": "assistant", - "content": prompt_message.content, - "tool_calls": [ - { - "id": tool_call.id, - "type": tool_call.type, - "function": { - "name": tool_call.function.name, - "arguments": tool_call.function.arguments, - }, - } - for tool_call in prompt_message.tool_calls - ], - } - ) - else: - params["messages"].append({"role": "assistant", "content": prompt_message.content}) - else: - params["messages"].append( - {"role": prompt_message.role.value, "content": prompt_message.content} - ) - else: - # chatglm model - for prompt_message in new_prompt_messages: - # merge system message to user message - if prompt_message.role in { - PromptMessageRole.SYSTEM, - PromptMessageRole.TOOL, - PromptMessageRole.USER, - }: - if len(params["messages"]) > 0 and params["messages"][-1]["role"] == "user": - params["messages"][-1]["content"] += "\n\n" + prompt_message.content - else: - params["messages"].append({"role": "user", "content": prompt_message.content}) - else: - params["messages"].append( - {"role": prompt_message.role.value, "content": prompt_message.content} - ) - - if tools and len(tools) > 0: - params["tools"] = [{"type": "function", "function": helper.dump_model(tool)} for tool in tools] - - if stream: - response = client.chat.completions.create(stream=stream, **params, **extra_model_kwargs) - return self._handle_generate_stream_response(model, credentials_kwargs, tools, response, prompt_messages) - - response = client.chat.completions.create(**params, **extra_model_kwargs) - return self._handle_generate_response(model, credentials_kwargs, tools, response, prompt_messages) - - def _construct_glm_4v_parameter(self, model: str, prompt_messages: list[PromptMessage], model_parameters: dict): - messages = [ - {"role": message.role.value, "content": self._construct_glm_4v_messages(message.content)} - for message in prompt_messages - ] - - params = {"model": model, "messages": messages, **model_parameters} - - return params - - def _construct_glm_4v_messages(self, prompt_message: Union[str, list[PromptMessageContent]]) -> list[dict]: - if isinstance(prompt_message, str): - return [{"type": "text", "text": prompt_message}] - - return [ - {"type": "image_url", "image_url": {"url": self._remove_image_header(item.data)}} - if item.type == PromptMessageContentType.IMAGE - else {"type": "text", "text": item.data} - for item in prompt_message - ] - - def _remove_image_header(self, image: str) -> str: - if image.startswith("data:image"): - return image.split(",")[1] - - return image - - def _handle_generate_response( - self, - model: str, - credentials: dict, - tools: Optional[list[PromptMessageTool]], - response: Completion, - prompt_messages: list[PromptMessage], - ) -> LLMResult: - """ - Handle llm response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - text = "" - assistant_tool_calls: list[AssistantPromptMessage.ToolCall] = [] - for choice in response.choices: - if choice.message.tool_calls: - for tool_call in choice.message.tool_calls: - if tool_call.type == "function": - assistant_tool_calls.append( - AssistantPromptMessage.ToolCall( - id=tool_call.id, - type=tool_call.type, - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=tool_call.function.name, - arguments=tool_call.function.arguments, - ), - ) - ) - - text += choice.message.content or "" - - prompt_usage = response.usage.prompt_tokens - completion_usage = response.usage.completion_tokens - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_usage, completion_usage) - - # transform response - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=AssistantPromptMessage(content=text, tool_calls=assistant_tool_calls), - usage=usage, - ) - - return result - - def _handle_generate_stream_response( - self, - model: str, - credentials: dict, - tools: Optional[list[PromptMessageTool]], - responses: Generator[ChatCompletionChunk, None, None], - prompt_messages: list[PromptMessage], - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - full_assistant_content = "" - for chunk in responses: - if len(chunk.choices) == 0: - continue - - delta = chunk.choices[0] - - if delta.finish_reason is None and (delta.delta.content is None or delta.delta.content == ""): - continue - - assistant_tool_calls: list[AssistantPromptMessage.ToolCall] = [] - for tool_call in delta.delta.tool_calls or []: - if tool_call.type == "function": - assistant_tool_calls.append( - AssistantPromptMessage.ToolCall( - id=tool_call.id, - type=tool_call.type, - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=tool_call.function.name, - arguments=tool_call.function.arguments, - ), - ) - ) - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage( - content=delta.delta.content or "", tool_calls=assistant_tool_calls - ) - - full_assistant_content += delta.delta.content or "" - - if delta.finish_reason is not None and chunk.usage is not None: - completion_tokens = chunk.usage.completion_tokens - prompt_tokens = chunk.usage.prompt_tokens - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint="", - delta=LLMResultChunkDelta( - index=delta.index, - message=assistant_prompt_message, - finish_reason=delta.finish_reason, - usage=usage, - ), - ) - else: - yield LLMResultChunk( - model=chunk.model, - prompt_messages=prompt_messages, - system_fingerprint="", - delta=LLMResultChunkDelta( - index=delta.index, message=assistant_prompt_message, finish_reason=delta.finish_reason - ), - ) - - def _convert_one_message_to_text(self, message: PromptMessage) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt = "\n\nHuman:" - ai_prompt = "\n\nAssistant:" - content = message.content - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage | ToolPromptMessage): - message_text = content - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - def _convert_messages_to_prompt( - self, messages: list[PromptMessage], tools: Optional[list[PromptMessageTool]] = None - ) -> str: - """ - :param messages: List of PromptMessage to combine. - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - if tools and len(tools) > 0: - text += "\n\nTools:" - for tool in tools: - text += f"\n{tool.json()}" - - # trim off the trailing ' ' that might come from the "Assistant: " - return text.rstrip() diff --git a/api/core/model_runtime/model_providers/zhipuai/text_embedding/__init__.py b/api/core/model_runtime/model_providers/zhipuai/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-2.yaml b/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-2.yaml deleted file mode 100644 index f1b8b356028e25..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-2.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: embedding-2 -model_type: text-embedding -model_properties: - context_size: 8192 -pricing: - input: '0.0005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-3.yaml b/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-3.yaml deleted file mode 100644 index 5c55c911c4bdd1..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-3.yaml +++ /dev/null @@ -1,8 +0,0 @@ -model: embedding-3 -model_type: text-embedding -model_properties: - context_size: 8192 -pricing: - input: '0.0005' - unit: '0.001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/zhipuai/text_embedding/text_embedding.yaml b/api/core/model_runtime/model_providers/zhipuai/text_embedding/text_embedding.yaml deleted file mode 100644 index b9f5bc6397a36b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/text_embedding/text_embedding.yaml +++ /dev/null @@ -1,4 +0,0 @@ -model: text_embedding -model_type: text-embedding -model_properties: - context_size: 512 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai.py deleted file mode 100644 index e75aad6eb0eb53..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai.py +++ /dev/null @@ -1,27 +0,0 @@ -import logging - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.model_provider import ModelProvider - -logger = logging.getLogger(__name__) - - -class ZhipuaiProvider(ModelProvider): - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - try: - model_instance = self.get_model_instance(ModelType.LLM) - - model_instance.validate_credentials(model="glm-4", credentials=credentials) - except CredentialsValidateFailedError as ex: - raise ex - except Exception as ex: - logger.exception(f"{self.get_provider_schema().provider} credentials validate failed") - raise ex diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai.yaml b/api/core/model_runtime/model_providers/zhipuai/zhipuai.yaml deleted file mode 100644 index 303a549128a89c..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai.yaml +++ /dev/null @@ -1,31 +0,0 @@ -provider: zhipuai -label: - zh_Hans: 智谱 AI - en_US: ZHIPU AI -icon_small: - en_US: icon_s_en.svg -icon_large: - zh_Hans: icon_l_zh.svg - en_US: icon_l_en.svg -background: "#EFF1FE" -help: - title: - en_US: Get your API key from ZHIPU AI - zh_Hans: 从智谱 AI 获取 API Key - url: - en_US: https://open.bigmodel.cn/usercenter/apikeys -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: APIKey - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 APIKey - en_US: Enter your APIKey diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/__init__.py deleted file mode 100644 index fc71d64714bd96..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/__init__.py +++ /dev/null @@ -1,15 +0,0 @@ -from .__version__ import __version__ -from ._client import ZhipuAI -from .core import ( - APIAuthenticationError, - APIConnectionError, - APIInternalError, - APIReachLimitError, - APIRequestFailedError, - APIResponseError, - APIResponseValidationError, - APIServerFlowExceedError, - APIStatusError, - APITimeoutError, - ZhipuAIError, -) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/__version__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/__version__.py deleted file mode 100644 index 51f8c49ecb827d..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/__version__.py +++ /dev/null @@ -1 +0,0 @@ -__version__ = "v2.1.0" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/_client.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/_client.py deleted file mode 100644 index 705d371e628f08..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/_client.py +++ /dev/null @@ -1,82 +0,0 @@ -from __future__ import annotations - -import os -from collections.abc import Mapping -from typing import Union - -import httpx -from httpx import Timeout -from typing_extensions import override - -from . import api_resource -from .core import NOT_GIVEN, ZHIPUAI_DEFAULT_MAX_RETRIES, HttpClient, NotGiven, ZhipuAIError, _jwt_token - - -class ZhipuAI(HttpClient): - chat: api_resource.chat.Chat - api_key: str - _disable_token_cache: bool = True - - def __init__( - self, - *, - api_key: str | None = None, - base_url: str | httpx.URL | None = None, - timeout: Union[float, Timeout, None, NotGiven] = NOT_GIVEN, - max_retries: int = ZHIPUAI_DEFAULT_MAX_RETRIES, - http_client: httpx.Client | None = None, - custom_headers: Mapping[str, str] | None = None, - disable_token_cache: bool = True, - _strict_response_validation: bool = False, - ) -> None: - if api_key is None: - api_key = os.environ.get("ZHIPUAI_API_KEY") - if api_key is None: - raise ZhipuAIError("未提供api_key，请通过参数或环境变量提供") - self.api_key = api_key - self._disable_token_cache = disable_token_cache - - if base_url is None: - base_url = os.environ.get("ZHIPUAI_BASE_URL") - if base_url is None: - base_url = "https://open.bigmodel.cn/api/paas/v4" - from .__version__ import __version__ - - super().__init__( - version=__version__, - base_url=base_url, - max_retries=max_retries, - timeout=timeout, - custom_httpx_client=http_client, - custom_headers=custom_headers, - _strict_response_validation=_strict_response_validation, - ) - self.chat = api_resource.chat.Chat(self) - self.images = api_resource.images.Images(self) - self.embeddings = api_resource.embeddings.Embeddings(self) - self.files = api_resource.files.Files(self) - self.fine_tuning = api_resource.fine_tuning.FineTuning(self) - self.batches = api_resource.Batches(self) - self.knowledge = api_resource.Knowledge(self) - self.tools = api_resource.Tools(self) - self.videos = api_resource.Videos(self) - self.assistant = api_resource.Assistant(self) - - @property - @override - def auth_headers(self) -> dict[str, str]: - api_key = self.api_key - if self._disable_token_cache: - return {"Authorization": f"Bearer {api_key}"} - else: - return {"Authorization": f"Bearer {_jwt_token.generate_token(api_key)}"} - - def __del__(self) -> None: - if not hasattr(self, "_has_custom_http_client") or not hasattr(self, "close") or not hasattr(self, "_client"): - # if the '__init__' method raised an error, self would not have client attr - return - - if self._has_custom_http_client: - return - - self.close() diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/__init__.py deleted file mode 100644 index 4fe0719dde3e0b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/__init__.py +++ /dev/null @@ -1,34 +0,0 @@ -from .assistant import ( - Assistant, -) -from .batches import Batches -from .chat import ( - AsyncCompletions, - Chat, - Completions, -) -from .embeddings import Embeddings -from .files import Files, FilesWithRawResponse -from .fine_tuning import FineTuning -from .images import Images -from .knowledge import Knowledge -from .tools import Tools -from .videos import ( - Videos, -) - -__all__ = [ - "Videos", - "AsyncCompletions", - "Chat", - "Completions", - "Images", - "Embeddings", - "Files", - "FilesWithRawResponse", - "FineTuning", - "Batches", - "Knowledge", - "Tools", - "Assistant", -] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/assistant/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/assistant/__init__.py deleted file mode 100644 index ce619aa7f09222..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/assistant/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .assistant import Assistant - -__all__ = ["Assistant"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/assistant/assistant.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/assistant/assistant.py deleted file mode 100644 index f772340a82c4be..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/assistant/assistant.py +++ /dev/null @@ -1,122 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING, Optional - -import httpx - -from ...core import ( - NOT_GIVEN, - BaseAPI, - Body, - Headers, - NotGiven, - StreamResponse, - deepcopy_minimal, - make_request_options, - maybe_transform, -) -from ...types.assistant import AssistantCompletion -from ...types.assistant.assistant_conversation_resp import ConversationUsageListResp -from ...types.assistant.assistant_support_resp import AssistantSupportResp - -if TYPE_CHECKING: - from ..._client import ZhipuAI - -from ...types.assistant import assistant_conversation_params, assistant_create_params - -__all__ = ["Assistant"] - - -class Assistant(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def conversation( - self, - assistant_id: str, - model: str, - messages: list[assistant_create_params.ConversationMessage], - *, - stream: bool = True, - conversation_id: Optional[str] = None, - attachments: Optional[list[assistant_create_params.AssistantAttachments]] = None, - metadata: dict | None = None, - request_id: str = None, - user_id: str = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> StreamResponse[AssistantCompletion]: - body = deepcopy_minimal( - { - "assistant_id": assistant_id, - "model": model, - "messages": messages, - "stream": stream, - "conversation_id": conversation_id, - "attachments": attachments, - "metadata": metadata, - "request_id": request_id, - "user_id": user_id, - } - ) - return self._post( - "/assistant", - body=maybe_transform(body, assistant_create_params.AssistantParameters), - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=AssistantCompletion, - stream=stream or True, - stream_cls=StreamResponse[AssistantCompletion], - ) - - def query_support( - self, - *, - assistant_id_list: list[str] = None, - request_id: str = None, - user_id: str = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> AssistantSupportResp: - body = deepcopy_minimal( - { - "assistant_id_list": assistant_id_list, - "request_id": request_id, - "user_id": user_id, - } - ) - return self._post( - "/assistant/list", - body=body, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=AssistantSupportResp, - ) - - def query_conversation_usage( - self, - assistant_id: str, - page: int = 1, - page_size: int = 10, - *, - request_id: str = None, - user_id: str = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> ConversationUsageListResp: - body = deepcopy_minimal( - { - "assistant_id": assistant_id, - "page": page, - "page_size": page_size, - "request_id": request_id, - "user_id": user_id, - } - ) - return self._post( - "/assistant/conversation/list", - body=maybe_transform(body, assistant_conversation_params.ConversationParameters), - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=ConversationUsageListResp, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/batches.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/batches.py deleted file mode 100644 index ae2f2be85eb9b4..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/batches.py +++ /dev/null @@ -1,146 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING, Literal, Optional - -import httpx - -from ..core import NOT_GIVEN, BaseAPI, Body, Headers, NotGiven, make_request_options, maybe_transform -from ..core.pagination import SyncCursorPage -from ..types import batch_create_params, batch_list_params -from ..types.batch import Batch - -if TYPE_CHECKING: - from .._client import ZhipuAI - - -class Batches(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def create( - self, - *, - completion_window: str | None = None, - endpoint: Literal["/v1/chat/completions", "/v1/embeddings"], - input_file_id: str, - metadata: Optional[dict[str, str]] | NotGiven = NOT_GIVEN, - auto_delete_input_file: bool = True, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> Batch: - return self._post( - "/batches", - body=maybe_transform( - { - "completion_window": completion_window, - "endpoint": endpoint, - "input_file_id": input_file_id, - "metadata": metadata, - "auto_delete_input_file": auto_delete_input_file, - }, - batch_create_params.BatchCreateParams, - ), - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=Batch, - ) - - def retrieve( - self, - batch_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> Batch: - """ - Retrieves a batch. - - Args: - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - """ - if not batch_id: - raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}") - return self._get( - f"/batches/{batch_id}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=Batch, - ) - - def list( - self, - *, - after: str | NotGiven = NOT_GIVEN, - limit: int | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> SyncCursorPage[Batch]: - """List your organization's batches. - - Args: - after: A cursor for use in pagination. - - `after` is an object ID that defines your place - in the list. For instance, if you make a list request and receive 100 objects, - ending with obj_foo, your subsequent call can include after=obj_foo in order to - fetch the next page of the list. - - limit: A limit on the number of objects to be returned. Limit can range between 1 and - 100, and the default is 20. - - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - """ - return self._get_api_list( - "/batches", - page=SyncCursorPage[Batch], - options=make_request_options( - extra_headers=extra_headers, - extra_body=extra_body, - timeout=timeout, - query=maybe_transform( - { - "after": after, - "limit": limit, - }, - batch_list_params.BatchListParams, - ), - ), - model=Batch, - ) - - def cancel( - self, - batch_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> Batch: - """ - Cancels an in-progress batch. - - Args: - batch_id: The ID of the batch to cancel. - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - - """ - if not batch_id: - raise ValueError(f"Expected a non-empty value for `batch_id` but received {batch_id!r}") - return self._post( - f"/batches/{batch_id}/cancel", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=Batch, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/__init__.py deleted file mode 100644 index 5cd8dc6f339a60..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from .async_completions import AsyncCompletions -from .chat import Chat -from .completions import Completions - -__all__ = ["AsyncCompletions", "Chat", "Completions"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/async_completions.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/async_completions.py deleted file mode 100644 index 05510a3ec421d0..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/async_completions.py +++ /dev/null @@ -1,115 +0,0 @@ -from __future__ import annotations - -import logging -from typing import TYPE_CHECKING, Literal, Optional, Union - -import httpx - -from ...core import ( - NOT_GIVEN, - BaseAPI, - Body, - Headers, - NotGiven, - drop_prefix_image_data, - make_request_options, - maybe_transform, -) -from ...types.chat.async_chat_completion import AsyncCompletion, AsyncTaskStatus -from ...types.chat.code_geex import code_geex_params -from ...types.sensitive_word_check import SensitiveWordCheckRequest - -logger = logging.getLogger(__name__) - -if TYPE_CHECKING: - from ..._client import ZhipuAI - - -class AsyncCompletions(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def create( - self, - *, - model: str, - request_id: Optional[str] | NotGiven = NOT_GIVEN, - user_id: Optional[str] | NotGiven = NOT_GIVEN, - do_sample: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN, - temperature: Optional[float] | NotGiven = NOT_GIVEN, - top_p: Optional[float] | NotGiven = NOT_GIVEN, - max_tokens: int | NotGiven = NOT_GIVEN, - seed: int | NotGiven = NOT_GIVEN, - messages: Union[str, list[str], list[int], list[list[int]], None], - stop: Optional[Union[str, list[str], None]] | NotGiven = NOT_GIVEN, - sensitive_word_check: Optional[SensitiveWordCheckRequest] | NotGiven = NOT_GIVEN, - tools: Optional[object] | NotGiven = NOT_GIVEN, - tool_choice: str | NotGiven = NOT_GIVEN, - meta: Optional[dict[str, str]] | NotGiven = NOT_GIVEN, - extra: Optional[code_geex_params.CodeGeexExtra] | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> AsyncTaskStatus: - _cast_type = AsyncTaskStatus - logger.debug(f"temperature:{temperature}, top_p:{top_p}") - if temperature is not None and temperature != NOT_GIVEN: - if temperature <= 0: - do_sample = False - temperature = 0.01 - # logger.warning("temperature:取值范围是：(0.0, 1.0) 开区间，do_sample重写为:false（参数top_p temperature不生效）") # noqa: E501 - if temperature >= 1: - temperature = 0.99 - # logger.warning("temperature:取值范围是：(0.0, 1.0) 开区间") - if top_p is not None and top_p != NOT_GIVEN: - if top_p >= 1: - top_p = 0.99 - # logger.warning("top_p:取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1") - if top_p <= 0: - top_p = 0.01 - # logger.warning("top_p:取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1") - - logger.debug(f"temperature:{temperature}, top_p:{top_p}") - if isinstance(messages, list): - for item in messages: - if item.get("content"): - item["content"] = drop_prefix_image_data(item["content"]) - - body = { - "model": model, - "request_id": request_id, - "user_id": user_id, - "temperature": temperature, - "top_p": top_p, - "do_sample": do_sample, - "max_tokens": max_tokens, - "seed": seed, - "messages": messages, - "stop": stop, - "sensitive_word_check": sensitive_word_check, - "tools": tools, - "tool_choice": tool_choice, - "meta": meta, - "extra": maybe_transform(extra, code_geex_params.CodeGeexExtra), - } - return self._post( - "/async/chat/completions", - body=body, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=_cast_type, - stream=False, - ) - - def retrieve_completion_result( - self, - id: str, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> Union[AsyncCompletion, AsyncTaskStatus]: - _cast_type = Union[AsyncCompletion, AsyncTaskStatus] - return self._get( - path=f"/async-result/{id}", - cast_type=_cast_type, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/chat.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/chat.py deleted file mode 100644 index b3cc46566c7bf3..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/chat.py +++ /dev/null @@ -1,18 +0,0 @@ -from typing import TYPE_CHECKING - -from ...core import BaseAPI, cached_property -from .async_completions import AsyncCompletions -from .completions import Completions - -if TYPE_CHECKING: - pass - - -class Chat(BaseAPI): - @cached_property - def completions(self) -> Completions: - return Completions(self._client) - - @cached_property - def asyncCompletions(self) -> AsyncCompletions: # noqa: N802 - return AsyncCompletions(self._client) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/completions.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/completions.py deleted file mode 100644 index 8e5bb454e6ce7e..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/chat/completions.py +++ /dev/null @@ -1,108 +0,0 @@ -from __future__ import annotations - -import logging -from typing import TYPE_CHECKING, Literal, Optional, Union - -import httpx - -from ...core import ( - NOT_GIVEN, - BaseAPI, - Body, - Headers, - NotGiven, - StreamResponse, - deepcopy_minimal, - drop_prefix_image_data, - make_request_options, - maybe_transform, -) -from ...types.chat.chat_completion import Completion -from ...types.chat.chat_completion_chunk import ChatCompletionChunk -from ...types.chat.code_geex import code_geex_params -from ...types.sensitive_word_check import SensitiveWordCheckRequest - -logger = logging.getLogger(__name__) - -if TYPE_CHECKING: - from ..._client import ZhipuAI - - -class Completions(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def create( - self, - *, - model: str, - request_id: Optional[str] | NotGiven = NOT_GIVEN, - user_id: Optional[str] | NotGiven = NOT_GIVEN, - do_sample: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN, - stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN, - temperature: Optional[float] | NotGiven = NOT_GIVEN, - top_p: Optional[float] | NotGiven = NOT_GIVEN, - max_tokens: int | NotGiven = NOT_GIVEN, - seed: int | NotGiven = NOT_GIVEN, - messages: Union[str, list[str], list[int], object, None], - stop: Optional[Union[str, list[str], None]] | NotGiven = NOT_GIVEN, - sensitive_word_check: Optional[SensitiveWordCheckRequest] | NotGiven = NOT_GIVEN, - tools: Optional[object] | NotGiven = NOT_GIVEN, - tool_choice: str | NotGiven = NOT_GIVEN, - meta: Optional[dict[str, str]] | NotGiven = NOT_GIVEN, - extra: Optional[code_geex_params.CodeGeexExtra] | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> Completion | StreamResponse[ChatCompletionChunk]: - logger.debug(f"temperature:{temperature}, top_p:{top_p}") - if temperature is not None and temperature != NOT_GIVEN: - if temperature <= 0: - do_sample = False - temperature = 0.01 - # logger.warning("temperature:取值范围是：(0.0, 1.0) 开区间，do_sample重写为:false（参数top_p temperature不生效）") # noqa: E501 - if temperature >= 1: - temperature = 0.99 - # logger.warning("temperature:取值范围是：(0.0, 1.0) 开区间") - if top_p is not None and top_p != NOT_GIVEN: - if top_p >= 1: - top_p = 0.99 - # logger.warning("top_p:取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1") - if top_p <= 0: - top_p = 0.01 - # logger.warning("top_p:取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1") - - logger.debug(f"temperature:{temperature}, top_p:{top_p}") - if isinstance(messages, list): - for item in messages: - if item.get("content"): - item["content"] = drop_prefix_image_data(item["content"]) - - body = deepcopy_minimal( - { - "model": model, - "request_id": request_id, - "user_id": user_id, - "temperature": temperature, - "top_p": top_p, - "do_sample": do_sample, - "max_tokens": max_tokens, - "seed": seed, - "messages": messages, - "stop": stop, - "sensitive_word_check": sensitive_word_check, - "stream": stream, - "tools": tools, - "tool_choice": tool_choice, - "meta": meta, - "extra": maybe_transform(extra, code_geex_params.CodeGeexExtra), - } - ) - return self._post( - "/chat/completions", - body=body, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=Completion, - stream=stream or False, - stream_cls=StreamResponse[ChatCompletionChunk], - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/embeddings.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/embeddings.py deleted file mode 100644 index 4b4baef9421ba6..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/embeddings.py +++ /dev/null @@ -1,50 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING, Optional, Union - -import httpx - -from ..core import NOT_GIVEN, BaseAPI, Body, Headers, NotGiven, make_request_options -from ..types.embeddings import EmbeddingsResponded - -if TYPE_CHECKING: - from .._client import ZhipuAI - - -class Embeddings(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def create( - self, - *, - input: Union[str, list[str], list[int], list[list[int]]], - model: Union[str], - dimensions: Union[int] | NotGiven = NOT_GIVEN, - encoding_format: str | NotGiven = NOT_GIVEN, - user: str | NotGiven = NOT_GIVEN, - request_id: Optional[str] | NotGiven = NOT_GIVEN, - sensitive_word_check: Optional[object] | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - disable_strict_validation: Optional[bool] | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> EmbeddingsResponded: - _cast_type = EmbeddingsResponded - if disable_strict_validation: - _cast_type = object - return self._post( - "/embeddings", - body={ - "input": input, - "model": model, - "dimensions": dimensions, - "encoding_format": encoding_format, - "user": user, - "request_id": request_id, - "sensitive_word_check": sensitive_word_check, - }, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=_cast_type, - stream=False, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/files.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/files.py deleted file mode 100644 index ba9de75b7ef092..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/files.py +++ /dev/null @@ -1,194 +0,0 @@ -from __future__ import annotations - -from collections.abc import Mapping -from typing import TYPE_CHECKING, Literal, cast - -import httpx - -from ..core import ( - NOT_GIVEN, - BaseAPI, - Body, - FileTypes, - Headers, - NotGiven, - _legacy_binary_response, - _legacy_response, - deepcopy_minimal, - extract_files, - make_request_options, - maybe_transform, -) -from ..types.files import FileDeleted, FileObject, ListOfFileObject, UploadDetail, file_create_params - -if TYPE_CHECKING: - from .._client import ZhipuAI - -__all__ = ["Files", "FilesWithRawResponse"] - - -class Files(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def create( - self, - *, - file: FileTypes = None, - upload_detail: list[UploadDetail] = None, - purpose: Literal["fine-tune", "retrieval", "batch"], - knowledge_id: str = None, - sentence_size: int = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> FileObject: - if not file and not upload_detail: - raise ValueError("At least one of `file` and `upload_detail` must be provided.") - body = deepcopy_minimal( - { - "file": file, - "upload_detail": upload_detail, - "purpose": purpose, - "knowledge_id": knowledge_id, - "sentence_size": sentence_size, - } - ) - files = extract_files(cast(Mapping[str, object], body), paths=[["file"]]) - if files: - # It should be noted that the actual Content-Type header that will be - # sent to the server will contain a `boundary` parameter, e.g. - # multipart/form-data; boundary=---abc-- - extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})} - return self._post( - "/files", - body=maybe_transform(body, file_create_params.FileCreateParams), - files=files, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=FileObject, - ) - - # def retrieve( - # self, - # file_id: str, - # *, - # extra_headers: Headers | None = None, - # extra_body: Body | None = None, - # timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - # ) -> FileObject: - # """ - # Returns information about a specific file. - # - # Args: - # file_id: The ID of the file to retrieve information about - # extra_headers: Send extra headers - # - # extra_body: Add additional JSON properties to the request - # - # timeout: Override the client-level default timeout for this request, in seconds - # """ - # if not file_id: - # raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}") - # return self._get( - # f"/files/{file_id}", - # options=make_request_options( - # extra_headers=extra_headers, extra_body=extra_body, timeout=timeout - # ), - # cast_type=FileObject, - # ) - - def list( - self, - *, - purpose: str | NotGiven = NOT_GIVEN, - limit: int | NotGiven = NOT_GIVEN, - after: str | NotGiven = NOT_GIVEN, - order: str | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> ListOfFileObject: - return self._get( - "/files", - cast_type=ListOfFileObject, - options=make_request_options( - extra_headers=extra_headers, - extra_body=extra_body, - timeout=timeout, - query={ - "purpose": purpose, - "limit": limit, - "after": after, - "order": order, - }, - ), - ) - - def delete( - self, - file_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> FileDeleted: - """ - Delete a file. - - Args: - file_id: The ID of the file to delete - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - """ - if not file_id: - raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}") - return self._delete( - f"/files/{file_id}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=FileDeleted, - ) - - def content( - self, - file_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> _legacy_response.HttpxBinaryResponseContent: - """ - Returns the contents of the specified file. - - Args: - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - """ - if not file_id: - raise ValueError(f"Expected a non-empty value for `file_id` but received {file_id!r}") - extra_headers = {"Accept": "application/binary", **(extra_headers or {})} - return self._get( - f"/files/{file_id}/content", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=_legacy_binary_response.HttpxBinaryResponseContent, - ) - - -class FilesWithRawResponse: - def __init__(self, files: Files) -> None: - self._files = files - - self.create = _legacy_response.to_raw_response_wrapper( - files.create, - ) - self.list = _legacy_response.to_raw_response_wrapper( - files.list, - ) - self.content = _legacy_response.to_raw_response_wrapper( - files.content, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/__init__.py deleted file mode 100644 index 7c309b83416803..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from .fine_tuning import FineTuning -from .jobs import Jobs -from .models import FineTunedModels - -__all__ = ["Jobs", "FineTunedModels", "FineTuning"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/fine_tuning.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/fine_tuning.py deleted file mode 100644 index 8670f7de00df84..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/fine_tuning.py +++ /dev/null @@ -1,18 +0,0 @@ -from typing import TYPE_CHECKING - -from ...core import BaseAPI, cached_property -from .jobs import Jobs -from .models import FineTunedModels - -if TYPE_CHECKING: - pass - - -class FineTuning(BaseAPI): - @cached_property - def jobs(self) -> Jobs: - return Jobs(self._client) - - @cached_property - def models(self) -> FineTunedModels: - return FineTunedModels(self._client) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/jobs/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/jobs/__init__.py deleted file mode 100644 index 40777a153f272a..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/jobs/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .jobs import Jobs - -__all__ = ["Jobs"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/jobs/jobs.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/jobs/jobs.py deleted file mode 100644 index 8b038cadc06407..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/jobs/jobs.py +++ /dev/null @@ -1,152 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING, Optional - -import httpx - -from ....core import ( - NOT_GIVEN, - BaseAPI, - Body, - Headers, - NotGiven, - make_request_options, -) -from ....types.fine_tuning import ( - FineTuningJob, - FineTuningJobEvent, - ListOfFineTuningJob, - job_create_params, -) - -if TYPE_CHECKING: - from ...._client import ZhipuAI - -__all__ = ["Jobs"] - - -class Jobs(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def create( - self, - *, - model: str, - training_file: str, - hyperparameters: job_create_params.Hyperparameters | NotGiven = NOT_GIVEN, - suffix: Optional[str] | NotGiven = NOT_GIVEN, - request_id: Optional[str] | NotGiven = NOT_GIVEN, - validation_file: Optional[str] | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> FineTuningJob: - return self._post( - "/fine_tuning/jobs", - body={ - "model": model, - "training_file": training_file, - "hyperparameters": hyperparameters, - "suffix": suffix, - "validation_file": validation_file, - "request_id": request_id, - }, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=FineTuningJob, - ) - - def retrieve( - self, - fine_tuning_job_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> FineTuningJob: - return self._get( - f"/fine_tuning/jobs/{fine_tuning_job_id}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=FineTuningJob, - ) - - def list( - self, - *, - after: str | NotGiven = NOT_GIVEN, - limit: int | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> ListOfFineTuningJob: - return self._get( - "/fine_tuning/jobs", - cast_type=ListOfFineTuningJob, - options=make_request_options( - extra_headers=extra_headers, - extra_body=extra_body, - timeout=timeout, - query={ - "after": after, - "limit": limit, - }, - ), - ) - - def cancel( - self, - fine_tuning_job_id: str, - *, - # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # noqa: E501 - # The extra values given here take precedence over values defined on the client or passed to this method. - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> FineTuningJob: - if not fine_tuning_job_id: - raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}") - return self._post( - f"/fine_tuning/jobs/{fine_tuning_job_id}/cancel", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=FineTuningJob, - ) - - def list_events( - self, - fine_tuning_job_id: str, - *, - after: str | NotGiven = NOT_GIVEN, - limit: int | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> FineTuningJobEvent: - return self._get( - f"/fine_tuning/jobs/{fine_tuning_job_id}/events", - cast_type=FineTuningJobEvent, - options=make_request_options( - extra_headers=extra_headers, - extra_body=extra_body, - timeout=timeout, - query={ - "after": after, - "limit": limit, - }, - ), - ) - - def delete( - self, - fine_tuning_job_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> FineTuningJob: - if not fine_tuning_job_id: - raise ValueError(f"Expected a non-empty value for `fine_tuning_job_id` but received {fine_tuning_job_id!r}") - return self._delete( - f"/fine_tuning/jobs/{fine_tuning_job_id}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=FineTuningJob, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/models/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/models/__init__.py deleted file mode 100644 index d832635bafbc6f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/models/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .fine_tuned_models import FineTunedModels - -__all__ = ["FineTunedModels"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/models/fine_tuned_models.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/models/fine_tuned_models.py deleted file mode 100644 index 29c023e3b1cd5a..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/fine_tuning/models/fine_tuned_models.py +++ /dev/null @@ -1,41 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING - -import httpx - -from ....core import ( - NOT_GIVEN, - BaseAPI, - Body, - Headers, - NotGiven, - make_request_options, -) -from ....types.fine_tuning.models import FineTunedModelsStatus - -if TYPE_CHECKING: - from ...._client import ZhipuAI - -__all__ = ["FineTunedModels"] - - -class FineTunedModels(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def delete( - self, - fine_tuned_model: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> FineTunedModelsStatus: - if not fine_tuned_model: - raise ValueError(f"Expected a non-empty value for `fine_tuned_model` but received {fine_tuned_model!r}") - return self._delete( - f"fine_tuning/fine_tuned_models/{fine_tuned_model}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=FineTunedModelsStatus, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/images.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/images.py deleted file mode 100644 index 8ad411913fa115..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/images.py +++ /dev/null @@ -1,59 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING, Optional - -import httpx - -from ..core import NOT_GIVEN, BaseAPI, Body, Headers, NotGiven, make_request_options -from ..types.image import ImagesResponded -from ..types.sensitive_word_check import SensitiveWordCheckRequest - -if TYPE_CHECKING: - from .._client import ZhipuAI - - -class Images(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def generations( - self, - *, - prompt: str, - model: str | NotGiven = NOT_GIVEN, - n: Optional[int] | NotGiven = NOT_GIVEN, - quality: Optional[str] | NotGiven = NOT_GIVEN, - response_format: Optional[str] | NotGiven = NOT_GIVEN, - size: Optional[str] | NotGiven = NOT_GIVEN, - style: Optional[str] | NotGiven = NOT_GIVEN, - sensitive_word_check: Optional[SensitiveWordCheckRequest] | NotGiven = NOT_GIVEN, - user: str | NotGiven = NOT_GIVEN, - request_id: Optional[str] | NotGiven = NOT_GIVEN, - user_id: Optional[str] | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - disable_strict_validation: Optional[bool] | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> ImagesResponded: - _cast_type = ImagesResponded - if disable_strict_validation: - _cast_type = object - return self._post( - "/images/generations", - body={ - "prompt": prompt, - "model": model, - "n": n, - "quality": quality, - "response_format": response_format, - "sensitive_word_check": sensitive_word_check, - "size": size, - "style": style, - "user": user, - "user_id": user_id, - "request_id": request_id, - }, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=_cast_type, - stream=False, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/__init__.py deleted file mode 100644 index 5a67d743c35b9b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .knowledge import Knowledge - -__all__ = ["Knowledge"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/document/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/document/__init__.py deleted file mode 100644 index fd289e2232b955..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/document/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .document import Document - -__all__ = ["Document"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/document/document.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/document/document.py deleted file mode 100644 index 2c4066d8930342..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/document/document.py +++ /dev/null @@ -1,217 +0,0 @@ -from __future__ import annotations - -from collections.abc import Mapping -from typing import TYPE_CHECKING, Literal, Optional, cast - -import httpx - -from ....core import ( - NOT_GIVEN, - BaseAPI, - Body, - FileTypes, - Headers, - NotGiven, - deepcopy_minimal, - extract_files, - make_request_options, - maybe_transform, -) -from ....types.files import UploadDetail, file_create_params -from ....types.knowledge.document import DocumentData, DocumentObject, document_edit_params, document_list_params -from ....types.knowledge.document.document_list_resp import DocumentPage - -if TYPE_CHECKING: - from ...._client import ZhipuAI - -__all__ = ["Document"] - - -class Document(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def create( - self, - *, - file: FileTypes = None, - custom_separator: Optional[list[str]] = None, - upload_detail: list[UploadDetail] = None, - purpose: Literal["retrieval"], - knowledge_id: str = None, - sentence_size: int = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> DocumentObject: - if not file and not upload_detail: - raise ValueError("At least one of `file` and `upload_detail` must be provided.") - body = deepcopy_minimal( - { - "file": file, - "upload_detail": upload_detail, - "purpose": purpose, - "custom_separator": custom_separator, - "knowledge_id": knowledge_id, - "sentence_size": sentence_size, - } - ) - files = extract_files(cast(Mapping[str, object], body), paths=[["file"]]) - if files: - # It should be noted that the actual Content-Type header that will be - # sent to the server will contain a `boundary` parameter, e.g. - # multipart/form-data; boundary=---abc-- - extra_headers = {"Content-Type": "multipart/form-data", **(extra_headers or {})} - return self._post( - "/files", - body=maybe_transform(body, file_create_params.FileCreateParams), - files=files, - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=DocumentObject, - ) - - def edit( - self, - document_id: str, - knowledge_type: str, - *, - custom_separator: Optional[list[str]] = None, - sentence_size: Optional[int] = None, - callback_url: Optional[str] = None, - callback_header: Optional[dict[str, str]] = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> httpx.Response: - """ - - Args: - document_id: 知识id - knowledge_type: 知识类型: - 1:文章知识: 支持pdf,url,docx - 2.问答知识-文档: 支持pdf,url,docx - 3.问答知识-表格: 支持xlsx - 4.商品库-表格: 支持xlsx - 5.自定义: 支持pdf,url,docx - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - :param knowledge_type: - :param document_id: - :param timeout: - :param extra_body: - :param callback_header: - :param sentence_size: - :param extra_headers: - :param callback_url: - :param custom_separator: - """ - if not document_id: - raise ValueError(f"Expected a non-empty value for `document_id` but received {document_id!r}") - - body = deepcopy_minimal( - { - "id": document_id, - "knowledge_type": knowledge_type, - "custom_separator": custom_separator, - "sentence_size": sentence_size, - "callback_url": callback_url, - "callback_header": callback_header, - } - ) - - return self._put( - f"/document/{document_id}", - body=maybe_transform(body, document_edit_params.DocumentEditParams), - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=httpx.Response, - ) - - def list( - self, - knowledge_id: str, - *, - purpose: str | NotGiven = NOT_GIVEN, - page: str | NotGiven = NOT_GIVEN, - limit: str | NotGiven = NOT_GIVEN, - order: Literal["desc", "asc"] | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> DocumentPage: - return self._get( - "/files", - options=make_request_options( - extra_headers=extra_headers, - extra_body=extra_body, - timeout=timeout, - query=maybe_transform( - { - "knowledge_id": knowledge_id, - "purpose": purpose, - "page": page, - "limit": limit, - "order": order, - }, - document_list_params.DocumentListParams, - ), - ), - cast_type=DocumentPage, - ) - - def delete( - self, - document_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> httpx.Response: - """ - Delete a file. - - Args: - - document_id: 知识id - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - """ - if not document_id: - raise ValueError(f"Expected a non-empty value for `document_id` but received {document_id!r}") - - return self._delete( - f"/document/{document_id}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=httpx.Response, - ) - - def retrieve( - self, - document_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> DocumentData: - """ - - Args: - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - """ - if not document_id: - raise ValueError(f"Expected a non-empty value for `document_id` but received {document_id!r}") - - return self._get( - f"/document/{document_id}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=DocumentData, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/knowledge.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/knowledge.py deleted file mode 100644 index fea4c73ac997c3..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/knowledge.py +++ /dev/null @@ -1,173 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING, Literal, Optional - -import httpx - -from ...core import ( - NOT_GIVEN, - BaseAPI, - Body, - Headers, - NotGiven, - cached_property, - deepcopy_minimal, - make_request_options, - maybe_transform, -) -from ...types.knowledge import KnowledgeInfo, KnowledgeUsed, knowledge_create_params, knowledge_list_params -from ...types.knowledge.knowledge_list_resp import KnowledgePage -from .document import Document - -if TYPE_CHECKING: - from ..._client import ZhipuAI - -__all__ = ["Knowledge"] - - -class Knowledge(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - @cached_property - def document(self) -> Document: - return Document(self._client) - - def create( - self, - embedding_id: int, - name: str, - *, - customer_identifier: Optional[str] = None, - description: Optional[str] = None, - background: Optional[Literal["blue", "red", "orange", "purple", "sky"]] = None, - icon: Optional[Literal["question", "book", "seal", "wrench", "tag", "horn", "house"]] = None, - bucket_id: Optional[str] = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> KnowledgeInfo: - body = deepcopy_minimal( - { - "embedding_id": embedding_id, - "name": name, - "customer_identifier": customer_identifier, - "description": description, - "background": background, - "icon": icon, - "bucket_id": bucket_id, - } - ) - return self._post( - "/knowledge", - body=maybe_transform(body, knowledge_create_params.KnowledgeBaseParams), - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=KnowledgeInfo, - ) - - def modify( - self, - knowledge_id: str, - embedding_id: int, - *, - name: str, - description: Optional[str] = None, - background: Optional[Literal["blue", "red", "orange", "purple", "sky"]] = None, - icon: Optional[Literal["question", "book", "seal", "wrench", "tag", "horn", "house"]] = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> httpx.Response: - body = deepcopy_minimal( - { - "id": knowledge_id, - "embedding_id": embedding_id, - "name": name, - "description": description, - "background": background, - "icon": icon, - } - ) - return self._put( - f"/knowledge/{knowledge_id}", - body=maybe_transform(body, knowledge_create_params.KnowledgeBaseParams), - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=httpx.Response, - ) - - def query( - self, - *, - page: int | NotGiven = 1, - size: int | NotGiven = 10, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> KnowledgePage: - return self._get( - "/knowledge", - options=make_request_options( - extra_headers=extra_headers, - extra_body=extra_body, - timeout=timeout, - query=maybe_transform( - { - "page": page, - "size": size, - }, - knowledge_list_params.KnowledgeListParams, - ), - ), - cast_type=KnowledgePage, - ) - - def delete( - self, - knowledge_id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> httpx.Response: - """ - Delete a file. - - Args: - knowledge_id: 知识库ID - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - """ - if not knowledge_id: - raise ValueError("Expected a non-empty value for `knowledge_id`") - - return self._delete( - f"/knowledge/{knowledge_id}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=httpx.Response, - ) - - def used( - self, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> KnowledgeUsed: - """ - Returns the contents of the specified file. - - Args: - extra_headers: Send extra headers - - extra_body: Add additional JSON properties to the request - - timeout: Override the client-level default timeout for this request, in seconds - """ - return self._get( - "/knowledge/capacity", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=KnowledgeUsed, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/tools/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/tools/__init__.py deleted file mode 100644 index 43e4e37da1779f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/tools/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .tools import Tools - -__all__ = ["Tools"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/tools/tools.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/tools/tools.py deleted file mode 100644 index 3c3a630aff47d7..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/tools/tools.py +++ /dev/null @@ -1,65 +0,0 @@ -from __future__ import annotations - -import logging -from typing import TYPE_CHECKING, Literal, Optional, Union - -import httpx - -from ...core import ( - NOT_GIVEN, - BaseAPI, - Body, - Headers, - NotGiven, - StreamResponse, - deepcopy_minimal, - make_request_options, - maybe_transform, -) -from ...types.tools import WebSearch, WebSearchChunk, tools_web_search_params - -logger = logging.getLogger(__name__) - -if TYPE_CHECKING: - from ..._client import ZhipuAI - -__all__ = ["Tools"] - - -class Tools(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def web_search( - self, - *, - model: str, - request_id: Optional[str] | NotGiven = NOT_GIVEN, - stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN, - messages: Union[str, list[str], list[int], object, None], - scope: Optional[str] | NotGiven = NOT_GIVEN, - location: Optional[str] | NotGiven = NOT_GIVEN, - recent_days: Optional[int] | NotGiven = NOT_GIVEN, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> WebSearch | StreamResponse[WebSearchChunk]: - body = deepcopy_minimal( - { - "model": model, - "request_id": request_id, - "messages": messages, - "stream": stream, - "scope": scope, - "location": location, - "recent_days": recent_days, - } - ) - return self._post( - "/tools", - body=maybe_transform(body, tools_web_search_params.WebSearchParams), - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=WebSearch, - stream=stream or False, - stream_cls=StreamResponse[WebSearchChunk], - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/videos/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/videos/__init__.py deleted file mode 100644 index 6b0f99ed09efe3..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/videos/__init__.py +++ /dev/null @@ -1,7 +0,0 @@ -from .videos import ( - Videos, -) - -__all__ = [ - "Videos", -] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/videos/videos.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/videos/videos.py deleted file mode 100644 index f1f1c08036a660..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/videos/videos.py +++ /dev/null @@ -1,77 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING, Optional - -import httpx - -from ...core import ( - NOT_GIVEN, - BaseAPI, - Body, - Headers, - NotGiven, - deepcopy_minimal, - make_request_options, - maybe_transform, -) -from ...types.sensitive_word_check import SensitiveWordCheckRequest -from ...types.video import VideoObject, video_create_params - -if TYPE_CHECKING: - from ..._client import ZhipuAI - -__all__ = ["Videos"] - - -class Videos(BaseAPI): - def __init__(self, client: ZhipuAI) -> None: - super().__init__(client) - - def generations( - self, - model: str, - *, - prompt: str = None, - image_url: str = None, - sensitive_word_check: Optional[SensitiveWordCheckRequest] | NotGiven = NOT_GIVEN, - request_id: str = None, - user_id: str = None, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> VideoObject: - if not model and not model: - raise ValueError("At least one of `model` and `prompt` must be provided.") - body = deepcopy_minimal( - { - "model": model, - "prompt": prompt, - "image_url": image_url, - "sensitive_word_check": sensitive_word_check, - "request_id": request_id, - "user_id": user_id, - } - ) - return self._post( - "/videos/generations", - body=maybe_transform(body, video_create_params.VideoCreateParams), - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=VideoObject, - ) - - def retrieve_videos_result( - self, - id: str, - *, - extra_headers: Headers | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - ) -> VideoObject: - if not id: - raise ValueError("At least one of `id` must be provided.") - - return self._get( - f"/async-result/{id}", - options=make_request_options(extra_headers=extra_headers, extra_body=extra_body, timeout=timeout), - cast_type=VideoObject, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/__init__.py deleted file mode 100644 index 3d6466d279861a..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/__init__.py +++ /dev/null @@ -1,108 +0,0 @@ -from ._base_api import BaseAPI -from ._base_compat import ( - PYDANTIC_V2, - ConfigDict, - GenericModel, - cached_property, - field_get_default, - get_args, - get_model_config, - get_model_fields, - get_origin, - is_literal_type, - is_union, - parse_obj, -) -from ._base_models import BaseModel, construct_type -from ._base_type import ( - NOT_GIVEN, - Body, - FileTypes, - Headers, - IncEx, - ModelT, - NotGiven, - Query, -) -from ._constants import ( - ZHIPUAI_DEFAULT_LIMITS, - ZHIPUAI_DEFAULT_MAX_RETRIES, - ZHIPUAI_DEFAULT_TIMEOUT, -) -from ._errors import ( - APIAuthenticationError, - APIConnectionError, - APIInternalError, - APIReachLimitError, - APIRequestFailedError, - APIResponseError, - APIResponseValidationError, - APIServerFlowExceedError, - APIStatusError, - APITimeoutError, - ZhipuAIError, -) -from ._files import is_file_content -from ._http_client import HttpClient, make_request_options -from ._sse_client import StreamResponse -from ._utils import ( - deepcopy_minimal, - drop_prefix_image_data, - extract_files, - is_given, - is_list, - is_mapping, - maybe_transform, - parse_date, - parse_datetime, -) - -__all__ = [ - "BaseModel", - "construct_type", - "BaseAPI", - "NOT_GIVEN", - "Headers", - "NotGiven", - "Body", - "IncEx", - "ModelT", - "Query", - "FileTypes", - "PYDANTIC_V2", - "ConfigDict", - "GenericModel", - "get_args", - "is_union", - "parse_obj", - "get_origin", - "is_literal_type", - "get_model_config", - "get_model_fields", - "field_get_default", - "is_file_content", - "ZhipuAIError", - "APIStatusError", - "APIRequestFailedError", - "APIAuthenticationError", - "APIReachLimitError", - "APIInternalError", - "APIServerFlowExceedError", - "APIResponseError", - "APIResponseValidationError", - "APITimeoutError", - "make_request_options", - "HttpClient", - "ZHIPUAI_DEFAULT_TIMEOUT", - "ZHIPUAI_DEFAULT_MAX_RETRIES", - "ZHIPUAI_DEFAULT_LIMITS", - "is_list", - "is_mapping", - "parse_date", - "parse_datetime", - "is_given", - "maybe_transform", - "deepcopy_minimal", - "extract_files", - "StreamResponse", -] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_api.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_api.py deleted file mode 100644 index 3592ea6bacd170..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_api.py +++ /dev/null @@ -1,19 +0,0 @@ -from __future__ import annotations - -from typing import TYPE_CHECKING - -if TYPE_CHECKING: - from .._client import ZhipuAI - - -class BaseAPI: - _client: ZhipuAI - - def __init__(self, client: ZhipuAI) -> None: - self._client = client - self._delete = client.delete - self._get = client.get - self._post = client.post - self._put = client.put - self._patch = client.patch - self._get_api_list = client.get_api_list diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_compat.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_compat.py deleted file mode 100644 index 92a5d683be6732..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_compat.py +++ /dev/null @@ -1,209 +0,0 @@ -from __future__ import annotations - -from collections.abc import Callable -from datetime import date, datetime -from typing import TYPE_CHECKING, Any, Generic, TypeVar, Union, cast, overload - -import pydantic -from pydantic.fields import FieldInfo -from typing_extensions import Self - -from ._base_type import StrBytesIntFloat - -_T = TypeVar("_T") -_ModelT = TypeVar("_ModelT", bound=pydantic.BaseModel) - -# --------------- Pydantic v2 compatibility --------------- - -# Pyright incorrectly reports some of our functions as overriding a method when they don't -# pyright: reportIncompatibleMethodOverride=false - -PYDANTIC_V2 = pydantic.VERSION.startswith("2.") - -# v1 re-exports -if TYPE_CHECKING: - - def parse_date(value: date | StrBytesIntFloat) -> date: ... - - def parse_datetime(value: Union[datetime, StrBytesIntFloat]) -> datetime: ... - - def get_args(t: type[Any]) -> tuple[Any, ...]: ... - - def is_union(tp: type[Any] | None) -> bool: ... - - def get_origin(t: type[Any]) -> type[Any] | None: ... - - def is_literal_type(type_: type[Any]) -> bool: ... - - def is_typeddict(type_: type[Any]) -> bool: ... - -else: - if PYDANTIC_V2: - from pydantic.v1.typing import ( # noqa: I001 - get_args as get_args, # noqa: PLC0414 - is_union as is_union, # noqa: PLC0414 - get_origin as get_origin, # noqa: PLC0414 - is_typeddict as is_typeddict, # noqa: PLC0414 - is_literal_type as is_literal_type, # noqa: PLC0414 - ) - from pydantic.v1.datetime_parse import parse_date as parse_date, parse_datetime as parse_datetime # noqa: PLC0414 - else: - from pydantic.typing import ( # noqa: I001 - get_args as get_args, # noqa: PLC0414 - is_union as is_union, # noqa: PLC0414 - get_origin as get_origin, # noqa: PLC0414 - is_typeddict as is_typeddict, # noqa: PLC0414 - is_literal_type as is_literal_type, # noqa: PLC0414 - ) - from pydantic.datetime_parse import parse_date as parse_date, parse_datetime as parse_datetime # noqa: PLC0414 - - -# refactored config -if TYPE_CHECKING: - from pydantic import ConfigDict -else: - if PYDANTIC_V2: - from pydantic import ConfigDict - else: - # TODO: provide an error message here? - ConfigDict = None - - -# renamed methods / properties -def parse_obj(model: type[_ModelT], value: object) -> _ModelT: - if PYDANTIC_V2: - return model.model_validate(value) - else: - # pyright: ignore[reportDeprecated, reportUnnecessaryCast] - return cast(_ModelT, model.parse_obj(value)) - - -def field_is_required(field: FieldInfo) -> bool: - if PYDANTIC_V2: - return field.is_required() - return field.required # type: ignore - - -def field_get_default(field: FieldInfo) -> Any: - value = field.get_default() - if PYDANTIC_V2: - from pydantic_core import PydanticUndefined - - if value == PydanticUndefined: - return None - return value - return value - - -def field_outer_type(field: FieldInfo) -> Any: - if PYDANTIC_V2: - return field.annotation - return field.outer_type_ # type: ignore - - -def get_model_config(model: type[pydantic.BaseModel]) -> Any: - if PYDANTIC_V2: - return model.model_config - return model.__config__ # type: ignore - - -def get_model_fields(model: type[pydantic.BaseModel]) -> dict[str, FieldInfo]: - if PYDANTIC_V2: - return model.model_fields - return model.__fields__ # type: ignore - - -def model_copy(model: _ModelT) -> _ModelT: - if PYDANTIC_V2: - return model.model_copy() - return model.copy() # type: ignore - - -def model_json(model: pydantic.BaseModel, *, indent: int | None = None) -> str: - if PYDANTIC_V2: - return model.model_dump_json(indent=indent) - return model.json(indent=indent) # type: ignore - - -def model_dump( - model: pydantic.BaseModel, - *, - exclude_unset: bool = False, - exclude_defaults: bool = False, -) -> dict[str, Any]: - if PYDANTIC_V2: - return model.model_dump( - exclude_unset=exclude_unset, - exclude_defaults=exclude_defaults, - ) - return cast( - "dict[str, Any]", - model.dict( # pyright: ignore[reportDeprecated, reportUnnecessaryCast] - exclude_unset=exclude_unset, - exclude_defaults=exclude_defaults, - ), - ) - - -def model_parse(model: type[_ModelT], data: Any) -> _ModelT: - if PYDANTIC_V2: - return model.model_validate(data) - return model.parse_obj(data) # pyright: ignore[reportDeprecated] - - -# generic models -if TYPE_CHECKING: - - class GenericModel(pydantic.BaseModel): ... - -else: - if PYDANTIC_V2: - # there no longer needs to be a distinction in v2 but - # we still have to create our own subclass to avoid - # inconsistent MRO ordering errors - class GenericModel(pydantic.BaseModel): ... - - else: - import pydantic.generics - - class GenericModel(pydantic.generics.GenericModel, pydantic.BaseModel): ... - - -# cached properties -if TYPE_CHECKING: - cached_property = property - - # we define a separate type (copied from typeshed) - # that represents that `cached_property` is `set`able - # at runtime, which differs from `@property`. - # - # this is a separate type as editors likely special case - # `@property` and we don't want to cause issues just to have - # more helpful internal types. - - class typed_cached_property(Generic[_T]): # noqa: N801 - func: Callable[[Any], _T] - attrname: str | None - - def __init__(self, func: Callable[[Any], _T]) -> None: ... - - @overload - def __get__(self, instance: None, owner: type[Any] | None = None) -> Self: ... - - @overload - def __get__(self, instance: object, owner: type[Any] | None = None) -> _T: ... - - def __get__(self, instance: object, owner: type[Any] | None = None) -> _T | Self: - raise NotImplementedError() - - def __set_name__(self, owner: type[Any], name: str) -> None: ... - - # __set__ is not defined at runtime, but @cached_property is designed to be settable - def __set__(self, instance: object, value: _T) -> None: ... -else: - try: - from functools import cached_property - except ImportError: - from cached_property import cached_property - - typed_cached_property = cached_property diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_models.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_models.py deleted file mode 100644 index 6d8ba700b7b1dc..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_models.py +++ /dev/null @@ -1,670 +0,0 @@ -from __future__ import annotations - -import inspect -import os -from collections.abc import Callable -from datetime import date, datetime -from typing import TYPE_CHECKING, Any, ClassVar, Generic, Literal, TypeGuard, TypeVar, cast - -import pydantic -import pydantic.generics -from pydantic.fields import FieldInfo -from typing_extensions import ( - ParamSpec, - Protocol, - override, - runtime_checkable, -) - -from ._base_compat import ( - PYDANTIC_V2, - ConfigDict, - field_get_default, - get_args, - get_model_config, - get_model_fields, - get_origin, - is_literal_type, - is_union, - parse_obj, -) -from ._base_compat import ( - GenericModel as BaseGenericModel, -) -from ._base_type import ( - IncEx, - ModelT, -) -from ._utils import ( - PropertyInfo, - coerce_boolean, - extract_type_arg, - is_annotated_type, - is_list, - is_mapping, - parse_date, - parse_datetime, - strip_annotated_type, -) - -if TYPE_CHECKING: - from pydantic_core.core_schema import LiteralSchema, ModelField, ModelFieldsSchema - -__all__ = ["BaseModel", "GenericModel"] -_BaseModelT = TypeVar("_BaseModelT", bound="BaseModel") - -_T = TypeVar("_T") -P = ParamSpec("P") - - -@runtime_checkable -class _ConfigProtocol(Protocol): - allow_population_by_field_name: bool - - -class BaseModel(pydantic.BaseModel): - if PYDANTIC_V2: - model_config: ClassVar[ConfigDict] = ConfigDict( - extra="allow", defer_build=coerce_boolean(os.environ.get("DEFER_PYDANTIC_BUILD", "true")) - ) - else: - - @property - @override - def model_fields_set(self) -> set[str]: - # a forwards-compat shim for pydantic v2 - return self.__fields_set__ # type: ignore - - class Config(pydantic.BaseConfig): # pyright: ignore[reportDeprecated] - extra: Any = pydantic.Extra.allow # type: ignore - - def to_dict( - self, - *, - mode: Literal["json", "python"] = "python", - use_api_names: bool = True, - exclude_unset: bool = True, - exclude_defaults: bool = False, - exclude_none: bool = False, - warnings: bool = True, - ) -> dict[str, object]: - """Recursively generate a dictionary representation of the model, optionally specifying which fields to include or exclude. - - By default, fields that were not set by the API will not be included, - and keys will match the API response, *not* the property names from the model. - - For example, if the API responds with `"fooBar": true` but we've defined a `foo_bar: bool` property, - the output will use the `"fooBar"` key (unless `use_api_names=False` is passed). - - Args: - mode: - If mode is 'json', the dictionary will only contain JSON serializable types. e.g. `datetime` will be turned into a string, `"2024-3-22T18:11:19.117000Z"`. - If mode is 'python', the dictionary may contain any Python objects. e.g. `datetime(2024, 3, 22)` - - use_api_names: Whether to use the key that the API responded with or the property name. Defaults to `True`. - exclude_unset: Whether to exclude fields that have not been explicitly set. - exclude_defaults: Whether to exclude fields that are set to their default value from the output. - exclude_none: Whether to exclude fields that have a value of `None` from the output. - warnings: Whether to log warnings when invalid fields are encountered. This is only supported in Pydantic v2. - """ # noqa: E501 - return self.model_dump( - mode=mode, - by_alias=use_api_names, - exclude_unset=exclude_unset, - exclude_defaults=exclude_defaults, - exclude_none=exclude_none, - warnings=warnings, - ) - - def to_json( - self, - *, - indent: int | None = 2, - use_api_names: bool = True, - exclude_unset: bool = True, - exclude_defaults: bool = False, - exclude_none: bool = False, - warnings: bool = True, - ) -> str: - """Generates a JSON string representing this model as it would be received from or sent to the API (but with indentation). - - By default, fields that were not set by the API will not be included, - and keys will match the API response, *not* the property names from the model. - - For example, if the API responds with `"fooBar": true` but we've defined a `foo_bar: bool` property, - the output will use the `"fooBar"` key (unless `use_api_names=False` is passed). - - Args: - indent: Indentation to use in the JSON output. If `None` is passed, the output will be compact. Defaults to `2` - use_api_names: Whether to use the key that the API responded with or the property name. Defaults to `True`. - exclude_unset: Whether to exclude fields that have not been explicitly set. - exclude_defaults: Whether to exclude fields that have the default value. - exclude_none: Whether to exclude fields that have a value of `None`. - warnings: Whether to show any warnings that occurred during serialization. This is only supported in Pydantic v2. - """ # noqa: E501 - return self.model_dump_json( - indent=indent, - by_alias=use_api_names, - exclude_unset=exclude_unset, - exclude_defaults=exclude_defaults, - exclude_none=exclude_none, - warnings=warnings, - ) - - @override - def __str__(self) -> str: - # mypy complains about an invalid self arg - return f'{self.__repr_name__()}({self.__repr_str__(", ")})' # type: ignore[misc] - - # Override the 'construct' method in a way that supports recursive parsing without validation. - # Based on https://github.com/samuelcolvin/pydantic/issues/1168#issuecomment-817742836. - @classmethod - @override - def construct( - cls: type[ModelT], - _fields_set: set[str] | None = None, - **values: object, - ) -> ModelT: - m = cls.__new__(cls) - fields_values: dict[str, object] = {} - - config = get_model_config(cls) - populate_by_name = ( - config.allow_population_by_field_name - if isinstance(config, _ConfigProtocol) - else config.get("populate_by_name") - ) - - if _fields_set is None: - _fields_set = set() - - model_fields = get_model_fields(cls) - for name, field in model_fields.items(): - key = field.alias - if key is None or (key not in values and populate_by_name): - key = name - - if key in values: - fields_values[name] = _construct_field(value=values[key], field=field, key=key) - _fields_set.add(name) - else: - fields_values[name] = field_get_default(field) - - _extra = {} - for key, value in values.items(): - if key not in model_fields: - if PYDANTIC_V2: - _extra[key] = value - else: - _fields_set.add(key) - fields_values[key] = value - - object.__setattr__(m, "__dict__", fields_values) # noqa: PLC2801 - - if PYDANTIC_V2: - # these properties are copied from Pydantic's `model_construct()` method - object.__setattr__(m, "__pydantic_private__", None) # noqa: PLC2801 - object.__setattr__(m, "__pydantic_extra__", _extra) # noqa: PLC2801 - object.__setattr__(m, "__pydantic_fields_set__", _fields_set) # noqa: PLC2801 - else: - # init_private_attributes() does not exist in v2 - m._init_private_attributes() # type: ignore - - # copied from Pydantic v1's `construct()` method - object.__setattr__(m, "__fields_set__", _fields_set) # noqa: PLC2801 - - return m - - if not TYPE_CHECKING: - # type checkers incorrectly complain about this assignment - # because the type signatures are technically different - # although not in practice - model_construct = construct - - if not PYDANTIC_V2: - # we define aliases for some of the new pydantic v2 methods so - # that we can just document these methods without having to specify - # a specific pydantic version as some users may not know which - # pydantic version they are currently using - - @override - def model_dump( - self, - *, - mode: Literal["json", "python"] | str = "python", - include: IncEx = None, - exclude: IncEx = None, - by_alias: bool = False, - exclude_unset: bool = False, - exclude_defaults: bool = False, - exclude_none: bool = False, - round_trip: bool = False, - warnings: bool | Literal["none", "warn", "error"] = True, - context: dict[str, Any] | None = None, - serialize_as_any: bool = False, - ) -> dict[str, Any]: - """Usage docs: https://docs.pydantic.dev/2.4/concepts/serialization/#modelmodel_dump - - Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. - - Args: - mode: The mode in which `to_python` should run. - If mode is 'json', the dictionary will only contain JSON serializable types. - If mode is 'python', the dictionary may contain any Python objects. - include: A list of fields to include in the output. - exclude: A list of fields to exclude from the output. - by_alias: Whether to use the field's alias in the dictionary key if defined. - exclude_unset: Whether to exclude fields that are unset or None from the output. - exclude_defaults: Whether to exclude fields that are set to their default value from the output. - exclude_none: Whether to exclude fields that have a value of `None` from the output. - round_trip: Whether to enable serialization and deserialization round-trip support. - warnings: Whether to log warnings when invalid fields are encountered. - - Returns: - A dictionary representation of the model. - """ - if mode != "python": - raise ValueError("mode is only supported in Pydantic v2") - if round_trip != False: - raise ValueError("round_trip is only supported in Pydantic v2") - if warnings != True: - raise ValueError("warnings is only supported in Pydantic v2") - if context is not None: - raise ValueError("context is only supported in Pydantic v2") - if serialize_as_any != False: - raise ValueError("serialize_as_any is only supported in Pydantic v2") - return super().dict( # pyright: ignore[reportDeprecated] - include=include, - exclude=exclude, - by_alias=by_alias, - exclude_unset=exclude_unset, - exclude_defaults=exclude_defaults, - exclude_none=exclude_none, - ) - - @override - def model_dump_json( - self, - *, - indent: int | None = None, - include: IncEx = None, - exclude: IncEx = None, - by_alias: bool = False, - exclude_unset: bool = False, - exclude_defaults: bool = False, - exclude_none: bool = False, - round_trip: bool = False, - warnings: bool | Literal["none", "warn", "error"] = True, - context: dict[str, Any] | None = None, - serialize_as_any: bool = False, - ) -> str: - """Usage docs: https://docs.pydantic.dev/2.4/concepts/serialization/#modelmodel_dump_json - - Generates a JSON representation of the model using Pydantic's `to_json` method. - - Args: - indent: Indentation to use in the JSON output. If None is passed, the output will be compact. - include: Field(s) to include in the JSON output. Can take either a string or set of strings. - exclude: Field(s) to exclude from the JSON output. Can take either a string or set of strings. - by_alias: Whether to serialize using field aliases. - exclude_unset: Whether to exclude fields that have not been explicitly set. - exclude_defaults: Whether to exclude fields that have the default value. - exclude_none: Whether to exclude fields that have a value of `None`. - round_trip: Whether to use serialization/deserialization between JSON and class instance. - warnings: Whether to show any warnings that occurred during serialization. - - Returns: - A JSON string representation of the model. - """ - if round_trip != False: - raise ValueError("round_trip is only supported in Pydantic v2") - if warnings != True: - raise ValueError("warnings is only supported in Pydantic v2") - if context is not None: - raise ValueError("context is only supported in Pydantic v2") - if serialize_as_any != False: - raise ValueError("serialize_as_any is only supported in Pydantic v2") - return super().json( # type: ignore[reportDeprecated] - indent=indent, - include=include, - exclude=exclude, - by_alias=by_alias, - exclude_unset=exclude_unset, - exclude_defaults=exclude_defaults, - exclude_none=exclude_none, - ) - - -def _construct_field(value: object, field: FieldInfo, key: str) -> object: - if value is None: - return field_get_default(field) - - if PYDANTIC_V2: - type_ = field.annotation - else: - type_ = cast(type, field.outer_type_) # type: ignore - - if type_ is None: - raise RuntimeError(f"Unexpected field type is None for {key}") - - return construct_type(value=value, type_=type_) - - -def is_basemodel(type_: type) -> bool: - """Returns whether or not the given type is either a `BaseModel` or a union of `BaseModel`""" - if is_union(type_): - return any(is_basemodel(variant) for variant in get_args(type_)) - - return is_basemodel_type(type_) - - -def is_basemodel_type(type_: type) -> TypeGuard[type[BaseModel] | type[GenericModel]]: - origin = get_origin(type_) or type_ - return issubclass(origin, BaseModel) or issubclass(origin, GenericModel) - - -def build( - base_model_cls: Callable[P, _BaseModelT], - *args: P.args, - **kwargs: P.kwargs, -) -> _BaseModelT: - """Construct a BaseModel class without validation. - - This is useful for cases where you need to instantiate a `BaseModel` - from an API response as this provides type-safe params which isn't supported - by helpers like `construct_type()`. - - ```py - build(MyModel, my_field_a="foo", my_field_b=123) - ``` - """ - if args: - raise TypeError( - "Received positional arguments which are not supported; Keyword arguments must be used instead", - ) - - return cast(_BaseModelT, construct_type(type_=base_model_cls, value=kwargs)) - - -def construct_type_unchecked(*, value: object, type_: type[_T]) -> _T: - """Loose coercion to the expected type with construction of nested values. - - Note: the returned value from this function is not guaranteed to match the - given type. - """ - return cast(_T, construct_type(value=value, type_=type_)) - - -def construct_type(*, value: object, type_: type) -> object: - """Loose coercion to the expected type with construction of nested values. - - If the given value does not match the expected type then it is returned as-is. - """ - # we allow `object` as the input type because otherwise, passing things like - # `Literal['value']` will be reported as a type error by type checkers - type_ = cast("type[object]", type_) - - # unwrap `Annotated[T, ...]` -> `T` - if is_annotated_type(type_): - meta: tuple[Any, ...] = get_args(type_)[1:] - type_ = extract_type_arg(type_, 0) - else: - meta = () - # we need to use the origin class for any types that are subscripted generics - # e.g. Dict[str, object] - origin = get_origin(type_) or type_ - args = get_args(type_) - - if is_union(origin): - try: - return validate_type(type_=cast("type[object]", type_), value=value) - except Exception: - pass - - # if the type is a discriminated union then we want to construct the right variant - # in the union, even if the data doesn't match exactly, otherwise we'd break code - # that relies on the constructed class types, e.g. - # - # class FooType: - # kind: Literal['foo'] - # value: str - # - # class BarType: - # kind: Literal['bar'] - # value: int - # - # without this block, if the data we get is something like `{'kind': 'bar', 'value': 'foo'}` then - # we'd end up constructing `FooType` when it should be `BarType`. - discriminator = _build_discriminated_union_meta(union=type_, meta_annotations=meta) - if discriminator and is_mapping(value): - variant_value = value.get(discriminator.field_alias_from or discriminator.field_name) - if variant_value and isinstance(variant_value, str): - variant_type = discriminator.mapping.get(variant_value) - if variant_type: - return construct_type(type_=variant_type, value=value) - - # if the data is not valid, use the first variant that doesn't fail while deserializing - for variant in args: - try: - return construct_type(value=value, type_=variant) - except Exception: - continue - - raise RuntimeError(f"Could not convert data into a valid instance of {type_}") - if origin == dict: - if not is_mapping(value): - return value - - _, items_type = get_args(type_) # Dict[_, items_type] - return {key: construct_type(value=item, type_=items_type) for key, item in value.items()} - - if not is_literal_type(type_) and (issubclass(origin, BaseModel) or issubclass(origin, GenericModel)): - if is_list(value): - return [cast(Any, type_).construct(**entry) if is_mapping(entry) else entry for entry in value] - - if is_mapping(value): - if issubclass(type_, BaseModel): - return type_.construct(**value) # type: ignore[arg-type] - - return cast(Any, type_).construct(**value) - - if origin == list: - if not is_list(value): - return value - - inner_type = args[0] # List[inner_type] - return [construct_type(value=entry, type_=inner_type) for entry in value] - - if origin == float: - if isinstance(value, int): - coerced = float(value) - if coerced != value: - return value - return coerced - - return value - - if type_ == datetime: - try: - return parse_datetime(value) # type: ignore - except Exception: - return value - - if type_ == date: - try: - return parse_date(value) # type: ignore - except Exception: - return value - - return value - - -@runtime_checkable -class CachedDiscriminatorType(Protocol): - __discriminator__: DiscriminatorDetails - - -class DiscriminatorDetails: - field_name: str - """The name of the discriminator field in the variant class, e.g. - - ```py - class Foo(BaseModel): - type: Literal['foo'] - ``` - - Will result in field_name='type' - """ - - field_alias_from: str | None - """The name of the discriminator field in the API response, e.g. - - ```py - class Foo(BaseModel): - type: Literal['foo'] = Field(alias='type_from_api') - ``` - - Will result in field_alias_from='type_from_api' - """ - - mapping: dict[str, type] - """Mapping of discriminator value to variant type, e.g. - - {'foo': FooVariant, 'bar': BarVariant} - """ - - def __init__( - self, - *, - mapping: dict[str, type], - discriminator_field: str, - discriminator_alias: str | None, - ) -> None: - self.mapping = mapping - self.field_name = discriminator_field - self.field_alias_from = discriminator_alias - - -def _build_discriminated_union_meta(*, union: type, meta_annotations: tuple[Any, ...]) -> DiscriminatorDetails | None: - if isinstance(union, CachedDiscriminatorType): - return union.__discriminator__ - - discriminator_field_name: str | None = None - - for annotation in meta_annotations: - if isinstance(annotation, PropertyInfo) and annotation.discriminator is not None: - discriminator_field_name = annotation.discriminator - break - - if not discriminator_field_name: - return None - - mapping: dict[str, type] = {} - discriminator_alias: str | None = None - - for variant in get_args(union): - variant = strip_annotated_type(variant) - if is_basemodel_type(variant): - if PYDANTIC_V2: - field = _extract_field_schema_pv2(variant, discriminator_field_name) - if not field: - continue - - # Note: if one variant defines an alias then they all should - discriminator_alias = field.get("serialization_alias") - - field_schema = field["schema"] - - if field_schema["type"] == "literal": - for entry in cast("LiteralSchema", field_schema)["expected"]: - if isinstance(entry, str): - mapping[entry] = variant - else: - field_info = cast("dict[str, FieldInfo]", variant.__fields__).get(discriminator_field_name) # pyright: ignore[reportDeprecated, reportUnnecessaryCast] - if not field_info: - continue - - # Note: if one variant defines an alias then they all should - discriminator_alias = field_info.alias - - if field_info.annotation and is_literal_type(field_info.annotation): - for entry in get_args(field_info.annotation): - if isinstance(entry, str): - mapping[entry] = variant - - if not mapping: - return None - - details = DiscriminatorDetails( - mapping=mapping, - discriminator_field=discriminator_field_name, - discriminator_alias=discriminator_alias, - ) - cast(CachedDiscriminatorType, union).__discriminator__ = details - return details - - -def _extract_field_schema_pv2(model: type[BaseModel], field_name: str) -> ModelField | None: - schema = model.__pydantic_core_schema__ - if schema["type"] != "model": - return None - - fields_schema = schema["schema"] - if fields_schema["type"] != "model-fields": - return None - - fields_schema = cast("ModelFieldsSchema", fields_schema) - - field = fields_schema["fields"].get(field_name) - if not field: - return None - - return cast("ModelField", field) # pyright: ignore[reportUnnecessaryCast] - - -def validate_type(*, type_: type[_T], value: object) -> _T: - """Strict validation that the given value matches the expected type""" - if inspect.isclass(type_) and issubclass(type_, pydantic.BaseModel): - return cast(_T, parse_obj(type_, value)) - - return cast(_T, _validate_non_model_type(type_=type_, value=value)) - - -# Subclassing here confuses type checkers, so we treat this class as non-inheriting. -if TYPE_CHECKING: - GenericModel = BaseModel -else: - - class GenericModel(BaseGenericModel, BaseModel): - pass - - -if PYDANTIC_V2: - from pydantic import TypeAdapter - - def _validate_non_model_type(*, type_: type[_T], value: object) -> _T: - return TypeAdapter(type_).validate_python(value) - -elif not TYPE_CHECKING: - - class TypeAdapter(Generic[_T]): - """Used as a placeholder to easily convert runtime types to a Pydantic format - to provide validation. - - For example: - ```py - validated = RootModel[int](__root__="5").__root__ - # validated: 5 - ``` - """ - - def __init__(self, type_: type[_T]): - self.type_ = type_ - - def validate_python(self, value: Any) -> _T: - if not isinstance(value, self.type_): - raise ValueError(f"Invalid type: {value} is not of type {self.type_}") - return value - - def _validate_non_model_type(*, type_: type[_T], value: object) -> _T: - return TypeAdapter(type_).validate_python(value) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_type.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_type.py deleted file mode 100644 index ea1d3f09dc42ea..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_base_type.py +++ /dev/null @@ -1,170 +0,0 @@ -from __future__ import annotations - -from collections.abc import Callable, Mapping, Sequence -from os import PathLike -from typing import ( - IO, - TYPE_CHECKING, - Any, - Literal, - Optional, - TypeAlias, - TypeVar, - Union, -) - -import pydantic -from httpx import Response -from typing_extensions import Protocol, TypedDict, override, runtime_checkable - -Query = Mapping[str, object] -Body = object -AnyMapping = Mapping[str, object] -PrimitiveData = Union[str, int, float, bool, None] -Data = Union[PrimitiveData, list[Any], tuple[Any], "Mapping[str, Any]"] -ModelT = TypeVar("ModelT", bound=pydantic.BaseModel) -_T = TypeVar("_T") - -if TYPE_CHECKING: - NoneType: type[None] -else: - NoneType = type(None) - - -# Sentinel class used until PEP 0661 is accepted -class NotGiven: - """ - A sentinel singleton class used to distinguish omitted keyword arguments - from those passed in with the value None (which may have different behavior). - - For example: - - ```py - def get(timeout: Union[int, NotGiven, None] = NotGiven()) -> Response: ... - - get(timeout=1) # 1s timeout - get(timeout=None) # No timeout - get() # Default timeout behavior, which may not be statically known at the method definition. - ``` - """ - - def __bool__(self) -> Literal[False]: - return False - - @override - def __repr__(self) -> str: - return "NOT_GIVEN" - - -NotGivenOr = Union[_T, NotGiven] -NOT_GIVEN = NotGiven() - - -class Omit: - """In certain situations you need to be able to represent a case where a default value has - to be explicitly removed and `None` is not an appropriate substitute, for example: - - ```py - # as the default `Content-Type` header is `application/json` that will be sent - client.post('/upload/files', files={'file': b'my raw file content'}) - - # you can't explicitly override the header as it has to be dynamically generated - # to look something like: 'multipart/form-data; boundary=0d8382fcf5f8c3be01ca2e11002d2983' - client.post(..., headers={'Content-Type': 'multipart/form-data'}) - - # instead you can remove the default `application/json` header by passing Omit - client.post(..., headers={'Content-Type': Omit()}) - ``` - """ - - def __bool__(self) -> Literal[False]: - return False - - -@runtime_checkable -class ModelBuilderProtocol(Protocol): - @classmethod - def build( - cls: type[_T], - *, - response: Response, - data: object, - ) -> _T: ... - - -Headers = Mapping[str, Union[str, Omit]] - - -class HeadersLikeProtocol(Protocol): - def get(self, __key: str) -> str | None: ... - - -HeadersLike = Union[Headers, HeadersLikeProtocol] - -ResponseT = TypeVar( - "ResponseT", - bound="Union[str, None, BaseModel, list[Any], dict[str, Any], Response, UnknownResponse, ModelBuilderProtocol, BinaryResponseContent]", # noqa: E501 -) - -StrBytesIntFloat = Union[str, bytes, int, float] - -# Note: copied from Pydantic -# https://github.com/pydantic/pydantic/blob/32ea570bf96e84234d2992e1ddf40ab8a565925a/pydantic/main.py#L49 -IncEx: TypeAlias = "set[int] | set[str] | dict[int, Any] | dict[str, Any] | None" - -PostParser = Callable[[Any], Any] - - -@runtime_checkable -class InheritsGeneric(Protocol): - """Represents a type that has inherited from `Generic` - - The `__orig_bases__` property can be used to determine the resolved - type variable for a given base class. - """ - - __orig_bases__: tuple[_GenericAlias] - - -class _GenericAlias(Protocol): - __origin__: type[object] - - -class HttpxSendArgs(TypedDict, total=False): - auth: httpx.Auth - - -# for user input files -if TYPE_CHECKING: - Base64FileInput = Union[IO[bytes], PathLike[str]] - FileContent = Union[IO[bytes], bytes, PathLike[str]] -else: - Base64FileInput = Union[IO[bytes], PathLike] - FileContent = Union[IO[bytes], bytes, PathLike] - -FileTypes = Union[ - # file (or bytes) - FileContent, - # (filename, file (or bytes)) - tuple[Optional[str], FileContent], - # (filename, file (or bytes), content_type) - tuple[Optional[str], FileContent, Optional[str]], - # (filename, file (or bytes), content_type, headers) - tuple[Optional[str], FileContent, Optional[str], Mapping[str, str]], -] -RequestFiles = Union[Mapping[str, FileTypes], Sequence[tuple[str, FileTypes]]] - -# duplicate of the above but without our custom file support -HttpxFileContent = Union[bytes, IO[bytes]] -HttpxFileTypes = Union[ - # file (or bytes) - HttpxFileContent, - # (filename, file (or bytes)) - tuple[Optional[str], HttpxFileContent], - # (filename, file (or bytes), content_type) - tuple[Optional[str], HttpxFileContent, Optional[str]], - # (filename, file (or bytes), content_type, headers) - tuple[Optional[str], HttpxFileContent, Optional[str], Mapping[str, str]], -] - -HttpxRequestFiles = Union[Mapping[str, HttpxFileTypes], Sequence[tuple[str, HttpxFileTypes]]] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_constants.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_constants.py deleted file mode 100644 index 8e43bdebecb61f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_constants.py +++ /dev/null @@ -1,12 +0,0 @@ -import httpx - -RAW_RESPONSE_HEADER = "X-Stainless-Raw-Response" -# 通过 `Timeout` 控制接口`connect` 和 `read` 超时时间，默认为`timeout=300.0, connect=8.0` -ZHIPUAI_DEFAULT_TIMEOUT = httpx.Timeout(timeout=300.0, connect=8.0) -# 通过 `retry` 参数控制重试次数，默认为3次 -ZHIPUAI_DEFAULT_MAX_RETRIES = 3 -# 通过 `Limits` 控制最大连接数和保持连接数，默认为`max_connections=50, max_keepalive_connections=10` -ZHIPUAI_DEFAULT_LIMITS = httpx.Limits(max_connections=50, max_keepalive_connections=10) - -INITIAL_RETRY_DELAY = 0.5 -MAX_RETRY_DELAY = 8.0 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_errors.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_errors.py deleted file mode 100644 index e2c9d24c6c0d24..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_errors.py +++ /dev/null @@ -1,86 +0,0 @@ -from __future__ import annotations - -import httpx - -__all__ = [ - "ZhipuAIError", - "APIStatusError", - "APIRequestFailedError", - "APIAuthenticationError", - "APIReachLimitError", - "APIInternalError", - "APIServerFlowExceedError", - "APIResponseError", - "APIResponseValidationError", - "APITimeoutError", - "APIConnectionError", -] - - -class ZhipuAIError(Exception): - def __init__( - self, - message: str, - ) -> None: - super().__init__(message) - - -class APIStatusError(ZhipuAIError): - response: httpx.Response - status_code: int - - def __init__(self, message: str, *, response: httpx.Response) -> None: - super().__init__(message) - self.response = response - self.status_code = response.status_code - - -class APIRequestFailedError(APIStatusError): ... - - -class APIAuthenticationError(APIStatusError): ... - - -class APIReachLimitError(APIStatusError): ... - - -class APIInternalError(APIStatusError): ... - - -class APIServerFlowExceedError(APIStatusError): ... - - -class APIResponseError(ZhipuAIError): - message: str - request: httpx.Request - json_data: object - - def __init__(self, message: str, request: httpx.Request, json_data: object): - self.message = message - self.request = request - self.json_data = json_data - super().__init__(message) - - -class APIResponseValidationError(APIResponseError): - status_code: int - response: httpx.Response - - def __init__(self, response: httpx.Response, json_data: object | None, *, message: str | None = None) -> None: - super().__init__( - message=message or "Data returned by API invalid for expected schema.", - request=response.request, - json_data=json_data, - ) - self.response = response - self.status_code = response.status_code - - -class APIConnectionError(APIResponseError): - def __init__(self, *, message: str = "Connection error.", request: httpx.Request) -> None: - super().__init__(message, request, json_data=None) - - -class APITimeoutError(APIConnectionError): - def __init__(self, request: httpx.Request) -> None: - super().__init__(message="Request timed out.", request=request) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_files.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_files.py deleted file mode 100644 index f9d2e14d9ecb93..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_files.py +++ /dev/null @@ -1,75 +0,0 @@ -from __future__ import annotations - -import io -import os -import pathlib -from typing import TypeGuard, overload - -from ._base_type import ( - Base64FileInput, - FileContent, - FileTypes, - HttpxFileContent, - HttpxFileTypes, - HttpxRequestFiles, - RequestFiles, -) -from ._utils import is_mapping_t, is_sequence_t, is_tuple_t - - -def is_base64_file_input(obj: object) -> TypeGuard[Base64FileInput]: - return isinstance(obj, io.IOBase | os.PathLike) - - -def is_file_content(obj: object) -> TypeGuard[FileContent]: - return isinstance(obj, bytes | tuple | io.IOBase | os.PathLike) - - -def assert_is_file_content(obj: object, *, key: str | None = None) -> None: - if not is_file_content(obj): - prefix = f"Expected entry at `{key}`" if key is not None else f"Expected file input `{obj!r}`" - raise RuntimeError( - f"{prefix} to be bytes, an io.IOBase instance, PathLike or a tuple but received {type(obj)} instead. See https://github.com/openai/openai-python/tree/main#file-uploads" - ) from None - - -@overload -def to_httpx_files(files: None) -> None: ... - - -@overload -def to_httpx_files(files: RequestFiles) -> HttpxRequestFiles: ... - - -def to_httpx_files(files: RequestFiles | None) -> HttpxRequestFiles | None: - if files is None: - return None - - if is_mapping_t(files): - files = {key: _transform_file(file) for key, file in files.items()} - elif is_sequence_t(files): - files = [(key, _transform_file(file)) for key, file in files] - else: - raise TypeError(f"Unexpected file type input {type(files)}, expected mapping or sequence") - - return files - - -def _transform_file(file: FileTypes) -> HttpxFileTypes: - if is_file_content(file): - if isinstance(file, os.PathLike): - path = pathlib.Path(file) - return (path.name, path.read_bytes()) - - return file - - if is_tuple_t(file): - return (file[0], _read_file_content(file[1]), *file[2:]) - - raise TypeError("Expected file types input to be a FileContent type or to be a tuple") - - -def _read_file_content(file: FileContent) -> HttpxFileContent: - if isinstance(file, os.PathLike): - return pathlib.Path(file).read_bytes() - return file diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_http_client.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_http_client.py deleted file mode 100644 index ffdafb85d581fe..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_http_client.py +++ /dev/null @@ -1,910 +0,0 @@ -from __future__ import annotations - -import inspect -import logging -import time -import warnings -from collections.abc import Iterator, Mapping -from itertools import starmap -from random import random -from typing import TYPE_CHECKING, Any, Generic, Literal, Optional, TypeVar, Union, cast, overload - -import httpx -import pydantic -from httpx import URL, Timeout - -from . import _errors, get_origin -from ._base_compat import model_copy -from ._base_models import GenericModel, construct_type, validate_type -from ._base_type import ( - NOT_GIVEN, - AnyMapping, - Body, - Data, - Headers, - HttpxSendArgs, - ModelBuilderProtocol, - NotGiven, - Omit, - PostParser, - Query, - RequestFiles, - ResponseT, -) -from ._constants import ( - INITIAL_RETRY_DELAY, - MAX_RETRY_DELAY, - RAW_RESPONSE_HEADER, - ZHIPUAI_DEFAULT_LIMITS, - ZHIPUAI_DEFAULT_MAX_RETRIES, - ZHIPUAI_DEFAULT_TIMEOUT, -) -from ._errors import APIConnectionError, APIResponseValidationError, APIStatusError, APITimeoutError -from ._files import to_httpx_files -from ._legacy_response import LegacyAPIResponse -from ._request_opt import FinalRequestOptions, UserRequestInput -from ._response import APIResponse, BaseAPIResponse, extract_response_type -from ._sse_client import StreamResponse -from ._utils import flatten, is_given, is_mapping - -log: logging.Logger = logging.getLogger(__name__) - -# TODO: make base page type vars covariant -SyncPageT = TypeVar("SyncPageT", bound="BaseSyncPage[Any]") -# AsyncPageT = TypeVar("AsyncPageT", bound="BaseAsyncPage[Any]") - -_T = TypeVar("_T") -_T_co = TypeVar("_T_co", covariant=True) - -if TYPE_CHECKING: - from httpx._config import DEFAULT_TIMEOUT_CONFIG as HTTPX_DEFAULT_TIMEOUT -else: - try: - from httpx._config import DEFAULT_TIMEOUT_CONFIG as HTTPX_DEFAULT_TIMEOUT - except ImportError: - # taken from https://github.com/encode/httpx/blob/3ba5fe0d7ac70222590e759c31442b1cab263791/httpx/_config.py#L366 - HTTPX_DEFAULT_TIMEOUT = Timeout(5.0) - - -headers = { - "Accept": "application/json", - "Content-Type": "application/json; charset=UTF-8", -} - - -class PageInfo: - """Stores the necessary information to build the request to retrieve the next page. - - Either `url` or `params` must be set. - """ - - url: URL | NotGiven - params: Query | NotGiven - - @overload - def __init__( - self, - *, - url: URL, - ) -> None: ... - - @overload - def __init__( - self, - *, - params: Query, - ) -> None: ... - - def __init__( - self, - *, - url: URL | NotGiven = NOT_GIVEN, - params: Query | NotGiven = NOT_GIVEN, - ) -> None: - self.url = url - self.params = params - - -class BasePage(GenericModel, Generic[_T]): - """ - Defines the core interface for pagination. - - Type Args: - ModelT: The pydantic model that represents an item in the response. - - Methods: - has_next_page(): Check if there is another page available - next_page_info(): Get the necessary information to make a request for the next page - """ - - _options: FinalRequestOptions = pydantic.PrivateAttr() - _model: type[_T] = pydantic.PrivateAttr() - - def has_next_page(self) -> bool: - items = self._get_page_items() - if not items: - return False - return self.next_page_info() is not None - - def next_page_info(self) -> Optional[PageInfo]: ... - - def _get_page_items(self) -> Iterable[_T]: # type: ignore[empty-body] - ... - - def _params_from_url(self, url: URL) -> httpx.QueryParams: - # TODO: do we have to preprocess params here? - return httpx.QueryParams(cast(Any, self._options.params)).merge(url.params) - - def _info_to_options(self, info: PageInfo) -> FinalRequestOptions: - options = model_copy(self._options) - options._strip_raw_response_header() - - if not isinstance(info.params, NotGiven): - options.params = {**options.params, **info.params} - return options - - if not isinstance(info.url, NotGiven): - params = self._params_from_url(info.url) - url = info.url.copy_with(params=params) - options.params = dict(url.params) - options.url = str(url) - return options - - raise ValueError("Unexpected PageInfo state") - - -class BaseSyncPage(BasePage[_T], Generic[_T]): - _client: HttpClient = pydantic.PrivateAttr() - - def _set_private_attributes( - self, - client: HttpClient, - model: type[_T], - options: FinalRequestOptions, - ) -> None: - self._model = model - self._client = client - self._options = options - - # Pydantic uses a custom `__iter__` method to support casting BaseModels - # to dictionaries. e.g. dict(model). - # As we want to support `for item in page`, this is inherently incompatible - # with the default pydantic behavior. It is not possible to support both - # use cases at once. Fortunately, this is not a big deal as all other pydantic - # methods should continue to work as expected as there is an alternative method - # to cast a model to a dictionary, model.dict(), which is used internally - # by pydantic. - def __iter__(self) -> Iterator[_T]: # type: ignore - for page in self.iter_pages(): - yield from page._get_page_items() - - def iter_pages(self: SyncPageT) -> Iterator[SyncPageT]: - page = self - while True: - yield page - if page.has_next_page(): - page = page.get_next_page() - else: - return - - def get_next_page(self: SyncPageT) -> SyncPageT: - info = self.next_page_info() - if not info: - raise RuntimeError( - "No next page expected; please check `.has_next_page()` before calling `.get_next_page()`." - ) - - options = self._info_to_options(info) - return self._client._request_api_list(self._model, page=self.__class__, options=options) - - -class HttpClient: - _client: httpx.Client - _version: str - _base_url: URL - max_retries: int - timeout: Union[float, Timeout, None] - _limits: httpx.Limits - _has_custom_http_client: bool - _default_stream_cls: type[StreamResponse[Any]] | None = None - - _strict_response_validation: bool - - def __init__( - self, - *, - version: str, - base_url: URL, - _strict_response_validation: bool, - max_retries: int = ZHIPUAI_DEFAULT_MAX_RETRIES, - timeout: Union[float, Timeout, None], - limits: httpx.Limits | None = None, - custom_httpx_client: httpx.Client | None = None, - custom_headers: Mapping[str, str] | None = None, - ) -> None: - if limits is not None: - warnings.warn( - "The `connection_pool_limits` argument is deprecated. The `http_client` argument should be passed instead", # noqa: E501 - category=DeprecationWarning, - stacklevel=3, - ) - if custom_httpx_client is not None: - raise ValueError("The `http_client` argument is mutually exclusive with `connection_pool_limits`") - else: - limits = ZHIPUAI_DEFAULT_LIMITS - - if not is_given(timeout): - if custom_httpx_client and custom_httpx_client.timeout != HTTPX_DEFAULT_TIMEOUT: - timeout = custom_httpx_client.timeout - else: - timeout = ZHIPUAI_DEFAULT_TIMEOUT - self.max_retries = max_retries - self.timeout = timeout - self._limits = limits - self._has_custom_http_client = bool(custom_httpx_client) - self._client = custom_httpx_client or httpx.Client( - base_url=base_url, - timeout=self.timeout, - limits=limits, - ) - self._version = version - url = URL(url=base_url) - if not url.raw_path.endswith(b"/"): - url = url.copy_with(raw_path=url.raw_path + b"/") - self._base_url = url - self._custom_headers = custom_headers or {} - self._strict_response_validation = _strict_response_validation - - def _prepare_url(self, url: str) -> URL: - sub_url = URL(url) - if sub_url.is_relative_url: - request_raw_url = self._base_url.raw_path + sub_url.raw_path.lstrip(b"/") - return self._base_url.copy_with(raw_path=request_raw_url) - - return sub_url - - @property - def _default_headers(self): - return { - "Accept": "application/json", - "Content-Type": "application/json; charset=UTF-8", - "ZhipuAI-SDK-Ver": self._version, - "source_type": "zhipu-sdk-python", - "x-request-sdk": "zhipu-sdk-python", - **self.auth_headers, - **self._custom_headers, - } - - @property - def custom_auth(self) -> httpx.Auth | None: - return None - - @property - def auth_headers(self): - return {} - - def _prepare_headers(self, options: FinalRequestOptions) -> httpx.Headers: - custom_headers = options.headers or {} - headers_dict = _merge_mappings(self._default_headers, custom_headers) - - httpx_headers = httpx.Headers(headers_dict) - - return httpx_headers - - def _remaining_retries( - self, - remaining_retries: Optional[int], - options: FinalRequestOptions, - ) -> int: - return remaining_retries if remaining_retries is not None else options.get_max_retries(self.max_retries) - - def _calculate_retry_timeout( - self, - remaining_retries: int, - options: FinalRequestOptions, - response_headers: Optional[httpx.Headers] = None, - ) -> float: - max_retries = options.get_max_retries(self.max_retries) - - # If the API asks us to wait a certain amount of time (and it's a reasonable amount), just do what it says. - # retry_after = self._parse_retry_after_header(response_headers) - # if retry_after is not None and 0 < retry_after <= 60: - # return retry_after - - nb_retries = max_retries - remaining_retries - - # Apply exponential backoff, but not more than the max. - sleep_seconds = min(INITIAL_RETRY_DELAY * pow(2.0, nb_retries), MAX_RETRY_DELAY) - - # Apply some jitter, plus-or-minus half a second. - jitter = 1 - 0.25 * random() - timeout = sleep_seconds * jitter - return max(timeout, 0) - - def _build_request(self, options: FinalRequestOptions) -> httpx.Request: - kwargs: dict[str, Any] = {} - headers = self._prepare_headers(options) - url = self._prepare_url(options.url) - json_data = options.json_data - if options.extra_json is not None: - if json_data is None: - json_data = cast(Body, options.extra_json) - elif is_mapping(json_data): - json_data = _merge_mappings(json_data, options.extra_json) - else: - raise RuntimeError(f"Unexpected JSON data type, {type(json_data)}, cannot merge with `extra_body`") - - content_type = headers.get("Content-Type") - # multipart/form-data; boundary=---abc-- - if headers.get("Content-Type") == "multipart/form-data": - if "boundary" not in content_type: - # only remove the header if the boundary hasn't been explicitly set - # as the caller doesn't want httpx to come up with their own boundary - headers.pop("Content-Type") - - if json_data: - kwargs["data"] = self._make_multipartform(json_data) - - return self._client.build_request( - headers=headers, - timeout=self.timeout if isinstance(options.timeout, NotGiven) else options.timeout, - method=options.method, - url=url, - json=json_data, - files=options.files, - params=options.params, - **kwargs, - ) - - def _object_to_formdata(self, key: str, value: Data | Mapping[object, object]) -> list[tuple[str, str]]: - items = [] - - if isinstance(value, Mapping): - for k, v in value.items(): - items.extend(self._object_to_formdata(f"{key}[{k}]", v)) - return items - if isinstance(value, list | tuple): - for v in value: - items.extend(self._object_to_formdata(key + "[]", v)) - return items - - def _primitive_value_to_str(val) -> str: - # copied from httpx - if val is True: - return "true" - elif val is False: - return "false" - elif val is None: - return "" - return str(val) - - str_data = _primitive_value_to_str(value) - - if not str_data: - return [] - return [(key, str_data)] - - def _make_multipartform(self, data: Mapping[object, object]) -> dict[str, object]: - items = flatten(list(starmap(self._object_to_formdata, data.items()))) - - serialized: dict[str, object] = {} - for key, value in items: - if key in serialized: - raise ValueError(f"存在重复的键: {key};") - serialized[key] = value - return serialized - - def _process_response_data( - self, - *, - data: object, - cast_type: type[ResponseT], - response: httpx.Response, - ) -> ResponseT: - if data is None: - return cast(ResponseT, None) - - if cast_type is object: - return cast(ResponseT, data) - - try: - if inspect.isclass(cast_type) and issubclass(cast_type, ModelBuilderProtocol): - return cast(ResponseT, cast_type.build(response=response, data=data)) - - if self._strict_response_validation: - return cast(ResponseT, validate_type(type_=cast_type, value=data)) - - return cast(ResponseT, construct_type(type_=cast_type, value=data)) - except pydantic.ValidationError as err: - raise APIResponseValidationError(response=response, json_data=data) from err - - def _should_stream_response_body(self, request: httpx.Request) -> bool: - return request.headers.get(RAW_RESPONSE_HEADER) == "stream" # type: ignore[no-any-return] - - def _should_retry(self, response: httpx.Response) -> bool: - # Note: this is not a standard header - should_retry_header = response.headers.get("x-should-retry") - - # If the server explicitly says whether or not to retry, obey. - if should_retry_header == "true": - log.debug("Retrying as header `x-should-retry` is set to `true`") - return True - if should_retry_header == "false": - log.debug("Not retrying as header `x-should-retry` is set to `false`") - return False - - # Retry on request timeouts. - if response.status_code == 408: - log.debug("Retrying due to status code %i", response.status_code) - return True - - # Retry on lock timeouts. - if response.status_code == 409: - log.debug("Retrying due to status code %i", response.status_code) - return True - - # Retry on rate limits. - if response.status_code == 429: - log.debug("Retrying due to status code %i", response.status_code) - return True - - # Retry internal errors. - if response.status_code >= 500: - log.debug("Retrying due to status code %i", response.status_code) - return True - - log.debug("Not retrying") - return False - - def is_closed(self) -> bool: - return self._client.is_closed - - def close(self): - self._client.close() - - def __enter__(self): - return self - - def __exit__(self, exc_type, exc_val, exc_tb): - self.close() - - def request( - self, - cast_type: type[ResponseT], - options: FinalRequestOptions, - remaining_retries: Optional[int] = None, - *, - stream: bool = False, - stream_cls: type[StreamResponse] | None = None, - ) -> ResponseT | StreamResponse: - return self._request( - cast_type=cast_type, - options=options, - stream=stream, - stream_cls=stream_cls, - remaining_retries=remaining_retries, - ) - - def _request( - self, - *, - cast_type: type[ResponseT], - options: FinalRequestOptions, - remaining_retries: int | None, - stream: bool, - stream_cls: type[StreamResponse] | None, - ) -> ResponseT | StreamResponse: - retries = self._remaining_retries(remaining_retries, options) - request = self._build_request(options) - - kwargs: HttpxSendArgs = {} - if self.custom_auth is not None: - kwargs["auth"] = self.custom_auth - try: - response = self._client.send( - request, - stream=stream or self._should_stream_response_body(request=request), - **kwargs, - ) - except httpx.TimeoutException as err: - log.debug("Encountered httpx.TimeoutException", exc_info=True) - - if retries > 0: - return self._retry_request( - options, - cast_type, - retries, - stream=stream, - stream_cls=stream_cls, - response_headers=None, - ) - - log.debug("Raising timeout error") - raise APITimeoutError(request=request) from err - except Exception as err: - log.debug("Encountered Exception", exc_info=True) - - if retries > 0: - return self._retry_request( - options, - cast_type, - retries, - stream=stream, - stream_cls=stream_cls, - response_headers=None, - ) - - log.debug("Raising connection error") - raise APIConnectionError(request=request) from err - - log.debug( - 'HTTP Request: %s %s "%i %s"', request.method, request.url, response.status_code, response.reason_phrase - ) - - try: - response.raise_for_status() - except httpx.HTTPStatusError as err: # thrown on 4xx and 5xx status code - log.debug("Encountered httpx.HTTPStatusError", exc_info=True) - - if retries > 0 and self._should_retry(err.response): - err.response.close() - return self._retry_request( - options, - cast_type, - retries, - err.response.headers, - stream=stream, - stream_cls=stream_cls, - ) - - # If the response is streamed then we need to explicitly read the response - # to completion before attempting to access the response text. - if not err.response.is_closed: - err.response.read() - - log.debug("Re-raising status error") - raise self._make_status_error(err.response) from None - - # return self._parse_response( - # cast_type=cast_type, - # options=options, - # response=response, - # stream=stream, - # stream_cls=stream_cls, - # ) - return self._process_response( - cast_type=cast_type, - options=options, - response=response, - stream=stream, - stream_cls=stream_cls, - ) - - def _retry_request( - self, - options: FinalRequestOptions, - cast_type: type[ResponseT], - remaining_retries: int, - response_headers: httpx.Headers | None, - *, - stream: bool, - stream_cls: type[StreamResponse] | None, - ) -> ResponseT | StreamResponse: - remaining = remaining_retries - 1 - if remaining == 1: - log.debug("1 retry left") - else: - log.debug("%i retries left", remaining) - - timeout = self._calculate_retry_timeout(remaining, options, response_headers) - log.info("Retrying request to %s in %f seconds", options.url, timeout) - - # In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a - # different thread if necessary. - time.sleep(timeout) - - return self._request( - options=options, - cast_type=cast_type, - remaining_retries=remaining, - stream=stream, - stream_cls=stream_cls, - ) - - def _process_response( - self, - *, - cast_type: type[ResponseT], - options: FinalRequestOptions, - response: httpx.Response, - stream: bool, - stream_cls: type[StreamResponse] | None, - ) -> ResponseT: - # _legacy_response with raw_response_header to parser method - if response.request.headers.get(RAW_RESPONSE_HEADER) == "true": - return cast( - ResponseT, - LegacyAPIResponse( - raw=response, - client=self, - cast_type=cast_type, - stream=stream, - stream_cls=stream_cls, - options=options, - ), - ) - - origin = get_origin(cast_type) or cast_type - - if inspect.isclass(origin) and issubclass(origin, BaseAPIResponse): - if not issubclass(origin, APIResponse): - raise TypeError(f"API Response types must subclass {APIResponse}; Received {origin}") - - response_cls = cast("type[BaseAPIResponse[Any]]", cast_type) - return cast( - ResponseT, - response_cls( - raw=response, - client=self, - cast_type=extract_response_type(response_cls), - stream=stream, - stream_cls=stream_cls, - options=options, - ), - ) - - if cast_type == httpx.Response: - return cast(ResponseT, response) - - api_response = APIResponse( - raw=response, - client=self, - cast_type=cast("type[ResponseT]", cast_type), # pyright: ignore[reportUnnecessaryCast] - stream=stream, - stream_cls=stream_cls, - options=options, - ) - if bool(response.request.headers.get(RAW_RESPONSE_HEADER)): - return cast(ResponseT, api_response) - - return api_response.parse() - - def _request_api_list( - self, - model: type[object], - page: type[SyncPageT], - options: FinalRequestOptions, - ) -> SyncPageT: - def _parser(resp: SyncPageT) -> SyncPageT: - resp._set_private_attributes( - client=self, - model=model, - options=options, - ) - return resp - - options.post_parser = _parser - - return self.request(page, options, stream=False) - - @overload - def get( - self, - path: str, - *, - cast_type: type[ResponseT], - options: UserRequestInput = {}, - stream: Literal[False] = False, - ) -> ResponseT: ... - - @overload - def get( - self, - path: str, - *, - cast_type: type[ResponseT], - options: UserRequestInput = {}, - stream: Literal[True], - stream_cls: type[StreamResponse], - ) -> StreamResponse: ... - - @overload - def get( - self, - path: str, - *, - cast_type: type[ResponseT], - options: UserRequestInput = {}, - stream: bool, - stream_cls: type[StreamResponse] | None = None, - ) -> ResponseT | StreamResponse: ... - - def get( - self, - path: str, - *, - cast_type: type[ResponseT], - options: UserRequestInput = {}, - stream: bool = False, - stream_cls: type[StreamResponse] | None = None, - ) -> ResponseT: - opts = FinalRequestOptions.construct(method="get", url=path, **options) - return cast(ResponseT, self.request(cast_type, opts, stream=stream, stream_cls=stream_cls)) - - @overload - def post( - self, - path: str, - *, - cast_type: type[ResponseT], - body: Body | None = None, - options: UserRequestInput = {}, - files: RequestFiles | None = None, - stream: Literal[False] = False, - ) -> ResponseT: ... - - @overload - def post( - self, - path: str, - *, - cast_type: type[ResponseT], - body: Body | None = None, - options: UserRequestInput = {}, - files: RequestFiles | None = None, - stream: Literal[True], - stream_cls: type[StreamResponse], - ) -> StreamResponse: ... - - @overload - def post( - self, - path: str, - *, - cast_type: type[ResponseT], - body: Body | None = None, - options: UserRequestInput = {}, - files: RequestFiles | None = None, - stream: bool, - stream_cls: type[StreamResponse] | None = None, - ) -> ResponseT | StreamResponse: ... - - def post( - self, - path: str, - *, - cast_type: type[ResponseT], - body: Body | None = None, - options: UserRequestInput = {}, - files: RequestFiles | None = None, - stream: bool = False, - stream_cls: type[StreamResponse[Any]] | None = None, - ) -> ResponseT | StreamResponse: - opts = FinalRequestOptions.construct( - method="post", url=path, json_data=body, files=to_httpx_files(files), **options - ) - - return cast(ResponseT, self.request(cast_type, opts, stream=stream, stream_cls=stream_cls)) - - def patch( - self, - path: str, - *, - cast_type: type[ResponseT], - body: Body | None = None, - options: UserRequestInput = {}, - ) -> ResponseT: - opts = FinalRequestOptions.construct(method="patch", url=path, json_data=body, **options) - - return self.request( - cast_type=cast_type, - options=opts, - ) - - def put( - self, - path: str, - *, - cast_type: type[ResponseT], - body: Body | None = None, - options: UserRequestInput = {}, - files: RequestFiles | None = None, - ) -> ResponseT | StreamResponse: - opts = FinalRequestOptions.construct( - method="put", url=path, json_data=body, files=to_httpx_files(files), **options - ) - - return self.request( - cast_type=cast_type, - options=opts, - ) - - def delete( - self, - path: str, - *, - cast_type: type[ResponseT], - body: Body | None = None, - options: UserRequestInput = {}, - ) -> ResponseT | StreamResponse: - opts = FinalRequestOptions.construct(method="delete", url=path, json_data=body, **options) - - return self.request( - cast_type=cast_type, - options=opts, - ) - - def get_api_list( - self, - path: str, - *, - model: type[object], - page: type[SyncPageT], - body: Body | None = None, - options: UserRequestInput = {}, - method: str = "get", - ) -> SyncPageT: - opts = FinalRequestOptions.construct(method=method, url=path, json_data=body, **options) - return self._request_api_list(model, page, opts) - - def _make_status_error(self, response) -> APIStatusError: - response_text = response.text.strip() - status_code = response.status_code - error_msg = f"Error code: {status_code}, with error text {response_text}" - - if status_code == 400: - return _errors.APIRequestFailedError(message=error_msg, response=response) - elif status_code == 401: - return _errors.APIAuthenticationError(message=error_msg, response=response) - elif status_code == 429: - return _errors.APIReachLimitError(message=error_msg, response=response) - elif status_code == 500: - return _errors.APIInternalError(message=error_msg, response=response) - elif status_code == 503: - return _errors.APIServerFlowExceedError(message=error_msg, response=response) - return APIStatusError(message=error_msg, response=response) - - -def make_request_options( - *, - query: Query | None = None, - extra_headers: Headers | None = None, - extra_query: Query | None = None, - extra_body: Body | None = None, - timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, - post_parser: PostParser | NotGiven = NOT_GIVEN, -) -> UserRequestInput: - """Create a dict of type RequestOptions without keys of NotGiven values.""" - options: UserRequestInput = {} - if extra_headers is not None: - options["headers"] = extra_headers - - if extra_body is not None: - options["extra_json"] = cast(AnyMapping, extra_body) - - if query is not None: - options["params"] = query - - if extra_query is not None: - options["params"] = {**options.get("params", {}), **extra_query} - - if not isinstance(timeout, NotGiven): - options["timeout"] = timeout - - if is_given(post_parser): - # internal - options["post_parser"] = post_parser # type: ignore - - return options - - -def _merge_mappings( - obj1: Mapping[_T_co, Union[_T, Omit]], - obj2: Mapping[_T_co, Union[_T, Omit]], -) -> dict[_T_co, _T]: - """Merge two mappings of the same type, removing any values that are instances of `Omit`. - - In cases with duplicate keys the second mapping takes precedence. - """ - merged = {**obj1, **obj2} - return {key: value for key, value in merged.items() if not isinstance(value, Omit)} diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_jwt_token.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_jwt_token.py deleted file mode 100644 index 21f158a5f45251..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_jwt_token.py +++ /dev/null @@ -1,31 +0,0 @@ -import time - -import cachetools.func -import jwt - -# 缓存时间 3分钟 -CACHE_TTL_SECONDS = 3 * 60 - -# token 有效期比缓存时间 多30秒 -API_TOKEN_TTL_SECONDS = CACHE_TTL_SECONDS + 30 - - -@cachetools.func.ttl_cache(maxsize=10, ttl=CACHE_TTL_SECONDS) -def generate_token(apikey: str): - try: - api_key, secret = apikey.split(".") - except Exception as e: - raise Exception("invalid api_key", e) - - payload = { - "api_key": api_key, - "exp": int(round(time.time() * 1000)) + API_TOKEN_TTL_SECONDS * 1000, - "timestamp": int(round(time.time() * 1000)), - } - ret = jwt.encode( - payload, - secret, - algorithm="HS256", - headers={"alg": "HS256", "sign_type": "SIGN"}, - ) - return ret diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_legacy_binary_response.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_legacy_binary_response.py deleted file mode 100644 index 51623bd860951f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_legacy_binary_response.py +++ /dev/null @@ -1,207 +0,0 @@ -from __future__ import annotations - -import os -from collections.abc import AsyncIterator, Iterator -from typing import Any - -import httpx - - -class HttpxResponseContent: - @property - def content(self) -> bytes: - raise NotImplementedError("This method is not implemented for this class.") - - @property - def text(self) -> str: - raise NotImplementedError("This method is not implemented for this class.") - - @property - def encoding(self) -> str | None: - raise NotImplementedError("This method is not implemented for this class.") - - @property - def charset_encoding(self) -> str | None: - raise NotImplementedError("This method is not implemented for this class.") - - def json(self, **kwargs: Any) -> Any: - raise NotImplementedError("This method is not implemented for this class.") - - def read(self) -> bytes: - raise NotImplementedError("This method is not implemented for this class.") - - def iter_bytes(self, chunk_size: int | None = None) -> Iterator[bytes]: - raise NotImplementedError("This method is not implemented for this class.") - - def iter_text(self, chunk_size: int | None = None) -> Iterator[str]: - raise NotImplementedError("This method is not implemented for this class.") - - def iter_lines(self) -> Iterator[str]: - raise NotImplementedError("This method is not implemented for this class.") - - def iter_raw(self, chunk_size: int | None = None) -> Iterator[bytes]: - raise NotImplementedError("This method is not implemented for this class.") - - def write_to_file( - self, - file: str | os.PathLike[str], - ) -> None: - raise NotImplementedError("This method is not implemented for this class.") - - def stream_to_file( - self, - file: str | os.PathLike[str], - *, - chunk_size: int | None = None, - ) -> None: - raise NotImplementedError("This method is not implemented for this class.") - - def close(self) -> None: - raise NotImplementedError("This method is not implemented for this class.") - - async def aread(self) -> bytes: - raise NotImplementedError("This method is not implemented for this class.") - - async def aiter_bytes(self, chunk_size: int | None = None) -> AsyncIterator[bytes]: - raise NotImplementedError("This method is not implemented for this class.") - - async def aiter_text(self, chunk_size: int | None = None) -> AsyncIterator[str]: - raise NotImplementedError("This method is not implemented for this class.") - - async def aiter_lines(self) -> AsyncIterator[str]: - raise NotImplementedError("This method is not implemented for this class.") - - async def aiter_raw(self, chunk_size: int | None = None) -> AsyncIterator[bytes]: - raise NotImplementedError("This method is not implemented for this class.") - - async def astream_to_file( - self, - file: str | os.PathLike[str], - *, - chunk_size: int | None = None, - ) -> None: - raise NotImplementedError("This method is not implemented for this class.") - - async def aclose(self) -> None: - raise NotImplementedError("This method is not implemented for this class.") - - -class HttpxBinaryResponseContent(HttpxResponseContent): - response: httpx.Response - - def __init__(self, response: httpx.Response) -> None: - self.response = response - - @property - def content(self) -> bytes: - return self.response.content - - @property - def encoding(self) -> str | None: - return self.response.encoding - - @property - def charset_encoding(self) -> str | None: - return self.response.charset_encoding - - def read(self) -> bytes: - return self.response.read() - - def text(self) -> str: - raise NotImplementedError("Not implemented for binary response content") - - def json(self, **kwargs: Any) -> Any: - raise NotImplementedError("Not implemented for binary response content") - - def iter_text(self, chunk_size: int | None = None) -> Iterator[str]: - raise NotImplementedError("Not implemented for binary response content") - - def iter_lines(self) -> Iterator[str]: - raise NotImplementedError("Not implemented for binary response content") - - async def aiter_text(self, chunk_size: int | None = None) -> AsyncIterator[str]: - raise NotImplementedError("Not implemented for binary response content") - - async def aiter_lines(self) -> AsyncIterator[str]: - raise NotImplementedError("Not implemented for binary response content") - - def iter_bytes(self, chunk_size: int | None = None) -> Iterator[bytes]: - return self.response.iter_bytes(chunk_size) - - def iter_raw(self, chunk_size: int | None = None) -> Iterator[bytes]: - return self.response.iter_raw(chunk_size) - - def write_to_file( - self, - file: str | os.PathLike[str], - ) -> None: - """Write the output to the given file. - - Accepts a filename or any path-like object, e.g. pathlib.Path - - Note: if you want to stream the data to the file instead of writing - all at once then you should use `.with_streaming_response` when making - the API request, e.g. `client.with_streaming_response.foo().stream_to_file('my_filename.txt')` - """ - with open(file, mode="wb") as f: - for data in self.response.iter_bytes(): - f.write(data) - - def stream_to_file( - self, - file: str | os.PathLike[str], - *, - chunk_size: int | None = None, - ) -> None: - with open(file, mode="wb") as f: - for data in self.response.iter_bytes(chunk_size): - f.write(data) - - def close(self) -> None: - return self.response.close() - - async def aread(self) -> bytes: - return await self.response.aread() - - async def aiter_bytes(self, chunk_size: int | None = None) -> AsyncIterator[bytes]: - return self.response.aiter_bytes(chunk_size) - - async def aiter_raw(self, chunk_size: int | None = None) -> AsyncIterator[bytes]: - return self.response.aiter_raw(chunk_size) - - async def astream_to_file( - self, - file: str | os.PathLike[str], - *, - chunk_size: int | None = None, - ) -> None: - path = anyio.Path(file) - async with await path.open(mode="wb") as f: - async for data in self.response.aiter_bytes(chunk_size): - await f.write(data) - - async def aclose(self) -> None: - return await self.response.aclose() - - -class HttpxTextBinaryResponseContent(HttpxBinaryResponseContent): - response: httpx.Response - - @property - def text(self) -> str: - return self.response.text - - def json(self, **kwargs: Any) -> Any: - return self.response.json(**kwargs) - - def iter_text(self, chunk_size: int | None = None) -> Iterator[str]: - return self.response.iter_text(chunk_size) - - def iter_lines(self) -> Iterator[str]: - return self.response.iter_lines() - - async def aiter_text(self, chunk_size: int | None = None) -> AsyncIterator[str]: - return self.response.aiter_text(chunk_size) - - async def aiter_lines(self) -> AsyncIterator[str]: - return self.response.aiter_lines() diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_legacy_response.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_legacy_response.py deleted file mode 100644 index 51bf21bcdc17a8..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_legacy_response.py +++ /dev/null @@ -1,341 +0,0 @@ -from __future__ import annotations - -import datetime -import functools -import inspect -import logging -from collections.abc import Callable -from typing import TYPE_CHECKING, Any, Generic, TypeVar, Union, cast, get_origin, overload - -import httpx -import pydantic -from typing_extensions import ParamSpec, override - -from ._base_models import BaseModel, is_basemodel -from ._base_type import NoneType -from ._constants import RAW_RESPONSE_HEADER -from ._errors import APIResponseValidationError -from ._legacy_binary_response import HttpxResponseContent, HttpxTextBinaryResponseContent -from ._sse_client import StreamResponse, extract_stream_chunk_type, is_stream_class_type -from ._utils import extract_type_arg, is_annotated_type, is_given - -if TYPE_CHECKING: - from ._http_client import HttpClient - from ._request_opt import FinalRequestOptions - -P = ParamSpec("P") -R = TypeVar("R") -_T = TypeVar("_T") - -log: logging.Logger = logging.getLogger(__name__) - - -class LegacyAPIResponse(Generic[R]): - """This is a legacy class as it will be replaced by `APIResponse` - and `AsyncAPIResponse` in the `_response.py` file in the next major - release. - - For the sync client this will mostly be the same with the exception - of `content` & `text` will be methods instead of properties. In the - async client, all methods will be async. - - A migration script will be provided & the migration in general should - be smooth. - """ - - _cast_type: type[R] - _client: HttpClient - _parsed_by_type: dict[type[Any], Any] - _stream: bool - _stream_cls: type[StreamResponse[Any]] | None - _options: FinalRequestOptions - - http_response: httpx.Response - - def __init__( - self, - *, - raw: httpx.Response, - cast_type: type[R], - client: HttpClient, - stream: bool, - stream_cls: type[StreamResponse[Any]] | None, - options: FinalRequestOptions, - ) -> None: - self._cast_type = cast_type - self._client = client - self._parsed_by_type = {} - self._stream = stream - self._stream_cls = stream_cls - self._options = options - self.http_response = raw - - @property - def request_id(self) -> str | None: - return self.http_response.headers.get("x-request-id") # type: ignore[no-any-return] - - @overload - def parse(self, *, to: type[_T]) -> _T: ... - - @overload - def parse(self) -> R: ... - - def parse(self, *, to: type[_T] | None = None) -> R | _T: - """Returns the rich python representation of this response's data. - - NOTE: For the async client: this will become a coroutine in the next major version. - - For lower-level control, see `.read()`, `.json()`, `.iter_bytes()`. - - You can customize the type that the response is parsed into through - the `to` argument, e.g. - - ```py - from zhipuai import BaseModel - - - class MyModel(BaseModel): - foo: str - - - obj = response.parse(to=MyModel) - print(obj.foo) - ``` - - We support parsing: - - `BaseModel` - - `dict` - - `list` - - `Union` - - `str` - - `int` - - `float` - - `httpx.Response` - """ - cache_key = to if to is not None else self._cast_type - cached = self._parsed_by_type.get(cache_key) - if cached is not None: - return cached # type: ignore[no-any-return] - - parsed = self._parse(to=to) - if is_given(self._options.post_parser): - parsed = self._options.post_parser(parsed) - - self._parsed_by_type[cache_key] = parsed - return parsed - - @property - def headers(self) -> httpx.Headers: - return self.http_response.headers - - @property - def http_request(self) -> httpx.Request: - return self.http_response.request - - @property - def status_code(self) -> int: - return self.http_response.status_code - - @property - def url(self) -> httpx.URL: - return self.http_response.url - - @property - def method(self) -> str: - return self.http_request.method - - @property - def content(self) -> bytes: - """Return the binary response content. - - NOTE: this will be removed in favour of `.read()` in the - next major version. - """ - return self.http_response.content - - @property - def text(self) -> str: - """Return the decoded response content. - - NOTE: this will be turned into a method in the next major version. - """ - return self.http_response.text - - @property - def http_version(self) -> str: - return self.http_response.http_version - - @property - def is_closed(self) -> bool: - return self.http_response.is_closed - - @property - def elapsed(self) -> datetime.timedelta: - """The time taken for the complete request/response cycle to complete.""" - return self.http_response.elapsed - - def _parse(self, *, to: type[_T] | None = None) -> R | _T: - # unwrap `Annotated[T, ...]` -> `T` - if to and is_annotated_type(to): - to = extract_type_arg(to, 0) - - if self._stream: - if to: - if not is_stream_class_type(to): - raise TypeError(f"Expected custom parse type to be a subclass of {StreamResponse}") - - return cast( - _T, - to( - cast_type=extract_stream_chunk_type( - to, - failure_message="Expected custom stream type to be passed with a type argument, e.g. StreamResponse[ChunkType]", # noqa: E501 - ), - response=self.http_response, - client=cast(Any, self._client), - ), - ) - - if self._stream_cls: - return cast( - R, - self._stream_cls( - cast_type=extract_stream_chunk_type(self._stream_cls), - response=self.http_response, - client=cast(Any, self._client), - ), - ) - - stream_cls = cast("type[StreamResponse[Any]] | None", self._client._default_stream_cls) - if stream_cls is None: - raise MissingStreamClassError() - - return cast( - R, - stream_cls( - cast_type=self._cast_type, - response=self.http_response, - client=cast(Any, self._client), - ), - ) - - cast_type = to if to is not None else self._cast_type - - # unwrap `Annotated[T, ...]` -> `T` - if is_annotated_type(cast_type): - cast_type = extract_type_arg(cast_type, 0) - - if cast_type is NoneType: - return cast(R, None) - - response = self.http_response - if cast_type == str: - return cast(R, response.text) - - if cast_type == int: - return cast(R, int(response.text)) - - if cast_type == float: - return cast(R, float(response.text)) - - origin = get_origin(cast_type) or cast_type - - if inspect.isclass(origin) and issubclass(origin, HttpxResponseContent): - # in the response, e.g. mime file - *_, filename = response.headers.get("content-disposition", "").split("filename=") - # 判断文件类型是jsonl类型的使用HttpxTextBinaryResponseContent - if filename and filename.endswith(".jsonl") or filename and filename.endswith(".xlsx"): - return cast(R, HttpxTextBinaryResponseContent(response)) - else: - return cast(R, cast_type(response)) # type: ignore - - if origin == LegacyAPIResponse: - raise RuntimeError("Unexpected state - cast_type is `APIResponse`") - - if inspect.isclass(origin) and issubclass(origin, httpx.Response): - # Because of the invariance of our ResponseT TypeVar, users can subclass httpx.Response - # and pass that class to our request functions. We cannot change the variance to be either - # covariant or contravariant as that makes our usage of ResponseT illegal. We could construct - # the response class ourselves but that is something that should be supported directly in httpx - # as it would be easy to incorrectly construct the Response object due to the multitude of arguments. - if cast_type != httpx.Response: - raise ValueError("Subclasses of httpx.Response cannot be passed to `cast_type`") - return cast(R, response) - - if inspect.isclass(origin) and not issubclass(origin, BaseModel) and issubclass(origin, pydantic.BaseModel): - raise TypeError("Pydantic models must subclass our base model type, e.g. `from openai import BaseModel`") - - if ( - cast_type is not object - and origin is not list - and origin is not dict - and origin is not Union - and not issubclass(origin, BaseModel) - ): - raise RuntimeError( - f"Unsupported type, expected {cast_type} to be a subclass of {BaseModel}, {dict}, {list}, {Union}, {NoneType}, {str} or {httpx.Response}." # noqa: E501 - ) - - # split is required to handle cases where additional information is included - # in the response, e.g. application/json; charset=utf-8 - content_type, *_ = response.headers.get("content-type", "*").split(";") - if content_type != "application/json": - if is_basemodel(cast_type): - try: - data = response.json() - except Exception as exc: - log.debug("Could not read JSON from response data due to %s - %s", type(exc), exc) - else: - return self._client._process_response_data( - data=data, - cast_type=cast_type, # type: ignore - response=response, - ) - - if self._client._strict_response_validation: - raise APIResponseValidationError( - response=response, - message=f"Expected Content-Type response header to be `application/json` but received `{content_type}` instead.", # noqa: E501 - json_data=response.text, - ) - - # If the API responds with content that isn't JSON then we just return - # the (decoded) text without performing any parsing so that you can still - # handle the response however you need to. - return response.text # type: ignore - - data = response.json() - - return self._client._process_response_data( - data=data, - cast_type=cast_type, # type: ignore - response=response, - ) - - @override - def __repr__(self) -> str: - return f"" - - -class MissingStreamClassError(TypeError): - def __init__(self) -> None: - super().__init__( - "The `stream` argument was set to `True` but the `stream_cls` argument was not given. See `openai._streaming` for reference", # noqa: E501 - ) - - -def to_raw_response_wrapper(func: Callable[P, R]) -> Callable[P, LegacyAPIResponse[R]]: - """Higher order function that takes one of our bound API methods and wraps it - to support returning the raw `APIResponse` object directly. - """ - - @functools.wraps(func) - def wrapped(*args: P.args, **kwargs: P.kwargs) -> LegacyAPIResponse[R]: - extra_headers: dict[str, str] = {**(cast(Any, kwargs.get("extra_headers")) or {})} - extra_headers[RAW_RESPONSE_HEADER] = "true" - - kwargs["extra_headers"] = extra_headers - - return cast(LegacyAPIResponse[R], func(*args, **kwargs)) - - return wrapped diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_request_opt.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_request_opt.py deleted file mode 100644 index c3b894b3a3d88f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_request_opt.py +++ /dev/null @@ -1,97 +0,0 @@ -from __future__ import annotations - -from collections.abc import Callable -from typing import TYPE_CHECKING, Any, ClassVar, Union, cast - -import pydantic.generics -from httpx import Timeout -from typing_extensions import Required, TypedDict, Unpack, final - -from ._base_compat import PYDANTIC_V2, ConfigDict -from ._base_type import AnyMapping, Body, Headers, HttpxRequestFiles, NotGiven, Query -from ._constants import RAW_RESPONSE_HEADER -from ._utils import is_given, strip_not_given - - -class UserRequestInput(TypedDict, total=False): - headers: Headers - max_retries: int - timeout: float | Timeout | None - params: Query - extra_json: AnyMapping - - -class FinalRequestOptionsInput(TypedDict, total=False): - method: Required[str] - url: Required[str] - params: Query - headers: Headers - max_retries: int - timeout: float | Timeout | None - files: HttpxRequestFiles | None - json_data: Body - extra_json: AnyMapping - - -@final -class FinalRequestOptions(pydantic.BaseModel): - method: str - url: str - params: Query = {} - headers: Union[Headers, NotGiven] = NotGiven() - max_retries: Union[int, NotGiven] = NotGiven() - timeout: Union[float, Timeout, None, NotGiven] = NotGiven() - files: Union[HttpxRequestFiles, None] = None - idempotency_key: Union[str, None] = None - post_parser: Union[Callable[[Any], Any], NotGiven] = NotGiven() - - # It should be noted that we cannot use `json` here as that would override - # a BaseModel method in an incompatible fashion. - json_data: Union[Body, None] = None - extra_json: Union[AnyMapping, None] = None - - if PYDANTIC_V2: - model_config: ClassVar[ConfigDict] = ConfigDict(arbitrary_types_allowed=True) - else: - - class Config(pydantic.BaseConfig): # pyright: ignore[reportDeprecated] - arbitrary_types_allowed: bool = True - - def get_max_retries(self, max_retries: int) -> int: - if isinstance(self.max_retries, NotGiven): - return max_retries - return self.max_retries - - def _strip_raw_response_header(self) -> None: - if not is_given(self.headers): - return - - if self.headers.get(RAW_RESPONSE_HEADER): - self.headers = {**self.headers} - self.headers.pop(RAW_RESPONSE_HEADER) - - # override the `construct` method so that we can run custom transformations. - # this is necessary as we don't want to do any actual runtime type checking - # (which means we can't use validators) but we do want to ensure that `NotGiven` - # values are not present - # - # type ignore required because we're adding explicit types to `**values` - @classmethod - def construct( # type: ignore - cls, - _fields_set: set[str] | None = None, - **values: Unpack[UserRequestInput], - ) -> FinalRequestOptions: - kwargs: dict[str, Any] = { - # we unconditionally call `strip_not_given` on any value - # as it will just ignore any non-mapping types - key: strip_not_given(value) - for key, value in values.items() - } - if PYDANTIC_V2: - return super().model_construct(_fields_set, **kwargs) - return cast(FinalRequestOptions, super().construct(_fields_set, **kwargs)) # pyright: ignore[reportDeprecated] - - if not TYPE_CHECKING: - # type checkers incorrectly complain about this assignment - model_construct = construct diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_response.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_response.py deleted file mode 100644 index 92e601805569f3..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_response.py +++ /dev/null @@ -1,398 +0,0 @@ -from __future__ import annotations - -import datetime -import inspect -import logging -from collections.abc import Iterator -from typing import TYPE_CHECKING, Any, Generic, TypeVar, Union, cast, get_origin, overload - -import httpx -import pydantic -from typing_extensions import ParamSpec, override - -from ._base_models import BaseModel, is_basemodel -from ._base_type import NoneType -from ._errors import APIResponseValidationError, ZhipuAIError -from ._sse_client import StreamResponse, extract_stream_chunk_type, is_stream_class_type -from ._utils import extract_type_arg, extract_type_var_from_base, is_annotated_type, is_given - -if TYPE_CHECKING: - from ._http_client import HttpClient - from ._request_opt import FinalRequestOptions - -P = ParamSpec("P") -R = TypeVar("R") -_T = TypeVar("_T") -_APIResponseT = TypeVar("_APIResponseT", bound="APIResponse[Any]") -log: logging.Logger = logging.getLogger(__name__) - - -class BaseAPIResponse(Generic[R]): - _cast_type: type[R] - _client: HttpClient - _parsed_by_type: dict[type[Any], Any] - _is_sse_stream: bool - _stream_cls: type[StreamResponse[Any]] - _options: FinalRequestOptions - http_response: httpx.Response - - def __init__( - self, - *, - raw: httpx.Response, - cast_type: type[R], - client: HttpClient, - stream: bool, - stream_cls: type[StreamResponse[Any]] | None = None, - options: FinalRequestOptions, - ) -> None: - self._cast_type = cast_type - self._client = client - self._parsed_by_type = {} - self._is_sse_stream = stream - self._stream_cls = stream_cls - self._options = options - self.http_response = raw - - def _parse(self, *, to: type[_T] | None = None) -> R | _T: - # unwrap `Annotated[T, ...]` -> `T` - if to and is_annotated_type(to): - to = extract_type_arg(to, 0) - - if self._is_sse_stream: - if to: - if not is_stream_class_type(to): - raise TypeError(f"Expected custom parse type to be a subclass of {StreamResponse}") - - return cast( - _T, - to( - cast_type=extract_stream_chunk_type( - to, - failure_message="Expected custom stream type to be passed with a type argument, e.g. StreamResponse[ChunkType]", # noqa: E501 - ), - response=self.http_response, - client=cast(Any, self._client), - ), - ) - - if self._stream_cls: - return cast( - R, - self._stream_cls( - cast_type=extract_stream_chunk_type(self._stream_cls), - response=self.http_response, - client=cast(Any, self._client), - ), - ) - - stream_cls = cast("type[Stream[Any]] | None", self._client._default_stream_cls) - if stream_cls is None: - raise MissingStreamClassError() - - return cast( - R, - stream_cls( - cast_type=self._cast_type, - response=self.http_response, - client=cast(Any, self._client), - ), - ) - - cast_type = to if to is not None else self._cast_type - - # unwrap `Annotated[T, ...]` -> `T` - if is_annotated_type(cast_type): - cast_type = extract_type_arg(cast_type, 0) - - if cast_type is NoneType: - return cast(R, None) - - response = self.http_response - if cast_type == str: - return cast(R, response.text) - - if cast_type == bytes: - return cast(R, response.content) - - if cast_type == int: - return cast(R, int(response.text)) - - if cast_type == float: - return cast(R, float(response.text)) - - origin = get_origin(cast_type) or cast_type - - # handle the legacy binary response case - if inspect.isclass(cast_type) and cast_type.__name__ == "HttpxBinaryResponseContent": - return cast(R, cast_type(response)) # type: ignore - - if origin == APIResponse: - raise RuntimeError("Unexpected state - cast_type is `APIResponse`") - - if inspect.isclass(origin) and issubclass(origin, httpx.Response): - # Because of the invariance of our ResponseT TypeVar, users can subclass httpx.Response - # and pass that class to our request functions. We cannot change the variance to be either - # covariant or contravariant as that makes our usage of ResponseT illegal. We could construct - # the response class ourselves but that is something that should be supported directly in httpx - # as it would be easy to incorrectly construct the Response object due to the multitude of arguments. - if cast_type != httpx.Response: - raise ValueError("Subclasses of httpx.Response cannot be passed to `cast_type`") - return cast(R, response) - - if inspect.isclass(origin) and not issubclass(origin, BaseModel) and issubclass(origin, pydantic.BaseModel): - raise TypeError("Pydantic models must subclass our base model type, e.g. `from openai import BaseModel`") - - if ( - cast_type is not object - and origin is not list - and origin is not dict - and origin is not Union - and not issubclass(origin, BaseModel) - ): - raise RuntimeError( - f"Unsupported type, expected {cast_type} to be a subclass of {BaseModel}, {dict}, {list}, {Union}, {NoneType}, {str} or {httpx.Response}." # noqa: E501 - ) - - # split is required to handle cases where additional information is included - # in the response, e.g. application/json; charset=utf-8 - content_type, *_ = response.headers.get("content-type", "*").split(";") - if content_type != "application/json": - if is_basemodel(cast_type): - try: - data = response.json() - except Exception as exc: - log.debug("Could not read JSON from response data due to %s - %s", type(exc), exc) - else: - return self._client._process_response_data( - data=data, - cast_type=cast_type, # type: ignore - response=response, - ) - - if self._client._strict_response_validation: - raise APIResponseValidationError( - response=response, - message=f"Expected Content-Type response header to be `application/json` but received `{content_type}` instead.", # noqa: E501 - json_data=response.text, - ) - - # If the API responds with content that isn't JSON then we just return - # the (decoded) text without performing any parsing so that you can still - # handle the response however you need to. - return response.text # type: ignore - - data = response.json() - - return self._client._process_response_data( - data=data, - cast_type=cast_type, # type: ignore - response=response, - ) - - @property - def headers(self) -> httpx.Headers: - return self.http_response.headers - - @property - def http_request(self) -> httpx.Request: - """Returns the httpx Request instance associated with the current response.""" - return self.http_response.request - - @property - def status_code(self) -> int: - return self.http_response.status_code - - @property - def url(self) -> httpx.URL: - """Returns the URL for which the request was made.""" - return self.http_response.url - - @property - def method(self) -> str: - return self.http_request.method - - @property - def http_version(self) -> str: - return self.http_response.http_version - - @property - def elapsed(self) -> datetime.timedelta: - """The time taken for the complete request/response cycle to complete.""" - return self.http_response.elapsed - - @property - def is_closed(self) -> bool: - """Whether or not the response body has been closed. - - If this is False then there is response data that has not been read yet. - You must either fully consume the response body or call `.close()` - before discarding the response to prevent resource leaks. - """ - return self.http_response.is_closed - - @override - def __repr__(self) -> str: - return f"<{self.__class__.__name__} [{self.status_code} {self.http_response.reason_phrase}] type={self._cast_type}>" # noqa: E501 - - -class APIResponse(BaseAPIResponse[R]): - @property - def request_id(self) -> str | None: - return self.http_response.headers.get("x-request-id") # type: ignore[no-any-return] - - @overload - def parse(self, *, to: type[_T]) -> _T: ... - - @overload - def parse(self) -> R: ... - - def parse(self, *, to: type[_T] | None = None) -> R | _T: - """Returns the rich python representation of this response's data. - - For lower-level control, see `.read()`, `.json()`, `.iter_bytes()`. - - You can customize the type that the response is parsed into through - the `to` argument, e.g. - - ```py - from openai import BaseModel - - - class MyModel(BaseModel): - foo: str - - - obj = response.parse(to=MyModel) - print(obj.foo) - ``` - - We support parsing: - - `BaseModel` - - `dict` - - `list` - - `Union` - - `str` - - `int` - - `float` - - `httpx.Response` - """ - cache_key = to if to is not None else self._cast_type - cached = self._parsed_by_type.get(cache_key) - if cached is not None: - return cached # type: ignore[no-any-return] - - if not self._is_sse_stream: - self.read() - - parsed = self._parse(to=to) - if is_given(self._options.post_parser): - parsed = self._options.post_parser(parsed) - - self._parsed_by_type[cache_key] = parsed - return parsed - - def read(self) -> bytes: - """Read and return the binary response content.""" - try: - return self.http_response.read() - except httpx.StreamConsumed as exc: - # The default error raised by httpx isn't very - # helpful in our case so we re-raise it with - # a different error message. - raise StreamAlreadyConsumed() from exc - - def text(self) -> str: - """Read and decode the response content into a string.""" - self.read() - return self.http_response.text - - def json(self) -> object: - """Read and decode the JSON response content.""" - self.read() - return self.http_response.json() - - def close(self) -> None: - """Close the response and release the connection. - - Automatically called if the response body is read to completion. - """ - self.http_response.close() - - def iter_bytes(self, chunk_size: int | None = None) -> Iterator[bytes]: - """ - A byte-iterator over the decoded response content. - - This automatically handles gzip, deflate and brotli encoded responses. - """ - yield from self.http_response.iter_bytes(chunk_size) - - def iter_text(self, chunk_size: int | None = None) -> Iterator[str]: - """A str-iterator over the decoded response content - that handles both gzip, deflate, etc but also detects the content's - string encoding. - """ - yield from self.http_response.iter_text(chunk_size) - - def iter_lines(self) -> Iterator[str]: - """Like `iter_text()` but will only yield chunks for each line""" - yield from self.http_response.iter_lines() - - -class MissingStreamClassError(TypeError): - def __init__(self) -> None: - super().__init__( - "The `stream` argument was set to `True` but the `stream_cls` argument was not given. See `openai._streaming` for reference", # noqa: E501 - ) - - -class StreamAlreadyConsumed(ZhipuAIError): # noqa: N818 - """ - Attempted to read or stream content, but the content has already - been streamed. - - This can happen if you use a method like `.iter_lines()` and then attempt - to read th entire response body afterwards, e.g. - - ```py - response = await client.post(...) - async for line in response.iter_lines(): - ... # do something with `line` - - content = await response.read() - # ^ error - ``` - - If you want this behavior you'll need to either manually accumulate the response - content or call `await response.read()` before iterating over the stream. - """ - - def __init__(self) -> None: - message = ( - "Attempted to read or stream some content, but the content has " - "already been streamed. " - "This could be due to attempting to stream the response " - "content more than once." - "\n\n" - "You can fix this by manually accumulating the response content while streaming " - "or by calling `.read()` before starting to stream." - ) - super().__init__(message) - - -def extract_response_type(typ: type[BaseAPIResponse[Any]]) -> type: - """Given a type like `APIResponse[T]`, returns the generic type variable `T`. - - This also handles the case where a concrete subclass is given, e.g. - ```py - class MyResponse(APIResponse[bytes]): - ... - - extract_response_type(MyResponse) -> bytes - ``` - """ - return extract_type_var_from_base( - typ, - generic_bases=cast("tuple[type, ...]", (BaseAPIResponse, APIResponse)), - index=0, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_sse_client.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_sse_client.py deleted file mode 100644 index cbc449d24421d0..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_sse_client.py +++ /dev/null @@ -1,206 +0,0 @@ -from __future__ import annotations - -import inspect -import json -from collections.abc import Iterator, Mapping -from typing import TYPE_CHECKING, Generic, TypeGuard, cast - -import httpx - -from . import get_origin -from ._base_type import ResponseT -from ._errors import APIResponseError -from ._utils import extract_type_var_from_base, is_mapping - -_FIELD_SEPARATOR = ":" - -if TYPE_CHECKING: - from ._http_client import HttpClient - - -class StreamResponse(Generic[ResponseT]): - response: httpx.Response - _cast_type: type[ResponseT] - - def __init__( - self, - *, - cast_type: type[ResponseT], - response: httpx.Response, - client: HttpClient, - ) -> None: - self.response = response - self._cast_type = cast_type - self._data_process_func = client._process_response_data - self._stream_chunks = self.__stream__() - - def __next__(self) -> ResponseT: - return self._stream_chunks.__next__() - - def __iter__(self) -> Iterator[ResponseT]: - yield from self._stream_chunks - - def __stream__(self) -> Iterator[ResponseT]: - sse_line_parser = SSELineParser() - iterator = sse_line_parser.iter_lines(self.response.iter_lines()) - - for sse in iterator: - if sse.data.startswith("[DONE]"): - break - - if sse.event is None: - data = sse.json_data() - if isinstance(data, Mapping) and data.get("error"): - raise APIResponseError( - message="An error occurred during streaming", - request=self.response.request, - json_data=data["error"], - ) - if sse.event is None: - data = sse.json_data() - if is_mapping(data) and data.get("error"): - message = None - error = data.get("error") - if is_mapping(error): - message = error.get("message") - if not message or not isinstance(message, str): - message = "An error occurred during streaming" - - raise APIResponseError( - message=message, - request=self.response.request, - json_data=data["error"], - ) - yield self._data_process_func(data=data, cast_type=self._cast_type, response=self.response) - - else: - data = sse.json_data() - - if sse.event == "error" and is_mapping(data) and data.get("error"): - message = None - error = data.get("error") - if is_mapping(error): - message = error.get("message") - if not message or not isinstance(message, str): - message = "An error occurred during streaming" - - raise APIResponseError( - message=message, - request=self.response.request, - json_data=data["error"], - ) - yield self._data_process_func(data=data, cast_type=self._cast_type, response=self.response) - - for sse in iterator: - pass - - -class Event: - def __init__( - self, event: str | None = None, data: str | None = None, id: str | None = None, retry: int | None = None - ): - self._event = event - self._data = data - self._id = id - self._retry = retry - - def __repr__(self): - data_len = len(self._data) if self._data else 0 - return ( - f"Event(event={self._event}, data={self._data} ,data_length={data_len}, id={self._id}, retry={self._retry}" - ) - - @property - def event(self): - return self._event - - @property - def data(self): - return self._data - - def json_data(self): - return json.loads(self._data) - - @property - def id(self): - return self._id - - @property - def retry(self): - return self._retry - - -class SSELineParser: - _data: list[str] - _event: str | None - _retry: int | None - _id: str | None - - def __init__(self): - self._event = None - self._data = [] - self._id = None - self._retry = None - - def iter_lines(self, lines: Iterator[str]) -> Iterator[Event]: - for line in lines: - line = line.rstrip("\n") - if not line: - if self._event is None and not self._data and self._id is None and self._retry is None: - continue - sse_event = Event(event=self._event, data="\n".join(self._data), id=self._id, retry=self._retry) - self._event = None - self._data = [] - self._id = None - self._retry = None - - yield sse_event - self.decode_line(line) - - def decode_line(self, line: str): - if line.startswith(":") or not line: - return - - field, _p, value = line.partition(":") - - value = value.removeprefix(" ") - if field == "data": - self._data.append(value) - elif field == "event": - self._event = value - elif field == "retry": - try: - self._retry = int(value) - except (TypeError, ValueError): - pass - return - - -def is_stream_class_type(typ: type) -> TypeGuard[type[StreamResponse[object]]]: - """TypeGuard for determining whether or not the given type is a subclass of `Stream` / `AsyncStream`""" - origin = get_origin(typ) or typ - return inspect.isclass(origin) and issubclass(origin, StreamResponse) - - -def extract_stream_chunk_type( - stream_cls: type, - *, - failure_message: str | None = None, -) -> type: - """Given a type like `StreamResponse[T]`, returns the generic type variable `T`. - - This also handles the case where a concrete subclass is given, e.g. - ```py - class MyStream(StreamResponse[bytes]): - ... - - extract_stream_chunk_type(MyStream) -> bytes - ``` - """ - - return extract_type_var_from_base( - stream_cls, - index=0, - generic_bases=cast("tuple[type, ...]", (StreamResponse,)), - failure_message=failure_message, - ) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/__init__.py deleted file mode 100644 index a66b095816b8b0..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/__init__.py +++ /dev/null @@ -1,52 +0,0 @@ -from ._utils import ( # noqa: I001 - remove_notgiven_indict as remove_notgiven_indict, # noqa: PLC0414 - flatten as flatten, # noqa: PLC0414 - is_dict as is_dict, # noqa: PLC0414 - is_list as is_list, # noqa: PLC0414 - is_given as is_given, # noqa: PLC0414 - is_tuple as is_tuple, # noqa: PLC0414 - is_mapping as is_mapping, # noqa: PLC0414 - is_tuple_t as is_tuple_t, # noqa: PLC0414 - parse_date as parse_date, # noqa: PLC0414 - is_iterable as is_iterable, # noqa: PLC0414 - is_sequence as is_sequence, # noqa: PLC0414 - coerce_float as coerce_float, # noqa: PLC0414 - is_mapping_t as is_mapping_t, # noqa: PLC0414 - removeprefix as removeprefix, # noqa: PLC0414 - removesuffix as removesuffix, # noqa: PLC0414 - extract_files as extract_files, # noqa: PLC0414 - is_sequence_t as is_sequence_t, # noqa: PLC0414 - required_args as required_args, # noqa: PLC0414 - coerce_boolean as coerce_boolean, # noqa: PLC0414 - coerce_integer as coerce_integer, # noqa: PLC0414 - file_from_path as file_from_path, # noqa: PLC0414 - parse_datetime as parse_datetime, # noqa: PLC0414 - strip_not_given as strip_not_given, # noqa: PLC0414 - deepcopy_minimal as deepcopy_minimal, # noqa: PLC0414 - get_async_library as get_async_library, # noqa: PLC0414 - maybe_coerce_float as maybe_coerce_float, # noqa: PLC0414 - get_required_header as get_required_header, # noqa: PLC0414 - maybe_coerce_boolean as maybe_coerce_boolean, # noqa: PLC0414 - maybe_coerce_integer as maybe_coerce_integer, # noqa: PLC0414 - drop_prefix_image_data as drop_prefix_image_data, # noqa: PLC0414 -) - - -from ._typing import ( - is_list_type as is_list_type, # noqa: PLC0414 - is_union_type as is_union_type, # noqa: PLC0414 - extract_type_arg as extract_type_arg, # noqa: PLC0414 - is_iterable_type as is_iterable_type, # noqa: PLC0414 - is_required_type as is_required_type, # noqa: PLC0414 - is_annotated_type as is_annotated_type, # noqa: PLC0414 - strip_annotated_type as strip_annotated_type, # noqa: PLC0414 - extract_type_var_from_base as extract_type_var_from_base, # noqa: PLC0414 -) - -from ._transform import ( - PropertyInfo as PropertyInfo, # noqa: PLC0414 - transform as transform, # noqa: PLC0414 - async_transform as async_transform, # noqa: PLC0414 - maybe_transform as maybe_transform, # noqa: PLC0414 - async_maybe_transform as async_maybe_transform, # noqa: PLC0414 -) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_transform.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_transform.py deleted file mode 100644 index e8ef1f79358a96..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_transform.py +++ /dev/null @@ -1,383 +0,0 @@ -from __future__ import annotations - -import base64 -import io -import pathlib -from collections.abc import Mapping -from datetime import date, datetime -from typing import Any, Literal, TypeVar, cast, get_args, get_type_hints - -import anyio -import pydantic -from typing_extensions import override - -from .._base_compat import is_typeddict, model_dump -from .._files import is_base64_file_input -from ._typing import ( - extract_type_arg, - is_annotated_type, - is_iterable_type, - is_list_type, - is_required_type, - is_union_type, - strip_annotated_type, -) -from ._utils import ( - is_iterable, - is_list, - is_mapping, -) - -_T = TypeVar("_T") - - -# TODO: support for drilling globals() and locals() -# TODO: ensure works correctly with forward references in all cases - - -PropertyFormat = Literal["iso8601", "base64", "custom"] - - -class PropertyInfo: - """Metadata class to be used in Annotated types to provide information about a given type. - - For example: - - class MyParams(TypedDict): - account_holder_name: Annotated[str, PropertyInfo(alias='accountHolderName')] - - This means that {'account_holder_name': 'Robert'} will be transformed to {'accountHolderName': 'Robert'} before being sent to the API. - """ # noqa: E501 - - alias: str | None - format: PropertyFormat | None - format_template: str | None - discriminator: str | None - - def __init__( - self, - *, - alias: str | None = None, - format: PropertyFormat | None = None, - format_template: str | None = None, - discriminator: str | None = None, - ) -> None: - self.alias = alias - self.format = format - self.format_template = format_template - self.discriminator = discriminator - - @override - def __repr__(self) -> str: - return f"{self.__class__.__name__}(alias='{self.alias}', format={self.format}, format_template='{self.format_template}', discriminator='{self.discriminator}')" # noqa: E501 - - -def maybe_transform( - data: object, - expected_type: object, -) -> Any | None: - """Wrapper over `transform()` that allows `None` to be passed. - - See `transform()` for more details. - """ - if data is None: - return None - return transform(data, expected_type) - - -# Wrapper over _transform_recursive providing fake types -def transform( - data: _T, - expected_type: object, -) -> _T: - """Transform dictionaries based off of type information from the given type, for example: - - ```py - class Params(TypedDict, total=False): - card_id: Required[Annotated[str, PropertyInfo(alias="cardID")]] - - - transformed = transform({"card_id": ""}, Params) - # {'cardID': ''} - ``` - - Any keys / data that does not have type information given will be included as is. - - It should be noted that the transformations that this function does are not represented in the type system. - """ - transformed = _transform_recursive(data, annotation=cast(type, expected_type)) - return cast(_T, transformed) - - -def _get_annotated_type(type_: type) -> type | None: - """If the given type is an `Annotated` type then it is returned, if not `None` is returned. - - This also unwraps the type when applicable, e.g. `Required[Annotated[T, ...]]` - """ - if is_required_type(type_): - # Unwrap `Required[Annotated[T, ...]]` to `Annotated[T, ...]` - type_ = get_args(type_)[0] - - if is_annotated_type(type_): - return type_ - - return None - - -def _maybe_transform_key(key: str, type_: type) -> str: - """Transform the given `data` based on the annotations provided in `type_`. - - Note: this function only looks at `Annotated` types that contain `PropertInfo` metadata. - """ - annotated_type = _get_annotated_type(type_) - if annotated_type is None: - # no `Annotated` definition for this type, no transformation needed - return key - - # ignore the first argument as it is the actual type - annotations = get_args(annotated_type)[1:] - for annotation in annotations: - if isinstance(annotation, PropertyInfo) and annotation.alias is not None: - return annotation.alias - - return key - - -def _transform_recursive( - data: object, - *, - annotation: type, - inner_type: type | None = None, -) -> object: - """Transform the given data against the expected type. - - Args: - annotation: The direct type annotation given to the particular piece of data. - This may or may not be wrapped in metadata types, e.g. `Required[T]`, `Annotated[T, ...]` etc - - inner_type: If applicable, this is the "inside" type. This is useful in certain cases where the outside type - is a container type such as `List[T]`. In that case `inner_type` should be set to `T` so that each entry in - the list can be transformed using the metadata from the container type. - - Defaults to the same value as the `annotation` argument. - """ - if inner_type is None: - inner_type = annotation - - stripped_type = strip_annotated_type(inner_type) - if is_typeddict(stripped_type) and is_mapping(data): - return _transform_typeddict(data, stripped_type) - - if ( - # List[T] - (is_list_type(stripped_type) and is_list(data)) - # Iterable[T] - or (is_iterable_type(stripped_type) and is_iterable(data) and not isinstance(data, str)) - ): - inner_type = extract_type_arg(stripped_type, 0) - return [_transform_recursive(d, annotation=annotation, inner_type=inner_type) for d in data] - - if is_union_type(stripped_type): - # For union types we run the transformation against all subtypes to ensure that everything is transformed. - # - # TODO: there may be edge cases where the same normalized field name will transform to two different names - # in different subtypes. - for subtype in get_args(stripped_type): - data = _transform_recursive(data, annotation=annotation, inner_type=subtype) - return data - - if isinstance(data, pydantic.BaseModel): - return model_dump(data, exclude_unset=True) - - annotated_type = _get_annotated_type(annotation) - if annotated_type is None: - return data - - # ignore the first argument as it is the actual type - annotations = get_args(annotated_type)[1:] - for annotation in annotations: - if isinstance(annotation, PropertyInfo) and annotation.format is not None: - return _format_data(data, annotation.format, annotation.format_template) - - return data - - -def _format_data(data: object, format_: PropertyFormat, format_template: str | None) -> object: - if isinstance(data, date | datetime): - if format_ == "iso8601": - return data.isoformat() - - if format_ == "custom" and format_template is not None: - return data.strftime(format_template) - - if format_ == "base64" and is_base64_file_input(data): - binary: str | bytes | None = None - - if isinstance(data, pathlib.Path): - binary = data.read_bytes() - elif isinstance(data, io.IOBase): - binary = data.read() - - if isinstance(binary, str): # type: ignore[unreachable] - binary = binary.encode() - - if not isinstance(binary, bytes): - raise RuntimeError(f"Could not read bytes from {data}; Received {type(binary)}") - - return base64.b64encode(binary).decode("ascii") - - return data - - -def _transform_typeddict( - data: Mapping[str, object], - expected_type: type, -) -> Mapping[str, object]: - result: dict[str, object] = {} - annotations = get_type_hints(expected_type, include_extras=True) - for key, value in data.items(): - type_ = annotations.get(key) - if type_ is None: - # we do not have a type annotation for this field, leave it as is - result[key] = value - else: - result[_maybe_transform_key(key, type_)] = _transform_recursive(value, annotation=type_) - return result - - -async def async_maybe_transform( - data: object, - expected_type: object, -) -> Any | None: - """Wrapper over `async_transform()` that allows `None` to be passed. - - See `async_transform()` for more details. - """ - if data is None: - return None - return await async_transform(data, expected_type) - - -async def async_transform( - data: _T, - expected_type: object, -) -> _T: - """Transform dictionaries based off of type information from the given type, for example: - - ```py - class Params(TypedDict, total=False): - card_id: Required[Annotated[str, PropertyInfo(alias="cardID")]] - - - transformed = transform({"card_id": ""}, Params) - # {'cardID': ''} - ``` - - Any keys / data that does not have type information given will be included as is. - - It should be noted that the transformations that this function does are not represented in the type system. - """ - transformed = await _async_transform_recursive(data, annotation=cast(type, expected_type)) - return cast(_T, transformed) - - -async def _async_transform_recursive( - data: object, - *, - annotation: type, - inner_type: type | None = None, -) -> object: - """Transform the given data against the expected type. - - Args: - annotation: The direct type annotation given to the particular piece of data. - This may or may not be wrapped in metadata types, e.g. `Required[T]`, `Annotated[T, ...]` etc - - inner_type: If applicable, this is the "inside" type. This is useful in certain cases where the outside type - is a container type such as `List[T]`. In that case `inner_type` should be set to `T` so that each entry in - the list can be transformed using the metadata from the container type. - - Defaults to the same value as the `annotation` argument. - """ - if inner_type is None: - inner_type = annotation - - stripped_type = strip_annotated_type(inner_type) - if is_typeddict(stripped_type) and is_mapping(data): - return await _async_transform_typeddict(data, stripped_type) - - if ( - # List[T] - (is_list_type(stripped_type) and is_list(data)) - # Iterable[T] - or (is_iterable_type(stripped_type) and is_iterable(data) and not isinstance(data, str)) - ): - inner_type = extract_type_arg(stripped_type, 0) - return [await _async_transform_recursive(d, annotation=annotation, inner_type=inner_type) for d in data] - - if is_union_type(stripped_type): - # For union types we run the transformation against all subtypes to ensure that everything is transformed. - # - # TODO: there may be edge cases where the same normalized field name will transform to two different names - # in different subtypes. - for subtype in get_args(stripped_type): - data = await _async_transform_recursive(data, annotation=annotation, inner_type=subtype) - return data - - if isinstance(data, pydantic.BaseModel): - return model_dump(data, exclude_unset=True) - - annotated_type = _get_annotated_type(annotation) - if annotated_type is None: - return data - - # ignore the first argument as it is the actual type - annotations = get_args(annotated_type)[1:] - for annotation in annotations: - if isinstance(annotation, PropertyInfo) and annotation.format is not None: - return await _async_format_data(data, annotation.format, annotation.format_template) - - return data - - -async def _async_format_data(data: object, format_: PropertyFormat, format_template: str | None) -> object: - if isinstance(data, date | datetime): - if format_ == "iso8601": - return data.isoformat() - - if format_ == "custom" and format_template is not None: - return data.strftime(format_template) - - if format_ == "base64" and is_base64_file_input(data): - binary: str | bytes | None = None - - if isinstance(data, pathlib.Path): - binary = await anyio.Path(data).read_bytes() - elif isinstance(data, io.IOBase): - binary = data.read() - - if isinstance(binary, str): # type: ignore[unreachable] - binary = binary.encode() - - if not isinstance(binary, bytes): - raise RuntimeError(f"Could not read bytes from {data}; Received {type(binary)}") - - return base64.b64encode(binary).decode("ascii") - - return data - - -async def _async_transform_typeddict( - data: Mapping[str, object], - expected_type: type, -) -> Mapping[str, object]: - result: dict[str, object] = {} - annotations = get_type_hints(expected_type, include_extras=True) - for key, value in data.items(): - type_ = annotations.get(key) - if type_ is None: - # we do not have a type annotation for this field, leave it as is - result[key] = value - else: - result[_maybe_transform_key(key, type_)] = await _async_transform_recursive(value, annotation=type_) - return result diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_typing.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_typing.py deleted file mode 100644 index c7c54dcc37458d..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_typing.py +++ /dev/null @@ -1,122 +0,0 @@ -from __future__ import annotations - -from collections import abc as _c_abc -from collections.abc import Iterable -from typing import Annotated, Any, TypeVar, cast, get_args, get_origin - -from typing_extensions import Required - -from .._base_compat import is_union as _is_union -from .._base_type import InheritsGeneric - - -def is_annotated_type(typ: type) -> bool: - return get_origin(typ) == Annotated - - -def is_list_type(typ: type) -> bool: - return (get_origin(typ) or typ) == list - - -def is_iterable_type(typ: type) -> bool: - """If the given type is `typing.Iterable[T]`""" - origin = get_origin(typ) or typ - return origin in {Iterable, _c_abc.Iterable} - - -def is_union_type(typ: type) -> bool: - return _is_union(get_origin(typ)) - - -def is_required_type(typ: type) -> bool: - return get_origin(typ) == Required - - -def is_typevar(typ: type) -> bool: - # type ignore is required because type checkers - # think this expression will always return False - return type(typ) == TypeVar # type: ignore - - -# Extracts T from Annotated[T, ...] or from Required[Annotated[T, ...]] -def strip_annotated_type(typ: type) -> type: - if is_required_type(typ) or is_annotated_type(typ): - return strip_annotated_type(cast(type, get_args(typ)[0])) - - return typ - - -def extract_type_arg(typ: type, index: int) -> type: - args = get_args(typ) - try: - return cast(type, args[index]) - except IndexError as err: - raise RuntimeError(f"Expected type {typ} to have a type argument at index {index} but it did not") from err - - -def extract_type_var_from_base( - typ: type, - *, - generic_bases: tuple[type, ...], - index: int, - failure_message: str | None = None, -) -> type: - """Given a type like `Foo[T]`, returns the generic type variable `T`. - - This also handles the case where a concrete subclass is given, e.g. - ```py - class MyResponse(Foo[bytes]): - ... - - extract_type_var(MyResponse, bases=(Foo,), index=0) -> bytes - ``` - - And where a generic subclass is given: - ```py - _T = TypeVar('_T') - class MyResponse(Foo[_T]): - ... - - extract_type_var(MyResponse[bytes], bases=(Foo,), index=0) -> bytes - ``` - """ - cls = cast(object, get_origin(typ) or typ) - if cls in generic_bases: - # we're given the class directly - return extract_type_arg(typ, index) - - # if a subclass is given - # --- - # this is needed as __orig_bases__ is not present in the typeshed stubs - # because it is intended to be for internal use only, however there does - # not seem to be a way to resolve generic TypeVars for inherited subclasses - # without using it. - if isinstance(cls, InheritsGeneric): - target_base_class: Any | None = None - for base in cls.__orig_bases__: - if base.__origin__ in generic_bases: - target_base_class = base - break - - if target_base_class is None: - raise RuntimeError( - "Could not find the generic base class;\n" - "This should never happen;\n" - f"Does {cls} inherit from one of {generic_bases} ?" - ) - - extracted = extract_type_arg(target_base_class, index) - if is_typevar(extracted): - # If the extracted type argument is itself a type variable - # then that means the subclass itself is generic, so we have - # to resolve the type argument from the class itself, not - # the base class. - # - # Note: if there is more than 1 type argument, the subclass could - # change the ordering of the type arguments, this is not currently - # supported. - return extract_type_arg(typ, index) - - return extracted - - raise RuntimeError(failure_message or f"Could not resolve inner type variable at index {index} for {typ}") diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_utils.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_utils.py deleted file mode 100644 index ce5e7786aa2937..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/_utils/_utils.py +++ /dev/null @@ -1,409 +0,0 @@ -from __future__ import annotations - -import functools -import inspect -import os -import re -from collections.abc import Callable, Iterable, Mapping, Sequence -from pathlib import Path -from typing import ( - Any, - TypeGuard, - TypeVar, - Union, - cast, - overload, -) - -import sniffio - -from .._base_compat import parse_date as parse_date # noqa: PLC0414 -from .._base_compat import parse_datetime as parse_datetime # noqa: PLC0414 -from .._base_type import FileTypes, Headers, HeadersLike, NotGiven, NotGivenOr - - -def remove_notgiven_indict(obj): - if obj is None or (not isinstance(obj, Mapping)): - return obj - return {key: value for key, value in obj.items() if not isinstance(value, NotGiven)} - - -_T = TypeVar("_T") -_TupleT = TypeVar("_TupleT", bound=tuple[object, ...]) -_MappingT = TypeVar("_MappingT", bound=Mapping[str, object]) -_SequenceT = TypeVar("_SequenceT", bound=Sequence[object]) -CallableT = TypeVar("CallableT", bound=Callable[..., Any]) - - -def flatten(t: Iterable[Iterable[_T]]) -> list[_T]: - return [item for sublist in t for item in sublist] - - -def extract_files( - # TODO: this needs to take Dict but variance issues..... - # create protocol type ? - query: Mapping[str, object], - *, - paths: Sequence[Sequence[str]], -) -> list[tuple[str, FileTypes]]: - """Recursively extract files from the given dictionary based on specified paths. - - A path may look like this ['foo', 'files', '', 'data']. - - Note: this mutates the given dictionary. - """ - files: list[tuple[str, FileTypes]] = [] - for path in paths: - files.extend(_extract_items(query, path, index=0, flattened_key=None)) - return files - - -def _extract_items( - obj: object, - path: Sequence[str], - *, - index: int, - flattened_key: str | None, -) -> list[tuple[str, FileTypes]]: - try: - key = path[index] - except IndexError: - if isinstance(obj, NotGiven): - # no value was provided - we can safely ignore - return [] - - # cyclical import - from .._files import assert_is_file_content - - # We have exhausted the path, return the entry we found. - assert_is_file_content(obj, key=flattened_key) - assert flattened_key is not None - return [(flattened_key, cast(FileTypes, obj))] - - index += 1 - if is_dict(obj): - try: - # We are at the last entry in the path so we must remove the field - if (len(path)) == index: - item = obj.pop(key) - else: - item = obj[key] - except KeyError: - # Key was not present in the dictionary, this is not indicative of an error - # as the given path may not point to a required field. We also do not want - # to enforce required fields as the API may differ from the spec in some cases. - return [] - if flattened_key is None: - flattened_key = key - else: - flattened_key += f"[{key}]" - return _extract_items( - item, - path, - index=index, - flattened_key=flattened_key, - ) - elif is_list(obj): - if key != "": - return [] - - return flatten( - [ - _extract_items( - item, - path, - index=index, - flattened_key=flattened_key + "[]" if flattened_key is not None else "[]", - ) - for item in obj - ] - ) - - # Something unexpected was passed, just ignore it. - return [] - - -def is_given(obj: NotGivenOr[_T]) -> TypeGuard[_T]: - return not isinstance(obj, NotGiven) - - -# Type safe methods for narrowing types with TypeVars. -# The default narrowing for isinstance(obj, dict) is dict[unknown, unknown], -# however this cause Pyright to rightfully report errors. As we know we don't -# care about the contained types we can safely use `object` in it's place. -# -# There are two separate functions defined, `is_*` and `is_*_t` for different use cases. -# `is_*` is for when you're dealing with an unknown input -# `is_*_t` is for when you're narrowing a known union type to a specific subset - - -def is_tuple(obj: object) -> TypeGuard[tuple[object, ...]]: - return isinstance(obj, tuple) - - -def is_tuple_t(obj: _TupleT | object) -> TypeGuard[_TupleT]: - return isinstance(obj, tuple) - - -def is_sequence(obj: object) -> TypeGuard[Sequence[object]]: - return isinstance(obj, Sequence) - - -def is_sequence_t(obj: _SequenceT | object) -> TypeGuard[_SequenceT]: - return isinstance(obj, Sequence) - - -def is_mapping(obj: object) -> TypeGuard[Mapping[str, object]]: - return isinstance(obj, Mapping) - - -def is_mapping_t(obj: _MappingT | object) -> TypeGuard[_MappingT]: - return isinstance(obj, Mapping) - - -def is_dict(obj: object) -> TypeGuard[dict[object, object]]: - return isinstance(obj, dict) - - -def is_list(obj: object) -> TypeGuard[list[object]]: - return isinstance(obj, list) - - -def is_iterable(obj: object) -> TypeGuard[Iterable[object]]: - return isinstance(obj, Iterable) - - -def deepcopy_minimal(item: _T) -> _T: - """Minimal reimplementation of copy.deepcopy() that will only copy certain object types: - - - mappings, e.g. `dict` - - list - - This is done for performance reasons. - """ - if is_mapping(item): - return cast(_T, {k: deepcopy_minimal(v) for k, v in item.items()}) - if is_list(item): - return cast(_T, [deepcopy_minimal(entry) for entry in item]) - return item - - -# copied from https://github.com/Rapptz/RoboDanny -def human_join(seq: Sequence[str], *, delim: str = ", ", final: str = "or") -> str: - size = len(seq) - if size == 0: - return "" - - if size == 1: - return seq[0] - - if size == 2: - return f"{seq[0]} {final} {seq[1]}" - - return delim.join(seq[:-1]) + f" {final} {seq[-1]}" - - -def quote(string: str) -> str: - """Add single quotation marks around the given string. Does *not* do any escaping.""" - return f"'{string}'" - - -def required_args(*variants: Sequence[str]) -> Callable[[CallableT], CallableT]: - """Decorator to enforce a given set of arguments or variants of arguments are passed to the decorated function. - - Useful for enforcing runtime validation of overloaded functions. - - Example usage: - ```py - @overload - def foo(*, a: str) -> str: - ... - - - @overload - def foo(*, b: bool) -> str: - ... - - - # This enforces the same constraints that a static type checker would - # i.e. that either a or b must be passed to the function - @required_args(["a"], ["b"]) - def foo(*, a: str | None = None, b: bool | None = None) -> str: - ... - ``` - """ - - def inner(func: CallableT) -> CallableT: - params = inspect.signature(func).parameters - positional = [ - name - for name, param in params.items() - if param.kind - in { - param.POSITIONAL_ONLY, - param.POSITIONAL_OR_KEYWORD, - } - ] - - @functools.wraps(func) - def wrapper(*args: object, **kwargs: object) -> object: - given_params: set[str] = set() - for i, _ in enumerate(args): - try: - given_params.add(positional[i]) - except IndexError: - raise TypeError( - f"{func.__name__}() takes {len(positional)} argument(s) but {len(args)} were given" - ) from None - - given_params.update(kwargs.keys()) - - for variant in variants: - matches = all(param in given_params for param in variant) - if matches: - break - else: # no break - if len(variants) > 1: - variations = human_join( - ["(" + human_join([quote(arg) for arg in variant], final="and") + ")" for variant in variants] - ) - msg = f"Missing required arguments; Expected either {variations} arguments to be given" - else: - # TODO: this error message is not deterministic - missing = list(set(variants[0]) - given_params) - if len(missing) > 1: - msg = f"Missing required arguments: {human_join([quote(arg) for arg in missing])}" - else: - msg = f"Missing required argument: {quote(missing[0])}" - raise TypeError(msg) - return func(*args, **kwargs) - - return wrapper # type: ignore - - return inner - - -_K = TypeVar("_K") -_V = TypeVar("_V") - - -@overload -def strip_not_given(obj: None) -> None: ... - - -@overload -def strip_not_given(obj: Mapping[_K, _V | NotGiven]) -> dict[_K, _V]: ... - - -@overload -def strip_not_given(obj: object) -> object: ... - - -def strip_not_given(obj: object | None) -> object: - """Remove all top-level keys where their values are instances of `NotGiven`""" - if obj is None: - return None - - if not is_mapping(obj): - return obj - - return {key: value for key, value in obj.items() if not isinstance(value, NotGiven)} - - -def coerce_integer(val: str) -> int: - return int(val, base=10) - - -def coerce_float(val: str) -> float: - return float(val) - - -def coerce_boolean(val: str) -> bool: - return val in {"true", "1", "on"} - - -def maybe_coerce_integer(val: str | None) -> int | None: - if val is None: - return None - return coerce_integer(val) - - -def maybe_coerce_float(val: str | None) -> float | None: - if val is None: - return None - return coerce_float(val) - - -def maybe_coerce_boolean(val: str | None) -> bool | None: - if val is None: - return None - return coerce_boolean(val) - - -def removeprefix(string: str, prefix: str) -> str: - """Remove a prefix from a string. - - Backport of `str.removeprefix` for Python < 3.9 - """ - if string.startswith(prefix): - return string[len(prefix) :] - return string - - -def removesuffix(string: str, suffix: str) -> str: - """Remove a suffix from a string. - - Backport of `str.removesuffix` for Python < 3.9 - """ - if string.endswith(suffix): - return string[: -len(suffix)] - return string - - -def file_from_path(path: str) -> FileTypes: - contents = Path(path).read_bytes() - file_name = os.path.basename(path) - return (file_name, contents) - - -def get_required_header(headers: HeadersLike, header: str) -> str: - lower_header = header.lower() - if isinstance(headers, Mapping): - headers = cast(Headers, headers) - for k, v in headers.items(): - if k.lower() == lower_header and isinstance(v, str): - return v - - """ to deal with the case where the header looks like Stainless-Event-Id """ - intercaps_header = re.sub(r"([^\w])(\w)", lambda pat: pat.group(1) + pat.group(2).upper(), header.capitalize()) - - for normalized_header in [header, lower_header, header.upper(), intercaps_header]: - value = headers.get(normalized_header) - if value: - return value - - raise ValueError(f"Could not find {header} header") - - -def get_async_library() -> str: - try: - return sniffio.current_async_library() - except Exception: - return "false" - - -def drop_prefix_image_data(content: Union[str, list[dict]]) -> Union[str, list[dict]]: - """ - 删除 ;base64, 前缀 - :param image_data: - :return: - """ - if isinstance(content, list): - for data in content: - if data.get("type") == "image_url": - image_data = data.get("image_url").get("url") - if image_data.startswith("data:image/"): - image_data = image_data.split("base64,")[-1] - data["image_url"]["url"] = image_data - - return content diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/logs.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/logs.py deleted file mode 100644 index e5fce94c00e9e0..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/logs.py +++ /dev/null @@ -1,78 +0,0 @@ -import logging -import os -import time - -logger = logging.getLogger(__name__) - - -class LoggerNameFilter(logging.Filter): - def filter(self, record): - # return record.name.startswith("loom_core") or record.name in "ERROR" or ( - # record.name.startswith("uvicorn.error") - # and record.getMessage().startswith("Uvicorn running on") - # ) - return True - - -def get_log_file(log_path: str, sub_dir: str): - """ - sub_dir should contain a timestamp. - """ - log_dir = os.path.join(log_path, sub_dir) - # Here should be creating a new directory each time, so `exist_ok=False` - os.makedirs(log_dir, exist_ok=False) - return os.path.join(log_dir, "zhipuai.log") - - -def get_config_dict(log_level: str, log_file_path: str, log_backup_count: int, log_max_bytes: int) -> dict: - # for windows, the path should be a raw string. - log_file_path = log_file_path.encode("unicode-escape").decode() if os.name == "nt" else log_file_path - log_level = log_level.upper() - config_dict = { - "version": 1, - "disable_existing_loggers": False, - "formatters": { - "formatter": {"format": ("%(asctime)s %(name)-12s %(process)d %(levelname)-8s %(message)s")}, - }, - "filters": { - "logger_name_filter": { - "()": __name__ + ".LoggerNameFilter", - }, - }, - "handlers": { - "stream_handler": { - "class": "logging.StreamHandler", - "formatter": "formatter", - "level": log_level, - # "stream": "ext://sys.stdout", - # "filters": ["logger_name_filter"], - }, - "file_handler": { - "class": "logging.handlers.RotatingFileHandler", - "formatter": "formatter", - "level": log_level, - "filename": log_file_path, - "mode": "a", - "maxBytes": log_max_bytes, - "backupCount": log_backup_count, - "encoding": "utf8", - }, - }, - "loggers": { - "loom_core": { - "handlers": ["stream_handler", "file_handler"], - "level": log_level, - "propagate": False, - } - }, - "root": { - "level": log_level, - "handlers": ["stream_handler", "file_handler"], - }, - } - return config_dict - - -def get_timestamp_ms(): - t = time.time() - return int(round(t * 1000)) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/pagination.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/pagination.py deleted file mode 100644 index 7f0b1b91d98556..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/core/pagination.py +++ /dev/null @@ -1,62 +0,0 @@ -# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details. - -from typing import Any, Generic, Optional, TypeVar, cast - -from typing_extensions import Protocol, override, runtime_checkable - -from ._http_client import BasePage, BaseSyncPage, PageInfo - -__all__ = ["SyncPage", "SyncCursorPage"] - -_T = TypeVar("_T") - - -@runtime_checkable -class CursorPageItem(Protocol): - id: Optional[str] - - -class SyncPage(BaseSyncPage[_T], BasePage[_T], Generic[_T]): - """Note: no pagination actually occurs yet, this is for forwards-compatibility.""" - - data: list[_T] - object: str - - @override - def _get_page_items(self) -> list[_T]: - data = self.data - if not data: - return [] - return data - - @override - def next_page_info(self) -> None: - """ - This page represents a response that isn't actually paginated at the API level - so there will never be a next page. - """ - return None - - -class SyncCursorPage(BaseSyncPage[_T], BasePage[_T], Generic[_T]): - data: list[_T] - - @override - def _get_page_items(self) -> list[_T]: - data = self.data - if not data: - return [] - return data - - @override - def next_page_info(self) -> Optional[PageInfo]: - data = self.data - if not data: - return None - - item = cast(Any, data[-1]) - if not isinstance(item, CursorPageItem) or item.id is None: - # TODO emit warning log - return None - - return PageInfo(params={"after": item.id}) diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/__init__.py deleted file mode 100644 index 9f941fb91c8776..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from .assistant_completion import AssistantCompletion - -__all__ = [ - "AssistantCompletion", -] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_completion.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_completion.py deleted file mode 100644 index cbfb6edaeb1f19..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_completion.py +++ /dev/null @@ -1,40 +0,0 @@ -from typing import Any, Optional - -from ...core import BaseModel -from .message import MessageContent - -__all__ = ["AssistantCompletion", "CompletionUsage"] - - -class ErrorInfo(BaseModel): - code: str # 错误码 - message: str # 错误信息 - - -class AssistantChoice(BaseModel): - index: int # 结果下标 - delta: MessageContent # 当前会话输出消息体 - finish_reason: str - """ - # 推理结束原因 stop代表推理自然结束或触发停止词。 sensitive 代表模型推理内容被安全审核接口拦截。请注意，针对此类内容，请用户自行判断并决定是否撤回已公开的内容。 - # network_error 代表模型推理服务异常。 - """ # noqa: E501 - metadata: dict # 元信息，拓展字段 - - -class CompletionUsage(BaseModel): - prompt_tokens: int # 输入的 tokens 数量 - completion_tokens: int # 输出的 tokens 数量 - total_tokens: int # 总 tokens 数量 - - -class AssistantCompletion(BaseModel): - id: str # 请求 ID - conversation_id: str # 会话 ID - assistant_id: str # 智能体 ID - created: int # 请求创建时间，Unix 时间戳 - status: str # 返回状态，包括：`completed` 表示生成结束`in_progress`表示生成中 `failed` 表示生成异常 - last_error: Optional[ErrorInfo] # 异常信息 - choices: list[AssistantChoice] # 增量返回的信息 - metadata: Optional[dict[str, Any]] # 元信息，拓展字段 - usage: Optional[CompletionUsage] # tokens 数量统计 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_conversation_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_conversation_params.py deleted file mode 100644 index 03f14f4238f37f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_conversation_params.py +++ /dev/null @@ -1,7 +0,0 @@ -from typing import TypedDict - - -class ConversationParameters(TypedDict, total=False): - assistant_id: str # 智能体 ID - page: int # 当前分页 - page_size: int # 分页数量 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_conversation_resp.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_conversation_resp.py deleted file mode 100644 index d1833d220a2e3b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_conversation_resp.py +++ /dev/null @@ -1,29 +0,0 @@ -from ...core import BaseModel - -__all__ = ["ConversationUsageListResp"] - - -class Usage(BaseModel): - prompt_tokens: int # 用户输入的 tokens 数量 - completion_tokens: int # 模型输入的 tokens 数量 - total_tokens: int # 总 tokens 数量 - - -class ConversationUsage(BaseModel): - id: str # 会话 id - assistant_id: str # 智能体Assistant id - create_time: int # 创建时间 - update_time: int # 更新时间 - usage: Usage # 会话中 tokens 数量统计 - - -class ConversationUsageList(BaseModel): - assistant_id: str # 智能体id - has_more: bool # 是否还有更多页 - conversation_list: list[ConversationUsage] # 返回的 - - -class ConversationUsageListResp(BaseModel): - code: int - msg: str - data: ConversationUsageList diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_create_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_create_params.py deleted file mode 100644 index 2def1025cd2b33..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_create_params.py +++ /dev/null @@ -1,32 +0,0 @@ -from typing import Optional, TypedDict, Union - - -class AssistantAttachments: - file_id: str - - -class MessageTextContent: - type: str # 目前支持 type = text - text: str - - -MessageContent = Union[MessageTextContent] - - -class ConversationMessage(TypedDict): - """会话消息体""" - - role: str # 用户的输入角色，例如 'user' - content: list[MessageContent] # 会话消息体的内容 - - -class AssistantParameters(TypedDict, total=False): - """智能体参数类""" - - assistant_id: str # 智能体 ID - conversation_id: Optional[str] # 会话 ID，不传则创建新会话 - model: str # 模型名称，默认为 'GLM-4-Assistant' - stream: bool # 是否支持流式 SSE，需要传入 True - messages: list[ConversationMessage] # 会话消息体 - attachments: Optional[list[AssistantAttachments]] # 会话指定的文件，非必填 - metadata: Optional[dict] # 元信息，拓展字段，非必填 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_support_resp.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_support_resp.py deleted file mode 100644 index 0709cdbcad25e1..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/assistant_support_resp.py +++ /dev/null @@ -1,21 +0,0 @@ -from ...core import BaseModel - -__all__ = ["AssistantSupportResp"] - - -class AssistantSupport(BaseModel): - assistant_id: str # 智能体的 Assistant id，用于智能体会话 - created_at: int # 创建时间 - updated_at: int # 更新时间 - name: str # 智能体名称 - avatar: str # 智能体头像 - description: str # 智能体描述 - status: str # 智能体状态，目前只有 publish - tools: list[str] # 智能体支持的工具名 - starter_prompts: list[str] # 智能体启动推荐的 prompt - - -class AssistantSupportResp(BaseModel): - code: int - msg: str - data: list[AssistantSupport] # 智能体列表 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/__init__.py deleted file mode 100644 index 562e0151e53b48..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .message_content import MessageContent - -__all__ = ["MessageContent"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/message_content.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/message_content.py deleted file mode 100644 index 6a1a438a6fe03d..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/message_content.py +++ /dev/null @@ -1,13 +0,0 @@ -from typing import Annotated, TypeAlias, Union - -from ....core._utils import PropertyInfo -from .text_content_block import TextContentBlock -from .tools_delta_block import ToolsDeltaBlock - -__all__ = ["MessageContent"] - - -MessageContent: TypeAlias = Annotated[ - Union[ToolsDeltaBlock, TextContentBlock], - PropertyInfo(discriminator="type"), -] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/text_content_block.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/text_content_block.py deleted file mode 100644 index 865fb1139e2f75..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/text_content_block.py +++ /dev/null @@ -1,14 +0,0 @@ -from typing import Literal - -from ....core import BaseModel - -__all__ = ["TextContentBlock"] - - -class TextContentBlock(BaseModel): - content: str - - role: str = "assistant" - - type: Literal["content"] = "content" - """Always `content`.""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/code_interpreter_delta_block.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/code_interpreter_delta_block.py deleted file mode 100644 index 9d569b282ef9f7..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/code_interpreter_delta_block.py +++ /dev/null @@ -1,27 +0,0 @@ -from typing import Literal - -__all__ = ["CodeInterpreterToolBlock"] - -from .....core import BaseModel - - -class CodeInterpreterToolOutput(BaseModel): - """代码工具输出结果""" - - type: str # 代码执行日志，目前只有 logs - logs: str # 代码执行的日志结果 - error_msg: str # 错误信息 - - -class CodeInterpreter(BaseModel): - """代码解释器""" - - input: str # 生成的代码片段，输入给代码沙盒 - outputs: list[CodeInterpreterToolOutput] # 代码执行后的输出结果 - - -class CodeInterpreterToolBlock(BaseModel): - """代码工具块""" - - code_interpreter: CodeInterpreter # 代码解释器对象 - type: Literal["code_interpreter"] # 调用工具的类型，始终为 `code_interpreter` diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/drawing_tool_delta_block.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/drawing_tool_delta_block.py deleted file mode 100644 index 0b6895556b6164..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/drawing_tool_delta_block.py +++ /dev/null @@ -1,21 +0,0 @@ -from typing import Literal - -from .....core import BaseModel - -__all__ = ["DrawingToolBlock"] - - -class DrawingToolOutput(BaseModel): - image: str - - -class DrawingTool(BaseModel): - input: str - outputs: list[DrawingToolOutput] - - -class DrawingToolBlock(BaseModel): - drawing_tool: DrawingTool - - type: Literal["drawing_tool"] - """Always `drawing_tool`.""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/function_delta_block.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/function_delta_block.py deleted file mode 100644 index c439bc4b3fbbb8..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/function_delta_block.py +++ /dev/null @@ -1,22 +0,0 @@ -from typing import Literal, Union - -__all__ = ["FunctionToolBlock"] - -from .....core import BaseModel - - -class FunctionToolOutput(BaseModel): - content: str - - -class FunctionTool(BaseModel): - name: str - arguments: Union[str, dict] - outputs: list[FunctionToolOutput] - - -class FunctionToolBlock(BaseModel): - function: FunctionTool - - type: Literal["function"] - """Always `drawing_tool`.""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/retrieval_delta_black.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/retrieval_delta_black.py deleted file mode 100644 index 4789e9378a8a39..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/retrieval_delta_black.py +++ /dev/null @@ -1,41 +0,0 @@ -from typing import Literal - -from .....core import BaseModel - - -class RetrievalToolOutput(BaseModel): - """ - This class represents the output of a retrieval tool. - - Attributes: - - text (str): The text snippet retrieved from the knowledge base. - - document (str): The name of the document from which the text snippet was retrieved, returned only in intelligent configuration. - """ # noqa: E501 - - text: str - document: str - - -class RetrievalTool(BaseModel): - """ - This class represents the outputs of a retrieval tool. - - Attributes: - - outputs (List[RetrievalToolOutput]): A list of text snippets and their respective document names retrieved from the knowledge base. - """ # noqa: E501 - - outputs: list[RetrievalToolOutput] - - -class RetrievalToolBlock(BaseModel): - """ - This class represents a block for invoking the retrieval tool. - - Attributes: - - retrieval (RetrievalTool): An instance of the RetrievalTool class containing the retrieval outputs. - - type (Literal["retrieval"]): The type of tool being used, always set to "retrieval". - """ - - retrieval: RetrievalTool - type: Literal["retrieval"] - """Always `retrieval`.""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/tools_type.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/tools_type.py deleted file mode 100644 index 98544053d4c83a..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/tools_type.py +++ /dev/null @@ -1,16 +0,0 @@ -from typing import Annotated, TypeAlias, Union - -from .....core._utils import PropertyInfo -from .code_interpreter_delta_block import CodeInterpreterToolBlock -from .drawing_tool_delta_block import DrawingToolBlock -from .function_delta_block import FunctionToolBlock -from .retrieval_delta_black import RetrievalToolBlock -from .web_browser_delta_block import WebBrowserToolBlock - -__all__ = ["ToolsType"] - - -ToolsType: TypeAlias = Annotated[ - Union[DrawingToolBlock, CodeInterpreterToolBlock, WebBrowserToolBlock, RetrievalToolBlock, FunctionToolBlock], - PropertyInfo(discriminator="type"), -] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/web_browser_delta_block.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/web_browser_delta_block.py deleted file mode 100644 index 966e6fe0c84fef..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools/web_browser_delta_block.py +++ /dev/null @@ -1,48 +0,0 @@ -from typing import Literal - -from .....core import BaseModel - -__all__ = ["WebBrowserToolBlock"] - - -class WebBrowserOutput(BaseModel): - """ - This class represents the output of a web browser search result. - - Attributes: - - title (str): The title of the search result. - - link (str): The URL link to the search result's webpage. - - content (str): The textual content extracted from the search result. - - error_msg (str): Any error message encountered during the search or retrieval process. - """ - - title: str - link: str - content: str - error_msg: str - - -class WebBrowser(BaseModel): - """ - This class represents the input and outputs of a web browser search. - - Attributes: - - input (str): The input query for the web browser search. - - outputs (List[WebBrowserOutput]): A list of search results returned by the web browser. - """ - - input: str - outputs: list[WebBrowserOutput] - - -class WebBrowserToolBlock(BaseModel): - """ - This class represents a block for invoking the web browser tool. - - Attributes: - - web_browser (WebBrowser): An instance of the WebBrowser class containing the search input and outputs. - - type (Literal["web_browser"]): The type of tool being used, always set to "web_browser". - """ - - web_browser: WebBrowser - type: Literal["web_browser"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools_delta_block.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools_delta_block.py deleted file mode 100644 index 781a1ab819c286..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/assistant/message/tools_delta_block.py +++ /dev/null @@ -1,16 +0,0 @@ -from typing import Literal - -from ....core import BaseModel -from .tools.tools_type import ToolsType - -__all__ = ["ToolsDeltaBlock"] - - -class ToolsDeltaBlock(BaseModel): - tool_calls: list[ToolsType] - """The index of the content part in the message.""" - - role: str = "tool" - - type: Literal["tool_calls"] = "tool_calls" - """Always `tool_calls`.""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch.py deleted file mode 100644 index 560562915c9d32..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch.py +++ /dev/null @@ -1,82 +0,0 @@ -# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details. - -import builtins -from typing import Literal, Optional - -from ..core import BaseModel -from .batch_error import BatchError -from .batch_request_counts import BatchRequestCounts - -__all__ = ["Batch", "Errors"] - - -class Errors(BaseModel): - data: Optional[list[BatchError]] = None - - object: Optional[str] = None - """这个类型，一直是`list`。""" - - -class Batch(BaseModel): - id: str - - completion_window: str - """用于执行请求的地址信息。""" - - created_at: int - """这是 Unix timestamp (in seconds) 表示的创建时间。""" - - endpoint: str - """这是ZhipuAI endpoint的地址。""" - - input_file_id: str - """标记为batch的输入文件的ID。""" - - object: Literal["batch"] - """这个类型，一直是`batch`.""" - - status: Literal[ - "validating", "failed", "in_progress", "finalizing", "completed", "expired", "cancelling", "cancelled" - ] - """batch 的状态。""" - - cancelled_at: Optional[int] = None - """Unix timestamp (in seconds) 表示的取消时间。""" - - cancelling_at: Optional[int] = None - """Unix timestamp (in seconds) 表示发起取消的请求时间 """ - - completed_at: Optional[int] = None - """Unix timestamp (in seconds) 表示的完成时间。""" - - error_file_id: Optional[str] = None - """这个文件id包含了执行请求失败的请求的输出。""" - - errors: Optional[Errors] = None - - expired_at: Optional[int] = None - """Unix timestamp (in seconds) 表示的将在过期时间。""" - - expires_at: Optional[int] = None - """Unix timestamp (in seconds) 触发过期""" - - failed_at: Optional[int] = None - """Unix timestamp (in seconds) 表示的失败时间。""" - - finalizing_at: Optional[int] = None - """Unix timestamp (in seconds) 表示的最终时间。""" - - in_progress_at: Optional[int] = None - """Unix timestamp (in seconds) 表示的开始处理时间。""" - - metadata: Optional[builtins.object] = None - """ - key:value形式的元数据，以便将信息存储 - 结构化格式。键的长度是64个字符，值最长512个字符 - """ - - output_file_id: Optional[str] = None - """完成请求的输出文件的ID。""" - - request_counts: Optional[BatchRequestCounts] = None - """批次中不同状态的请求计数""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_create_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_create_params.py deleted file mode 100644 index 3dae65ea46fcbe..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_create_params.py +++ /dev/null @@ -1,37 +0,0 @@ -from __future__ import annotations - -from typing import Literal, Optional - -from typing_extensions import Required, TypedDict - -__all__ = ["BatchCreateParams"] - - -class BatchCreateParams(TypedDict, total=False): - completion_window: Required[str] - """The time frame within which the batch should be processed. - - Currently only `24h` is supported. - """ - - endpoint: Required[Literal["/v1/chat/completions", "/v1/embeddings"]] - """The endpoint to be used for all requests in the batch. - - Currently `/v1/chat/completions` and `/v1/embeddings` are supported. - """ - - input_file_id: Required[str] - """The ID of an uploaded file that contains requests for the new batch. - - See [upload file](https://platform.openai.com/docs/api-reference/files/create) - for how to upload a file. - - Your input file must be formatted as a - [JSONL file](https://platform.openai.com/docs/api-reference/batch/requestInput), - and must be uploaded with the purpose `batch`. - """ - - metadata: Optional[dict[str, str]] - """Optional custom metadata for the batch.""" - - auto_delete_input_file: Optional[bool] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_error.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_error.py deleted file mode 100644 index f934db19781e41..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_error.py +++ /dev/null @@ -1,21 +0,0 @@ -# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details. - -from typing import Optional - -from ..core import BaseModel - -__all__ = ["BatchError"] - - -class BatchError(BaseModel): - code: Optional[str] = None - """定义的业务错误码""" - - line: Optional[int] = None - """文件中的行号""" - - message: Optional[str] = None - """关于对话文件中的错误的描述""" - - param: Optional[str] = None - """参数名称，如果有的话""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_list_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_list_params.py deleted file mode 100644 index 1a681671320eca..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_list_params.py +++ /dev/null @@ -1,20 +0,0 @@ -from __future__ import annotations - -from typing_extensions import TypedDict - -__all__ = ["BatchListParams"] - - -class BatchListParams(TypedDict, total=False): - after: str - """分页的游标，用于获取下一页的数据。 - - `after` 是一个指向当前页面的游标，用于获取下一页的数据。如果没有提供 `after`，则返回第一页的数据。 - list. - """ - - limit: int - """这个参数用于限制返回的结果数量。 - - Limit 用于限制返回的结果数量。默认值为 10 - """ diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_request_counts.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_request_counts.py deleted file mode 100644 index ca3ccae625052b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/batch_request_counts.py +++ /dev/null @@ -1,14 +0,0 @@ -from ..core import BaseModel - -__all__ = ["BatchRequestCounts"] - - -class BatchRequestCounts(BaseModel): - completed: int - """这个数字表示已经完成的请求。""" - - failed: int - """这个数字表示失败的请求。""" - - total: int - """这个数字表示总的请求。""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/async_chat_completion.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/async_chat_completion.py deleted file mode 100644 index c1eed070f32d9f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/async_chat_completion.py +++ /dev/null @@ -1,22 +0,0 @@ -from typing import Optional - -from ...core import BaseModel -from .chat_completion import CompletionChoice, CompletionUsage - -__all__ = ["AsyncTaskStatus", "AsyncCompletion"] - - -class AsyncTaskStatus(BaseModel): - id: Optional[str] = None - request_id: Optional[str] = None - model: Optional[str] = None - task_status: Optional[str] = None - - -class AsyncCompletion(BaseModel): - id: Optional[str] = None - request_id: Optional[str] = None - model: Optional[str] = None - task_status: str - choices: list[CompletionChoice] - usage: CompletionUsage diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completion.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completion.py deleted file mode 100644 index 1945a826cda2d0..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completion.py +++ /dev/null @@ -1,43 +0,0 @@ -from typing import Optional - -from ...core import BaseModel - -__all__ = ["Completion", "CompletionUsage"] - - -class Function(BaseModel): - arguments: str - name: str - - -class CompletionMessageToolCall(BaseModel): - id: str - function: Function - type: str - - -class CompletionMessage(BaseModel): - content: Optional[str] = None - role: str - tool_calls: Optional[list[CompletionMessageToolCall]] = None - - -class CompletionUsage(BaseModel): - prompt_tokens: int - completion_tokens: int - total_tokens: int - - -class CompletionChoice(BaseModel): - index: int - finish_reason: str - message: CompletionMessage - - -class Completion(BaseModel): - model: Optional[str] = None - created: Optional[int] = None - choices: list[CompletionChoice] - request_id: Optional[str] = None - id: Optional[str] = None - usage: CompletionUsage diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completion_chunk.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completion_chunk.py deleted file mode 100644 index 27fad0008a1dd4..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completion_chunk.py +++ /dev/null @@ -1,57 +0,0 @@ -from typing import Any, Optional - -from ...core import BaseModel - -__all__ = [ - "CompletionUsage", - "ChatCompletionChunk", - "Choice", - "ChoiceDelta", - "ChoiceDeltaFunctionCall", - "ChoiceDeltaToolCall", - "ChoiceDeltaToolCallFunction", -] - - -class ChoiceDeltaFunctionCall(BaseModel): - arguments: Optional[str] = None - name: Optional[str] = None - - -class ChoiceDeltaToolCallFunction(BaseModel): - arguments: Optional[str] = None - name: Optional[str] = None - - -class ChoiceDeltaToolCall(BaseModel): - index: int - id: Optional[str] = None - function: Optional[ChoiceDeltaToolCallFunction] = None - type: Optional[str] = None - - -class ChoiceDelta(BaseModel): - content: Optional[str] = None - role: Optional[str] = None - tool_calls: Optional[list[ChoiceDeltaToolCall]] = None - - -class Choice(BaseModel): - delta: ChoiceDelta - finish_reason: Optional[str] = None - index: int - - -class CompletionUsage(BaseModel): - prompt_tokens: int - completion_tokens: int - total_tokens: int - - -class ChatCompletionChunk(BaseModel): - id: Optional[str] = None - choices: list[Choice] - created: Optional[int] = None - model: Optional[str] = None - usage: Optional[CompletionUsage] = None - extra_json: dict[str, Any] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completions_create_param.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completions_create_param.py deleted file mode 100644 index 6ee4dc4794b201..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/chat_completions_create_param.py +++ /dev/null @@ -1,8 +0,0 @@ -from typing import Optional - -from typing_extensions import TypedDict - - -class Reference(TypedDict, total=False): - enable: Optional[bool] - search_query: Optional[str] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/code_geex/code_geex_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/code_geex/code_geex_params.py deleted file mode 100644 index 666b38855cd637..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/chat/code_geex/code_geex_params.py +++ /dev/null @@ -1,146 +0,0 @@ -from typing import Literal, Optional - -from typing_extensions import Required, TypedDict - -__all__ = [ - "CodeGeexTarget", - "CodeGeexContext", - "CodeGeexExtra", -] - - -class CodeGeexTarget(TypedDict, total=False): - """补全的内容参数""" - - path: Optional[str] - """文件路径""" - language: Required[ - Literal[ - "c", - "c++", - "cpp", - "c#", - "csharp", - "c-sharp", - "css", - "cuda", - "dart", - "lua", - "objectivec", - "objective-c", - "objective-c++", - "python", - "perl", - "prolog", - "swift", - "lisp", - "java", - "scala", - "tex", - "jsx", - "tsx", - "vue", - "markdown", - "html", - "php", - "js", - "javascript", - "typescript", - "go", - "shell", - "rust", - "sql", - "kotlin", - "vb", - "ruby", - "pascal", - "r", - "fortran", - "lean", - "matlab", - "delphi", - "scheme", - "basic", - "assembly", - "groovy", - "abap", - "gdscript", - "haskell", - "julia", - "elixir", - "excel", - "clojure", - "actionscript", - "solidity", - "powershell", - "erlang", - "cobol", - "alloy", - "awk", - "thrift", - "sparql", - "augeas", - "cmake", - "f-sharp", - "stan", - "isabelle", - "dockerfile", - "rmarkdown", - "literate-agda", - "tcl", - "glsl", - "antlr", - "verilog", - "racket", - "standard-ml", - "elm", - "yaml", - "smalltalk", - "ocaml", - "idris", - "visual-basic", - "protocol-buffer", - "bluespec", - "applescript", - "makefile", - "tcsh", - "maple", - "systemverilog", - "literate-coffeescript", - "vhdl", - "restructuredtext", - "sas", - "literate-haskell", - "java-server-pages", - "coffeescript", - "emacs-lisp", - "mathematica", - "xslt", - "zig", - "common-lisp", - "stata", - "agda", - "ada", - ] - ] - """代码语言类型，如python""" - code_prefix: Required[str] - """补全位置的前文""" - code_suffix: Required[str] - """补全位置的后文""" - - -class CodeGeexContext(TypedDict, total=False): - """附加代码""" - - path: Required[str] - """附加代码文件的路径""" - code: Required[str] - """附加的代码内容""" - - -class CodeGeexExtra(TypedDict, total=False): - target: Required[CodeGeexTarget] - """补全的内容参数""" - contexts: Optional[list[CodeGeexContext]] - """附加代码""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/embeddings.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/embeddings.py deleted file mode 100644 index 8425b5c86688dd..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/embeddings.py +++ /dev/null @@ -1,21 +0,0 @@ -from __future__ import annotations - -from typing import Optional - -from ..core import BaseModel -from .chat.chat_completion import CompletionUsage - -__all__ = ["Embedding", "EmbeddingsResponded"] - - -class Embedding(BaseModel): - object: str - index: Optional[int] = None - embedding: list[float] - - -class EmbeddingsResponded(BaseModel): - object: str - data: list[Embedding] - model: str - usage: CompletionUsage diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/__init__.py deleted file mode 100644 index bbaf59e4d7d17a..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from .file_deleted import FileDeleted -from .file_object import FileObject, ListOfFileObject -from .upload_detail import UploadDetail - -__all__ = ["FileObject", "ListOfFileObject", "UploadDetail", "FileDeleted"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_create_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_create_params.py deleted file mode 100644 index 4ef93b1c05acae..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_create_params.py +++ /dev/null @@ -1,38 +0,0 @@ -from __future__ import annotations - -from typing import Literal, Optional - -from typing_extensions import Required, TypedDict - -__all__ = ["FileCreateParams"] - -from ...core import FileTypes -from . import UploadDetail - - -class FileCreateParams(TypedDict, total=False): - file: FileTypes - """file和 upload_detail二选一必填""" - - upload_detail: list[UploadDetail] - """file和 upload_detail二选一必填""" - - purpose: Required[Literal["fine-tune", "retrieval", "batch"]] - """ - 上传文件的用途，支持 "fine-tune和 "retrieval" - retrieval支持上传Doc、Docx、PDF、Xlsx、URL类型文件，且单个文件的大小不超过 5MB。 - fine-tune支持上传.jsonl文件且当前单个文件的大小最大可为 100 MB ，文件中语料格式需满足微调指南中所描述的格式。 - """ - custom_separator: Optional[list[str]] - """ - 当 purpose 为 retrieval 且文件类型为 pdf, url, docx 时上传，切片规则默认为 `\n`。 - """ - knowledge_id: str - """ - 当文件上传目的为 retrieval 时，需要指定知识库ID进行上传。 - """ - - sentence_size: int - """ - 当文件上传目的为 retrieval 时，需要指定知识库ID进行上传。 - """ diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_deleted.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_deleted.py deleted file mode 100644 index a384b1a69a5735..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_deleted.py +++ /dev/null @@ -1,13 +0,0 @@ -from typing import Literal - -from ...core import BaseModel - -__all__ = ["FileDeleted"] - - -class FileDeleted(BaseModel): - id: str - - deleted: bool - - object: Literal["file"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_object.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_object.py deleted file mode 100644 index 8f9d0fbb8e6ce3..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/file_object.py +++ /dev/null @@ -1,22 +0,0 @@ -from typing import Optional - -from ...core import BaseModel - -__all__ = ["FileObject", "ListOfFileObject"] - - -class FileObject(BaseModel): - id: Optional[str] = None - bytes: Optional[int] = None - created_at: Optional[int] = None - filename: Optional[str] = None - object: Optional[str] = None - purpose: Optional[str] = None - status: Optional[str] = None - status_details: Optional[str] = None - - -class ListOfFileObject(BaseModel): - object: Optional[str] = None - data: list[FileObject] - has_more: Optional[bool] = None diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/upload_detail.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/upload_detail.py deleted file mode 100644 index 8f1ca5ce5756aa..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/files/upload_detail.py +++ /dev/null @@ -1,13 +0,0 @@ -from typing import Optional - -from ...core import BaseModel - - -class UploadDetail(BaseModel): - url: str - knowledge_type: int - file_name: Optional[str] = None - sentence_size: Optional[int] = None - custom_separator: Optional[list[str]] = None - callback_url: Optional[str] = None - callback_header: Optional[dict[str, str]] = None diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/__init__.py deleted file mode 100644 index 416f516ef7bf1c..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from __future__ import annotations - -from .fine_tuning_job import FineTuningJob, ListOfFineTuningJob -from .fine_tuning_job_event import FineTuningJobEvent diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/fine_tuning_job.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/fine_tuning_job.py deleted file mode 100644 index 75c7553dbe35c6..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/fine_tuning_job.py +++ /dev/null @@ -1,51 +0,0 @@ -from typing import Optional, Union - -from ...core import BaseModel - -__all__ = ["FineTuningJob", "Error", "Hyperparameters", "ListOfFineTuningJob"] - - -class Error(BaseModel): - code: str - message: str - param: Optional[str] = None - - -class Hyperparameters(BaseModel): - n_epochs: Union[str, int, None] = None - - -class FineTuningJob(BaseModel): - id: Optional[str] = None - - request_id: Optional[str] = None - - created_at: Optional[int] = None - - error: Optional[Error] = None - - fine_tuned_model: Optional[str] = None - - finished_at: Optional[int] = None - - hyperparameters: Optional[Hyperparameters] = None - - model: Optional[str] = None - - object: Optional[str] = None - - result_files: list[str] - - status: str - - trained_tokens: Optional[int] = None - - training_file: str - - validation_file: Optional[str] = None - - -class ListOfFineTuningJob(BaseModel): - object: Optional[str] = None - data: list[FineTuningJob] - has_more: Optional[bool] = None diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/fine_tuning_job_event.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/fine_tuning_job_event.py deleted file mode 100644 index f996cff11430b0..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/fine_tuning_job_event.py +++ /dev/null @@ -1,35 +0,0 @@ -from typing import Optional, Union - -from ...core import BaseModel - -__all__ = ["FineTuningJobEvent", "Metric", "JobEvent"] - - -class Metric(BaseModel): - epoch: Optional[Union[str, int, float]] = None - current_steps: Optional[int] = None - total_steps: Optional[int] = None - elapsed_time: Optional[str] = None - remaining_time: Optional[str] = None - trained_tokens: Optional[int] = None - loss: Optional[Union[str, int, float]] = None - eval_loss: Optional[Union[str, int, float]] = None - acc: Optional[Union[str, int, float]] = None - eval_acc: Optional[Union[str, int, float]] = None - learning_rate: Optional[Union[str, int, float]] = None - - -class JobEvent(BaseModel): - object: Optional[str] = None - id: Optional[str] = None - type: Optional[str] = None - created_at: Optional[int] = None - level: Optional[str] = None - message: Optional[str] = None - data: Optional[Metric] = None - - -class FineTuningJobEvent(BaseModel): - object: Optional[str] = None - data: list[JobEvent] - has_more: Optional[bool] = None diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/job_create_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/job_create_params.py deleted file mode 100644 index e1ebc352bc97fd..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/job_create_params.py +++ /dev/null @@ -1,15 +0,0 @@ -from __future__ import annotations - -from typing import Literal, Union - -from typing_extensions import TypedDict - -__all__ = ["Hyperparameters"] - - -class Hyperparameters(TypedDict, total=False): - batch_size: Union[Literal["auto"], int] - - learning_rate_multiplier: Union[Literal["auto"], float] - - n_epochs: Union[Literal["auto"], int] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/models/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/models/__init__.py deleted file mode 100644 index 57d0d2511dbc14..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/models/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .fine_tuned_models import FineTunedModelsStatus diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/models/fine_tuned_models.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/models/fine_tuned_models.py deleted file mode 100644 index b286a5b5774d3d..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/fine_tuning/models/fine_tuned_models.py +++ /dev/null @@ -1,13 +0,0 @@ -from typing import ClassVar - -from ....core import PYDANTIC_V2, BaseModel, ConfigDict - -__all__ = ["FineTunedModelsStatus"] - - -class FineTunedModelsStatus(BaseModel): - if PYDANTIC_V2: - model_config: ClassVar[ConfigDict] = ConfigDict(extra="allow", protected_namespaces=()) - request_id: str # 请求id - model_name: str # 模型名称 - delete_status: str # 删除状态 deleting（删除中）, deleted （已删除） diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/image.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/image.py deleted file mode 100644 index 3bcad0acabd215..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/image.py +++ /dev/null @@ -1,18 +0,0 @@ -from __future__ import annotations - -from typing import Optional - -from ..core import BaseModel - -__all__ = ["GeneratedImage", "ImagesResponded"] - - -class GeneratedImage(BaseModel): - b64_json: Optional[str] = None - url: Optional[str] = None - revised_prompt: Optional[str] = None - - -class ImagesResponded(BaseModel): - created: int - data: list[GeneratedImage] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/__init__.py deleted file mode 100644 index 8c81d703e214a3..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/__init__.py +++ /dev/null @@ -1,8 +0,0 @@ -from .knowledge import KnowledgeInfo -from .knowledge_used import KnowledgeStatistics, KnowledgeUsed - -__all__ = [ - "KnowledgeInfo", - "KnowledgeStatistics", - "KnowledgeUsed", -] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/__init__.py deleted file mode 100644 index 59cb41d7124a7f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/__init__.py +++ /dev/null @@ -1,8 +0,0 @@ -from .document import DocumentData, DocumentFailedInfo, DocumentObject, DocumentSuccessInfo - -__all__ = [ - "DocumentData", - "DocumentObject", - "DocumentSuccessInfo", - "DocumentFailedInfo", -] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document.py deleted file mode 100644 index 980bc6f4a7c40d..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document.py +++ /dev/null @@ -1,51 +0,0 @@ -from typing import Optional - -from ....core import BaseModel - -__all__ = ["DocumentData", "DocumentObject", "DocumentSuccessInfo", "DocumentFailedInfo"] - - -class DocumentSuccessInfo(BaseModel): - documentId: Optional[str] = None - """文件id""" - filename: Optional[str] = None - """文件名称""" - - -class DocumentFailedInfo(BaseModel): - failReason: Optional[str] = None - """上传失败的原因，包括：文件格式不支持、文件大小超出限制、知识库容量已满、容量上限为 50 万字。""" - filename: Optional[str] = None - """文件名称""" - documentId: Optional[str] = None - """知识库id""" - - -class DocumentObject(BaseModel): - """文档信息""" - - successInfos: Optional[list[DocumentSuccessInfo]] = None - """上传成功的文件信息""" - failedInfos: Optional[list[DocumentFailedInfo]] = None - """上传失败的文件信息""" - - -class DocumentDataFailInfo(BaseModel): - """失败原因""" - - embedding_code: Optional[int] = ( - None # 失败码 10001：知识不可用，知识库空间已达上限 10002：知识不可用，知识库空间已达上限(字数超出限制) - ) - embedding_msg: Optional[str] = None # 失败原因 - - -class DocumentData(BaseModel): - id: str = None # 知识唯一id - custom_separator: list[str] = None # 切片规则 - sentence_size: str = None # 切片大小 - length: int = None # 文件大小（字节） - word_num: int = None # 文件字数 - name: str = None # 文件名 - url: str = None # 文件下载链接 - embedding_stat: int = None # 0:向量化中 1:向量化完成 2:向量化失败 - failInfo: Optional[DocumentDataFailInfo] = None # 失败原因 向量化失败embedding_stat=2的时候 会有此值 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_edit_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_edit_params.py deleted file mode 100644 index 509cb3a451af5f..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_edit_params.py +++ /dev/null @@ -1,29 +0,0 @@ -from typing import Optional, TypedDict - -__all__ = ["DocumentEditParams"] - - -class DocumentEditParams(TypedDict): - """ - 知识参数类型定义 - - Attributes: - id (str): 知识ID - knowledge_type (int): 知识类型: - 1:文章知识: 支持pdf,url,docx - 2.问答知识-文档: 支持pdf,url,docx - 3.问答知识-表格: 支持xlsx - 4.商品库-表格: 支持xlsx - 5.自定义: 支持pdf,url,docx - custom_separator (Optional[List[str]]): 当前知识类型为自定义(knowledge_type=5)时的切片规则，默认\n - sentence_size (Optional[int]): 当前知识类型为自定义(knowledge_type=5)时的切片字数，取值范围: 20-2000，默认300 - callback_url (Optional[str]): 回调地址 - callback_header (Optional[dict]): 回调时携带的header - """ - - id: str - knowledge_type: int - custom_separator: Optional[list[str]] - sentence_size: Optional[int] - callback_url: Optional[str] - callback_header: Optional[dict[str, str]] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_list_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_list_params.py deleted file mode 100644 index 910c8c045e1b97..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_list_params.py +++ /dev/null @@ -1,26 +0,0 @@ -from __future__ import annotations - -from typing import Optional - -from typing_extensions import TypedDict - - -class DocumentListParams(TypedDict, total=False): - """ - 文件查询参数类型定义 - - Attributes: - purpose (Optional[str]): 文件用途 - knowledge_id (Optional[str]): 当文件用途为 retrieval 时，需要提供查询的知识库ID - page (Optional[int]): 页，默认1 - limit (Optional[int]): 查询文件列表数，默认10 - after (Optional[str]): 查询指定fileID之后的文件列表（当文件用途为 fine-tune 时需要） - order (Optional[str]): 排序规则，可选值['desc', 'asc']，默认desc（当文件用途为 fine-tune 时需要） - """ - - purpose: Optional[str] - knowledge_id: Optional[str] - page: Optional[int] - limit: Optional[int] - after: Optional[str] - order: Optional[str] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_list_resp.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_list_resp.py deleted file mode 100644 index acae4fad9ff36b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/document/document_list_resp.py +++ /dev/null @@ -1,11 +0,0 @@ -from __future__ import annotations - -from ....core import BaseModel -from . import DocumentData - -__all__ = ["DocumentPage"] - - -class DocumentPage(BaseModel): - list: list[DocumentData] - object: str diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge.py deleted file mode 100644 index bc6f159eb211e5..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge.py +++ /dev/null @@ -1,21 +0,0 @@ -from typing import Optional - -from ...core import BaseModel - -__all__ = ["KnowledgeInfo"] - - -class KnowledgeInfo(BaseModel): - id: Optional[str] = None - """知识库唯一 id""" - embedding_id: Optional[str] = ( - None # 知识库绑定的向量化模型 见模型列表 [内部服务开放接口文档](https://lslfd0slxc.feishu.cn/docx/YauWdbBiMopV0FxB7KncPWCEn8f#H15NduiQZo3ugmxnWQFcfAHpnQ4) - ) - name: Optional[str] = None # 知识库名称 100字限制 - customer_identifier: Optional[str] = None # 用户标识 长度32位以内 - description: Optional[str] = None # 知识库描述 500字限制 - background: Optional[str] = None # 背景颜色（给枚举）'blue', 'red', 'orange', 'purple', 'sky' - icon: Optional[str] = ( - None # 知识库图标（给枚举） question: 问号、book: 书籍、seal: 印章、wrench: 扳手、tag: 标签、horn: 喇叭、house: 房子 # noqa: E501 - ) - bucket_id: Optional[str] = None # 桶id 限制32位 diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_create_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_create_params.py deleted file mode 100644 index c3da201727c34a..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_create_params.py +++ /dev/null @@ -1,30 +0,0 @@ -from __future__ import annotations - -from typing import Literal, Optional - -from typing_extensions import TypedDict - -__all__ = ["KnowledgeBaseParams"] - - -class KnowledgeBaseParams(TypedDict): - """ - 知识库参数类型定义 - - Attributes: - embedding_id (int): 知识库绑定的向量化模型ID - name (str): 知识库名称，限制100字 - customer_identifier (Optional[str]): 用户标识，长度32位以内 - description (Optional[str]): 知识库描述，限制500字 - background (Optional[Literal['blue', 'red', 'orange', 'purple', 'sky']]): 背景颜色 - icon (Optional[Literal['question', 'book', 'seal', 'wrench', 'tag', 'horn', 'house']]): 知识库图标 - bucket_id (Optional[str]): 桶ID，限制32位 - """ - - embedding_id: int - name: str - customer_identifier: Optional[str] - description: Optional[str] - background: Optional[Literal["blue", "red", "orange", "purple", "sky"]] = None - icon: Optional[Literal["question", "book", "seal", "wrench", "tag", "horn", "house"]] = None - bucket_id: Optional[str] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_list_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_list_params.py deleted file mode 100644 index a221b28e4603be..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_list_params.py +++ /dev/null @@ -1,15 +0,0 @@ -from __future__ import annotations - -from typing_extensions import TypedDict - -__all__ = ["KnowledgeListParams"] - - -class KnowledgeListParams(TypedDict, total=False): - page: int = 1 - """ 页码，默认 1，第一页 - """ - - size: int = 10 - """每页数量 默认10 - """ diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_list_resp.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_list_resp.py deleted file mode 100644 index e462eddc550d61..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_list_resp.py +++ /dev/null @@ -1,11 +0,0 @@ -from __future__ import annotations - -from ...core import BaseModel -from . import KnowledgeInfo - -__all__ = ["KnowledgePage"] - - -class KnowledgePage(BaseModel): - list: list[KnowledgeInfo] - object: str diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_used.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_used.py deleted file mode 100644 index cfda7097026c59..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/knowledge/knowledge_used.py +++ /dev/null @@ -1,21 +0,0 @@ -from typing import Optional - -from ...core import BaseModel - -__all__ = ["KnowledgeStatistics", "KnowledgeUsed"] - - -class KnowledgeStatistics(BaseModel): - """ - 使用量统计 - """ - - word_num: Optional[int] = None - length: Optional[int] = None - - -class KnowledgeUsed(BaseModel): - used: Optional[KnowledgeStatistics] = None - """已使用量""" - total: Optional[KnowledgeStatistics] = None - """知识库总量""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/sensitive_word_check/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/sensitive_word_check/__init__.py deleted file mode 100644 index c9bd60419ce606..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/sensitive_word_check/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .sensitive_word_check import SensitiveWordCheckRequest - -__all__ = ["SensitiveWordCheckRequest"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/sensitive_word_check/sensitive_word_check.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/sensitive_word_check/sensitive_word_check.py deleted file mode 100644 index 0c37d99e653292..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/sensitive_word_check/sensitive_word_check.py +++ /dev/null @@ -1,14 +0,0 @@ -from typing import Optional - -from typing_extensions import TypedDict - - -class SensitiveWordCheckRequest(TypedDict, total=False): - type: Optional[str] - """敏感词类型，当前仅支持ALL""" - status: Optional[str] - """敏感词启用禁用状态 - 启用：ENABLE - 禁用：DISABLE - 备注：默认开启敏感词校验，如果要关闭敏感词校验，需联系商务获取对应权限，否则敏感词禁用不生效。 - """ diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/__init__.py deleted file mode 100644 index 62f77344eee56b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/__init__.py +++ /dev/null @@ -1,9 +0,0 @@ -from .web_search import ( - SearchIntent, - SearchRecommend, - SearchResult, - WebSearch, -) -from .web_search_chunk import WebSearchChunk - -__all__ = ["WebSearch", "SearchIntent", "SearchResult", "SearchRecommend", "WebSearchChunk"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/tools_web_search_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/tools_web_search_params.py deleted file mode 100644 index b3a3b26f07ee58..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/tools_web_search_params.py +++ /dev/null @@ -1,35 +0,0 @@ -from __future__ import annotations - -from typing import Optional, Union - -from typing_extensions import TypedDict - -__all__ = ["WebSearchParams"] - - -class WebSearchParams(TypedDict): - """ - 工具名：web-search-pro参数类型定义 - - Attributes: - :param model: str, 模型名称 - :param request_id: Optional[str], 请求ID - :param stream: Optional[bool], 是否流式 - :param messages: Union[str, List[str], List[int], object, None], - 包含历史对话上下文的内容，按照 {"role": "user", "content": "你好"} 的json 数组形式进行传参 - 当前版本仅支持 User Message 单轮对话，工具会理解User Message并进行搜索， - 请尽可能传入不带指令格式的用户原始提问，以提高搜索准确率。 - :param scope: Optional[str], 指定搜索范围，全网、学术等，默认全网 - :param location: Optional[str], 指定搜索用户地区 location 提高相关性 - :param recent_days: Optional[int],支持指定返回 N 天（1-30）更新的搜索结果 - - - """ - - model: str - request_id: Optional[str] - stream: Optional[bool] - messages: Union[str, list[str], list[int], object, None] - scope: Optional[str] = None - location: Optional[str] = None - recent_days: Optional[int] = None diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/web_search.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/web_search.py deleted file mode 100644 index ac9fa3821e979b..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/web_search.py +++ /dev/null @@ -1,71 +0,0 @@ -from typing import Optional - -from ...core import BaseModel - -__all__ = [ - "WebSearch", - "SearchIntent", - "SearchResult", - "SearchRecommend", -] - - -class SearchIntent(BaseModel): - index: int - # 搜索轮次，默认为 0 - query: str - # 搜索优化 query - intent: str - # 判断的意图类型 - keywords: str - # 搜索关键词 - - -class SearchResult(BaseModel): - index: int - # 搜索轮次，默认为 0 - title: str - # 标题 - link: str - # 链接 - content: str - # 内容 - icon: str - # 图标 - media: str - # 来源媒体 - refer: str - # 角标序号 [ref_1] - - -class SearchRecommend(BaseModel): - index: int - # 搜索轮次，默认为 0 - query: str - # 推荐query - - -class WebSearchMessageToolCall(BaseModel): - id: str - search_intent: Optional[SearchIntent] - search_result: Optional[SearchResult] - search_recommend: Optional[SearchRecommend] - type: str - - -class WebSearchMessage(BaseModel): - role: str - tool_calls: Optional[list[WebSearchMessageToolCall]] = None - - -class WebSearchChoice(BaseModel): - index: int - finish_reason: str - message: WebSearchMessage - - -class WebSearch(BaseModel): - created: Optional[int] = None - choices: list[WebSearchChoice] - request_id: Optional[str] = None - id: Optional[str] = None diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/web_search_chunk.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/web_search_chunk.py deleted file mode 100644 index 7fb0e02bb58719..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/tools/web_search_chunk.py +++ /dev/null @@ -1,33 +0,0 @@ -from typing import Optional - -from ...core import BaseModel -from .web_search import SearchIntent, SearchRecommend, SearchResult - -__all__ = ["WebSearchChunk"] - - -class ChoiceDeltaToolCall(BaseModel): - index: int - id: Optional[str] = None - - search_intent: Optional[SearchIntent] = None - search_result: Optional[SearchResult] = None - search_recommend: Optional[SearchRecommend] = None - type: Optional[str] = None - - -class ChoiceDelta(BaseModel): - role: Optional[str] = None - tool_calls: Optional[list[ChoiceDeltaToolCall]] = None - - -class Choice(BaseModel): - delta: ChoiceDelta - finish_reason: Optional[str] = None - index: int - - -class WebSearchChunk(BaseModel): - id: Optional[str] = None - choices: list[Choice] - created: Optional[int] = None diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/__init__.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/__init__.py deleted file mode 100644 index b14072b1a771af..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from .video_object import VideoObject, VideoResult - -__all__ = ["VideoObject", "VideoResult"] diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/video_create_params.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/video_create_params.py deleted file mode 100644 index f5489d708e7227..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/video_create_params.py +++ /dev/null @@ -1,27 +0,0 @@ -from __future__ import annotations - -from typing import Optional - -from typing_extensions import TypedDict - -__all__ = ["VideoCreateParams"] - -from ..sensitive_word_check import SensitiveWordCheckRequest - - -class VideoCreateParams(TypedDict, total=False): - model: str - """模型编码""" - prompt: str - """所需视频的文本描述""" - image_url: str - """所需视频的文本描述""" - sensitive_word_check: Optional[SensitiveWordCheckRequest] - """支持 URL 或者 Base64、传入 image 奖进行图生视频 - * 图片格式： - * 图片大小：""" - request_id: str - """由用户端传参，需保证唯一性；用于区分每次请求的唯一标识，用户端不传时平台会默认生成。""" - - user_id: str - """用户端。""" diff --git a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/video_object.py b/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/video_object.py deleted file mode 100644 index 85c3844d8a791c..00000000000000 --- a/api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/types/video/video_object.py +++ /dev/null @@ -1,30 +0,0 @@ -from typing import Optional - -from ...core import BaseModel - -__all__ = ["VideoObject", "VideoResult"] - - -class VideoResult(BaseModel): - url: str - """视频url""" - cover_image_url: str - """预览图""" - - -class VideoObject(BaseModel): - id: Optional[str] = None - """智谱 AI 开放平台生成的任务订单号，调用请求结果接口时请使用此订单号""" - - model: str - """模型名称""" - - video_result: list[VideoResult] - """视频生成结果""" - - task_status: str - """处理状态，PROCESSING（处理中），SUCCESS（成功），FAIL（失败） - 注：处理中状态需通过查询获取结果""" - - request_id: str - """用户在客户端请求时提交的任务编号或者平台生成的任务编号""" diff --git a/api/core/plugin/entities/plugin_daemon.py b/api/core/plugin/entities/plugin_daemon.py index c5dced121faa05..554353c6c9e938 100644 --- a/api/core/plugin/entities/plugin_daemon.py +++ b/api/core/plugin/entities/plugin_daemon.py @@ -1,8 +1,11 @@ +from datetime import datetime from enum import Enum from typing import Generic, Optional, TypeVar -from pydantic import BaseModel +from pydantic import BaseModel, ConfigDict, Field +from core.model_runtime.entities.model_entities import AIModelEntity +from core.model_runtime.entities.provider_entities import ProviderEntity from core.tools.entities.tool_entities import ToolProviderEntityWithPlugin T = TypeVar("T", bound=(BaseModel | dict | list | bool)) @@ -22,6 +25,7 @@ class InstallPluginMessage(BaseModel): """ Message for installing a plugin. """ + class Event(Enum): Info = "info" Done = "done" @@ -42,4 +46,44 @@ class PluginBasicBooleanResponse(BaseModel): """ Basic boolean response from plugin daemon. """ - result: bool \ No newline at end of file + + result: bool + + +class PluginModelSchemaEntity(BaseModel): + model_schema: AIModelEntity = Field(description="The model schema.") + + # pydantic configs + model_config = ConfigDict(protected_namespaces=()) + + +class PluginModelProviderEntity(BaseModel): + id: str = Field(alias="ID", description="ID") + created_at: datetime = Field(alias="CreatedAt", description="The created at time of the model provider.") + updated_at: datetime = Field(alias="UpdatedAt", description="The updated at time of the model provider.") + provider: str = Field(description="The provider of the model.") + tenant_id: str = Field(description="The tenant ID.") + plugin_unique_identifier: str = Field(description="The plugin unique identifier.") + plugin_id: str = Field(description="The plugin ID.") + declaration: ProviderEntity = Field(description="The declaration of the model provider.") + + +class PluginNumTokensResponse(BaseModel): + """ + Response for number of tokens. + """ + + num_tokens: int = Field(description="The number of tokens.") + + +class PluginStringResultResponse(BaseModel): + result: str = Field(description="The result of the string.") + + +class PluginVoiceEntity(BaseModel): + name: str = Field(description="The name of the voice.") + value: str = Field(description="The value of the voice.") + + +class PluginVoicesResponse(BaseModel): + voices: list[PluginVoiceEntity] = Field(description="The result of the voices.") diff --git a/api/core/plugin/entities/request.py b/api/core/plugin/entities/request.py index 5fe9ea1ddaf878..af40ebc5ca5b31 100644 --- a/api/core/plugin/entities/request.py +++ b/api/core/plugin/entities/request.py @@ -1,7 +1,7 @@ from collections.abc import Mapping from typing import Any, Literal, Optional -from pydantic import BaseModel, Field, field_validator +from pydantic import BaseModel, ConfigDict, Field, field_validator from core.entities.provider_entities import BasicProviderConfig from core.model_runtime.entities.message_entities import ( @@ -39,6 +39,8 @@ class BaseRequestInvokeModel(BaseModel): model: str model_type: ModelType + model_config = ConfigDict(protected_namespaces=()) + class RequestInvokeLLM(BaseRequestInvokeModel): """ @@ -53,6 +55,8 @@ class RequestInvokeLLM(BaseRequestInvokeModel): stop: Optional[list[str]] = Field(default_factory=list) stream: Optional[bool] = False + model_config = ConfigDict(protected_namespaces=()) + @field_validator("prompt_messages", mode="before") @classmethod def convert_prompt_messages(cls, v): diff --git a/api/core/plugin/manager/asset.py b/api/core/plugin/manager/asset.py index df76f56a6dc8d9..fc4a99ad49abb9 100644 --- a/api/core/plugin/manager/asset.py +++ b/api/core/plugin/manager/asset.py @@ -2,11 +2,11 @@ class PluginAssetManager(BasePluginManager): - def fetch_asset(self, id: str) -> bytes: + def fetch_asset(self, tenant_id: str, id: str) -> bytes: """ Fetch an asset by id. """ - response = self._request(method="GET", path=f"/assets/plugin/{id}") + response = self._request(method="GET", path=f"plugin/{tenant_id}/assets/{id}") if response.status_code != 200: raise ValueError(f"can not found asset {id}") return response.content diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index fd18b3798e9b6a..1e050427d4e890 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -132,8 +132,19 @@ def _request_with_plugin_daemon_response_stream( line_data = json.loads(line) rep = PluginDaemonBasicResponse[type](**line_data) if rep.code != 0: - raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") + raise PluginDaemonRespError(rep.message, rep.code) if rep.data is None: raise ValueError("got empty data from plugin daemon") yield rep.data - \ No newline at end of file + + +class PluginDaemonRespError(Exception): + """ + Plugin daemon response error. + """ + + def __init__(self, resp_message: str, code: int): + super().__init__() + self.message = f"got error from plugin daemon: {resp_message}, code: {code}" + self.resp_message = resp_message + self.code = code diff --git a/api/core/plugin/manager/model.py b/api/core/plugin/manager/model.py index 4411d76fe10079..e34e9b516efa90 100644 --- a/api/core/plugin/manager/model.py +++ b/api/core/plugin/manager/model.py @@ -1,13 +1,523 @@ -from core.model_runtime.entities.provider_entities import ProviderEntity -from core.plugin.manager.base import BasePluginManager +import binascii +from collections.abc import Generator, Sequence +from typing import IO, Optional + +from core.model_runtime.entities.llm_entities import LLMResultChunk +from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool +from core.model_runtime.entities.model_entities import AIModelEntity +from core.model_runtime.entities.rerank_entities import RerankResult +from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult +from core.model_runtime.utils.encoders import jsonable_encoder +from core.plugin.entities.plugin_daemon import ( + PluginBasicBooleanResponse, + PluginModelProviderEntity, + PluginModelSchemaEntity, + PluginNumTokensResponse, + PluginStringResultResponse, + PluginVoicesResponse, +) +from core.plugin.manager.base import BasePluginManager, PluginDaemonRespError class PluginModelManager(BasePluginManager): - def fetch_model_providers(self, tenant_id: str) -> list[ProviderEntity]: + def fetch_model_providers(self, tenant_id: str) -> Sequence[PluginModelProviderEntity]: """ Fetch model providers for the given tenant. """ response = self._request_with_plugin_daemon_response( - "GET", f"plugin/{tenant_id}/models", list[ProviderEntity], params={"page": 1, "page_size": 256} + "GET", + f"plugin/{tenant_id}/management/models", + list[PluginModelProviderEntity], + params={"page": 1, "page_size": 256}, ) return response + + def get_model_schema( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + ) -> AIModelEntity | None: + """ + Get model schema + """ + response = self._request_with_plugin_daemon_response_stream( + "POST", + f"plugin/{tenant_id}/dispatch/model/schema", + PluginModelSchemaEntity, + data={ + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + }, + }, + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp.model_schema + + return None + + def validate_provider_credentials( + self, tenant_id: str, user_id: str, plugin_id: str, provider: str, credentials: dict + ) -> bool: + """ + validate the credentials of the provider + """ + response = self._request_with_plugin_daemon_response_stream( + "POST", + f"plugin/{tenant_id}/dispatch/model/validate_provider_credentials", + PluginBasicBooleanResponse, + data={ + "user_id": user_id, + "data": { + "provider": provider, + "credentials": credentials, + }, + }, + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp.result + + return False + + def validate_model_credentials( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + ) -> bool: + """ + validate the credentials of the provider + """ + response = self._request_with_plugin_daemon_response_stream( + "POST", + f"plugin/{tenant_id}/dispatch/model/validate_model_credentials", + PluginBasicBooleanResponse, + data={ + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + }, + }, + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp.result + + return False + + def invoke_llm( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model: str, + credentials: dict, + prompt_messages: list[PromptMessage], + model_parameters: Optional[dict] = None, + tools: Optional[list[PromptMessageTool]] = None, + stop: Optional[list[str]] = None, + stream: bool = True, + ) -> Generator[LLMResultChunk, None, None]: + """ + Invoke llm + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/llm/invoke", + type=LLMResultChunk, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": "llm", + "model": model, + "credentials": credentials, + "prompt_messages": prompt_messages, + "model_parameters": model_parameters, + "tools": tools, + "stop": stop, + "stream": stream, + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + try: + yield from response + except PluginDaemonRespError as e: + raise ValueError(e.resp_message + str(e.code)) + + def get_llm_num_tokens( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + prompt_messages: list[PromptMessage], + tools: Optional[list[PromptMessageTool]] = None, + ) -> int: + """ + Get number of tokens for llm + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/llm/num_tokens", + type=PluginNumTokensResponse, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + "prompt_messages": prompt_messages, + "tools": tools, + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp.num_tokens + + return 0 + + def invoke_text_embedding( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model: str, + credentials: dict, + texts: list[str], + ) -> TextEmbeddingResult: + """ + Invoke text embedding + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/text_embedding/invoke", + type=TextEmbeddingResult, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": "text-embedding", + "model": model, + "credentials": credentials, + "texts": texts, + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp + + raise ValueError("Failed to invoke text embedding") + + def get_text_embedding_num_tokens( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + texts: list[str], + ) -> int: + """ + Get number of tokens for text embedding + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/text_embedding/num_tokens", + type=PluginNumTokensResponse, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + "texts": texts, + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp.num_tokens + + return 0 + + def invoke_rerank( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + query: str, + docs: list[str], + score_threshold: Optional[float] = None, + top_n: Optional[int] = None, + ) -> RerankResult: + """ + Invoke rerank + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/rerank/invoke", + type=RerankResult, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + "query": query, + "docs": docs, + "score_threshold": score_threshold, + "top_n": top_n, + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp + + raise ValueError("Failed to invoke rerank") + + def invoke_tts( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + content_text: str, + voice: str, + ) -> Generator[bytes, None, None]: + """ + Invoke tts + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/tts/invoke", + type=PluginStringResultResponse, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + "content_text": content_text, + "voice": voice, + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + try: + for result in response: + hex_str = result.result + yield binascii.unhexlify(hex_str) + except PluginDaemonRespError as e: + raise ValueError(e.resp_message + str(e.code)) + + def get_tts_model_voices( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + language: Optional[str] = None, + ) -> list[dict]: + """ + Get tts model voices + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/model/voices", + type=PluginVoicesResponse, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + "language": language, + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + for voice in resp.voices: + return [{"name": voice.name, "value": voice.value}] + + return [] + + def invoke_speech_to_text( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + file: IO[bytes], + ) -> str: + """ + Invoke speech to text + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/speech2text/invoke", + type=PluginStringResultResponse, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + "file": binascii.hexlify(file.read()).decode(), + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp.result + + raise ValueError("Failed to invoke speech to text") + + def invoke_moderation( + self, + tenant_id: str, + user_id: str, + plugin_id: str, + provider: str, + model_type: str, + model: str, + credentials: dict, + text: str, + ) -> bool: + """ + Invoke moderation + """ + response = self._request_with_plugin_daemon_response_stream( + method="POST", + path=f"plugin/{tenant_id}/dispatch/moderation/invoke", + type=PluginBasicBooleanResponse, + data=jsonable_encoder( + { + "user_id": user_id, + "data": { + "provider": provider, + "model_type": model_type, + "model": model, + "credentials": credentials, + "text": text, + }, + } + ), + headers={ + "X-Plugin-ID": plugin_id, + "Content-Type": "application/json", + }, + ) + + for resp in response: + return resp.result + + raise ValueError("Failed to invoke moderation") diff --git a/api/core/provider_manager.py b/api/core/provider_manager.py index 3a1fe300dfd311..cb49a6cf5619b7 100644 --- a/api/core/provider_manager.py +++ b/api/core/provider_manager.py @@ -22,7 +22,7 @@ from core.helper.position_helper import is_filtered from core.model_runtime.entities.model_entities import ModelType from core.model_runtime.entities.provider_entities import CredentialFormSchema, FormType, ProviderEntity -from core.model_runtime.model_providers import model_provider_factory +from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory from extensions import ext_hosting_provider from extensions.ext_database import db from extensions.ext_redis import redis_client @@ -97,6 +97,7 @@ def get_configurations(self, tenant_id: str) -> ProviderConfigurations: provider_name_to_provider_model_records_dict = self._get_all_provider_models(tenant_id) # Get all provider entities + model_provider_factory = ModelProviderFactory(tenant_id) provider_entities = model_provider_factory.get_providers() # Get All preferred provider types of the workspace @@ -204,12 +205,10 @@ def get_provider_model_bundle(self, tenant_id: str, provider: str, model_type: M if not provider_configuration: raise ValueError(f"Provider {provider} does not exist.") - provider_instance = provider_configuration.get_provider_instance() - model_type_instance = provider_instance.get_model_instance(model_type) + model_type_instance = provider_configuration.get_model_type_instance(model_type) return ProviderModelBundle( configuration=provider_configuration, - provider_instance=provider_instance, model_type_instance=model_type_instance, ) @@ -257,8 +256,8 @@ def get_default_model(self, tenant_id: str, model_type: ModelType) -> Optional[D if not default_model: return None - provider_instance = model_provider_factory.get_provider_instance(default_model.provider_name) - provider_schema = provider_instance.get_provider_schema() + model_provider_factory = ModelProviderFactory(tenant_id) + provider_schema = model_provider_factory.get_provider_schema(provider=default_model.provider_name) return DefaultModelEntity( model=default_model.model_name, diff --git a/api/core/tools/utils/model_invocation_utils.py b/api/core/tools/utils/model_invocation_utils.py index 4e226810d6ac90..b3c3292f5d58c2 100644 --- a/api/core/tools/utils/model_invocation_utils.py +++ b/api/core/tools/utils/model_invocation_utils.py @@ -10,7 +10,7 @@ from core.model_manager import ModelManager from core.model_runtime.entities.llm_entities import LLMResult from core.model_runtime.entities.message_entities import PromptMessage -from core.model_runtime.entities.model_entities import ModelType +from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType from core.model_runtime.errors.invoke import ( InvokeAuthorizationError, InvokeBadRequestError, @@ -18,7 +18,7 @@ InvokeRateLimitError, InvokeServerUnavailableError, ) -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel, ModelPropertyKey +from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel from core.model_runtime.utils.encoders import jsonable_encoder from extensions.ext_database import db from models.tools import ToolModelInvoke diff --git a/api/services/model_load_balancing_service.py b/api/services/model_load_balancing_service.py index e7b9422cfe1e08..5c5c0c16078ba5 100644 --- a/api/services/model_load_balancing_service.py +++ b/api/services/model_load_balancing_service.py @@ -14,7 +14,7 @@ ModelCredentialSchema, ProviderCredentialSchema, ) -from core.model_runtime.model_providers import model_provider_factory +from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory from core.provider_manager import ProviderManager from extensions.ext_database import db from models.provider import LoadBalancingModelConfig @@ -527,6 +527,7 @@ def _custom_credentials_validate( credentials[key] = encrypter.decrypt_token(tenant_id, original_credentials[key]) if validate: + model_provider_factory = ModelProviderFactory(tenant_id) if isinstance(credential_schemas, ModelCredentialSchema): credentials = model_provider_factory.model_credentials_validate( provider=provider_configuration.provider.provider, diff --git a/api/services/model_provider_service.py b/api/services/model_provider_service.py index 384a072b371fdd..630d575f8225cf 100644 --- a/api/services/model_provider_service.py +++ b/api/services/model_provider_service.py @@ -1,16 +1,12 @@ import logging -import mimetypes import os -from pathlib import Path -from typing import Optional, cast +from typing import Optional import requests -from flask import current_app from core.entities.model_entities import ModelStatus, ProviderModelWithStatusEntity from core.model_runtime.entities.model_entities import ModelType, ParameterRule -from core.model_runtime.model_providers import model_provider_factory -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel +from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory from core.provider_manager import ProviderManager from models.provider import ProviderType from services.entities.model_provider_entities import ( @@ -100,7 +96,7 @@ def get_models_by_provider(self, tenant_id: str, provider: str) -> list[ModelWit ModelWithProviderEntityResponse(model) for model in provider_configurations.get_models(provider=provider) ] - def get_provider_credentials(self, tenant_id: str, provider: str) -> dict: + def get_provider_credentials(self, tenant_id: str, provider: str) -> Optional[dict]: """ get provider credentials. @@ -176,7 +172,7 @@ def remove_provider_credentials(self, tenant_id: str, provider: str) -> None: # Remove custom provider credentials. provider_configuration.delete_custom_credentials() - def get_model_credentials(self, tenant_id: str, provider: str, model_type: str, model: str) -> dict: + def get_model_credentials(self, tenant_id: str, provider: str, model_type: str, model: str) -> Optional[dict]: """ get model credentials. @@ -351,18 +347,17 @@ def get_model_parameter_rules(self, tenant_id: str, provider: str, model: str) - if not provider_configuration: raise ValueError(f"Provider {provider} does not exist.") - # Get model instance of LLM - model_type_instance = provider_configuration.get_model_type_instance(ModelType.LLM) - model_type_instance = cast(LargeLanguageModel, model_type_instance) - # fetch credentials credentials = provider_configuration.get_current_credentials(model_type=ModelType.LLM, model=model) if not credentials: return [] - # Call get_parameter_rules method of model instance to get model parameter rules - return model_type_instance.get_parameter_rules(model=model, credentials=credentials) + model_schema = provider_configuration.get_model_schema( + model_type=ModelType.LLM, model=model, credentials=credentials + ) + + return model_schema.parameter_rules if model_schema else [] def get_default_model_of_model_type(self, tenant_id: str, model_type: str) -> Optional[DefaultModelResponse]: """ @@ -410,52 +405,21 @@ def update_default_model_of_model_type(self, tenant_id: str, model_type: str, pr ) def get_model_provider_icon( - self, provider: str, icon_type: str, lang: str + self, tenant_id: str, provider: str, icon_type: str, lang: str ) -> tuple[Optional[bytes], Optional[str]]: """ get model provider icon. + :param tenant_id: workspace id :param provider: provider name :param icon_type: icon type (icon_small or icon_large) :param lang: language (zh_Hans or en_US) :return: """ - provider_instance = model_provider_factory.get_provider_instance(provider) - provider_schema = provider_instance.get_provider_schema() - - if icon_type.lower() == "icon_small": - if not provider_schema.icon_small: - raise ValueError(f"Provider {provider} does not have small icon.") - - if lang.lower() == "zh_hans": - file_name = provider_schema.icon_small.zh_Hans - else: - file_name = provider_schema.icon_small.en_US - else: - if not provider_schema.icon_large: - raise ValueError(f"Provider {provider} does not have large icon.") + model_provider_factory = ModelProviderFactory(tenant_id) + byte_data = model_provider_factory.get_provider_icon(provider, icon_type, lang) - if lang.lower() == "zh_hans": - file_name = provider_schema.icon_large.zh_Hans - else: - file_name = provider_schema.icon_large.en_US - - root_path = current_app.root_path - provider_instance_path = os.path.dirname( - os.path.join(root_path, provider_instance.__class__.__module__.replace(".", "/")) - ) - file_path = os.path.join(provider_instance_path, "_assets") - file_path = os.path.join(file_path, file_name) - - if not os.path.exists(file_path): - return None, None - - mimetype, _ = mimetypes.guess_type(file_path) - mimetype = mimetype or "application/octet-stream" - - # read binary from file - byte_data = Path(file_path).read_bytes() - return byte_data, mimetype + return byte_data, "application/octet-stream" def switch_preferred_provider(self, tenant_id: str, provider: str, preferred_provider_type: str) -> None: """ @@ -525,6 +489,9 @@ def disable_model(self, tenant_id: str, provider: str, model: str, model_type: s def free_quota_submit(self, tenant_id: str, provider: str): api_key = os.environ.get("FREE_QUOTA_APPLY_API_KEY") api_base_url = os.environ.get("FREE_QUOTA_APPLY_BASE_URL") + if not api_base_url: + raise Exception("FREE_QUOTA_APPLY_BASE_URL is not set") + api_url = api_base_url + "/api/v1/providers/apply" headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"} @@ -546,6 +513,9 @@ def free_quota_submit(self, tenant_id: str, provider: str): def free_quota_qualification_verify(self, tenant_id: str, provider: str, token: Optional[str]): api_key = os.environ.get("FREE_QUOTA_APPLY_API_KEY") api_base_url = os.environ.get("FREE_QUOTA_APPLY_BASE_URL") + if not api_base_url: + raise Exception("FREE_QUOTA_APPLY_BASE_URL is not set") + api_url = api_base_url + "/api/v1/providers/qualification-verify" headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"} diff --git a/api/tests/integration_tests/model_runtime/test_model_provider_factory.py b/api/tests/integration_tests/model_runtime/test_model_provider_factory.py index 0ec4b0b7243176..5cb8a6252af20c 100644 --- a/api/tests/integration_tests/model_runtime/test_model_provider_factory.py +++ b/api/tests/integration_tests/model_runtime/test_model_provider_factory.py @@ -9,7 +9,7 @@ def test_get_providers(): - factory = ModelProviderFactory() + factory = ModelProviderFactory("test_tenant") providers = factory.get_providers() for provider in providers: @@ -20,7 +20,7 @@ def test_get_providers(): def test_get_models(): - factory = ModelProviderFactory() + factory = ModelProviderFactory("test_tenant") providers = factory.get_models( model_type=ModelType.LLM, provider_configs=[ @@ -51,19 +51,7 @@ def test_get_models(): def test_provider_credentials_validate(): - factory = ModelProviderFactory() + factory = ModelProviderFactory("test_tenant") factory.provider_credentials_validate( provider="openai", credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")} ) - - -def test__get_model_provider_map(): - factory = ModelProviderFactory() - model_providers = factory._get_model_provider_map() - - for name, model_provider in model_providers.items(): - logger.debug(name) - logger.debug(model_provider.provider_instance) - - assert len(model_providers) >= 1 - assert isinstance(model_providers["openai"], ModelProviderExtension) diff --git a/api/tests/integration_tests/workflow/nodes/test_llm.py b/api/tests/integration_tests/workflow/nodes/test_llm.py index dfb43650d20c1c..aff6e1c48199f8 100644 --- a/api/tests/integration_tests/workflow/nodes/test_llm.py +++ b/api/tests/integration_tests/workflow/nodes/test_llm.py @@ -115,7 +115,6 @@ def test_execute_llm(setup_openai_mock): custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)), model_settings=[], ), - provider_instance=provider_instance, model_type_instance=model_type_instance, ) model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model="gpt-3.5-turbo") @@ -203,7 +202,6 @@ def test_execute_llm_with_jinja2(setup_code_executor_mock, setup_openai_mock): custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)), model_settings=[], ), - provider_instance=provider_instance, model_type_instance=model_type_instance, ) diff --git a/api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py b/api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py index 88435c40227371..90c0d54e171a37 100644 --- a/api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py +++ b/api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py @@ -35,23 +35,27 @@ def get_mocked_fetch_model_config( mode: str, credentials: dict, ): - provider_instance = ModelProviderFactory().get_provider_instance(provider) - model_type_instance = provider_instance.get_model_instance(ModelType.LLM) + model_provider_factory = ModelProviderFactory(tenant_id="test_tenant") + model_type_instance = model_provider_factory.get_model_type_instance(provider, ModelType.LLM) provider_model_bundle = ProviderModelBundle( configuration=ProviderConfiguration( tenant_id="1", - provider=provider_instance.get_provider_schema(), + provider=model_provider_factory.get_provider_schema(provider), preferred_provider_type=ProviderType.CUSTOM, using_provider_type=ProviderType.CUSTOM, system_configuration=SystemConfiguration(enabled=False), custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)), model_settings=[], ), - provider_instance=provider_instance, model_type_instance=model_type_instance, ) model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model=model) - model_schema = model_type_instance.get_model_schema(model) + model_schema = model_provider_factory.get_model_schema( + provider=provider, + model_type=model_type_instance.model_type, + model=model, + credentials=credentials, + ) assert model_schema is not None model_config = ModelConfigWithCredentialsEntity( model=model, diff --git a/api/tests/unit_tests/core/test_provider_manager.py b/api/tests/unit_tests/core/test_provider_manager.py index 2f4214a5801de1..44284e03d0bfb5 100644 --- a/api/tests/unit_tests/core/test_provider_manager.py +++ b/api/tests/unit_tests/core/test_provider_manager.py @@ -1,12 +1,13 @@ from core.entities.provider_entities import ModelSettings from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.model_providers import model_provider_factory +from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory from core.provider_manager import ProviderManager from models.provider import LoadBalancingModelConfig, ProviderModelSetting def test__to_model_settings(mocker): # Get all provider entities + model_provider_factory = ModelProviderFactory("test_tenant") provider_entities = model_provider_factory.get_providers() provider_entity = None @@ -71,6 +72,7 @@ def test__to_model_settings(mocker): def test__to_model_settings_only_one_lb(mocker): # Get all provider entities + model_provider_factory = ModelProviderFactory("test_tenant") provider_entities = model_provider_factory.get_providers() provider_entity = None @@ -123,6 +125,7 @@ def test__to_model_settings_only_one_lb(mocker): def test__to_model_settings_lb_disabled(mocker): # Get all provider entities + model_provider_factory = ModelProviderFactory("test_tenant") provider_entities = model_provider_factory.get_providers() provider_entity = None From 47c8824be689b6224ba6e6f2b28f1d1484a9ecb0 Mon Sep 17 00:00:00 2001 From: takatost Date: Sun, 29 Sep 2024 00:14:44 +0800 Subject: [PATCH 061/325] feat: move model request to plugin daemon --- api/configs/feature/__init__.py | 14 +++--- api/controllers/console/app/workflow.py | 18 ++++---- api/controllers/console/workspace/plugin.py | 8 ++-- api/controllers/inner_api/plugin/__init__.py | 2 +- api/controllers/inner_api/plugin/wraps.py | 45 ++++++++++--------- api/core/agent/entities.py | 1 + api/core/agent/fc_agent_runner.py | 4 +- .../agent_chat/generate_response_converter.py | 10 +++-- .../base_app_generate_response_converter.py | 7 ++- api/core/app/apps/base_app_generator.py | 9 ++-- api/core/app/apps/chat/app_generator.py | 3 +- .../apps/chat/generate_response_converter.py | 10 +++-- api/core/app/apps/completion/app_generator.py | 12 +++-- .../completion/generate_response_converter.py | 10 +++-- api/core/app/apps/workflow/app_generator.py | 16 +++---- .../workflow/generate_response_converter.py | 10 +++-- .../plugin_tool_callback_handler.py | 2 +- api/core/entities/parameter_entities.py | 2 +- api/core/entities/provider_entities.py | 4 +- api/core/file/tool_file_parser.py | 4 +- api/core/plugin/backwards_invocation/node.py | 2 +- api/core/rag/retrieval/dataset_retrieval.py | 4 +- api/core/tools/entities/tool_entities.py | 3 -- .../utils/workflow_configuration_sync.py | 2 +- api/core/tools/workflow_as_tool/provider.py | 30 +++++++------ api/models/base.py | 2 +- .../tools/api_tools_manage_service.py | 6 +-- api/services/workflow_service.py | 4 +- .../plugin/tools/test_fetch_all_tools.py | 1 - 29 files changed, 127 insertions(+), 118 deletions(-) diff --git a/api/configs/feature/__init__.py b/api/configs/feature/__init__.py index 1b0364c2fc9835..8e03415ae03360 100644 --- a/api/configs/feature/__init__.py +++ b/api/configs/feature/__init__.py @@ -114,20 +114,18 @@ class PluginConfig(BaseSettings): """ Plugin configs """ + PLUGIN_API_URL: HttpUrl = Field( - description='Plugin API URL', - default='http://plugin:5002', + description="Plugin API URL", + default="http://plugin:5002", ) PLUGIN_API_KEY: str = Field( - description='Plugin API key', - default='plugin-api-key', + description="Plugin API key", + default="plugin-api-key", ) - INNER_API_KEY_FOR_PLUGIN: str = Field( - description='Inner api key for plugin', - default='inner-api-key' - ) + INNER_API_KEY_FOR_PLUGIN: str = Field(description="Inner api key for plugin", default="inner-api-key") class EndpointConfig(BaseSettings): diff --git a/api/controllers/console/app/workflow.py b/api/controllers/console/app/workflow.py index 19c6e14cc43758..22a1fbb563bf57 100644 --- a/api/controllers/console/app/workflow.py +++ b/api/controllers/console/app/workflow.py @@ -140,7 +140,7 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() @@ -167,7 +167,7 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() @@ -209,7 +209,7 @@ def post(self, app_model: App, node_id: str): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() @@ -246,7 +246,7 @@ def post(self, app_model: App, node_id: str): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() @@ -283,7 +283,7 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() @@ -336,7 +336,7 @@ def post(self, app_model: App, node_id: str): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() @@ -388,7 +388,7 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() @@ -428,7 +428,7 @@ def get(self, app_model: App, block_type: str): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() @@ -464,7 +464,7 @@ def post(self, app_model: App): # The role of the current user in the ta table must be admin, owner, or editor if not current_user.is_editor: raise Forbidden() - + if not isinstance(current_user, Account): raise Forbidden() diff --git a/api/controllers/console/workspace/plugin.py b/api/controllers/console/workspace/plugin.py index c3e89321d6bbf5..4001b69a595733 100644 --- a/api/controllers/console/workspace/plugin.py +++ b/api/controllers/console/workspace/plugin.py @@ -17,11 +17,9 @@ def get(self): user = current_user if not user.is_admin_or_owner: raise Forbidden() - + tenant_id = user.current_tenant_id - return { - "key": PluginDebuggingService.get_plugin_debugging_key(tenant_id) - } + return {"key": PluginDebuggingService.get_plugin_debugging_key(tenant_id)} -api.add_resource(PluginDebuggingKeyApi, "/workspaces/current/plugin/debugging-key") \ No newline at end of file +api.add_resource(PluginDebuggingKeyApi, "/workspaces/current/plugin/debugging-key") diff --git a/api/controllers/inner_api/plugin/__init__.py b/api/controllers/inner_api/plugin/__init__.py index fd1918e6b26fee..48aad58ec84321 100644 --- a/api/controllers/inner_api/plugin/__init__.py +++ b/api/controllers/inner_api/plugin/__init__.py @@ -1 +1 @@ -from .plugin import * \ No newline at end of file +from .plugin import * diff --git a/api/controllers/inner_api/plugin/wraps.py b/api/controllers/inner_api/plugin/wraps.py index aa1f36d33c7dc4..07249013f9e7f7 100644 --- a/api/controllers/inner_api/plugin/wraps.py +++ b/api/controllers/inner_api/plugin/wraps.py @@ -16,31 +16,36 @@ def decorator(view_func): def decorated_view(*args, **kwargs): # fetch json body parser = reqparse.RequestParser() - parser.add_argument('tenant_id', type=str, required=True, location='json') - parser.add_argument('user_id', type=str, required=True, location='json') + parser.add_argument("tenant_id", type=str, required=True, location="json") + parser.add_argument("user_id", type=str, required=True, location="json") kwargs = parser.parse_args() - user_id = kwargs.get('user_id') - tenant_id = kwargs.get('tenant_id') + user_id = kwargs.get("user_id") + tenant_id = kwargs.get("tenant_id") - del kwargs['tenant_id'] - del kwargs['user_id'] + del kwargs["tenant_id"] + del kwargs["user_id"] try: - tenant_model = db.session.query(Tenant).filter( - Tenant.id == tenant_id, - ).first() + tenant_model = ( + db.session.query(Tenant) + .filter( + Tenant.id == tenant_id, + ) + .first() + ) except Exception: - raise ValueError('tenant not found') + raise ValueError("tenant not found") if not tenant_model: - raise ValueError('tenant not found') + raise ValueError("tenant not found") - kwargs['tenant_model'] = tenant_model - kwargs['user_id'] = user_id + kwargs["tenant_model"] = tenant_model + kwargs["user_id"] = user_id return view_func(*args, **kwargs) + return decorated_view if view is None: @@ -55,18 +60,18 @@ def decorated_view(*args, **kwargs): try: data = request.get_json() except Exception: - raise ValueError('invalid json') - + raise ValueError("invalid json") + try: payload = payload_type(**data) except Exception as e: - raise ValueError(f'invalid payload: {str(e)}') - - kwargs['payload'] = payload + raise ValueError(f"invalid payload: {str(e)}") + + kwargs["payload"] = payload return view_func(*args, **kwargs) - + return decorated_view - + if view is None: return decorator else: diff --git a/api/core/agent/entities.py b/api/core/agent/entities.py index b51a1635495893..5287b9a7144fda 100644 --- a/api/core/agent/entities.py +++ b/api/core/agent/entities.py @@ -10,6 +10,7 @@ class AgentToolEntity(BaseModel): """ Agent Tool Entity. """ + provider_type: ToolProviderType provider_id: str tool_name: str diff --git a/api/core/agent/fc_agent_runner.py b/api/core/agent/fc_agent_runner.py index 991c542846626a..afdb1d70e22469 100644 --- a/api/core/agent/fc_agent_runner.py +++ b/api/core/agent/fc_agent_runner.py @@ -366,9 +366,7 @@ def extract_blocking_tool_calls(self, llm_result: LLMResult) -> list[tuple[str, return tool_calls - def _init_system_message( - self, prompt_template: str, prompt_messages: list[PromptMessage] - ) -> list[PromptMessage]: + def _init_system_message(self, prompt_template: str, prompt_messages: list[PromptMessage]) -> list[PromptMessage]: """ Initialize system message """ diff --git a/api/core/app/apps/agent_chat/generate_response_converter.py b/api/core/app/apps/agent_chat/generate_response_converter.py index 5f294432c94187..99c95b296af4f3 100644 --- a/api/core/app/apps/agent_chat/generate_response_converter.py +++ b/api/core/app/apps/agent_chat/generate_response_converter.py @@ -50,8 +50,9 @@ def convert_blocking_simple_response(cls, blocking_response: ChatbotAppBlockingR return response @classmethod - def convert_stream_full_response(cls, stream_response: Generator[ChatbotAppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_full_response( + cls, stream_response: Generator[ChatbotAppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: """ Convert stream full response. :param stream_response: stream response @@ -80,8 +81,9 @@ def convert_stream_full_response(cls, stream_response: Generator[ChatbotAppStrea yield response_chunk @classmethod - def convert_stream_simple_response(cls, stream_response: Generator[ChatbotAppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_simple_response( + cls, stream_response: Generator[ChatbotAppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: """ Convert stream simple response. :param stream_response: stream response diff --git a/api/core/app/apps/base_app_generate_response_converter.py b/api/core/app/apps/base_app_generate_response_converter.py index e5b77538c7bba0..c38e67d5779c68 100644 --- a/api/core/app/apps/base_app_generate_response_converter.py +++ b/api/core/app/apps/base_app_generate_response_converter.py @@ -20,6 +20,7 @@ def convert( if isinstance(response, AppBlockingResponse): return cls.convert_blocking_full_response(response) else: + def _generate_full_response() -> Generator[dict | str, Any, None]: yield from cls.convert_stream_simple_response(response) @@ -28,6 +29,7 @@ def _generate_full_response() -> Generator[dict | str, Any, None]: if isinstance(response, AppBlockingResponse): return cls.convert_blocking_simple_response(response) else: + def _generate_simple_response() -> Generator[dict | str, Any, None]: yield from cls.convert_stream_simple_response(response) @@ -45,8 +47,9 @@ def convert_blocking_simple_response(cls, blocking_response: AppBlockingResponse @classmethod @abstractmethod - def convert_stream_full_response(cls, stream_response: Generator[AppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_full_response( + cls, stream_response: Generator[AppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: raise NotImplementedError @classmethod diff --git a/api/core/app/apps/base_app_generator.py b/api/core/app/apps/base_app_generator.py index 2da0fd058401c0..06a18864b77874 100644 --- a/api/core/app/apps/base_app_generator.py +++ b/api/core/app/apps/base_app_generator.py @@ -64,11 +64,12 @@ def convert_to_event_stream(cls, generator: Union[dict, Generator[dict | str, No if isinstance(generator, dict): return generator else: + def gen(): for message in generator: if isinstance(message, dict): - yield f'data: {json.dumps(message)}\n\n' + yield f"data: {json.dumps(message)}\n\n" else: - yield f'event: {message}\n\n' - - return gen() \ No newline at end of file + yield f"event: {message}\n\n" + + return gen() diff --git a/api/core/app/apps/chat/app_generator.py b/api/core/app/apps/chat/app_generator.py index cec2217093f1cc..492ae4924409bc 100644 --- a/api/core/app/apps/chat/app_generator.py +++ b/api/core/app/apps/chat/app_generator.py @@ -50,7 +50,8 @@ def generate( @overload def generate( - self, app_model: App, + self, + app_model: App, user: Union[Account, EndUser], args: Any, invoke_from: InvokeFrom, diff --git a/api/core/app/apps/chat/generate_response_converter.py b/api/core/app/apps/chat/generate_response_converter.py index c7e29686e9de7f..f67df2f1ad5df1 100644 --- a/api/core/app/apps/chat/generate_response_converter.py +++ b/api/core/app/apps/chat/generate_response_converter.py @@ -50,8 +50,9 @@ def convert_blocking_simple_response(cls, blocking_response: ChatbotAppBlockingR return response @classmethod - def convert_stream_full_response(cls, stream_response: Generator[ChatbotAppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_full_response( + cls, stream_response: Generator[ChatbotAppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: """ Convert stream full response. :param stream_response: stream response @@ -80,8 +81,9 @@ def convert_stream_full_response(cls, stream_response: Generator[ChatbotAppStrea yield response_chunk @classmethod - def convert_stream_simple_response(cls, stream_response: Generator[ChatbotAppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_simple_response( + cls, stream_response: Generator[ChatbotAppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: """ Convert stream simple response. :param stream_response: stream response diff --git a/api/core/app/apps/completion/app_generator.py b/api/core/app/apps/completion/app_generator.py index 2e99e4ef709fb4..729ff1e1e0b522 100644 --- a/api/core/app/apps/completion/app_generator.py +++ b/api/core/app/apps/completion/app_generator.py @@ -52,19 +52,17 @@ def generate( @overload def generate( - self, app_model: App, + self, + app_model: App, user: Union[Account, EndUser], args: dict, invoke_from: InvokeFrom, stream: bool = False, ) -> dict | Generator[str, None, None]: ... - def generate(self, app_model: App, - user: Union[Account, EndUser], - args: Any, - invoke_from: InvokeFrom, - stream: bool = True) \ - -> Union[dict, Generator[str, None, None]]: + def generate( + self, app_model: App, user: Union[Account, EndUser], args: Any, invoke_from: InvokeFrom, stream: bool = True + ) -> Union[dict, Generator[str, None, None]]: """ Generate App response. diff --git a/api/core/app/apps/completion/generate_response_converter.py b/api/core/app/apps/completion/generate_response_converter.py index 77aa1e37a23202..6f8d0894d55424 100644 --- a/api/core/app/apps/completion/generate_response_converter.py +++ b/api/core/app/apps/completion/generate_response_converter.py @@ -49,8 +49,9 @@ def convert_blocking_simple_response(cls, blocking_response: CompletionAppBlocki return response @classmethod - def convert_stream_full_response(cls, stream_response: Generator[CompletionAppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_full_response( + cls, stream_response: Generator[CompletionAppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: """ Convert stream full response. :param stream_response: stream response @@ -78,8 +79,9 @@ def convert_stream_full_response(cls, stream_response: Generator[CompletionAppSt yield response_chunk @classmethod - def convert_stream_simple_response(cls, stream_response: Generator[CompletionAppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_simple_response( + cls, stream_response: Generator[CompletionAppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: """ Convert stream simple response. :param stream_response: stream response diff --git a/api/core/app/apps/workflow/app_generator.py b/api/core/app/apps/workflow/app_generator.py index f11fedebc886a7..8edbeee3dd5156 100644 --- a/api/core/app/apps/workflow/app_generator.py +++ b/api/core/app/apps/workflow/app_generator.py @@ -42,7 +42,7 @@ def generate( invoke_from: InvokeFrom, stream: Literal[True] = True, call_depth: int = 0, - workflow_thread_pool_id: Optional[str] = None + workflow_thread_pool_id: Optional[str] = None, ) -> Generator[dict | str, None, None]: ... @overload @@ -60,7 +60,8 @@ def generate( @overload def generate( - self, app_model: App, + self, + app_model: App, workflow: Workflow, user: Union[Account, EndUser], args: dict, @@ -143,7 +144,7 @@ def _generate( application_generate_entity: WorkflowAppGenerateEntity, invoke_from: InvokeFrom, stream: bool = True, - workflow_thread_pool_id: Optional[str] = None + workflow_thread_pool_id: Optional[str] = None, ) -> Union[dict, Generator[str | dict, None, None]]: """ Generate App response. @@ -189,12 +190,9 @@ def _generate( return WorkflowAppGenerateResponseConverter.convert(response=response, invoke_from=invoke_from) - def single_iteration_generate(self, app_model: App, - workflow: Workflow, - node_id: str, - user: Account | EndUser, - args: dict, - stream: bool = True) -> dict[str, Any] | Generator[str | dict, Any, None]: + def single_iteration_generate( + self, app_model: App, workflow: Workflow, node_id: str, user: Account | EndUser, args: dict, stream: bool = True + ) -> dict[str, Any] | Generator[str | dict, Any, None]: """ Generate App response. diff --git a/api/core/app/apps/workflow/generate_response_converter.py b/api/core/app/apps/workflow/generate_response_converter.py index 989834ef3b0ab0..72357e5e0c3927 100644 --- a/api/core/app/apps/workflow/generate_response_converter.py +++ b/api/core/app/apps/workflow/generate_response_converter.py @@ -34,8 +34,9 @@ def convert_blocking_simple_response(cls, blocking_response: WorkflowAppBlocking return cls.convert_blocking_full_response(blocking_response) @classmethod - def convert_stream_full_response(cls, stream_response: Generator[WorkflowAppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_full_response( + cls, stream_response: Generator[WorkflowAppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: """ Convert stream full response. :param stream_response: stream response @@ -62,8 +63,9 @@ def convert_stream_full_response(cls, stream_response: Generator[WorkflowAppStre yield response_chunk @classmethod - def convert_stream_simple_response(cls, stream_response: Generator[WorkflowAppStreamResponse, None, None]) \ - -> Generator[dict | str, None, None]: + def convert_stream_simple_response( + cls, stream_response: Generator[WorkflowAppStreamResponse, None, None] + ) -> Generator[dict | str, None, None]: """ Convert stream simple response. :param stream_response: stream response diff --git a/api/core/callback_handler/plugin_tool_callback_handler.py b/api/core/callback_handler/plugin_tool_callback_handler.py index e9b9784014fe35..033b8d423cc246 100644 --- a/api/core/callback_handler/plugin_tool_callback_handler.py +++ b/api/core/callback_handler/plugin_tool_callback_handler.py @@ -2,4 +2,4 @@ class DifyPluginCallbackHandler(DifyAgentCallbackHandler): - """Callback Handler that prints to std out.""" \ No newline at end of file + """Callback Handler that prints to std out.""" diff --git a/api/core/entities/parameter_entities.py b/api/core/entities/parameter_entities.py index cc402de7736a55..0045fbf2b49f88 100644 --- a/api/core/entities/parameter_entities.py +++ b/api/core/entities/parameter_entities.py @@ -27,4 +27,4 @@ class ModelConfigScope(Enum): TTS = "tts" SPEECH2TEXT = "speech2text" MODERATION = "moderation" - VISION = "vision" \ No newline at end of file + VISION = "vision" diff --git a/api/core/entities/provider_entities.py b/api/core/entities/provider_entities.py index 88b16f13afb0aa..53d52b5866c0ea 100644 --- a/api/core/entities/provider_entities.py +++ b/api/core/entities/provider_entities.py @@ -116,6 +116,7 @@ class BasicProviderConfig(BaseModel): """ Base model class for common provider settings like credentials """ + class Type(Enum): SECRET_INPUT = CommonParameterType.SECRET_INPUT.value TEXT_INPUT = CommonParameterType.TEXT_INPUT.value @@ -135,7 +136,7 @@ def value_of(cls, value: str) -> "ProviderConfig.Type": for mode in cls: if mode.value == value: return mode - raise ValueError(f'invalid mode value {value}') + raise ValueError(f"invalid mode value {value}") type: Type = Field(..., description="The type of the credentials") name: str = Field(..., description="The name of the credentials") @@ -145,6 +146,7 @@ class ProviderConfig(BasicProviderConfig): """ Model class for common provider settings like credentials """ + class Option(BaseModel): value: str = Field(..., description="The value of the option") label: I18nObject = Field(..., description="The label of the option") diff --git a/api/core/file/tool_file_parser.py b/api/core/file/tool_file_parser.py index 4d113a9cc28e2e..a17b7be3675ab1 100644 --- a/api/core/file/tool_file_parser.py +++ b/api/core/file/tool_file_parser.py @@ -3,9 +3,7 @@ if TYPE_CHECKING: from core.tools.tool_file_manager import ToolFileManager -tool_file_manager: dict[str, Any] = { - 'manager': None -} +tool_file_manager: dict[str, Any] = {"manager": None} class ToolFileParser: diff --git a/api/core/plugin/backwards_invocation/node.py b/api/core/plugin/backwards_invocation/node.py index 4c1d21437e609f..1bd5d84e4c6488 100644 --- a/api/core/plugin/backwards_invocation/node.py +++ b/api/core/plugin/backwards_invocation/node.py @@ -114,4 +114,4 @@ def invoke_question_classifier( "inputs": execution.inputs_dict, "outputs": execution.outputs_dict, "process_data": execution.process_data_dict, - } \ No newline at end of file + } diff --git a/api/core/rag/retrieval/dataset_retrieval.py b/api/core/rag/retrieval/dataset_retrieval.py index bd5cf86628de14..ebcf5a2575b98b 100644 --- a/api/core/rag/retrieval/dataset_retrieval.py +++ b/api/core/rag/retrieval/dataset_retrieval.py @@ -492,8 +492,9 @@ def to_dataset_retriever_tool( score_threshold_enabled = retrieval_model_config.get("score_threshold_enabled") if score_threshold_enabled: score_threshold = retrieval_model_config.get("score_threshold") - + from core.tools.utils.dataset_retriever.dataset_retriever_tool import DatasetRetrieverTool + tool = DatasetRetrieverTool.from_dataset( dataset=dataset, top_k=top_k, @@ -506,6 +507,7 @@ def to_dataset_retriever_tool( tools.append(tool) elif retrieve_config.retrieve_strategy == DatasetRetrieveConfigEntity.RetrieveStrategy.MULTIPLE: from core.tools.utils.dataset_retriever.dataset_multi_retriever_tool import DatasetMultiRetrieverTool + tool = DatasetMultiRetrieverTool.from_dataset( dataset_ids=[dataset.id for dataset in available_datasets], tenant_id=tenant_id, diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 07ea2d2b11f1fe..0808ff721d16d2 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -375,6 +375,3 @@ class ToolInvokeFrom(Enum): WORKFLOW = "workflow" AGENT = "agent" - - - diff --git a/api/core/tools/utils/workflow_configuration_sync.py b/api/core/tools/utils/workflow_configuration_sync.py index 7f20605024d1f1..df09609402d181 100644 --- a/api/core/tools/utils/workflow_configuration_sync.py +++ b/api/core/tools/utils/workflow_configuration_sync.py @@ -43,4 +43,4 @@ def check_is_synced( for parameter in tool_configurations: if parameter.name not in variable_names: - raise ValueError('parameter configuration mismatch, please republish the tool to update') + raise ValueError("parameter configuration mismatch, please republish the tool to update") diff --git a/api/core/tools/workflow_as_tool/provider.py b/api/core/tools/workflow_as_tool/provider.py index 2d0d33ffd9a138..dec353ec93469b 100644 --- a/api/core/tools/workflow_as_tool/provider.py +++ b/api/core/tools/workflow_as_tool/provider.py @@ -65,7 +65,7 @@ def from_db(cls, db_provider: WorkflowToolProvider) -> "WorkflowToolProviderCont @property def provider_type(self) -> ToolProviderType: return ToolProviderType.WORKFLOW - + def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> WorkflowTool: """ get db provider tool @@ -73,10 +73,11 @@ def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> :param app: the app :return: the tool """ - workflow: Workflow | None = db.session.query(Workflow).filter( - Workflow.app_id == db_provider.app_id, - Workflow.version == db_provider.version - ).first() + workflow: Workflow | None = ( + db.session.query(Workflow) + .filter(Workflow.app_id == db_provider.app_id, Workflow.version == db_provider.version) + .first() + ) if not workflow: raise ValueError("workflow not found") @@ -84,10 +85,7 @@ def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> # fetch start node graph: Mapping = workflow.graph_dict features_dict: Mapping = workflow.features_dict - features = WorkflowAppConfigManager.convert_features( - config_dict=features_dict, - app_mode=AppMode.WORKFLOW - ) + features = WorkflowAppConfigManager.convert_features(config_dict=features_dict, app_mode=AppMode.WORKFLOW) parameters = db_provider.parameter_configurations variables = WorkflowToolConfigurationUtils.get_workflow_graph_variables(graph) @@ -180,14 +178,18 @@ def get_tools(self, tenant_id: str) -> list[WorkflowTool]: if self.tools is not None: return self.tools - db_providers: WorkflowToolProvider | None = db.session.query(WorkflowToolProvider).filter( - WorkflowToolProvider.tenant_id == tenant_id, - WorkflowToolProvider.app_id == self.provider_id, - ).first() + db_providers: WorkflowToolProvider | None = ( + db.session.query(WorkflowToolProvider) + .filter( + WorkflowToolProvider.tenant_id == tenant_id, + WorkflowToolProvider.app_id == self.provider_id, + ) + .first() + ) if not db_providers: return [] - + app = db_providers.app if not app: raise ValueError("can not read app of workflow") diff --git a/api/models/base.py b/api/models/base.py index 1c2dcc40b94f8a..fa2b68a5d245bb 100644 --- a/api/models/base.py +++ b/api/models/base.py @@ -2,4 +2,4 @@ class Base(DeclarativeBase): - pass \ No newline at end of file + pass diff --git a/api/services/tools/api_tools_manage_service.py b/api/services/tools/api_tools_manage_service.py index 58f0e7bbf52098..82bfc8c8e5bcfe 100644 --- a/api/services/tools/api_tools_manage_service.py +++ b/api/services/tools/api_tools_manage_service.py @@ -161,7 +161,7 @@ def create_api_tool_provider( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.entity.identity.name + provider_identity=provider_controller.entity.identity.name, ) encrypted_credentials = tool_configuration.encrypt(credentials) @@ -293,7 +293,7 @@ def update_api_tool_provider( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.entity.identity.name + provider_identity=provider_controller.entity.identity.name, ) original_credentials = tool_configuration.decrypt(provider.credentials) @@ -412,7 +412,7 @@ def test_api_tool_preview( tenant_id=tenant_id, config=provider_controller.get_credentials_schema(), provider_type=provider_controller.provider_type.value, - provider_identity=provider_controller.entity.identity.name + provider_identity=provider_controller.entity.identity.name, ) decrypted_credentials = tool_configuration.decrypt(credentials) # check if the credential has changed, save the original credential diff --git a/api/services/workflow_service.py b/api/services/workflow_service.py index a1e2f3105738b8..eec3d26a7b1b5a 100644 --- a/api/services/workflow_service.py +++ b/api/services/workflow_service.py @@ -238,7 +238,7 @@ def run_draft_workflow_node( db.session.commit() return workflow_node_execution - + def run_free_workflow_node( self, node_data: dict, tenant_id: str, user_id: str, node_id: str, user_inputs: dict[str, Any] ) -> WorkflowNodeExecution: @@ -258,7 +258,7 @@ def run_free_workflow_node( ), start_at=start_at, tenant_id=tenant_id, - node_id=node_id + node_id=node_id, ) return workflow_node_execution diff --git a/api/tests/integration_tests/plugin/tools/test_fetch_all_tools.py b/api/tests/integration_tests/plugin/tools/test_fetch_all_tools.py index d50bba4eccc103..c6d836ed6dd965 100644 --- a/api/tests/integration_tests/plugin/tools/test_fetch_all_tools.py +++ b/api/tests/integration_tests/plugin/tools/test_fetch_all_tools.py @@ -6,4 +6,3 @@ def test_fetch_all_plugin_tools(setup_http_mock): manager = PluginToolManager() tools = manager.fetch_tool_providers(tenant_id="test-tenant") assert len(tools) >= 1 - From 7b76b1ff82b3cb28f5ef2da024f9a9629449a2cb Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Sun, 29 Sep 2024 13:12:22 +0800 Subject: [PATCH 062/325] Merge fix/chore-fix into fix/chore-fix --- api/core/plugin/entities/plugin_daemon.py | 19 ++++++++ api/core/plugin/manager/base.py | 56 +++++++++++++++++------ api/core/tools/tool_manager.py | 3 -- 3 files changed, 61 insertions(+), 17 deletions(-) diff --git a/api/core/plugin/entities/plugin_daemon.py b/api/core/plugin/entities/plugin_daemon.py index 554353c6c9e938..ebce6e6cee649f 100644 --- a/api/core/plugin/entities/plugin_daemon.py +++ b/api/core/plugin/entities/plugin_daemon.py @@ -87,3 +87,22 @@ class PluginVoiceEntity(BaseModel): class PluginVoicesResponse(BaseModel): voices: list[PluginVoiceEntity] = Field(description="The result of the voices.") + + +class PluginDaemonError(BaseModel): + """ + Error from plugin daemon. + """ + + error_type: str + message: str + args: Optional[dict] = None + + +class PluginDaemonInnerError(Exception): + code: int + message: str + + def __init__(self, code: int, message: str): + self.code = code + self.message = message diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index 1e050427d4e890..cb402849e982a2 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -1,13 +1,20 @@ import json from collections.abc import Callable, Generator -from typing import TypeVar +from typing import Optional, TypeVar import requests from pydantic import BaseModel from yarl import URL from configs import dify_config -from core.plugin.entities.plugin_daemon import PluginDaemonBasicResponse +from core.model_runtime.errors.invoke import ( + InvokeAuthorizationError, + InvokeBadRequestError, + InvokeConnectionError, + InvokeRateLimitError, + InvokeServerUnavailableError, +) +from core.plugin.entities.plugin_daemon import PluginDaemonBasicResponse, PluginDaemonError, PluginDaemonInnerError plugin_daemon_inner_api_baseurl = dify_config.PLUGIN_API_URL plugin_daemon_inner_api_key = dify_config.PLUGIN_API_KEY @@ -110,6 +117,12 @@ def _request_with_plugin_daemon_response( rep = PluginDaemonBasicResponse[type](**json_response) if rep.code != 0: + if rep.code == -500: + try: + error = PluginDaemonError(**json.loads(rep.message)) + self._handle_plugin_daemon_error(error.error_type, error.message, error.args) + except Exception as e: + raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") if rep.data is None: raise ValueError("got empty data from plugin daemon") @@ -132,19 +145,34 @@ def _request_with_plugin_daemon_response_stream( line_data = json.loads(line) rep = PluginDaemonBasicResponse[type](**line_data) if rep.code != 0: - raise PluginDaemonRespError(rep.message, rep.code) + if rep.code == -500: + try: + error = PluginDaemonError(**json.loads(rep.message)) + self._handle_plugin_daemon_error(error.error_type, error.message, error.args) + except Exception as e: + raise PluginDaemonInnerError(code=rep.code, message=rep.message) + raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") if rep.data is None: raise ValueError("got empty data from plugin daemon") yield rep.data - -class PluginDaemonRespError(Exception): - """ - Plugin daemon response error. - """ - - def __init__(self, resp_message: str, code: int): - super().__init__() - self.message = f"got error from plugin daemon: {resp_message}, code: {code}" - self.resp_message = resp_message - self.code = code + def _handle_plugin_daemon_error(self, error_type: str, message: str, args: Optional[dict] = None): + """ + handle the error from plugin daemon + """ + args = args or {} + + if error_type == PluginDaemonInnerError.__name__: + raise PluginDaemonInnerError(code=-500, message=message) + elif error_type == InvokeRateLimitError.__name__: + raise InvokeRateLimitError(description=args.get("description")) + elif error_type == InvokeAuthorizationError.__name__: + raise InvokeAuthorizationError(description=args.get("description")) + elif error_type == InvokeBadRequestError.__name__: + raise InvokeBadRequestError(description=args.get("description")) + elif error_type == InvokeConnectionError.__name__: + raise InvokeConnectionError(description=args.get("description")) + elif error_type == InvokeServerUnavailableError.__name__: + raise InvokeServerUnavailableError(description=args.get("description")) + else: + raise ValueError(f"got unknown error from plugin daemon: {error_type}, message: {message}, args: {args}") diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 225cd0c251f596..698ce3e900639d 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -618,9 +618,6 @@ def user_get_api_provider(cls, provider: str, tenant_id: str) -> dict: """ get api provider """ - """ - get tool provider - """ provider_obj: ApiToolProvider | None = ( db.session.query(ApiToolProvider) .filter( From 635a53ea38cad192c169060c475158b624d8e028 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Sun, 29 Sep 2024 13:23:14 +0800 Subject: [PATCH 063/325] fix: import undefined types --- api/core/plugin/manager/model.py | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/api/core/plugin/manager/model.py b/api/core/plugin/manager/model.py index e34e9b516efa90..30bd9bc0a8e034 100644 --- a/api/core/plugin/manager/model.py +++ b/api/core/plugin/manager/model.py @@ -10,13 +10,14 @@ from core.model_runtime.utils.encoders import jsonable_encoder from core.plugin.entities.plugin_daemon import ( PluginBasicBooleanResponse, + PluginDaemonInnerError, PluginModelProviderEntity, PluginModelSchemaEntity, PluginNumTokensResponse, PluginStringResultResponse, PluginVoicesResponse, ) -from core.plugin.manager.base import BasePluginManager, PluginDaemonRespError +from core.plugin.manager.base import BasePluginManager class PluginModelManager(BasePluginManager): @@ -179,8 +180,8 @@ def invoke_llm( try: yield from response - except PluginDaemonRespError as e: - raise ValueError(e.resp_message + str(e.code)) + except PluginDaemonInnerError as e: + raise ValueError(e.message + str(e.code)) def get_llm_num_tokens( self, @@ -395,8 +396,8 @@ def invoke_tts( for result in response: hex_str = result.result yield binascii.unhexlify(hex_str) - except PluginDaemonRespError as e: - raise ValueError(e.resp_message + str(e.code)) + except PluginDaemonInnerError as e: + raise ValueError(e.message + str(e.code)) def get_tts_model_voices( self, From 735e57b73a27aa59960ca9a439e755d20124f4a5 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Sun, 29 Sep 2024 13:46:16 +0800 Subject: [PATCH 064/325] fix: transform generic error message into correct type --- api/core/plugin/manager/base.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/api/core/plugin/manager/base.py b/api/core/plugin/manager/base.py index cb402849e982a2..ebfa68b914d882 100644 --- a/api/core/plugin/manager/base.py +++ b/api/core/plugin/manager/base.py @@ -120,9 +120,10 @@ def _request_with_plugin_daemon_response( if rep.code == -500: try: error = PluginDaemonError(**json.loads(rep.message)) - self._handle_plugin_daemon_error(error.error_type, error.message, error.args) except Exception as e: raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") + + self._handle_plugin_daemon_error(error.error_type, error.message, error.args) raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") if rep.data is None: raise ValueError("got empty data from plugin daemon") @@ -148,9 +149,10 @@ def _request_with_plugin_daemon_response_stream( if rep.code == -500: try: error = PluginDaemonError(**json.loads(rep.message)) - self._handle_plugin_daemon_error(error.error_type, error.message, error.args) except Exception as e: raise PluginDaemonInnerError(code=rep.code, message=rep.message) + + self._handle_plugin_daemon_error(error.error_type, error.message, error.args) raise ValueError(f"got error from plugin daemon: {rep.message}, code: {rep.code}") if rep.data is None: raise ValueError("got empty data from plugin daemon") From c8bc3892b339e0c36e40683e05d870399a011dca Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Sun, 29 Sep 2024 14:44:22 +0800 Subject: [PATCH 065/325] refactor: invoke tool from dify --- api/core/plugin/manager/tool.py | 52 +++++++++++++++++++++++++++++---- api/core/tools/tool_manager.py | 8 ++--- 2 files changed, 50 insertions(+), 10 deletions(-) diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py index 4f5fa1fa5ccfba..5981bcb55eb9e8 100644 --- a/api/core/plugin/manager/tool.py +++ b/api/core/plugin/manager/tool.py @@ -7,9 +7,23 @@ class PluginToolManager(BasePluginManager): + def _split_provider(self, provider: str) -> tuple[str, str]: + """ + split the provider to plugin_id and provider_name + + provider follows format: plugin_id/provider_name + """ + if "/" in provider: + parts = provider.split("/", 1) + if len(parts) == 2: + return parts[0], parts[1] + raise ValueError(f"invalid provider format: {provider}") + + raise ValueError(f"invalid provider format: {provider}") + def fetch_tool_providers(self, tenant_id: str) -> list[PluginToolProviderEntity]: """ - Fetch tool providers for the given asset. + Fetch tool providers for the given tenant. """ def transformer(json_response: dict[str, Any]) -> dict: @@ -28,18 +42,44 @@ def transformer(json_response: dict[str, Any]) -> dict: params={"page": 1, "page_size": 256}, transformer=transformer, ) + + for provider in response: + provider.declaration.identity.name = f"{provider.plugin_id}/{provider.declaration.identity.name}" + + return response + + def fetch_tool_provider(self, tenant_id: str, provider: str) -> PluginToolProviderEntity: + """ + Fetch tool provider for the given tenant and plugin. + """ + plugin_id, provider_name = self._split_provider(provider) + + response = self._request_with_plugin_daemon_response( + "GET", + f"plugin/{tenant_id}/management/tool", + PluginToolProviderEntity, + params={"provider": provider_name, "plugin_id": plugin_id}, + ) + + response.declaration.identity.name = f"{response.plugin_id}/{response.declaration.identity.name}" + return response def invoke( self, tenant_id: str, user_id: str, - plugin_id: str, tool_provider: str, tool_name: str, credentials: dict[str, Any], tool_parameters: dict[str, Any], ) -> Generator[ToolInvokeMessage, None, None]: + """ + Invoke the tool with the given tenant, user, plugin, provider, name, credentials and parameters. + """ + + plugin_id, provider_name = self._split_provider(tool_provider) + response = self._request_with_plugin_daemon_response_stream( "POST", f"plugin/{tenant_id}/dispatch/tool/invoke", @@ -47,7 +87,7 @@ def invoke( data={ "user_id": user_id, "data": { - "provider": tool_provider, + "provider": provider_name, "tool": tool_name, "credentials": credentials, "tool_parameters": tool_parameters, @@ -61,11 +101,13 @@ def invoke( return response def validate_provider_credentials( - self, tenant_id: str, user_id: str, plugin_id: str, provider: str, credentials: dict[str, Any] + self, tenant_id: str, user_id: str, provider: str, credentials: dict[str, Any] ) -> bool: """ validate the credentials of the provider """ + plugin_id, provider_name = self._split_provider(provider) + response = self._request_with_plugin_daemon_response_stream( "POST", f"plugin/{tenant_id}/dispatch/tool/validate_credentials", @@ -73,7 +115,7 @@ def validate_provider_credentials( data={ "user_id": user_id, "data": { - "provider": provider, + "provider": provider_name, "credentials": credentials, }, }, diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 698ce3e900639d..0463f84817bdfc 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -59,6 +59,8 @@ def get_builtin_provider( :param tenant_id: the id of the tenant :return: the provider """ + # split provider to + if len(cls._hardcoded_providers) == 0: # init the builtin providers cls.load_hardcoded_providers_cache() @@ -77,8 +79,7 @@ def get_plugin_provider(cls, provider: str, tenant_id: str) -> PluginToolProvide get the plugin provider """ manager = PluginToolManager() - providers = manager.fetch_tool_providers(tenant_id) - provider_entity = next((x for x in providers if x.declaration.identity.name == provider), None) + provider_entity = manager.fetch_tool_provider(tenant_id, provider) if not provider_entity: raise ToolProviderNotFoundError(f"plugin provider {provider} not found") @@ -181,9 +182,6 @@ def get_tool_runtime( ) elif provider_type == ToolProviderType.API: - if tenant_id is None: - raise ValueError("tenant id is required for api provider") - api_provider, credentials = cls.get_api_provider_controller(tenant_id, provider_id) # decrypt the credentials From e9e5c8806ab9c84b021fa17fae62da8cbf444adb Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Sun, 29 Sep 2024 17:00:58 +0800 Subject: [PATCH 066/325] refactor: using DeclarativeBase as parent class of models, refactored tools --- api/controllers/console/setup.py | 4 +- .../console/workspace/tool_providers.py | 13 ++- api/core/plugin/manager/tool.py | 21 +++- api/core/tools/plugin_tool/provider.py | 7 +- api/core/tools/plugin_tool/tool.py | 6 +- api/core/tools/tool_manager.py | 11 +- api/migrations/env.py | 7 +- ...ase_max_length_of_builtin_tool_provider.py | 39 +++++++ api/models/base.py | 6 +- api/models/model.py | 107 +++++++++--------- api/models/provider.py | 15 +-- api/models/source.py | 5 +- api/models/task.py | 5 +- api/models/tool.py | 3 +- api/models/tools.py | 52 ++++++++- api/models/web.py | 5 +- api/models/workflow.py | 39 ++++--- 17 files changed, 225 insertions(+), 120 deletions(-) create mode 100644 api/migrations/versions/2024_09_29_0835-ddcc8bbef391_increase_max_length_of_builtin_tool_provider.py diff --git a/api/controllers/console/setup.py b/api/controllers/console/setup.py index 46b4ef5d87a8a0..b66e74aee0cf84 100644 --- a/api/controllers/console/setup.py +++ b/api/controllers/console/setup.py @@ -6,7 +6,7 @@ from configs import dify_config from libs.helper import StrLen, email, get_remote_ip from libs.password import valid_password -from models.model import DifySetup +from models.model import DifySetup, db from services.account_service import RegisterService, TenantService from . import api @@ -69,7 +69,7 @@ def decorated(*args, **kwargs): def get_setup_status(): if dify_config.EDITION == "SELF_HOSTED": - return DifySetup.query.first() + return db.session.query(DifySetup).first() else: return True diff --git a/api/controllers/console/workspace/tool_providers.py b/api/controllers/console/workspace/tool_providers.py index 1b49103ced63ed..14edc9ac136ba7 100644 --- a/api/controllers/console/workspace/tool_providers.py +++ b/api/controllers/console/workspace/tool_providers.py @@ -610,16 +610,17 @@ def get(self): api.add_resource(ToolProviderListApi, "/workspaces/current/tool-providers") # builtin tool provider -api.add_resource(ToolBuiltinProviderListToolsApi, "/workspaces/current/tool-provider/builtin//tools") -api.add_resource(ToolBuiltinProviderDeleteApi, "/workspaces/current/tool-provider/builtin//delete") -api.add_resource(ToolBuiltinProviderUpdateApi, "/workspaces/current/tool-provider/builtin//update") +api.add_resource(ToolBuiltinProviderListToolsApi, "/workspaces/current/tool-provider/builtin//tools") +api.add_resource(ToolBuiltinProviderDeleteApi, "/workspaces/current/tool-provider/builtin//delete") +api.add_resource(ToolBuiltinProviderUpdateApi, "/workspaces/current/tool-provider/builtin//update") api.add_resource( - ToolBuiltinProviderGetCredentialsApi, "/workspaces/current/tool-provider/builtin//credentials" + ToolBuiltinProviderGetCredentialsApi, "/workspaces/current/tool-provider/builtin//credentials" ) api.add_resource( - ToolBuiltinProviderCredentialsSchemaApi, "/workspaces/current/tool-provider/builtin//credentials_schema" + ToolBuiltinProviderCredentialsSchemaApi, + "/workspaces/current/tool-provider/builtin//credentials_schema", ) -api.add_resource(ToolBuiltinProviderIconApi, "/workspaces/current/tool-provider/builtin//icon") +api.add_resource(ToolBuiltinProviderIconApi, "/workspaces/current/tool-provider/builtin//icon") # api tool provider api.add_resource(ToolApiProviderAddApi, "/workspaces/current/tool-provider/api/add") diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py index 5981bcb55eb9e8..50970243a11955 100644 --- a/api/core/plugin/manager/tool.py +++ b/api/core/plugin/manager/tool.py @@ -14,9 +14,9 @@ def _split_provider(self, provider: str) -> tuple[str, str]: provider follows format: plugin_id/provider_name """ if "/" in provider: - parts = provider.split("/", 1) - if len(parts) == 2: - return parts[0], parts[1] + parts = provider.split("/", -1) + if len(parts) >= 2: + return "/".join(parts[:-1]), parts[-1] raise ValueError(f"invalid provider format: {provider}") raise ValueError(f"invalid provider format: {provider}") @@ -46,6 +46,10 @@ def transformer(json_response: dict[str, Any]) -> dict: for provider in response: provider.declaration.identity.name = f"{provider.plugin_id}/{provider.declaration.identity.name}" + # override the provider name for each tool to plugin_id/provider_name + for tool in provider.declaration.tools: + tool.identity.provider = provider.declaration.identity.name + return response def fetch_tool_provider(self, tenant_id: str, provider: str) -> PluginToolProviderEntity: @@ -54,15 +58,26 @@ def fetch_tool_provider(self, tenant_id: str, provider: str) -> PluginToolProvid """ plugin_id, provider_name = self._split_provider(provider) + def transformer(json_response: dict[str, Any]) -> dict: + for tool in json_response.get("data", {}).get("declaration", {}).get("tools", []): + tool["identity"]["provider"] = provider_name + + return json_response + response = self._request_with_plugin_daemon_response( "GET", f"plugin/{tenant_id}/management/tool", PluginToolProviderEntity, params={"provider": provider_name, "plugin_id": plugin_id}, + transformer=transformer, ) response.declaration.identity.name = f"{response.plugin_id}/{response.declaration.identity.name}" + # override the provider name for each tool to plugin_id/provider_name + for tool in response.declaration.tools: + tool.identity.provider = response.declaration.identity.name + return response def invoke( diff --git a/api/core/tools/plugin_tool/provider.py b/api/core/tools/plugin_tool/provider.py index 4982e7405662d2..b6758df2bb106d 100644 --- a/api/core/tools/plugin_tool/provider.py +++ b/api/core/tools/plugin_tool/provider.py @@ -11,12 +11,10 @@ class PluginToolProviderController(BuiltinToolProviderController): entity: ToolProviderEntityWithPlugin tenant_id: str - plugin_id: str - def __init__(self, entity: ToolProviderEntityWithPlugin, tenant_id: str, plugin_id: str) -> None: + def __init__(self, entity: ToolProviderEntityWithPlugin, tenant_id: str) -> None: self.entity = entity self.tenant_id = tenant_id - self.plugin_id = plugin_id @property def provider_type(self) -> ToolProviderType: @@ -35,7 +33,6 @@ def _validate_credentials(self, user_id: str, credentials: dict[str, Any]) -> No if not manager.validate_provider_credentials( tenant_id=self.tenant_id, user_id=user_id, - plugin_id=self.plugin_id, provider=self.entity.identity.name, credentials=credentials, ): @@ -54,7 +51,6 @@ def get_tool(self, tool_name: str) -> PluginTool: entity=tool_entity, runtime=ToolRuntime(tenant_id=self.tenant_id), tenant_id=self.tenant_id, - plugin_id=self.plugin_id, ) def get_tools(self) -> list[PluginTool]: @@ -66,7 +62,6 @@ def get_tools(self) -> list[PluginTool]: entity=tool_entity, runtime=ToolRuntime(tenant_id=self.tenant_id), tenant_id=self.tenant_id, - plugin_id=self.plugin_id, ) for tool_entity in self.entity.tools ] diff --git a/api/core/tools/plugin_tool/tool.py b/api/core/tools/plugin_tool/tool.py index 7a4f147cd04085..7c6c4de3e00828 100644 --- a/api/core/tools/plugin_tool/tool.py +++ b/api/core/tools/plugin_tool/tool.py @@ -9,12 +9,10 @@ class PluginTool(Tool): tenant_id: str - plugin_id: str - def __init__(self, entity: ToolEntity, runtime: ToolRuntime, tenant_id: str, plugin_id: str) -> None: + def __init__(self, entity: ToolEntity, runtime: ToolRuntime, tenant_id: str) -> None: super().__init__(entity, runtime) self.tenant_id = tenant_id - self.plugin_id = plugin_id @property def tool_provider_type(self) -> ToolProviderType: @@ -25,7 +23,6 @@ def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Generator[To return manager.invoke( tenant_id=self.tenant_id, user_id=user_id, - plugin_id=self.plugin_id, tool_provider=self.entity.identity.provider, tool_name=self.entity.identity.name, credentials=self.runtime.credentials, @@ -37,5 +34,4 @@ def fork_tool_runtime(self, runtime: ToolRuntime) -> "PluginTool": entity=self.entity, runtime=runtime, tenant_id=self.tenant_id, - plugin_id=self.plugin_id, ) diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 0463f84817bdfc..fdd7e8385b3971 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -86,7 +86,6 @@ def get_plugin_provider(cls, provider: str, tenant_id: str) -> PluginToolProvide return PluginToolProviderController( entity=provider_entity.declaration, tenant_id=tenant_id, - plugin_id=provider_entity.plugin_id, ) @classmethod @@ -158,12 +157,11 @@ def get_tool_runtime( # decrypt the credentials credentials = builtin_provider.credentials - controller = cls.get_builtin_provider(provider_id, tenant_id) tool_configuration = ProviderConfigEncrypter( tenant_id=tenant_id, - config=controller.get_credentials_schema(), - provider_type=controller.provider_type.value, - provider_identity=controller.entity.identity.name, + config=provider_controller.get_credentials_schema(), + provider_type=provider_controller.provider_type.value, + provider_identity=provider_controller.entity.identity.name, ) decrypted_credentials = tool_configuration.decrypt(credentials) @@ -400,7 +398,6 @@ def list_plugin_providers(cls, tenant_id: str) -> list[PluginToolProviderControl PluginToolProviderController( entity=provider.declaration, tenant_id=tenant_id, - plugin_id=provider.plugin_id, ) for provider in provider_entities ] @@ -525,7 +522,7 @@ def list_providers_from_api( ) if isinstance(provider, PluginToolProviderController): - result_providers[f"plugin_provider.{user_provider.name}.{provider.plugin_id}"] = user_provider + result_providers[f"plugin_provider.{user_provider.name}"] = user_provider else: result_providers[f"builtin_provider.{user_provider.name}"] = user_provider diff --git a/api/migrations/env.py b/api/migrations/env.py index ad3a122c04bc2d..a5d815dcfd44bc 100644 --- a/api/migrations/env.py +++ b/api/migrations/env.py @@ -31,19 +31,16 @@ def get_engine_url(): # from myapp import mymodel # target_metadata = mymodel.Base.metadata config.set_main_option('sqlalchemy.url', get_engine_url()) -target_db = current_app.extensions['migrate'].db # other values from the config, defined by the needs of env.py, # can be acquired: # my_important_option = config.get_main_option("my_important_option") # ... etc. +from models.base import Base def get_metadata(): - if hasattr(target_db, 'metadatas'): - return target_db.metadatas[None] - return target_db.metadata - + return Base.metadata def include_object(object, name, type_, reflected, compare_to): if type_ == "foreign_key_constraint": diff --git a/api/migrations/versions/2024_09_29_0835-ddcc8bbef391_increase_max_length_of_builtin_tool_provider.py b/api/migrations/versions/2024_09_29_0835-ddcc8bbef391_increase_max_length_of_builtin_tool_provider.py new file mode 100644 index 00000000000000..4b16fe7f310442 --- /dev/null +++ b/api/migrations/versions/2024_09_29_0835-ddcc8bbef391_increase_max_length_of_builtin_tool_provider.py @@ -0,0 +1,39 @@ +"""increase max length of builtin tool provider + +Revision ID: ddcc8bbef391 +Revises: d57ba9ebb251 +Create Date: 2024-09-29 08:35:58.062698 + +""" +from alembic import op +import models as models +import sqlalchemy as sa + + +# revision identifiers, used by Alembic. +revision = 'ddcc8bbef391' +down_revision = 'd57ba9ebb251' +branch_labels = None +depends_on = None + + +def upgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('tool_builtin_providers', schema=None) as batch_op: + batch_op.alter_column('provider', + existing_type=sa.VARCHAR(length=40), + type_=sa.String(length=256), + existing_nullable=False) + + # ### end Alembic commands ### + + +def downgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('tool_builtin_providers', schema=None) as batch_op: + batch_op.alter_column('provider', + existing_type=sa.String(length=256), + type_=sa.VARCHAR(length=40), + existing_nullable=False) + + # ### end Alembic commands ### diff --git a/api/models/base.py b/api/models/base.py index fa2b68a5d245bb..da4648efa695a3 100644 --- a/api/models/base.py +++ b/api/models/base.py @@ -1,5 +1,5 @@ -from sqlalchemy.orm import DeclarativeBase +from sqlalchemy.orm import declarative_base +from extensions.ext_database import metadata -class Base(DeclarativeBase): - pass +Base = declarative_base(metadata=metadata) diff --git a/api/models/model.py b/api/models/model.py index 2fad0f54095498..660c7e0a360257 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -2,12 +2,15 @@ import re import uuid from enum import Enum -from typing import Optional +from typing import TYPE_CHECKING, Optional + +if TYPE_CHECKING: + from models.workflow import Workflow from flask import request from flask_login import UserMixin -from sqlalchemy import Float, func, text -from sqlalchemy.orm import Mapped, mapped_column, relationship +from sqlalchemy import Float, Index, PrimaryKeyConstraint, func, text +from sqlalchemy.orm import Mapped, mapped_column from configs import dify_config from core.file.tool_file_parser import ToolFileParser @@ -20,7 +23,7 @@ from .types import StringUUID -class DifySetup(db.Model): +class DifySetup(Base): __tablename__ = "dify_setups" __table_args__ = (db.PrimaryKeyConstraint("version", name="dify_setup_pkey"),) @@ -55,7 +58,7 @@ class IconType(Enum): EMOJI = "emoji" -class App(db.Model): +class App(Base): __tablename__ = "apps" __table_args__ = (db.PrimaryKeyConstraint("id", name="app_pkey"), db.Index("app_tenant_id_idx", "tenant_id")) @@ -133,7 +136,8 @@ def is_agent(self) -> bool: return False if not app_model_config.agent_mode: return False - if self.app_model_config.agent_mode_dict.get("enabled", False) and self.app_model_config.agent_mode_dict.get( + + if app_model_config.agent_mode_dict.get("enabled", False) and app_model_config.agent_mode_dict.get( "strategy", "" ) in {"function_call", "react"}: self.mode = AppMode.AGENT_CHAT.value @@ -250,7 +254,7 @@ def app(self): return app @property - def model_dict(self) -> dict: + def model_dict(self): return json.loads(self.model) if self.model else None @property @@ -284,6 +288,9 @@ def annotation_reply_dict(self) -> dict: ) if annotation_setting: collection_binding_detail = annotation_setting.collection_binding_detail + if not collection_binding_detail: + raise ValueError("Collection binding detail not found") + return { "id": annotation_setting.id, "enabled": True, @@ -314,7 +321,7 @@ def external_data_tools_list(self) -> list[dict]: return json.loads(self.external_data_tools) if self.external_data_tools else [] @property - def user_input_form_list(self) -> dict: + def user_input_form_list(self): return json.loads(self.user_input_form) if self.user_input_form else [] @property @@ -458,7 +465,7 @@ def copy(self): return new_app_model_config -class RecommendedApp(db.Model): +class RecommendedApp(Base): __tablename__ = "recommended_apps" __table_args__ = ( db.PrimaryKeyConstraint("id", name="recommended_app_pkey"), @@ -486,7 +493,7 @@ def app(self): return app -class InstalledApp(db.Model): +class InstalledApp(Base): __tablename__ = "installed_apps" __table_args__ = ( db.PrimaryKeyConstraint("id", name="installed_app_pkey"), @@ -522,7 +529,7 @@ class Conversation(Base): db.Index("conversation_app_from_user_idx", "app_id", "from_source", "from_end_user_id"), ) - id: Mapped[str] = mapped_column(StringUUID, server_default=db.text("uuid_generate_v4()")) + id = db.Column(StringUUID, server_default=db.text("uuid_generate_v4()")) app_id = db.Column(StringUUID, nullable=False) app_model_config_id = db.Column(StringUUID, nullable=True) model_provider = db.Column(db.String(255), nullable=True) @@ -546,10 +553,8 @@ class Conversation(Base): created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) - messages: Mapped[list["Message"]] = relationship( - "Message", backref="conversation", lazy="select", passive_deletes="all" - ) - message_annotations: Mapped[list["MessageAnnotation"]] = relationship( + messages = db.relationship("Message", backref="conversation", lazy="select", passive_deletes="all") + message_annotations = db.relationship( "MessageAnnotation", backref="conversation", lazy="select", passive_deletes="all" ) @@ -578,7 +583,7 @@ def model_config(self): ) if not app_model_config: - raise ValueError("app config not found") + return {} model_config = app_model_config.to_dict() @@ -692,12 +697,12 @@ def in_debug_mode(self): class Message(Base): __tablename__ = "messages" __table_args__ = ( - db.PrimaryKeyConstraint("id", name="message_pkey"), - db.Index("message_app_id_idx", "app_id", "created_at"), - db.Index("message_conversation_id_idx", "conversation_id"), - db.Index("message_end_user_idx", "app_id", "from_source", "from_end_user_id"), - db.Index("message_account_idx", "app_id", "from_source", "from_account_id"), - db.Index("message_workflow_run_id_idx", "conversation_id", "workflow_run_id"), + PrimaryKeyConstraint("id", name="message_pkey"), + Index("message_app_id_idx", "app_id", "created_at"), + Index("message_conversation_id_idx", "conversation_id"), + Index("message_end_user_idx", "app_id", "from_source", "from_end_user_id"), + Index("message_account_idx", "app_id", "from_source", "from_account_id"), + Index("message_workflow_run_id_idx", "conversation_id", "workflow_run_id"), ) id = db.Column(StringUUID, server_default=db.text("uuid_generate_v4()")) @@ -705,10 +710,10 @@ class Message(Base): model_provider = db.Column(db.String(255), nullable=True) model_id = db.Column(db.String(255), nullable=True) override_model_configs = db.Column(db.Text) - conversation_id: Mapped[str] = mapped_column(StringUUID, db.ForeignKey("conversations.id"), nullable=False) - inputs: Mapped[str] = mapped_column(db.JSON) - query: Mapped[str] = mapped_column(db.Text, nullable=False) - message: Mapped[str] = mapped_column(db.JSON, nullable=False) + conversation_id = db.Column(StringUUID, db.ForeignKey("conversations.id"), nullable=False) + inputs = db.Column(db.JSON) + query = db.Column(db.Text, nullable=False) + message = db.Column(db.JSON, nullable=False) message_tokens = db.Column(db.Integer, nullable=False, server_default=db.text("0")) message_unit_price = db.Column(db.Numeric(10, 4), nullable=False) message_price_unit = db.Column(db.Numeric(10, 7), nullable=False, server_default=db.text("0.001")) @@ -974,7 +979,7 @@ def from_dict(cls, data: dict): ) -class MessageFeedback(db.Model): +class MessageFeedback(Base): __tablename__ = "message_feedbacks" __table_args__ = ( db.PrimaryKeyConstraint("id", name="message_feedback_pkey"), @@ -1009,15 +1014,15 @@ class MessageFile(Base): db.Index("message_file_created_by_idx", "created_by"), ) - id: Mapped[str] = mapped_column(StringUUID, server_default=db.text("uuid_generate_v4()")) - message_id: Mapped[str] = mapped_column(StringUUID, nullable=False) - type: Mapped[str] = mapped_column(db.String(255), nullable=False) - transfer_method: Mapped[str] = mapped_column(db.String(255), nullable=False) - url: Mapped[str] = mapped_column(db.Text, nullable=True) - belongs_to: Mapped[str] = mapped_column(db.String(255), nullable=True) - upload_file_id: Mapped[str] = mapped_column(StringUUID, nullable=True) - created_by_role: Mapped[str] = mapped_column(db.String(255), nullable=False) - created_by: Mapped[str] = mapped_column(StringUUID, nullable=False) + id = db.Column(StringUUID, server_default=db.text("uuid_generate_v4()")) + message_id = db.Column(StringUUID, nullable=False) + type = db.Column(db.String(255), nullable=False) + transfer_method = db.Column(db.String(255), nullable=False) + url = db.Column(db.Text, nullable=True) + belongs_to = db.Column(db.String(255), nullable=True) + upload_file_id = db.Column(StringUUID, nullable=True) + created_by_role = db.Column(db.String(255), nullable=False) + created_by = db.Column(StringUUID, nullable=False) created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) @@ -1032,7 +1037,7 @@ class MessageAnnotation(Base): id = db.Column(StringUUID, server_default=db.text("uuid_generate_v4()")) app_id = db.Column(StringUUID, nullable=False) - conversation_id: Mapped[str] = mapped_column(StringUUID, db.ForeignKey("conversations.id"), nullable=True) + conversation_id = db.Column(StringUUID, db.ForeignKey("conversations.id"), nullable=True) message_id = db.Column(StringUUID, nullable=True) question = db.Column(db.Text, nullable=True) content = db.Column(db.Text, nullable=False) @@ -1052,7 +1057,7 @@ def annotation_create_account(self): return account -class AppAnnotationHitHistory(db.Model): +class AppAnnotationHitHistory(Base): __tablename__ = "app_annotation_hit_histories" __table_args__ = ( db.PrimaryKeyConstraint("id", name="app_annotation_hit_histories_pkey"), @@ -1090,7 +1095,7 @@ def annotation_create_account(self): return account -class AppAnnotationSetting(db.Model): +class AppAnnotationSetting(Base): __tablename__ = "app_annotation_settings" __table_args__ = ( db.PrimaryKeyConstraint("id", name="app_annotation_settings_pkey"), @@ -1138,7 +1143,7 @@ def collection_binding_detail(self): return collection_binding_detail -class OperationLog(db.Model): +class OperationLog(Base): __tablename__ = "operation_logs" __table_args__ = ( db.PrimaryKeyConstraint("id", name="operation_log_pkey"), @@ -1155,7 +1160,7 @@ class OperationLog(db.Model): updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class EndUser(UserMixin, db.Model): +class EndUser(UserMixin, Base): __tablename__ = "end_users" __table_args__ = ( db.PrimaryKeyConstraint("id", name="end_user_pkey"), @@ -1175,7 +1180,7 @@ class EndUser(UserMixin, db.Model): updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class Site(db.Model): +class Site(Base): __tablename__ = "sites" __table_args__ = ( db.PrimaryKeyConstraint("id", name="site_pkey"), @@ -1222,7 +1227,7 @@ def app_base_url(self): return dify_config.APP_WEB_URL or request.url_root.rstrip("/") -class ApiToken(db.Model): +class ApiToken(Base): __tablename__ = "api_tokens" __table_args__ = ( db.PrimaryKeyConstraint("id", name="api_token_pkey"), @@ -1249,7 +1254,7 @@ def generate_api_key(prefix, n): return result -class UploadFile(db.Model): +class UploadFile(Base): __tablename__ = "upload_files" __table_args__ = ( db.PrimaryKeyConstraint("id", name="upload_file_pkey"), @@ -1273,7 +1278,7 @@ class UploadFile(db.Model): hash = db.Column(db.String(255), nullable=True) -class ApiRequest(db.Model): +class ApiRequest(Base): __tablename__ = "api_requests" __table_args__ = ( db.PrimaryKeyConstraint("id", name="api_request_pkey"), @@ -1290,7 +1295,7 @@ class ApiRequest(db.Model): created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class MessageChain(db.Model): +class MessageChain(Base): __tablename__ = "message_chains" __table_args__ = ( db.PrimaryKeyConstraint("id", name="message_chain_pkey"), @@ -1395,7 +1400,7 @@ def tool_inputs_dict(self) -> dict: return {} @property - def tool_outputs_dict(self) -> dict: + def tool_outputs_dict(self): tools = self.tools try: if self.observation: @@ -1417,7 +1422,7 @@ def tool_outputs_dict(self) -> dict: return dict.fromkeys(tools, self.observation) -class DatasetRetrieverResource(db.Model): +class DatasetRetrieverResource(Base): __tablename__ = "dataset_retriever_resources" __table_args__ = ( db.PrimaryKeyConstraint("id", name="dataset_retriever_resource_pkey"), @@ -1444,7 +1449,7 @@ class DatasetRetrieverResource(db.Model): created_at = db.Column(db.DateTime, nullable=False, server_default=db.func.current_timestamp()) -class Tag(db.Model): +class Tag(Base): __tablename__ = "tags" __table_args__ = ( db.PrimaryKeyConstraint("id", name="tag_pkey"), @@ -1462,7 +1467,7 @@ class Tag(db.Model): created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class TagBinding(db.Model): +class TagBinding(Base): __tablename__ = "tag_bindings" __table_args__ = ( db.PrimaryKeyConstraint("id", name="tag_binding_pkey"), @@ -1478,7 +1483,7 @@ class TagBinding(db.Model): created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class TraceAppConfig(db.Model): +class TraceAppConfig(Base): __tablename__ = "trace_app_config" __table_args__ = ( db.PrimaryKeyConstraint("id", name="tracing_app_config_pkey"), diff --git a/api/models/provider.py b/api/models/provider.py index 644915e781084b..d3c6db9babb073 100644 --- a/api/models/provider.py +++ b/api/models/provider.py @@ -1,6 +1,7 @@ from enum import Enum from extensions.ext_database import db +from models.base import Base from .types import StringUUID @@ -35,7 +36,7 @@ def value_of(value): raise ValueError(f"No matching enum found for value '{value}'") -class Provider(db.Model): +class Provider(Base): """ Provider model representing the API providers and their configurations. """ @@ -88,7 +89,7 @@ def is_enabled(self): return self.is_valid and self.token_is_set -class ProviderModel(db.Model): +class ProviderModel(Base): """ Provider model representing the API provider_models and their configurations. """ @@ -113,7 +114,7 @@ class ProviderModel(db.Model): updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class TenantDefaultModel(db.Model): +class TenantDefaultModel(Base): __tablename__ = "tenant_default_models" __table_args__ = ( db.PrimaryKeyConstraint("id", name="tenant_default_model_pkey"), @@ -129,7 +130,7 @@ class TenantDefaultModel(db.Model): updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class TenantPreferredModelProvider(db.Model): +class TenantPreferredModelProvider(Base): __tablename__ = "tenant_preferred_model_providers" __table_args__ = ( db.PrimaryKeyConstraint("id", name="tenant_preferred_model_provider_pkey"), @@ -144,7 +145,7 @@ class TenantPreferredModelProvider(db.Model): updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class ProviderOrder(db.Model): +class ProviderOrder(Base): __tablename__ = "provider_orders" __table_args__ = ( db.PrimaryKeyConstraint("id", name="provider_order_pkey"), @@ -169,7 +170,7 @@ class ProviderOrder(db.Model): updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class ProviderModelSetting(db.Model): +class ProviderModelSetting(Base): """ Provider model settings for record the model enabled status and load balancing status. """ @@ -191,7 +192,7 @@ class ProviderModelSetting(db.Model): updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class LoadBalancingModelConfig(db.Model): +class LoadBalancingModelConfig(Base): """ Configurations for load balancing models. """ diff --git a/api/models/source.py b/api/models/source.py index 07695f06e6cf00..efd94227d0593a 100644 --- a/api/models/source.py +++ b/api/models/source.py @@ -3,11 +3,12 @@ from sqlalchemy.dialects.postgresql import JSONB from extensions.ext_database import db +from models.base import Base from .types import StringUUID -class DataSourceOauthBinding(db.Model): +class DataSourceOauthBinding(Base): __tablename__ = "data_source_oauth_bindings" __table_args__ = ( db.PrimaryKeyConstraint("id", name="source_binding_pkey"), @@ -25,7 +26,7 @@ class DataSourceOauthBinding(db.Model): disabled = db.Column(db.Boolean, nullable=True, server_default=db.text("false")) -class DataSourceApiKeyAuthBinding(db.Model): +class DataSourceApiKeyAuthBinding(Base): __tablename__ = "data_source_api_key_auth_bindings" __table_args__ = ( db.PrimaryKeyConstraint("id", name="data_source_api_key_auth_binding_pkey"), diff --git a/api/models/task.py b/api/models/task.py index 57b147c78db110..6fab2a72c26712 100644 --- a/api/models/task.py +++ b/api/models/task.py @@ -3,9 +3,10 @@ from celery import states from extensions.ext_database import db +from models.base import Base -class CeleryTask(db.Model): +class CeleryTask(Base): """Task result/status.""" __tablename__ = "celery_taskmeta" @@ -29,7 +30,7 @@ class CeleryTask(db.Model): queue = db.Column(db.String(155), nullable=True) -class CeleryTaskSet(db.Model): +class CeleryTaskSet(Base): """TaskSet result.""" __tablename__ = "celery_tasksetmeta" diff --git a/api/models/tool.py b/api/models/tool.py index a81bb65174a724..d70c90585193c7 100644 --- a/api/models/tool.py +++ b/api/models/tool.py @@ -2,6 +2,7 @@ from enum import Enum from extensions.ext_database import db +from models.base import Base from .types import StringUUID @@ -17,7 +18,7 @@ def value_of(value): raise ValueError(f"No matching enum found for value '{value}'") -class ToolProvider(db.Model): +class ToolProvider(Base): __tablename__ = "tool_providers" __table_args__ = ( db.PrimaryKeyConstraint("id", name="tool_provider_pkey"), diff --git a/api/models/tools.py b/api/models/tools.py index 485e16b2280def..1e99749b243e6f 100644 --- a/api/models/tools.py +++ b/api/models/tools.py @@ -1,8 +1,11 @@ import json from datetime import datetime +from deprecated import deprecated +from sqlalchemy import ForeignKey from sqlalchemy.orm import Mapped, mapped_column +from core.tools.entities.common_entities import I18nObject from core.tools.entities.tool_bundle import ApiToolBundle from core.tools.entities.tool_entities import ApiProviderSchemaType, WorkflowToolParameterConfiguration from extensions.ext_database import db @@ -31,7 +34,7 @@ class BuiltinToolProvider(Base): # who created this tool provider user_id: Mapped[str] = mapped_column(StringUUID, nullable=False) # name of the tool provider - provider: Mapped[str] = mapped_column(db.String(40), nullable=False) + provider: Mapped[str] = mapped_column(db.String(256), nullable=False) # credential of the tool provider encrypted_credentials: Mapped[str] = mapped_column(db.Text, nullable=True) created_at: Mapped[datetime] = mapped_column( @@ -182,7 +185,7 @@ def app(self) -> App | None: return db.session.query(App).filter(App.id == self.app_id).first() -class ToolModelInvoke(db.Model): +class ToolModelInvoke(Base): """ store the invoke logs from tool invoke """ @@ -219,7 +222,7 @@ class ToolModelInvoke(db.Model): updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) -class ToolConversationVariables(db.Model): +class ToolConversationVariables(Base): """ store the conversation variables from tool invoke """ @@ -275,3 +278,46 @@ class ToolFile(Base): mimetype: Mapped[str] = mapped_column(db.String(255), nullable=False) # original url original_url: Mapped[str] = mapped_column(db.String(2048), nullable=True) + + +@deprecated +class DeprecatedPublishedAppTool(Base): + """ + The table stores the apps published as a tool for each person. + """ + + __tablename__ = "tool_published_apps" + __table_args__ = ( + db.PrimaryKeyConstraint("id", name="published_app_tool_pkey"), + db.UniqueConstraint("app_id", "user_id", name="unique_published_app_tool"), + ) + + # id of the tool provider + id = db.Column(StringUUID, server_default=db.text("uuid_generate_v4()")) + # id of the app + app_id = db.Column(StringUUID, ForeignKey("apps.id"), nullable=False) + # who published this tool + user_id = db.Column(StringUUID, nullable=False) + # description of the tool, stored in i18n format, for human + description = db.Column(db.Text, nullable=False) + # llm_description of the tool, for LLM + llm_description = db.Column(db.Text, nullable=False) + # query description, query will be seem as a parameter of the tool, + # to describe this parameter to llm, we need this field + query_description = db.Column(db.Text, nullable=False) + # query name, the name of the query parameter + query_name = db.Column(db.String(40), nullable=False) + # name of the tool provider + tool_name = db.Column(db.String(40), nullable=False) + # author + author = db.Column(db.String(40), nullable=False) + created_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) + updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) + + @property + def description_i18n(self) -> I18nObject: + return I18nObject(**json.loads(self.description)) + + @property + def app(self) -> App: + return db.session.query(App).filter(App.id == self.app_id).first() diff --git a/api/models/web.py b/api/models/web.py index bc088c185d5a8b..934008a4434a6f 100644 --- a/api/models/web.py +++ b/api/models/web.py @@ -1,10 +1,11 @@ from extensions.ext_database import db +from models.base import Base from .model import Message from .types import StringUUID -class SavedMessage(db.Model): +class SavedMessage(Base): __tablename__ = "saved_messages" __table_args__ = ( db.PrimaryKeyConstraint("id", name="saved_message_pkey"), @@ -23,7 +24,7 @@ def message(self): return db.session.query(Message).filter(Message.id == self.message_id).first() -class PinnedConversation(db.Model): +class PinnedConversation(Base): __tablename__ = "pinned_conversations" __table_args__ = ( db.PrimaryKeyConstraint("id", name="pinned_conversation_pkey"), diff --git a/api/models/workflow.py b/api/models/workflow.py index 9c93ea4cea84e7..0b7d255954e10a 100644 --- a/api/models/workflow.py +++ b/api/models/workflow.py @@ -2,10 +2,13 @@ from collections.abc import Mapping, Sequence from datetime import datetime from enum import Enum -from typing import Any, Optional, Union +from typing import TYPE_CHECKING, Any, Union -from sqlalchemy import func -from sqlalchemy.orm import Mapped +if TYPE_CHECKING: + from models.model import AppMode + +from sqlalchemy import Index, PrimaryKeyConstraint, func +from sqlalchemy.orm import Mapped, mapped_column import contexts from constants import HIDDEN_VALUE @@ -13,6 +16,7 @@ from core.helper import encrypter from extensions.ext_database import db from libs import helper +from models.base import Base from .account import Account from .types import StringUUID @@ -75,7 +79,7 @@ def from_app_mode(cls, app_mode: Union[str, "AppMode"]) -> "WorkflowType": return cls.WORKFLOW if app_mode == AppMode.WORKFLOW else cls.CHAT -class Workflow(db.Model): +class Workflow(Base): """ Workflow, for `Workflow App` and `Chat App workflow mode`. @@ -345,7 +349,7 @@ def value_of(cls, value: str) -> "WorkflowRunStatus": raise ValueError(f"invalid workflow run status value {value}") -class WorkflowRun(db.Model): +class WorkflowRun(Base): """ Workflow Run @@ -436,7 +440,7 @@ def outputs_dict(self): return json.loads(self.outputs) if self.outputs else None @property - def message(self) -> Optional["Message"]: + def message(self): from models.model import Message return ( @@ -542,7 +546,7 @@ def value_of(cls, value: str) -> "WorkflowNodeExecutionStatus": raise ValueError(f"invalid workflow node execution status value {value}") -class WorkflowNodeExecution(db.Model): +class WorkflowNodeExecution(Base): """ Workflow Node Execution @@ -708,7 +712,7 @@ def value_of(cls, value: str) -> "WorkflowAppLogCreatedFrom": raise ValueError(f"invalid workflow app log created from value {value}") -class WorkflowAppLog(db.Model): +class WorkflowAppLog(Base): """ Workflow App execution log, excluding workflow debugging records. @@ -770,15 +774,20 @@ def created_by_end_user(self): return db.session.get(EndUser, self.created_by) if created_by_role == CreatedByRole.END_USER else None -class ConversationVariable(db.Model): +class ConversationVariable(Base): __tablename__ = "workflow_conversation_variables" + __table_args__ = ( + PrimaryKeyConstraint("id", "conversation_id", name="workflow_conversation_variables_pkey"), + Index("workflow__conversation_variables_app_id_idx", "app_id"), + Index("workflow__conversation_variables_created_at_idx", "created_at"), + ) - id: Mapped[str] = db.Column(StringUUID, primary_key=True) - conversation_id: Mapped[str] = db.Column(StringUUID, nullable=False, primary_key=True) - app_id: Mapped[str] = db.Column(StringUUID, nullable=False, index=True) - data = db.Column(db.Text, nullable=False) - created_at = db.Column(db.DateTime, nullable=False, index=True, server_default=db.text("CURRENT_TIMESTAMP(0)")) - updated_at = db.Column( + id: Mapped[str] = mapped_column(StringUUID, primary_key=True) + conversation_id: Mapped[str] = mapped_column(StringUUID, nullable=False, primary_key=True) + app_id: Mapped[str] = mapped_column(StringUUID, nullable=False) + data = mapped_column(db.Text, nullable=False) + created_at = mapped_column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)")) + updated_at = mapped_column( db.DateTime, nullable=False, server_default=func.current_timestamp(), onupdate=func.current_timestamp() ) From 957ab093c909ec15b46c32665617b9a9660faea2 Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Sun, 29 Sep 2024 17:07:40 +0800 Subject: [PATCH 067/325] enhancement: reduce requests to plugin daemon --- api/core/tools/tool_manager.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index fdd7e8385b3971..2f747a317e0e43 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -123,12 +123,13 @@ def get_tool_runtime( :return: the tool """ if provider_type == ToolProviderType.BUILT_IN: - builtin_tool = cls.get_builtin_tool(provider_id, tool_name, tenant_id) - if not builtin_tool: - raise ValueError(f"tool {tool_name} not found") - # check if the builtin tool need credentials provider_controller = cls.get_builtin_provider(provider_id, tenant_id) + + builtin_tool = provider_controller.get_tool(tool_name) + if not builtin_tool: + raise ToolProviderNotFoundError(f"builtin tool {tool_name} not found") + if not provider_controller.need_credentials: return cast( BuiltinTool, From 823637349819d5603fd3a90eb2229411b4769e3d Mon Sep 17 00:00:00 2001 From: takatost Date: Sun, 29 Sep 2024 18:15:18 +0800 Subject: [PATCH 068/325] feat: remove unused codes --- api/Dockerfile | 4 + .../console/datasets/datasets_document.py | 15 +- .../model_runtime/entities/model_entities.py | 5 - .../model_providers/__base/ai_model.py | 222 +- .../model_providers/__base/audio.mp3 | Bin 218880 -> 0 bytes .../model_providers/__base/model_provider.py | 120 - .../__base/moderation_model.py | 26 +- .../model_providers/__base/rerank_model.py | 44 +- .../__base/speech2text_model.py | 41 +- .../model_providers/__base/text2img_model.py | 54 - .../__base/text_embedding_model.py | 38 +- .../__base/tokenizers/gpt2_tokenzier.py | 33 +- .../model_providers/__base/tts_model.py | 124 +- .../text_embedding/text_embedding.py | 191 -- .../baichuan/text_embedding/text_embedding.py | 207 -- .../cohere/text_embedding/text_embedding.py | 223 -- .../model_providers/fireworks/fireworks.yaml | 30 - 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100644 api/tests/integration_tests/model_runtime/zhipuai/test_provider.py delete mode 100644 api/tests/integration_tests/model_runtime/zhipuai/test_text_embedding.py delete mode 100644 api/tests/unit_tests/core/model_runtime/model_providers/__init__.py delete mode 100644 api/tests/unit_tests/core/model_runtime/model_providers/wenxin/__init__.py delete mode 100644 api/tests/unit_tests/core/model_runtime/model_providers/wenxin/test_text_embedding.py diff --git a/api/Dockerfile b/api/Dockerfile index 6483f8281b7fa6..d32f70321d5c6d 100644 --- a/api/Dockerfile +++ b/api/Dockerfile @@ -67,6 +67,10 @@ ENV PATH="${VIRTUAL_ENV}/bin:${PATH}" # Download nltk data RUN python -c "import nltk; nltk.download('punkt'); nltk.download('averaged_perceptron_tagger')" +ENV TIKTOKEN_CACHE_DIR=/app/api/.tiktoken_cache + +RUN python -c "import tiktoken; tiktoken.encoding_for_model('gpt2')" + # Copy source code COPY . /app/api/ diff --git a/api/controllers/console/datasets/datasets_document.py b/api/controllers/console/datasets/datasets_document.py index 829ef11e521d8e..ca6c5717271268 100644 --- a/api/controllers/console/datasets/datasets_document.py +++ b/api/controllers/console/datasets/datasets_document.py @@ -6,7 +6,6 @@ from flask_login import current_user from flask_restful import Resource, fields, marshal, marshal_with, reqparse from sqlalchemy import asc, desc -from transformers.hf_argparser import string_to_bool from werkzeug.exceptions import Forbidden, NotFound import services @@ -145,7 +144,19 @@ def get(self, dataset_id): sort = request.args.get("sort", default="-created_at", type=str) # "yes", "true", "t", "y", "1" convert to True, while others convert to False. try: - fetch = string_to_bool(request.args.get("fetch", default="false")) + fetch_val = request.args.get("fetch", default="false") + if isinstance(fetch_val, bool): + fetch = fetch_val + else: + if fetch_val.lower() in ("yes", "true", "t", "y", "1"): + fetch = True + elif fetch_val.lower() in ("no", "false", "f", "n", "0"): + fetch = False + else: + raise ArgumentTypeError( + f"Truthy value expected: got {fetch_val} but expected one of yes/no, true/false, t/f, y/n, 1/0 " + f"(case insensitive)." + ) except (ArgumentTypeError, ValueError, Exception) as e: fetch = False dataset = DatasetService.get_dataset(dataset_id) diff --git a/api/core/model_runtime/entities/model_entities.py b/api/core/model_runtime/entities/model_entities.py index 52ea787c3ad572..09b9e3aa0d44d2 100644 --- a/api/core/model_runtime/entities/model_entities.py +++ b/api/core/model_runtime/entities/model_entities.py @@ -18,7 +18,6 @@ class ModelType(Enum): SPEECH2TEXT = "speech2text" MODERATION = "moderation" TTS = "tts" - TEXT2IMG = "text2img" @classmethod def value_of(cls, origin_model_type: str) -> "ModelType": @@ -37,8 +36,6 @@ def value_of(cls, origin_model_type: str) -> "ModelType": return cls.SPEECH2TEXT elif origin_model_type in {"tts", cls.TTS.value}: return cls.TTS - elif origin_model_type in {"text2img", cls.TEXT2IMG.value}: - return cls.TEXT2IMG elif origin_model_type == cls.MODERATION.value: return cls.MODERATION else: @@ -62,8 +59,6 @@ def to_origin_model_type(self) -> str: return "tts" elif self == self.MODERATION: return "moderation" - elif self == self.TEXT2IMG: - return "text2img" else: raise ValueError(f"invalid model type {self}") diff --git a/api/core/model_runtime/model_providers/__base/ai_model.py b/api/core/model_runtime/model_providers/__base/ai_model.py index 6b04ba2efd9ca3..a28d69ce8084e6 100644 --- a/api/core/model_runtime/model_providers/__base/ai_model.py +++ b/api/core/model_runtime/model_providers/__base/ai_model.py @@ -1,26 +1,18 @@ import decimal -import os -from collections.abc import Mapping from typing import Optional from pydantic import ConfigDict, Field -from core.helper.position_helper import get_position_map, sort_by_position_map -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.defaults import PARAMETER_RULE_TEMPLATE from core.model_runtime.entities.model_entities import ( AIModelEntity, - DefaultParameterName, - FetchFrom, ModelType, PriceConfig, PriceInfo, PriceType, ) from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError -from core.model_runtime.model_providers.__base.tokenizers.gpt2_tokenzier import GPT2Tokenizer from core.plugin.entities.plugin_daemon import PluginModelProviderEntity -from core.tools.utils.yaml_utils import load_yaml_file +from core.plugin.manager.model import PluginModelManager class AIModel: @@ -117,93 +109,7 @@ def get_price(self, model: str, credentials: dict, price_type: PriceType, tokens currency=price_config.currency, ) - def predefined_models(self) -> list[AIModelEntity]: - """ - Get all predefined models for given provider. - - :return: - """ - if self.model_schemas: - return self.model_schemas - - model_schemas = [] - - # get module name - model_type = self.__class__.__module__.split(".")[-1] - - # get provider name - provider_name = self.__class__.__module__.split(".")[-3] - - # get the path of current classes - current_path = os.path.abspath(__file__) - # get parent path of the current path - provider_model_type_path = os.path.join( - os.path.dirname(os.path.dirname(current_path)), provider_name, model_type - ) - - # get all yaml files path under provider_model_type_path that do not start with __ - model_schema_yaml_paths = [ - os.path.join(provider_model_type_path, model_schema_yaml) - for model_schema_yaml in os.listdir(provider_model_type_path) - if not model_schema_yaml.startswith("__") - and not model_schema_yaml.startswith("_") - and os.path.isfile(os.path.join(provider_model_type_path, model_schema_yaml)) - and model_schema_yaml.endswith(".yaml") - ] - - # get _position.yaml file path - position_map = get_position_map(provider_model_type_path) - - # traverse all model_schema_yaml_paths - for model_schema_yaml_path in model_schema_yaml_paths: - # read yaml data from yaml file - yaml_data = load_yaml_file(model_schema_yaml_path) - - new_parameter_rules = [] - for parameter_rule in yaml_data.get("parameter_rules", []): - if "use_template" in parameter_rule: - try: - default_parameter_name = DefaultParameterName.value_of(parameter_rule["use_template"]) - default_parameter_rule = self._get_default_parameter_rule_variable_map(default_parameter_name) - copy_default_parameter_rule = default_parameter_rule.copy() - copy_default_parameter_rule.update(parameter_rule) - parameter_rule = copy_default_parameter_rule - except ValueError: - pass - - if "label" not in parameter_rule: - parameter_rule["label"] = {"zh_Hans": parameter_rule["name"], "en_US": parameter_rule["name"]} - - new_parameter_rules.append(parameter_rule) - - yaml_data["parameter_rules"] = new_parameter_rules - - if "label" not in yaml_data: - yaml_data["label"] = {"zh_Hans": yaml_data["model"], "en_US": yaml_data["model"]} - - yaml_data["fetch_from"] = FetchFrom.PREDEFINED_MODEL.value - - try: - # yaml_data to entity - model_schema = AIModelEntity(**yaml_data) - except Exception as e: - model_schema_yaml_file_name = os.path.basename(model_schema_yaml_path).rstrip(".yaml") - raise Exception( - f"Invalid model schema for {provider_name}.{model_type}.{model_schema_yaml_file_name}: {str(e)}" - ) - - # cache model schema - model_schemas.append(model_schema) - - # resort model schemas by position - model_schemas = sort_by_position_map(position_map, model_schemas, lambda x: x.model) - - # cache model schemas - self.model_schemas = model_schemas - - return model_schemas - - def get_model_schema(self, model: str, credentials: Optional[Mapping] = None) -> Optional[AIModelEntity]: + def get_model_schema(self, model: str, credentials: Optional[dict] = None) -> Optional[AIModelEntity]: """ Get model schema by model name and credentials @@ -211,117 +117,13 @@ def get_model_schema(self, model: str, credentials: Optional[Mapping] = None) -> :param credentials: model credentials :return: model schema """ - # get predefined models (predefined_models) - models = self.predefined_models() - - model_map = {model.model: model for model in models} - if model in model_map: - return model_map[model] - - if credentials: - model_schema = self.get_customizable_model_schema_from_credentials(model, credentials) - if model_schema: - return model_schema - - return None - - def get_customizable_model_schema_from_credentials( - self, model: str, credentials: Mapping - ) -> Optional[AIModelEntity]: - """ - Get customizable model schema from credentials - - :param model: model name - :param credentials: model credentials - :return: model schema - """ - return self._get_customizable_model_schema(model, credentials) - - def _get_customizable_model_schema(self, model: str, credentials: Mapping) -> Optional[AIModelEntity]: - """ - Get customizable model schema and fill in the template - """ - schema = self.get_customizable_model_schema(model, credentials) - - if not schema: - return None - - # fill in the template - new_parameter_rules = [] - for parameter_rule in schema.parameter_rules: - if parameter_rule.use_template: - try: - default_parameter_name = DefaultParameterName.value_of(parameter_rule.use_template) - default_parameter_rule = self._get_default_parameter_rule_variable_map(default_parameter_name) - if not parameter_rule.max and "max" in default_parameter_rule: - parameter_rule.max = default_parameter_rule["max"] - if not parameter_rule.min and "min" in default_parameter_rule: - parameter_rule.min = default_parameter_rule["min"] - if not parameter_rule.default and "default" in default_parameter_rule: - parameter_rule.default = default_parameter_rule["default"] - if not parameter_rule.precision and "precision" in default_parameter_rule: - parameter_rule.precision = default_parameter_rule["precision"] - if not parameter_rule.required and "required" in default_parameter_rule: - parameter_rule.required = default_parameter_rule["required"] - if not parameter_rule.help and "help" in default_parameter_rule: - parameter_rule.help = I18nObject( - en_US=default_parameter_rule["help"]["en_US"], - ) - if ( - parameter_rule.help - and not parameter_rule.help.en_US - and ("help" in default_parameter_rule and "en_US" in default_parameter_rule["help"]) - ): - parameter_rule.help.en_US = default_parameter_rule["help"]["en_US"] - if ( - parameter_rule.help - and not parameter_rule.help.zh_Hans - and ("help" in default_parameter_rule and "zh_Hans" in default_parameter_rule["help"]) - ): - parameter_rule.help.zh_Hans = default_parameter_rule["help"].get( - "zh_Hans", default_parameter_rule["help"]["en_US"] - ) - except ValueError: - pass - - new_parameter_rules.append(parameter_rule) - - schema.parameter_rules = new_parameter_rules - - return schema - - def get_customizable_model_schema(self, model: str, credentials: Mapping) -> Optional[AIModelEntity]: - """ - Get customizable model schema - - :param model: model name - :param credentials: model credentials - :return: model schema - """ - return None - - def _get_default_parameter_rule_variable_map(self, name: DefaultParameterName) -> dict: - """ - Get default parameter rule for given name - - :param name: parameter name - :return: parameter rule - """ - default_parameter_rule = PARAMETER_RULE_TEMPLATE.get(name) - - if not default_parameter_rule: - raise Exception(f"Invalid model parameter rule name {name}") - - return default_parameter_rule - - def _get_num_tokens_by_gpt2(self, text: str) -> int: - """ - Get number of tokens for given prompt messages by gpt2 - Some provider models do not provide an interface for obtaining the number of tokens. - Here, the gpt2 tokenizer is used to calculate the number of tokens. - This method can be executed offline, and the gpt2 tokenizer has been cached in the project. - - :param text: plain text of prompt. You need to convert the original message to plain text - :return: number of tokens - """ - return GPT2Tokenizer.get_num_tokens(text) + plugin_model_manager = PluginModelManager() + return plugin_model_manager.get_model_schema( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model_type=self.model_type.value, + model=model, + credentials=credentials or {}, + ) diff --git a/api/core/model_runtime/model_providers/__base/audio.mp3 b/api/core/model_runtime/model_providers/__base/audio.mp3 deleted file mode 100644 index 7c86e02e160909223668c7b21a60b68afc74ef98..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 218880 zcmcG0cU%)$`|qR>0t85?2}MIdYQTghO-T?C6%_@#E?|uKe_w%`b+?x!iKJ%Q(e9v>vGv|B}LC1Iq0`6m9MKwl zQOLqq<%dJL>PQ|d8Lmeek1oD$l{)`(=EI!niFJ=puYcHLhj3{$8WrtKb_;(&JYUIZfDf`YPj9t!!tV+X^-In;Qw`dl@%@0fArnB(okKn+wjEjDj ztawKL&zVY^EbBl{V7?=pyFUHZPb})0FdW9ERrL}%K$<^&i;sgHl|tF^fBIMhiMsJ$ 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os -from abc import ABC, abstractmethod -from typing import Optional - -from core.helper.module_import_helper import get_subclasses_from_module, import_module_from_source -from core.model_runtime.entities.model_entities import AIModelEntity, ModelType -from core.model_runtime.entities.provider_entities import ProviderEntity -from core.model_runtime.model_providers.__base.ai_model import AIModel -from core.tools.utils.yaml_utils import load_yaml_file - - -class ModelProvider(ABC): - provider_schema: Optional[ProviderEntity] = None - model_instance_map: dict[str, AIModel] = {} - - @abstractmethod - def validate_provider_credentials(self, credentials: dict) -> None: - """ - Validate provider credentials - You can choose any validate_credentials method of model type or implement validate method by yourself, - such as: get model list api - - if validate failed, raise exception - - :param credentials: provider credentials, credentials form defined in `provider_credential_schema`. - """ - raise NotImplementedError - - def get_provider_schema(self) -> ProviderEntity: - """ - Get provider schema - - :return: provider schema - """ - if self.provider_schema: - return self.provider_schema - - # get dirname of the current path - provider_name = self.__class__.__module__.split(".")[-1] - - # get the path of the model_provider classes - base_path = os.path.abspath(__file__) - current_path = os.path.join(os.path.dirname(os.path.dirname(base_path)), provider_name) - - # read provider schema from yaml file - yaml_path = os.path.join(current_path, f"{provider_name}.yaml") - yaml_data = load_yaml_file(yaml_path) - - try: - # yaml_data to entity - provider_schema = ProviderEntity(**yaml_data) - except Exception as e: - raise Exception(f"Invalid provider schema for {provider_name}: {str(e)}") - - # cache schema - self.provider_schema = provider_schema - - return provider_schema - - def models(self, model_type: ModelType) -> list[AIModelEntity]: - """ - Get all models for given model type - - :param model_type: model type defined in `ModelType` - :return: list of models - """ - provider_schema = self.get_provider_schema() - if model_type not in provider_schema.supported_model_types: - return [] - - # get model instance of the model type - model_instance = self.get_model_instance(model_type) - - # get predefined models (predefined_models) - models = model_instance.predefined_models() - - # return models - return models - - def get_model_instance(self, model_type: ModelType) -> AIModel: - """ - Get model instance - - :param model_type: model type defined in `ModelType` - :return: - """ - # get dirname of the current path - provider_name = self.__class__.__module__.split(".")[-1] - - if f"{provider_name}.{model_type.value}" in self.model_instance_map: - return self.model_instance_map[f"{provider_name}.{model_type.value}"] - - # get the path of the model type classes - base_path = os.path.abspath(__file__) - model_type_name = model_type.value.replace("-", "_") - model_type_path = os.path.join(os.path.dirname(os.path.dirname(base_path)), provider_name, model_type_name) - model_type_py_path = os.path.join(model_type_path, f"{model_type_name}.py") - - if not os.path.isdir(model_type_path) or not os.path.exists(model_type_py_path): - raise Exception(f"Invalid model type {model_type} for provider {provider_name}") - - # Dynamic loading {model_type_name}.py file and find the subclass of AIModel - parent_module = ".".join(self.__class__.__module__.split(".")[:-1]) - mod = import_module_from_source( - module_name=f"{parent_module}.{model_type_name}.{model_type_name}", py_file_path=model_type_py_path - ) - model_class = next( - filter( - lambda x: x.__module__ == mod.__name__ and not x.__abstractmethods__, - get_subclasses_from_module(mod, AIModel), - ), - None, - ) - if not model_class: - raise Exception(f"Missing AIModel Class for model type {model_type} in {model_type_py_path}") - - model_instance_map = model_class() - self.model_instance_map[f"{provider_name}.{model_type.value}"] = model_instance_map - - return model_instance_map diff --git a/api/core/model_runtime/model_providers/__base/moderation_model.py b/api/core/model_runtime/model_providers/__base/moderation_model.py index d04414ccb87a63..f98d7572c727d0 100644 --- a/api/core/model_runtime/model_providers/__base/moderation_model.py +++ b/api/core/model_runtime/model_providers/__base/moderation_model.py @@ -1,11 +1,11 @@ import time -from abc import abstractmethod from typing import Optional from pydantic import ConfigDict from core.model_runtime.entities.model_entities import ModelType from core.model_runtime.model_providers.__base.ai_model import AIModel +from core.plugin.manager.model import PluginModelManager class ModerationModel(AIModel): @@ -31,19 +31,15 @@ def invoke(self, model: str, credentials: dict, text: str, user: Optional[str] = self.started_at = time.perf_counter() try: - return self._invoke(model, credentials, text, user) + plugin_model_manager = PluginModelManager() + return plugin_model_manager.invoke_moderation( + tenant_id=self.tenant_id, + user_id=user or "unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model=model, + credentials=credentials, + text=text, + ) except Exception as e: raise self._transform_invoke_error(e) - - @abstractmethod - def _invoke(self, model: str, credentials: dict, text: str, user: Optional[str] = None) -> bool: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param text: text to moderate - :param user: unique user id - :return: false if text is safe, true otherwise - """ - raise NotImplementedError diff --git a/api/core/model_runtime/model_providers/__base/rerank_model.py b/api/core/model_runtime/model_providers/__base/rerank_model.py index 5fb96047425592..e905cb18d46282 100644 --- a/api/core/model_runtime/model_providers/__base/rerank_model.py +++ b/api/core/model_runtime/model_providers/__base/rerank_model.py @@ -1,10 +1,9 @@ -import time -from abc import abstractmethod from typing import Optional from core.model_runtime.entities.model_entities import ModelType from core.model_runtime.entities.rerank_entities import RerankResult from core.model_runtime.model_providers.__base.ai_model import AIModel +from core.plugin.manager.model import PluginModelManager class RerankModel(AIModel): @@ -36,34 +35,19 @@ def invoke( :param user: unique user id :return: rerank result """ - self.started_at = time.perf_counter() - try: - return self._invoke(model, credentials, query, docs, score_threshold, top_n, user) + plugin_model_manager = PluginModelManager() + return plugin_model_manager.invoke_rerank( + tenant_id=self.tenant_id, + user_id=user or "unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model=model, + credentials=credentials, + query=query, + docs=docs, + score_threshold=score_threshold, + top_n=top_n, + ) except Exception as e: raise self._transform_invoke_error(e) - - @abstractmethod - def _invoke( - self, - model: str, - credentials: dict, - query: str, - docs: list[str], - score_threshold: Optional[float] = None, - top_n: Optional[int] = None, - user: Optional[str] = None, - ) -> RerankResult: - """ - Invoke rerank model - - :param model: model name - :param credentials: model credentials - :param query: search query - :param docs: docs for reranking - :param score_threshold: score threshold - :param top_n: top n - :param user: unique user id - :return: rerank result - """ - raise NotImplementedError diff --git a/api/core/model_runtime/model_providers/__base/speech2text_model.py b/api/core/model_runtime/model_providers/__base/speech2text_model.py index b6b0b737436d9c..97ff322f09c2d2 100644 --- a/api/core/model_runtime/model_providers/__base/speech2text_model.py +++ b/api/core/model_runtime/model_providers/__base/speech2text_model.py @@ -1,11 +1,10 @@ -import os -from abc import abstractmethod from typing import IO, Optional from pydantic import ConfigDict from core.model_runtime.entities.model_entities import ModelType from core.model_runtime.model_providers.__base.ai_model import AIModel +from core.plugin.manager.model import PluginModelManager class Speech2TextModel(AIModel): @@ -20,7 +19,7 @@ class Speech2TextModel(AIModel): def invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: """ - Invoke large language model + Invoke speech to text model :param model: model name :param credentials: model credentials @@ -29,31 +28,15 @@ def invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[ :return: text for given audio file """ try: - return self._invoke(model, credentials, file, user) + plugin_model_manager = PluginModelManager() + return plugin_model_manager.invoke_speech_to_text( + tenant_id=self.tenant_id, + user_id=user or "unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model=model, + credentials=credentials, + file=file, + ) except Exception as e: raise self._transform_invoke_error(e) - - @abstractmethod - def _invoke(self, model: str, credentials: dict, file: IO[bytes], user: Optional[str] = None) -> str: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param file: audio file - :param user: unique user id - :return: text for given audio file - """ - raise NotImplementedError - - def _get_demo_file_path(self) -> str: - """ - Get demo file for given model - - :return: demo file - """ - # Get the directory of the current file - current_dir = os.path.dirname(os.path.abspath(__file__)) - - # Construct the path to the audio file - return os.path.join(current_dir, "audio.mp3") diff --git a/api/core/model_runtime/model_providers/__base/text2img_model.py b/api/core/model_runtime/model_providers/__base/text2img_model.py deleted file mode 100644 index a5810e2f0e4b09..00000000000000 --- a/api/core/model_runtime/model_providers/__base/text2img_model.py +++ /dev/null @@ -1,54 +0,0 @@ -from abc import abstractmethod -from typing import IO, Optional - -from pydantic import ConfigDict - -from core.model_runtime.entities.model_entities import ModelType -from core.model_runtime.model_providers.__base.ai_model import AIModel - - -class Text2ImageModel(AIModel): - """ - Model class for text2img model. - """ - - model_type: ModelType = ModelType.TEXT2IMG - - # pydantic configs - model_config = ConfigDict(protected_namespaces=()) - - def invoke( - self, model: str, credentials: dict, prompt: str, model_parameters: dict, user: Optional[str] = None - ) -> list[IO[bytes]]: - """ - Invoke Text2Image model - - :param model: model name - :param credentials: model credentials - :param prompt: prompt for image generation - :param model_parameters: model parameters - :param user: unique user id - - :return: image bytes - """ - try: - return self._invoke(model, credentials, prompt, model_parameters, user) - except Exception as e: - raise self._transform_invoke_error(e) - - @abstractmethod - def _invoke( - self, model: str, credentials: dict, prompt: str, model_parameters: dict, user: Optional[str] = None - ) -> list[IO[bytes]]: - """ - Invoke Text2Image model - - :param model: model name - :param credentials: model credentials - :param prompt: prompt for image generation - :param model_parameters: model parameters - :param user: unique user id - - :return: image bytes - """ - raise NotImplementedError diff --git a/api/core/model_runtime/model_providers/__base/text_embedding_model.py b/api/core/model_runtime/model_providers/__base/text_embedding_model.py index 1a5c40ed516da1..beade743623a6a 100644 --- a/api/core/model_runtime/model_providers/__base/text_embedding_model.py +++ b/api/core/model_runtime/model_providers/__base/text_embedding_model.py @@ -1,5 +1,3 @@ -import time -from abc import abstractmethod from typing import Optional from pydantic import ConfigDict @@ -39,34 +37,21 @@ def invoke( :param input_type: input type :return: embeddings result """ - self.started_at = time.perf_counter() - try: - return self._invoke(model, credentials, texts, user, input_type) + plugin_model_manager = PluginModelManager() + return plugin_model_manager.invoke_text_embedding( + tenant_id=self.tenant_id, + user_id=user or "unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model=model, + credentials=credentials, + texts=texts, + input_type=input_type.value, + ) except Exception as e: raise self._transform_invoke_error(e) - @abstractmethod - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - raise NotImplementedError - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: """ Get number of tokens for given prompt messages @@ -82,7 +67,6 @@ def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int user_id="unknown", plugin_id=self.plugin_id, provider=self.provider_name, - model_type=self.model_type.value, model=model, credentials=credentials, texts=texts, diff --git a/api/core/model_runtime/model_providers/__base/tokenizers/gpt2_tokenzier.py b/api/core/model_runtime/model_providers/__base/tokenizers/gpt2_tokenzier.py index 5fe6dda6ad5d79..609c11d22f1cb7 100644 --- a/api/core/model_runtime/model_providers/__base/tokenizers/gpt2_tokenzier.py +++ b/api/core/model_runtime/model_providers/__base/tokenizers/gpt2_tokenzier.py @@ -1,34 +1,9 @@ -from os.path import abspath, dirname, join -from threading import Lock -from typing import Any - -from transformers import GPT2Tokenizer as TransformerGPT2Tokenizer - -_tokenizer = None -_lock = Lock() +import tiktoken class GPT2Tokenizer: - @staticmethod - def _get_num_tokens_by_gpt2(text: str) -> int: - """ - use gpt2 tokenizer to get num tokens - """ - _tokenizer = GPT2Tokenizer.get_encoder() - tokens = _tokenizer.encode(text, verbose=False) - return len(tokens) - @staticmethod def get_num_tokens(text: str) -> int: - return GPT2Tokenizer._get_num_tokens_by_gpt2(text) - - @staticmethod - def get_encoder() -> Any: - global _tokenizer, _lock - with _lock: - if _tokenizer is None: - base_path = abspath(__file__) - gpt2_tokenizer_path = join(dirname(base_path), "gpt2") - _tokenizer = TransformerGPT2Tokenizer.from_pretrained(gpt2_tokenizer_path) - - return _tokenizer + encoding = tiktoken.encoding_for_model("gpt2") + tiktoken_vec = encoding.encode(text) + return len(tiktoken_vec) diff --git a/api/core/model_runtime/model_providers/__base/tts_model.py b/api/core/model_runtime/model_providers/__base/tts_model.py index 70be9322a75d53..8cefa63ebfb97f 100644 --- a/api/core/model_runtime/model_providers/__base/tts_model.py +++ b/api/core/model_runtime/model_providers/__base/tts_model.py @@ -1,12 +1,11 @@ import logging -import re -from abc import abstractmethod from typing import Optional from pydantic import ConfigDict -from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType +from core.model_runtime.entities.model_entities import ModelType from core.model_runtime.model_providers.__base.ai_model import AIModel +from core.plugin.manager.model import PluginModelManager logger = logging.getLogger(__name__) @@ -37,36 +36,21 @@ def invoke( :return: translated audio file """ try: - return self._invoke( + plugin_model_manager = PluginModelManager() + return plugin_model_manager.invoke_tts( + tenant_id=self.tenant_id, + user_id=user or "unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, model=model, credentials=credentials, - user=user, content_text=content_text, voice=voice, - tenant_id=tenant_id, ) except Exception as e: raise self._transform_invoke_error(e) - @abstractmethod - def _invoke( - self, model: str, tenant_id: str, credentials: dict, content_text: str, voice: str, user: Optional[str] = None - ): - """ - Invoke large language model - - :param model: model name - :param tenant_id: user tenant id - :param credentials: model credentials - :param voice: model timbre - :param content_text: text content to be translated - :param streaming: output is streaming - :param user: unique user id - :return: translated audio file - """ - raise NotImplementedError - - def get_tts_model_voices(self, model: str, credentials: dict, language: Optional[str] = None) -> list: + def get_tts_model_voices(self, model: str, credentials: dict, language: Optional[str] = None) -> list[dict]: """ Get voice for given tts model voices @@ -75,83 +59,13 @@ def get_tts_model_voices(self, model: str, credentials: dict, language: Optional :param credentials: model credentials :return: voices lists """ - model_schema = self.get_model_schema(model, credentials) - - if model_schema and ModelPropertyKey.VOICES in model_schema.model_properties: - voices = model_schema.model_properties[ModelPropertyKey.VOICES] - if language: - return [ - {"name": d["name"], "value": d["mode"]} - for d in voices - if language and language in d.get("language") - ] - else: - return [{"name": d["name"], "value": d["mode"]} for d in voices] - - def _get_model_default_voice(self, model: str, credentials: dict) -> any: - """ - Get voice for given tts model - - :param model: model name - :param credentials: model credentials - :return: voice - """ - model_schema = self.get_model_schema(model, credentials) - - if model_schema and ModelPropertyKey.DEFAULT_VOICE in model_schema.model_properties: - return model_schema.model_properties[ModelPropertyKey.DEFAULT_VOICE] - - def _get_model_audio_type(self, model: str, credentials: dict) -> str: - """ - Get audio type for given tts model - - :param model: model name - :param credentials: model credentials - :return: voice - """ - model_schema = self.get_model_schema(model, credentials) - - if model_schema and ModelPropertyKey.AUDIO_TYPE in model_schema.model_properties: - return model_schema.model_properties[ModelPropertyKey.AUDIO_TYPE] - - def _get_model_word_limit(self, model: str, credentials: dict) -> int: - """ - Get audio type for given tts model - :return: audio type - """ - model_schema = self.get_model_schema(model, credentials) - - if model_schema and ModelPropertyKey.WORD_LIMIT in model_schema.model_properties: - return model_schema.model_properties[ModelPropertyKey.WORD_LIMIT] - - def _get_model_workers_limit(self, model: str, credentials: dict) -> int: - """ - Get audio max workers for given tts model - :return: audio type - """ - model_schema = self.get_model_schema(model, credentials) - - if model_schema and ModelPropertyKey.MAX_WORKERS in model_schema.model_properties: - return model_schema.model_properties[ModelPropertyKey.MAX_WORKERS] - - @staticmethod - def _split_text_into_sentences(org_text, max_length=2000, pattern=r"[。.!?]"): - match = re.compile(pattern) - tx = match.finditer(org_text) - start = 0 - result = [] - one_sentence = "" - for i in tx: - end = i.regs[0][1] - tmp = org_text[start:end] - if len(one_sentence + tmp) > max_length: - result.append(one_sentence) - one_sentence = "" - one_sentence += tmp - start = end - last_sens = org_text[start:] - if last_sens: - one_sentence += last_sens - if one_sentence != "": - result.append(one_sentence) - return result + plugin_model_manager = PluginModelManager() + return plugin_model_manager.get_tts_model_voices( + tenant_id=self.tenant_id, + user_id="unknown", + plugin_id=self.plugin_id, + provider=self.provider_name, + model=model, + credentials=credentials, + language=language, + ) diff --git a/api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py deleted file mode 100644 index 8701a3805002eb..00000000000000 --- a/api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py +++ /dev/null @@ -1,191 +0,0 @@ -import base64 -import copy -import time -from typing import Optional, Union - -import numpy as np -import tiktoken -from openai import AzureOpenAI - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import AIModelEntity, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.azure_openai._common import _CommonAzureOpenAI -from core.model_runtime.model_providers.azure_openai._constant import EMBEDDING_BASE_MODELS, AzureBaseModel - - -class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel): - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - base_model_name = credentials["base_model_name"] - credentials_kwargs = self._to_credential_kwargs(credentials) - client = AzureOpenAI(**credentials_kwargs) - - extra_model_kwargs = {} - if user: - extra_model_kwargs["user"] = user - - extra_model_kwargs["encoding_format"] = "base64" - - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - - embeddings: list[list[float]] = [[] for _ in range(len(texts))] - tokens = [] - indices = [] - used_tokens = 0 - - try: - enc = tiktoken.encoding_for_model(base_model_name) - except KeyError: - enc = tiktoken.get_encoding("cl100k_base") - - for i, text in enumerate(texts): - token = enc.encode(text) - for j in range(0, len(token), context_size): - tokens += [token[j : j + context_size]] - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(tokens), max_chunks) - - for i in _iter: - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, client=client, texts=tokens[i : i + max_chunks], extra_model_kwargs=extra_model_kwargs - ) - - used_tokens += embedding_used_tokens - batched_embeddings += embeddings_batch - - results: list[list[list[float]]] = [[] for _ in range(len(texts))] - num_tokens_in_batch: list[list[int]] = [[] for _ in range(len(texts))] - for i in range(len(indices)): - results[indices[i]].append(batched_embeddings[i]) - num_tokens_in_batch[indices[i]].append(len(tokens[i])) - - for i in range(len(texts)): - _result = results[i] - if len(_result) == 0: - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, client=client, texts="", extra_model_kwargs=extra_model_kwargs - ) - - used_tokens += embedding_used_tokens - average = embeddings_batch[0] - else: - average = np.average(_result, axis=0, weights=num_tokens_in_batch[i]) - embeddings[i] = (average / np.linalg.norm(average)).tolist() - - # calc usage - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - - return TextEmbeddingResult(embeddings=embeddings, usage=usage, model=base_model_name) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - if len(texts) == 0: - return 0 - - try: - enc = tiktoken.encoding_for_model(credentials["base_model_name"]) - except KeyError: - enc = tiktoken.get_encoding("cl100k_base") - - total_num_tokens = 0 - for text in texts: - # calculate the number of tokens in the encoded text - tokenized_text = enc.encode(text) - total_num_tokens += len(tokenized_text) - - return total_num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - if "openai_api_base" not in credentials: - raise CredentialsValidateFailedError("Azure OpenAI API Base Endpoint is required") - - if "openai_api_key" not in credentials: - raise CredentialsValidateFailedError("Azure OpenAI API key is required") - - if "base_model_name" not in credentials: - raise CredentialsValidateFailedError("Base Model Name is required") - - if not self._get_ai_model_entity(credentials["base_model_name"], model): - raise CredentialsValidateFailedError(f'Base Model Name {credentials["base_model_name"]} is invalid') - - try: - credentials_kwargs = self._to_credential_kwargs(credentials) - client = AzureOpenAI(**credentials_kwargs) - - self._embedding_invoke(model=model, client=client, texts=["ping"], extra_model_kwargs={}) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]: - ai_model_entity = self._get_ai_model_entity(credentials["base_model_name"], model) - return ai_model_entity.entity - - @staticmethod - def _embedding_invoke( - model: str, client: AzureOpenAI, texts: Union[list[str], str], extra_model_kwargs: dict - ) -> tuple[list[list[float]], int]: - response = client.embeddings.create( - input=texts, - model=model, - **extra_model_kwargs, - ) - - if "encoding_format" in extra_model_kwargs and extra_model_kwargs["encoding_format"] == "base64": - # decode base64 embedding - return ( - [list(np.frombuffer(base64.b64decode(data.embedding), dtype="float32")) for data in response.data], - response.usage.total_tokens, - ) - - return [data.embedding for data in response.data], response.usage.total_tokens - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - @staticmethod - def _get_ai_model_entity(base_model_name: str, model: str) -> AzureBaseModel: - for ai_model_entity in EMBEDDING_BASE_MODELS: - if ai_model_entity.base_model_name == base_model_name: - ai_model_entity_copy = copy.deepcopy(ai_model_entity) - ai_model_entity_copy.entity.model = model - ai_model_entity_copy.entity.label.en_US = model - ai_model_entity_copy.entity.label.zh_Hans = model - return ai_model_entity_copy - - return None diff --git a/api/core/model_runtime/model_providers/baichuan/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/baichuan/text_embedding/text_embedding.py deleted file mode 100644 index 56b9be1c365340..00000000000000 --- a/api/core/model_runtime/model_providers/baichuan/text_embedding/text_embedding.py +++ /dev/null @@ -1,207 +0,0 @@ -import time -from json import dumps -from typing import Optional - -from requests import post - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.baichuan.llm.baichuan_tokenizer import BaichuanTokenizer -from core.model_runtime.model_providers.baichuan.llm.baichuan_turbo_errors import ( - BadRequestError, - InsufficientAccountBalanceError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) - - -class BaichuanTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for BaiChuan text embedding model. - """ - - api_base: str = "http://api.baichuan-ai.com/v1/embeddings" - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - api_key = credentials["api_key"] - if model != "baichuan-text-embedding": - raise ValueError("Invalid model name") - if not api_key: - raise CredentialsValidateFailedError("api_key is required") - - # split into chunks of batch size 16 - chunks = [] - for i in range(0, len(texts), 16): - chunks.append(texts[i : i + 16]) - - embeddings = [] - token_usage = 0 - - for chunk in chunks: - # embedding chunk - chunk_embeddings, chunk_usage = self.embedding(model=model, api_key=api_key, texts=chunk, user=user) - - embeddings.extend(chunk_embeddings) - token_usage += chunk_usage - - result = TextEmbeddingResult( - model=model, - embeddings=embeddings, - usage=self._calc_response_usage(model=model, credentials=credentials, tokens=token_usage), - ) - - return result - - def embedding( - self, model: str, api_key, texts: list[str], user: Optional[str] = None - ) -> tuple[list[list[float]], int]: - """ - Embed given texts - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :return: embeddings result - """ - url = self.api_base - headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"} - - data = {"model": "Baichuan-Text-Embedding", "input": texts} - - try: - response = post(url, headers=headers, data=dumps(data)) - except Exception as e: - raise InvokeConnectionError(str(e)) - - if response.status_code != 200: - try: - resp = response.json() - # try to parse error message - err = resp["error"]["code"] - msg = resp["error"]["message"] - except Exception as e: - raise InternalServerError(f"Failed to convert response to json: {e} with text: {response.text}") - - if err == "invalid_api_key": - raise InvalidAPIKeyError(msg) - elif err == "insufficient_quota": - raise InsufficientAccountBalanceError(msg) - elif err == "invalid_authentication": - raise InvalidAuthenticationError(msg) - elif err and "rate" in err: - raise RateLimitReachedError(msg) - elif err and "internal" in err: - raise InternalServerError(msg) - elif err == "api_key_empty": - raise InvalidAPIKeyError(msg) - else: - raise InternalServerError(f"Unknown error: {err} with message: {msg}") - - try: - resp = response.json() - embeddings = resp["data"] - usage = resp["usage"] - except Exception as e: - raise InternalServerError(f"Failed to convert response to json: {e} with text: {response.text}") - - return [data["embedding"] for data in embeddings], usage["total_tokens"] - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - for text in texts: - # use BaichuanTokenizer to get num tokens - num_tokens += BaichuanTokenizer._get_num_tokens(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except InvalidAPIKeyError: - raise CredentialsValidateFailedError("Invalid api key") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [InternalServerError], - InvokeRateLimitError: [RateLimitReachedError], - InvokeAuthorizationError: [ - InvalidAuthenticationError, - InsufficientAccountBalanceError, - InvalidAPIKeyError, - ], - InvokeBadRequestError: [BadRequestError, KeyError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py deleted file mode 100644 index 4da20806904ba0..00000000000000 --- a/api/core/model_runtime/model_providers/cohere/text_embedding/text_embedding.py +++ /dev/null @@ -1,223 +0,0 @@ -import time -from typing import Optional - -import cohere -import numpy as np -from cohere.core import RequestOptions - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - - -class CohereTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for Cohere text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - # get model properties - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - - embeddings: list[list[float]] = [[] for _ in range(len(texts))] - tokens = [] - indices = [] - used_tokens = 0 - - for i, text in enumerate(texts): - tokenize_response = self._tokenize(model=model, credentials=credentials, text=text) - - for j in range(0, len(tokenize_response), context_size): - tokens += [tokenize_response[j : j + context_size]] - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(tokens), max_chunks) - - for i in _iter: - # call embedding model - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, credentials=credentials, texts=["".join(token) for token in tokens[i : i + max_chunks]] - ) - - used_tokens += embedding_used_tokens - batched_embeddings += embeddings_batch - - results: list[list[list[float]]] = [[] for _ in range(len(texts))] - num_tokens_in_batch: list[list[int]] = [[] for _ in range(len(texts))] - for i in range(len(indices)): - results[indices[i]].append(batched_embeddings[i]) - num_tokens_in_batch[indices[i]].append(len(tokens[i])) - - for i in range(len(texts)): - _result = results[i] - if len(_result) == 0: - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, credentials=credentials, texts=[" "] - ) - - used_tokens += embedding_used_tokens - average = embeddings_batch[0] - else: - average = np.average(_result, axis=0, weights=num_tokens_in_batch[i]) - embeddings[i] = (average / np.linalg.norm(average)).tolist() - - # calc usage - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - - return TextEmbeddingResult(embeddings=embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - if len(texts) == 0: - return 0 - - full_text = " ".join(texts) - - try: - response = self._tokenize(model=model, credentials=credentials, text=full_text) - except Exception as e: - raise self._transform_invoke_error(e) - - return len(response) - - def _tokenize(self, model: str, credentials: dict, text: str) -> list[str]: - """ - Tokenize text - :param model: model name - :param credentials: model credentials - :param text: text to tokenize - :return: - """ - if not text: - return [] - - # initialize client - client = cohere.Client(credentials.get("api_key"), base_url=credentials.get("base_url")) - - response = client.tokenize(text=text, model=model, offline=False, request_options=RequestOptions(max_retries=0)) - - return response.token_strings - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # call embedding model - self._embedding_invoke(model=model, credentials=credentials, texts=["ping"]) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _embedding_invoke(self, model: str, credentials: dict, texts: list[str]) -> tuple[list[list[float]], int]: - """ - Invoke embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: embeddings and used tokens - """ - # initialize client - client = cohere.Client(credentials.get("api_key"), base_url=credentials.get("base_url")) - - # call embedding model - response = client.embed( - texts=texts, - model=model, - input_type="search_document" if len(texts) > 1 else "search_query", - request_options=RequestOptions(max_retries=1), - ) - - return response.embeddings, int(response.meta.billed_units.input_tokens) - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [cohere.errors.service_unavailable_error.ServiceUnavailableError], - InvokeServerUnavailableError: [cohere.errors.internal_server_error.InternalServerError], - InvokeRateLimitError: [cohere.errors.too_many_requests_error.TooManyRequestsError], - InvokeAuthorizationError: [ - cohere.errors.unauthorized_error.UnauthorizedError, - cohere.errors.forbidden_error.ForbiddenError, - ], - InvokeBadRequestError: [ - cohere.core.api_error.ApiError, - cohere.errors.bad_request_error.BadRequestError, - cohere.errors.not_found_error.NotFoundError, - ], - } diff --git a/api/core/model_runtime/model_providers/fireworks/fireworks.yaml b/api/core/model_runtime/model_providers/fireworks/fireworks.yaml deleted file mode 100644 index cdb87a55e94660..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/fireworks.yaml +++ /dev/null @@ -1,30 +0,0 @@ -provider: fireworks -label: - zh_Hans: Fireworks AI - en_US: Fireworks AI -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#FCFDFF" -help: - title: - en_US: Get your API Key from Fireworks AI - zh_Hans: 从 Fireworks AI 获取 API Key - url: - en_US: https://fireworks.ai/account/api-keys -supported_model_types: - - llm - - text-embedding -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: fireworks_api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-11b-vision-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-11b-vision-instruct.yaml deleted file mode 100644 index 31415a24fa8b7e..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-11b-vision-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3p2-11b-vision-instruct -label: - zh_Hans: Llama 3.2 11B Vision Instruct - en_US: Llama 3.2 11B Vision Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.2' - output: '0.2' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-1b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-1b-instruct.yaml deleted file mode 100644 index c2fd77d2568d29..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-1b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3p2-1b-instruct -label: - zh_Hans: Llama 3.2 1B Instruct - en_US: Llama 3.2 1B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.1' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-3b-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-3b-instruct.yaml deleted file mode 100644 index 4b3c459c7bf2fc..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-3b-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3p2-3b-instruct -label: - zh_Hans: Llama 3.2 3B Instruct - en_US: Llama 3.2 3B Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.1' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-90b-vision-instruct.yaml b/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-90b-vision-instruct.yaml deleted file mode 100644 index 0aece7455d6254..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/llm/llama-v3p2-90b-vision-instruct.yaml +++ /dev/null @@ -1,46 +0,0 @@ -model: accounts/fireworks/models/llama-v3p2-90b-vision-instruct -label: - zh_Hans: Llama 3.2 90B Vision Instruct - en_US: Llama 3.2 90B Vision Instruct -model_type: llm -features: - - agent-thought - - tool-call -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - - name: max_tokens - use_template: max_tokens - - name: context_length_exceeded_behavior - default: None - label: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - help: - zh_Hans: 上下文长度超出行为 - en_US: Context Length Exceeded Behavior - type: string - options: - - None - - truncate - - error - - name: response_format - use_template: response_format -pricing: - input: '0.9' - output: '0.9' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/fireworks/text_embedding/UAE-Large-V1.yaml b/api/core/model_runtime/model_providers/fireworks/text_embedding/UAE-Large-V1.yaml deleted file mode 100644 index d7c11691cf9bbc..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/text_embedding/UAE-Large-V1.yaml +++ /dev/null @@ -1,12 +0,0 @@ -model: WhereIsAI/UAE-Large-V1 -label: - zh_Hans: UAE-Large-V1 - en_US: UAE-Large-V1 -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 1 -pricing: - input: '0.008' - unit: '0.000001' - currency: 'USD' diff --git a/api/core/model_runtime/model_providers/fireworks/text_embedding/__init__.py b/api/core/model_runtime/model_providers/fireworks/text_embedding/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/core/model_runtime/model_providers/fireworks/text_embedding/gte-base.yaml b/api/core/model_runtime/model_providers/fireworks/text_embedding/gte-base.yaml deleted file mode 100644 index d09bafb4d312f9..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/text_embedding/gte-base.yaml +++ /dev/null @@ -1,12 +0,0 @@ -model: thenlper/gte-base -label: - zh_Hans: GTE-base - en_US: GTE-base -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 1 -pricing: - input: '0.008' - unit: '0.000001' - currency: 'USD' diff --git a/api/core/model_runtime/model_providers/fireworks/text_embedding/gte-large.yaml b/api/core/model_runtime/model_providers/fireworks/text_embedding/gte-large.yaml deleted file mode 100644 index c41fa2f9d32361..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/text_embedding/gte-large.yaml +++ /dev/null @@ -1,12 +0,0 @@ -model: thenlper/gte-large -label: - zh_Hans: GTE-large - en_US: GTE-large -model_type: text-embedding -model_properties: - context_size: 512 - max_chunks: 1 -pricing: - input: '0.008' - unit: '0.000001' - currency: 'USD' diff --git a/api/core/model_runtime/model_providers/fireworks/text_embedding/nomic-embed-text-v1.5.yaml b/api/core/model_runtime/model_providers/fireworks/text_embedding/nomic-embed-text-v1.5.yaml deleted file mode 100644 index c9098503d96529..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/text_embedding/nomic-embed-text-v1.5.yaml +++ /dev/null @@ -1,12 +0,0 @@ -model: nomic-ai/nomic-embed-text-v1.5 -label: - zh_Hans: nomic-embed-text-v1.5 - en_US: nomic-embed-text-v1.5 -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 16 -pricing: - input: '0.008' - unit: '0.000001' - currency: 'USD' diff --git a/api/core/model_runtime/model_providers/fireworks/text_embedding/nomic-embed-text-v1.yaml b/api/core/model_runtime/model_providers/fireworks/text_embedding/nomic-embed-text-v1.yaml deleted file mode 100644 index 89078d3ff69f93..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/text_embedding/nomic-embed-text-v1.yaml +++ /dev/null @@ -1,12 +0,0 @@ -model: nomic-ai/nomic-embed-text-v1 -label: - zh_Hans: nomic-embed-text-v1 - en_US: nomic-embed-text-v1 -model_type: text-embedding -model_properties: - context_size: 8192 - max_chunks: 16 -pricing: - input: '0.008' - unit: '0.000001' - currency: 'USD' diff --git a/api/core/model_runtime/model_providers/fireworks/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/fireworks/text_embedding/text_embedding.py deleted file mode 100644 index cdce69ff380338..00000000000000 --- a/api/core/model_runtime/model_providers/fireworks/text_embedding/text_embedding.py +++ /dev/null @@ -1,151 +0,0 @@ -import time -from collections.abc import Mapping -from typing import Optional, Union - -import numpy as np -from openai import OpenAI - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.fireworks._common import _CommonFireworks - - -class FireworksTextEmbeddingModel(_CommonFireworks, TextEmbeddingModel): - """ - Model class for Fireworks text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - extra_model_kwargs = {} - if user: - extra_model_kwargs["user"] = user - - extra_model_kwargs["encoding_format"] = "float" - - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - - inputs = [] - indices = [] - used_tokens = 0 - - for i, text in enumerate(texts): - # Here token count is only an approximation based on the GPT2 tokenizer - # TODO: Optimize for better token estimation and chunking - num_tokens = self._get_num_tokens_by_gpt2(text) - - if num_tokens >= context_size: - cutoff = int(np.floor(len(text) * (context_size / num_tokens))) - # if num tokens is larger than context length, only use the start - inputs.append(text[0:cutoff]) - else: - inputs.append(text) - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(inputs), max_chunks) - - for i in _iter: - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, - client=client, - texts=inputs[i : i + max_chunks], - extra_model_kwargs=extra_model_kwargs, - ) - used_tokens += embedding_used_tokens - batched_embeddings += embeddings_batch - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - return TextEmbeddingResult(embeddings=batched_embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - return sum(self._get_num_tokens_by_gpt2(text) for text in texts) - - def validate_credentials(self, model: str, credentials: Mapping) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - # call embedding model - self._embedding_invoke(model=model, client=client, texts=["ping"], extra_model_kwargs={}) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _embedding_invoke( - self, model: str, client: OpenAI, texts: Union[list[str], str], extra_model_kwargs: dict - ) -> tuple[list[list[float]], int]: - """ - Invoke embedding model - :param model: model name - :param client: model client - :param texts: texts to embed - :param extra_model_kwargs: extra model kwargs - :return: embeddings and used tokens - """ - response = client.embeddings.create(model=model, input=texts, **extra_model_kwargs) - return [data.embedding for data in response.data], response.usage.total_tokens - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - input_price_info = self.get_price( - model=model, credentials=credentials, tokens=tokens, price_type=PriceType.INPUT - ) - - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/fishaudio/fishaudio.yaml b/api/core/model_runtime/model_providers/fishaudio/fishaudio.yaml deleted file mode 100644 index 479eb7fb85bd76..00000000000000 --- a/api/core/model_runtime/model_providers/fishaudio/fishaudio.yaml +++ /dev/null @@ -1,76 +0,0 @@ -provider: fishaudio -label: - en_US: Fish Audio -description: - en_US: Models provided by Fish Audio, currently only support TTS. - zh_Hans: Fish Audio 提供的模型，目前仅支持 TTS。 -icon_small: - en_US: fishaudio_s_en.svg -icon_large: - en_US: fishaudio_l_en.svg -background: "#E5E7EB" -help: - title: - en_US: Get your API key from Fish Audio - zh_Hans: 从 Fish Audio 获取你的 API Key - url: - en_US: https://fish.audio/go-api/ -supported_model_types: - - tts -configurate_methods: - - predefined-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: api_base - label: - en_US: API URL - type: text-input - required: false - default: https://api.fish.audio - placeholder: - en_US: Enter your API URL - zh_Hans: 在此输入您的 API URL - - variable: use_public_models - label: - en_US: Use Public Models - type: select - required: false - default: "false" - placeholder: - en_US: Toggle to use public models - zh_Hans: 切换以使用公共模型 - options: - - value: "true" - label: - en_US: Allow Public Models - zh_Hans: 使用公共模型 - - value: "false" - label: - en_US: Private Models Only - zh_Hans: 仅使用私有模型 - - variable: latency - label: - en_US: Latency - type: select - required: false - default: "normal" - placeholder: - en_US: Toggle to choice latency - zh_Hans: 切换以调整延迟 - options: - - value: "balanced" - label: - en_US: Low (may affect quality) - zh_Hans: 低延迟 (可能降低质量) - - value: "normal" - label: - en_US: Normal - zh_Hans: 标准 diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-001.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-001.yaml deleted file mode 100644 index d84e9937e0b661..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-001.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-flash-001 -label: - en_US: Gemini 1.5 Flash 001 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-002.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-002.yaml deleted file mode 100644 index 2ff70564b2a951..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-002.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-flash-002 -label: - en_US: Gemini 1.5 Flash 002 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-8b-exp-0924.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-8b-exp-0924.yaml deleted file mode 100644 index 2aea8149f4c794..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash-8b-exp-0924.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-flash-8b-exp-0924 -label: - en_US: Gemini 1.5 Flash 8B 0924 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash.yaml deleted file mode 100644 index dfd55c3a949c97..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-flash.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-flash -label: - en_US: Gemini 1.5 Flash -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-001.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-001.yaml deleted file mode 100644 index a1feff171d48c2..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-001.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-pro-001 -label: - en_US: Gemini 1.5 Pro 001 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 2097152 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-002.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-002.yaml deleted file mode 100644 index 9ae07a06c5118b..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro-002.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-pro-002 -label: - en_US: Gemini 1.5 Pro 002 -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 2097152 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro.yaml b/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro.yaml deleted file mode 100644 index bdd70b34a21dc5..00000000000000 --- a/api/core/model_runtime/model_providers/google/llm/gemini-1.5-pro.yaml +++ /dev/null @@ -1,48 +0,0 @@ -model: gemini-1.5-pro -label: - en_US: Gemini 1.5 Pro -model_type: llm -features: - - agent-thought - - vision - - tool-call - - stream-tool-call -model_properties: - mode: chat - context_size: 2097152 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - zh_Hans: 取样数量 - en_US: Top k - type: int - help: - zh_Hans: 仅从每个后续标记的前 K 个选项中采样。 - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: max_tokens_to_sample - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 - - name: response_format - use_template: response_format - - name: stream - label: - zh_Hans: 流式输出 - en_US: Stream - type: boolean - help: - zh_Hans: 流式输出允许模型在生成文本的过程中逐步返回结果，而不是一次性生成全部结果后再返回。 - en_US: Streaming output allows the model to return results incrementally as it generates text, rather than generating all the results at once. - default: false -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama-3.2-11b-text-preview.yaml b/api/core/model_runtime/model_providers/groq/llm/llama-3.2-11b-text-preview.yaml deleted file mode 100644 index 019d45372361d3..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama-3.2-11b-text-preview.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama-3.2-11b-text-preview -label: - zh_Hans: Llama 3.2 11B Text (Preview) - en_US: Llama 3.2 11B Text (Preview) -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.05' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama-3.2-1b-preview.yaml b/api/core/model_runtime/model_providers/groq/llm/llama-3.2-1b-preview.yaml deleted file mode 100644 index a44e4ff508eb82..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama-3.2-1b-preview.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama-3.2-1b-preview -label: - zh_Hans: Llama 3.2 1B Text (Preview) - en_US: Llama 3.2 1B Text (Preview) -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.05' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama-3.2-3b-preview.yaml b/api/core/model_runtime/model_providers/groq/llm/llama-3.2-3b-preview.yaml deleted file mode 100644 index f2fdd0a05e027a..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama-3.2-3b-preview.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama-3.2-3b-preview -label: - zh_Hans: Llama 3.2 3B Text (Preview) - en_US: Llama 3.2 3B Text (Preview) -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.05' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/groq/llm/llama-3.2-90b-text-preview.yaml b/api/core/model_runtime/model_providers/groq/llm/llama-3.2-90b-text-preview.yaml deleted file mode 100644 index 3b34e7c07996bd..00000000000000 --- a/api/core/model_runtime/model_providers/groq/llm/llama-3.2-90b-text-preview.yaml +++ /dev/null @@ -1,25 +0,0 @@ -model: llama-3.2-90b-text-preview -label: - zh_Hans: Llama 3.2 90B Text (Preview) - en_US: Llama 3.2 90B Text (Preview) -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: max_tokens - use_template: max_tokens - default: 512 - min: 1 - max: 8192 -pricing: - input: '0.05' - output: '0.1' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/huggingface_hub/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/huggingface_hub/text_embedding/text_embedding.py deleted file mode 100644 index b2e6d1b6520c72..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_hub/text_embedding/text_embedding.py +++ /dev/null @@ -1,189 +0,0 @@ -import json -import time -from typing import Optional - -import numpy as np -import requests -from huggingface_hub import HfApi, InferenceClient - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.huggingface_hub._common import _CommonHuggingfaceHub - -HUGGINGFACE_ENDPOINT_API = "https://api.endpoints.huggingface.cloud/v2/endpoint/" - - -class HuggingfaceHubTextEmbeddingModel(_CommonHuggingfaceHub, TextEmbeddingModel): - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - client = InferenceClient(token=credentials["huggingfacehub_api_token"]) - - execute_model = model - - if credentials["huggingfacehub_api_type"] == "inference_endpoints": - execute_model = credentials["huggingfacehub_endpoint_url"] - - output = client.post( - json={"inputs": texts, "options": {"wait_for_model": False, "use_cache": False}}, model=execute_model - ) - - embeddings = json.loads(output.decode()) - - tokens = self.get_num_tokens(model, credentials, texts) - usage = self._calc_response_usage(model, credentials, tokens) - - return TextEmbeddingResult(embeddings=self._mean_pooling(embeddings), usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - num_tokens = 0 - for text in texts: - num_tokens += self._get_num_tokens_by_gpt2(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - try: - if "huggingfacehub_api_type" not in credentials: - raise CredentialsValidateFailedError("Huggingface Hub Endpoint Type must be provided.") - - if "huggingfacehub_api_token" not in credentials: - raise CredentialsValidateFailedError("Huggingface Hub API Token must be provided.") - - if credentials["huggingfacehub_api_type"] == "inference_endpoints": - if "huggingface_namespace" not in credentials: - raise CredentialsValidateFailedError( - "Huggingface Hub User Name / Organization Name must be provided." - ) - - if "huggingfacehub_endpoint_url" not in credentials: - raise CredentialsValidateFailedError("Huggingface Hub Endpoint URL must be provided.") - - if "task_type" not in credentials: - raise CredentialsValidateFailedError("Huggingface Hub Task Type must be provided.") - - if credentials["task_type"] != "feature-extraction": - raise CredentialsValidateFailedError("Huggingface Hub Task Type is invalid.") - - self._check_endpoint_url_model_repository_name(credentials, model) - - model = credentials["huggingfacehub_endpoint_url"] - - elif credentials["huggingfacehub_api_type"] == "hosted_inference_api": - self._check_hosted_model_task_type(credentials["huggingfacehub_api_token"], model) - else: - raise CredentialsValidateFailedError("Huggingface Hub Endpoint Type is invalid.") - - client = InferenceClient(token=credentials["huggingfacehub_api_token"]) - client.feature_extraction(text="hello world", model=model) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]: - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TEXT_EMBEDDING, - model_properties={"context_size": 10000, "max_chunks": 1}, - ) - return entity - - # https://huggingface.co/docs/api-inference/detailed_parameters#feature-extraction-task - # Returned values are a list of floats, or a list[list[floats]] - # (depending on if you sent a string or a list of string, - # and if the automatic reduction, usually mean_pooling for instance was applied for you or not. - # This should be explained on the model's README.) - @staticmethod - def _mean_pooling(embeddings: list) -> list[float]: - # If automatic reduction by giving model, no need to mean_pooling. - # For example one: List[List[float]] - if not isinstance(embeddings[0][0], list): - return embeddings - - # For example two: List[List[List[float]]], need to mean_pooling. - sentence_embeddings = [np.mean(embedding[0], axis=0).tolist() for embedding in embeddings] - return sentence_embeddings - - @staticmethod - def _check_hosted_model_task_type(huggingfacehub_api_token: str, model_name: str) -> None: - hf_api = HfApi(token=huggingfacehub_api_token) - model_info = hf_api.model_info(repo_id=model_name) - - try: - if not model_info: - raise ValueError(f"Model {model_name} not found.") - - if "inference" in model_info.cardData and not model_info.cardData["inference"]: - raise ValueError(f"Inference API has been turned off for this model {model_name}.") - - valid_tasks = "feature-extraction" - if model_info.pipeline_tag not in valid_tasks: - raise ValueError(f"Model {model_name} is not a valid task, must be one of {valid_tasks}.") - except Exception as e: - raise CredentialsValidateFailedError(f"{str(e)}") - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - @staticmethod - def _check_endpoint_url_model_repository_name(credentials: dict, model_name: str): - try: - url = f'{HUGGINGFACE_ENDPOINT_API}{credentials["huggingface_namespace"]}' - headers = { - "Authorization": f'Bearer {credentials["huggingfacehub_api_token"]}', - "Content-Type": "application/json", - } - - response = requests.get(url=url, headers=headers) - - if response.status_code != 200: - raise ValueError("User Name or Organization Name is invalid.") - - model_repository_name = "" - - for item in response.json().get("items", []): - if item.get("status", {}).get("url") == credentials["huggingfacehub_endpoint_url"]: - model_repository_name = item.get("model", {}).get("repository") - break - - if model_repository_name != model_name: - raise ValueError( - f"Model Name {model_name} is invalid. Please check it on the inference endpoints console." - ) - - except Exception as e: - raise ValueError(str(e)) diff --git a/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/text_embedding.py deleted file mode 100644 index b8ff3ca549a63b..00000000000000 --- a/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/text_embedding.py +++ /dev/null @@ -1,209 +0,0 @@ -import time -from typing import Optional - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.huggingface_tei.tei_helper import TeiHelper - - -class HuggingfaceTeiTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for Text Embedding Inference text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - credentials should be like: - { - 'server_url': 'server url', - 'model_uid': 'model uid', - } - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - server_url = credentials["server_url"] - - server_url = server_url.removesuffix("/") - - # get model properties - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - - inputs = [] - indices = [] - used_tokens = 0 - - # get tokenized results from TEI - batched_tokenize_result = TeiHelper.invoke_tokenize(server_url, texts) - - for i, (text, tokenize_result) in enumerate(zip(texts, batched_tokenize_result)): - # Check if the number of tokens is larger than the context size - num_tokens = len(tokenize_result) - - if num_tokens >= context_size: - # Find the best cutoff point - pre_special_token_count = 0 - for token in tokenize_result: - if token["special"]: - pre_special_token_count += 1 - else: - break - rest_special_token_count = ( - len([token for token in tokenize_result if token["special"]]) - pre_special_token_count - ) - - # Calculate the cutoff point, leave 20 extra space to avoid exceeding the limit - token_cutoff = context_size - rest_special_token_count - 20 - - # Find the cutoff index - cutpoint_token = tokenize_result[token_cutoff] - cutoff = cutpoint_token["start"] - - inputs.append(text[0:cutoff]) - else: - inputs.append(text) - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(inputs), max_chunks) - - try: - used_tokens = 0 - for i in _iter: - iter_texts = inputs[i : i + max_chunks] - results = TeiHelper.invoke_embeddings(server_url, iter_texts) - embeddings = results["data"] - embeddings = [embedding["embedding"] for embedding in embeddings] - batched_embeddings.extend(embeddings) - - usage = results["usage"] - used_tokens += usage["total_tokens"] - except RuntimeError as e: - raise InvokeServerUnavailableError(str(e)) - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - - result = TextEmbeddingResult(model=model, embeddings=batched_embeddings, usage=usage) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - server_url = credentials["server_url"] - - server_url = server_url.removesuffix("/") - - batch_tokens = TeiHelper.invoke_tokenize(server_url, texts) - num_tokens = sum(len(tokens) for tokens in batch_tokens) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - server_url = credentials["server_url"] - extra_args = TeiHelper.get_tei_extra_parameter(server_url, model) - print(extra_args) - if extra_args.model_type != "embedding": - raise CredentialsValidateFailedError("Current model is not a embedding model") - - credentials["context_size"] = extra_args.max_input_length - credentials["max_chunks"] = extra_args.max_client_batch_size - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TEXT_EMBEDDING, - model_properties={ - ModelPropertyKey.MAX_CHUNKS: int(credentials.get("max_chunks", 1)), - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", 512)), - }, - parameter_rules=[], - ) - - return entity diff --git a/api/core/model_runtime/model_providers/hunyuan/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/hunyuan/text_embedding/text_embedding.py deleted file mode 100644 index 75701ebc54a749..00000000000000 --- a/api/core/model_runtime/model_providers/hunyuan/text_embedding/text_embedding.py +++ /dev/null @@ -1,169 +0,0 @@ -import json -import logging -import time -from typing import Optional - -from tencentcloud.common import credential -from tencentcloud.common.exception import TencentCloudSDKException -from tencentcloud.common.profile.client_profile import ClientProfile -from tencentcloud.common.profile.http_profile import HttpProfile -from tencentcloud.hunyuan.v20230901 import hunyuan_client, models - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - -logger = logging.getLogger(__name__) - - -class HunyuanTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for Hunyuan text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - - if model != "hunyuan-embedding": - raise ValueError("Invalid model name") - - client = self._setup_hunyuan_client(credentials) - - embeddings = [] - token_usage = 0 - - for input in texts: - request = models.GetEmbeddingRequest() - params = {"Input": input} - request.from_json_string(json.dumps(params)) - response = client.GetEmbedding(request) - usage = response.Usage.TotalTokens - - embeddings.extend([data.Embedding for data in response.Data]) - token_usage += usage - - result = TextEmbeddingResult( - model=model, - embeddings=embeddings, - usage=self._calc_response_usage(model=model, credentials=credentials, tokens=token_usage), - ) - - return result - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate credentials - """ - try: - client = self._setup_hunyuan_client(credentials) - - req = models.ChatCompletionsRequest() - params = { - "Model": model, - "Messages": [{"Role": "user", "Content": "hello"}], - "TopP": 1, - "Temperature": 0, - "Stream": False, - } - req.from_json_string(json.dumps(params)) - client.ChatCompletions(req) - except Exception as e: - raise CredentialsValidateFailedError(f"Credentials validation failed: {e}") - - def _setup_hunyuan_client(self, credentials): - secret_id = credentials["secret_id"] - secret_key = credentials["secret_key"] - cred = credential.Credential(secret_id, secret_key) - httpProfile = HttpProfile() - httpProfile.endpoint = "hunyuan.tencentcloudapi.com" - clientProfile = ClientProfile() - clientProfile.httpProfile = httpProfile - client = hunyuan_client.HunyuanClient(cred, "", clientProfile) - return client - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeError: [TencentCloudSDKException], - } - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - # client = self._setup_hunyuan_client(credentials) - - num_tokens = 0 - for text in texts: - num_tokens += self._get_num_tokens_by_gpt2(text) - # use client.GetTokenCount to get num tokens - # request = models.GetTokenCountRequest() - # params = { - # "Prompt": text - # } - # request.from_json_string(json.dumps(params)) - # response = client.GetTokenCount(request) - # num_tokens += response.TokenCount - - return num_tokens diff --git a/api/core/model_runtime/model_providers/jina/jina.yaml b/api/core/model_runtime/model_providers/jina/jina.yaml deleted file mode 100644 index 970b22965b5d29..00000000000000 --- a/api/core/model_runtime/model_providers/jina/jina.yaml +++ /dev/null @@ -1,69 +0,0 @@ -provider: jina -label: - en_US: Jina AI -description: - en_US: Embedding and Rerank Model Supported -icon_small: - en_US: icon_s_en.svg -icon_large: - en_US: icon_l_en.svg -background: "#EFFDFD" -help: - title: - en_US: Get your API key from Jina AI - zh_Hans: 从 Jina AI 获取 API Key - url: - en_US: https://jina.ai/ -supported_model_types: - - text-embedding - - rerank -configurate_methods: - - predefined-model - - customizable-model -provider_credential_schema: - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key -model_credential_schema: - model: - label: - en_US: Model Name - zh_Hans: 模型名称 - placeholder: - en_US: Enter your model name - zh_Hans: 输入模型名称 - credential_form_schemas: - - variable: api_key - label: - en_US: API Key - type: secret-input - required: true - placeholder: - zh_Hans: 在此输入您的 API Key - en_US: Enter your API Key - - variable: base_url - label: - zh_Hans: 服务器 URL - en_US: Base URL - type: text-input - required: true - placeholder: - zh_Hans: Base URL, e.g. https://api.jina.ai/v1 - en_US: Base URL, e.g. https://api.jina.ai/v1 - default: 'https://api.jina.ai/v1' - - variable: context_size - label: - zh_Hans: 上下文大小 - en_US: Context size - placeholder: - zh_Hans: 输入上下文大小 - en_US: Enter context size - required: false - type: text-input - default: '8192' diff --git a/api/core/model_runtime/model_providers/jina/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/jina/text_embedding/text_embedding.py deleted file mode 100644 index b39712951256c8..00000000000000 --- a/api/core/model_runtime/model_providers/jina/text_embedding/text_embedding.py +++ /dev/null @@ -1,199 +0,0 @@ -import time -from json import JSONDecodeError, dumps -from typing import Optional - -from requests import post - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.jina.text_embedding.jina_tokenizer import JinaTokenizer - - -class JinaTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for Jina text embedding model. - """ - - api_base: str = "https://api.jina.ai/v1" - - def _to_payload(self, model: str, texts: list[str], credentials: dict, input_type: EmbeddingInputType) -> dict: - """ - Parse model credentials - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: parsed credentials - """ - - def transform_jina_input_text(model, text): - if model == "jina-clip-v1": - return {"text": text} - return text - - data = {"model": model, "input": [transform_jina_input_text(model, text) for text in texts]} - - # model specific parameters - if model == "jina-embeddings-v3": - # set `task` type according to input type for the best performance - data["task"] = "retrieval.query" if input_type == EmbeddingInputType.QUERY else "retrieval.passage" - - return data - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - api_key = credentials["api_key"] - if not api_key: - raise CredentialsValidateFailedError("api_key is required") - - base_url = credentials.get("base_url", self.api_base) - base_url = base_url.removesuffix("/") - - url = base_url + "/embeddings" - headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"} - - data = self._to_payload(model=model, texts=texts, credentials=credentials, input_type=input_type) - - try: - response = post(url, headers=headers, data=dumps(data)) - except Exception as e: - raise InvokeConnectionError(str(e)) - - if response.status_code != 200: - try: - resp = response.json() - msg = resp["detail"] - if response.status_code == 401: - raise InvokeAuthorizationError(msg) - elif response.status_code == 429: - raise InvokeRateLimitError(msg) - elif response.status_code == 500: - raise InvokeServerUnavailableError(msg) - else: - raise InvokeBadRequestError(msg) - except JSONDecodeError as e: - raise InvokeServerUnavailableError( - f"Failed to convert response to json: {e} with text: {response.text}" - ) - - try: - resp = response.json() - embeddings = resp["data"] - usage = resp["usage"] - except Exception as e: - raise InvokeServerUnavailableError(f"Failed to convert response to json: {e} with text: {response.text}") - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=usage["total_tokens"]) - - result = TextEmbeddingResult( - model=model, embeddings=[[float(data) for data in x["embedding"]] for x in embeddings], usage=usage - ) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - for text in texts: - # use JinaTokenizer to get num tokens - num_tokens += JinaTokenizer.get_num_tokens(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except Exception as e: - raise CredentialsValidateFailedError(f"Credentials validation failed: {e}") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError, InvokeBadRequestError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.TEXT_EMBEDDING, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size"))}, - ) - - return entity diff --git a/api/core/model_runtime/model_providers/localai/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/localai/text_embedding/text_embedding.py deleted file mode 100644 index ab8ca76c2f0971..00000000000000 --- a/api/core/model_runtime/model_providers/localai/text_embedding/text_embedding.py +++ /dev/null @@ -1,189 +0,0 @@ -import time -from json import JSONDecodeError, dumps -from typing import Optional - -from requests import post -from yarl import URL - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - - -class LocalAITextEmbeddingModel(TextEmbeddingModel): - """ - Model class for LocalAI text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - if len(texts) != 1: - raise InvokeBadRequestError("Only one text is supported") - - server_url = credentials["server_url"] - model_name = model - if not server_url: - raise CredentialsValidateFailedError("server_url is required") - if not model_name: - raise CredentialsValidateFailedError("model_name is required") - - url = server_url - headers = {"Authorization": "Bearer 123", "Content-Type": "application/json"} - - data = {"model": model_name, "input": texts[0]} - - try: - response = post(str(URL(url) / "embeddings"), headers=headers, data=dumps(data), timeout=10) - except Exception as e: - raise InvokeConnectionError(str(e)) - - if response.status_code != 200: - try: - resp = response.json() - code = resp["error"]["code"] - msg = resp["error"]["message"] - if code == 500: - raise InvokeServerUnavailableError(msg) - - if response.status_code == 401: - raise InvokeAuthorizationError(msg) - elif response.status_code == 429: - raise InvokeRateLimitError(msg) - elif response.status_code == 500: - raise InvokeServerUnavailableError(msg) - else: - raise InvokeError(msg) - except JSONDecodeError as e: - raise InvokeServerUnavailableError( - f"Failed to convert response to json: {e} with text: {response.text}" - ) - - try: - resp = response.json() - embeddings = resp["data"] - usage = resp["usage"] - except Exception as e: - raise InvokeServerUnavailableError(f"Failed to convert response to json: {e} with text: {response.text}") - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=usage["total_tokens"]) - - result = TextEmbeddingResult( - model=model, embeddings=[[float(data) for data in x["embedding"]] for x in embeddings], usage=usage - ) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - for text in texts: - # use GPT2Tokenizer to get num tokens - num_tokens += self._get_num_tokens_by_gpt2(text) - return num_tokens - - def _get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - Get customizable model schema - - :param model: model name - :param credentials: model credentials - :return: model schema - """ - return AIModelEntity( - model=model, - label=I18nObject(zh_Hans=model, en_US=model), - model_type=ModelType.TEXT_EMBEDDING, - features=[], - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", "512")), - ModelPropertyKey.MAX_CHUNKS: 1, - }, - parameter_rules=[], - ) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except InvokeAuthorizationError: - raise CredentialsValidateFailedError("Invalid credentials") - except InvokeConnectionError as e: - raise CredentialsValidateFailedError(f"Invalid credentials: {e}") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/minimax/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/minimax/text_embedding/text_embedding.py deleted file mode 100644 index 74d2a221d1b57e..00000000000000 --- a/api/core/model_runtime/model_providers/minimax/text_embedding/text_embedding.py +++ /dev/null @@ -1,184 +0,0 @@ -import time -from json import dumps -from typing import Optional - -from requests import post - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.minimax.llm.errors import ( - BadRequestError, - InsufficientAccountBalanceError, - InternalServerError, - InvalidAPIKeyError, - InvalidAuthenticationError, - RateLimitReachedError, -) - - -class MinimaxTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for Minimax text embedding model. - """ - - api_base: str = "https://api.minimax.chat/v1/embeddings" - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - api_key = credentials["minimax_api_key"] - group_id = credentials["minimax_group_id"] - if model != "embo-01": - raise ValueError("Invalid model name") - if not api_key: - raise CredentialsValidateFailedError("api_key is required") - url = f"{self.api_base}?GroupId={group_id}" - headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"} - - data = {"model": "embo-01", "texts": texts, "type": "db"} - - try: - response = post(url, headers=headers, data=dumps(data)) - except Exception as e: - raise InvokeConnectionError(str(e)) - - if response.status_code != 200: - raise InvokeServerUnavailableError(response.text) - - try: - resp = response.json() - # check if there is an error - if resp["base_resp"]["status_code"] != 0: - code = resp["base_resp"]["status_code"] - msg = resp["base_resp"]["status_msg"] - self._handle_error(code, msg) - - embeddings = resp["vectors"] - total_tokens = resp["total_tokens"] - except InvalidAuthenticationError: - raise InvalidAPIKeyError("Invalid api key") - except KeyError as e: - raise InternalServerError(f"Failed to convert response to json: {e} with text: {response.text}") - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=total_tokens) - - result = TextEmbeddingResult(model=model, embeddings=embeddings, usage=usage) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - for text in texts: - # use MinimaxTokenizer to get num tokens - num_tokens += self._get_num_tokens_by_gpt2(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except InvalidAPIKeyError: - raise CredentialsValidateFailedError("Invalid api key") - - def _handle_error(self, code: int, msg: str): - if code in {1000, 1001}: - raise InternalServerError(msg) - elif code == 1002: - raise RateLimitReachedError(msg) - elif code == 1004: - raise InvalidAuthenticationError(msg) - elif code == 1008: - raise InsufficientAccountBalanceError(msg) - elif code == 2013: - raise BadRequestError(msg) - else: - raise InternalServerError(msg) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [InternalServerError], - InvokeRateLimitError: [RateLimitReachedError], - InvokeAuthorizationError: [ - InvalidAuthenticationError, - InsufficientAccountBalanceError, - InvalidAPIKeyError, - ], - InvokeBadRequestError: [BadRequestError, KeyError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/mixedbread/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/mixedbread/text_embedding/text_embedding.py deleted file mode 100644 index 68b7b448bfec75..00000000000000 --- a/api/core/model_runtime/model_providers/mixedbread/text_embedding/text_embedding.py +++ /dev/null @@ -1,170 +0,0 @@ -import time -from json import JSONDecodeError, dumps -from typing import Optional - -import requests - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - - -class MixedBreadTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for MixedBread text embedding model. - """ - - api_base: str = "https://api.mixedbread.ai/v1" - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - api_key = credentials["api_key"] - if not api_key: - raise CredentialsValidateFailedError("api_key is required") - - base_url = credentials.get("base_url", self.api_base) - base_url = base_url.removesuffix("/") - - url = base_url + "/embeddings" - headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"} - - data = {"model": model, "input": texts} - - try: - response = requests.post(url, headers=headers, data=dumps(data)) - except Exception as e: - raise InvokeConnectionError(str(e)) - - if response.status_code != 200: - try: - resp = response.json() - msg = resp["detail"] - if response.status_code == 401: - raise InvokeAuthorizationError(msg) - elif response.status_code == 429: - raise InvokeRateLimitError(msg) - elif response.status_code == 500: - raise InvokeServerUnavailableError(msg) - else: - raise InvokeBadRequestError(msg) - except JSONDecodeError as e: - raise InvokeServerUnavailableError( - f"Failed to convert response to json: {e} with text: {response.text}" - ) - - try: - resp = response.json() - embeddings = resp["data"] - usage = resp["usage"] - except Exception as e: - raise InvokeServerUnavailableError(f"Failed to convert response to json: {e} with text: {response.text}") - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=usage["total_tokens"]) - - result = TextEmbeddingResult( - model=model, embeddings=[[float(data) for data in x["embedding"]] for x in embeddings], usage=usage - ) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - return sum(self._get_num_tokens_by_gpt2(text) for text in texts) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except Exception as e: - raise CredentialsValidateFailedError(f"Credentials validation failed: {e}") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError, InvokeBadRequestError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.TEXT_EMBEDDING, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", "512"))}, - ) - - return entity diff --git a/api/core/model_runtime/model_providers/model_provider_factory.py b/api/core/model_runtime/model_providers/model_provider_factory.py index 1370676f0e1d85..f2c6d6a6502e62 100644 --- a/api/core/model_runtime/model_providers/model_provider_factory.py +++ b/api/core/model_runtime/model_providers/model_provider_factory.py @@ -13,7 +13,6 @@ from core.model_runtime.model_providers.__base.moderation_model import ModerationModel from core.model_runtime.model_providers.__base.rerank_model import RerankModel from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel -from core.model_runtime.model_providers.__base.text2img_model import Text2ImageModel from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel from core.model_runtime.model_providers.__base.tts_model import TTSModel from core.model_runtime.schema_validators.model_credential_schema_validator import ModelCredentialSchemaValidator @@ -284,8 +283,6 @@ def get_model_type_instance(self, provider: str, model_type: ModelType) -> AIMod return ModerationModel(**init_params) elif model_type == ModelType.TTS: return TTSModel(**init_params) - elif model_type == ModelType.TEXT2IMG: - return Text2ImageModel(**init_params) def get_provider_icon(self, provider: str, icon_type: str, lang: str) -> bytes: """ diff --git a/api/core/model_runtime/model_providers/nomic/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/nomic/text_embedding/text_embedding.py deleted file mode 100644 index 857dfb5f41e2f5..00000000000000 --- a/api/core/model_runtime/model_providers/nomic/text_embedding/text_embedding.py +++ /dev/null @@ -1,165 +0,0 @@ -import time -from functools import wraps -from typing import Optional - -from nomic import embed -from nomic import login as nomic_login - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import ( - EmbeddingUsage, - TextEmbeddingResult, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import ( - TextEmbeddingModel, -) -from core.model_runtime.model_providers.nomic._common import _CommonNomic - - -def nomic_login_required(func): - @wraps(func) - def wrapper(*args, **kwargs): - try: - if not kwargs.get("credentials"): - raise ValueError("missing credentials parameters") - credentials = kwargs.get("credentials") - if "nomic_api_key" not in credentials: - raise ValueError("missing nomic_api_key in credentials parameters") - # nomic login - nomic_login(credentials["nomic_api_key"]) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - return func(*args, **kwargs) - - return wrapper - - -class NomicTextEmbeddingModel(_CommonNomic, TextEmbeddingModel): - """ - Model class for nomic text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - embeddings, prompt_tokens, total_tokens = self.embed_text( - model=model, - credentials=credentials, - texts=texts, - ) - - # calc usage - usage = self._calc_response_usage( - model=model, credentials=credentials, tokens=prompt_tokens, total_tokens=total_tokens - ) - return TextEmbeddingResult(embeddings=embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - return sum(self._get_num_tokens_by_gpt2(text) for text in texts) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # call embedding model - self.embed_text(model=model, credentials=credentials, texts=["ping"]) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @nomic_login_required - def embed_text(self, model: str, credentials: dict, texts: list[str]) -> tuple[list[list[float]], int, int]: - """Call out to Nomic's embedding endpoint. - - Args: - model: The model to use for embedding. - texts: The list of texts to embed. - - Returns: - List of embeddings, one for each text, and tokens usage. - """ - embeddings: list[list[float]] = [] - prompt_tokens = 0 - total_tokens = 0 - - response = embed.text( - model=model, - texts=texts, - ) - - if not (response and "embeddings" in response): - raise ValueError("Embedding data is missing in the response.") - - if not (response and "usage" in response): - raise ValueError("Response usage is missing.") - - if "prompt_tokens" not in response["usage"]: - raise ValueError("Response usage does not contain prompt tokens.") - - if "total_tokens" not in response["usage"]: - raise ValueError("Response usage does not contain total tokens.") - - embeddings = [list(map(float, e)) for e in response["embeddings"]] - total_tokens = response["usage"]["total_tokens"] - prompt_tokens = response["usage"]["prompt_tokens"] - return embeddings, prompt_tokens, total_tokens - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int, total_tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: prompt tokens - :param total_tokens: total tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, - credentials=credentials, - price_type=PriceType.INPUT, - tokens=tokens, - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=total_tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/nvidia/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/nvidia/text_embedding/text_embedding.py deleted file mode 100644 index 936ceb8dd2c60e..00000000000000 --- a/api/core/model_runtime/model_providers/nvidia/text_embedding/text_embedding.py +++ /dev/null @@ -1,158 +0,0 @@ -import time -from json import JSONDecodeError, dumps -from typing import Optional - -from requests import post - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - - -class NvidiaTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for Nvidia text embedding model. - """ - - api_base: str = "https://ai.api.nvidia.com/v1/retrieval/nvidia/embeddings" - models: list[str] = ["NV-Embed-QA"] - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - api_key = credentials["api_key"] - if model not in self.models: - raise InvokeBadRequestError("Invalid model name") - if not api_key: - raise CredentialsValidateFailedError("api_key is required") - url = self.api_base - headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"} - - data = {"model": model, "input": texts[0], "input_type": "query"} - - try: - response = post(url, headers=headers, data=dumps(data)) - except Exception as e: - raise InvokeConnectionError(str(e)) - - if response.status_code != 200: - try: - resp = response.json() - msg = resp["detail"] - if response.status_code == 401: - raise InvokeAuthorizationError(msg) - elif response.status_code == 429: - raise InvokeRateLimitError(msg) - elif response.status_code == 500: - raise InvokeServerUnavailableError(msg) - else: - raise InvokeError(msg) - except JSONDecodeError as e: - raise InvokeServerUnavailableError( - f"Failed to convert response to json: {e} with text: {response.text}" - ) - - try: - resp = response.json() - embeddings = resp["data"] - usage = resp["usage"] - except Exception as e: - raise InvokeServerUnavailableError(f"Failed to convert response to json: {e} with text: {response.text}") - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=usage["total_tokens"]) - - result = TextEmbeddingResult( - model=model, embeddings=[[float(data) for data in x["embedding"]] for x in embeddings], usage=usage - ) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - for text in texts: - # use JinaTokenizer to get num tokens - num_tokens += self._get_num_tokens_by_gpt2(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except InvokeAuthorizationError: - raise CredentialsValidateFailedError("Invalid api key") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/oci/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/oci/text_embedding/text_embedding.py deleted file mode 100644 index 4de9296ccaa92d..00000000000000 --- a/api/core/model_runtime/model_providers/oci/text_embedding/text_embedding.py +++ /dev/null @@ -1,224 +0,0 @@ -import base64 -import copy -import time -from typing import Optional - -import numpy as np -import oci - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - -request_template = { - "compartmentId": "", - "servingMode": {"modelId": "cohere.embed-english-light-v3.0", "servingType": "ON_DEMAND"}, - "truncate": "NONE", - "inputs": [""], -} -oci_config_template = { - "user": "", - "fingerprint": "", - "tenancy": "", - "region": "", - "compartment_id": "", - "key_content": "", -} - - -class OCITextEmbeddingModel(TextEmbeddingModel): - """ - Model class for Cohere text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - # get model properties - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - - inputs = [] - indices = [] - used_tokens = 0 - - for i, text in enumerate(texts): - # Here token count is only an approximation based on the GPT2 tokenizer - num_tokens = self._get_num_tokens_by_gpt2(text) - - if num_tokens >= context_size: - cutoff = int(len(text) * (np.floor(context_size / num_tokens))) - # if num tokens is larger than context length, only use the start - inputs.append(text[0:cutoff]) - else: - inputs.append(text) - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(inputs), max_chunks) - - for i in _iter: - # call embedding model - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, credentials=credentials, texts=inputs[i : i + max_chunks] - ) - - used_tokens += embedding_used_tokens - batched_embeddings += embeddings_batch - - # calc usage - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - - return TextEmbeddingResult(embeddings=batched_embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - return sum(self._get_num_tokens_by_gpt2(text) for text in texts) - - def get_num_characters(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - characters = 0 - for text in texts: - characters += len(text) - return characters - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # call embedding model - self._embedding_invoke(model=model, credentials=credentials, texts=["ping"]) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _embedding_invoke(self, model: str, credentials: dict, texts: list[str]) -> tuple[list[list[float]], int]: - """ - Invoke embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: embeddings and used tokens - """ - - # oci - # initialize client - oci_config = copy.deepcopy(oci_config_template) - if "oci_config_content" in credentials: - oci_config_content = base64.b64decode(credentials.get("oci_config_content")).decode("utf-8") - config_items = oci_config_content.split("/") - if len(config_items) != 5: - raise CredentialsValidateFailedError( - "oci_config_content should be base64.b64encode(" - "'user_ocid/fingerprint/tenancy_ocid/region/compartment_ocid'.encode('utf-8'))" - ) - oci_config["user"] = config_items[0] - oci_config["fingerprint"] = config_items[1] - oci_config["tenancy"] = config_items[2] - oci_config["region"] = config_items[3] - oci_config["compartment_id"] = config_items[4] - else: - raise CredentialsValidateFailedError("need to set oci_config_content in credentials ") - if "oci_key_content" in credentials: - oci_key_content = base64.b64decode(credentials.get("oci_key_content")).decode("utf-8") - oci_config["key_content"] = oci_key_content.encode(encoding="utf-8") - else: - raise CredentialsValidateFailedError("need to set oci_config_content in credentials ") - # oci_config = oci.config.from_file('~/.oci/config', credentials.get('oci_api_profile')) - compartment_id = oci_config["compartment_id"] - client = oci.generative_ai_inference.GenerativeAiInferenceClient(config=oci_config) - # call embedding model - request_args = copy.deepcopy(request_template) - request_args["compartmentId"] = compartment_id - request_args["servingMode"]["modelId"] = model - request_args["inputs"] = texts - response = client.embed_text(request_args) - return response.data.embeddings, self.get_num_characters(model=model, credentials=credentials, texts=texts) - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError], - } diff --git a/api/core/model_runtime/model_providers/ollama/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/ollama/text_embedding/text_embedding.py deleted file mode 100644 index 5cf3f1c6fa87f3..00000000000000 --- a/api/core/model_runtime/model_providers/ollama/text_embedding/text_embedding.py +++ /dev/null @@ -1,211 +0,0 @@ -import json -import logging -import time -from decimal import Decimal -from typing import Optional -from urllib.parse import urljoin - -import numpy as np -import requests - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - PriceConfig, - PriceType, -) -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - -logger = logging.getLogger(__name__) - - -class OllamaEmbeddingModel(TextEmbeddingModel): - """ - Model class for an Ollama text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - - # Prepare headers and payload for the request - headers = {"Content-Type": "application/json"} - - endpoint_url = credentials.get("base_url") - if not endpoint_url.endswith("/"): - endpoint_url += "/" - - endpoint_url = urljoin(endpoint_url, "api/embed") - - # get model properties - context_size = self._get_context_size(model, credentials) - - inputs = [] - used_tokens = 0 - - for text in texts: - # Here token count is only an approximation based on the GPT2 tokenizer - num_tokens = self._get_num_tokens_by_gpt2(text) - - if num_tokens >= context_size: - cutoff = int(np.floor(len(text) * (context_size / num_tokens))) - # if num tokens is larger than context length, only use the start - inputs.append(text[0:cutoff]) - else: - inputs.append(text) - - # Prepare the payload for the request - payload = {"input": inputs, "model": model, "options": {"use_mmap": True}} - - # Make the request to the Ollama API - response = requests.post(endpoint_url, headers=headers, data=json.dumps(payload), timeout=(10, 300)) - - response.raise_for_status() # Raise an exception for HTTP errors - response_data = response.json() - - # Extract embeddings and used tokens from the response - embeddings = response_data["embeddings"] - embedding_used_tokens = self.get_num_tokens(model, credentials, inputs) - - used_tokens += embedding_used_tokens - - # calc usage - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - - return TextEmbeddingResult(embeddings=embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Approximate number of tokens for given messages using GPT2 tokenizer - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - return sum(self._get_num_tokens_by_gpt2(text) for text in texts) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except InvokeError as ex: - raise CredentialsValidateFailedError(f"An error occurred during credentials validation: {ex.description}") - except Exception as ex: - raise CredentialsValidateFailedError(f"An error occurred during credentials validation: {str(ex)}") - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.TEXT_EMBEDDING, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size")), - ModelPropertyKey.MAX_CHUNKS: 1, - }, - parameter_rules=[], - pricing=PriceConfig( - input=Decimal(credentials.get("input_price", 0)), - unit=Decimal(credentials.get("unit", 0)), - currency=credentials.get("currency", "USD"), - ), - ) - - return entity - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeAuthorizationError: [ - requests.exceptions.InvalidHeader, # Missing or Invalid API Key - ], - InvokeBadRequestError: [ - requests.exceptions.HTTPError, # Invalid Endpoint URL or model name - requests.exceptions.InvalidURL, # Misconfigured request or other API error - ], - InvokeRateLimitError: [ - requests.exceptions.RetryError # Too many requests sent in a short period of time - ], - InvokeServerUnavailableError: [ - requests.exceptions.ConnectionError, # Engine Overloaded - requests.exceptions.HTTPError, # Server Error - ], - InvokeConnectionError: [ - requests.exceptions.ConnectTimeout, # Timeout - requests.exceptions.ReadTimeout, # Timeout - ], - } diff --git a/api/core/model_runtime/model_providers/openai/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/openai/text_embedding/text_embedding.py deleted file mode 100644 index 16f1a0cfa1117b..00000000000000 --- a/api/core/model_runtime/model_providers/openai/text_embedding/text_embedding.py +++ /dev/null @@ -1,203 +0,0 @@ -import base64 -import time -from typing import Optional, Union - -import numpy as np -import tiktoken -from openai import OpenAI - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.openai._common import _CommonOpenAI - - -class OpenAITextEmbeddingModel(_CommonOpenAI, TextEmbeddingModel): - """ - Model class for OpenAI text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - # init model client - client = OpenAI(**credentials_kwargs) - - extra_model_kwargs = {} - if user: - extra_model_kwargs["user"] = user - - extra_model_kwargs["encoding_format"] = "base64" - - # get model properties - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - - embeddings: list[list[float]] = [[] for _ in range(len(texts))] - tokens = [] - indices = [] - used_tokens = 0 - - try: - enc = tiktoken.encoding_for_model(model) - except KeyError: - enc = tiktoken.get_encoding("cl100k_base") - - for i, text in enumerate(texts): - token = enc.encode(text) - for j in range(0, len(token), context_size): - tokens += [token[j : j + context_size]] - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(tokens), max_chunks) - - for i in _iter: - # call embedding model - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, client=client, texts=tokens[i : i + max_chunks], extra_model_kwargs=extra_model_kwargs - ) - - used_tokens += embedding_used_tokens - batched_embeddings += embeddings_batch - - results: list[list[list[float]]] = [[] for _ in range(len(texts))] - num_tokens_in_batch: list[list[int]] = [[] for _ in range(len(texts))] - for i in range(len(indices)): - results[indices[i]].append(batched_embeddings[i]) - num_tokens_in_batch[indices[i]].append(len(tokens[i])) - - for i in range(len(texts)): - _result = results[i] - if len(_result) == 0: - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, client=client, texts="", extra_model_kwargs=extra_model_kwargs - ) - - used_tokens += embedding_used_tokens - average = embeddings_batch[0] - else: - average = np.average(_result, axis=0, weights=num_tokens_in_batch[i]) - embeddings[i] = (average / np.linalg.norm(average)).tolist() - - # calc usage - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - - return TextEmbeddingResult(embeddings=embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - if len(texts) == 0: - return 0 - - try: - enc = tiktoken.encoding_for_model(model) - except KeyError: - enc = tiktoken.get_encoding("cl100k_base") - - total_num_tokens = 0 - for text in texts: - # calculate the number of tokens in the encoded text - tokenized_text = enc.encode(text) - total_num_tokens += len(tokenized_text) - - return total_num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - # call embedding model - self._embedding_invoke(model=model, client=client, texts=["ping"], extra_model_kwargs={}) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _embedding_invoke( - self, model: str, client: OpenAI, texts: Union[list[str], str], extra_model_kwargs: dict - ) -> tuple[list[list[float]], int]: - """ - Invoke embedding model - - :param model: model name - :param client: model client - :param texts: texts to embed - :param extra_model_kwargs: extra model kwargs - :return: embeddings and used tokens - """ - # call embedding model - response = client.embeddings.create( - input=texts, - model=model, - **extra_model_kwargs, - ) - - if "encoding_format" in extra_model_kwargs and extra_model_kwargs["encoding_format"] == "base64": - # decode base64 embedding - return ( - [list(np.frombuffer(base64.b64decode(data.embedding), dtype="float32")) for data in response.data], - response.usage.total_tokens, - ) - - return [data.embedding for data in response.data], response.usage.total_tokens - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/openai_api_compatible/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/openai_api_compatible/text_embedding/text_embedding.py deleted file mode 100644 index 64fa6aaa3c5a71..00000000000000 --- a/api/core/model_runtime/model_providers/openai_api_compatible/text_embedding/text_embedding.py +++ /dev/null @@ -1,217 +0,0 @@ -import json -import time -from decimal import Decimal -from typing import Optional -from urllib.parse import urljoin - -import numpy as np -import requests - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - PriceConfig, - PriceType, -) -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.openai_api_compatible._common import _CommonOaiApiCompat - - -class OAICompatEmbeddingModel(_CommonOaiApiCompat, TextEmbeddingModel): - """ - Model class for an OpenAI API-compatible text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - - # Prepare headers and payload for the request - headers = {"Content-Type": "application/json"} - - api_key = credentials.get("api_key") - if api_key: - headers["Authorization"] = f"Bearer {api_key}" - - endpoint_url = credentials.get("endpoint_url") - if not endpoint_url.endswith("/"): - endpoint_url += "/" - - endpoint_url = urljoin(endpoint_url, "embeddings") - - extra_model_kwargs = {} - if user: - extra_model_kwargs["user"] = user - - extra_model_kwargs["encoding_format"] = "float" - - # get model properties - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - - inputs = [] - indices = [] - used_tokens = 0 - - for i, text in enumerate(texts): - # Here token count is only an approximation based on the GPT2 tokenizer - # TODO: Optimize for better token estimation and chunking - num_tokens = self._get_num_tokens_by_gpt2(text) - - if num_tokens >= context_size: - cutoff = int(np.floor(len(text) * (context_size / num_tokens))) - # if num tokens is larger than context length, only use the start - inputs.append(text[0:cutoff]) - else: - inputs.append(text) - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(inputs), max_chunks) - - for i in _iter: - # Prepare the payload for the request - payload = {"input": inputs[i : i + max_chunks], "model": model, **extra_model_kwargs} - - # Make the request to the OpenAI API - response = requests.post(endpoint_url, headers=headers, data=json.dumps(payload), timeout=(10, 300)) - - response.raise_for_status() # Raise an exception for HTTP errors - response_data = response.json() - - # Extract embeddings and used tokens from the response - embeddings_batch = [data["embedding"] for data in response_data["data"]] - embedding_used_tokens = response_data["usage"]["total_tokens"] - - used_tokens += embedding_used_tokens - batched_embeddings += embeddings_batch - - # calc usage - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - - return TextEmbeddingResult(embeddings=batched_embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Approximate number of tokens for given messages using GPT2 tokenizer - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - return sum(self._get_num_tokens_by_gpt2(text) for text in texts) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - headers = {"Content-Type": "application/json"} - - api_key = credentials.get("api_key") - - if api_key: - headers["Authorization"] = f"Bearer {api_key}" - - endpoint_url = credentials.get("endpoint_url") - if not endpoint_url.endswith("/"): - endpoint_url += "/" - - endpoint_url = urljoin(endpoint_url, "embeddings") - - payload = {"input": "ping", "model": model} - - response = requests.post(url=endpoint_url, headers=headers, data=json.dumps(payload), timeout=(10, 300)) - - if response.status_code != 200: - raise CredentialsValidateFailedError( - f"Credentials validation failed with status code {response.status_code}" - ) - - try: - json_result = response.json() - except json.JSONDecodeError as e: - raise CredentialsValidateFailedError("Credentials validation failed: JSON decode error") - - if "model" not in json_result: - raise CredentialsValidateFailedError("Credentials validation failed: invalid response") - except CredentialsValidateFailedError: - raise - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.TEXT_EMBEDDING, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size")), - ModelPropertyKey.MAX_CHUNKS: 1, - }, - parameter_rules=[], - pricing=PriceConfig( - input=Decimal(credentials.get("input_price", 0)), - unit=Decimal(credentials.get("unit", 0)), - currency=credentials.get("currency", "USD"), - ), - ) - - return entity - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/openllm/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/openllm/text_embedding/text_embedding.py deleted file mode 100644 index c5d43309127822..00000000000000 --- a/api/core/model_runtime/model_providers/openllm/text_embedding/text_embedding.py +++ /dev/null @@ -1,155 +0,0 @@ -import time -from json import dumps -from typing import Optional - -from requests import post -from requests.exceptions import ConnectionError, InvalidSchema, MissingSchema - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - - -class OpenLLMTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for OpenLLM text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - server_url = credentials["server_url"] - if not server_url: - raise CredentialsValidateFailedError("server_url is required") - - headers = {"Content-Type": "application/json", "accept": "application/json"} - - url = f"{server_url}/v1/embeddings" - - data = texts - try: - response = post(url, headers=headers, data=dumps(data)) - except (ConnectionError, InvalidSchema, MissingSchema) as e: - # cloud not connect to the server - raise InvokeAuthorizationError(f"Invalid server URL: {e}") - except Exception as e: - raise InvokeConnectionError(str(e)) - - if response.status_code != 200: - if response.status_code == 400: - raise InvokeBadRequestError(response.text) - elif response.status_code == 404: - raise InvokeAuthorizationError(response.text) - elif response.status_code == 500: - raise InvokeServerUnavailableError(response.text) - - try: - resp = response.json()[0] - embeddings = resp["embeddings"] - total_tokens = resp["num_tokens"] - except KeyError as e: - raise InvokeServerUnavailableError(f"Failed to convert response to json: {e} with text: {response.text}") - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=total_tokens) - - result = TextEmbeddingResult(model=model, embeddings=embeddings, usage=usage) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - for text in texts: - # use GPT2Tokenizer to get num tokens - num_tokens += self._get_num_tokens_by_gpt2(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except InvokeAuthorizationError: - raise CredentialsValidateFailedError("Invalid server_url") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/replicate/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/replicate/text_embedding/text_embedding.py deleted file mode 100644 index 9f724a77ac040b..00000000000000 --- a/api/core/model_runtime/model_providers/replicate/text_embedding/text_embedding.py +++ /dev/null @@ -1,152 +0,0 @@ -import json -import time -from typing import Optional - -from replicate import Client as ReplicateClient - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.replicate._common import _CommonReplicate - - -class ReplicateEmbeddingModel(_CommonReplicate, TextEmbeddingModel): - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - client = ReplicateClient(api_token=credentials["replicate_api_token"], timeout=30) - - if "model_version" in credentials: - model_version = credentials["model_version"] - else: - model_info = client.models.get(model) - model_version = model_info.latest_version.id - - replicate_model_version = f"{model}:{model_version}" - - text_input_key = self._get_text_input_key(model, model_version, client) - - embeddings = self._generate_embeddings_by_text_input_key(client, replicate_model_version, text_input_key, texts) - - tokens = self.get_num_tokens(model, credentials, texts) - usage = self._calc_response_usage(model, credentials, tokens) - - return TextEmbeddingResult(model=model, embeddings=embeddings, usage=usage) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - num_tokens = 0 - for text in texts: - num_tokens += self._get_num_tokens_by_gpt2(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - if "replicate_api_token" not in credentials: - raise CredentialsValidateFailedError("Replicate Access Token must be provided.") - - try: - client = ReplicateClient(api_token=credentials["replicate_api_token"], timeout=30) - - if "model_version" in credentials: - model_version = credentials["model_version"] - else: - model_info = client.models.get(model) - model_version = model_info.latest_version.id - - replicate_model_version = f"{model}:{model_version}" - - text_input_key = self._get_text_input_key(model, model_version, client) - - self._generate_embeddings_by_text_input_key( - client, replicate_model_version, text_input_key, ["Hello worlds!"] - ) - except Exception as e: - raise CredentialsValidateFailedError(str(e)) - - def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]: - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TEXT_EMBEDDING, - model_properties={"context_size": 4096, "max_chunks": 1}, - ) - return entity - - @staticmethod - def _get_text_input_key(model: str, model_version: str, client: ReplicateClient) -> str: - model_info = client.models.get(model) - model_info_version = model_info.versions.get(model_version) - - # sort through the openapi schema to get the name of text, texts or inputs - input_properties = sorted( - model_info_version.openapi_schema["components"]["schemas"]["Input"]["properties"].items(), - key=lambda item: item[1].get("x-order", 0), - ) - - for input_property in input_properties: - if input_property[0] in {"text", "texts", "inputs"}: - text_input_key = input_property[0] - return text_input_key - - return "" - - @staticmethod - def _generate_embeddings_by_text_input_key( - client: ReplicateClient, replicate_model_version: str, text_input_key: str, texts: list[str] - ) -> list[list[float]]: - if text_input_key in {"text", "inputs"}: - embeddings = [] - for text in texts: - result = client.run(replicate_model_version, input={text_input_key: text}) - embeddings.append(result[0].get("embedding")) - - return [list(map(float, e)) for e in embeddings] - elif "texts" == text_input_key: - result = client.run( - replicate_model_version, - input={ - "texts": json.dumps(texts), - "batch_size": 4, - "convert_to_numpy": False, - "normalize_embeddings": True, - }, - ) - return result - else: - raise ValueError(f"embeddings input key is invalid: {text_input_key}") - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/sagemaker/llm/llm.py b/api/core/model_runtime/model_providers/sagemaker/llm/llm.py deleted file mode 100644 index 97b76920443840..00000000000000 --- a/api/core/model_runtime/model_providers/sagemaker/llm/llm.py +++ /dev/null @@ -1,463 +0,0 @@ -import json -import logging -import re -from collections.abc import Generator, Iterator -from typing import Any, Optional, Union, cast - -# from openai.types.chat import ChatCompletion, ChatCompletionChunk -import boto3 -from sagemaker import Predictor, serializers -from sagemaker.session import Session - -from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContent, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - I18nObject, - ModelFeature, - ModelPropertyKey, - ModelType, - ParameterRule, - ParameterType, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -logger = logging.getLogger(__name__) - - -def inference(predictor, messages: list[dict[str, Any]], params: dict[str, Any], stop: list, stream=False): - """ - params: - predictor : Sagemaker Predictor - messages (List[Dict[str,Any]]): message list。 - messages = [ - {"role": "system", "content":"please answer in Chinese"}, - {"role": "user", "content": "who are you? what are you doing?"}, - ] - params (Dict[str,Any]): model parameters for LLM。 - stream (bool): False by default。 - - response: - result of inference if stream is False - Iterator of Chunks if stream is True - """ - payload = { - "model": params.get("model_name"), - "stop": stop, - "messages": messages, - "stream": stream, - "max_tokens": params.get("max_new_tokens", params.get("max_tokens", 2048)), - "temperature": params.get("temperature", 0.1), - "top_p": params.get("top_p", 0.9), - } - - if not stream: - response = predictor.predict(payload) - return response - else: - response_stream = predictor.predict_stream(payload) - return response_stream - - -class SageMakerLargeLanguageModel(LargeLanguageModel): - """ - Model class for Cohere large language model. - """ - - sagemaker_session: Any = None - predictor: Any = None - sagemaker_endpoint: str = None - - def _handle_chat_generate_response( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool], - resp: bytes, - ) -> LLMResult: - """ - handle normal chat generate response - """ - resp_obj = json.loads(resp.decode("utf-8")) - resp_str = resp_obj.get("choices")[0].get("message").get("content") - - if len(resp_str) == 0: - raise InvokeServerUnavailableError("Empty response") - - assistant_prompt_message = AssistantPromptMessage(content=resp_str, tool_calls=[]) - - prompt_tokens = self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - completion_tokens = self._num_tokens_from_messages(messages=[assistant_prompt_message], tools=tools) - - usage = self._calc_response_usage( - model=model, credentials=credentials, prompt_tokens=prompt_tokens, completion_tokens=completion_tokens - ) - - response = LLMResult( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=None, - usage=usage, - message=assistant_prompt_message, - ) - - return response - - def _handle_chat_stream_response( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: list[PromptMessageTool], - resp: Iterator[bytes], - ) -> Generator: - """ - handle stream chat generate response - """ - full_response = "" - buffer = "" - for chunk_bytes in resp: - buffer += chunk_bytes.decode("utf-8") - last_idx = 0 - for match in re.finditer(r"^data:\s*(.+?)(\n\n)", buffer): - try: - data = json.loads(match.group(1).strip()) - last_idx = match.span()[1] - - if "content" in data["choices"][0]["delta"]: - chunk_content = data["choices"][0]["delta"]["content"] - assistant_prompt_message = AssistantPromptMessage(content=chunk_content, tool_calls=[]) - - if data["choices"][0]["finish_reason"] is not None: - temp_assistant_prompt_message = AssistantPromptMessage(content=full_response, tool_calls=[]) - prompt_tokens = self._num_tokens_from_messages(messages=prompt_messages, tools=tools) - completion_tokens = self._num_tokens_from_messages( - messages=[temp_assistant_prompt_message], tools=[] - ) - usage = self._calc_response_usage( - model=model, - credentials=credentials, - prompt_tokens=prompt_tokens, - completion_tokens=completion_tokens, - ) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=None, - delta=LLMResultChunkDelta( - index=0, - message=assistant_prompt_message, - finish_reason=data["choices"][0]["finish_reason"], - usage=usage, - ), - ) - else: - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - system_fingerprint=None, - delta=LLMResultChunkDelta(index=0, message=assistant_prompt_message), - ) - - full_response += chunk_content - except (json.JSONDecodeError, KeyError, IndexError) as e: - logger.info("json parse exception, content: {}".format(match.group(1).strip())) - pass - - buffer = buffer[last_idx:] - - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - if not self.sagemaker_session: - access_key = credentials.get("aws_access_key_id") - secret_key = credentials.get("aws_secret_access_key") - aws_region = credentials.get("aws_region") - boto_session = None - if aws_region: - if access_key and secret_key: - boto_session = boto3.Session( - aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name=aws_region - ) - else: - boto_session = boto3.Session(region_name=aws_region) - else: - boto_session = boto3.Session() - - sagemaker_client = boto_session.client("sagemaker") - self.sagemaker_session = Session(boto_session=boto_session, sagemaker_client=sagemaker_client) - - if self.sagemaker_endpoint != credentials.get("sagemaker_endpoint"): - self.sagemaker_endpoint = credentials.get("sagemaker_endpoint") - self.predictor = Predictor( - endpoint_name=self.sagemaker_endpoint, - sagemaker_session=self.sagemaker_session, - serializer=serializers.JSONSerializer(), - ) - - messages: list[dict[str, Any]] = [{"role": p.role.value, "content": p.content} for p in prompt_messages] - response = inference( - predictor=self.predictor, messages=messages, params=model_parameters, stop=stop, stream=stream - ) - - if stream: - if tools and len(tools) > 0: - raise InvokeBadRequestError(f"{model}'s tool calls does not support stream mode") - - return self._handle_chat_stream_response( - model=model, credentials=credentials, prompt_messages=prompt_messages, tools=tools, resp=response - ) - return self._handle_chat_generate_response( - model=model, credentials=credentials, prompt_messages=prompt_messages, tools=tools, resp=response - ) - - def _convert_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict for OpenAI Compatibility API - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(PromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - sub_message_dict = { - "type": "image_url", - "image_url": {"url": message_content.data, "detail": message_content.detail.value}, - } - sub_messages.append(sub_message_dict) - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - if message.tool_calls and len(message.tool_calls) > 0: - message_dict["function_call"] = { - "name": message.tool_calls[0].function.name, - "arguments": message.tool_calls[0].function.arguments, - } - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - elif isinstance(message, ToolPromptMessage): - message = cast(ToolPromptMessage, message) - message_dict = {"tool_call_id": message.tool_call_id, "role": "tool", "content": message.content} - else: - raise ValueError(f"Unknown message type {type(message)}") - - return message_dict - - def _num_tokens_from_messages( - self, messages: list[PromptMessage], tools: list[PromptMessageTool], is_completion_model: bool = False - ) -> int: - def tokens(text: str): - return self._get_num_tokens_by_gpt2(text) - - if is_completion_model: - return sum(tokens(str(message.content)) for message in messages) - - tokens_per_message = 3 - tokens_per_name = 1 - - num_tokens = 0 - messages_dict = [self._convert_prompt_message_to_dict(m) for m in messages] - for message in messages_dict: - num_tokens += tokens_per_message - for key, value in message.items(): - if isinstance(value, list): - text = "" - for item in value: - if isinstance(item, dict) and item["type"] == "text": - text += item["text"] - - value = text - - if key == "tool_calls": - for tool_call in value: - for t_key, t_value in tool_call.items(): - num_tokens += tokens(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += tokens(f_key) - num_tokens += tokens(f_value) - else: - num_tokens += tokens(t_key) - num_tokens += tokens(t_value) - if key == "function_call": - for t_key, t_value in value.items(): - num_tokens += tokens(t_key) - if t_key == "function": - for f_key, f_value in t_value.items(): - num_tokens += tokens(f_key) - num_tokens += tokens(f_value) - else: - num_tokens += tokens(t_key) - num_tokens += tokens(t_value) - else: - num_tokens += tokens(str(value)) - - if key == "name": - num_tokens += tokens_per_name - num_tokens += 3 - - if tools: - num_tokens += self._num_tokens_for_tools(tools) - - return num_tokens - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - # get model mode - try: - return self._num_tokens_from_messages(prompt_messages, tools) - except Exception as e: - raise self._transform_invoke_error(e) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # get model mode - pass - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - rules = [ - ParameterRule( - name="temperature", - type=ParameterType.FLOAT, - use_template="temperature", - label=I18nObject(zh_Hans="温度", en_US="Temperature"), - ), - ParameterRule( - name="top_p", - type=ParameterType.FLOAT, - use_template="top_p", - label=I18nObject(zh_Hans="Top P", en_US="Top P"), - ), - ParameterRule( - name="max_tokens", - type=ParameterType.INT, - use_template="max_tokens", - min=1, - max=credentials.get("context_length", 2048), - default=512, - label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"), - ), - ] - - completion_type = LLMMode.value_of(credentials["mode"]).value - - features = [] - - support_function_call = credentials.get("support_function_call", False) - if support_function_call: - features.append(ModelFeature.TOOL_CALL) - - support_vision = credentials.get("support_vision", False) - if support_vision: - features.append(ModelFeature.VISION) - - context_length = credentials.get("context_length", 2048) - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.LLM, - features=features, - model_properties={ModelPropertyKey.MODE: completion_type, ModelPropertyKey.CONTEXT_SIZE: context_length}, - parameter_rules=rules, - ) - - return entity diff --git a/api/core/model_runtime/model_providers/sagemaker/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/sagemaker/text_embedding/text_embedding.py deleted file mode 100644 index 8f993ce6722522..00000000000000 --- a/api/core/model_runtime/model_providers/sagemaker/text_embedding/text_embedding.py +++ /dev/null @@ -1,200 +0,0 @@ -import itertools -import json -import logging -import time -from typing import Any, Optional - -import boto3 - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel - -BATCH_SIZE = 20 -CONTEXT_SIZE = 8192 - -logger = logging.getLogger(__name__) - - -def batch_generator(generator, batch_size): - while True: - batch = list(itertools.islice(generator, batch_size)) - if not batch: - break - yield batch - - -class SageMakerEmbeddingModel(TextEmbeddingModel): - """ - Model class for Cohere text embedding model. - """ - - sagemaker_client: Any = None - - def _sagemaker_embedding(self, sm_client, endpoint_name, content_list: list[str]): - response_model = sm_client.invoke_endpoint( - EndpointName=endpoint_name, - Body=json.dumps({"inputs": content_list, "parameters": {}, "is_query": False, "instruction": ""}), - ContentType="application/json", - ) - json_str = response_model["Body"].read().decode("utf8") - json_obj = json.loads(json_str) - embeddings = json_obj["embeddings"] - return embeddings - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - # get model properties - try: - line = 1 - if not self.sagemaker_client: - access_key = credentials.get("aws_access_key_id") - secret_key = credentials.get("aws_secret_access_key") - aws_region = credentials.get("aws_region") - if aws_region: - if access_key and secret_key: - self.sagemaker_client = boto3.client( - "sagemaker-runtime", - aws_access_key_id=access_key, - aws_secret_access_key=secret_key, - region_name=aws_region, - ) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime", region_name=aws_region) - else: - self.sagemaker_client = boto3.client("sagemaker-runtime") - - line = 2 - sagemaker_endpoint = credentials.get("sagemaker_endpoint") - - line = 3 - truncated_texts = [item[:CONTEXT_SIZE] for item in texts] - - batches = batch_generator((text for text in truncated_texts), batch_size=BATCH_SIZE) - all_embeddings = [] - - line = 4 - for batch in batches: - embeddings = self._sagemaker_embedding(self.sagemaker_client, sagemaker_endpoint, batch) - all_embeddings.extend(embeddings) - - line = 5 - # calc usage - usage = self._calc_response_usage( - model=model, - credentials=credentials, - tokens=0, # It's not SAAS API, usage is meaningless - ) - line = 6 - - return TextEmbeddingResult(embeddings=all_embeddings, usage=usage, model=model) - - except Exception as e: - logger.exception(f"Exception {e}, line : {line}") - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - return 0 - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - print("validate_credentials ok....") - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError], - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TEXT_EMBEDDING, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: CONTEXT_SIZE, - ModelPropertyKey.MAX_CHUNKS: BATCH_SIZE, - }, - parameter_rules=[], - ) - - return entity diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml deleted file mode 100644 index 8d1df82140b79f..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml +++ /dev/null @@ -1,28 +0,0 @@ -- Qwen/Qwen2.5-72B-Instruct -- Qwen/Qwen2.5-32B-Instruct -- Qwen/Qwen2.5-14B-Instruct -- Qwen/Qwen2.5-7B-Instruct -- Qwen/Qwen2.5-Coder-7B-Instruct -- Qwen/Qwen2.5-Math-72B-Instruct -- Qwen/Qwen2-72B-Instruct -- Qwen/Qwen2-57B-A14B-Instruct -- Qwen/Qwen2-7B-Instruct -- Qwen/Qwen2-1.5B-Instruct -- deepseek-ai/DeepSeek-V2.5 -- deepseek-ai/DeepSeek-V2-Chat -- deepseek-ai/DeepSeek-Coder-V2-Instruct -- THUDM/glm-4-9b-chat -- 01-ai/Yi-1.5-34B-Chat-16K -- 01-ai/Yi-1.5-9B-Chat-16K -- 01-ai/Yi-1.5-6B-Chat -- internlm/internlm2_5-20b-chat -- internlm/internlm2_5-7b-chat -- meta-llama/Meta-Llama-3.1-405B-Instruct -- meta-llama/Meta-Llama-3.1-70B-Instruct -- meta-llama/Meta-Llama-3.1-8B-Instruct -- meta-llama/Meta-Llama-3-70B-Instruct -- meta-llama/Meta-Llama-3-8B-Instruct -- google/gemma-2-27b-it -- google/gemma-2-9b-it -- mistralai/Mistral-7B-Instruct-v0.2 -- mistralai/Mixtral-8x7B-Instruct-v0.1 diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-20b-chat.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-20b-chat.yaml deleted file mode 100644 index d9663582e5ca26..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-20b-chat.yaml +++ /dev/null @@ -1,30 +0,0 @@ -model: internlm/internlm2_5-20b-chat -label: - en_US: internlm/internlm2_5-20b-chat -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 32768 -parameter_rules: - - name: temperature - use_template: temperature - - name: max_tokens - use_template: max_tokens - type: int - default: 512 - min: 1 - max: 4096 - help: - zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。 - en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter. - - name: top_p - use_template: top_p - - name: frequency_penalty - use_template: frequency_penalty -pricing: - input: '1' - output: '1' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-coder-7b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-coder-7b-instruct.yaml deleted file mode 100644 index 76526200ccdccc..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-coder-7b-instruct.yaml +++ /dev/null @@ -1,74 +0,0 @@ -model: Qwen/Qwen2.5-Coder-7B-Instruct -label: - en_US: Qwen/Qwen2.5-Coder-7B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 131072 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 8192 - min: 1 - max: 8192 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '0' - output: '0' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-math-72b-instruct.yaml b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-math-72b-instruct.yaml deleted file mode 100644 index 90afa0cfd5b96a..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2.5-math-72b-instruct.yaml +++ /dev/null @@ -1,74 +0,0 @@ -model: Qwen/Qwen2.5-Math-72B-Instruct -label: - en_US: Qwen/Qwen2.5-Math-72B-Instruct -model_type: llm -features: - - agent-thought -model_properties: - mode: chat - context_size: 4096 -parameter_rules: - - name: temperature - use_template: temperature - type: float - default: 0.3 - min: 0.0 - max: 2.0 - help: - zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。 - en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain. - - name: max_tokens - use_template: max_tokens - type: int - default: 2000 - min: 1 - max: 2000 - help: - zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。 - en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time. - - name: top_p - use_template: top_p - type: float - default: 0.8 - min: 0.1 - max: 0.9 - help: - zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。 - en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated. - - name: top_k - type: int - min: 0 - max: 99 - label: - zh_Hans: 取样数量 - en_US: Top k - help: - zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。 - en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated. - - name: seed - required: false - type: int - default: 1234 - label: - zh_Hans: 随机种子 - en_US: Random seed - help: - zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。 - en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time. - - name: repetition_penalty - required: false - type: float - default: 1.1 - label: - zh_Hans: 重复惩罚 - en_US: Repetition penalty - help: - zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。 - en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment. - - name: response_format - use_template: response_format -pricing: - input: '4.13' - output: '4.13' - unit: '0.000001' - currency: RMB diff --git a/api/core/model_runtime/model_providers/siliconflow/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/siliconflow/text_embedding/text_embedding.py deleted file mode 100644 index c5dcc126107aa2..00000000000000 --- a/api/core/model_runtime/model_providers/siliconflow/text_embedding/text_embedding.py +++ /dev/null @@ -1,46 +0,0 @@ -from typing import Optional - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.model_providers.openai_api_compatible.text_embedding.text_embedding import ( - OAICompatEmbeddingModel, -) - - -class SiliconflowTextEmbeddingModel(OAICompatEmbeddingModel): - """ - Model class for Siliconflow text embedding model. - """ - - def validate_credentials(self, model: str, credentials: dict) -> None: - self._add_custom_parameters(credentials) - super().validate_credentials(model, credentials) - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - self._add_custom_parameters(credentials) - return super()._invoke(model, credentials, texts, user) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - self._add_custom_parameters(credentials) - return super().get_num_tokens(model, credentials, texts) - - @classmethod - def _add_custom_parameters(cls, credentials: dict) -> None: - credentials["endpoint_url"] = "https://api.siliconflow.cn/v1" diff --git a/api/core/model_runtime/model_providers/spark/llm/llm.py b/api/core/model_runtime/model_providers/spark/llm/llm.py deleted file mode 100644 index 1181ba699af886..00000000000000 --- a/api/core/model_runtime/model_providers/spark/llm/llm.py +++ /dev/null @@ -1,309 +0,0 @@ -import threading -from collections.abc import Generator -from typing import Optional, Union - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -from ._client import SparkLLMClient - - -class SparkLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # invoke model - return self._generate(model, credentials, prompt_messages, model_parameters, stop, stream, user) - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return: - """ - prompt = self._convert_messages_to_prompt(prompt_messages) - - return self._get_num_tokens_by_gpt2(prompt) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - self._generate( - model=model, - credentials=credentials, - prompt_messages=[ - UserPromptMessage(content="ping"), - ], - model_parameters={ - "temperature": 0.5, - }, - stream=False, - ) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - extra_model_kwargs = {} - if stop: - extra_model_kwargs["stop_sequences"] = stop - - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - client = SparkLLMClient( - model=model, - **credentials_kwargs, - ) - - thread = threading.Thread( - target=client.run, - args=( - [ - {"role": prompt_message.role.value, "content": prompt_message.content} - for prompt_message in prompt_messages - ], - user, - model_parameters, - stream, - ), - ) - thread.start() - - if stream: - return self._handle_generate_stream_response(thread, model, credentials, client, prompt_messages) - - return self._handle_generate_response(thread, model, credentials, client, prompt_messages) - - def _handle_generate_response( - self, - thread: threading.Thread, - model: str, - credentials: dict, - client: SparkLLMClient, - prompt_messages: list[PromptMessage], - ) -> LLMResult: - """ - Handle llm response - - :param model: model name - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - completion = "" - - for content in client.subscribe(): - if isinstance(content, dict): - delta = content["data"] - else: - delta = content - - completion += delta - - thread.join() - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=completion) - - # calculate num tokens - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - - return result - - def _handle_generate_stream_response( - self, - thread: threading.Thread, - model: str, - credentials: dict, - client: SparkLLMClient, - prompt_messages: list[PromptMessage], - ) -> Generator: - """ - Handle llm stream response - - :param thread: thread - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - completion = "" - for index, content in enumerate(client.subscribe()): - if isinstance(content, dict): - delta = content["data"] - else: - delta = content - completion += delta - assistant_prompt_message = AssistantPromptMessage( - content=delta or "", - ) - temp_assistant_prompt_message = AssistantPromptMessage( - content=completion, - ) - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [temp_assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message, usage=usage), - ) - - thread.join() - - def _to_credential_kwargs(self, credentials: dict) -> dict: - """ - Transform credentials to kwargs for model instance - - :param credentials: - :return: - """ - credentials_kwargs = { - "app_id": credentials["app_id"], - "api_secret": credentials["api_secret"], - "api_key": credentials["api_key"], - } - - return credentials_kwargs - - def _convert_one_message_to_text(self, message: PromptMessage) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt = "\n\nHuman:" - ai_prompt = "\n\nAssistant:" - content = message.content - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage): - message_text = content - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str: - """ - Format a list of messages into a full prompt for the Anthropic model - - :param messages: List of PromptMessage to combine. - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - # trim off the trailing ' ' that might come from the "Assistant: " - return text.rstrip() - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: [], - InvokeServerUnavailableError: [], - InvokeRateLimitError: [], - InvokeAuthorizationError: [], - InvokeBadRequestError: [], - } diff --git a/api/core/model_runtime/model_providers/tongyi/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/tongyi/text_embedding/text_embedding.py deleted file mode 100644 index 736cd44df8888f..00000000000000 --- a/api/core/model_runtime/model_providers/tongyi/text_embedding/text_embedding.py +++ /dev/null @@ -1,177 +0,0 @@ -import time -from typing import Optional - -import dashscope -import numpy as np - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import ( - EmbeddingUsage, - TextEmbeddingResult, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import ( - TextEmbeddingModel, -) -from core.model_runtime.model_providers.tongyi._common import _CommonTongyi - - -class TongyiTextEmbeddingModel(_CommonTongyi, TextEmbeddingModel): - """ - Model class for Tongyi text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - credentials_kwargs = self._to_credential_kwargs(credentials) - - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - inputs = [] - indices = [] - used_tokens = 0 - - for i, text in enumerate(texts): - # Here token count is only an approximation based on the GPT2 tokenizer - num_tokens = self._get_num_tokens_by_gpt2(text) - - if num_tokens >= context_size: - cutoff = int(np.floor(len(text) * (context_size / num_tokens))) - # if num tokens is larger than context length, only use the start - inputs.append(text[0:cutoff]) - else: - inputs.append(text) - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(inputs), max_chunks) - - for i in _iter: - embeddings_batch, embedding_used_tokens = self.embed_documents( - credentials_kwargs=credentials_kwargs, - model=model, - texts=inputs[i : i + max_chunks], - ) - used_tokens += embedding_used_tokens - batched_embeddings += embeddings_batch - - # calc usage - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - return TextEmbeddingResult(embeddings=batched_embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - if len(texts) == 0: - return 0 - total_num_tokens = 0 - for text in texts: - total_num_tokens += self._get_num_tokens_by_gpt2(text) - - return total_num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - - # call embedding model - self.embed_documents(credentials_kwargs=credentials_kwargs, model=model, texts=["ping"]) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - @staticmethod - def embed_documents(credentials_kwargs: dict, model: str, texts: list[str]) -> tuple[list[list[float]], int]: - """Call out to Tongyi's embedding endpoint. - - Args: - credentials_kwargs: The credentials to use for the call. - model: The model to use for embedding. - texts: The list of texts to embed. - - Returns: - List of embeddings, one for each text, and tokens usage. - """ - embeddings = [] - embedding_used_tokens = 0 - for text in texts: - response = dashscope.TextEmbedding.call( - api_key=credentials_kwargs["dashscope_api_key"], - model=model, - input=text, - text_type="document", - ) - if response.output and "embeddings" in response.output and response.output["embeddings"]: - data = response.output["embeddings"][0] - if "embedding" in data: - embeddings.append(data["embedding"]) - else: - raise ValueError("Embedding data is missing in the response.") - else: - raise ValueError("Response output is missing or does not contain embeddings.") - - if response.usage and "total_tokens" in response.usage: - embedding_used_tokens += response.usage["total_tokens"] - else: - raise ValueError("Response usage is missing or does not contain total tokens.") - - return [list(map(float, e)) for e in embeddings], embedding_used_tokens - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, - credentials=credentials, - price_type=PriceType.INPUT, - tokens=tokens, - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/upstage/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/upstage/text_embedding/text_embedding.py deleted file mode 100644 index b6509cd26cfa28..00000000000000 --- a/api/core/model_runtime/model_providers/upstage/text_embedding/text_embedding.py +++ /dev/null @@ -1,197 +0,0 @@ -import base64 -import time -from collections.abc import Mapping -from typing import Union - -import numpy as np -from openai import OpenAI -from tokenizers import Tokenizer - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.upstage._common import _CommonUpstage - - -class UpstageTextEmbeddingModel(_CommonUpstage, TextEmbeddingModel): - """ - Model class for Upstage text embedding model. - """ - - def _get_tokenizer(self) -> Tokenizer: - return Tokenizer.from_pretrained("upstage/solar-1-mini-tokenizer") - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: str | None = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - extra_model_kwargs = {} - if user: - extra_model_kwargs["user"] = user - extra_model_kwargs["encoding_format"] = "base64" - - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - - embeddings: list[list[float]] = [[] for _ in range(len(texts))] - tokens = [] - indices = [] - used_tokens = 0 - - tokenizer = self._get_tokenizer() - - for i, text in enumerate(texts): - token = tokenizer.encode(text, add_special_tokens=False).tokens - for j in range(0, len(token), context_size): - tokens += [token[j : j + context_size]] - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(tokens), max_chunks) - - for i in _iter: - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, - client=client, - texts=tokens[i : i + max_chunks], - extra_model_kwargs=extra_model_kwargs, - ) - - used_tokens += embedding_used_tokens - batched_embeddings += embeddings_batch - - results: list[list[list[float]]] = [[] for _ in range(len(texts))] - num_tokens_in_batch: list[list[int]] = [[] for _ in range(len(texts))] - - for i in range(len(indices)): - results[indices[i]].append(batched_embeddings[i]) - num_tokens_in_batch[indices[i]].append(len(tokens[i])) - - for i in range(len(texts)): - _result = results[i] - if len(_result) == 0: - embeddings_batch, embedding_used_tokens = self._embedding_invoke( - model=model, - client=client, - texts=[texts[i]], - extra_model_kwargs=extra_model_kwargs, - ) - used_tokens += embedding_used_tokens - average = embeddings_batch[0] - else: - average = np.average(_result, axis=0, weights=num_tokens_in_batch[i]) - embeddings[i] = (average / np.linalg.norm(average)).tolist() - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens) - - return TextEmbeddingResult(embeddings=embeddings, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - tokenizer = self._get_tokenizer() - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - if len(texts) == 0: - return 0 - - tokenizer = self._get_tokenizer() - - total_num_tokens = 0 - for text in texts: - # calculate the number of tokens in the encoded text - tokenized_text = tokenizer.encode(text) - total_num_tokens += len(tokenized_text) - - return total_num_tokens - - def validate_credentials(self, model: str, credentials: Mapping) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - # transform credentials to kwargs for model instance - credentials_kwargs = self._to_credential_kwargs(credentials) - client = OpenAI(**credentials_kwargs) - - # call embedding model - self._embedding_invoke(model=model, client=client, texts=["ping"], extra_model_kwargs={}) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _embedding_invoke( - self, model: str, client: OpenAI, texts: Union[list[str], str], extra_model_kwargs: dict - ) -> tuple[list[list[float]], int]: - """ - Invoke embedding model - :param model: model name - :param client: model client - :param texts: texts to embed - :param extra_model_kwargs: extra model kwargs - :return: embeddings and used tokens - """ - response = client.embeddings.create(model=model, input=texts, **extra_model_kwargs) - - if "encoding_format" in extra_model_kwargs and extra_model_kwargs["encoding_format"] == "base64": - return ( - [ - list(np.frombuffer(base64.b64decode(embedding.embedding), dtype=np.float32)) - for embedding in response.data - ], - response.usage.total_tokens, - ) - - return [data.embedding for data in response.data], response.usage.total_tokens - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - input_price_info = self.get_price( - model=model, credentials=credentials, tokens=tokens, price_type=PriceType.INPUT - ) - - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-flash-001.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-flash-001.yaml deleted file mode 100644 index f5386be06da6be..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-flash-001.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: gemini-1.5-flash-001 -label: - en_US: Gemini 1.5 Flash 001 -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - en_US: Top k - type: int - help: - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_output_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-flash-002.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-flash-002.yaml deleted file mode 100644 index 97bd44f06b5145..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-flash-002.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: gemini-1.5-flash-002 -label: - en_US: Gemini 1.5 Flash 002 -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - en_US: Top k - type: int - help: - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_output_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-pro-001.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-pro-001.yaml deleted file mode 100644 index 5e08f2294e2ebf..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-pro-001.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: gemini-1.5-pro-001 -label: - en_US: Gemini 1.5 Pro 001 -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - en_US: Top k - type: int - help: - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_output_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-pro-002.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-pro-002.yaml deleted file mode 100644 index 8f327ea2f3d37e..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-1.5-pro-002.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: gemini-1.5-pro-002 -label: - en_US: Gemini 1.5 Pro 002 -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - en_US: Top k - type: int - help: - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_output_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-flash-experimental.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-flash-experimental.yaml deleted file mode 100644 index 0f5eb34c0cdf03..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-flash-experimental.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: gemini-flash-experimental -label: - en_US: Gemini Flash Experimental -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - en_US: Top k - type: int - help: - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_output_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-pro-experimental.yaml b/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-pro-experimental.yaml deleted file mode 100644 index fa31cabb85abb0..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/gemini-pro-experimental.yaml +++ /dev/null @@ -1,37 +0,0 @@ -model: gemini-pro-experimental -label: - en_US: Gemini Pro Experimental -model_type: llm -features: - - agent-thought - - vision -model_properties: - mode: chat - context_size: 1048576 -parameter_rules: - - name: temperature - use_template: temperature - - name: top_p - use_template: top_p - - name: top_k - label: - en_US: Top k - type: int - help: - en_US: Only sample from the top K options for each subsequent token. - required: false - - name: presence_penalty - use_template: presence_penalty - - name: frequency_penalty - use_template: frequency_penalty - - name: max_output_tokens - use_template: max_tokens - required: true - default: 8192 - min: 1 - max: 8192 -pricing: - input: '0.00' - output: '0.00' - unit: '0.000001' - currency: USD diff --git a/api/core/model_runtime/model_providers/vertex_ai/llm/llm.py b/api/core/model_runtime/model_providers/vertex_ai/llm/llm.py deleted file mode 100644 index 1dd785d5454082..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/llm/llm.py +++ /dev/null @@ -1,733 +0,0 @@ -import base64 -import io -import json -import logging -import time -from collections.abc import Generator -from typing import Optional, Union, cast - -import google.auth.transport.requests -import vertexai.generative_models as glm -from anthropic import AnthropicVertex, Stream -from anthropic.types import ( - ContentBlockDeltaEvent, - Message, - MessageDeltaEvent, - MessageStartEvent, - MessageStopEvent, - MessageStreamEvent, -) -from google.api_core import exceptions -from google.cloud import aiplatform -from google.oauth2 import service_account -from PIL import Image - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessage, - PromptMessageContentType, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - ToolPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel - -logger = logging.getLogger(__name__) - - -class VertexAiLargeLanguageModel(LargeLanguageModel): - def _invoke( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param tools: tools for tool calling - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - # invoke anthropic models via anthropic official SDK - if "claude" in model: - return self._generate_anthropic(model, credentials, prompt_messages, model_parameters, stop, stream, user) - # invoke Gemini model - return self._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user) - - def _generate_anthropic( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke Anthropic large language model - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :return: full response or stream response chunk generator result - """ - # use Anthropic official SDK references - # - https://github.com/anthropics/anthropic-sdk-python - service_account_info = json.loads(base64.b64decode(credentials["vertex_service_account_key"])) - project_id = credentials["vertex_project_id"] - SCOPES = ["https://www.googleapis.com/auth/cloud-platform"] - token = "" - - # get access token from service account credential - if service_account_info: - credentials = service_account.Credentials.from_service_account_info(service_account_info, scopes=SCOPES) - request = google.auth.transport.requests.Request() - credentials.refresh(request) - token = credentials.token - - # Vertex AI Anthropic Claude3 Opus model available in us-east5 region, Sonnet and Haiku available - # in us-central1 region - if "opus" in model or "claude-3-5-sonnet" in model: - location = "us-east5" - else: - location = "us-central1" - - # use access token to authenticate - if token: - client = AnthropicVertex(region=location, project_id=project_id, access_token=token) - # When access token is empty, try to use the Google Cloud VM's built-in service account - # or the GOOGLE_APPLICATION_CREDENTIALS environment variable - else: - client = AnthropicVertex( - region=location, - project_id=project_id, - ) - - extra_model_kwargs = {} - if stop: - extra_model_kwargs["stop_sequences"] = stop - - system, prompt_message_dicts = self._convert_claude_prompt_messages(prompt_messages) - - if system: - extra_model_kwargs["system"] = system - - response = client.messages.create( - model=model, messages=prompt_message_dicts, stream=stream, **model_parameters, **extra_model_kwargs - ) - - if stream: - return self._handle_claude_stream_response(model, credentials, response, prompt_messages) - - return self._handle_claude_response(model, credentials, response, prompt_messages) - - def _handle_claude_response( - self, model: str, credentials: dict, response: Message, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm chat response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: full response chunk generator result - """ - - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=response.content[0].text) - - # calculate num tokens - if response.usage: - # transform usage - prompt_tokens = response.usage.input_tokens - completion_tokens = response.usage.output_tokens - else: - # calculate num tokens - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - response = LLMResult( - model=response.model, prompt_messages=prompt_messages, message=assistant_prompt_message, usage=usage - ) - - return response - - def _handle_claude_stream_response( - self, - model: str, - credentials: dict, - response: Stream[MessageStreamEvent], - prompt_messages: list[PromptMessage], - ) -> Generator: - """ - Handle llm chat stream response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: full response or stream response chunk generator result - """ - - try: - full_assistant_content = "" - return_model = None - input_tokens = 0 - output_tokens = 0 - finish_reason = None - index = 0 - - for chunk in response: - if isinstance(chunk, MessageStartEvent): - return_model = chunk.message.model - input_tokens = chunk.message.usage.input_tokens - elif isinstance(chunk, MessageDeltaEvent): - output_tokens = chunk.usage.output_tokens - finish_reason = chunk.delta.stop_reason - elif isinstance(chunk, MessageStopEvent): - usage = self._calc_response_usage(model, credentials, input_tokens, output_tokens) - yield LLMResultChunk( - model=return_model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index + 1, - message=AssistantPromptMessage(content=""), - finish_reason=finish_reason, - usage=usage, - ), - ) - elif isinstance(chunk, ContentBlockDeltaEvent): - chunk_text = chunk.delta.text or "" - full_assistant_content += chunk_text - assistant_prompt_message = AssistantPromptMessage( - content=chunk_text or "", - ) - index = chunk.index - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - ), - ) - except Exception as ex: - raise InvokeError(str(ex)) - - def _calc_claude_response_usage( - self, model: str, credentials: dict, prompt_tokens: int, completion_tokens: int - ) -> LLMUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param prompt_tokens: prompt tokens - :param completion_tokens: completion tokens - :return: usage - """ - # get prompt price info - prompt_price_info = self.get_price( - model=model, - credentials=credentials, - price_type=PriceType.INPUT, - tokens=prompt_tokens, - ) - - # get completion price info - completion_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.OUTPUT, tokens=completion_tokens - ) - - # transform usage - usage = LLMUsage( - prompt_tokens=prompt_tokens, - prompt_unit_price=prompt_price_info.unit_price, - prompt_price_unit=prompt_price_info.unit, - prompt_price=prompt_price_info.total_amount, - completion_tokens=completion_tokens, - completion_unit_price=completion_price_info.unit_price, - completion_price_unit=completion_price_info.unit, - completion_price=completion_price_info.total_amount, - total_tokens=prompt_tokens + completion_tokens, - total_price=prompt_price_info.total_amount + completion_price_info.total_amount, - currency=prompt_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - def _convert_claude_prompt_messages(self, prompt_messages: list[PromptMessage]) -> tuple[str, list[dict]]: - """ - Convert prompt messages to dict list and system - """ - - system = "" - first_loop = True - for message in prompt_messages: - if isinstance(message, SystemPromptMessage): - message.content = message.content.strip() - if first_loop: - system = message.content - first_loop = False - else: - system += "\n" - system += message.content - - prompt_message_dicts = [] - for message in prompt_messages: - if not isinstance(message, SystemPromptMessage): - prompt_message_dicts.append(self._convert_claude_prompt_message_to_dict(message)) - - return system, prompt_message_dicts - - def _convert_claude_prompt_message_to_dict(self, message: PromptMessage) -> dict: - """ - Convert PromptMessage to dict - """ - if isinstance(message, UserPromptMessage): - message = cast(UserPromptMessage, message) - if isinstance(message.content, str): - message_dict = {"role": "user", "content": message.content} - else: - sub_messages = [] - for message_content in message.content: - if message_content.type == PromptMessageContentType.TEXT: - message_content = cast(TextPromptMessageContent, message_content) - sub_message_dict = {"type": "text", "text": message_content.data} - sub_messages.append(sub_message_dict) - elif message_content.type == PromptMessageContentType.IMAGE: - message_content = cast(ImagePromptMessageContent, message_content) - if not message_content.data.startswith("data:"): - # fetch image data from url - try: - image_content = requests.get(message_content.data).content - with Image.open(io.BytesIO(image_content)) as img: - mime_type = f"image/{img.format.lower()}" - base64_data = base64.b64encode(image_content).decode("utf-8") - except Exception as ex: - raise ValueError(f"Failed to fetch image data from url {message_content.data}, {ex}") - else: - data_split = message_content.data.split(";base64,") - mime_type = data_split[0].replace("data:", "") - base64_data = data_split[1] - - if mime_type not in {"image/jpeg", "image/png", "image/gif", "image/webp"}: - raise ValueError( - f"Unsupported image type {mime_type}, " - f"only support image/jpeg, image/png, image/gif, and image/webp" - ) - - sub_message_dict = { - "type": "image", - "source": {"type": "base64", "media_type": mime_type, "data": base64_data}, - } - sub_messages.append(sub_message_dict) - - message_dict = {"role": "user", "content": sub_messages} - elif isinstance(message, AssistantPromptMessage): - message = cast(AssistantPromptMessage, message) - message_dict = {"role": "assistant", "content": message.content} - elif isinstance(message, SystemPromptMessage): - message = cast(SystemPromptMessage, message) - message_dict = {"role": "system", "content": message.content} - else: - raise ValueError(f"Got unknown type {message}") - - return message_dict - - def get_num_tokens( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - tools: Optional[list[PromptMessageTool]] = None, - ) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param prompt_messages: prompt messages - :param tools: tools for tool calling - :return:md = gml.GenerativeModel(model) - """ - prompt = self._convert_messages_to_prompt(prompt_messages) - - return self._get_num_tokens_by_gpt2(prompt) - - def _convert_messages_to_prompt(self, messages: list[PromptMessage]) -> str: - """ - Format a list of messages into a full prompt for the Google model - - :param messages: List of PromptMessage to combine. - :return: Combined string with necessary human_prompt and ai_prompt tags. - """ - messages = messages.copy() # don't mutate the original list - - text = "".join(self._convert_one_message_to_text(message) for message in messages) - - return text.rstrip() - - def _convert_tools_to_glm_tool(self, tools: list[PromptMessageTool]) -> glm.Tool: - """ - Convert tool messages to glm tools - - :param tools: tool messages - :return: glm tools - """ - return glm.Tool( - function_declarations=[ - glm.FunctionDeclaration( - name=tool.name, - parameters=glm.Schema( - type=glm.Type.OBJECT, - properties={ - key: { - "type_": value.get("type", "string").upper(), - "description": value.get("description", ""), - "enum": value.get("enum", []), - } - for key, value in tool.parameters.get("properties", {}).items() - }, - required=tool.parameters.get("required", []), - ), - ) - for tool in tools - ] - ) - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - - try: - ping_message = SystemPromptMessage(content="ping") - self._generate(model, credentials, [ping_message], {"max_tokens_to_sample": 5}) - - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _generate( - self, - model: str, - credentials: dict, - prompt_messages: list[PromptMessage], - model_parameters: dict, - tools: Optional[list[PromptMessageTool]] = None, - stop: Optional[list[str]] = None, - stream: bool = True, - user: Optional[str] = None, - ) -> Union[LLMResult, Generator]: - """ - Invoke large language model - - :param model: model name - :param credentials: credentials kwargs - :param prompt_messages: prompt messages - :param model_parameters: model parameters - :param stop: stop words - :param stream: is stream response - :param user: unique user id - :return: full response or stream response chunk generator result - """ - config_kwargs = model_parameters.copy() - config_kwargs["max_output_tokens"] = config_kwargs.pop("max_tokens_to_sample", None) - - if stop: - config_kwargs["stop_sequences"] = stop - - service_account_info = json.loads(base64.b64decode(credentials["vertex_service_account_key"])) - project_id = credentials["vertex_project_id"] - location = credentials["vertex_location"] - if service_account_info: - service_accountSA = service_account.Credentials.from_service_account_info(service_account_info) - aiplatform.init(credentials=service_accountSA, project=project_id, location=location) - else: - aiplatform.init(project=project_id, location=location) - - history = [] - system_instruction = "" - # hack for gemini-pro-vision, which currently does not support multi-turn chat - if model == "gemini-1.0-pro-vision-001": - last_msg = prompt_messages[-1] - content = self._format_message_to_glm_content(last_msg) - history.append(content) - else: - for msg in prompt_messages: - if isinstance(msg, SystemPromptMessage): - system_instruction = msg.content - else: - content = self._format_message_to_glm_content(msg) - if history and history[-1].role == content.role: - history[-1].parts.extend(content.parts) - else: - history.append(content) - - google_model = glm.GenerativeModel(model_name=model, system_instruction=system_instruction) - - response = google_model.generate_content( - contents=history, - generation_config=glm.GenerationConfig(**config_kwargs), - stream=stream, - tools=self._convert_tools_to_glm_tool(tools) if tools else None, - ) - - if stream: - return self._handle_generate_stream_response(model, credentials, response, prompt_messages) - - return self._handle_generate_response(model, credentials, response, prompt_messages) - - def _handle_generate_response( - self, model: str, credentials: dict, response: glm.GenerationResponse, prompt_messages: list[PromptMessage] - ) -> LLMResult: - """ - Handle llm response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response - """ - # transform assistant message to prompt message - assistant_prompt_message = AssistantPromptMessage(content=response.candidates[0].content.parts[0].text) - - # calculate num tokens - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - # transform response - result = LLMResult( - model=model, - prompt_messages=prompt_messages, - message=assistant_prompt_message, - usage=usage, - ) - - return result - - def _handle_generate_stream_response( - self, model: str, credentials: dict, response: glm.GenerationResponse, prompt_messages: list[PromptMessage] - ) -> Generator: - """ - Handle llm stream response - - :param model: model name - :param credentials: credentials - :param response: response - :param prompt_messages: prompt messages - :return: llm response chunk generator result - """ - index = -1 - for chunk in response: - for part in chunk.candidates[0].content.parts: - assistant_prompt_message = AssistantPromptMessage(content="") - - if part.text: - assistant_prompt_message.content += part.text - - if part.function_call: - assistant_prompt_message.tool_calls = [ - AssistantPromptMessage.ToolCall( - id=part.function_call.name, - type="function", - function=AssistantPromptMessage.ToolCall.ToolCallFunction( - name=part.function_call.name, - arguments=json.dumps(dict(part.function_call.args.items())), - ), - ) - ] - - index += 1 - - if not hasattr(chunk, "finish_reason") or not chunk.finish_reason: - # transform assistant message to prompt message - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta(index=index, message=assistant_prompt_message), - ) - else: - # calculate num tokens - prompt_tokens = self.get_num_tokens(model, credentials, prompt_messages) - completion_tokens = self.get_num_tokens(model, credentials, [assistant_prompt_message]) - - # transform usage - usage = self._calc_response_usage(model, credentials, prompt_tokens, completion_tokens) - - yield LLMResultChunk( - model=model, - prompt_messages=prompt_messages, - delta=LLMResultChunkDelta( - index=index, - message=assistant_prompt_message, - finish_reason=chunk.candidates[0].finish_reason, - usage=usage, - ), - ) - - def _convert_one_message_to_text(self, message: PromptMessage) -> str: - """ - Convert a single message to a string. - - :param message: PromptMessage to convert. - :return: String representation of the message. - """ - human_prompt = "\n\nuser:" - ai_prompt = "\n\nmodel:" - - content = message.content - if isinstance(content, list): - content = "".join(c.data for c in content if c.type != PromptMessageContentType.IMAGE) - - if isinstance(message, UserPromptMessage): - message_text = f"{human_prompt} {content}" - elif isinstance(message, AssistantPromptMessage): - message_text = f"{ai_prompt} {content}" - elif isinstance(message, SystemPromptMessage | ToolPromptMessage): - message_text = f"{human_prompt} {content}" - else: - raise ValueError(f"Got unknown type {message}") - - return message_text - - def _format_message_to_glm_content(self, message: PromptMessage) -> glm.Content: - """ - Format a single message into glm.Content for Google API - - :param message: one PromptMessage - :return: glm Content representation of message - """ - if isinstance(message, UserPromptMessage): - glm_content = glm.Content(role="user", parts=[]) - - if isinstance(message.content, str): - glm_content = glm.Content(role="user", parts=[glm.Part.from_text(message.content)]) - else: - parts = [] - for c in message.content: - if c.type == PromptMessageContentType.TEXT: - parts.append(glm.Part.from_text(c.data)) - else: - metadata, data = c.data.split(",", 1) - mime_type = metadata.split(";", 1)[0].split(":")[1] - parts.append(glm.Part.from_data(mime_type=mime_type, data=data)) - glm_content = glm.Content(role="user", parts=parts) - return glm_content - elif isinstance(message, AssistantPromptMessage): - if message.content: - glm_content = glm.Content(role="model", parts=[glm.Part.from_text(message.content)]) - if message.tool_calls: - glm_content = glm.Content( - role="model", - parts=[ - glm.Part.from_function_response( - glm.FunctionCall( - name=message.tool_calls[0].function.name, - args=json.loads(message.tool_calls[0].function.arguments), - ) - ) - ], - ) - return glm_content - elif isinstance(message, ToolPromptMessage): - glm_content = glm.Content( - role="function", - parts=[ - glm.Part( - function_response=glm.FunctionResponse( - name=message.name, response={"response": message.content} - ) - ) - ], - ) - return glm_content - else: - raise ValueError(f"Got unknown type {message}") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the ermd = gml.GenerativeModel(model) error type thrown to the caller - The value is the md = gml.GenerativeModel(model) error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke emd = gml.GenerativeModel(model) error mapping - """ - return { - InvokeConnectionError: [exceptions.RetryError], - InvokeServerUnavailableError: [ - exceptions.ServiceUnavailable, - exceptions.InternalServerError, - exceptions.BadGateway, - exceptions.GatewayTimeout, - exceptions.DeadlineExceeded, - ], - InvokeRateLimitError: [exceptions.ResourceExhausted, exceptions.TooManyRequests], - InvokeAuthorizationError: [ - exceptions.Unauthenticated, - exceptions.PermissionDenied, - exceptions.Unauthenticated, - exceptions.Forbidden, - ], - InvokeBadRequestError: [ - exceptions.BadRequest, - exceptions.InvalidArgument, - exceptions.FailedPrecondition, - exceptions.OutOfRange, - exceptions.NotFound, - exceptions.MethodNotAllowed, - exceptions.Conflict, - exceptions.AlreadyExists, - exceptions.Aborted, - exceptions.LengthRequired, - exceptions.PreconditionFailed, - exceptions.RequestRangeNotSatisfiable, - exceptions.Cancelled, - ], - } diff --git a/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text_embedding.py deleted file mode 100644 index fce9544df0a414..00000000000000 --- a/api/core/model_runtime/model_providers/vertex_ai/text_embedding/text_embedding.py +++ /dev/null @@ -1,187 +0,0 @@ -import base64 -import json -import time -from decimal import Decimal -from typing import Optional - -import tiktoken -from google.cloud import aiplatform -from google.oauth2 import service_account -from vertexai.language_models import TextEmbeddingModel as VertexTextEmbeddingModel - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - PriceConfig, - PriceType, -) -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.vertex_ai._common import _CommonVertexAi - - -class VertexAiTextEmbeddingModel(_CommonVertexAi, TextEmbeddingModel): - """ - Model class for Vertex AI text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - service_account_info = json.loads(base64.b64decode(credentials["vertex_service_account_key"])) - project_id = credentials["vertex_project_id"] - location = credentials["vertex_location"] - if service_account_info: - service_accountSA = service_account.Credentials.from_service_account_info(service_account_info) - aiplatform.init(credentials=service_accountSA, project=project_id, location=location) - else: - aiplatform.init(project=project_id, location=location) - - client = VertexTextEmbeddingModel.from_pretrained(model) - - embeddings_batch, embedding_used_tokens = self._embedding_invoke(client=client, texts=texts) - - # calc usage - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=embedding_used_tokens) - - return TextEmbeddingResult(embeddings=embeddings_batch, usage=usage, model=model) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - if len(texts) == 0: - return 0 - - try: - enc = tiktoken.encoding_for_model(model) - except KeyError: - enc = tiktoken.get_encoding("cl100k_base") - - total_num_tokens = 0 - for text in texts: - # calculate the number of tokens in the encoded text - tokenized_text = enc.encode(text) - total_num_tokens += len(tokenized_text) - - return total_num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - service_account_info = json.loads(base64.b64decode(credentials["vertex_service_account_key"])) - project_id = credentials["vertex_project_id"] - location = credentials["vertex_location"] - if service_account_info: - service_accountSA = service_account.Credentials.from_service_account_info(service_account_info) - aiplatform.init(credentials=service_accountSA, project=project_id, location=location) - else: - aiplatform.init(project=project_id, location=location) - - client = VertexTextEmbeddingModel.from_pretrained(model) - - # call embedding model - self._embedding_invoke(model=model, client=client, texts=["ping"]) - except Exception as ex: - raise CredentialsValidateFailedError(str(ex)) - - def _embedding_invoke(self, client: VertexTextEmbeddingModel, texts: list[str]) -> [list[float], int]: # type: ignore - """ - Invoke embedding model - - :param model: model name - :param client: model client - :param texts: texts to embed - :return: embeddings and used tokens - """ - response = client.get_embeddings(texts) - - embeddings = [] - token_usage = 0 - - for i in range(len(response)): - embeddings.append(response[i].values) - token_usage += int(response[i].statistics.token_count) - - return embeddings, token_usage - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.TEXT_EMBEDDING, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties={ - ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size")), - ModelPropertyKey.MAX_CHUNKS: 1, - }, - parameter_rules=[], - pricing=PriceConfig( - input=Decimal(credentials.get("input_price", 0)), - unit=Decimal(credentials.get("unit", 0)), - currency=credentials.get("currency", "USD"), - ), - ) - - return entity diff --git a/api/core/model_runtime/model_providers/volcengine_maas/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/volcengine_maas/text_embedding/text_embedding.py deleted file mode 100644 index 0dd4037c958567..00000000000000 --- a/api/core/model_runtime/model_providers/volcengine_maas/text_embedding/text_embedding.py +++ /dev/null @@ -1,198 +0,0 @@ -import time -from decimal import Decimal -from typing import Optional - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import ( - AIModelEntity, - FetchFrom, - ModelPropertyKey, - ModelType, - PriceConfig, - PriceType, -) -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.volcengine_maas.client import ArkClientV3 -from core.model_runtime.model_providers.volcengine_maas.legacy.client import MaaSClient -from core.model_runtime.model_providers.volcengine_maas.legacy.errors import ( - AuthErrors, - BadRequestErrors, - ConnectionErrors, - MaasError, - RateLimitErrors, - ServerUnavailableErrors, -) -from core.model_runtime.model_providers.volcengine_maas.text_embedding.models import get_model_config - - -class VolcengineMaaSTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for VolcengineMaaS text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - if ArkClientV3.is_legacy(credentials): - return self._generate_v2(model, credentials, texts, user) - - return self._generate_v3(model, credentials, texts, user) - - def _generate_v2( - self, model: str, credentials: dict, texts: list[str], user: Optional[str] = None - ) -> TextEmbeddingResult: - client = MaaSClient.from_credential(credentials) - resp = MaaSClient.wrap_exception(lambda: client.embeddings(texts)) - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=resp["usage"]["total_tokens"]) - - result = TextEmbeddingResult(model=model, embeddings=[v["embedding"] for v in resp["data"]], usage=usage) - - return result - - def _generate_v3( - self, model: str, credentials: dict, texts: list[str], user: Optional[str] = None - ) -> TextEmbeddingResult: - client = ArkClientV3.from_credentials(credentials) - resp = client.embeddings(texts) - - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=resp.usage.total_tokens) - - result = TextEmbeddingResult(model=model, embeddings=[v.embedding for v in resp.data], usage=usage) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - for text in texts: - # use GPT2Tokenizer to get num tokens - num_tokens += self._get_num_tokens_by_gpt2(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - if ArkClientV3.is_legacy(credentials): - return self._validate_credentials_v2(model, credentials) - return self._validate_credentials_v3(model, credentials) - - def _validate_credentials_v2(self, model: str, credentials: dict) -> None: - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except MaasError as e: - raise CredentialsValidateFailedError(e.message) - - def _validate_credentials_v3(self, model: str, credentials: dict) -> None: - try: - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except Exception as e: - raise CredentialsValidateFailedError(e) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - """ - Map model invoke error to unified error - The key is the error type thrown to the caller - The value is the error type thrown by the model, - which needs to be converted into a unified error type for the caller. - - :return: Invoke error mapping - """ - return { - InvokeConnectionError: ConnectionErrors.values(), - InvokeServerUnavailableError: ServerUnavailableErrors.values(), - InvokeRateLimitError: RateLimitErrors.values(), - InvokeAuthorizationError: AuthErrors.values(), - InvokeBadRequestError: BadRequestErrors.values(), - } - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity: - """ - generate custom model entities from credentials - """ - model_config = get_model_config(credentials) - model_properties = { - ModelPropertyKey.CONTEXT_SIZE: model_config.properties.context_size, - ModelPropertyKey.MAX_CHUNKS: model_config.properties.max_chunks, - } - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - model_type=ModelType.TEXT_EMBEDDING, - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_properties=model_properties, - parameter_rules=[], - pricing=PriceConfig( - input=Decimal(credentials.get("input_price", 0)), - unit=Decimal(credentials.get("unit", 0)), - currency=credentials.get("currency", "USD"), - ), - ) - - return entity - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/wenxin/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/wenxin/text_embedding/text_embedding.py deleted file mode 100644 index c21d0c055277f7..00000000000000 --- a/api/core/model_runtime/model_providers/wenxin/text_embedding/text_embedding.py +++ /dev/null @@ -1,187 +0,0 @@ -import time -from abc import abstractmethod -from collections.abc import Mapping -from json import dumps -from typing import Any, Optional - -import numpy as np -from requests import Response, post - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.model_entities import PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import InvokeError -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.wenxin._common import BaiduAccessToken, _CommonWenxin -from core.model_runtime.model_providers.wenxin.wenxin_errors import ( - BadRequestError, - InternalServerError, - invoke_error_mapping, -) - - -class TextEmbedding: - @abstractmethod - def embed_documents(self, model: str, texts: list[str], user: str) -> (list[list[float]], int, int): - raise NotImplementedError - - -class WenxinTextEmbedding(_CommonWenxin, TextEmbedding): - def embed_documents(self, model: str, texts: list[str], user: str) -> (list[list[float]], int, int): - access_token = self._get_access_token() - url = f"{self.api_bases[model]}?access_token={access_token}" - body = self._build_embed_request_body(model, texts, user) - headers = { - "Content-Type": "application/json", - } - - resp = post(url, data=dumps(body), headers=headers) - if resp.status_code != 200: - raise InternalServerError(f"Failed to invoke ernie bot: {resp.text}") - return self._handle_embed_response(model, resp) - - def _build_embed_request_body(self, model: str, texts: list[str], user: str) -> dict[str, Any]: - if len(texts) == 0: - raise BadRequestError("The number of texts should not be zero.") - body = { - "input": texts, - "user_id": user, - } - return body - - def _handle_embed_response(self, model: str, response: Response) -> (list[list[float]], int, int): - data = response.json() - if "error_code" in data: - code = data["error_code"] - msg = data["error_msg"] - # raise error - self._handle_error(code, msg) - - embeddings = [v["embedding"] for v in data["data"]] - _usage = data["usage"] - tokens = _usage["prompt_tokens"] - total_tokens = _usage["total_tokens"] - - return embeddings, tokens, total_tokens - - -class WenxinTextEmbeddingModel(TextEmbeddingModel): - def _create_text_embedding(self, api_key: str, secret_key: str) -> TextEmbedding: - return WenxinTextEmbedding(api_key, secret_key) - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - - api_key = credentials["api_key"] - secret_key = credentials["secret_key"] - embedding: TextEmbedding = self._create_text_embedding(api_key, secret_key) - user = user or "ErnieBotDefault" - - context_size = self._get_context_size(model, credentials) - max_chunks = self._get_max_chunks(model, credentials) - inputs = [] - indices = [] - used_tokens = 0 - used_total_tokens = 0 - - for i, text in enumerate(texts): - # Here token count is only an approximation based on the GPT2 tokenizer - num_tokens = self._get_num_tokens_by_gpt2(text) - - if num_tokens >= context_size: - cutoff = int(np.floor(len(text) * (context_size / num_tokens))) - # if num tokens is larger than context length, only use the start - inputs.append(text[0:cutoff]) - else: - inputs.append(text) - indices += [i] - - batched_embeddings = [] - _iter = range(0, len(inputs), max_chunks) - for i in _iter: - embeddings_batch, _used_tokens, _total_used_tokens = embedding.embed_documents( - model, inputs[i : i + max_chunks], user - ) - used_tokens += _used_tokens - used_total_tokens += _total_used_tokens - batched_embeddings += embeddings_batch - - usage = self._calc_response_usage(model, credentials, used_tokens, used_total_tokens) - return TextEmbeddingResult( - model=model, - embeddings=batched_embeddings, - usage=usage, - ) - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - if len(texts) == 0: - return 0 - total_num_tokens = 0 - for text in texts: - total_num_tokens += self._get_num_tokens_by_gpt2(text) - - return total_num_tokens - - def validate_credentials(self, model: str, credentials: Mapping) -> None: - api_key = credentials["api_key"] - secret_key = credentials["secret_key"] - try: - BaiduAccessToken.get_access_token(api_key, secret_key) - except Exception as e: - raise CredentialsValidateFailedError(f"Credentials validation failed: {e}") - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return invoke_error_mapping() - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int, total_tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=total_tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage diff --git a/api/core/model_runtime/model_providers/xinference/text_embedding/text_embedding.py b/api/core/model_runtime/model_providers/xinference/text_embedding/text_embedding.py deleted file mode 100644 index 16272391320d55..00000000000000 --- a/api/core/model_runtime/model_providers/xinference/text_embedding/text_embedding.py +++ /dev/null @@ -1,204 +0,0 @@ -import time -from typing import Optional - -from xinference_client.client.restful.restful_client import Client, RESTfulEmbeddingModelHandle - -from core.embedding.embedding_constant import EmbeddingInputType -from core.model_runtime.entities.common_entities import I18nObject -from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType -from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult -from core.model_runtime.errors.invoke import ( - InvokeAuthorizationError, - InvokeBadRequestError, - InvokeConnectionError, - InvokeError, - InvokeRateLimitError, - InvokeServerUnavailableError, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel -from core.model_runtime.model_providers.xinference.xinference_helper import XinferenceHelper - - -class XinferenceTextEmbeddingModel(TextEmbeddingModel): - """ - Model class for Xinference text embedding model. - """ - - def _invoke( - self, - model: str, - credentials: dict, - texts: list[str], - user: Optional[str] = None, - input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT, - ) -> TextEmbeddingResult: - """ - Invoke text embedding model - - credentials should be like: - { - 'server_url': 'server url', - 'model_uid': 'model uid', - } - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :param user: unique user id - :param input_type: input type - :return: embeddings result - """ - server_url = credentials["server_url"] - model_uid = credentials["model_uid"] - api_key = credentials.get("api_key") - server_url = server_url.removesuffix("/") - auth_headers = {"Authorization": f"Bearer {api_key}"} if api_key else {} - - try: - handle = RESTfulEmbeddingModelHandle(model_uid, server_url, auth_headers) - embeddings = handle.create_embedding(input=texts) - except RuntimeError as e: - raise InvokeServerUnavailableError(str(e)) - - """ - for convenience, the response json is like: - class Embedding(TypedDict): - object: Literal["list"] - model: str - data: List[EmbeddingData] - usage: EmbeddingUsage - class EmbeddingUsage(TypedDict): - prompt_tokens: int - total_tokens: int - class EmbeddingData(TypedDict): - index: int - object: str - embedding: List[float] - """ - - usage = embeddings["usage"] - usage = self._calc_response_usage(model=model, credentials=credentials, tokens=usage["total_tokens"]) - - result = TextEmbeddingResult( - model=model, embeddings=[embedding["embedding"] for embedding in embeddings["data"]], usage=usage - ) - - return result - - def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int: - """ - Get number of tokens for given prompt messages - - :param model: model name - :param credentials: model credentials - :param texts: texts to embed - :return: - """ - num_tokens = 0 - for text in texts: - # use GPT2Tokenizer to get num tokens - num_tokens += self._get_num_tokens_by_gpt2(text) - return num_tokens - - def validate_credentials(self, model: str, credentials: dict) -> None: - """ - Validate model credentials - - :param model: model name - :param credentials: model credentials - :return: - """ - try: - if "/" in credentials["model_uid"] or "?" in credentials["model_uid"] or "#" in credentials["model_uid"]: - raise CredentialsValidateFailedError("model_uid should not contain /, ?, or #") - - server_url = credentials["server_url"] - model_uid = credentials["model_uid"] - api_key = credentials.get("api_key") - extra_args = XinferenceHelper.get_xinference_extra_parameter( - server_url=server_url, - model_uid=model_uid, - api_key=api_key, - ) - - if extra_args.max_tokens: - credentials["max_tokens"] = extra_args.max_tokens - server_url = server_url.removesuffix("/") - - client = Client( - base_url=server_url, - api_key=api_key, - ) - - try: - handle = client.get_model(model_uid=model_uid) - except RuntimeError as e: - raise InvokeAuthorizationError(e) - - if not isinstance(handle, RESTfulEmbeddingModelHandle): - raise InvokeBadRequestError( - "please check model type, the model you want to invoke is not a text embedding model" - ) - - self._invoke(model=model, credentials=credentials, texts=["ping"]) - except InvokeAuthorizationError as e: - raise CredentialsValidateFailedError(f"Failed to validate credentials for model {model}: {e}") - except RuntimeError as e: - raise CredentialsValidateFailedError(e) - - @property - def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]: - return { - InvokeConnectionError: [InvokeConnectionError], - InvokeServerUnavailableError: [InvokeServerUnavailableError], - InvokeRateLimitError: [InvokeRateLimitError], - InvokeAuthorizationError: [InvokeAuthorizationError], - InvokeBadRequestError: [KeyError], - } - - def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage: - """ - Calculate response usage - - :param model: model name - :param credentials: model credentials - :param tokens: input tokens - :return: usage - """ - # get input price info - input_price_info = self.get_price( - model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens - ) - - # transform usage - usage = EmbeddingUsage( - tokens=tokens, - total_tokens=tokens, - unit_price=input_price_info.unit_price, - price_unit=input_price_info.unit, - total_price=input_price_info.total_amount, - currency=input_price_info.currency, - latency=time.perf_counter() - self.started_at, - ) - - return usage - - def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None: - """ - used to define customizable model schema - """ - - entity = AIModelEntity( - model=model, - label=I18nObject(en_US=model), - fetch_from=FetchFrom.CUSTOMIZABLE_MODEL, - model_type=ModelType.TEXT_EMBEDDING, - model_properties={ - ModelPropertyKey.MAX_CHUNKS: 1, - ModelPropertyKey.CONTEXT_SIZE: "max_tokens" in credentials and credentials["max_tokens"] or 512, - }, - parameter_rules=[], - ) - - return entity diff --git a/api/core/plugin/manager/model.py b/api/core/plugin/manager/model.py index 30bd9bc0a8e034..fb58c4bb8df5c1 100644 --- a/api/core/plugin/manager/model.py +++ b/api/core/plugin/manager/model.py @@ -235,6 +235,7 @@ def invoke_text_embedding( model: str, credentials: dict, texts: list[str], + input_type: str, ) -> TextEmbeddingResult: """ Invoke text embedding @@ -252,6 +253,7 @@ def invoke_text_embedding( "model": model, "credentials": credentials, "texts": texts, + "input_type": input_type, }, } ), @@ -272,7 +274,6 @@ def get_text_embedding_num_tokens( user_id: str, plugin_id: str, provider: str, - model_type: str, model: str, credentials: dict, texts: list[str], @@ -289,7 +290,7 @@ def get_text_embedding_num_tokens( "user_id": user_id, "data": { "provider": provider, - "model_type": model_type, + "model_type": "text-embedding", "model": model, "credentials": credentials, "texts": texts, @@ -313,7 +314,6 @@ def invoke_rerank( user_id: str, plugin_id: str, provider: str, - model_type: str, model: str, credentials: dict, query: str, @@ -333,7 +333,7 @@ def invoke_rerank( "user_id": user_id, "data": { "provider": provider, - "model_type": model_type, + "model_type": "rerank", "model": model, "credentials": credentials, "query": query, @@ -360,7 +360,6 @@ def invoke_tts( user_id: str, plugin_id: str, provider: str, - model_type: str, model: str, credentials: dict, content_text: str, @@ -378,7 +377,7 @@ def invoke_tts( "user_id": user_id, "data": { "provider": provider, - "model_type": model_type, + "model_type": "tts", "model": model, "credentials": credentials, "content_text": content_text, @@ -405,7 +404,6 @@ def get_tts_model_voices( user_id: str, plugin_id: str, provider: str, - model_type: str, model: str, credentials: dict, language: Optional[str] = None, @@ -422,7 +420,7 @@ def get_tts_model_voices( "user_id": user_id, "data": { "provider": provider, - "model_type": model_type, + "model_type": "tts", "model": model, "credentials": credentials, "language": language, @@ -447,7 +445,6 @@ def invoke_speech_to_text( user_id: str, plugin_id: str, provider: str, - model_type: str, model: str, credentials: dict, file: IO[bytes], @@ -464,7 +461,7 @@ def invoke_speech_to_text( "user_id": user_id, "data": { "provider": provider, - "model_type": model_type, + "model_type": "speech2text", "model": model, "credentials": credentials, "file": binascii.hexlify(file.read()).decode(), @@ -488,7 +485,6 @@ def invoke_moderation( user_id: str, plugin_id: str, provider: str, - model_type: str, model: str, credentials: dict, text: str, @@ -505,7 +501,7 @@ def invoke_moderation( "user_id": user_id, "data": { "provider": provider, - "model_type": model_type, + "model_type": "moderation", "model": model, "credentials": credentials, "text": text, diff --git a/api/core/provider_manager.py b/api/core/provider_manager.py index cb49a6cf5619b7..ae3934327e1cba 100644 --- a/api/core/provider_manager.py +++ b/api/core/provider_manager.py @@ -244,12 +244,11 @@ def get_default_model(self, tenant_id: str, model_type: ModelType) -> Optional[D (model for model in available_models if model.model == "gpt-4"), available_models[0] ) - default_model = TenantDefaultModel( - tenant_id=tenant_id, - model_type=model_type.to_origin_model_type(), - provider_name=available_model.provider.provider, - model_name=available_model.model, - ) + default_model = TenantDefaultModel() + default_model.tenant_id = tenant_id + default_model.model_type = model_type.to_origin_model_type() + default_model.provider_name = available_model.provider.provider + default_model.model_name = available_model.model db.session.add(default_model) db.session.commit() @@ -489,15 +488,14 @@ def _init_trial_provider_records( # Init trial provider records if not exists if ProviderQuotaType.TRIAL not in provider_quota_to_provider_record_dict: try: - provider_record = Provider( - tenant_id=tenant_id, - provider_name=provider_name, - provider_type=ProviderType.SYSTEM.value, - quota_type=ProviderQuotaType.TRIAL.value, - quota_limit=quota.quota_limit, - quota_used=0, - is_valid=True, - ) + provider_record = Provider() + provider_record.tenant_id = tenant_id + provider_record.provider_name = provider_name + provider_record.provider_type = ProviderType.SYSTEM.value + provider_record.quota_type = ProviderQuotaType.TRIAL.value + provider_record.quota_limit = quota.quota_limit + provider_record.quota_used = 0 + provider_record.is_valid = True db.session.add(provider_record) db.session.commit() except IntegrityError: diff --git a/api/core/tools/builtin_tool/tool.py b/api/core/tools/builtin_tool/tool.py index fe77f9ac77bc74..abba542b8edb2a 100644 --- a/api/core/tools/builtin_tool/tool.py +++ b/api/core/tools/builtin_tool/tool.py @@ -3,7 +3,6 @@ from core.tools.__base.tool import Tool from core.tools.entities.tool_entities import ToolProviderType from core.tools.utils.model_invocation_utils import ModelInvocationUtils -from core.tools.utils.web_reader_tool import get_url _SUMMARY_PROMPT = """You are a professional language researcher, you are interested in the language and you can quickly aimed at the main point of an webpage and reproduce it in your own words but @@ -124,9 +123,3 @@ def summarize(content: str) -> str: return self.summary(user_id=user_id, content=result) return result - - def get_url(self, url: str, user_agent: str | None = None) -> str: - """ - get url - """ - return get_url(url, user_agent=user_agent) diff --git a/api/core/tools/utils/web_reader_tool.py b/api/core/tools/utils/web_reader_tool.py deleted file mode 100644 index dcbae9f5aa2260..00000000000000 --- a/api/core/tools/utils/web_reader_tool.py +++ /dev/null @@ -1,357 +0,0 @@ -import hashlib -import json -import mimetypes -import os -import re -import site -import subprocess -import tempfile -import unicodedata -from contextlib import contextmanager -from pathlib import Path -from urllib.parse import unquote - -import chardet -import cloudscraper -from bs4 import BeautifulSoup, CData, Comment, NavigableString -from regex import regex - -from core.helper import ssrf_proxy -from core.rag.extractor import extract_processor -from core.rag.extractor.extract_processor import ExtractProcessor - -FULL_TEMPLATE = """ -TITLE: {title} -AUTHORS: {authors} -PUBLISH DATE: {publish_date} -TOP_IMAGE_URL: {top_image} -TEXT: - -{text} -""" - - -def page_result(text: str, cursor: int, max_length: int) -> str: - """Page through `text` and return a substring of `max_length` characters starting from `cursor`.""" - return text[cursor : cursor + max_length] - - -def get_url(url: str, user_agent: str | None = None) -> str: - """Fetch URL and return the contents as a string.""" - headers = { - "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)" - " Chrome/91.0.4472.124 Safari/537.36" - } - if user_agent: - headers["User-Agent"] = user_agent - - main_content_type = None - supported_content_types = extract_processor.SUPPORT_URL_CONTENT_TYPES + ["text/html"] - response = ssrf_proxy.head(url, headers=headers, follow_redirects=True, timeout=(5, 10)) - - if response.status_code == 200: - # check content-type - content_type = response.headers.get("Content-Type") - if content_type: - main_content_type = response.headers.get("Content-Type").split(";")[0].strip() - else: - content_disposition = response.headers.get("Content-Disposition", "") - filename_match = re.search(r'filename="([^"]+)"', content_disposition) - if filename_match: - filename = unquote(filename_match.group(1)) - extension = re.search(r"\.(\w+)$", filename) - if extension: - main_content_type = mimetypes.guess_type(filename)[0] - - if main_content_type not in supported_content_types: - return "Unsupported content-type [{}] of URL.".format(main_content_type) - - if main_content_type in extract_processor.SUPPORT_URL_CONTENT_TYPES: - return ExtractProcessor.load_from_url(url, return_text=True) - - response = ssrf_proxy.get(url, headers=headers, follow_redirects=True, timeout=(120, 300)) - elif response.status_code == 403: - scraper = cloudscraper.create_scraper() - scraper.perform_request = ssrf_proxy.make_request - response = scraper.get(url, headers=headers, follow_redirects=True, timeout=(120, 300)) - - if response.status_code != 200: - return "URL returned status code {}.".format(response.status_code) - - # Detect encoding using chardet - detected_encoding = chardet.detect(response.content) - encoding = detected_encoding["encoding"] - if encoding: - try: - content = response.content.decode(encoding) - except (UnicodeDecodeError, TypeError): - content = response.text - else: - content = response.text - - a = extract_using_readabilipy(content) - - if not a["plain_text"] or not a["plain_text"].strip(): - return "" - - res = FULL_TEMPLATE.format( - title=a["title"], - authors=a["byline"], - publish_date=a["date"], - top_image="", - text=a["plain_text"] or "", - ) - - return res - - -def extract_using_readabilipy(html): - with tempfile.NamedTemporaryFile(delete=False, mode="w+") as f_html: - f_html.write(html) - f_html.close() - html_path = f_html.name - - # Call Mozilla's Readability.js Readability.parse() function via node, writing output to a temporary file - article_json_path = html_path + ".json" - jsdir = os.path.join(find_module_path("readabilipy"), "javascript") - with chdir(jsdir): - subprocess.check_call(["node", "ExtractArticle.js", "-i", html_path, "-o", article_json_path]) - - # Read output of call to Readability.parse() from JSON file and return as Python dictionary - input_json = json.loads(Path(article_json_path).read_text(encoding="utf-8")) - - # Deleting files after processing - os.unlink(article_json_path) - os.unlink(html_path) - - article_json = { - "title": None, - "byline": None, - "date": None, - "content": None, - "plain_content": None, - "plain_text": None, - } - # Populate article fields from readability fields where present - if input_json: - if input_json.get("title"): - article_json["title"] = input_json["title"] - if input_json.get("byline"): - article_json["byline"] = input_json["byline"] - if input_json.get("date"): - article_json["date"] = input_json["date"] - if input_json.get("content"): - article_json["content"] = input_json["content"] - article_json["plain_content"] = plain_content(article_json["content"], False, False) - article_json["plain_text"] = extract_text_blocks_as_plain_text(article_json["plain_content"]) - if input_json.get("textContent"): - article_json["plain_text"] = input_json["textContent"] - article_json["plain_text"] = re.sub(r"\n\s*\n", "\n", article_json["plain_text"]) - - return article_json - - -def find_module_path(module_name): - for package_path in site.getsitepackages(): - potential_path = os.path.join(package_path, module_name) - if os.path.exists(potential_path): - return potential_path - - return None - - -@contextmanager -def chdir(path): - """Change directory in context and return to original on exit""" - # From https://stackoverflow.com/a/37996581, couldn't find a built-in - original_path = os.getcwd() - os.chdir(path) - try: - yield - finally: - os.chdir(original_path) - - -def extract_text_blocks_as_plain_text(paragraph_html): - # Load article as DOM - soup = BeautifulSoup(paragraph_html, "html.parser") - # Select all lists - list_elements = soup.find_all(["ul", "ol"]) - # Prefix text in all list items with "* " and make lists paragraphs - for list_element in list_elements: - plain_items = "".join( - list(filter(None, [plain_text_leaf_node(li)["text"] for li in list_element.find_all("li")])) - ) - list_element.string = plain_items - list_element.name = "p" - # Select all text blocks - text_blocks = [s.parent for s in soup.find_all(string=True)] - text_blocks = [plain_text_leaf_node(block) for block in text_blocks] - # Drop empty paragraphs - text_blocks = list(filter(lambda p: p["text"] is not None, text_blocks)) - return text_blocks - - -def plain_text_leaf_node(element): - # Extract all text, stripped of any child HTML elements and normalize it - plain_text = normalize_text(element.get_text()) - if plain_text != "" and element.name == "li": - plain_text = "* {}, ".format(plain_text) - if plain_text == "": - plain_text = None - if "data-node-index" in element.attrs: - plain = {"node_index": element["data-node-index"], "text": plain_text} - else: - plain = {"text": plain_text} - return plain - - -def plain_content(readability_content, content_digests, node_indexes): - # Load article as DOM - soup = BeautifulSoup(readability_content, "html.parser") - # Make all elements plain - elements = plain_elements(soup.contents, content_digests, node_indexes) - if node_indexes: - # Add node index attributes to nodes - elements = [add_node_indexes(element) for element in elements] - # Replace article contents with plain elements - soup.contents = elements - return str(soup) - - -def plain_elements(elements, content_digests, node_indexes): - # Get plain content versions of all elements - elements = [plain_element(element, content_digests, node_indexes) for element in elements] - if content_digests: - # Add content digest attribute to nodes - elements = [add_content_digest(element) for element in elements] - return elements - - -def plain_element(element, content_digests, node_indexes): - # For lists, we make each item plain text - if is_leaf(element): - # For leaf node elements, extract the text content, discarding any HTML tags - # 1. Get element contents as text - plain_text = element.get_text() - # 2. Normalize the extracted text string to a canonical representation - plain_text = normalize_text(plain_text) - # 3. Update element content to be plain text - element.string = plain_text - elif is_text(element): - if is_non_printing(element): - # The simplified HTML may have come from Readability.js so might - # have non-printing text (e.g. Comment or CData). In this case, we - # keep the structure, but ensure that the string is empty. - element = type(element)("") - else: - plain_text = element.string - plain_text = normalize_text(plain_text) - element = type(element)(plain_text) - else: - # If not a leaf node or leaf type call recursively on child nodes, replacing - element.contents = plain_elements(element.contents, content_digests, node_indexes) - return element - - -def add_node_indexes(element, node_index="0"): - # Can't add attributes to string types - if is_text(element): - return element - # Add index to current element - element["data-node-index"] = node_index - # Add index to child elements - for local_idx, child in enumerate([c for c in element.contents if not is_text(c)], start=1): - # Can't add attributes to leaf string types - child_index = "{stem}.{local}".format(stem=node_index, local=local_idx) - add_node_indexes(child, node_index=child_index) - return element - - -def normalize_text(text): - """Normalize unicode and whitespace.""" - # Normalize unicode first to try and standardize whitespace characters as much as possible before normalizing them - text = strip_control_characters(text) - text = normalize_unicode(text) - text = normalize_whitespace(text) - return text - - -def strip_control_characters(text): - """Strip out unicode control characters which might break the parsing.""" - # Unicode control characters - # [Cc]: Other, Control [includes new lines] - # [Cf]: Other, Format - # [Cn]: Other, Not Assigned - # [Co]: Other, Private Use - # [Cs]: Other, Surrogate - control_chars = {"Cc", "Cf", "Cn", "Co", "Cs"} - retained_chars = ["\t", "\n", "\r", "\f"] - - # Remove non-printing control characters - return "".join( - [ - "" if (unicodedata.category(char) in control_chars) and (char not in retained_chars) else char - for char in text - ] - ) - - -def normalize_unicode(text): - """Normalize unicode such that things that are visually equivalent map to the same unicode string where possible.""" - normal_form = "NFKC" - text = unicodedata.normalize(normal_form, text) - return text - - -def normalize_whitespace(text): - """Replace runs of whitespace characters with a single space as this is what happens when HTML text is displayed.""" - text = regex.sub(r"\s+", " ", text) - # Remove leading and trailing whitespace - text = text.strip() - return text - - -def is_leaf(element): - return element.name in {"p", "li"} - - -def is_text(element): - return isinstance(element, NavigableString) - - -def is_non_printing(element): - return any(isinstance(element, _e) for _e in [Comment, CData]) - - -def add_content_digest(element): - if not is_text(element): - element["data-content-digest"] = content_digest(element) - return element - - -def content_digest(element): - if is_text(element): - # Hash - trimmed_string = element.string.strip() - if trimmed_string == "": - digest = "" - else: - digest = hashlib.sha256(trimmed_string.encode("utf-8")).hexdigest() - else: - contents = element.contents - num_contents = len(contents) - if num_contents == 0: - # No hash when no child elements exist - digest = "" - elif num_contents == 1: - # If single child, use digest of child - digest = content_digest(contents[0]) - else: - # Build content digest from the "non-empty" digests of child nodes - digest = hashlib.sha256() - child_digests = list(filter(lambda x: x != "", [content_digest(content) for content in contents])) - for child in child_digests: - digest.update(child.encode("utf-8")) - digest = digest.hexdigest() - return digest diff --git a/api/poetry.lock b/api/poetry.lock index 85c68cd75f1292..5c8485990cc67a 100644 --- a/api/poetry.lock +++ b/api/poetry.lock @@ -2,13 +2,13 @@ [[package]] name = "aiohappyeyeballs" -version = "2.4.0" +version = "2.4.2" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.8" files = [ - {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"}, - {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"}, + {file = "aiohappyeyeballs-2.4.2-py3-none-any.whl", hash = "sha256:8522691d9a154ba1145b157d6d5c15e5c692527ce6a53c5e5f9876977f6dab2f"}, + {file = "aiohappyeyeballs-2.4.2.tar.gz", hash = "sha256:4ca893e6c5c1f5bf3888b04cb5a3bee24995398efef6e0b9f747b5e89d84fd74"}, ] [[package]] @@ -123,20 +123,6 @@ yarl = ">=1.0,<2.0" [package.extras] speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"] -[[package]] -name = "aiohttp-retry" -version = "2.8.3" -description = "Simple retry client for aiohttp" -optional = false -python-versions = ">=3.7" -files = [ - {file = "aiohttp_retry-2.8.3-py3-none-any.whl", hash = "sha256:3aeeead8f6afe48272db93ced9440cf4eda8b6fd7ee2abb25357b7eb28525b45"}, - {file = "aiohttp_retry-2.8.3.tar.gz", hash = "sha256:9a8e637e31682ad36e1ff9f8bcba912fcfc7d7041722bc901a4b948da4d71ea9"}, -] - -[package.dependencies] -aiohttp = "*" - [[package]] name = "aiosignal" version = "1.3.1" @@ -153,13 +139,13 @@ frozenlist = ">=1.1.0" [[package]] name = "alembic" -version = "1.13.2" +version = "1.13.3" description = "A database migration tool for SQLAlchemy." optional = false python-versions = ">=3.8" files = [ - {file = "alembic-1.13.2-py3-none-any.whl", hash = "sha256:6b8733129a6224a9a711e17c99b08462dbf7cc9670ba8f2e2ae9af860ceb1953"}, - {file = "alembic-1.13.2.tar.gz", hash = "sha256:1ff0ae32975f4fd96028c39ed9bb3c867fe3af956bd7bb37343b54c9fe7445ef"}, + {file = "alembic-1.13.3-py3-none-any.whl", hash = "sha256:908e905976d15235fae59c9ac42c4c5b75cfcefe3d27c0fbf7ae15a37715d80e"}, + {file = "alembic-1.13.3.tar.gz", hash = "sha256:203503117415561e203aa14541740643a611f641517f0209fcae63e9fa09f1a2"}, ] [package.dependencies] @@ -293,13 +279,13 @@ alibabacloud-tea = "*" [[package]] name = "alibabacloud-tea" -version = "0.3.9" +version = "0.3.10" description = "The tea module of alibabaCloud Python SDK." optional = false python-versions = ">=3.6" files = [ - {file = "alibabacloud-tea-0.3.9.tar.gz", hash = "sha256:a9689770003fa9313d1995812f9fe36a2be315e5cdfc8d58de0d96808219ced9"}, - {file = "alibabacloud_tea-0.3.9-py3-none-any.whl", hash = "sha256:402fd2a92e6729f228d8c0300b182f80019edce19d83afa497aeb15fd7947f9a"}, + {file = "alibabacloud-tea-0.3.10.tar.gz", hash = "sha256:bcf972416af5d8b5e671078c2ec20296dbc792e85e68acd685730a0a016afd2a"}, + {file = "alibabacloud_tea-0.3.10-py3-none-any.whl", hash = "sha256:9136f302a3baea8a1528f500bf5d47c3727b827a09b5c14b283ca53578e30082"}, ] [package.dependencies] @@ -321,17 +307,17 @@ alibabacloud-tea = ">=0.0.1" [[package]] name = "alibabacloud-tea-openapi" -version = "0.3.11" +version = "0.3.12" description = "Alibaba Cloud openapi SDK Library for Python" optional = false python-versions = ">=3.6" files = [ - {file = "alibabacloud_tea_openapi-0.3.11.tar.gz", hash = "sha256:3f5cace1b1aeb8a64587574097403cfd066b86ee4c3c9abde587f9abfcad38de"}, + {file = "alibabacloud_tea_openapi-0.3.12.tar.gz", hash = "sha256:2e14809f357438e62c1ef4976a7655110dd54a75bbfa7d905fa3798355cfd974"}, ] [package.dependencies] -alibabacloud_credentials = ">=0.3.1,<1.0.0" -alibabacloud_gateway_spi = ">=0.0.1,<1.0.0" +alibabacloud_credentials = ">=0.3.5,<1.0.0" +alibabacloud_gateway_spi = ">=0.0.2,<1.0.0" alibabacloud_openapi_util = ">=0.2.1,<1.0.0" alibabacloud_tea_util = ">=0.3.13,<1.0.0" alibabacloud_tea_xml = ">=0.0.2,<1.0.0" @@ -429,39 +415,15 @@ files = [ {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, ] -[[package]] -name = "anthropic" -version = "0.23.1" -description = "The official Python library for the anthropic API" -optional = false -python-versions = ">=3.7" -files = [ - 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-pydantic = "*" -requests = "*" -typing-extensions = "*" - -[package.extras] -dev = ["black", "cython (>=0.29)", "flake8 (>=3.8.0)", "ipython (>=6.5.0)", "pytest (>=3.5.0)", "pytest-asyncio (>=0.14.0)", "pytest-cov (>=2.5.0)", "pytest-forked (>=1.0)", "pytest-mock (>=3.11.1)", "pytest-timeout (>=1.2.0)"] - [[package]] name = "xlrd" version = "2.0.1" @@ -10253,51 +8713,6 @@ files = [ idna = ">=2.0" multidict = ">=4.0" -[[package]] -name = "yfinance" -version = "0.2.43" -description = "Download market data from Yahoo! Finance API" -optional = false -python-versions = "*" -files = [ - {file = "yfinance-0.2.43-py2.py3-none-any.whl", hash = "sha256:11b4f5515b17450bd3bdcdc26b299aeeaea7ff9cb63d0fa0a865f460c0c7618f"}, - {file = "yfinance-0.2.43.tar.gz", hash = "sha256:32404597f325a2a2c2708aceb8d552088dd26891ac0e6018f6c5f3f2f61055f0"}, -] - -[package.dependencies] -beautifulsoup4 = ">=4.11.1" -frozendict = ">=2.3.4" -html5lib = ">=1.1" -lxml = ">=4.9.1" -multitasking = ">=0.0.7" -numpy = ">=1.16.5" -pandas = ">=1.3.0" -peewee = ">=3.16.2" -platformdirs = ">=2.0.0" -pytz = ">=2022.5" -requests = ">=2.31" - -[package.extras] -nospam = ["requests-cache (>=1.0)", "requests-ratelimiter (>=0.3.1)"] -repair = ["scipy (>=1.6.3)"] - -[[package]] -name = "zhipuai" -version = "1.0.7" -description = "A SDK library for accessing big model apis from ZhipuAI" -optional = false -python-versions = ">=3.6" -files = [ - {file = "zhipuai-1.0.7-py3-none-any.whl", hash = "sha256:360c01b8c2698f366061452e86d5a36a5ff68a576ea33940da98e4806f232530"}, - {file = "zhipuai-1.0.7.tar.gz", hash = "sha256:b80f699543d83cce8648acf1ce32bc2725d1c1c443baffa5882abc2cc704d581"}, -] - -[package.dependencies] -cachetools = "*" -dataclasses = "*" -PyJWT = "*" -requests = "*" - [[package]] name = "zipp" version = "3.20.2" @@ -10501,4 +8916,4 @@ cffi = ["cffi (>=1.11)"] [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.13" -content-hash = "c4580c22e2b220c8c80dbc3f765060a09e14874ed29b690c13a533bf0365e789" +content-hash = "46120eb2caaf416a798cfe425674e3dcf83a9c7f1b1273e7703ca32ebea21ffd" diff --git a/api/pyproject.toml b/api/pyproject.toml index e737761f3b2c0b..b5501ff228d48e 100644 --- a/api/pyproject.toml +++ b/api/pyproject.toml @@ -134,7 +134,6 @@ package-mode = false ############################################################ [tool.poetry.dependencies] -anthropic = "~0.23.1" authlib = "1.3.1" azure-identity = "1.16.1" azure-storage-blob = "12.13.0" @@ -145,10 +144,8 @@ bs4 = "~0.0.1" cachetools = "~5.3.0" celery = "~5.3.6" chardet = "~5.1.0" -cohere = "~5.2.4" cos-python-sdk-v5 = "1.9.30" esdk-obs-python = "3.24.6.1" -dashscope = { version = "~1.17.0", extras = ["tokenizer"] } flask = "~3.0.1" flask-compress = "~1.14" flask-cors = "~4.0.0" @@ -169,13 +166,12 @@ google-generativeai = "0.8.1" googleapis-common-protos = "1.63.0" gunicorn = "~22.0.0" httpx = { version = "~0.27.0", extras = ["socks"] } -huggingface-hub = "~0.16.4" jieba = "0.42.1" langfuse = "^2.48.0" langsmith = "^0.1.77" mailchimp-transactional = "~1.0.50" markdown = "~3.5.1" -novita-client = "^0.5.7" +nltk = "3.8.1" numpy = "~1.26.4" openai = "~1.29.0" openpyxl = "~3.1.5" @@ -192,9 +188,7 @@ python = ">=3.10,<3.13" python-docx = "~1.1.0" python-dotenv = "1.0.0" pyyaml = "~6.0.1" -readabilipy = "0.2.0" redis = { version = "~5.0.3", extras = ["hiredis"] } -replicate = "~0.22.0" resend = "~0.7.0" scikit-learn = "^1.5.1" sentry-sdk = { version = "~1.44.1", extras = ["flask"] } @@ -202,21 +196,15 @@ sqlalchemy = "~2.0.29" tencentcloud-sdk-python-hunyuan = "~3.0.1158" tiktoken = "~0.7.0" tokenizers = "~0.15.0" -transformers = "~4.35.0" unstructured = { version = "~0.10.27", extras = ["docx", "epub", "md", "msg", "ppt", "pptx"] } -websocket-client = "~1.7.0" werkzeug = "~3.0.1" -xinference-client = "0.15.2" yarl = "~1.9.4" -zhipuai = "1.0.7" # Before adding new dependency, consider place it in alphabet order (a-z) and suitable group. ############################################################ # Related transparent dependencies with pinned version # required by main implementations ############################################################ -azure-ai-ml = "^1.19.0" -azure-ai-inference = "^1.0.0b3" volcengine-python-sdk = {extras = ["ark"], version = "^1.0.98"} oci = "^2.133.0" tos = "^2.7.1" @@ -231,20 +219,7 @@ safetensors = "~0.4.3" ############################################################ [tool.poetry.group.tool.dependencies] -arxiv = "2.1.0" -cloudscraper = "1.2.71" -matplotlib = "~3.8.2" -newspaper3k = "0.2.8" -duckduckgo-search = "^6.2.6" -jsonpath-ng = "1.6.1" -numexpr = "~2.9.0" -opensearch-py = "2.4.0" qrcode = "~7.4.2" -twilio = "~9.0.4" -vanna = { version = "0.5.5", extras = ["postgres", "mysql", "clickhouse", "duckdb"] } -wikipedia = "1.4.0" -yfinance = "~0.2.40" -nltk = "3.8.1" ############################################################ # VDB dependencies required by vector store clients ############################################################ diff --git a/api/tests/integration_tests/model_runtime/__mock/anthropic.py b/api/tests/integration_tests/model_runtime/__mock/anthropic.py deleted file mode 100644 index 79a3dc03941c9f..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/anthropic.py +++ /dev/null @@ -1,98 +0,0 @@ -import os -from collections.abc import Iterable -from typing import Any, Literal, Union - -import anthropic -import pytest -from _pytest.monkeypatch import MonkeyPatch -from anthropic import Anthropic, Stream -from anthropic.resources import Messages -from anthropic.types import ( - ContentBlock, - ContentBlockDeltaEvent, - Message, - MessageDeltaEvent, - MessageDeltaUsage, - MessageParam, - MessageStartEvent, - MessageStopEvent, - MessageStreamEvent, - TextDelta, - Usage, -) -from anthropic.types.message_delta_event import Delta - -MOCK = os.getenv("MOCK_SWITCH", "false") == "true" - - -class MockAnthropicClass: - @staticmethod - def mocked_anthropic_chat_create_sync(model: str) -> Message: - return Message( - id="msg-123", - type="message", - role="assistant", - content=[ContentBlock(text="hello, I'm a chatbot from anthropic", type="text")], - model=model, - stop_reason="stop_sequence", - usage=Usage(input_tokens=1, output_tokens=1), - ) - - @staticmethod - def mocked_anthropic_chat_create_stream(model: str) -> Stream[MessageStreamEvent]: - full_response_text = "hello, I'm a chatbot from anthropic" - - yield MessageStartEvent( - type="message_start", - message=Message( - id="msg-123", - content=[], - role="assistant", - model=model, - stop_reason=None, - type="message", - usage=Usage(input_tokens=1, output_tokens=1), - ), - ) - - index = 0 - for i in range(0, len(full_response_text)): - yield ContentBlockDeltaEvent( - type="content_block_delta", delta=TextDelta(text=full_response_text[i], type="text_delta"), index=index - ) - - index += 1 - - yield MessageDeltaEvent( - type="message_delta", delta=Delta(stop_reason="stop_sequence"), usage=MessageDeltaUsage(output_tokens=1) - ) - - yield MessageStopEvent(type="message_stop") - - def mocked_anthropic( - self: Messages, - *, - max_tokens: int, - messages: Iterable[MessageParam], - model: str, - stream: Literal[True], - **kwargs: Any, - ) -> Union[Message, Stream[MessageStreamEvent]]: - if len(self._client.api_key) < 18: - raise anthropic.AuthenticationError("Invalid API key") - - if stream: - return MockAnthropicClass.mocked_anthropic_chat_create_stream(model=model) - else: - return MockAnthropicClass.mocked_anthropic_chat_create_sync(model=model) - - -@pytest.fixture -def setup_anthropic_mock(request, monkeypatch: MonkeyPatch): - if MOCK: - monkeypatch.setattr(Messages, "create", MockAnthropicClass.mocked_anthropic) - - yield - - if MOCK: - monkeypatch.undo() diff --git a/api/tests/integration_tests/model_runtime/__mock/fishaudio.py b/api/tests/integration_tests/model_runtime/__mock/fishaudio.py deleted file mode 100644 index bec3babeafddab..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/fishaudio.py +++ /dev/null @@ -1,82 +0,0 @@ -import os -from collections.abc import Callable -from typing import Literal - -import httpx -import pytest -from _pytest.monkeypatch import MonkeyPatch - - -def mock_get(*args, **kwargs): - if kwargs.get("headers", {}).get("Authorization") != "Bearer test": - raise httpx.HTTPStatusError( - "Invalid API key", - request=httpx.Request("GET", ""), - response=httpx.Response(401), - ) - - return httpx.Response( - 200, - json={ - "items": [ - {"title": "Model 1", "_id": "model1"}, - {"title": "Model 2", "_id": "model2"}, - ] - }, - request=httpx.Request("GET", ""), - ) - - -def mock_stream(*args, **kwargs): - class MockStreamResponse: - def __init__(self): - self.status_code = 200 - - def __enter__(self): - return self - - def __exit__(self, exc_type, exc_val, exc_tb): - pass - - def iter_bytes(self): - yield b"Mocked audio data" - - return MockStreamResponse() - - -def mock_fishaudio( - monkeypatch: MonkeyPatch, - methods: list[Literal["list-models", "tts"]], -) -> Callable[[], None]: - """ - mock fishaudio module - - :param monkeypatch: pytest monkeypatch fixture - :return: unpatch function - """ - - def unpatch() -> None: - monkeypatch.undo() - - if "list-models" in methods: - monkeypatch.setattr(httpx, "get", mock_get) - - if "tts" in methods: - monkeypatch.setattr(httpx, "stream", mock_stream) - - return unpatch - - -MOCK = os.getenv("MOCK_SWITCH", "false").lower() == "true" - - -@pytest.fixture -def setup_fishaudio_mock(request, monkeypatch): - methods = request.param if hasattr(request, "param") else [] - if MOCK: - unpatch = mock_fishaudio(monkeypatch, methods=methods) - - yield - - if MOCK: - unpatch() diff --git a/api/tests/integration_tests/model_runtime/__mock/google.py b/api/tests/integration_tests/model_runtime/__mock/google.py deleted file mode 100644 index 402bd9c2c21f69..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/google.py +++ /dev/null @@ -1,116 +0,0 @@ -from collections.abc import Generator - -import google.generativeai.types.generation_types as generation_config_types -import pytest -from _pytest.monkeypatch import MonkeyPatch -from google.ai import generativelanguage as glm -from google.ai.generativelanguage_v1beta.types import content as gag_content -from google.generativeai import GenerativeModel -from google.generativeai.client import _ClientManager, configure -from google.generativeai.types import GenerateContentResponse, content_types, safety_types -from google.generativeai.types.generation_types import BaseGenerateContentResponse - -current_api_key = "" - - -class MockGoogleResponseClass: - _done = False - - def __iter__(self): - full_response_text = "it's google!" - - for i in range(0, len(full_response_text) + 1, 1): - if i == len(full_response_text): - self._done = True - yield GenerateContentResponse( - done=True, iterator=None, result=glm.GenerateContentResponse({}), chunks=[] - ) - else: - yield GenerateContentResponse( - done=False, iterator=None, result=glm.GenerateContentResponse({}), chunks=[] - ) - - -class MockGoogleResponseCandidateClass: - finish_reason = "stop" - - @property - def content(self) -> gag_content.Content: - return gag_content.Content(parts=[gag_content.Part(text="it's google!")]) - - -class MockGoogleClass: - @staticmethod - def generate_content_sync() -> GenerateContentResponse: - return GenerateContentResponse(done=True, iterator=None, result=glm.GenerateContentResponse({}), chunks=[]) - - @staticmethod - def generate_content_stream() -> Generator[GenerateContentResponse, None, None]: - return MockGoogleResponseClass() - - def generate_content( - self: GenerativeModel, - contents: content_types.ContentsType, - *, - generation_config: generation_config_types.GenerationConfigType | None = None, - safety_settings: safety_types.SafetySettingOptions | None = None, - stream: bool = False, - **kwargs, - ) -> GenerateContentResponse: - global current_api_key - - if len(current_api_key) < 16: - raise Exception("Invalid API key") - - if stream: - return MockGoogleClass.generate_content_stream() - - return MockGoogleClass.generate_content_sync() - - @property - def generative_response_text(self) -> str: - return "it's google!" - - @property - def generative_response_candidates(self) -> list[MockGoogleResponseCandidateClass]: - return [MockGoogleResponseCandidateClass()] - - def make_client(self: _ClientManager, name: str): - global current_api_key - - if name.endswith("_async"): - name = name.split("_")[0] - cls = getattr(glm, name.title() + "ServiceAsyncClient") - else: - cls = getattr(glm, name.title() + "ServiceClient") - - # Attempt to configure using defaults. - if not self.client_config: - configure() - - client_options = self.client_config.get("client_options", None) - if client_options: - current_api_key = client_options.api_key - - def nop(self, *args, **kwargs): - pass - - original_init = cls.__init__ - cls.__init__ = nop - client: glm.GenerativeServiceClient = cls(**self.client_config) - cls.__init__ = original_init - - if not self.default_metadata: - return client - - -@pytest.fixture -def setup_google_mock(request, monkeypatch: MonkeyPatch): - monkeypatch.setattr(BaseGenerateContentResponse, "text", MockGoogleClass.generative_response_text) - monkeypatch.setattr(BaseGenerateContentResponse, "candidates", MockGoogleClass.generative_response_candidates) - monkeypatch.setattr(GenerativeModel, "generate_content", MockGoogleClass.generate_content) - monkeypatch.setattr(_ClientManager, "make_client", MockGoogleClass.make_client) - - yield - - monkeypatch.undo() diff --git a/api/tests/integration_tests/model_runtime/__mock/huggingface.py b/api/tests/integration_tests/model_runtime/__mock/huggingface.py deleted file mode 100644 index 97038ef5963e87..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/huggingface.py +++ /dev/null @@ -1,20 +0,0 @@ -import os - -import pytest -from _pytest.monkeypatch import MonkeyPatch -from huggingface_hub import InferenceClient - -from tests.integration_tests.model_runtime.__mock.huggingface_chat import MockHuggingfaceChatClass - -MOCK = os.getenv("MOCK_SWITCH", "false").lower() == "true" - - -@pytest.fixture -def setup_huggingface_mock(request, monkeypatch: MonkeyPatch): - if MOCK: - monkeypatch.setattr(InferenceClient, "text_generation", MockHuggingfaceChatClass.text_generation) - - yield - - if MOCK: - monkeypatch.undo() diff --git a/api/tests/integration_tests/model_runtime/__mock/huggingface_chat.py b/api/tests/integration_tests/model_runtime/__mock/huggingface_chat.py deleted file mode 100644 index 9ee76c935c9873..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/huggingface_chat.py +++ /dev/null @@ -1,56 +0,0 @@ -import re -from collections.abc import Generator -from typing import Any, Literal, Optional, Union - -from _pytest.monkeypatch import MonkeyPatch -from huggingface_hub import InferenceClient -from huggingface_hub.inference._text_generation import ( - Details, - StreamDetails, - TextGenerationResponse, - TextGenerationStreamResponse, - Token, -) -from huggingface_hub.utils import BadRequestError - - -class MockHuggingfaceChatClass: - @staticmethod - def generate_create_sync(model: str) -> TextGenerationResponse: - response = TextGenerationResponse( - generated_text="You can call me Miku Miku o~e~o~", - details=Details( - finish_reason="length", - generated_tokens=6, - tokens=[Token(id=0, text="You", logprob=0.0, special=False) for i in range(0, 6)], - ), - ) - - return response - - @staticmethod - def generate_create_stream(model: str) -> Generator[TextGenerationStreamResponse, None, None]: - full_text = "You can call me Miku Miku o~e~o~" - - for i in range(0, len(full_text)): - response = TextGenerationStreamResponse( - token=Token(id=i, text=full_text[i], logprob=0.0, special=False), - ) - response.generated_text = full_text[i] - response.details = StreamDetails(finish_reason="stop_sequence", generated_tokens=1) - - yield response - - def text_generation( - self: InferenceClient, prompt: str, *, stream: Literal[False] = ..., model: Optional[str] = None, **kwargs: Any - ) -> Union[TextGenerationResponse, Generator[TextGenerationStreamResponse, None, None]]: - # check if key is valid - if not re.match(r"Bearer\shf\-[a-zA-Z0-9]{16,}", self.headers["authorization"]): - raise BadRequestError("Invalid API key") - - if model is None: - raise BadRequestError("Invalid model") - - if stream: - return MockHuggingfaceChatClass.generate_create_stream(model) - return MockHuggingfaceChatClass.generate_create_sync(model) diff --git a/api/tests/integration_tests/model_runtime/__mock/huggingface_tei.py b/api/tests/integration_tests/model_runtime/__mock/huggingface_tei.py deleted file mode 100644 index b9a721c803fc52..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/huggingface_tei.py +++ /dev/null @@ -1,94 +0,0 @@ -from core.model_runtime.model_providers.huggingface_tei.tei_helper import TeiModelExtraParameter - - -class MockTEIClass: - @staticmethod - def get_tei_extra_parameter(server_url: str, model_name: str) -> TeiModelExtraParameter: - # During mock, we don't have a real server to query, so we just return a dummy value - if "rerank" in model_name: - model_type = "reranker" - else: - model_type = "embedding" - - return TeiModelExtraParameter(model_type=model_type, max_input_length=512, max_client_batch_size=1) - - @staticmethod - def invoke_tokenize(server_url: str, texts: list[str]) -> list[list[dict]]: - # Use space as token separator, and split the text into tokens - tokenized_texts = [] - for text in texts: - tokens = text.split(" ") - current_index = 0 - tokenized_text = [] - for idx, token in enumerate(tokens): - s_token = { - "id": idx, - "text": token, - "special": False, - "start": current_index, - "stop": current_index + len(token), - } - current_index += len(token) + 1 - tokenized_text.append(s_token) - tokenized_texts.append(tokenized_text) - return tokenized_texts - - @staticmethod - def invoke_embeddings(server_url: str, texts: list[str]) -> dict: - # { - # "object": "list", - # "data": [ - # { - # "object": "embedding", - # "embedding": [...], - # "index": 0 - # } - # ], - # "model": "MODEL_NAME", - # "usage": { - # "prompt_tokens": 3, - # "total_tokens": 3 - # } - # } - embeddings = [] - for idx in range(len(texts)): - embedding = [0.1] * 768 - embeddings.append( - { - "object": "embedding", - "embedding": embedding, - "index": idx, - } - ) - return { - "object": "list", - "data": embeddings, - "model": "MODEL_NAME", - "usage": { - "prompt_tokens": sum(len(text.split(" ")) for text in texts), - "total_tokens": sum(len(text.split(" ")) for text in texts), - }, - } - - @staticmethod - def invoke_rerank(server_url: str, query: str, texts: list[str]) -> list[dict]: - # Example response: - # [ - # { - # "index": 0, - # "text": "Deep Learning is ...", - # "score": 0.9950755 - # } - # ] - reranked_docs = [] - for idx, text in enumerate(texts): - reranked_docs.append( - { - "index": idx, - "text": text, - "score": 0.9, - } - ) - # For mock, only return the first document - break - return reranked_docs diff --git a/api/tests/integration_tests/model_runtime/__mock/nomic_embeddings.py b/api/tests/integration_tests/model_runtime/__mock/nomic_embeddings.py deleted file mode 100644 index 281e866e45c2e9..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/nomic_embeddings.py +++ /dev/null @@ -1,59 +0,0 @@ -import os -from collections.abc import Callable -from typing import Any, Literal, Union - -import pytest - -# import monkeypatch -from _pytest.monkeypatch import MonkeyPatch -from nomic import embed - - -def create_embedding(texts: list[str], model: str, **kwargs: Any) -> dict: - texts_len = len(texts) - - foo_embedding_sample = 0.123456 - - combined = { - "embeddings": [[foo_embedding_sample for _ in range(768)] for _ in range(texts_len)], - "usage": {"prompt_tokens": texts_len, "total_tokens": texts_len}, - "model": model, - "inference_mode": "remote", - } - - return combined - - -def mock_nomic( - monkeypatch: MonkeyPatch, - methods: list[Literal["text_embedding"]], -) -> Callable[[], None]: - """ - mock nomic module - - :param monkeypatch: pytest monkeypatch fixture - :return: unpatch function - """ - - def unpatch() -> None: - monkeypatch.undo() - - if "text_embedding" in methods: - monkeypatch.setattr(embed, "text", create_embedding) - - return unpatch - - -MOCK = os.getenv("MOCK_SWITCH", "false").lower() == "true" - - -@pytest.fixture -def setup_nomic_mock(request, monkeypatch): - methods = request.param if hasattr(request, "param") else [] - if MOCK: - unpatch = mock_nomic(monkeypatch, methods=methods) - - yield - - if MOCK: - unpatch() diff --git a/api/tests/integration_tests/model_runtime/__mock/openai.py b/api/tests/integration_tests/model_runtime/__mock/openai.py index 6637f4f212a50e..22d099739adc31 100644 --- a/api/tests/integration_tests/model_runtime/__mock/openai.py +++ b/api/tests/integration_tests/model_runtime/__mock/openai.py @@ -6,19 +6,9 @@ # import monkeypatch from _pytest.monkeypatch import MonkeyPatch -from openai.resources.audio.transcriptions import Transcriptions -from openai.resources.chat import Completions as ChatCompletions -from openai.resources.completions import Completions -from openai.resources.embeddings import Embeddings -from openai.resources.models import Models from openai.resources.moderations import Moderations -from tests.integration_tests.model_runtime.__mock.openai_chat import MockChatClass -from tests.integration_tests.model_runtime.__mock.openai_completion import MockCompletionsClass -from tests.integration_tests.model_runtime.__mock.openai_embeddings import MockEmbeddingsClass from tests.integration_tests.model_runtime.__mock.openai_moderation import MockModerationClass -from tests.integration_tests.model_runtime.__mock.openai_remote import MockModelClass -from tests.integration_tests.model_runtime.__mock.openai_speech2text import MockSpeech2TextClass def mock_openai( @@ -35,24 +25,9 @@ def mock_openai( def unpatch() -> None: monkeypatch.undo() - if "completion" in methods: - monkeypatch.setattr(Completions, "create", MockCompletionsClass.completion_create) - - if "chat" in methods: - monkeypatch.setattr(ChatCompletions, "create", MockChatClass.chat_create) - - if "remote" in methods: - monkeypatch.setattr(Models, "list", MockModelClass.list) - if "moderation" in methods: monkeypatch.setattr(Moderations, "create", MockModerationClass.moderation_create) - if "speech2text" in methods: - monkeypatch.setattr(Transcriptions, "create", MockSpeech2TextClass.speech2text_create) - - if "text_embedding" in methods: - monkeypatch.setattr(Embeddings, "create", MockEmbeddingsClass.create_embeddings) - return unpatch diff --git a/api/tests/integration_tests/model_runtime/__mock/openai_chat.py b/api/tests/integration_tests/model_runtime/__mock/openai_chat.py deleted file mode 100644 index 439f7d56e9b5d5..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/openai_chat.py +++ /dev/null @@ -1,269 +0,0 @@ -import re -from collections.abc import Generator -from json import dumps, loads -from time import time - -# import monkeypatch -from typing import Any, Literal, Optional, Union - -from openai import AzureOpenAI, OpenAI -from openai._types import NOT_GIVEN, NotGiven -from openai.resources.chat.completions import Completions -from openai.types import Completion as CompletionMessage -from openai.types.chat import ( - ChatCompletion, - ChatCompletionChunk, - ChatCompletionMessageParam, - ChatCompletionMessageToolCall, - ChatCompletionToolChoiceOptionParam, - ChatCompletionToolParam, - completion_create_params, -) -from openai.types.chat.chat_completion import ChatCompletion as _ChatCompletion -from openai.types.chat.chat_completion import Choice as _ChatCompletionChoice -from openai.types.chat.chat_completion_chunk import ( - Choice, - ChoiceDelta, - ChoiceDeltaFunctionCall, - ChoiceDeltaToolCall, - ChoiceDeltaToolCallFunction, -) -from openai.types.chat.chat_completion_message import ChatCompletionMessage, FunctionCall -from openai.types.chat.chat_completion_message_tool_call import Function -from openai.types.completion_usage import CompletionUsage - -from core.model_runtime.errors.invoke import InvokeAuthorizationError - - -class MockChatClass: - @staticmethod - def generate_function_call( - functions: list[completion_create_params.Function] | NotGiven = NOT_GIVEN, - ) -> Optional[FunctionCall]: - if not functions or len(functions) == 0: - return None - function: completion_create_params.Function = functions[0] - function_name = function["name"] - function_description = function["description"] - function_parameters = function["parameters"] - function_parameters_type = function_parameters["type"] - if function_parameters_type != "object": - return None - function_parameters_properties = function_parameters["properties"] - function_parameters_required = function_parameters["required"] - parameters = {} - for parameter_name, parameter in function_parameters_properties.items(): - if parameter_name not in function_parameters_required: - continue - parameter_type = parameter["type"] - if parameter_type == "string": - if "enum" in parameter: - if len(parameter["enum"]) == 0: - continue - parameters[parameter_name] = parameter["enum"][0] - else: - parameters[parameter_name] = "kawaii" - elif parameter_type == "integer": - parameters[parameter_name] = 114514 - elif parameter_type == "number": - parameters[parameter_name] = 1919810.0 - elif parameter_type == "boolean": - parameters[parameter_name] = True - - return FunctionCall(name=function_name, arguments=dumps(parameters)) - - @staticmethod - def generate_tool_calls(tools=NOT_GIVEN) -> Optional[list[ChatCompletionMessageToolCall]]: - list_tool_calls = [] - if not tools or len(tools) == 0: - return None - tool = tools[0] - - if "type" in tools and tools["type"] != "function": - return None - - function = tool["function"] - - function_call = MockChatClass.generate_function_call(functions=[function]) - if function_call is None: - return None - - list_tool_calls.append( - ChatCompletionMessageToolCall( - id="sakurajima-mai", - function=Function( - name=function_call.name, - arguments=function_call.arguments, - ), - type="function", - ) - ) - - return list_tool_calls - - @staticmethod - def mocked_openai_chat_create_sync( - model: str, - functions: list[completion_create_params.Function] | NotGiven = NOT_GIVEN, - tools: list[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, - ) -> CompletionMessage: - tool_calls = [] - function_call = MockChatClass.generate_function_call(functions=functions) - if not function_call: - tool_calls = MockChatClass.generate_tool_calls(tools=tools) - - return _ChatCompletion( - id="cmpl-3QJQa5jXJ5Z5X", - choices=[ - _ChatCompletionChoice( - finish_reason="content_filter", - index=0, - message=ChatCompletionMessage( - content="elaina", role="assistant", function_call=function_call, tool_calls=tool_calls - ), - ) - ], - created=int(time()), - model=model, - object="chat.completion", - system_fingerprint="", - usage=CompletionUsage( - prompt_tokens=2, - completion_tokens=1, - total_tokens=3, - ), - ) - - @staticmethod - def mocked_openai_chat_create_stream( - model: str, - functions: list[completion_create_params.Function] | NotGiven = NOT_GIVEN, - tools: list[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, - ) -> Generator[ChatCompletionChunk, None, None]: - tool_calls = [] - function_call = MockChatClass.generate_function_call(functions=functions) - if not function_call: - tool_calls = MockChatClass.generate_tool_calls(tools=tools) - - full_text = "Hello, world!\n\n```python\nprint('Hello, world!')\n```" - for i in range(0, len(full_text) + 1): - if i == len(full_text): - yield ChatCompletionChunk( - id="cmpl-3QJQa5jXJ5Z5X", - choices=[ - Choice( - delta=ChoiceDelta( - content="", - function_call=ChoiceDeltaFunctionCall( - name=function_call.name, - arguments=function_call.arguments, - ) - if function_call - else None, - role="assistant", - tool_calls=[ - ChoiceDeltaToolCall( - index=0, - id="misaka-mikoto", - function=ChoiceDeltaToolCallFunction( - name=tool_calls[0].function.name, - arguments=tool_calls[0].function.arguments, - ), - type="function", - ) - ] - if tool_calls and len(tool_calls) > 0 - else None, - ), - finish_reason="function_call", - index=0, - ) - ], - created=int(time()), - model=model, - object="chat.completion.chunk", - system_fingerprint="", - usage=CompletionUsage( - prompt_tokens=2, - completion_tokens=17, - total_tokens=19, - ), - ) - else: - yield ChatCompletionChunk( - id="cmpl-3QJQa5jXJ5Z5X", - choices=[ - Choice( - delta=ChoiceDelta( - content=full_text[i], - role="assistant", - ), - finish_reason="content_filter", - index=0, - ) - ], - created=int(time()), - model=model, - object="chat.completion.chunk", - system_fingerprint="", - ) - - def chat_create( - self: Completions, - *, - messages: list[ChatCompletionMessageParam], - model: Union[ - str, - Literal[ - "gpt-4-1106-preview", - "gpt-4-vision-preview", - "gpt-4", - "gpt-4-0314", - "gpt-4-0613", - "gpt-4-32k", - "gpt-4-32k-0314", - "gpt-4-32k-0613", - "gpt-3.5-turbo-1106", - "gpt-3.5-turbo", - "gpt-3.5-turbo-16k", - "gpt-3.5-turbo-0301", - "gpt-3.5-turbo-0613", - "gpt-3.5-turbo-16k-0613", - ], - ], - functions: list[completion_create_params.Function] | NotGiven = NOT_GIVEN, - response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN, - stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN, - tools: list[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, - **kwargs: Any, - ): - openai_models = [ - "gpt-4-1106-preview", - "gpt-4-vision-preview", - "gpt-4", - "gpt-4-0314", - "gpt-4-0613", - "gpt-4-32k", - "gpt-4-32k-0314", - "gpt-4-32k-0613", - "gpt-3.5-turbo-1106", - "gpt-3.5-turbo", - "gpt-3.5-turbo-16k", - "gpt-3.5-turbo-0301", - "gpt-3.5-turbo-0613", - "gpt-3.5-turbo-16k-0613", - ] - azure_openai_models = ["gpt35", "gpt-4v", "gpt-35-turbo"] - if not re.match(r"^(https?):\/\/[^\s\/$.?#].[^\s]*$", str(self._client.base_url)): - raise InvokeAuthorizationError("Invalid base url") - if model in openai_models + azure_openai_models: - if not re.match(r"sk-[a-zA-Z0-9]{24,}$", self._client.api_key) and type(self._client) == OpenAI: - # sometime, provider use OpenAI compatible API will not have api key or have different api key format - # so we only check if model is in openai_models - raise InvokeAuthorizationError("Invalid api key") - if len(self._client.api_key) < 18 and type(self._client) == AzureOpenAI: - raise InvokeAuthorizationError("Invalid api key") - if stream: - return MockChatClass.mocked_openai_chat_create_stream(model=model, functions=functions, tools=tools) - - return MockChatClass.mocked_openai_chat_create_sync(model=model, functions=functions, tools=tools) diff --git a/api/tests/integration_tests/model_runtime/__mock/openai_completion.py b/api/tests/integration_tests/model_runtime/__mock/openai_completion.py deleted file mode 100644 index 14223668e036d9..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/openai_completion.py +++ /dev/null @@ -1,130 +0,0 @@ -import re -from collections.abc import Generator -from time import time - -# import monkeypatch -from typing import Any, Literal, Optional, Union - -from openai import AzureOpenAI, BadRequestError, OpenAI -from openai._types import NOT_GIVEN, NotGiven -from openai.resources.completions import Completions -from openai.types import Completion as CompletionMessage -from openai.types.completion import CompletionChoice -from openai.types.completion_usage import CompletionUsage - -from core.model_runtime.errors.invoke import InvokeAuthorizationError - - -class MockCompletionsClass: - @staticmethod - def mocked_openai_completion_create_sync(model: str) -> CompletionMessage: - return CompletionMessage( - id="cmpl-3QJQa5jXJ5Z5X", - object="text_completion", - created=int(time()), - model=model, - system_fingerprint="", - choices=[ - CompletionChoice( - text="mock", - index=0, - logprobs=None, - finish_reason="stop", - ) - ], - usage=CompletionUsage( - prompt_tokens=2, - completion_tokens=1, - total_tokens=3, - ), - ) - - @staticmethod - def mocked_openai_completion_create_stream(model: str) -> Generator[CompletionMessage, None, None]: - full_text = "Hello, world!\n\n```python\nprint('Hello, world!')\n```" - for i in range(0, len(full_text) + 1): - if i == len(full_text): - yield CompletionMessage( - id="cmpl-3QJQa5jXJ5Z5X", - object="text_completion", - created=int(time()), - model=model, - system_fingerprint="", - choices=[ - CompletionChoice( - text="", - index=0, - logprobs=None, - finish_reason="stop", - ) - ], - usage=CompletionUsage( - prompt_tokens=2, - completion_tokens=17, - total_tokens=19, - ), - ) - else: - yield CompletionMessage( - id="cmpl-3QJQa5jXJ5Z5X", - object="text_completion", - created=int(time()), - model=model, - system_fingerprint="", - choices=[ - CompletionChoice(text=full_text[i], index=0, logprobs=None, finish_reason="content_filter") - ], - ) - - def completion_create( - self: Completions, - *, - model: Union[ - str, - Literal[ - "babbage-002", - "davinci-002", - "gpt-3.5-turbo-instruct", - "text-davinci-003", - "text-davinci-002", - "text-davinci-001", - "code-davinci-002", - "text-curie-001", - "text-babbage-001", - "text-ada-001", - ], - ], - prompt: Union[str, list[str], list[int], list[list[int]], None], - stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN, - **kwargs: Any, - ): - openai_models = [ - "babbage-002", - "davinci-002", - "gpt-3.5-turbo-instruct", - "text-davinci-003", - "text-davinci-002", - "text-davinci-001", - "code-davinci-002", - "text-curie-001", - "text-babbage-001", - "text-ada-001", - ] - azure_openai_models = ["gpt-35-turbo-instruct"] - - if not re.match(r"^(https?):\/\/[^\s\/$.?#].[^\s]*$", str(self._client.base_url)): - raise InvokeAuthorizationError("Invalid base url") - if model in openai_models + azure_openai_models: - if not re.match(r"sk-[a-zA-Z0-9]{24,}$", self._client.api_key) and type(self._client) == OpenAI: - # sometime, provider use OpenAI compatible API will not have api key or have different api key format - # so we only check if model is in openai_models - raise InvokeAuthorizationError("Invalid api key") - if len(self._client.api_key) < 18 and type(self._client) == AzureOpenAI: - raise InvokeAuthorizationError("Invalid api key") - - if not prompt: - raise BadRequestError("Invalid prompt") - if stream: - return MockCompletionsClass.mocked_openai_completion_create_stream(model=model) - - return MockCompletionsClass.mocked_openai_completion_create_sync(model=model) diff --git a/api/tests/integration_tests/model_runtime/__mock/openai_embeddings.py b/api/tests/integration_tests/model_runtime/__mock/openai_embeddings.py deleted file mode 100644 index e27b9891f5c8a8..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/openai_embeddings.py +++ /dev/null @@ -1,58 +0,0 @@ -import re -from typing import Any, Literal, Union - -from openai import OpenAI -from openai._types import NOT_GIVEN, NotGiven -from openai.resources.embeddings import Embeddings -from openai.types.create_embedding_response import CreateEmbeddingResponse, Usage -from openai.types.embedding import Embedding - -from core.model_runtime.errors.invoke import InvokeAuthorizationError - - -class MockEmbeddingsClass: - def create_embeddings( - self: Embeddings, - *, - input: Union[str, list[str], list[int], list[list[int]]], - model: Union[str, Literal["text-embedding-ada-002"]], - encoding_format: Literal["float", "base64"] | NotGiven = NOT_GIVEN, - **kwargs: Any, - ) -> CreateEmbeddingResponse: - if isinstance(input, str): - input = [input] - - if not re.match(r"^(https?):\/\/[^\s\/$.?#].[^\s]*$", str(self._client.base_url)): - raise InvokeAuthorizationError("Invalid base url") - - if len(self._client.api_key) < 18: - raise InvokeAuthorizationError("Invalid API key") - - if encoding_format == "float": - return CreateEmbeddingResponse( - data=[ - Embedding(embedding=[0.23333 for _ in range(233)], index=i, object="embedding") - for i in range(len(input)) - ], - model=model, - object="list", - # marked: usage of embeddings should equal the number of testcase - usage=Usage(prompt_tokens=2, total_tokens=2), - ) - - embeddings = "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" # noqa: E501 - - data = [] - for i, text in enumerate(input): - obj = Embedding(embedding=[], index=i, object="embedding") - obj.embedding = embeddings - - data.append(obj) - - return CreateEmbeddingResponse( - data=data, - model=model, - object="list", - # marked: usage of embeddings should equal the number of testcase - usage=Usage(prompt_tokens=2, total_tokens=2), - ) diff --git a/api/tests/integration_tests/model_runtime/__mock/openai_remote.py b/api/tests/integration_tests/model_runtime/__mock/openai_remote.py deleted file mode 100644 index cb8f2495438783..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/openai_remote.py +++ /dev/null @@ -1,23 +0,0 @@ -from time import time - -from openai.resources.models import Models -from openai.types.model import Model - - -class MockModelClass: - """ - mock class for openai.models.Models - """ - - def list( - self, - **kwargs, - ) -> list[Model]: - return [ - Model( - id="ft:gpt-3.5-turbo-0613:personal::8GYJLPDQ", - created=int(time()), - object="model", - owned_by="organization:org-123", - ) - ] diff --git a/api/tests/integration_tests/model_runtime/__mock/openai_speech2text.py b/api/tests/integration_tests/model_runtime/__mock/openai_speech2text.py deleted file mode 100644 index a51dcab4be7467..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/openai_speech2text.py +++ /dev/null @@ -1,29 +0,0 @@ -import re -from typing import Any, Literal, Union - -from openai._types import NOT_GIVEN, FileTypes, NotGiven -from openai.resources.audio.transcriptions import Transcriptions -from openai.types.audio.transcription import Transcription - -from core.model_runtime.errors.invoke import InvokeAuthorizationError - - -class MockSpeech2TextClass: - def speech2text_create( - self: Transcriptions, - *, - file: FileTypes, - model: Union[str, Literal["whisper-1"]], - language: str | NotGiven = NOT_GIVEN, - prompt: str | NotGiven = NOT_GIVEN, - response_format: Literal["json", "text", "srt", "verbose_json", "vtt"] | NotGiven = NOT_GIVEN, - temperature: float | NotGiven = NOT_GIVEN, - **kwargs: Any, - ) -> Transcription: - if not re.match(r"^(https?):\/\/[^\s\/$.?#].[^\s]*$", str(self._client.base_url)): - raise InvokeAuthorizationError("Invalid base url") - - if len(self._client.api_key) < 18: - raise InvokeAuthorizationError("Invalid API key") - - return Transcription(text="1, 2, 3, 4, 5, 6, 7, 8, 9, 10") diff --git a/api/tests/integration_tests/model_runtime/__mock/xinference.py b/api/tests/integration_tests/model_runtime/__mock/xinference.py deleted file mode 100644 index 8deb50635f3d56..00000000000000 --- a/api/tests/integration_tests/model_runtime/__mock/xinference.py +++ /dev/null @@ -1,170 +0,0 @@ -import os -import re -from typing import Union - -import pytest -from _pytest.monkeypatch import MonkeyPatch -from requests import Response -from requests.exceptions import ConnectionError -from requests.sessions import Session -from xinference_client.client.restful.restful_client import ( - Client, - RESTfulChatModelHandle, - RESTfulEmbeddingModelHandle, - RESTfulGenerateModelHandle, - RESTfulRerankModelHandle, -) -from xinference_client.types import Embedding, EmbeddingData, EmbeddingUsage - - -class MockXinferenceClass: - def get_chat_model(self: Client, model_uid: str) -> Union[RESTfulGenerateModelHandle, RESTfulChatModelHandle]: - if not re.match(r"https?:\/\/[^\s\/$.?#].[^\s]*$", self.base_url): - raise RuntimeError("404 Not Found") - - if "generate" == model_uid: - return RESTfulGenerateModelHandle(model_uid, base_url=self.base_url, auth_headers={}) - if "chat" == model_uid: - return RESTfulChatModelHandle(model_uid, base_url=self.base_url, auth_headers={}) - if "embedding" == model_uid: - return RESTfulEmbeddingModelHandle(model_uid, base_url=self.base_url, auth_headers={}) - if "rerank" == model_uid: - return RESTfulRerankModelHandle(model_uid, base_url=self.base_url, auth_headers={}) - raise RuntimeError("404 Not Found") - - def get(self: Session, url: str, **kwargs): - response = Response() - if "v1/models/" in url: - # get model uid - model_uid = url.split("/")[-1] or "" - if not re.match( - r"[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}", model_uid - ) and model_uid not in {"generate", "chat", "embedding", "rerank"}: - response.status_code = 404 - response._content = b"{}" - return response - - # check if url is valid - if not re.match(r"^(https?):\/\/[^\s\/$.?#].[^\s]*$", url): - response.status_code = 404 - response._content = b"{}" - return response - - if model_uid in {"generate", "chat"}: - response.status_code = 200 - response._content = b"""{ - "model_type": "LLM", - "address": "127.0.0.1:43877", - "accelerators": [ - "0", - "1" - ], - "model_name": "chatglm3-6b", - "model_lang": [ - "en" - ], - "model_ability": [ - "generate", - "chat" - ], - "model_description": "latest chatglm3", - "model_format": "pytorch", - "model_size_in_billions": 7, - "quantization": "none", - "model_hub": "huggingface", - "revision": null, - "context_length": 2048, - "replica": 1 - }""" - return response - - elif model_uid == "embedding": - response.status_code = 200 - response._content = b"""{ - "model_type": "embedding", - "address": "127.0.0.1:43877", - "accelerators": [ - "0", - "1" - ], - "model_name": "bge", - "model_lang": [ - "en" - ], - "revision": null, - "max_tokens": 512 - }""" - return response - - elif "v1/cluster/auth" in url: - response.status_code = 200 - response._content = b"""{ - "auth": true - }""" - return response - - def _check_cluster_authenticated(self): - self._cluster_authed = True - - def rerank( - self: RESTfulRerankModelHandle, documents: list[str], query: str, top_n: int, return_documents: bool - ) -> dict: - # check if self._model_uid is a valid uuid - if ( - not re.match(r"[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}", self._model_uid) - and self._model_uid != "rerank" - ): - raise RuntimeError("404 Not Found") - - if not re.match(r"^(https?):\/\/[^\s\/$.?#].[^\s]*$", self._base_url): - raise RuntimeError("404 Not Found") - - if top_n is None: - top_n = 1 - - return { - "results": [ - {"index": i, "document": doc, "relevance_score": 0.9} for i, doc in enumerate(documents[:top_n]) - ] - } - - def create_embedding(self: RESTfulGenerateModelHandle, input: Union[str, list[str]], **kwargs) -> dict: - # check if self._model_uid is a valid uuid - if ( - not re.match(r"[a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12}", self._model_uid) - and self._model_uid != "embedding" - ): - raise RuntimeError("404 Not Found") - - if isinstance(input, str): - input = [input] - ipt_len = len(input) - - embedding = Embedding( - object="list", - model=self._model_uid, - data=[ - EmbeddingData(index=i, object="embedding", embedding=[1919.810 for _ in range(768)]) - for i in range(ipt_len) - ], - usage=EmbeddingUsage(prompt_tokens=ipt_len, total_tokens=ipt_len), - ) - - return embedding - - -MOCK = os.getenv("MOCK_SWITCH", "false").lower() == "true" - - -@pytest.fixture -def setup_xinference_mock(request, monkeypatch: MonkeyPatch): - if MOCK: - monkeypatch.setattr(Client, "get_model", MockXinferenceClass.get_chat_model) - monkeypatch.setattr(Client, "_check_cluster_authenticated", MockXinferenceClass._check_cluster_authenticated) - monkeypatch.setattr(Session, "get", MockXinferenceClass.get) - monkeypatch.setattr(RESTfulEmbeddingModelHandle, "create_embedding", MockXinferenceClass.create_embedding) - monkeypatch.setattr(RESTfulRerankModelHandle, "rerank", MockXinferenceClass.rerank) - yield - - if MOCK: - monkeypatch.undo() diff --git a/api/tests/integration_tests/model_runtime/anthropic/__init__.py b/api/tests/integration_tests/model_runtime/anthropic/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/anthropic/test_llm.py b/api/tests/integration_tests/model_runtime/anthropic/test_llm.py deleted file mode 100644 index 8f7e9ec48743bf..00000000000000 --- a/api/tests/integration_tests/model_runtime/anthropic/test_llm.py +++ /dev/null @@ -1,92 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.anthropic.llm.llm import AnthropicLargeLanguageModel -from tests.integration_tests.model_runtime.__mock.anthropic import setup_anthropic_mock - - -@pytest.mark.parametrize("setup_anthropic_mock", [["none"]], indirect=True) -def test_validate_credentials(setup_anthropic_mock): - model = AnthropicLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="claude-instant-1.2", credentials={"anthropic_api_key": "invalid_key"}) - - model.validate_credentials( - model="claude-instant-1.2", credentials={"anthropic_api_key": os.environ.get("ANTHROPIC_API_KEY")} - ) - - -@pytest.mark.parametrize("setup_anthropic_mock", [["none"]], indirect=True) -def test_invoke_model(setup_anthropic_mock): - model = AnthropicLargeLanguageModel() - - response = model.invoke( - model="claude-instant-1.2", - credentials={ - "anthropic_api_key": os.environ.get("ANTHROPIC_API_KEY"), - "anthropic_api_url": os.environ.get("ANTHROPIC_API_URL"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "top_p": 1.0, "max_tokens": 10}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -@pytest.mark.parametrize("setup_anthropic_mock", [["none"]], indirect=True) -def test_invoke_stream_model(setup_anthropic_mock): - model = AnthropicLargeLanguageModel() - - response = model.invoke( - model="claude-instant-1.2", - credentials={"anthropic_api_key": os.environ.get("ANTHROPIC_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = AnthropicLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="claude-instant-1.2", - credentials={"anthropic_api_key": os.environ.get("ANTHROPIC_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 18 diff --git a/api/tests/integration_tests/model_runtime/anthropic/test_provider.py b/api/tests/integration_tests/model_runtime/anthropic/test_provider.py deleted file mode 100644 index 6f1e50f431849f..00000000000000 --- a/api/tests/integration_tests/model_runtime/anthropic/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.anthropic.anthropic import AnthropicProvider -from tests.integration_tests.model_runtime.__mock.anthropic import setup_anthropic_mock - - -@pytest.mark.parametrize("setup_anthropic_mock", [["none"]], indirect=True) -def 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b/api/tests/integration_tests/model_runtime/azure_ai_studio/test_llm.py deleted file mode 100644 index 8655b43d8f0b3d..00000000000000 --- a/api/tests/integration_tests/model_runtime/azure_ai_studio/test_llm.py +++ /dev/null @@ -1,113 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.azure_ai_studio.llm.llm import AzureAIStudioLargeLanguageModel -from tests.integration_tests.model_runtime.__mock.azure_ai_studio import setup_azure_ai_studio_mock - - -@pytest.mark.parametrize("setup_azure_ai_studio_mock", [["chat"]], indirect=True) -def test_validate_credentials(setup_azure_ai_studio_mock): - model = AzureAIStudioLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="gpt-35-turbo", - credentials={"api_key": "invalid_key", "api_base": os.getenv("AZURE_AI_STUDIO_API_BASE")}, - ) - - model.validate_credentials( - model="gpt-35-turbo", - credentials={ - "api_key": os.getenv("AZURE_AI_STUDIO_API_KEY"), - "api_base": os.getenv("AZURE_AI_STUDIO_API_BASE"), - }, - ) - - -@pytest.mark.parametrize("setup_azure_ai_studio_mock", [["chat"]], indirect=True) -def test_invoke_model(setup_azure_ai_studio_mock): - model = AzureAIStudioLargeLanguageModel() - - result = model.invoke( - model="gpt-35-turbo", - credentials={ - "api_key": os.getenv("AZURE_AI_STUDIO_API_KEY"), - "api_base": os.getenv("AZURE_AI_STUDIO_API_BASE"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_azure_ai_studio_mock", [["chat"]], indirect=True) -def test_invoke_stream_model(setup_azure_ai_studio_mock): - model = AzureAIStudioLargeLanguageModel() - - result = model.invoke( - model="gpt-35-turbo", - credentials={ - "api_key": os.getenv("AZURE_AI_STUDIO_API_KEY"), - "api_base": os.getenv("AZURE_AI_STUDIO_API_BASE"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - if chunk.delta.finish_reason is not None: - assert chunk.delta.usage is not None - assert chunk.delta.usage.completion_tokens > 0 - - -def test_get_num_tokens(): - model = AzureAIStudioLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="gpt-35-turbo", - credentials={ - "api_key": os.getenv("AZURE_AI_STUDIO_API_KEY"), - "api_base": os.getenv("AZURE_AI_STUDIO_API_BASE"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/azure_ai_studio/test_provider.py b/api/tests/integration_tests/model_runtime/azure_ai_studio/test_provider.py deleted file mode 100644 index 8afe38b09b9f02..00000000000000 --- a/api/tests/integration_tests/model_runtime/azure_ai_studio/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.azure_ai_studio.azure_ai_studio import AzureAIStudioProvider - - -def test_validate_provider_credentials(): - provider = AzureAIStudioProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials( - credentials={"api_key": os.getenv("AZURE_AI_STUDIO_API_KEY"), "api_base": os.getenv("AZURE_AI_STUDIO_API_BASE")} - ) diff --git a/api/tests/integration_tests/model_runtime/azure_ai_studio/test_rerank.py b/api/tests/integration_tests/model_runtime/azure_ai_studio/test_rerank.py deleted file mode 100644 index 466facc5fffcf6..00000000000000 --- a/api/tests/integration_tests/model_runtime/azure_ai_studio/test_rerank.py +++ /dev/null @@ -1,50 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.rerank_entities import RerankResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.azure_ai_studio.rerank.rerank import AzureAIStudioRerankModel - - -def test_validate_credentials(): - model = AzureAIStudioRerankModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="azure-ai-studio-rerank-v1", - credentials={"api_key": "invalid_key", "api_base": os.getenv("AZURE_AI_STUDIO_API_BASE")}, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - - -def test_invoke_model(): - model = AzureAIStudioRerankModel() - - result = model.invoke( - model="azure-ai-studio-rerank-v1", - credentials={ - "api_key": os.getenv("AZURE_AI_STUDIO_JWT_TOKEN"), - "api_base": os.getenv("AZURE_AI_STUDIO_API_BASE"), - }, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - - assert isinstance(result, RerankResult) - assert len(result.docs) == 1 - assert result.docs[0].index == 1 - assert result.docs[0].score >= 0.8 diff --git a/api/tests/integration_tests/model_runtime/azure_openai/__init__.py b/api/tests/integration_tests/model_runtime/azure_openai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/azure_openai/test_llm.py b/api/tests/integration_tests/model_runtime/azure_openai/test_llm.py deleted file mode 100644 index 8f50ebf7a6d03f..00000000000000 --- a/api/tests/integration_tests/model_runtime/azure_openai/test_llm.py +++ /dev/null @@ -1,290 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.azure_openai.llm.llm import AzureOpenAILargeLanguageModel -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_credentials_for_chat_model(setup_openai_mock): - model = AzureOpenAILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="gpt35", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": "invalid_key", - "base_model_name": "gpt-35-turbo", - }, - ) - - model.validate_credentials( - model="gpt35", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "gpt-35-turbo", - }, - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["completion"]], indirect=True) -def test_validate_credentials_for_completion_model(setup_openai_mock): - model = AzureOpenAILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="gpt-35-turbo-instruct", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": "invalid_key", - "base_model_name": "gpt-35-turbo-instruct", - }, - ) - - model.validate_credentials( - model="gpt-35-turbo-instruct", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "gpt-35-turbo-instruct", - }, - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["completion"]], indirect=True) -def test_invoke_completion_model(setup_openai_mock): - model = AzureOpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-35-turbo-instruct", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "gpt-35-turbo-instruct", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.0, "max_tokens": 1}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["completion"]], indirect=True) -def test_invoke_stream_completion_model(setup_openai_mock): - model = AzureOpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-35-turbo-instruct", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "gpt-35-turbo-instruct", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model(setup_openai_mock): - model = AzureOpenAILargeLanguageModel() - - result = model.invoke( - model="gpt35", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "gpt-35-turbo", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.0, - "top_p": 1.0, - "presence_penalty": 0.0, - "frequency_penalty": 0.0, - "max_tokens": 10, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_stream_chat_model(setup_openai_mock): - model = AzureOpenAILargeLanguageModel() - - result = model.invoke( - model="gpt35", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "gpt-35-turbo", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - if chunk.delta.finish_reason is not None: - assert chunk.delta.usage is not None - assert chunk.delta.usage.completion_tokens > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model_with_vision(setup_openai_mock): - model = AzureOpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-4v", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "gpt-4-vision-preview", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content=[ - TextPromptMessageContent( - data="Hello World!", - ), - ImagePromptMessageContent( - 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" - ), - ] - ), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model_with_tools(setup_openai_mock): - model = AzureOpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-35-turbo", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "gpt-35-turbo", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content="what's the weather today in London?", - ), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ), - PromptMessageTool( - name="get_stock_price", - description="Get the current stock price", - parameters={ - "type": "object", - "properties": {"symbol": {"type": "string", "description": "The stock symbol"}}, - "required": ["symbol"], - }, - ), - ], - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert isinstance(result.message, AssistantPromptMessage) - assert len(result.message.tool_calls) > 0 - - -def test_get_num_tokens(): - model = AzureOpenAILargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="gpt-35-turbo-instruct", - credentials={"base_model_name": "gpt-35-turbo-instruct"}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - ) - - assert num_tokens == 3 - - num_tokens = model.get_num_tokens( - model="gpt35", - credentials={"base_model_name": "gpt-35-turbo"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/azure_openai/test_text_embedding.py b/api/tests/integration_tests/model_runtime/azure_openai/test_text_embedding.py deleted file mode 100644 index a1ae2b2e5b740c..00000000000000 --- a/api/tests/integration_tests/model_runtime/azure_openai/test_text_embedding.py +++ /dev/null @@ -1,62 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.azure_openai.text_embedding.text_embedding import AzureOpenAITextEmbeddingModel -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["text_embedding"]], indirect=True) -def test_validate_credentials(setup_openai_mock): - model = AzureOpenAITextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="embedding", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": "invalid_key", - "base_model_name": "text-embedding-ada-002", - }, - ) - - model.validate_credentials( - model="embedding", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "text-embedding-ada-002", - }, - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["text_embedding"]], indirect=True) -def test_invoke_model(setup_openai_mock): - model = AzureOpenAITextEmbeddingModel() - - result = model.invoke( - model="embedding", - credentials={ - "openai_api_base": os.environ.get("AZURE_OPENAI_API_BASE"), - "openai_api_key": os.environ.get("AZURE_OPENAI_API_KEY"), - "base_model_name": "text-embedding-ada-002", - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 2 - - -def test_get_num_tokens(): - model = AzureOpenAITextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="embedding", credentials={"base_model_name": "text-embedding-ada-002"}, texts=["hello", "world"] - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/baichuan/__init__.py b/api/tests/integration_tests/model_runtime/baichuan/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/baichuan/test_llm.py b/api/tests/integration_tests/model_runtime/baichuan/test_llm.py deleted file mode 100644 index fe7fe968911439..00000000000000 --- a/api/tests/integration_tests/model_runtime/baichuan/test_llm.py +++ /dev/null @@ -1,172 +0,0 @@ -import os -from collections.abc import Generator -from time import sleep - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.baichuan.llm.llm import BaichuanLanguageModel - - -def test_predefined_models(): - model = BaichuanLanguageModel() - model_schemas = model.predefined_models() - assert len(model_schemas) >= 1 - assert isinstance(model_schemas[0], AIModelEntity) - - -def test_validate_credentials_for_chat_model(): - sleep(3) - model = BaichuanLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="baichuan2-turbo", credentials={"api_key": "invalid_key", "secret_key": "invalid_key"} - ) - - model.validate_credentials( - model="baichuan2-turbo", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - "secret_key": os.environ.get("BAICHUAN_SECRET_KEY"), - }, - ) - - -def test_invoke_model(): - sleep(3) - model = BaichuanLanguageModel() - - response = model.invoke( - model="baichuan2-turbo", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - "secret_key": os.environ.get("BAICHUAN_SECRET_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_model_with_system_message(): - sleep(3) - model = BaichuanLanguageModel() - - response = model.invoke( - model="baichuan2-turbo", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - "secret_key": os.environ.get("BAICHUAN_SECRET_KEY"), - }, - prompt_messages=[ - SystemPromptMessage(content="请记住你是Kasumi。"), - UserPromptMessage(content="现在告诉我你是谁？"), - ], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_stream_model(): - sleep(3) - model = BaichuanLanguageModel() - - response = model.invoke( - model="baichuan2-turbo", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - "secret_key": os.environ.get("BAICHUAN_SECRET_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_invoke_with_search(): - sleep(3) - model = BaichuanLanguageModel() - - response = model.invoke( - model="baichuan2-turbo", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - "secret_key": os.environ.get("BAICHUAN_SECRET_KEY"), - }, - prompt_messages=[UserPromptMessage(content="北京今天的天气怎么样")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - "with_search_enhance": True, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - total_message = "" - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if not chunk.delta.finish_reason else True - total_message += chunk.delta.message.content - - assert "不" not in total_message - - -def test_get_num_tokens(): - sleep(3) - model = BaichuanLanguageModel() - - response = model.get_num_tokens( - model="baichuan2-turbo", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - "secret_key": os.environ.get("BAICHUAN_SECRET_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - tools=[], - ) - - assert isinstance(response, int) - assert response == 9 diff --git a/api/tests/integration_tests/model_runtime/baichuan/test_provider.py b/api/tests/integration_tests/model_runtime/baichuan/test_provider.py deleted file mode 100644 index 4036edfb7a7062..00000000000000 --- a/api/tests/integration_tests/model_runtime/baichuan/test_provider.py +++ /dev/null @@ -1,15 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.baichuan.baichuan import BaichuanProvider - - -def test_validate_provider_credentials(): - provider = BaichuanProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={"api_key": "hahahaha"}) - - provider.validate_provider_credentials(credentials={"api_key": os.environ.get("BAICHUAN_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/baichuan/test_text_embedding.py b/api/tests/integration_tests/model_runtime/baichuan/test_text_embedding.py deleted file mode 100644 index cbc63f3978fb99..00000000000000 --- a/api/tests/integration_tests/model_runtime/baichuan/test_text_embedding.py +++ /dev/null @@ -1,87 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.baichuan.text_embedding.text_embedding import BaichuanTextEmbeddingModel - - -def test_validate_credentials(): - model = BaichuanTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="baichuan-text-embedding", credentials={"api_key": "invalid_key"}) - - model.validate_credentials( - model="baichuan-text-embedding", credentials={"api_key": os.environ.get("BAICHUAN_API_KEY")} - ) - - -def test_invoke_model(): - model = BaichuanTextEmbeddingModel() - - result = model.invoke( - model="baichuan-text-embedding", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 6 - - -def test_get_num_tokens(): - model = BaichuanTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="baichuan-text-embedding", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 - - -def test_max_chunks(): - model = BaichuanTextEmbeddingModel() - - result = model.invoke( - model="baichuan-text-embedding", - credentials={ - "api_key": os.environ.get("BAICHUAN_API_KEY"), - }, - texts=[ - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - ], - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 22 diff --git a/api/tests/integration_tests/model_runtime/bedrock/__init__.py b/api/tests/integration_tests/model_runtime/bedrock/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/bedrock/test_llm.py b/api/tests/integration_tests/model_runtime/bedrock/test_llm.py deleted file mode 100644 index c19ec35a6e45fc..00000000000000 --- a/api/tests/integration_tests/model_runtime/bedrock/test_llm.py +++ /dev/null @@ -1,103 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.bedrock.llm.llm import BedrockLargeLanguageModel - - -def test_validate_credentials(): - model = BedrockLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="meta.llama2-13b-chat-v1", credentials={"anthropic_api_key": "invalid_key"}) - - model.validate_credentials( - model="meta.llama2-13b-chat-v1", - credentials={ - "aws_region": os.getenv("AWS_REGION"), - "aws_access_key": os.getenv("AWS_ACCESS_KEY"), - "aws_secret_access_key": os.getenv("AWS_SECRET_ACCESS_KEY"), - }, - ) - - -def test_invoke_model(): - model = BedrockLargeLanguageModel() - - response = model.invoke( - model="meta.llama2-13b-chat-v1", - credentials={ - "aws_region": os.getenv("AWS_REGION"), - "aws_access_key": os.getenv("AWS_ACCESS_KEY"), - "aws_secret_access_key": os.getenv("AWS_SECRET_ACCESS_KEY"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "top_p": 1.0, "max_tokens_to_sample": 10}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = BedrockLargeLanguageModel() - - response = model.invoke( - model="meta.llama2-13b-chat-v1", - credentials={ - "aws_region": os.getenv("AWS_REGION"), - "aws_access_key": os.getenv("AWS_ACCESS_KEY"), - "aws_secret_access_key": os.getenv("AWS_SECRET_ACCESS_KEY"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens_to_sample": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - print(chunk) - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = BedrockLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="meta.llama2-13b-chat-v1", - credentials={ - "aws_region": os.getenv("AWS_REGION"), - "aws_access_key": os.getenv("AWS_ACCESS_KEY"), - "aws_secret_access_key": os.getenv("AWS_SECRET_ACCESS_KEY"), - }, - messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 18 diff --git a/api/tests/integration_tests/model_runtime/bedrock/test_provider.py b/api/tests/integration_tests/model_runtime/bedrock/test_provider.py deleted file mode 100644 index 080727829e9e2f..00000000000000 --- a/api/tests/integration_tests/model_runtime/bedrock/test_provider.py +++ /dev/null @@ -1,21 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.bedrock.bedrock import BedrockProvider - - -def test_validate_provider_credentials(): - provider = BedrockProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials( - credentials={ - "aws_region": os.getenv("AWS_REGION"), - "aws_access_key": os.getenv("AWS_ACCESS_KEY"), - "aws_secret_access_key": os.getenv("AWS_SECRET_ACCESS_KEY"), - } - ) diff --git a/api/tests/integration_tests/model_runtime/chatglm/__init__.py b/api/tests/integration_tests/model_runtime/chatglm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/chatglm/test_llm.py b/api/tests/integration_tests/model_runtime/chatglm/test_llm.py deleted file mode 100644 index 418e88874d1572..00000000000000 --- a/api/tests/integration_tests/model_runtime/chatglm/test_llm.py +++ /dev/null @@ -1,230 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.chatglm.llm.llm import ChatGLMLargeLanguageModel -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -def test_predefined_models(): - model = ChatGLMLargeLanguageModel() - model_schemas = model.predefined_models() - assert len(model_schemas) >= 1 - assert isinstance(model_schemas[0], AIModelEntity) - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_credentials_for_chat_model(setup_openai_mock): - model = ChatGLMLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="chatglm2-6b", credentials={"api_base": "invalid_key"}) - - model.validate_credentials(model="chatglm2-6b", credentials={"api_base": os.environ.get("CHATGLM_API_BASE")}) - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_model(setup_openai_mock): - model = ChatGLMLargeLanguageModel() - - response = model.invoke( - model="chatglm2-6b", - credentials={"api_base": os.environ.get("CHATGLM_API_BASE")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_stream_model(setup_openai_mock): - model = ChatGLMLargeLanguageModel() - - response = model.invoke( - model="chatglm2-6b", - credentials={"api_base": os.environ.get("CHATGLM_API_BASE")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_stream_model_with_functions(setup_openai_mock): - model = ChatGLMLargeLanguageModel() - - response = model.invoke( - model="chatglm3-6b", - credentials={"api_base": os.environ.get("CHATGLM_API_BASE")}, - prompt_messages=[ - SystemPromptMessage( - content="你是一个天气机器人，你不知道今天的天气怎么样，你需要通过调用一个函数来获取天气信息。" - ), - UserPromptMessage(content="波士顿天气如何？"), - ], - model_parameters={ - "temperature": 0, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=True, - tools=[ - PromptMessageTool( - name="get_current_weather", - description="Get the current weather in a given location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}, - }, - "required": ["location"], - }, - ) - ], - ) - - assert isinstance(response, Generator) - - call: LLMResultChunk = None - chunks = [] - - for chunk in response: - chunks.append(chunk) - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - if chunk.delta.message.tool_calls and len(chunk.delta.message.tool_calls) > 0: - call = chunk - break - - assert call is not None - assert call.delta.message.tool_calls[0].function.name == "get_current_weather" - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_model_with_functions(setup_openai_mock): - model = ChatGLMLargeLanguageModel() - - response = model.invoke( - model="chatglm3-6b", - credentials={"api_base": os.environ.get("CHATGLM_API_BASE")}, - prompt_messages=[UserPromptMessage(content="What is the weather like in San Francisco?")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=False, - tools=[ - PromptMessageTool( - name="get_current_weather", - description="Get the current weather in a given location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ) - ], - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - assert response.message.tool_calls[0].function.name == "get_current_weather" - - -def test_get_num_tokens(): - model = ChatGLMLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="chatglm2-6b", - credentials={"api_base": os.environ.get("CHATGLM_API_BASE")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - tools=[ - PromptMessageTool( - name="get_current_weather", - description="Get the current weather in a given location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ) - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 77 - - num_tokens = model.get_num_tokens( - model="chatglm2-6b", - credentials={"api_base": os.environ.get("CHATGLM_API_BASE")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/chatglm/test_provider.py b/api/tests/integration_tests/model_runtime/chatglm/test_provider.py deleted file mode 100644 index 7907805d072772..00000000000000 --- a/api/tests/integration_tests/model_runtime/chatglm/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.chatglm.chatglm import ChatGLMProvider -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_provider_credentials(setup_openai_mock): - provider = ChatGLMProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={"api_base": "hahahaha"}) - - provider.validate_provider_credentials(credentials={"api_base": os.environ.get("CHATGLM_API_BASE")}) diff --git a/api/tests/integration_tests/model_runtime/cohere/__init__.py b/api/tests/integration_tests/model_runtime/cohere/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/cohere/test_llm.py b/api/tests/integration_tests/model_runtime/cohere/test_llm.py deleted file mode 100644 index b7f707e935dbea..00000000000000 --- a/api/tests/integration_tests/model_runtime/cohere/test_llm.py +++ /dev/null @@ -1,191 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.cohere.llm.llm import CohereLargeLanguageModel - - -def test_validate_credentials_for_chat_model(): - model = CohereLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="command-light-chat", credentials={"api_key": "invalid_key"}) - - model.validate_credentials(model="command-light-chat", credentials={"api_key": os.environ.get("COHERE_API_KEY")}) - - -def test_validate_credentials_for_completion_model(): - model = CohereLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="command-light", credentials={"api_key": "invalid_key"}) - - model.validate_credentials(model="command-light", credentials={"api_key": os.environ.get("COHERE_API_KEY")}) - - -def test_invoke_completion_model(): - model = CohereLargeLanguageModel() - - credentials = {"api_key": os.environ.get("COHERE_API_KEY")} - - result = model.invoke( - model="command-light", - credentials=credentials, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.0, "max_tokens": 1}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - assert model._num_tokens_from_string("command-light", credentials, result.message.content) == 1 - - -def test_invoke_stream_completion_model(): - model = CohereLargeLanguageModel() - - result = model.invoke( - model="command-light", - credentials={"api_key": os.environ.get("COHERE_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_invoke_chat_model(): - model = CohereLargeLanguageModel() - - result = model.invoke( - model="command-light-chat", - credentials={"api_key": os.environ.get("COHERE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.0, - "p": 0.99, - "presence_penalty": 0.0, - "frequency_penalty": 0.0, - "max_tokens": 10, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -def test_invoke_stream_chat_model(): - model = CohereLargeLanguageModel() - - result = model.invoke( - model="command-light-chat", - credentials={"api_key": os.environ.get("COHERE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - if chunk.delta.finish_reason is not None: - assert chunk.delta.usage is not None - assert chunk.delta.usage.completion_tokens > 0 - - -def test_get_num_tokens(): - model = CohereLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="command-light", - credentials={"api_key": os.environ.get("COHERE_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - ) - - assert num_tokens == 3 - - num_tokens = model.get_num_tokens( - model="command-light-chat", - credentials={"api_key": os.environ.get("COHERE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 15 - - -def test_fine_tuned_model(): - model = CohereLargeLanguageModel() - - # test invoke - result = model.invoke( - model="85ec47be-6139-4f75-a4be-0f0ec1ef115c-ft", - credentials={"api_key": os.environ.get("COHERE_API_KEY"), "mode": "completion"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - - -def test_fine_tuned_chat_model(): - model = CohereLargeLanguageModel() - - # test invoke - result = model.invoke( - model="94f2d55a-4c79-4c00-bde4-23962e74b170-ft", - credentials={"api_key": os.environ.get("COHERE_API_KEY"), "mode": "chat"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) diff --git a/api/tests/integration_tests/model_runtime/cohere/test_provider.py b/api/tests/integration_tests/model_runtime/cohere/test_provider.py deleted file mode 100644 index fb7e6d34984a61..00000000000000 --- a/api/tests/integration_tests/model_runtime/cohere/test_provider.py +++ /dev/null @@ -1,15 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.cohere.cohere import CohereProvider - - -def test_validate_provider_credentials(): - provider = CohereProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={"api_key": os.environ.get("COHERE_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/cohere/test_rerank.py b/api/tests/integration_tests/model_runtime/cohere/test_rerank.py deleted file mode 100644 index a1b6922128570e..00000000000000 --- a/api/tests/integration_tests/model_runtime/cohere/test_rerank.py +++ /dev/null @@ -1,40 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.rerank_entities import RerankResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.cohere.rerank.rerank import CohereRerankModel - - -def test_validate_credentials(): - model = CohereRerankModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="rerank-english-v2.0", credentials={"api_key": "invalid_key"}) - - model.validate_credentials(model="rerank-english-v2.0", credentials={"api_key": os.environ.get("COHERE_API_KEY")}) - - -def test_invoke_model(): - model = CohereRerankModel() - - result = model.invoke( - model="rerank-english-v2.0", - credentials={"api_key": os.environ.get("COHERE_API_KEY")}, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) " - "is the capital of the United States. It is a federal district. The President of the USA and many major " - "national government offices are in the territory. This makes it the political center of the United " - "States of America.", - ], - score_threshold=0.8, - ) - - assert isinstance(result, RerankResult) - assert len(result.docs) == 1 - assert result.docs[0].index == 1 - assert result.docs[0].score >= 0.8 diff --git a/api/tests/integration_tests/model_runtime/cohere/test_text_embedding.py b/api/tests/integration_tests/model_runtime/cohere/test_text_embedding.py deleted file mode 100644 index ae26d36635d1b5..00000000000000 --- a/api/tests/integration_tests/model_runtime/cohere/test_text_embedding.py +++ /dev/null @@ -1,45 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.cohere.text_embedding.text_embedding import CohereTextEmbeddingModel - - -def test_validate_credentials(): - model = CohereTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="embed-multilingual-v3.0", credentials={"api_key": "invalid_key"}) - - model.validate_credentials( - model="embed-multilingual-v3.0", credentials={"api_key": os.environ.get("COHERE_API_KEY")} - ) - - -def test_invoke_model(): - model = CohereTextEmbeddingModel() - - result = model.invoke( - model="embed-multilingual-v3.0", - credentials={"api_key": os.environ.get("COHERE_API_KEY")}, - texts=["hello", "world", " ".join(["long_text"] * 100), " ".join(["another_long_text"] * 100)], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 4 - assert result.usage.total_tokens == 811 - - -def test_get_num_tokens(): - model = CohereTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="embed-multilingual-v3.0", - credentials={"api_key": os.environ.get("COHERE_API_KEY")}, - texts=["hello", "world"], - ) - - assert num_tokens == 3 diff --git a/api/tests/integration_tests/model_runtime/fireworks/__init__.py b/api/tests/integration_tests/model_runtime/fireworks/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/fireworks/test_llm.py b/api/tests/integration_tests/model_runtime/fireworks/test_llm.py deleted file mode 100644 index 699ca293a2fca8..00000000000000 --- a/api/tests/integration_tests/model_runtime/fireworks/test_llm.py +++ /dev/null @@ -1,186 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.fireworks.llm.llm import FireworksLargeLanguageModel - -"""FOR MOCK FIXTURES, DO NOT REMOVE""" -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -def test_predefined_models(): - model = FireworksLargeLanguageModel() - model_schemas = model.predefined_models() - - assert len(model_schemas) >= 1 - assert isinstance(model_schemas[0], AIModelEntity) - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_credentials_for_chat_model(setup_openai_mock): - model = FireworksLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - # model name to gpt-3.5-turbo because of mocking - model.validate_credentials(model="gpt-3.5-turbo", credentials={"fireworks_api_key": "invalid_key"}) - - model.validate_credentials( - model="accounts/fireworks/models/llama-v3p1-8b-instruct", - credentials={"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY")}, - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model(setup_openai_mock): - model = FireworksLargeLanguageModel() - - result = model.invoke( - model="accounts/fireworks/models/llama-v3p1-8b-instruct", - credentials={"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.0, - "top_p": 1.0, - "presence_penalty": 0.0, - "frequency_penalty": 0.0, - "max_tokens": 10, - }, - stop=["How"], - stream=False, - user="foo", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model_with_tools(setup_openai_mock): - model = FireworksLargeLanguageModel() - - result = model.invoke( - model="accounts/fireworks/models/llama-v3p1-8b-instruct", - credentials={"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content="what's the weather today in London?", - ), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ), - PromptMessageTool( - name="get_stock_price", - description="Get the current stock price", - parameters={ - "type": "object", - "properties": {"symbol": {"type": "string", "description": "The stock symbol"}}, - "required": ["symbol"], - }, - ), - ], - stream=False, - user="foo", - ) - - assert isinstance(result, LLMResult) - assert isinstance(result.message, AssistantPromptMessage) - assert len(result.message.tool_calls) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_stream_chat_model(setup_openai_mock): - model = FireworksLargeLanguageModel() - - result = model.invoke( - model="accounts/fireworks/models/llama-v3p1-8b-instruct", - credentials={"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="foo", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - if chunk.delta.finish_reason is not None: - assert chunk.delta.usage is not None - assert chunk.delta.usage.completion_tokens > 0 - - -def test_get_num_tokens(): - model = FireworksLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="accounts/fireworks/models/llama-v3p1-8b-instruct", - credentials={"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - ) - - assert num_tokens == 10 - - num_tokens = model.get_num_tokens( - model="accounts/fireworks/models/llama-v3p1-8b-instruct", - credentials={"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ), - ], - ) - - assert num_tokens == 77 diff --git a/api/tests/integration_tests/model_runtime/fireworks/test_provider.py b/api/tests/integration_tests/model_runtime/fireworks/test_provider.py deleted file mode 100644 index a68cf1a1a8fbda..00000000000000 --- a/api/tests/integration_tests/model_runtime/fireworks/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.fireworks.fireworks import FireworksProvider -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_provider_credentials(setup_openai_mock): - provider = FireworksProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/fireworks/test_text_embedding.py b/api/tests/integration_tests/model_runtime/fireworks/test_text_embedding.py deleted file mode 100644 index 7bf723b3a93742..00000000000000 --- a/api/tests/integration_tests/model_runtime/fireworks/test_text_embedding.py +++ /dev/null @@ -1,54 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.fireworks.text_embedding.text_embedding import FireworksTextEmbeddingModel -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["text_embedding"]], indirect=True) -def test_validate_credentials(setup_openai_mock): - model = FireworksTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="nomic-ai/nomic-embed-text-v1.5", credentials={"fireworks_api_key": "invalid_key"} - ) - - model.validate_credentials( - model="nomic-ai/nomic-embed-text-v1.5", credentials={"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY")} - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["text_embedding"]], indirect=True) -def test_invoke_model(setup_openai_mock): - model = FireworksTextEmbeddingModel() - - result = model.invoke( - model="nomic-ai/nomic-embed-text-v1.5", - credentials={ - "fireworks_api_key": os.environ.get("FIREWORKS_API_KEY"), - }, - texts=["hello", "world", " ".join(["long_text"] * 100), " ".join(["another_long_text"] * 100)], - user="foo", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 4 - assert result.usage.total_tokens == 2 - - -def test_get_num_tokens(): - model = FireworksTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="nomic-ai/nomic-embed-text-v1.5", - credentials={ - "fireworks_api_key": os.environ.get("FIREWORKS_API_KEY"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/fishaudio/__init__.py b/api/tests/integration_tests/model_runtime/fishaudio/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/fishaudio/test_provider.py b/api/tests/integration_tests/model_runtime/fishaudio/test_provider.py deleted file mode 100644 index 3526574b613238..00000000000000 --- a/api/tests/integration_tests/model_runtime/fishaudio/test_provider.py +++ /dev/null @@ -1,33 +0,0 @@ -import os - -import httpx -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.fishaudio.fishaudio import FishAudioProvider -from tests.integration_tests.model_runtime.__mock.fishaudio import setup_fishaudio_mock - - -@pytest.mark.parametrize("setup_fishaudio_mock", [["list-models"]], indirect=True) -def test_validate_provider_credentials(setup_fishaudio_mock): - print("-----", httpx.get) - provider = FishAudioProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials( - credentials={ - "api_key": "bad_api_key", - "api_base": os.environ.get("FISH_AUDIO_API_BASE", "https://api.fish.audio"), - "use_public_models": "false", - "latency": "normal", - } - ) - - provider.validate_provider_credentials( - credentials={ - "api_key": os.environ.get("FISH_AUDIO_API_KEY", "test"), - "api_base": os.environ.get("FISH_AUDIO_API_BASE", "https://api.fish.audio"), - "use_public_models": "false", - "latency": "normal", - } - ) diff --git a/api/tests/integration_tests/model_runtime/fishaudio/test_tts.py b/api/tests/integration_tests/model_runtime/fishaudio/test_tts.py deleted file mode 100644 index f61fee28b98e30..00000000000000 --- a/api/tests/integration_tests/model_runtime/fishaudio/test_tts.py +++ /dev/null @@ -1,32 +0,0 @@ -import os - -import pytest - -from core.model_runtime.model_providers.fishaudio.tts.tts import ( - FishAudioText2SpeechModel, -) -from tests.integration_tests.model_runtime.__mock.fishaudio import setup_fishaudio_mock - - -@pytest.mark.parametrize("setup_fishaudio_mock", [["tts"]], indirect=True) -def test_invoke_model(setup_fishaudio_mock): - model = FishAudioText2SpeechModel() - - result = model.invoke( - model="tts-default", - tenant_id="test", - credentials={ - "api_key": os.environ.get("FISH_AUDIO_API_KEY", "test"), - "api_base": os.environ.get("FISH_AUDIO_API_BASE", "https://api.fish.audio"), - "use_public_models": "false", - "latency": "normal", - }, - content_text="Hello, world!", - voice="03397b4c4be74759b72533b663fbd001", - ) - - content = b"" - for chunk in result: - content += chunk - - assert content != b"" diff --git a/api/tests/integration_tests/model_runtime/google/__init__.py b/api/tests/integration_tests/model_runtime/google/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/google/test_llm.py b/api/tests/integration_tests/model_runtime/google/test_llm.py deleted file mode 100644 index 34d08f270afe7e..00000000000000 --- a/api/tests/integration_tests/model_runtime/google/test_llm.py +++ /dev/null @@ -1,177 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.google.llm.llm import GoogleLargeLanguageModel -from tests.integration_tests.model_runtime.__mock.google import setup_google_mock - - -@pytest.mark.parametrize("setup_google_mock", [["none"]], indirect=True) -def test_validate_credentials(setup_google_mock): - model = GoogleLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="gemini-pro", credentials={"google_api_key": "invalid_key"}) - - model.validate_credentials(model="gemini-pro", credentials={"google_api_key": os.environ.get("GOOGLE_API_KEY")}) - - -@pytest.mark.parametrize("setup_google_mock", [["none"]], indirect=True) -def test_invoke_model(setup_google_mock): - model = GoogleLargeLanguageModel() - - response = model.invoke( - model="gemini-pro", - credentials={"google_api_key": os.environ.get("GOOGLE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Give me your worst dad joke or i will unplug you"), - AssistantPromptMessage( - content="Why did the scarecrow win an award? Because he was outstanding in his field!" - ), - UserPromptMessage( - content=[ - TextPromptMessageContent(data="ok something snarkier pls"), - TextPromptMessageContent(data="i may still unplug you"), - ] - ), - ], - model_parameters={"temperature": 0.5, "top_p": 1.0, "max_tokens_to_sample": 2048}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -@pytest.mark.parametrize("setup_google_mock", [["none"]], indirect=True) -def test_invoke_stream_model(setup_google_mock): - model = GoogleLargeLanguageModel() - - response = model.invoke( - model="gemini-pro", - credentials={"google_api_key": os.environ.get("GOOGLE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Give me your worst dad joke or i will unplug you"), - AssistantPromptMessage( - content="Why did the scarecrow win an award? Because he was outstanding in his field!" - ), - UserPromptMessage( - content=[ - TextPromptMessageContent(data="ok something snarkier pls"), - TextPromptMessageContent(data="i may still unplug you"), - ] - ), - ], - model_parameters={"temperature": 0.2, "top_k": 5, "max_tokens_to_sample": 2048}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -@pytest.mark.parametrize("setup_google_mock", [["none"]], indirect=True) -def test_invoke_chat_model_with_vision(setup_google_mock): - model = GoogleLargeLanguageModel() - - result = model.invoke( - model="gemini-pro-vision", - credentials={"google_api_key": os.environ.get("GOOGLE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content=[ - TextPromptMessageContent(data="what do you see?"), - ImagePromptMessageContent( - data="data:image/png;base64,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" - ), - ] - ), - ], - model_parameters={"temperature": 0.3, "top_p": 0.2, "top_k": 3, "max_tokens": 100}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_google_mock", [["none"]], indirect=True) -def test_invoke_chat_model_with_vision_multi_pics(setup_google_mock): - model = GoogleLargeLanguageModel() - - result = model.invoke( - model="gemini-pro-vision", - credentials={"google_api_key": os.environ.get("GOOGLE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage(content="You are a helpful AI assistant."), - UserPromptMessage( - content=[ - TextPromptMessageContent(data="what do you see?"), - ImagePromptMessageContent( - data="data:image/png;base64,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" - ), - ] - ), - AssistantPromptMessage(content="I see a blue letter 'D' with a gradient from light blue to dark blue."), - UserPromptMessage( - content=[ - TextPromptMessageContent(data="what about now?"), - ImagePromptMessageContent( - data="data:image/png;base64,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" - ), - ] - ), - ], - model_parameters={"temperature": 0.3, "top_p": 0.2, "top_k": 3, "max_tokens": 100}, - stream=False, - user="abc-123", - ) - - print(f"result: {result.message.content}") - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -def test_get_num_tokens(): - model = GoogleLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="gemini-pro", - credentials={"google_api_key": os.environ.get("GOOGLE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens > 0 # The exact number of tokens may vary based on the model's tokenization diff --git a/api/tests/integration_tests/model_runtime/google/test_provider.py b/api/tests/integration_tests/model_runtime/google/test_provider.py deleted file mode 100644 index c217e4fe058870..00000000000000 --- a/api/tests/integration_tests/model_runtime/google/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.google.google import GoogleProvider -from tests.integration_tests.model_runtime.__mock.google import setup_google_mock - - -@pytest.mark.parametrize("setup_google_mock", [["none"]], indirect=True) -def test_validate_provider_credentials(setup_google_mock): - provider = GoogleProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={"google_api_key": os.environ.get("GOOGLE_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/huggingface_hub/__init__.py b/api/tests/integration_tests/model_runtime/huggingface_hub/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/huggingface_hub/test_llm.py b/api/tests/integration_tests/model_runtime/huggingface_hub/test_llm.py deleted file mode 100644 index 6a6cc874fa2f30..00000000000000 --- a/api/tests/integration_tests/model_runtime/huggingface_hub/test_llm.py +++ /dev/null @@ -1,277 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.huggingface_hub.llm.llm import HuggingfaceHubLargeLanguageModel -from tests.integration_tests.model_runtime.__mock.huggingface import setup_huggingface_mock - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_hosted_inference_api_validate_credentials(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="HuggingFaceH4/zephyr-7b-beta", - credentials={"huggingfacehub_api_type": "hosted_inference_api", "huggingfacehub_api_token": "invalid_key"}, - ) - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="fake-model", - credentials={"huggingfacehub_api_type": "hosted_inference_api", "huggingfacehub_api_token": "invalid_key"}, - ) - - model.validate_credentials( - model="HuggingFaceH4/zephyr-7b-beta", - credentials={ - "huggingfacehub_api_type": "hosted_inference_api", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - }, - ) - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_hosted_inference_api_invoke_model(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - response = model.invoke( - model="HuggingFaceH4/zephyr-7b-beta", - credentials={ - "huggingfacehub_api_type": "hosted_inference_api", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_hosted_inference_api_invoke_stream_model(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - response = model.invoke( - model="HuggingFaceH4/zephyr-7b-beta", - credentials={ - "huggingfacehub_api_type": "hosted_inference_api", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_inference_endpoints_text_generation_validate_credentials(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="openchat/openchat_3.5", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": "invalid_key", - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT_GEN_ENDPOINT_URL"), - "task_type": "text-generation", - }, - ) - - model.validate_credentials( - model="openchat/openchat_3.5", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT_GEN_ENDPOINT_URL"), - "task_type": "text-generation", - }, - ) - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_inference_endpoints_text_generation_invoke_model(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - response = model.invoke( - model="openchat/openchat_3.5", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT_GEN_ENDPOINT_URL"), - "task_type": "text-generation", - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_inference_endpoints_text_generation_invoke_stream_model(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - response = model.invoke( - model="openchat/openchat_3.5", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT_GEN_ENDPOINT_URL"), - "task_type": "text-generation", - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_inference_endpoints_text2text_generation_validate_credentials(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="google/mt5-base", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": "invalid_key", - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL"), - "task_type": "text2text-generation", - }, - ) - - model.validate_credentials( - model="google/mt5-base", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL"), - "task_type": "text2text-generation", - }, - ) - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_inference_endpoints_text2text_generation_invoke_model(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - response = model.invoke( - model="google/mt5-base", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL"), - "task_type": "text2text-generation", - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -@pytest.mark.parametrize("setup_huggingface_mock", [["none"]], indirect=True) -def test_inference_endpoints_text2text_generation_invoke_stream_model(setup_huggingface_mock): - model = HuggingfaceHubLargeLanguageModel() - - response = model.invoke( - model="google/mt5-base", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL"), - "task_type": "text2text-generation", - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = HuggingfaceHubLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="google/mt5-base", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_TEXT2TEXT_GEN_ENDPOINT_URL"), - "task_type": "text2text-generation", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - ) - - assert num_tokens == 7 diff --git a/api/tests/integration_tests/model_runtime/huggingface_hub/test_text_embedding.py b/api/tests/integration_tests/model_runtime/huggingface_hub/test_text_embedding.py deleted file mode 100644 index 0ee593f38a494a..00000000000000 --- a/api/tests/integration_tests/model_runtime/huggingface_hub/test_text_embedding.py +++ /dev/null @@ -1,112 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.huggingface_hub.text_embedding.text_embedding import ( - HuggingfaceHubTextEmbeddingModel, -) - - -def test_hosted_inference_api_validate_credentials(): - model = HuggingfaceHubTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="facebook/bart-base", - credentials={ - "huggingfacehub_api_type": "hosted_inference_api", - "huggingfacehub_api_token": "invalid_key", - }, - ) - - model.validate_credentials( - model="facebook/bart-base", - credentials={ - "huggingfacehub_api_type": "hosted_inference_api", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - }, - ) - - -def test_hosted_inference_api_invoke_model(): - model = HuggingfaceHubTextEmbeddingModel() - - result = model.invoke( - model="facebook/bart-base", - credentials={ - "huggingfacehub_api_type": "hosted_inference_api", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - }, - texts=["hello", "world"], - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 2 - - -def test_inference_endpoints_validate_credentials(): - model = HuggingfaceHubTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="all-MiniLM-L6-v2", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": "invalid_key", - "huggingface_namespace": "Dify-AI", - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL"), - "task_type": "feature-extraction", - }, - ) - - model.validate_credentials( - model="all-MiniLM-L6-v2", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingface_namespace": "Dify-AI", - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL"), - "task_type": "feature-extraction", - }, - ) - - -def test_inference_endpoints_invoke_model(): - model = HuggingfaceHubTextEmbeddingModel() - - result = model.invoke( - model="all-MiniLM-L6-v2", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingface_namespace": "Dify-AI", - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL"), - "task_type": "feature-extraction", - }, - texts=["hello", "world"], - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 0 - - -def test_get_num_tokens(): - model = HuggingfaceHubTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="all-MiniLM-L6-v2", - credentials={ - "huggingfacehub_api_type": "inference_endpoints", - "huggingfacehub_api_token": os.environ.get("HUGGINGFACE_API_KEY"), - "huggingface_namespace": "Dify-AI", - "huggingfacehub_endpoint_url": os.environ.get("HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL"), - "task_type": "feature-extraction", - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/huggingface_tei/__init__.py b/api/tests/integration_tests/model_runtime/huggingface_tei/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/huggingface_tei/test_embeddings.py b/api/tests/integration_tests/model_runtime/huggingface_tei/test_embeddings.py deleted file mode 100644 index b1fa9d5ca5097f..00000000000000 --- a/api/tests/integration_tests/model_runtime/huggingface_tei/test_embeddings.py +++ /dev/null @@ -1,70 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.huggingface_tei.text_embedding.text_embedding import ( - HuggingfaceTeiTextEmbeddingModel, - TeiHelper, -) -from tests.integration_tests.model_runtime.__mock.huggingface_tei import MockTEIClass - -MOCK = os.getenv("MOCK_SWITCH", "false").lower() == "true" - - -@pytest.fixture -def setup_tei_mock(request, monkeypatch: pytest.MonkeyPatch): - if MOCK: - monkeypatch.setattr(TeiHelper, "get_tei_extra_parameter", MockTEIClass.get_tei_extra_parameter) - monkeypatch.setattr(TeiHelper, "invoke_tokenize", MockTEIClass.invoke_tokenize) - monkeypatch.setattr(TeiHelper, "invoke_embeddings", MockTEIClass.invoke_embeddings) - monkeypatch.setattr(TeiHelper, "invoke_rerank", MockTEIClass.invoke_rerank) - yield - - if MOCK: - monkeypatch.undo() - - -@pytest.mark.parametrize("setup_tei_mock", [["none"]], indirect=True) -def test_validate_credentials(setup_tei_mock): - model = HuggingfaceTeiTextEmbeddingModel() - # model name is only used in mock - model_name = "embedding" - - if MOCK: - # TEI Provider will check model type by API endpoint, at real server, the model type is correct. - # So we dont need to check model type here. Only check in mock - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="reranker", - credentials={ - "server_url": os.environ.get("TEI_EMBEDDING_SERVER_URL", ""), - }, - ) - - model.validate_credentials( - model=model_name, - credentials={ - "server_url": os.environ.get("TEI_EMBEDDING_SERVER_URL", ""), - }, - ) - - -@pytest.mark.parametrize("setup_tei_mock", [["none"]], indirect=True) -def test_invoke_model(setup_tei_mock): - model = HuggingfaceTeiTextEmbeddingModel() - model_name = "embedding" - - result = model.invoke( - model=model_name, - credentials={ - "server_url": os.environ.get("TEI_EMBEDDING_SERVER_URL", ""), - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens > 0 diff --git a/api/tests/integration_tests/model_runtime/huggingface_tei/test_rerank.py b/api/tests/integration_tests/model_runtime/huggingface_tei/test_rerank.py deleted file mode 100644 index 45370d9fba41b0..00000000000000 --- a/api/tests/integration_tests/model_runtime/huggingface_tei/test_rerank.py +++ /dev/null @@ -1,78 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.huggingface_tei.rerank.rerank import ( - HuggingfaceTeiRerankModel, -) -from core.model_runtime.model_providers.huggingface_tei.text_embedding.text_embedding import TeiHelper -from tests.integration_tests.model_runtime.__mock.huggingface_tei import MockTEIClass - -MOCK = os.getenv("MOCK_SWITCH", "false").lower() == "true" - - -@pytest.fixture -def setup_tei_mock(request, monkeypatch: pytest.MonkeyPatch): - if MOCK: - monkeypatch.setattr(TeiHelper, "get_tei_extra_parameter", MockTEIClass.get_tei_extra_parameter) - monkeypatch.setattr(TeiHelper, "invoke_tokenize", MockTEIClass.invoke_tokenize) - monkeypatch.setattr(TeiHelper, "invoke_embeddings", MockTEIClass.invoke_embeddings) - monkeypatch.setattr(TeiHelper, "invoke_rerank", MockTEIClass.invoke_rerank) - yield - - if MOCK: - monkeypatch.undo() - - -@pytest.mark.parametrize("setup_tei_mock", [["none"]], indirect=True) -def test_validate_credentials(setup_tei_mock): - model = HuggingfaceTeiRerankModel() - # model name is only used in mock - model_name = "reranker" - - if MOCK: - # TEI Provider will check model type by API endpoint, at real server, the model type is correct. - # So we dont need to check model type here. Only check in mock - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="embedding", - credentials={ - "server_url": os.environ.get("TEI_RERANK_SERVER_URL"), - }, - ) - - model.validate_credentials( - model=model_name, - credentials={ - "server_url": os.environ.get("TEI_RERANK_SERVER_URL"), - }, - ) - - -@pytest.mark.parametrize("setup_tei_mock", [["none"]], indirect=True) -def test_invoke_model(setup_tei_mock): - model = HuggingfaceTeiRerankModel() - # model name is only used in mock - model_name = "reranker" - - result = model.invoke( - model=model_name, - credentials={ - "server_url": os.environ.get("TEI_RERANK_SERVER_URL"), - }, - query="Who is Kasumi?", - docs=[ - 'Kasumi is a girl\'s name of Japanese origin meaning "mist".', - "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music ", - "and she leads a team named PopiParty.", - ], - score_threshold=0.8, - ) - - assert isinstance(result, RerankResult) - assert len(result.docs) == 1 - assert result.docs[0].index == 0 - assert result.docs[0].score >= 0.8 diff --git a/api/tests/integration_tests/model_runtime/hunyuan/__init__.py b/api/tests/integration_tests/model_runtime/hunyuan/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/hunyuan/test_llm.py b/api/tests/integration_tests/model_runtime/hunyuan/test_llm.py deleted file mode 100644 index b3049a06d9b98a..00000000000000 --- a/api/tests/integration_tests/model_runtime/hunyuan/test_llm.py +++ /dev/null @@ -1,90 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.hunyuan.llm.llm import HunyuanLargeLanguageModel - - -def test_validate_credentials(): - model = HunyuanLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="hunyuan-standard", credentials={"secret_id": "invalid_key", "secret_key": "invalid_key"} - ) - - model.validate_credentials( - model="hunyuan-standard", - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - }, - ) - - -def test_invoke_model(): - model = HunyuanLargeLanguageModel() - - response = model.invoke( - model="hunyuan-standard", - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Hi")], - model_parameters={"temperature": 0.5, "max_tokens": 10}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = HunyuanLargeLanguageModel() - - response = model.invoke( - model="hunyuan-standard", - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Hi")], - model_parameters={"temperature": 0.5, "max_tokens": 100, "seed": 1234}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = HunyuanLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="hunyuan-standard", - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 14 diff --git a/api/tests/integration_tests/model_runtime/hunyuan/test_provider.py b/api/tests/integration_tests/model_runtime/hunyuan/test_provider.py deleted file mode 100644 index e3748c2ce713d4..00000000000000 --- a/api/tests/integration_tests/model_runtime/hunyuan/test_provider.py +++ /dev/null @@ -1,20 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.hunyuan.hunyuan import HunyuanProvider - - -def test_validate_provider_credentials(): - provider = HunyuanProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={"secret_id": "invalid_key", "secret_key": "invalid_key"}) - - provider.validate_provider_credentials( - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - } - ) diff --git a/api/tests/integration_tests/model_runtime/hunyuan/test_text_embedding.py b/api/tests/integration_tests/model_runtime/hunyuan/test_text_embedding.py deleted file mode 100644 index 69d14dffeebf35..00000000000000 --- a/api/tests/integration_tests/model_runtime/hunyuan/test_text_embedding.py +++ /dev/null @@ -1,96 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.hunyuan.text_embedding.text_embedding import HunyuanTextEmbeddingModel - - -def test_validate_credentials(): - model = HunyuanTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="hunyuan-embedding", credentials={"secret_id": "invalid_key", "secret_key": "invalid_key"} - ) - - model.validate_credentials( - model="hunyuan-embedding", - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - }, - ) - - -def test_invoke_model(): - model = HunyuanTextEmbeddingModel() - - result = model.invoke( - model="hunyuan-embedding", - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 6 - - -def test_get_num_tokens(): - model = HunyuanTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="hunyuan-embedding", - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 - - -def test_max_chunks(): - model = HunyuanTextEmbeddingModel() - - result = model.invoke( - model="hunyuan-embedding", - credentials={ - "secret_id": os.environ.get("HUNYUAN_SECRET_ID"), - "secret_key": os.environ.get("HUNYUAN_SECRET_KEY"), - }, - texts=[ - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - "hello", - "world", - ], - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 22 diff --git a/api/tests/integration_tests/model_runtime/jina/__init__.py b/api/tests/integration_tests/model_runtime/jina/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/jina/test_provider.py b/api/tests/integration_tests/model_runtime/jina/test_provider.py deleted file mode 100644 index e3b6128c59d8df..00000000000000 --- a/api/tests/integration_tests/model_runtime/jina/test_provider.py +++ /dev/null @@ -1,15 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.jina.jina import JinaProvider - - -def test_validate_provider_credentials(): - provider = JinaProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={"api_key": "hahahaha"}) - - provider.validate_provider_credentials(credentials={"api_key": os.environ.get("JINA_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/jina/test_text_embedding.py b/api/tests/integration_tests/model_runtime/jina/test_text_embedding.py deleted file mode 100644 index 290735ec49e625..00000000000000 --- a/api/tests/integration_tests/model_runtime/jina/test_text_embedding.py +++ /dev/null @@ -1,49 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.jina.text_embedding.text_embedding import JinaTextEmbeddingModel - - -def test_validate_credentials(): - model = JinaTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="jina-embeddings-v2-base-en", credentials={"api_key": "invalid_key"}) - - model.validate_credentials( - model="jina-embeddings-v2-base-en", credentials={"api_key": os.environ.get("JINA_API_KEY")} - ) - - -def test_invoke_model(): - model = JinaTextEmbeddingModel() - - result = model.invoke( - model="jina-embeddings-v2-base-en", - credentials={ - "api_key": os.environ.get("JINA_API_KEY"), - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 6 - - -def test_get_num_tokens(): - model = JinaTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="jina-embeddings-v2-base-en", - credentials={ - "api_key": os.environ.get("JINA_API_KEY"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 6 diff --git a/api/tests/integration_tests/model_runtime/localai/__init__.py b/api/tests/integration_tests/model_runtime/localai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/localai/test_embedding.py b/api/tests/integration_tests/model_runtime/localai/test_embedding.py deleted file mode 100644 index 7fd9f2b3000a31..00000000000000 --- a/api/tests/integration_tests/model_runtime/localai/test_embedding.py +++ /dev/null @@ -1,4 +0,0 @@ -""" -LocalAI Embedding Interface is temporarily unavailable due to -we could not find a way to test it for now. -""" diff --git a/api/tests/integration_tests/model_runtime/localai/test_llm.py b/api/tests/integration_tests/model_runtime/localai/test_llm.py deleted file mode 100644 index aa5436c34fc7dd..00000000000000 --- a/api/tests/integration_tests/model_runtime/localai/test_llm.py +++ /dev/null @@ -1,174 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import ParameterRule -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.localai.llm.llm import LocalAILanguageModel - - -def test_validate_credentials_for_chat_model(): - model = LocalAILanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="chinese-llama-2-7b", - credentials={ - "server_url": "hahahaha", - "completion_type": "completion", - }, - ) - - model.validate_credentials( - model="chinese-llama-2-7b", - credentials={ - "server_url": os.environ.get("LOCALAI_SERVER_URL"), - "completion_type": "completion", - }, - ) - - -def test_invoke_completion_model(): - model = LocalAILanguageModel() - - response = model.invoke( - model="chinese-llama-2-7b", - credentials={ - "server_url": os.environ.get("LOCALAI_SERVER_URL"), - "completion_type": "completion", - }, - prompt_messages=[UserPromptMessage(content="ping")], - model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10}, - stop=[], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_chat_model(): - model = LocalAILanguageModel() - - response = model.invoke( - model="chinese-llama-2-7b", - credentials={ - "server_url": os.environ.get("LOCALAI_SERVER_URL"), - "completion_type": "chat_completion", - }, - prompt_messages=[UserPromptMessage(content="ping")], - model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10}, - stop=[], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_stream_completion_model(): - model = LocalAILanguageModel() - - response = model.invoke( - model="chinese-llama-2-7b", - credentials={ - "server_url": os.environ.get("LOCALAI_SERVER_URL"), - "completion_type": "completion", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10}, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_invoke_stream_chat_model(): - model = LocalAILanguageModel() - - response = model.invoke( - model="chinese-llama-2-7b", - credentials={ - "server_url": os.environ.get("LOCALAI_SERVER_URL"), - "completion_type": "chat_completion", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10}, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = LocalAILanguageModel() - - num_tokens = model.get_num_tokens( - model="????", - credentials={ - "server_url": os.environ.get("LOCALAI_SERVER_URL"), - "completion_type": "chat_completion", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - tools=[ - PromptMessageTool( - name="get_current_weather", - description="Get the current weather in a given location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ) - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 77 - - num_tokens = model.get_num_tokens( - model="????", - credentials={ - "server_url": os.environ.get("LOCALAI_SERVER_URL"), - "completion_type": "chat_completion", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 10 diff --git a/api/tests/integration_tests/model_runtime/localai/test_rerank.py b/api/tests/integration_tests/model_runtime/localai/test_rerank.py deleted file mode 100644 index 13c7df6d1473b0..00000000000000 --- a/api/tests/integration_tests/model_runtime/localai/test_rerank.py +++ /dev/null @@ -1,96 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.localai.rerank.rerank import LocalaiRerankModel - - -def test_validate_credentials_for_chat_model(): - model = LocalaiRerankModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="bge-reranker-v2-m3", - credentials={ - "server_url": "hahahaha", - "completion_type": "completion", - }, - ) - - model.validate_credentials( - model="bge-reranker-base", - credentials={ - "server_url": os.environ.get("LOCALAI_SERVER_URL"), - "completion_type": "completion", - }, - ) - - -def test_invoke_rerank_model(): - model = LocalaiRerankModel() - - response = model.invoke( - model="bge-reranker-base", - credentials={"server_url": os.environ.get("LOCALAI_SERVER_URL")}, - query="Organic skincare products for sensitive skin", - docs=[ - "Eco-friendly kitchenware for modern homes", - "Biodegradable cleaning supplies for eco-conscious consumers", - "Organic cotton baby clothes for sensitive skin", - "Natural organic skincare range for sensitive skin", - "Tech gadgets for smart homes: 2024 edition", - "Sustainable gardening tools and compost solutions", - "Sensitive skin-friendly facial cleansers and toners", - "Organic food wraps and storage solutions", - "Yoga mats made from recycled materials", - ], - top_n=3, - score_threshold=0.75, - user="abc-123", - ) - - assert isinstance(response, RerankResult) - assert len(response.docs) == 3 - - -def test__invoke(): - model = LocalaiRerankModel() - - # Test case 1: Empty docs - result = model._invoke( - model="bge-reranker-base", - credentials={"server_url": "https://example.com", "api_key": "1234567890"}, - query="Organic skincare products for sensitive skin", - docs=[], - top_n=3, - score_threshold=0.75, - user="abc-123", - ) - assert isinstance(result, RerankResult) - assert len(result.docs) == 0 - - # Test case 2: Valid invocation - result = model._invoke( - model="bge-reranker-base", - credentials={"server_url": "https://example.com", "api_key": "1234567890"}, - query="Organic skincare products for sensitive skin", - docs=[ - "Eco-friendly kitchenware for modern homes", - "Biodegradable cleaning supplies for eco-conscious consumers", - "Organic cotton baby clothes for sensitive skin", - "Natural organic skincare range for sensitive skin", - "Tech gadgets for smart homes: 2024 edition", - "Sustainable gardening tools and compost solutions", - "Sensitive skin-friendly facial cleansers and toners", - "Organic food wraps and storage solutions", - "Yoga mats made from recycled materials", - ], - top_n=3, - score_threshold=0.75, - user="abc-123", - ) - assert isinstance(result, RerankResult) - assert len(result.docs) == 3 - assert all(isinstance(doc, RerankDocument) for doc in result.docs) diff --git a/api/tests/integration_tests/model_runtime/localai/test_speech2text.py b/api/tests/integration_tests/model_runtime/localai/test_speech2text.py deleted file mode 100644 index 91b7a5752ce973..00000000000000 --- a/api/tests/integration_tests/model_runtime/localai/test_speech2text.py +++ /dev/null @@ -1,42 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.localai.speech2text.speech2text import LocalAISpeech2text - - -def test_validate_credentials(): - model = LocalAISpeech2text() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="whisper-1", credentials={"server_url": "invalid_url"}) - - model.validate_credentials(model="whisper-1", credentials={"server_url": os.environ.get("LOCALAI_SERVER_URL")}) - - -def test_invoke_model(): - model = LocalAISpeech2text() - - # Get the directory of the current file - current_dir = os.path.dirname(os.path.abspath(__file__)) - - # Get assets directory - assets_dir = os.path.join(os.path.dirname(current_dir), "assets") - - # Construct the path to the audio file - audio_file_path = os.path.join(assets_dir, "audio.mp3") - - # Open the file and get the file object - with open(audio_file_path, "rb") as audio_file: - file = audio_file - - result = model.invoke( - model="whisper-1", - credentials={"server_url": os.environ.get("LOCALAI_SERVER_URL")}, - file=file, - user="abc-123", - ) - - assert isinstance(result, str) - assert result == "1, 2, 3, 4, 5, 6, 7, 8, 9, 10" diff --git a/api/tests/integration_tests/model_runtime/minimax/__init__.py b/api/tests/integration_tests/model_runtime/minimax/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/minimax/test_embedding.py b/api/tests/integration_tests/model_runtime/minimax/test_embedding.py deleted file mode 100644 index cf2a28eb9eb2fe..00000000000000 --- a/api/tests/integration_tests/model_runtime/minimax/test_embedding.py +++ /dev/null @@ -1,58 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.minimax.text_embedding.text_embedding import MinimaxTextEmbeddingModel - - -def test_validate_credentials(): - model = MinimaxTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="embo-01", - credentials={"minimax_api_key": "invalid_key", "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID")}, - ) - - model.validate_credentials( - model="embo-01", - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - }, - ) - - -def test_invoke_model(): - model = MinimaxTextEmbeddingModel() - - result = model.invoke( - model="embo-01", - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 16 - - -def test_get_num_tokens(): - model = MinimaxTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="embo-01", - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/minimax/test_llm.py b/api/tests/integration_tests/model_runtime/minimax/test_llm.py deleted file mode 100644 index aacde04d326caf..00000000000000 --- a/api/tests/integration_tests/model_runtime/minimax/test_llm.py +++ /dev/null @@ -1,143 +0,0 @@ -import os -from collections.abc import Generator -from time import sleep - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, UserPromptMessage -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.minimax.llm.llm import MinimaxLargeLanguageModel - - -def test_predefined_models(): - model = MinimaxLargeLanguageModel() - model_schemas = model.predefined_models() - assert len(model_schemas) >= 1 - assert isinstance(model_schemas[0], AIModelEntity) - - -def test_validate_credentials_for_chat_model(): - sleep(3) - model = MinimaxLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="abab5.5-chat", credentials={"minimax_api_key": "invalid_key", "minimax_group_id": "invalid_key"} - ) - - model.validate_credentials( - model="abab5.5-chat", - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - }, - ) - - -def test_invoke_model(): - sleep(3) - model = MinimaxLargeLanguageModel() - - response = model.invoke( - model="abab5-chat", - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_stream_model(): - sleep(3) - model = MinimaxLargeLanguageModel() - - response = model.invoke( - model="abab5.5-chat", - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_invoke_with_search(): - sleep(3) - model = MinimaxLargeLanguageModel() - - response = model.invoke( - model="abab5.5-chat", - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - }, - prompt_messages=[UserPromptMessage(content="北京今天的天气怎么样")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - "plugin_web_search": True, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - total_message = "" - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - total_message += chunk.delta.message.content - assert len(chunk.delta.message.content) > 0 if not chunk.delta.finish_reason else True - - assert "参考资料" in total_message - - -def test_get_num_tokens(): - sleep(3) - model = MinimaxLargeLanguageModel() - - response = model.get_num_tokens( - model="abab5.5-chat", - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - tools=[], - ) - - assert isinstance(response, int) - assert response == 30 diff --git a/api/tests/integration_tests/model_runtime/minimax/test_provider.py b/api/tests/integration_tests/model_runtime/minimax/test_provider.py deleted file mode 100644 index 575ed13eef124a..00000000000000 --- a/api/tests/integration_tests/model_runtime/minimax/test_provider.py +++ /dev/null @@ -1,25 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.minimax.minimax import MinimaxProvider - - -def test_validate_provider_credentials(): - provider = MinimaxProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials( - credentials={ - "minimax_api_key": "hahahaha", - "minimax_group_id": "123", - } - ) - - provider.validate_provider_credentials( - credentials={ - "minimax_api_key": os.environ.get("MINIMAX_API_KEY"), - "minimax_group_id": os.environ.get("MINIMAX_GROUP_ID"), - } - ) diff --git a/api/tests/integration_tests/model_runtime/mixedbread/__init__.py b/api/tests/integration_tests/model_runtime/mixedbread/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/mixedbread/test_provider.py b/api/tests/integration_tests/model_runtime/mixedbread/test_provider.py deleted file mode 100644 index 25c9f3ce8dffa9..00000000000000 --- a/api/tests/integration_tests/model_runtime/mixedbread/test_provider.py +++ /dev/null @@ -1,28 +0,0 @@ -import os -from unittest.mock import Mock, patch - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.mixedbread.mixedbread import MixedBreadProvider - - -def test_validate_provider_credentials(): - provider = MixedBreadProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={"api_key": "hahahaha"}) - with patch("requests.post") as mock_post: - mock_response = Mock() - mock_response.json.return_value = { - "usage": {"prompt_tokens": 3, "total_tokens": 3}, - "model": "mixedbread-ai/mxbai-embed-large-v1", - "data": [{"embedding": [0.23333 for _ in range(1024)], "index": 0, "object": "embedding"}], - "object": "list", - "normalized": "true", - "encoding_format": "float", - "dimensions": 1024, - } - mock_response.status_code = 200 - mock_post.return_value = mock_response - provider.validate_provider_credentials(credentials={"api_key": os.environ.get("MIXEDBREAD_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/mixedbread/test_rerank.py b/api/tests/integration_tests/model_runtime/mixedbread/test_rerank.py deleted file mode 100644 index b65aab74aa96d3..00000000000000 --- a/api/tests/integration_tests/model_runtime/mixedbread/test_rerank.py +++ /dev/null @@ -1,100 +0,0 @@ -import os -from unittest.mock import Mock, patch - -import pytest - -from core.model_runtime.entities.rerank_entities import RerankResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.mixedbread.rerank.rerank import MixedBreadRerankModel - - -def test_validate_credentials(): - model = MixedBreadRerankModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="mxbai-rerank-large-v1", - credentials={"api_key": "invalid_key"}, - ) - with patch("httpx.post") as mock_post: - mock_response = Mock() - mock_response.json.return_value = { - "usage": {"prompt_tokens": 86, "total_tokens": 86}, - "model": "mixedbread-ai/mxbai-rerank-large-v1", - "data": [ - { - "index": 0, - "score": 0.06762695, - "input": "Carson City is the capital city of the American state of Nevada. At the 2010 United " - "States Census, Carson City had a population of 55,274.", - "object": "text_document", - }, - { - "index": 1, - "score": 0.057403564, - "input": "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific " - "Ocean that are a political division controlled by the United States. Its capital is " - "Saipan.", - "object": "text_document", - }, - ], - "object": "list", - "top_k": 2, - "return_input": True, - } - mock_response.status_code = 200 - mock_post.return_value = mock_response - model.validate_credentials( - model="mxbai-rerank-large-v1", - credentials={ - "api_key": os.environ.get("MIXEDBREAD_API_KEY"), - }, - ) - - -def test_invoke_model(): - model = MixedBreadRerankModel() - with patch("httpx.post") as mock_post: - mock_response = Mock() - mock_response.json.return_value = { - "usage": {"prompt_tokens": 56, "total_tokens": 56}, - "model": "mixedbread-ai/mxbai-rerank-large-v1", - "data": [ - { - "index": 0, - "score": 0.6044922, - "input": "Kasumi is a girl name of Japanese origin meaning mist.", - "object": "text_document", - }, - { - "index": 1, - "score": 0.0703125, - "input": "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music and she leads a " - "team named PopiParty.", - "object": "text_document", - }, - ], - "object": "list", - "top_k": 2, - "return_input": "true", - } - mock_response.status_code = 200 - mock_post.return_value = mock_response - result = model.invoke( - model="mxbai-rerank-large-v1", - credentials={ - "api_key": os.environ.get("MIXEDBREAD_API_KEY"), - }, - query="Who is Kasumi?", - docs=[ - "Kasumi is a girl name of Japanese origin meaning mist.", - "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music and she leads a team named " - "PopiParty.", - ], - score_threshold=0.5, - ) - - assert isinstance(result, RerankResult) - assert len(result.docs) == 1 - assert result.docs[0].index == 0 - assert result.docs[0].score >= 0.5 diff --git a/api/tests/integration_tests/model_runtime/mixedbread/test_text_embedding.py b/api/tests/integration_tests/model_runtime/mixedbread/test_text_embedding.py deleted file mode 100644 index ca97a1895113f0..00000000000000 --- a/api/tests/integration_tests/model_runtime/mixedbread/test_text_embedding.py +++ /dev/null @@ -1,78 +0,0 @@ -import os -from unittest.mock import Mock, patch - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.mixedbread.text_embedding.text_embedding import MixedBreadTextEmbeddingModel - - -def test_validate_credentials(): - model = MixedBreadTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="mxbai-embed-large-v1", credentials={"api_key": "invalid_key"}) - with patch("requests.post") as mock_post: - mock_response = Mock() - mock_response.json.return_value = { - "usage": {"prompt_tokens": 3, "total_tokens": 3}, - "model": "mixedbread-ai/mxbai-embed-large-v1", - "data": [{"embedding": [0.23333 for _ in range(1024)], "index": 0, "object": "embedding"}], - "object": "list", - "normalized": "true", - "encoding_format": "float", - "dimensions": 1024, - } - mock_response.status_code = 200 - mock_post.return_value = mock_response - model.validate_credentials( - model="mxbai-embed-large-v1", credentials={"api_key": os.environ.get("MIXEDBREAD_API_KEY")} - ) - - -def test_invoke_model(): - model = MixedBreadTextEmbeddingModel() - - with patch("requests.post") as mock_post: - mock_response = Mock() - mock_response.json.return_value = { - "usage": {"prompt_tokens": 6, "total_tokens": 6}, - "model": "mixedbread-ai/mxbai-embed-large-v1", - "data": [ - {"embedding": [0.23333 for _ in range(1024)], "index": 0, "object": "embedding"}, - {"embedding": [0.23333 for _ in range(1024)], "index": 1, "object": "embedding"}, - ], - "object": "list", - "normalized": "true", - "encoding_format": "float", - "dimensions": 1024, - } - mock_response.status_code = 200 - mock_post.return_value = mock_response - result = model.invoke( - model="mxbai-embed-large-v1", - credentials={ - "api_key": os.environ.get("MIXEDBREAD_API_KEY"), - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 6 - - -def test_get_num_tokens(): - model = MixedBreadTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="mxbai-embed-large-v1", - credentials={ - "api_key": os.environ.get("MIXEDBREAD_API_KEY"), - }, - texts=["ping"], - ) - - assert num_tokens == 1 diff --git a/api/tests/integration_tests/model_runtime/nomic/__init__.py b/api/tests/integration_tests/model_runtime/nomic/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/nomic/test_embeddings.py b/api/tests/integration_tests/model_runtime/nomic/test_embeddings.py deleted file mode 100644 index 52dc96ee95c1bc..00000000000000 --- a/api/tests/integration_tests/model_runtime/nomic/test_embeddings.py +++ /dev/null @@ -1,62 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.nomic.text_embedding.text_embedding import NomicTextEmbeddingModel -from tests.integration_tests.model_runtime.__mock.nomic_embeddings import setup_nomic_mock - - -@pytest.mark.parametrize("setup_nomic_mock", [["text_embedding"]], indirect=True) -def test_validate_credentials(setup_nomic_mock): - model = NomicTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="nomic-embed-text-v1.5", - credentials={ - "nomic_api_key": "invalid_key", - }, - ) - - model.validate_credentials( - model="nomic-embed-text-v1.5", - credentials={ - "nomic_api_key": os.environ.get("NOMIC_API_KEY"), - }, - ) - - -@pytest.mark.parametrize("setup_nomic_mock", [["text_embedding"]], indirect=True) -def test_invoke_model(setup_nomic_mock): - model = NomicTextEmbeddingModel() - - result = model.invoke( - model="nomic-embed-text-v1.5", - credentials={ - "nomic_api_key": os.environ.get("NOMIC_API_KEY"), - }, - texts=["hello", "world"], - user="foo", - ) - - assert isinstance(result, TextEmbeddingResult) - assert result.model == "nomic-embed-text-v1.5" - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 2 - - -@pytest.mark.parametrize("setup_nomic_mock", [["text_embedding"]], indirect=True) -def test_get_num_tokens(setup_nomic_mock): - model = NomicTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="nomic-embed-text-v1.5", - credentials={ - "nomic_api_key": os.environ.get("NOMIC_API_KEY"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/nomic/test_provider.py b/api/tests/integration_tests/model_runtime/nomic/test_provider.py deleted file mode 100644 index 6cad400c069555..00000000000000 --- a/api/tests/integration_tests/model_runtime/nomic/test_provider.py +++ /dev/null @@ -1,22 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.nomic.nomic import NomicAtlasProvider -from core.model_runtime.model_providers.nomic.text_embedding.text_embedding import NomicTextEmbeddingModel -from tests.integration_tests.model_runtime.__mock.nomic_embeddings import setup_nomic_mock - - -@pytest.mark.parametrize("setup_nomic_mock", [["text_embedding"]], indirect=True) -def test_validate_provider_credentials(setup_nomic_mock): - provider = NomicAtlasProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials( - credentials={ - "nomic_api_key": os.environ.get("NOMIC_API_KEY"), - }, - ) diff --git a/api/tests/integration_tests/model_runtime/novita/__init__.py b/api/tests/integration_tests/model_runtime/novita/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/novita/test_llm.py b/api/tests/integration_tests/model_runtime/novita/test_llm.py deleted file mode 100644 index 35fa0dc1904f7b..00000000000000 --- a/api/tests/integration_tests/model_runtime/novita/test_llm.py +++ /dev/null @@ -1,99 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.novita.llm.llm import NovitaLargeLanguageModel - - -def test_validate_credentials(): - model = NovitaLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="meta-llama/llama-3-8b-instruct", credentials={"api_key": "invalid_key", "mode": "chat"} - ) - - model.validate_credentials( - model="meta-llama/llama-3-8b-instruct", - credentials={"api_key": os.environ.get("NOVITA_API_KEY"), "mode": "chat"}, - ) - - -def test_invoke_model(): - model = NovitaLargeLanguageModel() - - response = model.invoke( - model="meta-llama/llama-3-8b-instruct", - credentials={"api_key": os.environ.get("NOVITA_API_KEY"), "mode": "completion"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_p": 0.5, - "max_tokens": 10, - }, - stop=["How"], - stream=False, - user="novita", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = NovitaLargeLanguageModel() - - response = model.invoke( - model="meta-llama/llama-3-8b-instruct", - credentials={"api_key": os.environ.get("NOVITA_API_KEY"), "mode": "chat"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "max_tokens": 100}, - stream=True, - user="novita", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - - -def test_get_num_tokens(): - model = NovitaLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="meta-llama/llama-3-8b-instruct", - credentials={ - "api_key": os.environ.get("NOVITA_API_KEY"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/novita/test_provider.py b/api/tests/integration_tests/model_runtime/novita/test_provider.py deleted file mode 100644 index 191af99db20bd9..00000000000000 --- a/api/tests/integration_tests/model_runtime/novita/test_provider.py +++ /dev/null @@ -1,19 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.novita.novita import NovitaProvider - - -def test_validate_provider_credentials(): - provider = NovitaProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials( - credentials={ - "api_key": os.environ.get("NOVITA_API_KEY"), - } - ) diff --git a/api/tests/integration_tests/model_runtime/oci/__init__.py b/api/tests/integration_tests/model_runtime/oci/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/oci/test_llm.py b/api/tests/integration_tests/model_runtime/oci/test_llm.py deleted file mode 100644 index 531f26a32e657c..00000000000000 --- a/api/tests/integration_tests/model_runtime/oci/test_llm.py +++ /dev/null @@ -1,130 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.oci.llm.llm import OCILargeLanguageModel - - -def test_validate_credentials(): - model = OCILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="cohere.command-r-plus", - credentials={"oci_config_content": "invalid_key", "oci_key_content": "invalid_key"}, - ) - - model.validate_credentials( - model="cohere.command-r-plus", - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - }, - ) - - -def test_invoke_model(): - model = OCILargeLanguageModel() - - response = model.invoke( - model="cohere.command-r-plus", - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - }, - prompt_messages=[UserPromptMessage(content="Hi")], - model_parameters={"temperature": 0.5, "max_tokens": 10}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = OCILargeLanguageModel() - - response = model.invoke( - model="meta.llama-3-70b-instruct", - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - }, - prompt_messages=[UserPromptMessage(content="Hi")], - model_parameters={"temperature": 0.5, "max_tokens": 100, "seed": 1234}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_invoke_model_with_function(): - model = OCILargeLanguageModel() - - response = model.invoke( - model="cohere.command-r-plus", - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - }, - prompt_messages=[UserPromptMessage(content="Hi")], - model_parameters={"temperature": 0.5, "max_tokens": 100, "seed": 1234}, - stream=False, - user="abc-123", - tools=[ - PromptMessageTool( - name="get_current_weather", - description="Get the current weather in a given location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}, - }, - "required": ["location"], - }, - ) - ], - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_get_num_tokens(): - model = OCILargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="cohere.command-r-plus", - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 18 diff --git a/api/tests/integration_tests/model_runtime/oci/test_provider.py b/api/tests/integration_tests/model_runtime/oci/test_provider.py deleted file mode 100644 index 2c7107c7ccfe45..00000000000000 --- a/api/tests/integration_tests/model_runtime/oci/test_provider.py +++ /dev/null @@ -1,20 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.oci.oci import OCIGENAIProvider - - -def test_validate_provider_credentials(): - provider = OCIGENAIProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials( - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - } - ) diff --git a/api/tests/integration_tests/model_runtime/oci/test_text_embedding.py b/api/tests/integration_tests/model_runtime/oci/test_text_embedding.py deleted file mode 100644 index 032c5c681a7aeb..00000000000000 --- a/api/tests/integration_tests/model_runtime/oci/test_text_embedding.py +++ /dev/null @@ -1,58 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.oci.text_embedding.text_embedding import OCITextEmbeddingModel - - -def test_validate_credentials(): - model = OCITextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="cohere.embed-multilingual-v3.0", - credentials={"oci_config_content": "invalid_key", "oci_key_content": "invalid_key"}, - ) - - model.validate_credentials( - model="cohere.embed-multilingual-v3.0", - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - }, - ) - - -def test_invoke_model(): - model = OCITextEmbeddingModel() - - result = model.invoke( - model="cohere.embed-multilingual-v3.0", - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - }, - texts=["hello", "world", " ".join(["long_text"] * 100), " ".join(["another_long_text"] * 100)], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 4 - # assert result.usage.total_tokens == 811 - - -def test_get_num_tokens(): - model = OCITextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="cohere.embed-multilingual-v3.0", - credentials={ - "oci_config_content": os.environ.get("OCI_CONFIG_CONTENT"), - "oci_key_content": os.environ.get("OCI_KEY_CONTENT"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/ollama/__init__.py b/api/tests/integration_tests/model_runtime/ollama/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/ollama/test_llm.py b/api/tests/integration_tests/model_runtime/ollama/test_llm.py deleted file mode 100644 index 58a1339f506458..00000000000000 --- a/api/tests/integration_tests/model_runtime/ollama/test_llm.py +++ /dev/null @@ -1,222 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.ollama.llm.llm import OllamaLargeLanguageModel - - -def test_validate_credentials(): - model = OllamaLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="mistral:text", - credentials={ - "base_url": "http://localhost:21434", - "mode": "chat", - "context_size": 2048, - "max_tokens": 2048, - }, - ) - - model.validate_credentials( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "chat", - "context_size": 2048, - "max_tokens": 2048, - }, - ) - - -def test_invoke_model(): - model = OllamaLargeLanguageModel() - - response = model.invoke( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "chat", - "context_size": 2048, - "max_tokens": 2048, - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "num_predict": 10}, - stop=["How"], - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = OllamaLargeLanguageModel() - - response = model.invoke( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "chat", - "context_size": 2048, - "max_tokens": 2048, - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "num_predict": 10}, - stop=["How"], - stream=True, - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - - -def test_invoke_completion_model(): - model = OllamaLargeLanguageModel() - - response = model.invoke( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "completion", - "context_size": 2048, - "max_tokens": 2048, - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "num_predict": 10}, - stop=["How"], - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_completion_model(): - model = OllamaLargeLanguageModel() - - response = model.invoke( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "completion", - "context_size": 2048, - "max_tokens": 2048, - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "num_predict": 10}, - stop=["How"], - stream=True, - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - - -def test_invoke_completion_model_with_vision(): - model = OllamaLargeLanguageModel() - - result = model.invoke( - model="llava", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "completion", - "context_size": 2048, - "max_tokens": 2048, - }, - prompt_messages=[ - UserPromptMessage( - content=[ - TextPromptMessageContent( - data="What is this in this picture?", - ), - ImagePromptMessageContent( - 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" - ), - ] - ) - ], - model_parameters={"temperature": 0.1, "num_predict": 100}, - stream=False, - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -def test_invoke_chat_model_with_vision(): - model = OllamaLargeLanguageModel() - - result = model.invoke( - model="llava", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "chat", - "context_size": 2048, - "max_tokens": 2048, - }, - prompt_messages=[ - UserPromptMessage( - content=[ - TextPromptMessageContent( - data="What is this in this picture?", - ), - ImagePromptMessageContent( - 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" - ), - ] - ) - ], - model_parameters={"temperature": 0.1, "num_predict": 100}, - stream=False, - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -def test_get_num_tokens(): - model = OllamaLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "chat", - "context_size": 2048, - "max_tokens": 2048, - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 6 diff --git a/api/tests/integration_tests/model_runtime/ollama/test_text_embedding.py b/api/tests/integration_tests/model_runtime/ollama/test_text_embedding.py deleted file mode 100644 index 3c4f740a4fd09c..00000000000000 --- a/api/tests/integration_tests/model_runtime/ollama/test_text_embedding.py +++ /dev/null @@ -1,65 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.ollama.text_embedding.text_embedding import OllamaEmbeddingModel - - -def test_validate_credentials(): - model = OllamaEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="mistral:text", - credentials={ - "base_url": "http://localhost:21434", - "mode": "chat", - "context_size": 4096, - }, - ) - - model.validate_credentials( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "chat", - "context_size": 4096, - }, - ) - - -def test_invoke_model(): - model = OllamaEmbeddingModel() - - result = model.invoke( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "chat", - "context_size": 4096, - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 2 - - -def test_get_num_tokens(): - model = OllamaEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="mistral:text", - credentials={ - "base_url": os.environ.get("OLLAMA_BASE_URL"), - "mode": "chat", - "context_size": 4096, - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/openai/test_llm.py b/api/tests/integration_tests/model_runtime/openai/test_llm.py deleted file mode 100644 index 3b3ea9ec800cbb..00000000000000 --- a/api/tests/integration_tests/model_runtime/openai/test_llm.py +++ /dev/null @@ -1,313 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity, ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.openai.llm.llm import OpenAILargeLanguageModel - -"""FOR MOCK FIXTURES, DO NOT REMOVE""" -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -def test_predefined_models(): - model = OpenAILargeLanguageModel() - model_schemas = model.predefined_models() - - assert len(model_schemas) >= 1 - assert isinstance(model_schemas[0], AIModelEntity) - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_credentials_for_chat_model(setup_openai_mock): - model = OpenAILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="gpt-3.5-turbo", credentials={"openai_api_key": "invalid_key"}) - - model.validate_credentials(model="gpt-3.5-turbo", credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}) - - -@pytest.mark.parametrize("setup_openai_mock", [["completion"]], indirect=True) -def test_validate_credentials_for_completion_model(setup_openai_mock): - model = OpenAILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="text-davinci-003", credentials={"openai_api_key": "invalid_key"}) - - model.validate_credentials( - model="text-davinci-003", credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")} - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["completion"]], indirect=True) -def test_invoke_completion_model(setup_openai_mock): - model = OpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-3.5-turbo-instruct", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY"), "openai_api_base": "https://api.openai.com"}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.0, "max_tokens": 1}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - assert model._num_tokens_from_string("gpt-3.5-turbo-instruct", result.message.content) == 1 - - -@pytest.mark.parametrize("setup_openai_mock", [["completion"]], indirect=True) -def test_invoke_stream_completion_model(setup_openai_mock): - model = OpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-3.5-turbo-instruct", - credentials={ - "openai_api_key": os.environ.get("OPENAI_API_KEY"), - "openai_organization": os.environ.get("OPENAI_ORGANIZATION"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model(setup_openai_mock): - model = OpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-3.5-turbo", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.0, - "top_p": 1.0, - "presence_penalty": 0.0, - "frequency_penalty": 0.0, - "max_tokens": 10, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model_with_vision(setup_openai_mock): - model = OpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-4-vision-preview", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content=[ - TextPromptMessageContent( - data="Hello World!", - ), - ImagePromptMessageContent( - 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" - ), - ] - ), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model_with_tools(setup_openai_mock): - model = OpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-3.5-turbo", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content="what's the weather today in London?", - ), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ), - PromptMessageTool( - name="get_stock_price", - description="Get the current stock price", - parameters={ - "type": "object", - "properties": {"symbol": {"type": "string", "description": "The stock symbol"}}, - "required": ["symbol"], - }, - ), - ], - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert isinstance(result.message, AssistantPromptMessage) - assert len(result.message.tool_calls) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_stream_chat_model(setup_openai_mock): - model = OpenAILargeLanguageModel() - - result = model.invoke( - model="gpt-3.5-turbo", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - if chunk.delta.finish_reason is not None: - assert chunk.delta.usage is not None - assert chunk.delta.usage.completion_tokens > 0 - - -def test_get_num_tokens(): - model = OpenAILargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="gpt-3.5-turbo-instruct", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - ) - - assert num_tokens == 3 - - num_tokens = model.get_num_tokens( - model="gpt-3.5-turbo", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ), - ], - ) - - assert num_tokens == 72 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat", "remote"]], indirect=True) -def test_fine_tuned_models(setup_openai_mock): - model = OpenAILargeLanguageModel() - - remote_models = model.remote_models(credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}) - - if not remote_models: - assert isinstance(remote_models, list) - else: - assert isinstance(remote_models[0], AIModelEntity) - - for llm_model in remote_models: - if llm_model.model_type == ModelType.LLM: - break - - assert isinstance(llm_model, AIModelEntity) - - # test invoke - result = model.invoke( - model=llm_model.model, - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - - -def test__get_num_tokens_by_gpt2(): - model = OpenAILargeLanguageModel() - num_tokens = model._get_num_tokens_by_gpt2("Hello World!") - - assert num_tokens == 3 diff --git a/api/tests/integration_tests/model_runtime/openai/test_provider.py b/api/tests/integration_tests/model_runtime/openai/test_provider.py deleted file mode 100644 index 4d56cfcf3c25f0..00000000000000 --- a/api/tests/integration_tests/model_runtime/openai/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openai.openai import OpenAIProvider -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_provider_credentials(setup_openai_mock): - provider = OpenAIProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/openai/test_speech2text.py b/api/tests/integration_tests/model_runtime/openai/test_speech2text.py deleted file mode 100644 index aa92c8b61fb684..00000000000000 --- a/api/tests/integration_tests/model_runtime/openai/test_speech2text.py +++ /dev/null @@ -1,45 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openai.speech2text.speech2text import OpenAISpeech2TextModel -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["speech2text"]], indirect=True) -def test_validate_credentials(setup_openai_mock): - model = OpenAISpeech2TextModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="whisper-1", credentials={"openai_api_key": "invalid_key"}) - - model.validate_credentials(model="whisper-1", credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}) - - -@pytest.mark.parametrize("setup_openai_mock", [["speech2text"]], indirect=True) -def test_invoke_model(setup_openai_mock): - model = OpenAISpeech2TextModel() - - # Get the directory of the current file - current_dir = os.path.dirname(os.path.abspath(__file__)) - - # Get assets directory - assets_dir = os.path.join(os.path.dirname(current_dir), "assets") - - # Construct the path to the audio file - audio_file_path = os.path.join(assets_dir, "audio.mp3") - - # Open the file and get the file object - with open(audio_file_path, "rb") as audio_file: - file = audio_file - - result = model.invoke( - model="whisper-1", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")}, - file=file, - user="abc-123", - ) - - assert isinstance(result, str) - assert result == "1, 2, 3, 4, 5, 6, 7, 8, 9, 10" diff --git a/api/tests/integration_tests/model_runtime/openai/test_text_embedding.py b/api/tests/integration_tests/model_runtime/openai/test_text_embedding.py deleted file mode 100644 index f5dd73f2d4cd60..00000000000000 --- a/api/tests/integration_tests/model_runtime/openai/test_text_embedding.py +++ /dev/null @@ -1,48 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openai.text_embedding.text_embedding import OpenAITextEmbeddingModel -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["text_embedding"]], indirect=True) -def test_validate_credentials(setup_openai_mock): - model = OpenAITextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="text-embedding-ada-002", credentials={"openai_api_key": "invalid_key"}) - - model.validate_credentials( - model="text-embedding-ada-002", credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY")} - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["text_embedding"]], indirect=True) -def test_invoke_model(setup_openai_mock): - model = OpenAITextEmbeddingModel() - - result = model.invoke( - model="text-embedding-ada-002", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY"), "openai_api_base": "https://api.openai.com"}, - texts=["hello", "world", " ".join(["long_text"] * 100), " ".join(["another_long_text"] * 100)], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 4 - assert result.usage.total_tokens == 2 - - -def test_get_num_tokens(): - model = OpenAITextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="text-embedding-ada-002", - credentials={"openai_api_key": os.environ.get("OPENAI_API_KEY"), "openai_api_base": "https://api.openai.com"}, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/openai_api_compatible/__init__.py b/api/tests/integration_tests/model_runtime/openai_api_compatible/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/openai_api_compatible/test_llm.py b/api/tests/integration_tests/model_runtime/openai_api_compatible/test_llm.py deleted file mode 100644 index f2302ef05e06de..00000000000000 --- a/api/tests/integration_tests/model_runtime/openai_api_compatible/test_llm.py +++ /dev/null @@ -1,197 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel - -""" -Using Together.ai's OpenAI-compatible API as testing endpoint -""" - - -def test_validate_credentials(): - model = OAIAPICompatLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={"api_key": "invalid_key", "endpoint_url": "https://api.together.xyz/v1/", "mode": "chat"}, - ) - - model.validate_credentials( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={ - "api_key": os.environ.get("TOGETHER_API_KEY"), - "endpoint_url": "https://api.together.xyz/v1/", - "mode": "chat", - }, - ) - - -def test_invoke_model(): - model = OAIAPICompatLargeLanguageModel() - - response = model.invoke( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={ - "api_key": os.environ.get("TOGETHER_API_KEY"), - "endpoint_url": "https://api.together.xyz/v1/", - "mode": "completion", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = OAIAPICompatLargeLanguageModel() - - response = model.invoke( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={ - "api_key": os.environ.get("TOGETHER_API_KEY"), - "endpoint_url": "https://api.together.xyz/v1/", - "mode": "chat", - "stream_mode_delimiter": "\\n\\n", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - - -def test_invoke_stream_model_without_delimiter(): - model = OAIAPICompatLargeLanguageModel() - - response = model.invoke( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={ - "api_key": os.environ.get("TOGETHER_API_KEY"), - "endpoint_url": "https://api.together.xyz/v1/", - "mode": "chat", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - - -# using OpenAI's ChatGPT-3.5 as testing endpoint -def test_invoke_chat_model_with_tools(): - model = OAIAPICompatLargeLanguageModel() - - result = model.invoke( - model="gpt-3.5-turbo", - credentials={ - "api_key": os.environ.get("OPENAI_API_KEY"), - "endpoint_url": "https://api.openai.com/v1/", - "mode": "chat", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content="what's the weather today in London?", - ), - ], - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}, - }, - "required": ["location"], - }, - ), - ], - model_parameters={"temperature": 0.0, "max_tokens": 1024}, - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert isinstance(result.message, AssistantPromptMessage) - assert len(result.message.tool_calls) > 0 - - -def test_get_num_tokens(): - model = OAIAPICompatLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={"api_key": os.environ.get("OPENAI_API_KEY"), "endpoint_url": "https://api.openai.com/v1/"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/openai_api_compatible/test_speech2text.py b/api/tests/integration_tests/model_runtime/openai_api_compatible/test_speech2text.py deleted file mode 100644 index cf805eafff4968..00000000000000 --- a/api/tests/integration_tests/model_runtime/openai_api_compatible/test_speech2text.py +++ /dev/null @@ -1,50 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openai_api_compatible.speech2text.speech2text import ( - OAICompatSpeech2TextModel, -) - - -def test_validate_credentials(): - model = OAICompatSpeech2TextModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="whisper-1", - credentials={"api_key": "invalid_key", "endpoint_url": "https://api.openai.com/v1/"}, - ) - - model.validate_credentials( - model="whisper-1", - credentials={"api_key": os.environ.get("OPENAI_API_KEY"), "endpoint_url": "https://api.openai.com/v1/"}, - ) - - -def test_invoke_model(): - model = OAICompatSpeech2TextModel() - - # Get the directory of the current file - current_dir = os.path.dirname(os.path.abspath(__file__)) - - # Get assets directory - assets_dir = os.path.join(os.path.dirname(current_dir), "assets") - - # Construct the path to the audio file - audio_file_path = os.path.join(assets_dir, "audio.mp3") - - # Open the file and get the file object - with open(audio_file_path, "rb") as audio_file: - file = audio_file - - result = model.invoke( - model="whisper-1", - credentials={"api_key": os.environ.get("OPENAI_API_KEY"), "endpoint_url": "https://api.openai.com/v1/"}, - file=file, - user="abc-123", - ) - - assert isinstance(result, str) - assert result == "1, 2, 3, 4, 5, 6, 7, 8, 9, 10" diff --git a/api/tests/integration_tests/model_runtime/openai_api_compatible/test_text_embedding.py b/api/tests/integration_tests/model_runtime/openai_api_compatible/test_text_embedding.py deleted file mode 100644 index 052b41605f6da2..00000000000000 --- a/api/tests/integration_tests/model_runtime/openai_api_compatible/test_text_embedding.py +++ /dev/null @@ -1,67 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openai_api_compatible.text_embedding.text_embedding import ( - OAICompatEmbeddingModel, -) - -""" -Using OpenAI's API as testing endpoint -""" - - -def test_validate_credentials(): - model = OAICompatEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="text-embedding-ada-002", - credentials={"api_key": "invalid_key", "endpoint_url": "https://api.openai.com/v1/", "context_size": 8184}, - ) - - model.validate_credentials( - model="text-embedding-ada-002", - credentials={ - "api_key": os.environ.get("OPENAI_API_KEY"), - "endpoint_url": "https://api.openai.com/v1/", - "context_size": 8184, - }, - ) - - -def test_invoke_model(): - model = OAICompatEmbeddingModel() - - result = model.invoke( - model="text-embedding-ada-002", - credentials={ - "api_key": os.environ.get("OPENAI_API_KEY"), - "endpoint_url": "https://api.openai.com/v1/", - "context_size": 8184, - }, - texts=["hello", "world", " ".join(["long_text"] * 100), " ".join(["another_long_text"] * 100)], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 4 - assert result.usage.total_tokens == 502 - - -def test_get_num_tokens(): - model = OAICompatEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="text-embedding-ada-002", - credentials={ - "api_key": os.environ.get("OPENAI_API_KEY"), - "endpoint_url": "https://api.openai.com/v1/embeddings", - "context_size": 8184, - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/openllm/__init__.py b/api/tests/integration_tests/model_runtime/openllm/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/openllm/test_embedding.py b/api/tests/integration_tests/model_runtime/openllm/test_embedding.py deleted file mode 100644 index 14d47217af62c8..00000000000000 --- a/api/tests/integration_tests/model_runtime/openllm/test_embedding.py +++ /dev/null @@ -1,57 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openllm.text_embedding.text_embedding import OpenLLMTextEmbeddingModel - - -def test_validate_credentials(): - model = OpenLLMTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="NOT IMPORTANT", - credentials={ - "server_url": "ww" + os.environ.get("OPENLLM_SERVER_URL"), - }, - ) - - model.validate_credentials( - model="NOT IMPORTANT", - credentials={ - "server_url": os.environ.get("OPENLLM_SERVER_URL"), - }, - ) - - -def test_invoke_model(): - model = OpenLLMTextEmbeddingModel() - - result = model.invoke( - model="NOT IMPORTANT", - credentials={ - "server_url": os.environ.get("OPENLLM_SERVER_URL"), - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens > 0 - - -def test_get_num_tokens(): - model = OpenLLMTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="NOT IMPORTANT", - credentials={ - "server_url": os.environ.get("OPENLLM_SERVER_URL"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/openllm/test_llm.py b/api/tests/integration_tests/model_runtime/openllm/test_llm.py deleted file mode 100644 index 35939e3cfe8bfd..00000000000000 --- a/api/tests/integration_tests/model_runtime/openllm/test_llm.py +++ /dev/null @@ -1,95 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openllm.llm.llm import OpenLLMLargeLanguageModel - - -def test_validate_credentials_for_chat_model(): - model = OpenLLMLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="NOT IMPORTANT", - credentials={ - "server_url": "invalid_key", - }, - ) - - model.validate_credentials( - model="NOT IMPORTANT", - credentials={ - "server_url": os.environ.get("OPENLLM_SERVER_URL"), - }, - ) - - -def test_invoke_model(): - model = OpenLLMLargeLanguageModel() - - response = model.invoke( - model="NOT IMPORTANT", - credentials={ - "server_url": os.environ.get("OPENLLM_SERVER_URL"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_stream_model(): - model = OpenLLMLargeLanguageModel() - - response = model.invoke( - model="NOT IMPORTANT", - credentials={ - "server_url": os.environ.get("OPENLLM_SERVER_URL"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = OpenLLMLargeLanguageModel() - - response = model.get_num_tokens( - model="NOT IMPORTANT", - credentials={ - "server_url": os.environ.get("OPENLLM_SERVER_URL"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - tools=[], - ) - - assert isinstance(response, int) - assert response == 3 diff --git a/api/tests/integration_tests/model_runtime/openrouter/__init__.py b/api/tests/integration_tests/model_runtime/openrouter/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/openrouter/test_llm.py b/api/tests/integration_tests/model_runtime/openrouter/test_llm.py deleted file mode 100644 index ce4876a73a740e..00000000000000 --- a/api/tests/integration_tests/model_runtime/openrouter/test_llm.py +++ /dev/null @@ -1,104 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.openrouter.llm.llm import OpenRouterLargeLanguageModel - - -def test_validate_credentials(): - model = OpenRouterLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="mistralai/mixtral-8x7b-instruct", credentials={"api_key": "invalid_key", "mode": "chat"} - ) - - model.validate_credentials( - model="mistralai/mixtral-8x7b-instruct", - credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "chat"}, - ) - - -def test_invoke_model(): - model = OpenRouterLargeLanguageModel() - - response = model.invoke( - model="mistralai/mixtral-8x7b-instruct", - credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "completion"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = OpenRouterLargeLanguageModel() - - response = model.invoke( - model="mistralai/mixtral-8x7b-instruct", - credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "chat"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - - -def test_get_num_tokens(): - model = OpenRouterLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="mistralai/mixtral-8x7b-instruct", - credentials={ - "api_key": os.environ.get("TOGETHER_API_KEY"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/replicate/__init__.py b/api/tests/integration_tests/model_runtime/replicate/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/replicate/test_llm.py b/api/tests/integration_tests/model_runtime/replicate/test_llm.py deleted file mode 100644 index b940005b715760..00000000000000 --- a/api/tests/integration_tests/model_runtime/replicate/test_llm.py +++ /dev/null @@ -1,112 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.replicate.llm.llm import ReplicateLargeLanguageModel - - -def test_validate_credentials(): - model = ReplicateLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="meta/llama-2-13b-chat", - credentials={ - "replicate_api_token": "invalid_key", - "model_version": "f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d", - }, - ) - - model.validate_credentials( - model="meta/llama-2-13b-chat", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d", - }, - ) - - -def test_invoke_model(): - model = ReplicateLargeLanguageModel() - - response = model.invoke( - model="meta/llama-2-13b-chat", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = ReplicateLargeLanguageModel() - - response = model.invoke( - model="mistralai/mixtral-8x7b-instruct-v0.1", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "2b56576fcfbe32fa0526897d8385dd3fb3d36ba6fd0dbe033c72886b81ade93e", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - - -def test_get_num_tokens(): - model = ReplicateLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "2b56576fcfbe32fa0526897d8385dd3fb3d36ba6fd0dbe033c72886b81ade93e", - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 14 diff --git a/api/tests/integration_tests/model_runtime/replicate/test_text_embedding.py b/api/tests/integration_tests/model_runtime/replicate/test_text_embedding.py deleted file mode 100644 index 397715f2252083..00000000000000 --- a/api/tests/integration_tests/model_runtime/replicate/test_text_embedding.py +++ /dev/null @@ -1,136 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.replicate.text_embedding.text_embedding import ReplicateEmbeddingModel - - -def test_validate_credentials_one(): - model = ReplicateEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="replicate/all-mpnet-base-v2", - credentials={ - "replicate_api_token": "invalid_key", - "model_version": "b6b7585c9640cd7a9572c6e129c9549d79c9c31f0d3fdce7baac7c67ca38f305", - }, - ) - - model.validate_credentials( - model="replicate/all-mpnet-base-v2", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "b6b7585c9640cd7a9572c6e129c9549d79c9c31f0d3fdce7baac7c67ca38f305", - }, - ) - - -def test_validate_credentials_two(): - model = ReplicateEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="nateraw/bge-large-en-v1.5", - credentials={ - "replicate_api_token": "invalid_key", - "model_version": "9cf9f015a9cb9c61d1a2610659cdac4a4ca222f2d3707a68517b18c198a9add1", - }, - ) - - model.validate_credentials( - model="nateraw/bge-large-en-v1.5", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "9cf9f015a9cb9c61d1a2610659cdac4a4ca222f2d3707a68517b18c198a9add1", - }, - ) - - -def test_invoke_model_one(): - model = ReplicateEmbeddingModel() - - result = model.invoke( - model="nateraw/bge-large-en-v1.5", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "9cf9f015a9cb9c61d1a2610659cdac4a4ca222f2d3707a68517b18c198a9add1", - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 2 - - -def test_invoke_model_two(): - model = ReplicateEmbeddingModel() - - result = model.invoke( - model="andreasjansson/clip-features", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "75b33f253f7714a281ad3e9b28f63e3232d583716ef6718f2e46641077ea040a", - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 2 - - -def test_invoke_model_three(): - model = ReplicateEmbeddingModel() - - result = model.invoke( - model="replicate/all-mpnet-base-v2", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "b6b7585c9640cd7a9572c6e129c9549d79c9c31f0d3fdce7baac7c67ca38f305", - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 2 - - -def test_invoke_model_four(): - model = ReplicateEmbeddingModel() - - result = model.invoke( - model="nateraw/jina-embeddings-v2-base-en", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "f8367a1c072ba2bc28af549d1faeacfe9b88b3f0e475add7a75091dac507f79e", - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 2 - - -def test_get_num_tokens(): - model = ReplicateEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="nateraw/jina-embeddings-v2-base-en", - credentials={ - "replicate_api_token": os.environ.get("REPLICATE_API_KEY"), - "model_version": "f8367a1c072ba2bc28af549d1faeacfe9b88b3f0e475add7a75091dac507f79e", - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/sagemaker/__init__.py b/api/tests/integration_tests/model_runtime/sagemaker/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/sagemaker/test_provider.py b/api/tests/integration_tests/model_runtime/sagemaker/test_provider.py deleted file mode 100644 index 9f0b439d6c32a1..00000000000000 --- a/api/tests/integration_tests/model_runtime/sagemaker/test_provider.py +++ /dev/null @@ -1,15 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.sagemaker.sagemaker import SageMakerProvider - - -def test_validate_provider_credentials(): - provider = SageMakerProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={}) diff --git a/api/tests/integration_tests/model_runtime/sagemaker/test_rerank.py b/api/tests/integration_tests/model_runtime/sagemaker/test_rerank.py deleted file mode 100644 index d5a6798a1ef735..00000000000000 --- a/api/tests/integration_tests/model_runtime/sagemaker/test_rerank.py +++ /dev/null @@ -1,55 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.rerank_entities import RerankResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.sagemaker.rerank.rerank import SageMakerRerankModel - - -def test_validate_credentials(): - model = SageMakerRerankModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="bge-m3-rerank-v2", - credentials={ - "aws_region": os.getenv("AWS_REGION"), - "aws_access_key": os.getenv("AWS_ACCESS_KEY"), - "aws_secret_access_key": os.getenv("AWS_SECRET_ACCESS_KEY"), - }, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - - -def test_invoke_model(): - model = SageMakerRerankModel() - - result = model.invoke( - model="bge-m3-rerank-v2", - credentials={ - "aws_region": os.getenv("AWS_REGION"), - "aws_access_key": os.getenv("AWS_ACCESS_KEY"), - "aws_secret_access_key": os.getenv("AWS_SECRET_ACCESS_KEY"), - }, - query="What is the capital of the United States?", - docs=[ - "Carson City is the capital city of the American state of Nevada. At the 2010 United States " - "Census, Carson City had a population of 55,274.", - "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that " - "are a political division controlled by the United States. Its capital is Saipan.", - ], - score_threshold=0.8, - ) - - assert isinstance(result, RerankResult) - assert len(result.docs) == 1 - assert result.docs[0].index == 1 - assert result.docs[0].score >= 0.8 diff --git a/api/tests/integration_tests/model_runtime/sagemaker/test_text_embedding.py b/api/tests/integration_tests/model_runtime/sagemaker/test_text_embedding.py deleted file mode 100644 index e4e404c7a86ae6..00000000000000 --- a/api/tests/integration_tests/model_runtime/sagemaker/test_text_embedding.py +++ /dev/null @@ -1,33 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.sagemaker.text_embedding.text_embedding import SageMakerEmbeddingModel - - -def test_validate_credentials(): - model = SageMakerEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="bge-m3", credentials={}) - - model.validate_credentials(model="bge-m3-embedding", credentials={}) - - -def test_invoke_model(): - model = SageMakerEmbeddingModel() - - result = model.invoke(model="bge-m3-embedding", credentials={}, texts=["hello", "world"], user="abc-123") - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - - -def test_get_num_tokens(): - model = SageMakerEmbeddingModel() - - num_tokens = model.get_num_tokens(model="bge-m3-embedding", credentials={}, texts=[]) - - assert num_tokens == 0 diff --git a/api/tests/integration_tests/model_runtime/siliconflow/__init__.py b/api/tests/integration_tests/model_runtime/siliconflow/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/siliconflow/test_llm.py b/api/tests/integration_tests/model_runtime/siliconflow/test_llm.py deleted file mode 100644 index f47c9c558808af..00000000000000 --- a/api/tests/integration_tests/model_runtime/siliconflow/test_llm.py +++ /dev/null @@ -1,73 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.siliconflow.llm.llm import SiliconflowLargeLanguageModel - - -def test_validate_credentials(): - model = SiliconflowLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="deepseek-ai/DeepSeek-V2-Chat", credentials={"api_key": "invalid_key"}) - - model.validate_credentials(model="deepseek-ai/DeepSeek-V2-Chat", credentials={"api_key": os.environ.get("API_KEY")}) - - -def test_invoke_model(): - model = SiliconflowLargeLanguageModel() - - response = model.invoke( - model="deepseek-ai/DeepSeek-V2-Chat", - credentials={"api_key": os.environ.get("API_KEY")}, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={"temperature": 0.5, "max_tokens": 10}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = SiliconflowLargeLanguageModel() - - response = model.invoke( - model="deepseek-ai/DeepSeek-V2-Chat", - credentials={"api_key": os.environ.get("API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.5, "max_tokens": 100, "seed": 1234}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = SiliconflowLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="deepseek-ai/DeepSeek-V2-Chat", - credentials={"api_key": os.environ.get("API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 12 diff --git a/api/tests/integration_tests/model_runtime/siliconflow/test_provider.py b/api/tests/integration_tests/model_runtime/siliconflow/test_provider.py deleted file mode 100644 index 8f70210b7a2ace..00000000000000 --- a/api/tests/integration_tests/model_runtime/siliconflow/test_provider.py +++ /dev/null @@ -1,15 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.siliconflow.siliconflow import SiliconflowProvider - - -def test_validate_provider_credentials(): - provider = SiliconflowProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={"api_key": os.environ.get("API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/siliconflow/test_rerank.py b/api/tests/integration_tests/model_runtime/siliconflow/test_rerank.py deleted file mode 100644 index ad794613f91013..00000000000000 --- a/api/tests/integration_tests/model_runtime/siliconflow/test_rerank.py +++ /dev/null @@ -1,47 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.rerank_entities import RerankResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.siliconflow.rerank.rerank import SiliconflowRerankModel - - -def test_validate_credentials(): - model = SiliconflowRerankModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="BAAI/bge-reranker-v2-m3", - credentials={"api_key": "invalid_key"}, - ) - - model.validate_credentials( - model="BAAI/bge-reranker-v2-m3", - credentials={ - "api_key": os.environ.get("API_KEY"), - }, - ) - - -def test_invoke_model(): - model = SiliconflowRerankModel() - - result = model.invoke( - model="BAAI/bge-reranker-v2-m3", - credentials={ - "api_key": os.environ.get("API_KEY"), - }, - query="Who is Kasumi?", - docs=[ - 'Kasumi is a girl\'s name of Japanese origin meaning "mist".', - "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music ", - "and she leads a team named PopiParty.", - ], - score_threshold=0.8, - ) - - assert isinstance(result, RerankResult) - assert len(result.docs) == 1 - assert result.docs[0].index == 0 - assert result.docs[0].score >= 0.8 diff --git a/api/tests/integration_tests/model_runtime/siliconflow/test_speech2text.py b/api/tests/integration_tests/model_runtime/siliconflow/test_speech2text.py deleted file mode 100644 index 0502ba5ab404bc..00000000000000 --- a/api/tests/integration_tests/model_runtime/siliconflow/test_speech2text.py +++ /dev/null @@ -1,45 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.siliconflow.speech2text.speech2text import SiliconflowSpeech2TextModel - - -def test_validate_credentials(): - model = SiliconflowSpeech2TextModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="iic/SenseVoiceSmall", - credentials={"api_key": "invalid_key"}, - ) - - model.validate_credentials( - model="iic/SenseVoiceSmall", - credentials={"api_key": os.environ.get("API_KEY")}, - ) - - -def test_invoke_model(): - model = SiliconflowSpeech2TextModel() - - # Get the directory of the current file - current_dir = os.path.dirname(os.path.abspath(__file__)) - - # Get assets directory - assets_dir = os.path.join(os.path.dirname(current_dir), "assets") - - # Construct the path to the audio file - audio_file_path = os.path.join(assets_dir, "audio.mp3") - - # Open the file and get the file object - with open(audio_file_path, "rb") as audio_file: - file = audio_file - - result = model.invoke( - model="iic/SenseVoiceSmall", credentials={"api_key": os.environ.get("API_KEY")}, file=file - ) - - assert isinstance(result, str) - assert result == "1,2,3,4,5,6,7,8,9,10." diff --git a/api/tests/integration_tests/model_runtime/siliconflow/test_text_embedding.py b/api/tests/integration_tests/model_runtime/siliconflow/test_text_embedding.py deleted file mode 100644 index ab143c10613a88..00000000000000 --- a/api/tests/integration_tests/model_runtime/siliconflow/test_text_embedding.py +++ /dev/null @@ -1,60 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.siliconflow.text_embedding.text_embedding import ( - SiliconflowTextEmbeddingModel, -) - - -def test_validate_credentials(): - model = SiliconflowTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="BAAI/bge-large-zh-v1.5", - credentials={"api_key": "invalid_key"}, - ) - - model.validate_credentials( - model="BAAI/bge-large-zh-v1.5", - credentials={ - "api_key": os.environ.get("API_KEY"), - }, - ) - - -def test_invoke_model(): - model = SiliconflowTextEmbeddingModel() - - result = model.invoke( - model="BAAI/bge-large-zh-v1.5", - credentials={ - "api_key": os.environ.get("API_KEY"), - }, - texts=[ - "hello", - "world", - ], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens == 6 - - -def test_get_num_tokens(): - model = SiliconflowTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="BAAI/bge-large-zh-v1.5", - credentials={ - "api_key": os.environ.get("API_KEY"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/spark/__init__.py b/api/tests/integration_tests/model_runtime/spark/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/spark/test_llm.py b/api/tests/integration_tests/model_runtime/spark/test_llm.py deleted file mode 100644 index 4fe2fd8c0a3eac..00000000000000 --- a/api/tests/integration_tests/model_runtime/spark/test_llm.py +++ /dev/null @@ -1,92 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.spark.llm.llm import SparkLargeLanguageModel - - -def test_validate_credentials(): - model = SparkLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="spark-1.5", credentials={"app_id": "invalid_key"}) - - model.validate_credentials( - model="spark-1.5", - credentials={ - "app_id": os.environ.get("SPARK_APP_ID"), - "api_secret": os.environ.get("SPARK_API_SECRET"), - "api_key": os.environ.get("SPARK_API_KEY"), - }, - ) - - -def test_invoke_model(): - model = SparkLargeLanguageModel() - - response = model.invoke( - model="spark-1.5", - credentials={ - "app_id": os.environ.get("SPARK_APP_ID"), - "api_secret": os.environ.get("SPARK_API_SECRET"), - "api_key": os.environ.get("SPARK_API_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={"temperature": 0.5, "max_tokens": 10}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = SparkLargeLanguageModel() - - response = model.invoke( - model="spark-1.5", - credentials={ - "app_id": os.environ.get("SPARK_APP_ID"), - "api_secret": os.environ.get("SPARK_API_SECRET"), - "api_key": os.environ.get("SPARK_API_KEY"), - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.5, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = SparkLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="spark-1.5", - credentials={ - "app_id": os.environ.get("SPARK_APP_ID"), - "api_secret": os.environ.get("SPARK_API_SECRET"), - "api_key": os.environ.get("SPARK_API_KEY"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 14 diff --git a/api/tests/integration_tests/model_runtime/spark/test_provider.py b/api/tests/integration_tests/model_runtime/spark/test_provider.py deleted file mode 100644 index 9da0df6bb3d556..00000000000000 --- a/api/tests/integration_tests/model_runtime/spark/test_provider.py +++ /dev/null @@ -1,21 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.spark.spark import SparkProvider - - -def test_validate_provider_credentials(): - provider = SparkProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials( - credentials={ - "app_id": os.environ.get("SPARK_APP_ID"), - "api_secret": os.environ.get("SPARK_API_SECRET"), - "api_key": os.environ.get("SPARK_API_KEY"), - } - ) diff --git a/api/tests/integration_tests/model_runtime/stepfun/__init__.py b/api/tests/integration_tests/model_runtime/stepfun/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/stepfun/test_llm.py b/api/tests/integration_tests/model_runtime/stepfun/test_llm.py deleted file mode 100644 index c03b1bae1f1574..00000000000000 --- a/api/tests/integration_tests/model_runtime/stepfun/test_llm.py +++ /dev/null @@ -1,125 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - ImagePromptMessageContent, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity, ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.stepfun.llm.llm import StepfunLargeLanguageModel - - -def test_validate_credentials(): - model = StepfunLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="step-1-8k", credentials={"api_key": "invalid_key"}) - - model.validate_credentials(model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}) - - -def test_invoke_model(): - model = StepfunLargeLanguageModel() - - response = model.invoke( - model="step-1-8k", - credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.9, "top_p": 0.7}, - stop=["Hi"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = StepfunLargeLanguageModel() - - response = model.invoke( - model="step-1-8k", - credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.9, "top_p": 0.7}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_customizable_model_schema(): - model = StepfunLargeLanguageModel() - - schema = model.get_customizable_model_schema( - model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")} - ) - assert isinstance(schema, AIModelEntity) - - -def test_invoke_chat_model_with_tools(): - model = StepfunLargeLanguageModel() - - result = model.invoke( - model="step-1-8k", - credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content="what's the weather today in Shanghai?", - ), - ], - model_parameters={"temperature": 0.9, "max_tokens": 100}, - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ), - PromptMessageTool( - name="get_stock_price", - description="Get the current stock price", - parameters={ - "type": "object", - "properties": {"symbol": {"type": "string", "description": "The stock symbol"}}, - "required": ["symbol"], - }, - ), - ], - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert isinstance(result.message, AssistantPromptMessage) - assert len(result.message.tool_calls) > 0 diff --git a/api/tests/integration_tests/model_runtime/test_tiktoken.py b/api/tests/integration_tests/model_runtime/test_tiktoken.py new file mode 100644 index 00000000000000..f92d9dc6037fd9 --- /dev/null +++ b/api/tests/integration_tests/model_runtime/test_tiktoken.py @@ -0,0 +1,11 @@ +import os + +import tiktoken + +from core.model_runtime.model_providers.__base.tokenizers.gpt2_tokenzier import GPT2Tokenizer + + +def test_tiktoken(): + os.environ["TIKTOKEN_CACHE_DIR"] = "/tmp/.tiktoken_cache" + GPT2Tokenizer.get_num_tokens("Hello, world!") + assert tiktoken.registry.ENCODING_CONSTRUCTORS is not None diff --git a/api/tests/integration_tests/model_runtime/togetherai/__init__.py b/api/tests/integration_tests/model_runtime/togetherai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/togetherai/test_llm.py b/api/tests/integration_tests/model_runtime/togetherai/test_llm.py deleted file mode 100644 index 06ebc2a82dc754..00000000000000 --- a/api/tests/integration_tests/model_runtime/togetherai/test_llm.py +++ /dev/null @@ -1,104 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.togetherai.llm.llm import TogetherAILargeLanguageModel - - -def test_validate_credentials(): - model = TogetherAILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", credentials={"api_key": "invalid_key", "mode": "chat"} - ) - - model.validate_credentials( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "chat"}, - ) - - -def test_invoke_model(): - model = TogetherAILargeLanguageModel() - - response = model.invoke( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "completion"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = TogetherAILargeLanguageModel() - - response = model.invoke( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "chat"}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Who are you?"), - ], - model_parameters={ - "temperature": 1.0, - "top_k": 2, - "top_p": 0.5, - }, - stop=["How"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - - -def test_get_num_tokens(): - model = TogetherAILargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="mistralai/Mixtral-8x7B-Instruct-v0.1", - credentials={ - "api_key": os.environ.get("TOGETHER_API_KEY"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/tongyi/__init__.py b/api/tests/integration_tests/model_runtime/tongyi/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/tongyi/test_llm.py b/api/tests/integration_tests/model_runtime/tongyi/test_llm.py deleted file mode 100644 index 61650735f2ad3f..00000000000000 --- a/api/tests/integration_tests/model_runtime/tongyi/test_llm.py +++ /dev/null @@ -1,75 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.tongyi.llm.llm import TongyiLargeLanguageModel - - -def test_validate_credentials(): - model = TongyiLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="qwen-turbo", credentials={"dashscope_api_key": "invalid_key"}) - - model.validate_credentials( - model="qwen-turbo", credentials={"dashscope_api_key": os.environ.get("TONGYI_DASHSCOPE_API_KEY")} - ) - - -def test_invoke_model(): - model = TongyiLargeLanguageModel() - - response = model.invoke( - model="qwen-turbo", - credentials={"dashscope_api_key": os.environ.get("TONGYI_DASHSCOPE_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={"temperature": 0.5, "max_tokens": 10}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = TongyiLargeLanguageModel() - - response = model.invoke( - model="qwen-turbo", - credentials={"dashscope_api_key": os.environ.get("TONGYI_DASHSCOPE_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.5, "max_tokens": 100, "seed": 1234}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = TongyiLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="qwen-turbo", - credentials={"dashscope_api_key": os.environ.get("TONGYI_DASHSCOPE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 12 diff --git a/api/tests/integration_tests/model_runtime/tongyi/test_provider.py b/api/tests/integration_tests/model_runtime/tongyi/test_provider.py deleted file mode 100644 index 0bc96c84e73195..00000000000000 --- a/api/tests/integration_tests/model_runtime/tongyi/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.tongyi.tongyi import TongyiProvider - - -def test_validate_provider_credentials(): - provider = TongyiProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials( - credentials={"dashscope_api_key": os.environ.get("TONGYI_DASHSCOPE_API_KEY")} - ) diff --git a/api/tests/integration_tests/model_runtime/tongyi/test_response_format.py b/api/tests/integration_tests/model_runtime/tongyi/test_response_format.py deleted file mode 100644 index 905e7907fde5a8..00000000000000 --- a/api/tests/integration_tests/model_runtime/tongyi/test_response_format.py +++ /dev/null @@ -1,80 +0,0 @@ -import json -import os -from collections.abc import Generator - -from core.model_runtime.entities.llm_entities import LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, UserPromptMessage -from core.model_runtime.model_providers.tongyi.llm.llm import TongyiLargeLanguageModel - - -def test_invoke_model_with_json_response(): - """ - Test the invocation of a model with JSON response. - """ - model_list = [ - "qwen-max-0403", - "qwen-max-1201", - "qwen-max-longcontext", - "qwen-max", - "qwen-plus-chat", - "qwen-plus", - "qwen-turbo-chat", - "qwen-turbo", - ] - for model_name in model_list: - print("testing model: ", model_name) - invoke_model_with_json_response(model_name) - - -def invoke_model_with_json_response(model_name="qwen-max-0403"): - """ - Method to invoke the model with JSON response format. - Args: - model_name (str): The name of the model to invoke. Defaults to "qwen-max-0403". - - Returns: - None - """ - model = TongyiLargeLanguageModel() - - response = model.invoke( - model=model_name, - credentials={"dashscope_api_key": os.environ.get("TONGYI_DASHSCOPE_API_KEY")}, - prompt_messages=[ - UserPromptMessage(content='output json data with format `{"data": "test", "code": 200, "msg": "success"}') - ], - model_parameters={ - "temperature": 0.5, - "max_tokens": 50, - "response_format": "JSON", - }, - stream=True, - user="abc-123", - ) - print("=====================================") - print(response) - assert isinstance(response, Generator) - output = "" - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - output += chunk.delta.message.content - assert is_json(output) - - -def is_json(s): - """ - Check if a string is a valid JSON. - - Args: - s (str): The string to check. - - Returns: - bool: True if the string is a valid JSON, False otherwise. - """ - try: - json.loads(s) - except ValueError: - return False - return True diff --git a/api/tests/integration_tests/model_runtime/upstage/__init__.py b/api/tests/integration_tests/model_runtime/upstage/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/upstage/test_llm.py b/api/tests/integration_tests/model_runtime/upstage/test_llm.py deleted file mode 100644 index bc7517acbe2601..00000000000000 --- a/api/tests/integration_tests/model_runtime/upstage/test_llm.py +++ /dev/null @@ -1,186 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity, ModelType -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel -from core.model_runtime.model_providers.upstage.llm.llm import UpstageLargeLanguageModel - -"""FOR MOCK FIXTURES, DO NOT REMOVE""" -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -def test_predefined_models(): - model = UpstageLargeLanguageModel() - model_schemas = model.predefined_models() - - assert len(model_schemas) >= 1 - assert isinstance(model_schemas[0], AIModelEntity) - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_credentials_for_chat_model(setup_openai_mock): - model = UpstageLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - # model name to gpt-3.5-turbo because of mocking - model.validate_credentials(model="gpt-3.5-turbo", credentials={"upstage_api_key": "invalid_key"}) - - model.validate_credentials( - model="solar-1-mini-chat", credentials={"upstage_api_key": os.environ.get("UPSTAGE_API_KEY")} - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model(setup_openai_mock): - model = UpstageLargeLanguageModel() - - result = model.invoke( - model="solar-1-mini-chat", - credentials={"upstage_api_key": os.environ.get("UPSTAGE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.0, - "top_p": 1.0, - "presence_penalty": 0.0, - "frequency_penalty": 0.0, - "max_tokens": 10, - }, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert len(result.message.content) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_chat_model_with_tools(setup_openai_mock): - model = UpstageLargeLanguageModel() - - result = model.invoke( - model="solar-1-mini-chat", - credentials={"upstage_api_key": os.environ.get("UPSTAGE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage( - content="what's the weather today in London?", - ), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ), - PromptMessageTool( - name="get_stock_price", - description="Get the current stock price", - parameters={ - "type": "object", - "properties": {"symbol": {"type": "string", "description": "The stock symbol"}}, - "required": ["symbol"], - }, - ), - ], - stream=False, - user="abc-123", - ) - - assert isinstance(result, LLMResult) - assert isinstance(result.message, AssistantPromptMessage) - assert len(result.message.tool_calls) > 0 - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_invoke_stream_chat_model(setup_openai_mock): - model = UpstageLargeLanguageModel() - - result = model.invoke( - model="solar-1-mini-chat", - credentials={"upstage_api_key": os.environ.get("UPSTAGE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={"temperature": 0.0, "max_tokens": 100}, - stream=True, - user="abc-123", - ) - - assert isinstance(result, Generator) - - for chunk in result: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - if chunk.delta.finish_reason is not None: - assert chunk.delta.usage is not None - assert chunk.delta.usage.completion_tokens > 0 - - -def test_get_num_tokens(): - model = UpstageLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="solar-1-mini-chat", - credentials={"upstage_api_key": os.environ.get("UPSTAGE_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - ) - - assert num_tokens == 13 - - num_tokens = model.get_num_tokens( - model="solar-1-mini-chat", - credentials={"upstage_api_key": os.environ.get("UPSTAGE_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - tools=[ - PromptMessageTool( - name="get_weather", - description="Determine weather in my location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ), - ], - ) - - assert num_tokens == 106 diff --git a/api/tests/integration_tests/model_runtime/upstage/test_provider.py b/api/tests/integration_tests/model_runtime/upstage/test_provider.py deleted file mode 100644 index 9d83779aa00a49..00000000000000 --- a/api/tests/integration_tests/model_runtime/upstage/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.upstage.upstage import UpstageProvider -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True) -def test_validate_provider_credentials(setup_openai_mock): - provider = UpstageProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={"upstage_api_key": os.environ.get("UPSTAGE_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/upstage/test_text_embedding.py b/api/tests/integration_tests/model_runtime/upstage/test_text_embedding.py deleted file mode 100644 index 8c83172fa3ff7e..00000000000000 --- a/api/tests/integration_tests/model_runtime/upstage/test_text_embedding.py +++ /dev/null @@ -1,54 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.upstage.text_embedding.text_embedding import UpstageTextEmbeddingModel -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock - - -@pytest.mark.parametrize("setup_openai_mock", [["text_embedding"]], indirect=True) -def test_validate_credentials(setup_openai_mock): - model = UpstageTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="solar-embedding-1-large-passage", credentials={"upstage_api_key": "invalid_key"} - ) - - model.validate_credentials( - model="solar-embedding-1-large-passage", credentials={"upstage_api_key": os.environ.get("UPSTAGE_API_KEY")} - ) - - -@pytest.mark.parametrize("setup_openai_mock", [["text_embedding"]], indirect=True) -def test_invoke_model(setup_openai_mock): - model = UpstageTextEmbeddingModel() - - result = model.invoke( - model="solar-embedding-1-large-passage", - credentials={ - "upstage_api_key": os.environ.get("UPSTAGE_API_KEY"), - }, - texts=["hello", "world", " ".join(["long_text"] * 100), " ".join(["another_long_text"] * 100)], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 4 - assert result.usage.total_tokens == 2 - - -def test_get_num_tokens(): - model = UpstageTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="solar-embedding-1-large-passage", - credentials={ - "upstage_api_key": os.environ.get("UPSTAGE_API_KEY"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 5 diff --git a/api/tests/integration_tests/model_runtime/volcengine_maas/__init__.py b/api/tests/integration_tests/model_runtime/volcengine_maas/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/volcengine_maas/test_embedding.py b/api/tests/integration_tests/model_runtime/volcengine_maas/test_embedding.py deleted file mode 100644 index f831c063a42630..00000000000000 --- a/api/tests/integration_tests/model_runtime/volcengine_maas/test_embedding.py +++ /dev/null @@ -1,79 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.volcengine_maas.text_embedding.text_embedding import ( - VolcengineMaaSTextEmbeddingModel, -) - - -def test_validate_credentials(): - model = VolcengineMaaSTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": "INVALID", - "volc_secret_access_key": "INVALID", - "endpoint_id": "INVALID", - "base_model_name": "Doubao-embedding", - }, - ) - - model.validate_credentials( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": os.environ.get("VOLC_API_KEY"), - "volc_secret_access_key": os.environ.get("VOLC_SECRET_KEY"), - "endpoint_id": os.environ.get("VOLC_EMBEDDING_ENDPOINT_ID"), - "base_model_name": "Doubao-embedding", - }, - ) - - -def test_invoke_model(): - model = VolcengineMaaSTextEmbeddingModel() - - result = model.invoke( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": os.environ.get("VOLC_API_KEY"), - "volc_secret_access_key": os.environ.get("VOLC_SECRET_KEY"), - "endpoint_id": os.environ.get("VOLC_EMBEDDING_ENDPOINT_ID"), - "base_model_name": "Doubao-embedding", - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens > 0 - - -def test_get_num_tokens(): - model = VolcengineMaaSTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": os.environ.get("VOLC_API_KEY"), - "volc_secret_access_key": os.environ.get("VOLC_SECRET_KEY"), - "endpoint_id": os.environ.get("VOLC_EMBEDDING_ENDPOINT_ID"), - "base_model_name": "Doubao-embedding", - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/volcengine_maas/test_llm.py b/api/tests/integration_tests/model_runtime/volcengine_maas/test_llm.py deleted file mode 100644 index 8ff9c414046e7d..00000000000000 --- a/api/tests/integration_tests/model_runtime/volcengine_maas/test_llm.py +++ /dev/null @@ -1,118 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.volcengine_maas.llm.llm import VolcengineMaaSLargeLanguageModel - - -def test_validate_credentials_for_chat_model(): - model = VolcengineMaaSLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": "INVALID", - "volc_secret_access_key": "INVALID", - "endpoint_id": "INVALID", - }, - ) - - model.validate_credentials( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": os.environ.get("VOLC_API_KEY"), - "volc_secret_access_key": os.environ.get("VOLC_SECRET_KEY"), - "endpoint_id": os.environ.get("VOLC_MODEL_ENDPOINT_ID"), - }, - ) - - -def test_invoke_model(): - model = VolcengineMaaSLargeLanguageModel() - - response = model.invoke( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": os.environ.get("VOLC_API_KEY"), - "volc_secret_access_key": os.environ.get("VOLC_SECRET_KEY"), - "endpoint_id": os.environ.get("VOLC_MODEL_ENDPOINT_ID"), - "base_model_name": "Skylark2-pro-4k", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_stream_model(): - model = VolcengineMaaSLargeLanguageModel() - - response = model.invoke( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": os.environ.get("VOLC_API_KEY"), - "volc_secret_access_key": os.environ.get("VOLC_SECRET_KEY"), - "endpoint_id": os.environ.get("VOLC_MODEL_ENDPOINT_ID"), - "base_model_name": "Skylark2-pro-4k", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "top_k": 1, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = VolcengineMaaSLargeLanguageModel() - - response = model.get_num_tokens( - model="NOT IMPORTANT", - credentials={ - "api_endpoint_host": "maas-api.ml-platform-cn-beijing.volces.com", - "volc_region": "cn-beijing", - "volc_access_key_id": os.environ.get("VOLC_API_KEY"), - "volc_secret_access_key": os.environ.get("VOLC_SECRET_KEY"), - "endpoint_id": os.environ.get("VOLC_MODEL_ENDPOINT_ID"), - "base_model_name": "Skylark2-pro-4k", - }, - prompt_messages=[UserPromptMessage(content="Hello World!")], - tools=[], - ) - - assert isinstance(response, int) - assert response == 6 diff --git a/api/tests/integration_tests/model_runtime/wenxin/__init__.py b/api/tests/integration_tests/model_runtime/wenxin/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/wenxin/test_embedding.py b/api/tests/integration_tests/model_runtime/wenxin/test_embedding.py deleted file mode 100644 index ac38340aecf7d2..00000000000000 --- a/api/tests/integration_tests/model_runtime/wenxin/test_embedding.py +++ /dev/null @@ -1,69 +0,0 @@ -import os -from time import sleep - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.model_providers.wenxin.text_embedding.text_embedding import WenxinTextEmbeddingModel - - -def test_invoke_embedding_v1(): - sleep(3) - model = WenxinTextEmbeddingModel() - - response = model.invoke( - model="embedding-v1", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - texts=["hello", "你好", "xxxxx"], - user="abc-123", - ) - - assert isinstance(response, TextEmbeddingResult) - assert len(response.embeddings) == 3 - assert isinstance(response.embeddings[0], list) - - -def test_invoke_embedding_bge_large_en(): - sleep(3) - model = WenxinTextEmbeddingModel() - - response = model.invoke( - model="bge-large-en", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - texts=["hello", "你好", "xxxxx"], - user="abc-123", - ) - - assert isinstance(response, TextEmbeddingResult) - assert len(response.embeddings) == 3 - assert isinstance(response.embeddings[0], list) - - -def test_invoke_embedding_bge_large_zh(): - sleep(3) - model = WenxinTextEmbeddingModel() - - response = model.invoke( - model="bge-large-zh", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - texts=["hello", "你好", "xxxxx"], - user="abc-123", - ) - - assert isinstance(response, TextEmbeddingResult) - assert len(response.embeddings) == 3 - assert isinstance(response.embeddings[0], list) - - -def test_invoke_embedding_tao_8k(): - sleep(3) - model = WenxinTextEmbeddingModel() - - response = model.invoke( - model="tao-8k", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - texts=["hello", "你好", "xxxxx"], - user="abc-123", - ) - - assert isinstance(response, TextEmbeddingResult) - assert len(response.embeddings) == 3 - assert isinstance(response.embeddings[0], list) diff --git a/api/tests/integration_tests/model_runtime/wenxin/test_llm.py b/api/tests/integration_tests/model_runtime/wenxin/test_llm.py deleted file mode 100644 index e2e58f15e025d8..00000000000000 --- a/api/tests/integration_tests/model_runtime/wenxin/test_llm.py +++ /dev/null @@ -1,214 +0,0 @@ -import os -from collections.abc import Generator -from time import sleep - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.wenxin.llm.llm import ErnieBotLargeLanguageModel - - -def test_predefined_models(): - model = ErnieBotLargeLanguageModel() - model_schemas = model.predefined_models() - assert len(model_schemas) >= 1 - assert isinstance(model_schemas[0], AIModelEntity) - - -def test_validate_credentials_for_chat_model(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="ernie-bot", credentials={"api_key": "invalid_key", "secret_key": "invalid_key"} - ) - - model.validate_credentials( - model="ernie-bot", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - ) - - -def test_invoke_model_ernie_bot(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - response = model.invoke( - model="ernie-bot", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_model_ernie_bot_turbo(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - response = model.invoke( - model="ernie-bot-turbo", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_model_ernie_8k(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - response = model.invoke( - model="ernie-bot-8k", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_model_ernie_bot_4(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - response = model.invoke( - model="ernie-bot-4", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -def test_invoke_stream_model(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - response = model.invoke( - model="ernie-3.5-8k", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_invoke_model_with_system(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - response = model.invoke( - model="ernie-bot", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - prompt_messages=[SystemPromptMessage(content="你是Kasumi"), UserPromptMessage(content="你是谁？")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert "kasumi" in response.message.content.lower() - - -def test_invoke_with_search(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - response = model.invoke( - model="ernie-bot", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - prompt_messages=[UserPromptMessage(content="北京今天的天气怎么样")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - "disable_search": True, - }, - stop=[], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - total_message = "" - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - total_message += chunk.delta.message.content - print(chunk.delta.message.content) - assert len(chunk.delta.message.content) > 0 if not chunk.delta.finish_reason else True - - # there should be 对不起、我不能、不支持…… - assert "不" in total_message or "抱歉" in total_message or "无法" in total_message - - -def test_get_num_tokens(): - sleep(3) - model = ErnieBotLargeLanguageModel() - - response = model.get_num_tokens( - model="ernie-bot", - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - tools=[], - ) - - assert isinstance(response, int) - assert response == 10 diff --git a/api/tests/integration_tests/model_runtime/wenxin/test_provider.py b/api/tests/integration_tests/model_runtime/wenxin/test_provider.py deleted file mode 100644 index 337c3d2a8010dd..00000000000000 --- a/api/tests/integration_tests/model_runtime/wenxin/test_provider.py +++ /dev/null @@ -1,17 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.wenxin.wenxin import WenxinProvider - - -def test_validate_provider_credentials(): - provider = WenxinProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={"api_key": "hahahaha", "secret_key": "hahahaha"}) - - provider.validate_provider_credentials( - credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")} - ) diff --git a/api/tests/integration_tests/model_runtime/xinference/__init__.py b/api/tests/integration_tests/model_runtime/xinference/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/xinference/test_embeddings.py b/api/tests/integration_tests/model_runtime/xinference/test_embeddings.py deleted file mode 100644 index 8e778d005a4bc3..00000000000000 --- a/api/tests/integration_tests/model_runtime/xinference/test_embeddings.py +++ /dev/null @@ -1,64 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.xinference.text_embedding.text_embedding import XinferenceTextEmbeddingModel -from tests.integration_tests.model_runtime.__mock.xinference import MOCK, setup_xinference_mock - - -@pytest.mark.parametrize("setup_xinference_mock", [["none"]], indirect=True) -def test_validate_credentials(setup_xinference_mock): - model = XinferenceTextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="bge-base-en", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": "www " + os.environ.get("XINFERENCE_EMBEDDINGS_MODEL_UID"), - }, - ) - - model.validate_credentials( - model="bge-base-en", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_EMBEDDINGS_MODEL_UID"), - }, - ) - - -@pytest.mark.parametrize("setup_xinference_mock", [["none"]], indirect=True) -def test_invoke_model(setup_xinference_mock): - model = XinferenceTextEmbeddingModel() - - result = model.invoke( - model="bge-base-en", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_EMBEDDINGS_MODEL_UID"), - }, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens > 0 - - -def test_get_num_tokens(): - model = XinferenceTextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="bge-base-en", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_EMBEDDINGS_MODEL_UID"), - }, - texts=["hello", "world"], - ) - - assert num_tokens == 2 diff --git a/api/tests/integration_tests/model_runtime/xinference/test_llm.py b/api/tests/integration_tests/model_runtime/xinference/test_llm.py deleted file mode 100644 index fb5e03855d2120..00000000000000 --- a/api/tests/integration_tests/model_runtime/xinference/test_llm.py +++ /dev/null @@ -1,366 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - TextPromptMessageContent, - UserPromptMessage, -) -from core.model_runtime.entities.model_entities import AIModelEntity -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.xinference.llm.llm import XinferenceAILargeLanguageModel - -"""FOR MOCK FIXTURES, DO NOT REMOVE""" -from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock -from tests.integration_tests.model_runtime.__mock.xinference import setup_xinference_mock - - -@pytest.mark.parametrize(("setup_openai_mock", "setup_xinference_mock"), [("chat", "none")], indirect=True) -def test_validate_credentials_for_chat_model(setup_openai_mock, setup_xinference_mock): - model = XinferenceAILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="ChatGLM3", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": "www " + os.environ.get("XINFERENCE_CHAT_MODEL_UID"), - }, - ) - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="aaaaa", credentials={"server_url": "", "model_uid": ""}) - - model.validate_credentials( - model="ChatGLM3", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_CHAT_MODEL_UID"), - }, - ) - - -@pytest.mark.parametrize(("setup_openai_mock", "setup_xinference_mock"), [("chat", "none")], indirect=True) -def test_invoke_chat_model(setup_openai_mock, setup_xinference_mock): - model = XinferenceAILargeLanguageModel() - - response = model.invoke( - model="ChatGLM3", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_CHAT_MODEL_UID"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -@pytest.mark.parametrize(("setup_openai_mock", "setup_xinference_mock"), [("chat", "none")], indirect=True) -def test_invoke_stream_chat_model(setup_openai_mock, setup_xinference_mock): - model = XinferenceAILargeLanguageModel() - - response = model.invoke( - model="ChatGLM3", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_CHAT_MODEL_UID"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -""" - Function calling of xinference does not support stream mode currently -""" -# def test_invoke_stream_chat_model_with_functions(): -# model = XinferenceAILargeLanguageModel() - -# response = model.invoke( -# model='ChatGLM3-6b', -# credentials={ -# 'server_url': os.environ.get('XINFERENCE_SERVER_URL'), -# 'model_type': 'text-generation', -# 'model_name': 'ChatGLM3', -# 'model_uid': os.environ.get('XINFERENCE_CHAT_MODEL_UID') -# }, -# prompt_messages=[ -# SystemPromptMessage( -# content='你是一个天气机器人，可以通过调用函数来获取天气信息', -# ), -# UserPromptMessage( -# content='波士顿天气如何？' -# ) -# ], -# model_parameters={ -# 'temperature': 0, -# 'top_p': 1.0, -# }, -# stop=['you'], -# user='abc-123', -# stream=True, -# tools=[ -# PromptMessageTool( -# name='get_current_weather', -# description='Get the current weather in a given location', -# parameters={ -# "type": "object", -# "properties": { -# "location": { -# "type": "string", -# "description": "The city and state e.g. San Francisco, CA" -# }, -# "unit": { -# "type": "string", -# "enum": ["celsius", "fahrenheit"] -# } -# }, -# "required": [ -# "location" -# ] -# } -# ) -# ] -# ) - -# assert isinstance(response, Generator) - -# call: LLMResultChunk = None -# chunks = [] - -# for chunk in response: -# chunks.append(chunk) -# assert isinstance(chunk, LLMResultChunk) -# assert isinstance(chunk.delta, LLMResultChunkDelta) -# assert isinstance(chunk.delta.message, AssistantPromptMessage) -# assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - -# if chunk.delta.message.tool_calls and len(chunk.delta.message.tool_calls) > 0: -# call = chunk -# break - -# assert call is not None -# assert call.delta.message.tool_calls[0].function.name == 'get_current_weather' - -# def test_invoke_chat_model_with_functions(): -# model = XinferenceAILargeLanguageModel() - -# response = model.invoke( -# model='ChatGLM3-6b', -# credentials={ -# 'server_url': os.environ.get('XINFERENCE_SERVER_URL'), -# 'model_type': 'text-generation', -# 'model_name': 'ChatGLM3', -# 'model_uid': os.environ.get('XINFERENCE_CHAT_MODEL_UID') -# }, -# prompt_messages=[ -# UserPromptMessage( -# content='What is the weather like in San Francisco?' -# ) -# ], -# model_parameters={ -# 'temperature': 0.7, -# 'top_p': 1.0, -# }, -# stop=['you'], -# user='abc-123', -# stream=False, -# tools=[ -# PromptMessageTool( -# name='get_current_weather', -# description='Get the current weather in a given location', -# parameters={ -# "type": "object", -# "properties": { -# "location": { -# "type": "string", -# "description": "The city and state e.g. San Francisco, CA" -# }, -# "unit": { -# "type": "string", -# "enum": [ -# "c", -# "f" -# ] -# } -# }, -# "required": [ -# "location" -# ] -# } -# ) -# ] -# ) - -# assert isinstance(response, LLMResult) -# assert len(response.message.content) > 0 -# assert response.usage.total_tokens > 0 -# assert response.message.tool_calls[0].function.name == 'get_current_weather' - - -@pytest.mark.parametrize(("setup_openai_mock", "setup_xinference_mock"), [("completion", "none")], indirect=True) -def test_validate_credentials_for_generation_model(setup_openai_mock, setup_xinference_mock): - model = XinferenceAILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="alapaca", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": "www " + os.environ.get("XINFERENCE_GENERATION_MODEL_UID"), - }, - ) - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="alapaca", credentials={"server_url": "", "model_uid": ""}) - - model.validate_credentials( - model="alapaca", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"), - }, - ) - - -@pytest.mark.parametrize(("setup_openai_mock", "setup_xinference_mock"), [("completion", "none")], indirect=True) -def test_invoke_generation_model(setup_openai_mock, setup_xinference_mock): - model = XinferenceAILargeLanguageModel() - - response = model.invoke( - model="alapaca", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"), - }, - prompt_messages=[UserPromptMessage(content="the United States is")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - user="abc-123", - stream=False, - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - assert response.usage.total_tokens > 0 - - -@pytest.mark.parametrize(("setup_openai_mock", "setup_xinference_mock"), [("completion", "none")], indirect=True) -def test_invoke_stream_generation_model(setup_openai_mock, setup_xinference_mock): - model = XinferenceAILargeLanguageModel() - - response = model.invoke( - model="alapaca", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"), - }, - prompt_messages=[UserPromptMessage(content="the United States is")], - model_parameters={ - "temperature": 0.7, - "top_p": 1.0, - }, - stop=["you"], - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = XinferenceAILargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="ChatGLM3", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - tools=[ - PromptMessageTool( - name="get_current_weather", - description="Get the current weather in a given location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ) - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 77 - - num_tokens = model.get_num_tokens( - model="ChatGLM3", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"), - }, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert isinstance(num_tokens, int) - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/xinference/test_rerank.py b/api/tests/integration_tests/model_runtime/xinference/test_rerank.py deleted file mode 100644 index 71ac4eef7c22be..00000000000000 --- a/api/tests/integration_tests/model_runtime/xinference/test_rerank.py +++ /dev/null @@ -1,52 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.rerank_entities import RerankResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.xinference.rerank.rerank import XinferenceRerankModel -from tests.integration_tests.model_runtime.__mock.xinference import MOCK, setup_xinference_mock - - -@pytest.mark.parametrize("setup_xinference_mock", [["none"]], indirect=True) -def test_validate_credentials(setup_xinference_mock): - model = XinferenceRerankModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials( - model="bge-reranker-base", - credentials={"server_url": "awdawdaw", "model_uid": os.environ.get("XINFERENCE_RERANK_MODEL_UID")}, - ) - - model.validate_credentials( - model="bge-reranker-base", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_RERANK_MODEL_UID"), - }, - ) - - -@pytest.mark.parametrize("setup_xinference_mock", [["none"]], indirect=True) -def test_invoke_model(setup_xinference_mock): - model = XinferenceRerankModel() - - result = model.invoke( - model="bge-reranker-base", - credentials={ - "server_url": os.environ.get("XINFERENCE_SERVER_URL"), - "model_uid": os.environ.get("XINFERENCE_RERANK_MODEL_UID"), - }, - query="Who is Kasumi?", - docs=[ - 'Kasumi is a girl\'s name of Japanese origin meaning "mist".', - "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music ", - "and she leads a team named PopiParty.", - ], - score_threshold=0.8, - ) - - assert isinstance(result, RerankResult) - assert len(result.docs) == 1 - assert result.docs[0].index == 0 - assert result.docs[0].score >= 0.8 diff --git a/api/tests/integration_tests/model_runtime/zhinao/__init__.py b/api/tests/integration_tests/model_runtime/zhinao/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/zhinao/test_llm.py b/api/tests/integration_tests/model_runtime/zhinao/test_llm.py deleted file mode 100644 index 4ca1b864764818..00000000000000 --- a/api/tests/integration_tests/model_runtime/zhinao/test_llm.py +++ /dev/null @@ -1,73 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.zhinao.llm.llm import ZhinaoLargeLanguageModel - - -def test_validate_credentials(): - model = ZhinaoLargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="360gpt2-pro", credentials={"api_key": "invalid_key"}) - - model.validate_credentials(model="360gpt2-pro", credentials={"api_key": os.environ.get("ZHINAO_API_KEY")}) - - -def test_invoke_model(): - model = ZhinaoLargeLanguageModel() - - response = model.invoke( - model="360gpt2-pro", - credentials={"api_key": os.environ.get("ZHINAO_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={"temperature": 0.5, "max_tokens": 10}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = ZhinaoLargeLanguageModel() - - response = model.invoke( - model="360gpt2-pro", - credentials={"api_key": os.environ.get("ZHINAO_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.5, "max_tokens": 100, "seed": 1234}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = ZhinaoLargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="360gpt2-pro", - credentials={"api_key": os.environ.get("ZHINAO_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 21 diff --git a/api/tests/integration_tests/model_runtime/zhinao/test_provider.py b/api/tests/integration_tests/model_runtime/zhinao/test_provider.py deleted file mode 100644 index c22f797919597c..00000000000000 --- a/api/tests/integration_tests/model_runtime/zhinao/test_provider.py +++ /dev/null @@ -1,15 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.zhinao.zhinao import ZhinaoProvider - - -def test_validate_provider_credentials(): - provider = ZhinaoProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={"api_key": os.environ.get("ZHINAO_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/zhipuai/__init__.py b/api/tests/integration_tests/model_runtime/zhipuai/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/integration_tests/model_runtime/zhipuai/test_llm.py b/api/tests/integration_tests/model_runtime/zhipuai/test_llm.py deleted file mode 100644 index 20380513eaa789..00000000000000 --- a/api/tests/integration_tests/model_runtime/zhipuai/test_llm.py +++ /dev/null @@ -1,109 +0,0 @@ -import os -from collections.abc import Generator - -import pytest - -from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta -from core.model_runtime.entities.message_entities import ( - AssistantPromptMessage, - PromptMessageTool, - SystemPromptMessage, - UserPromptMessage, -) -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.zhipuai.llm.llm import ZhipuAILargeLanguageModel - - -def test_validate_credentials(): - model = ZhipuAILargeLanguageModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="chatglm_turbo", credentials={"api_key": "invalid_key"}) - - model.validate_credentials(model="chatglm_turbo", credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}) - - -def test_invoke_model(): - model = ZhipuAILargeLanguageModel() - - response = model.invoke( - model="chatglm_turbo", - credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Who are you?")], - model_parameters={"temperature": 0.9, "top_p": 0.7}, - stop=["How"], - stream=False, - user="abc-123", - ) - - assert isinstance(response, LLMResult) - assert len(response.message.content) > 0 - - -def test_invoke_stream_model(): - model = ZhipuAILargeLanguageModel() - - response = model.invoke( - model="chatglm_turbo", - credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}, - prompt_messages=[UserPromptMessage(content="Hello World!")], - model_parameters={"temperature": 0.9, "top_p": 0.7}, - stream=True, - user="abc-123", - ) - - assert isinstance(response, Generator) - - for chunk in response: - assert isinstance(chunk, LLMResultChunk) - assert isinstance(chunk.delta, LLMResultChunkDelta) - assert isinstance(chunk.delta.message, AssistantPromptMessage) - assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True - - -def test_get_num_tokens(): - model = ZhipuAILargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="chatglm_turbo", - credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}, - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 14 - - -def test_get_tools_num_tokens(): - model = ZhipuAILargeLanguageModel() - - num_tokens = model.get_num_tokens( - model="tools", - credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}, - tools=[ - PromptMessageTool( - name="get_current_weather", - description="Get the current weather in a given location", - parameters={ - "type": "object", - "properties": { - "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"}, - "unit": {"type": "string", "enum": ["c", "f"]}, - }, - "required": ["location"], - }, - ) - ], - prompt_messages=[ - SystemPromptMessage( - content="You are a helpful AI assistant.", - ), - UserPromptMessage(content="Hello World!"), - ], - ) - - assert num_tokens == 88 diff --git a/api/tests/integration_tests/model_runtime/zhipuai/test_provider.py b/api/tests/integration_tests/model_runtime/zhipuai/test_provider.py deleted file mode 100644 index cb5bc0b20aafc1..00000000000000 --- a/api/tests/integration_tests/model_runtime/zhipuai/test_provider.py +++ /dev/null @@ -1,15 +0,0 @@ -import os - -import pytest - -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.zhipuai.zhipuai import ZhipuaiProvider - - -def test_validate_provider_credentials(): - provider = ZhipuaiProvider() - - with pytest.raises(CredentialsValidateFailedError): - provider.validate_provider_credentials(credentials={}) - - provider.validate_provider_credentials(credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}) diff --git a/api/tests/integration_tests/model_runtime/zhipuai/test_text_embedding.py b/api/tests/integration_tests/model_runtime/zhipuai/test_text_embedding.py deleted file mode 100644 index 9c97c91ecbdd94..00000000000000 --- a/api/tests/integration_tests/model_runtime/zhipuai/test_text_embedding.py +++ /dev/null @@ -1,41 +0,0 @@ -import os - -import pytest - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.errors.validate import CredentialsValidateFailedError -from core.model_runtime.model_providers.zhipuai.text_embedding.text_embedding import ZhipuAITextEmbeddingModel - - -def test_validate_credentials(): - model = ZhipuAITextEmbeddingModel() - - with pytest.raises(CredentialsValidateFailedError): - model.validate_credentials(model="text_embedding", credentials={"api_key": "invalid_key"}) - - model.validate_credentials(model="text_embedding", credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}) - - -def test_invoke_model(): - model = ZhipuAITextEmbeddingModel() - - result = model.invoke( - model="text_embedding", - credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}, - texts=["hello", "world"], - user="abc-123", - ) - - assert isinstance(result, TextEmbeddingResult) - assert len(result.embeddings) == 2 - assert result.usage.total_tokens > 0 - - -def test_get_num_tokens(): - model = ZhipuAITextEmbeddingModel() - - num_tokens = model.get_num_tokens( - model="text_embedding", credentials={"api_key": os.environ.get("ZHIPUAI_API_KEY")}, texts=["hello", "world"] - ) - - assert num_tokens == 2 diff --git a/api/tests/unit_tests/core/model_runtime/model_providers/__init__.py b/api/tests/unit_tests/core/model_runtime/model_providers/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/unit_tests/core/model_runtime/model_providers/wenxin/__init__.py b/api/tests/unit_tests/core/model_runtime/model_providers/wenxin/__init__.py deleted file mode 100644 index e69de29bb2d1d6..00000000000000 diff --git a/api/tests/unit_tests/core/model_runtime/model_providers/wenxin/test_text_embedding.py b/api/tests/unit_tests/core/model_runtime/model_providers/wenxin/test_text_embedding.py deleted file mode 100644 index 5b159b49b61f37..00000000000000 --- a/api/tests/unit_tests/core/model_runtime/model_providers/wenxin/test_text_embedding.py +++ /dev/null @@ -1,75 +0,0 @@ -import numpy as np - -from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult -from core.model_runtime.model_providers.__base.tokenizers.gpt2_tokenzier import GPT2Tokenizer -from core.model_runtime.model_providers.wenxin.text_embedding.text_embedding import ( - TextEmbedding, - WenxinTextEmbeddingModel, -) - - -def test_max_chunks(): - class _MockTextEmbedding(TextEmbedding): - def embed_documents(self, model: str, texts: list[str], user: str) -> (list[list[float]], int, int): - embeddings = [[1.0, 2.0, 3.0] for i in range(len(texts))] - tokens = 0 - for text in texts: - tokens += len(text) - - return embeddings, tokens, tokens - - def _create_text_embedding(api_key: str, secret_key: str) -> TextEmbedding: - return _MockTextEmbedding() - - model = "embedding-v1" - credentials = { - "api_key": "xxxx", - "secret_key": "yyyy", - } - embedding_model = WenxinTextEmbeddingModel() - context_size = embedding_model._get_context_size(model, credentials) - max_chunks = embedding_model._get_max_chunks(model, credentials) - embedding_model._create_text_embedding = _create_text_embedding - - texts = ["0123456789" for i in range(0, max_chunks * 2)] - result: TextEmbeddingResult = embedding_model.invoke(model, credentials, texts, "test") - assert len(result.embeddings) == max_chunks * 2 - - -def test_context_size(): - def get_num_tokens_by_gpt2(text: str) -> int: - return GPT2Tokenizer.get_num_tokens(text) - - def mock_text(token_size: int) -> str: - _text = "".join(["0" for i in range(token_size)]) - num_tokens = get_num_tokens_by_gpt2(_text) - ratio = int(np.floor(len(_text) / num_tokens)) - m_text = "".join([_text for i in range(ratio)]) - return m_text - - model = "embedding-v1" - credentials = { - "api_key": "xxxx", - "secret_key": "yyyy", - } - embedding_model = WenxinTextEmbeddingModel() - context_size = embedding_model._get_context_size(model, credentials) - - class _MockTextEmbedding(TextEmbedding): - def embed_documents(self, model: str, texts: list[str], user: str) -> (list[list[float]], int, int): - embeddings = [[1.0, 2.0, 3.0] for i in range(len(texts))] - tokens = 0 - for text in texts: - tokens += get_num_tokens_by_gpt2(text) - return embeddings, tokens, tokens - - def _create_text_embedding(api_key: str, secret_key: str) -> TextEmbedding: - return _MockTextEmbedding() - - embedding_model._create_text_embedding = _create_text_embedding - text = mock_text(context_size * 2) - assert get_num_tokens_by_gpt2(text) == context_size * 2 - - texts = [text] - result: TextEmbeddingResult = embedding_model.invoke(model, credentials, texts, "test") - assert result.usage.tokens == context_size From 8563155d1bd5db5bbc95c2785294c8b710908d0a Mon Sep 17 00:00:00 2001 From: takatost Date: Sun, 29 Sep 2024 18:18:01 +0800 Subject: [PATCH 069/325] feat: remove unused codes --- api/poetry.lock | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/api/poetry.lock b/api/poetry.lock index 5c8485990cc67a..92eca926d0d088 100644 --- a/api/poetry.lock +++ b/api/poetry.lock @@ -8916,4 +8916,4 @@ cffi = ["cffi (>=1.11)"] [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.13" -content-hash = "46120eb2caaf416a798cfe425674e3dcf83a9c7f1b1273e7703ca32ebea21ffd" +content-hash = "13b250c6d52b6ce0f72cc019106b62687070d1eeb93586477399ecdc6d314d4b" From d4e007f9db82fb3d12c274be4da71a1f4f106b3c Mon Sep 17 00:00:00 2001 From: Yeuoly Date: Sun, 29 Sep 2024 18:18:45 +0800 Subject: [PATCH 070/325] feat: support get tool runtime parameters --- api/core/plugin/manager/tool.py | 42 +++++++++++++++++++++++- api/core/tools/entities/tool_entities.py | 2 ++ api/core/tools/plugin_tool/tool.py | 18 +++++++++- api/core/tools/tool_manager.py | 6 +++- 4 files changed, 65 insertions(+), 3 deletions(-) diff --git a/api/core/plugin/manager/tool.py b/api/core/plugin/manager/tool.py index 50970243a11955..874b3ff596bc47 100644 --- a/api/core/plugin/manager/tool.py +++ b/api/core/plugin/manager/tool.py @@ -1,9 +1,11 @@ from collections.abc import Generator from typing import Any +from pydantic import BaseModel + from core.plugin.entities.plugin_daemon import PluginBasicBooleanResponse, PluginToolProviderEntity from core.plugin.manager.base import BasePluginManager -from core.tools.entities.tool_entities import ToolInvokeMessage +from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter class PluginToolManager(BasePluginManager): @@ -144,3 +146,41 @@ def validate_provider_credentials( return resp.result return False + + def get_runtime_parameters( + self, + tenant_id: str, + user_id: str, + provider: str, + credentials: dict[str, Any], + tool: str, + ) -> list[ToolParameter]: + """ + get the runtime parameters of the tool + """ + plugin_id, provider_name = self._split_provider(provider) + + class RuntimeParametersResponse(BaseModel): + parameters: list[ToolParameter] + + response = self._request_with_plugin_daemon_response_stream( + "GET", + f"plugin/{tenant_id}/dispatch/tool/get_runtime_parameters", + RuntimeParametersResponse, + params={ + "user_id": user_id, + "data": { + "provider": provider_name, + "tool": tool, + "credentials": credentials, + }, + }, + headers={ + "X-Plugin-ID": plugin_id, + }, + ) + + for resp in response: + return resp.parameters + + return [] diff --git a/api/core/tools/entities/tool_entities.py b/api/core/tools/entities/tool_entities.py index 0808ff721d16d2..d037b00d3379ac 100644 --- a/api/core/tools/entities/tool_entities.py +++ b/api/core/tools/entities/tool_entities.py @@ -298,6 +298,8 @@ class ToolEntity(BaseModel): identity: ToolIdentity parameters: list[ToolParameter] = Field(default_factory=list) description: Optional[ToolDescription] = None + # TODO: output schema + has_runtime_parameters: bool = Field(default=False, description="Whether the tool has runtime parameters") # pydantic configs model_config = ConfigDict(protected_namespaces=()) diff --git a/api/core/tools/plugin_tool/tool.py b/api/core/tools/plugin_tool/tool.py index 7c6c4de3e00828..afbd2e40bfd41e 100644 --- a/api/core/tools/plugin_tool/tool.py +++ b/api/core/tools/plugin_tool/tool.py @@ -4,7 +4,7 @@ from core.plugin.manager.tool import PluginToolManager from core.tools.__base.tool import Tool from core.tools.__base.tool_runtime import ToolRuntime -from core.tools.entities.tool_entities import ToolEntity, ToolInvokeMessage, ToolProviderType +from core.tools.entities.tool_entities import ToolEntity, ToolInvokeMessage, ToolParameter, ToolProviderType class PluginTool(Tool): @@ -35,3 +35,19 @@ def fork_tool_runtime(self, runtime: ToolRuntime) -> "PluginTool": runtime=runtime, tenant_id=self.tenant_id, ) + + def get_runtime_parameters(self) -> list[ToolParameter]: + """ + get the runtime parameters + """ + if not self.entity.has_runtime_parameters: + return self.entity.parameters + + manager = PluginToolManager() + return manager.get_runtime_parameters( + tenant_id=self.tenant_id, + user_id="", + provider=self.entity.identity.provider, + tool=self.entity.identity.name, + credentials=self.runtime.credentials, + ) diff --git a/api/core/tools/tool_manager.py b/api/core/tools/tool_manager.py index 2f747a317e0e43..d780d2866fcaf8 100644 --- a/api/core/tools/tool_manager.py +++ b/api/core/tools/tool_manager.py @@ -255,7 +255,11 @@ def _init_runtime_parameter(cls, parameter_rule: ToolParameter, parameters: dict @classmethod def get_agent_tool_runtime( - cls, tenant_id: str, app_id: str, agent_tool: AgentToolEntity, invoke_from: InvokeFrom = InvokeFrom.DEBUGGER + cls, + tenant_id: str, + app_id: str, + agent_tool: AgentToolEntity, + invoke_from: InvokeFrom = InvokeFrom.DEBUGGER, ) -> Tool: """ get the agent tool runtime From bcdb407be8f85a03aee8a5eca9e0c79c618a42d3 Mon Sep 17 00:00:00 2001 From: takatost Date: Sun, 29 Sep 2024 18:24:20 +0800 Subject: [PATCH 071/325] feat: remove unused codes --- .../__base/tokenizers/gpt2/merges.txt | 50001 --------------- .../tokenizers/gpt2/special_tokens_map.json | 23 - .../tokenizers/gpt2/tokenizer_config.json | 33 - .../__base/tokenizers/gpt2/vocab.json | 50259 ---------------- api/poetry.lock | 1011 +- api/pyproject.toml | 8 - 6 files changed, 122 insertions(+), 101213 deletions(-) delete mode 100644 api/core/model_runtime/model_providers/__base/tokenizers/gpt2/merges.txt delete mode 100644 api/core/model_runtime/model_providers/__base/tokenizers/gpt2/special_tokens_map.json delete mode 100644 api/core/model_runtime/model_providers/__base/tokenizers/gpt2/tokenizer_config.json delete mode 100644 api/core/model_runtime/model_providers/__base/tokenizers/gpt2/vocab.json diff --git a/api/core/model_runtime/model_providers/__base/tokenizers/gpt2/merges.txt b/api/core/model_runtime/model_providers/__base/tokenizers/gpt2/merges.txt deleted file mode 100644 index 226b0752cac778..00000000000000 --- a/api/core/model_runtime/model_providers/__base/tokenizers/gpt2/merges.txt +++ /dev/null @@ -1,50001 +0,0 @@ -#version: 0.2 -Ġ t -Ġ a -h e -i n -r e -o n -Ġt he -e r -Ġ s -a t -Ġ w -Ġ o -e n -Ġ c -i t -i s -a n -o r -e s -Ġ b -e d -Ġ f -in g -Ġ p -o u -Ġa n -a l -a r -Ġt o -Ġ m -Ġo f -Ġ in -Ġ d -Ġ h -Ġan d -i c -a s -l e -Ġt h -i on -o m -l l -en t -Ġ n -Ġ l -s t -Ġ re -v e -Ġ e -r o -l y -Ġb e -Ġ g -Ġ T -c t -Ġ S -i d -o t -Ġ I -u t -e t -Ġ A -Ġ is -Ġ on -i m -a m -o w -a y -a d -s e -Ġth at -Ġ C -i g -Ġf or -a c -Ġ y -v er -u r -Ġ u -l d -Ġs t -Ġ M -' s -Ġ he -Ġ it -at ion -it h -i r -c e -Ġy ou -i l -Ġ B -Ġw h -o l -Ġ P -Ġw ith -Ġ 1 -t er -c h -Ġa s -Ġw e -Ġ ( -n d -i ll -Ġ D -i f -Ġ 2 -a g -er s -k e -Ġ " -Ġ H -e m -Ġc on -Ġ W -Ġ R -he r -Ġw as -Ġ r -o d -Ġ F -u l -at e -Ġa t -r i -p p -o re -ĠT he -Ġs e -u s -Ġp ro -Ġh a -u m -Ġa re -Ġd e -a 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ub -Or ange -Ġfingert ips -ĠWood en -ĠK idd -ĠJ PM -ĠDam n -C ow -c odes -48 2 -Ġiniti ating -ĠEl k -ĠCut ting -Ġabsent ee -ĠV ance -ĠLil ith -G UI -Ġobsc ured -Ġdwar ves -ĠCh op -ĠB oko -Val ues -Ġmult imedia -Ġbrew ed -Reg ular -CRIP TION -ĠMort al -Ġa pex -Ġtravel er -Ġbo ils -Ġspray ing -Rep resent -ĠStars hip -4 28 -Ġdisappro val -Ġshadow y -Ġlament ed -ĠRe place -ĠFran ç -67 7 -d or -Ġunst oppable -Ġcoh orts -gy n -ĠClass ics -ĠAm ph -Ġsl uggish -ĠAdd iction -ĠPad res -Ġins cription -Ġin human -min us -ĠJere miah -at ars -Ter ror -ĠT os -ĠSh arma -ast a -c atch -Ġpl umbing -ĠTim bers -Sh ar -H al -ĠO sc -Ġcou pling -hum ans -Ġsp onge -Ġid ols -ĠSp a -ĠAdv ocate -ĠBe ats -lu a -Ġtick ing -Ġload er -ĠG ron -8 10 -Ġstim ulated -Ġside bar -ĠManufact urer -ore And -19 73 -Ġpra ises -ĠFl ores -dis able -ĠElect rical -ra ise -E th -Ġmigr ated -Ġlect urer -K ids -ĠCa vern -Ġk ettle -Ġgly c -ĠMand ela -ĠF ully -å§ « -FIN EST -Ġsquee zing -ĠRy der -amp oo -oreAnd Online -Inst oreAndOnline 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-Ġreform ing -Ġfrust rations -ĠDead pool -ĠBel ichick -ract or -ĠRagnar ok -ĠD rupal -ĠApp roximately -19 20 -ĠHub ble -arm or -ĠSar as -ĠJon as -Ġnostalg ic -Ġfeas ibility -Sah aran -Ġorb iting -Ġ9 70 -R u -Ġsh in -ĠInvestig ators -Ġinconsist encies -ĠP AN -B G -Ġgraz ing -Ġdetect ors -ĠStart up -ĠFun ny -ĠNa omi -Consider ing -Ġh og -ut f -ce mic -Ġfort ified -ĠFun ctions -Ġcod ec -nut rition -H at -" ! -micro soft -55 8 -ĠTh in -ĠA CE -Al ias -ĠO PS -p apers -P K -ãĢ İ -Ġimpro bable -N orthern -equ al -Ġlook out -Ġty res -ĠMod ified -ĠK op -Abs olutely -Ġbuild up -sil ver -Ġaud i -Ġgro tesque -ĠSab er -ĠPres byter -ON Y -Ġglac iers -ĠSho als -ĠK ass -ĠH RC -ĠNic ol -ĠL unch -ĠF oss -âĸ Ĵ -AD RA -ĠOne Plus -o ing -ground s -Ġincident al -Ġdatas ets -68 9 -ĠClarks on -Ġassemb ling -ĠCorrect ions -Ġdrink ers -Ġqual ifiers -Ġle ash -Ġunf ounded -ĠH undred -Ġkick off -T i -Ġrecon cil -ĠGr ants -ĠCompl iance -ĠDexter ity -Ġ19 06 -w arn -D allas -Max imum -n ard -av ia -be aut -ens itivity -tr ace -Ġpione ers -ĠF ract -ãĢ ı -Ġpre cept -Ġgloss y -ĠI EEE -Ac ross -Ġ6 80 -S leep -che on -Ġsatir ical -ĠMin otaur -ĠCla ude -Ġr é -ape go -Ġcar rot -ĠSem in -ino a -Ġz o -Ind ependent -Ġdiagn oses -ĠC ue -M AR -Ġrend ition -ĠK ik -Ġpath ology -Ġselect s -Link edIn -Ġass ay -ĠD res -Ġtext ual -post ed -IT AL -ĠM aul -N eal -Ġinter connected -Ġerr atic -ĠVir us -Ġ5 30 -Ġenvironmental ists -ĠP helps -Ġeng agements -ĠIN ST -Ġeconom ical -nox ious -Ġg earing -izz y -Ġfavor ably -ĠMcG ill -T erm -Ġh anged -Ġball park -ĠRe yes -Ġbe ware -ĠP sal -ĠMass acre -q i -Ġin accessible -acly sm -Ġfr ay -ill ac -Ġbitter ly -ĠCert ification -Mich igan -Ġir respective -al ore -Em pty -Ġendorse ments -Ġund et -f g -equ ipped -Ġmerc iless -ĠC ust -Ġimm ature -Ġvou cher -ĠBlack well -Ñ ı -h awk -dis ciplinary -ile e -ĠMak oto -ĠD ude -ãĥĩ ãĤ£ -Y ears -Ġin ver -Ġsh aman -ĠY ong -ip el -ell en -ĠCath y -br ids -Ġs arc -65 1 -N ear -Ġground work -Ġam az -Ġ4 15 -ĠHunting ton -hew s -ĠB ung -Ġarbit rarily -ĠW it -ĠAl berto -Ġdis qualified -best os -46 1 -Ġp c -Ġ28 4 -ro bat -Rob in -Ġh ugs -ĠTrans ition -ĠOcc asionally -Ġ3 26 -ĠWh ilst -ĠLe y -Ġspaces hip -cs v -Ġun successfully -ĠA u -le ck -ĠWing ed -ĠGrizz lies -. � -Ġne arer -ĠSorce ress -ĠInd igo -El se -8 40 -let es -Co ach -Ġup bringing -ĠK es -Ġseparat ist -Ġrac ists -Ġch ained -Ġabst inence -lear ning -Ġrein stated -Ġsymm etry -Ġremind ers -ĠChe vy -Ġm ont -Ġexempl ary -ĠT OR -Z X -Ġqual itative -ĠSt amp -ĠSav annah -ĠRoss i -Ġp aed -Ġdispens aries -ĠWall s -ĠCh ronic -Ġcompliment ary -ĠBeir ut -Ġ+ --- -igs list -Ġcrypt ographic -mas ters -ĠCap itals -Ġmax imal -Ġent ropy -Point s -Ġcombat ants -l ip -ĠGl ob -ĠB MC -ph ase -th ank -HT TP -Ġcomm uter -Ġ\( \ -.. / -ĠReg ener -ĠDO I -ĠActiv ision -Ġsl it -os al -RE M -Ġch ants -Y u -Ke ys -Bre xit -ĠFor ced -Ari zona -Ġsquad ron -IS O -ĠMal one -Ġ3 38 -Ġcontrast ing -Ġt idal -Ġlib el -Ġimpl anted -Ġupro ar -ĠC ater -Ġpropos itions -M anchester -ĠEuro s -it amin -G il -ĠEl ven -ĠSe 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", -al on -K rist -Ġmeas urable -Ġimagin able -Ġapost les -Y N -7 60 -Ġster oid -Ġspecific ity -ĠL ocated -ĠBeck er -ĠE du -ĠDiet ary -uts ch -ĠMar ilyn -Ġbl ister -ĠM EP -ĠK oz -ĠC MS -y ahoo -ĠCar ney -Ġbo asting -ĠC aleb -By te -read s -ad en -Pro blem -ĠWood ward -S we -S up -ĠK GB -Set up -Ġtac it -Ġret ribution -Ġd ues -ĠM ü -. ? -ä¸ Ń -p ots -Ġcame o -ĠP AL -educ ation -A my -like ly -g ling -Ġconstitution ally -ĠHam m -ĠSpe ak -Ġwid gets -br ate -Ġcra ppy -ĠI ter -Ġanticip ating -ĠB out -P ixel -ĠY ep -ĠLaur ie -Ġh ut -Ġbullet in -ĠSal vation -Ġch ats -ear able -Honest ly -AL TH -onse qu -c ult -isco very -ovy ch -Ġse lves -ĠSat oshi -S ounds -Ġconver gence -ĠRosen berg -19 74 -Ġnas al -Ġfull est -Ġfer ocious -x us -ist e -AM S -Ġlobb ied -Ġso othing -ĠGun n -t oday -0 24 -Ġinspir ational -ĠN BN -p b -g ewater -or ah -all owed -ĠCol iseum -Ġspecial izing -Ġinsane ly -ĠT ape -del ay -Ġt arn -ĠP ound -Ġmel anch -Ġdeploy ments -il and -Ġless en -Ġfur ry -ĠUE FA -Ġblood shed -ĠMe ier -ither ing -Ġhe irs -ĠJ aw -ax ter -ĠPublic ations -Ġal ters -int ention -ĠWinc hester -d etermination -ĠLif etime -th in -Mon ster -7 80 -Ġapprox imation -Ġsuper markets -ĠSecond s -or os -h uge -Ġb ribe -ĠLIM ITED -un ed -Ġmis interpret -ĠIn jury -Ġ3 67 -Ġthreshold s -ĠCarn ival -Ġgastro intestinal -Ġguid eline -Ġde ceived -f eatures -Ġpurported ly -ĠRon nie -ĠNew t -Ġsp acious -as us -Ġsuperhero es -ĠCyn thia -le gged -k amp -ch io -Ġth umbnail -ĠShir ley -ill ation -Ġshe ds -ĠZ y -E PA -Ġdam s -Ġy awn -n ah -ĠPe ggy -ĠE rie -ĠJu ventus -ĠF ountain -r x -don ald -al bum -ĠComp rehensive -Ġc aching -ĠU z -ulner ability -ĠPrinc iple -ĠJ ian -ing ers -cast s -ĠOs iris -ch art -t ile -ĠTiff any -ĠPatt on -ĠWh ip -Ġovers ized -J e -ĠCind erella -ĠB orders -ĠDa esh -M ah -Ġdog ma -Ġcommun ists -v u -Coun cil -Ġfresh water -Ġw ounding -Ġdeb acle -Ġyoung ster -Ġthread ed -ĠB ots -ĠSav ings -ãģ Ĥ -ol ing -oh o -Ġillum ination -M RI -Ġlo osen -tr ump -ag ency -ur ion -Ġmoment arily -ĠCh un -ĠBud apest -ĠAl ley -D isk -Ġaston ished -ĠCon quer -ĠAccount ing -h aving -ĠWe in -ĠAl right -Ġrev olver -Ġdel usion -Ġrelic s -Ġad herent -qu ant -Ġhand made -or io -Ġcomb ating -c oded -Ġquad ru -re th -N ik -ĠTrib al -ĠMyster ious -Ġin hal -ĠWin ning -ĠClass ification -ch anged -Ġun ab -Ġsc orn -icip ated -w l -ond uctor -Ġrein forcing -ĠChild hood -an ova -Ġadventure r -Ġdoctor al -ĠStrateg ies -Ġengulf ed -ĠEnc ounter -Ġl ashes -Crit ical -ric ular -ĠU TF -oci ation -check ing -ĠConsult ing -Run time -per iod -ĠAs gard -Ġdist illed -ĠPas adena -ĠD ying -ĠCOUN TY -Ġgran ite -Ġsm ack -Ġparach ute -ĠS UR -Virgin ia -ĠF urious -78 7 -ĠO kin -Ġcam el -ĠM bps -19 72 -ĠCh ao -ĠC yan -j oice -ef er -ĠW rap -ĠDeb ate -S eg -Ġfore arm -ĠIgn ore -Ġtim estamp -Ġprob ing -ĠNo on -ĠGra il -f en -Ġdorm ant -ĠFirst ly -ĠE ighth -ĠH UN -ĠDes ire -or as -Girl s -ĠDes mond -z ar -am ines -O AD -exec ute -Ġbo obs -ĠAT L -_ ( -Chel sea -Ġmasturb ation -ĠCo C -Ġdestroy er -ĠCh omsky -Ġsc atter 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