From 071eb732a5b57f8387125550bec24d85e88cec51 Mon Sep 17 00:00:00 2001 From: Brian Krabach Date: Wed, 6 Nov 2024 07:23:35 -0800 Subject: [PATCH] moves helpers from chat_driver to openai_client and adds more, adds subdrive convenience to assistant_drive (#220) --- assistants/explorer-assistant/uv.lock | 73 ++ .../guided-conversation-assistant/uv.lock | 102 ++ assistants/prospector-assistant/uv.lock | 41 + assistants/skill-assistant/uv.lock | 41 + .../python/python-02-simple-chatbot/uv.lock | 102 ++ .../python-03-multimodel-chatbot/uv.lock | 102 ++ .../assistant-drive/.vscode/settings.json | 14 +- .../assistant-drive/assistant_drive/drive.py | 7 +- .../chat-driver/chat_driver/__init__.py | 11 +- .../chat-driver/chat_driver/chat_driver.py | 227 ++++ .../in_memory_message_history_provider.py | 55 + .../local_message_history_provider.py | 47 +- .../python/chat-driver/chat_driver/logger.py | 43 - .../chat_driver/message_formatter.py | 16 - .../openai_chat_completion_driver.py | 289 ----- libraries/python/chat-driver/pyproject.toml | 12 +- .../tests/formatted_instructions_test.py | 62 ++ libraries/python/chat-driver/uv.lock | 991 ++++++++++++++++++ .../function-registry/.vscode/settings.json | 2 + .../function_registry/function.py | 51 +- .../function_registry/function_registry.py | 21 +- .../tests/test_command_parsing.py | 5 +- .../openai-client/.vscode/settings.json | 6 +- .../openai-client/openai_client/__init__.py | 6 + .../openai-client/openai_client/completion.py | 59 ++ .../openai-client/openai_client/errors.py | 74 ++ .../openai-client/openai_client/logging.py | 48 + .../openai-client/openai_client/messages.py | 70 +- .../openai-client/openai_client/tools.py | 161 +++ libraries/python/openai-client/pyproject.toml | 5 +- libraries/python/openai-client/uv.lock | 102 ++ libraries/python/skills/notebooks/uv.lock | 29 + libraries/python/skills/skill-library/uv.lock | 991 ++++++++++++++++++ .../skills/skills/document-skill/uv.lock | 991 ++++++++++++++++++ .../python/skills/skills/posix-skill/uv.lock | 991 ++++++++++++++++++ .../skills/skills/prospector-skill/uv.lock | 991 ++++++++++++++++++ .../skills/skills/skill-template/uv.lock | 991 ++++++++++++++++++ 37 files changed, 7425 insertions(+), 404 deletions(-) create mode 100644 libraries/python/chat-driver/chat_driver/chat_driver.py create mode 100644 libraries/python/chat-driver/chat_driver/in_memory_message_history_provider.py delete mode 100644 libraries/python/chat-driver/chat_driver/logger.py delete mode 100644 libraries/python/chat-driver/chat_driver/message_formatter.py delete mode 100644 libraries/python/chat-driver/chat_driver/openai_chat_completion_driver.py create mode 100644 libraries/python/chat-driver/tests/formatted_instructions_test.py create mode 100644 libraries/python/openai-client/openai_client/completion.py create mode 100644 libraries/python/openai-client/openai_client/errors.py create mode 100644 libraries/python/openai-client/openai_client/logging.py create mode 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specifier = ">=1.17.1" }, + { name = "context", editable = "../../libraries/python/context" }, + { name = "openai", specifier = ">=1.16.1" }, + { name = "pydantic", specifier = ">=2.6.1" }, + { name = "pydantic-settings", specifier = ">=2.3.4" }, + { name = "python-dotenv", specifier = ">=1.0.1" }, + { name = "requests", specifier = ">=2.32.0" }, + { name = "tiktoken", specifier = ">=0.7.0" }, +] + +[package.metadata.requires-dev] +dev = [ + { name = "pytest", specifier = ">=8.3.1" }, + { name = "pytest-asyncio", specifier = ">=0.23.8" }, + { name = "pytest-repeat", specifier = ">=0.9.3" }, +] + [[package]] name = "h11" version = "0.14.0" @@ -694,6 +728,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442 }, ] +[[package]] +name = "importlib-resources" +version = "6.4.5" +source = { 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"requests", specifier = ">=2.32.0" }, + { name = "tiktoken", specifier = ">=0.7.0" }, +] + +[package.metadata.requires-dev] +dev = [ + { name = "pytest", specifier = ">=8.3.1" }, + { name = "pytest-asyncio", specifier = ">=0.23.8" }, + { name = "pytest-repeat", specifier = ">=0.9.3" }, +] + [[package]] name = "google-ai-generativelanguage" version = "0.6.10" @@ -801,6 +864,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442 }, ] +[[package]] +name = "importlib-resources" +version = "6.4.5" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/98/be/f3e8c6081b684f176b761e6a2fef02a0be939740ed6f54109a2951d806f3/importlib_resources-6.4.5.tar.gz", hash = "sha256:980862a1d16c9e147a59603677fa2aa5fd82b87f223b6cb870695bcfce830065", size = 43372 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e1/6a/4604f9ae2fa62ef47b9de2fa5ad599589d28c9fd1d335f32759813dfa91e/importlib_resources-6.4.5-py3-none-any.whl", hash = "sha256:ac29d5f956f01d5e4bb63102a5a19957f1b9175e45649977264a1416783bb717", size = 36115 }, +] + [[package]] name = "isodate" version = "0.6.1" @@ -1014,8 +1086,10 @@ dependencies = [ { name = "azure-ai-contentsafety" }, { name = "azure-core", extra = ["aio"] }, { name = "azure-identity" }, + { name = "function-registry" }, { name = "openai" }, { name = "pillow" }, + { name = "python-liquid" }, { name = "semantic-workbench-assistant" }, { name = "tiktoken" }, ] @@ -1025,8 +1099,10 @@ requires-dist = [ { name = "azure-ai-contentsafety", specifier = ">=1.0.0" }, { name = "azure-core", extras = ["aio"], specifier = ">=1.30.0" }, { name = "azure-identity", specifier = ">=1.17.1" }, + { name = "function-registry", editable = "../../../libraries/python/function-registry" }, { name = "openai", specifier = ">=1.3.9" }, { name = "pillow", specifier = ">=11.0.0" }, + { name = "python-liquid", specifier = ">=1.12.1" }, { name = "semantic-workbench-assistant", editable = "../../../libraries/python/semantic-workbench-assistant" }, { name = "tiktoken", specifier = ">=0.7.0" }, ] @@ -1266,6 +1342,18 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/e5/0c/0e3c05b1c87bb6a1c76d281b0f35e78d2d80ac91b5f8f524cebf77f51049/pyparsing-3.1.4-py3-none-any.whl", hash = "sha256:a6a7ee4235a3f944aa1fa2249307708f893fe5717dc603503c6c7969c070fb7c", size = 104100 }, ] +[[package]] +name = "python-dateutil" +version = "2.9.0.post0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "six" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/66/c0/0c8b6ad9f17a802ee498c46e004a0eb49bc148f2fd230864601a86dcf6db/python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3", size = 342432 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427", size = 229892 }, +] + [[package]] name = "python-dotenv" version = "1.0.1" @@ -1284,6 +1372,20 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/35/a6/145655273568ee78a581e734cf35beb9e33a370b29c5d3c8fee3744de29f/python_json_logger-2.0.7-py3-none-any.whl", hash = "sha256:f380b826a991ebbe3de4d897aeec42760035ac760345e57b812938dc8b35e2bd", size = 8067 }, ] +[[package]] +name = "python-liquid" +version = "1.12.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "importlib-resources" }, + { name = "python-dateutil" }, + { name = "typing-extensions" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/59/b4/c4e39470edf507056333cd688a36bb7fbdb17090105d9f454ecf6ff09845/python_liquid-1.12.1.tar.gz", hash = "sha256:7367e979125859fb4116f360f224a89a52ecb455fb26843c43e4d800b389d325", size = 124636 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/2c/6e/bfd01926e28f6cf355a7a8460271ba135013870f5857b06f35dbf65ab237/python_liquid-1.12.1-py3-none-any.whl", hash = "sha256:2224312944be16c1a44406398eb8a07c7e57398d5c0ef15ff950946dbefe7c33", size = 206592 }, +] + [[package]] name = "python-multipart" version = "0.0.12" diff --git a/libraries/python/assistant-drive/.vscode/settings.json b/libraries/python/assistant-drive/.vscode/settings.json index 4dc5f49b..edcfc2b6 100644 --- a/libraries/python/assistant-drive/.vscode/settings.json +++ b/libraries/python/assistant-drive/.vscode/settings.json @@ -11,9 +11,7 @@ "editor.guides.bracketPairs": "active", "files.eol": "\n", "files.trimTrailingWhitespace": true, - "flake8.ignorePatterns": [ - "**/*.py" - ], // disable flake8 in favor of ruff + "flake8.ignorePatterns": ["**/*.py"], // disable flake8 in favor of ruff "jupyter.debugJustMyCode": false, "python.analysis.autoFormatStrings": true, "python.analysis.autoImportCompletions": true, @@ -23,17 +21,12 @@ "**/.data/**", "**/__pycache__/**" ], - "python.analysis.fixAll": [ - "source.unusedImports" - ], + "python.analysis.fixAll": ["source.unusedImports"], "python.analysis.inlayHints.functionReturnTypes": true, "python.analysis.typeCheckingMode": "basic", "python.defaultInterpreterPath": "${workspaceFolder}/.venv/bin/python", "python.testing.cwd": "${workspaceFolder}", - "python.testing.pytestArgs": [ - "--color", - "yes" - ], + "python.testing.pytestArgs": ["--color", "yes"], "python.testing.pytestEnabled": true, "search.exclude": { "**/.venv": true, @@ -65,6 +58,7 @@ "pydantic", "pypdf", "runtimes", + "subdrive", "tiktoken" ] } diff --git a/libraries/python/assistant-drive/assistant_drive/drive.py b/libraries/python/assistant-drive/assistant_drive/drive.py index fe5d1b22..fede8f30 100644 --- a/libraries/python/assistant-drive/assistant_drive/drive.py +++ b/libraries/python/assistant-drive/assistant_drive/drive.py @@ -117,6 +117,10 @@ def _unique_filename(self, filename: str, dir: str | None) -> str: return filename + def subdrive(self, dir: PathLike | str) -> "Drive": + config = DriveConfig(root=self.root_path / dir, default_if_exists_behavior=self.default_if_exists_behavior) + return Drive(config) + def write( self, content: BinaryIO, @@ -216,11 +220,12 @@ def write_model( filename: str, dir: str | None = None, serialization_context: dict[str, Any] | None = None, - if_exists: IfDriveFileExistsBehavior = IfDriveFileExistsBehavior.AUTO_RENAME, + if_exists: IfDriveFileExistsBehavior | None = None, ) -> None: """Write a pydantic model to a file.""" data_json = value.model_dump_json(context=serialization_context) data_bytes = data_json.encode("utf-8") + if_exists = if_exists or self.default_if_exists_behavior self.write(io.BytesIO(data_bytes), filename, dir, if_exists) ModelT = TypeVar("ModelT", bound=BaseModel) diff --git a/libraries/python/chat-driver/chat_driver/__init__.py b/libraries/python/chat-driver/chat_driver/__init__.py index eeb0d77b..76bbf0de 100644 --- a/libraries/python/chat-driver/chat_driver/__init__.py +++ b/libraries/python/chat-driver/chat_driver/__init__.py @@ -1,16 +1,25 @@ # As a convenience, allow users to import the Context and ContextProtocol from # the chat_driver package. +import logging + from context import Context, ContextProtocol +from openai_client.completion import JSON_OBJECT_RESPONSE_FORMAT, TEXT_RESPONSE_FORMAT, ResponseFormat +from .chat_driver import ( + ChatDriver, + ChatDriverConfig, +) from .local_message_history_provider import LocalMessageHistoryProvider, LocalMessageHistoryProviderConfig from .message_history_provider import MessageHistoryProviderProtocol -from .openai_chat_completion_driver import TEXT_RESPONSE_FORMAT, ChatDriver, ChatDriverConfig, ResponseFormat + +logger = logging.getLogger(__name__) __all__ = [ "ChatDriver", "ChatDriverConfig", "Context", "ContextProtocol", + "JSON_OBJECT_RESPONSE_FORMAT", "LocalMessageHistoryProvider", "LocalMessageHistoryProviderConfig", "MessageHistoryProviderProtocol", diff --git a/libraries/python/chat-driver/chat_driver/chat_driver.py b/libraries/python/chat-driver/chat_driver/chat_driver.py new file mode 100644 index 00000000..6f21f155 --- /dev/null +++ b/libraries/python/chat-driver/chat_driver/chat_driver.py @@ -0,0 +1,227 @@ +from dataclasses import dataclass, field +from typing import Any, Callable, Union + +from context import Context, ContextProtocol +from events import BaseEvent, ErrorEvent, MessageEvent +from function_registry.function_registry import FunctionRegistry +from openai import AsyncOpenAI +from openai.types.chat import ( + ChatCompletionMessageParam, + ChatCompletionSystemMessageParam, + ChatCompletionUserMessageParam, +) +from openai.types.chat.completion_create_params import ResponseFormat +from openai_client.completion import TEXT_RESPONSE_FORMAT, completion_message_string +from openai_client.errors import CompletionError +from openai_client.messages import MessageFormatter, format_message +from openai_client.tools import complete_with_tool_calls, function_registry_to_tools, tool_choice +from pydantic import BaseModel + +from .local_message_history_provider import ( + LocalMessageHistoryProvider, + LocalMessageHistoryProviderConfig, +) +from .message_history_provider import MessageHistoryProviderProtocol + + +@dataclass +class ChatDriverConfig: + openai_client: AsyncOpenAI + model: str + instructions: str | list[str] = "You are a helpful assistant." + instruction_formatter: MessageFormatter | None = None + context: ContextProtocol | None = None + message_provider: MessageHistoryProviderProtocol | None = None + commands: list[Callable] = field(default_factory=list) + functions: list[Callable] = field(default_factory=list) + + +class ChatDriver: + """ + A ChatDriver is a class that manages a conversation with a user. It provides + methods to add messages to the conversation, and to generate responses to + user messages. The ChatDriver uses the OpenAI API to generate responses, and + can call functions registered with the ChatDriver to generate parts of the + response. The ChatDriver also provides a way to register commands that can + be called by the user to execute functions directly. + + Instructions are messages that are sent to the OpenAI model before any other + messages. These instructions are used to guide the model in generating a + response. The ChatDriver allows you to set instructions that can be + formatted with variables. + + If you want to just generate responses using the OpenAI API, you should use + the client directly (but we do have some helpers in the openai_helpers + module) to make this simpler. + """ + + def __init__(self, config: ChatDriverConfig) -> None: + # A context object holds information about the current session, such as + # the session ID, the user ID, and the conversation ID. It also provides + # a method to emit events. If you do not supply one, one will be created + # for you with a random session ID. + self.context: ContextProtocol = config.context or Context() + + # Set up a default message provider. This provider stores messages in a + # local file. You can replace this with your own message provider that + # implements the MessageHistoryProviderProtocol. + self.message_provider: MessageHistoryProviderProtocol = config.message_provider or LocalMessageHistoryProvider( + LocalMessageHistoryProviderConfig(context=self.context) + ) + + self.instructions: list[str] = ( + config.instructions if isinstance(config.instructions, list) else [config.instructions] + ) + self.instruction_formatter = config.instruction_formatter or format_message + + # Now set up the OpenAI client and model. + self.client = config.openai_client + self.model = config.model + + # Functions that you register with the chat driver will be available to + # for GPT to call while generating a response. If the model generates a + # call to a function, the function will be executed, the result passed + # back to the model, and the model will continue generating the + # response. + self.function_registry = FunctionRegistry(self.context, config.functions) + self.functions = self.function_registry.functions + + # Commands are functions that can be called by the user by typing a + # command in the chat. When a command is received, the chat driver will + # execute the corresponding function and return the result to the user + # directly. + self.command_registry = FunctionRegistry(self.context, config.commands) + self.commands = self.command_registry.functions + + def _formatted_instructions(self, vars: dict[str, Any] | None) -> list[ChatCompletionSystemMessageParam]: + return ChatDriver.format_instructions(self.instructions, vars, self.instruction_formatter) + + async def add_message(self, message: ChatCompletionMessageParam) -> None: + await self.message_provider.append(message) + + # Commands are available to be run by the user message. + def register_command(self, function: Callable) -> None: + self.command_registry.register_function(function) + + def register_commands(self, functions: list[Callable]) -> None: + self.command_registry.register_functions(functions) + + # Functions are available to be called by the model during response + # generation. + def register_function(self, function: Callable) -> None: + self.function_registry.register_function(function) + + def register_functions(self, functions: list[Callable]) -> None: + self.function_registry.register_functions(functions) + + # Sometimes we want to register a function to be used by both the user and + # the model. + def register_function_and_command(self, function: Callable) -> None: + self.register_command(function) + self.register_function(function) + + def register_functions_and_commands(self, functions: list[Callable]) -> None: + self.register_commands(functions) + self.register_functions(functions) + + def get_functions(self) -> list[Callable]: + return [function.fn for function in self.function_registry.get_functions()] + + def get_commands(self) -> list[Callable]: + commands = [function.fn for function in self.command_registry.get_functions()] + return commands + + async def respond( + self, + message: str | None = None, + response_format: Union[ResponseFormat, type[BaseModel]] = TEXT_RESPONSE_FORMAT, + function_choice: list[str] | None = None, + instruction_parameters: dict[str, Any] | None = None, + ) -> BaseEvent: + """ + Respond to a user message. + + If the user message is a command, the command will be executed and the + result returned. + + All generated messages are added to the chat driver's message history. + + Otherwise, the message will be passed to the chat completion API and the + response returned in the specified request_format. + + The API response might be a request to call functions registered with + the chat driver. If so, we execute the functions and give the results + back to the model for the final response generation. + """ + + # If the message contains a command, execute it. + if message and message.startswith("/"): + command_string = message[1:] + try: + results = await self.command_registry.execute_function_string_with_string_response(command_string) + return MessageEvent(message=results) + except Exception as e: + return ErrorEvent(message=f"Error! {e}", metadata={"error": str(e)}) + + # If not a command, add the message to the history. + if message is not None: + user_message: ChatCompletionUserMessageParam = { + "role": "user", + "content": message, + } + await self.add_message(user_message) + + # Generate a response. + metadata = {} + + completion_args = { + "model": self.model, + "messages": [*self._formatted_instructions(instruction_parameters), *(await self.message_provider.get())], + "tools": function_registry_to_tools(self.function_registry), + "tool_choice": tool_choice(function_choice), + "response_format": response_format, + } + try: + completion, new_messages = await complete_with_tool_calls( + self.client, + self.function_registry, + completion_args, + metadata=metadata, + ) + except CompletionError as e: + return ErrorEvent(message=f"Error: {e.message}", metadata=metadata) + + # Add the new messages to the history. + for new_message in new_messages: + await self.add_message(new_message) + + # Return the response. + + return MessageEvent( + message=completion_message_string(completion) or None, + metadata=metadata, + ) + + @staticmethod + def format_instructions( + instructions: list[str], + vars: dict[str, Any] | None = None, + formatter: MessageFormatter | None = None, + ) -> list[ChatCompletionSystemMessageParam]: + """ + Chat Driver instructions are system messages given to the OpenAI model + before any other messages. These instructions are used to guide the model in + generating a response. We oftentimes need inject variables into the + instructions, so we provide a formatter function to format the instructions + with the variables. This method returns a list of system messages formatted + with the variables. + """ + formatter = formatter or format_message + instruction_messages: list[ChatCompletionSystemMessageParam] = [] + for instruction in instructions: + if vars: + formatted_instruction = formatter(instruction, vars) + else: + formatted_instruction = instruction + instruction_messages.append({"role": "system", "content": formatted_instruction}) + return instruction_messages diff --git a/libraries/python/chat-driver/chat_driver/in_memory_message_history_provider.py b/libraries/python/chat-driver/chat_driver/in_memory_message_history_provider.py new file mode 100644 index 00000000..9314a383 --- /dev/null +++ b/libraries/python/chat-driver/chat_driver/in_memory_message_history_provider.py @@ -0,0 +1,55 @@ +import asyncio +from typing import Any, Iterable + +from openai.types.chat import ChatCompletionMessageParam, ChatCompletionMessageToolCallParam +from openai_client.messages import ( + MessageFormatter, + assistant_message, + format_message, + system_message, + user_message, +) + + +class InMemoryMessageHistoryProvider: + def __init__( + self, + messages: list[ChatCompletionMessageParam] | None = None, + formatter: MessageFormatter | None = None, + ) -> None: + self.formatter: MessageFormatter = formatter or format_message + self.messages = messages or [] + + async def get(self) -> list[ChatCompletionMessageParam]: + """Get all messages. This method is required for conforming to the + MessageFormatter protocol.""" + return self.messages + + async def append(self, message: ChatCompletionMessageParam) -> None: + """Append a message to the history. This method is required for + conforming to the MessageFormatter protocol.""" + self.messages.append(message) + + def extend(self, messages: list[ChatCompletionMessageParam]) -> None: + self.messages.extend(messages) + + def set(self, messages: list[ChatCompletionMessageParam], vars: dict[str, Any]) -> None: + self.messages = messages + + def delete_all(self) -> None: + self.messages = [] + + def append_system_message(self, content: str, var: dict[str, Any] | None = None) -> None: + asyncio.run(self.append(system_message(content, var, self.formatter))) + + def append_user_message(self, content: str, var: dict[str, Any] | None = None) -> None: + asyncio.run(self.append(user_message(content, var, self.formatter))) + + def append_assistant_message( + self, + content: str, + refusal: str | None = None, + tool_calls: Iterable[ChatCompletionMessageToolCallParam] | None = None, + var: dict[str, Any] | None = None, + ) -> None: + asyncio.run(self.append(assistant_message(content, refusal, tool_calls, var, self.formatter))) diff --git a/libraries/python/chat-driver/chat_driver/local_message_history_provider.py b/libraries/python/chat-driver/chat_driver/local_message_history_provider.py index fecf2ae9..53cd6ec5 100644 --- a/libraries/python/chat-driver/chat_driver/local_message_history_provider.py +++ b/libraries/python/chat-driver/chat_driver/local_message_history_provider.py @@ -2,14 +2,22 @@ from dataclasses import dataclass, field from os import PathLike from pathlib import Path -from typing import Any +from typing import Any, Iterable from context.context import ContextProtocol from openai.types.chat import ( ChatCompletionMessageParam, + ChatCompletionMessageToolCallParam, +) +from openai_client.messages import ( + MessageFormatter, + assistant_message, + format_message, + system_message, + user_message, ) -from .message_formatter import MessageFormatter, format_message +from .message_history_provider import MessageHistoryProviderProtocol DEFAULT_DATA_DIR = Path(".data") @@ -22,13 +30,13 @@ class LocalMessageHistoryProviderConfig: formatter: MessageFormatter | None = None -class LocalMessageHistoryProvider: +class LocalMessageHistoryProvider(MessageHistoryProviderProtocol): def __init__(self, config: LocalMessageHistoryProviderConfig) -> None: if not config.data_dir: self.data_dir = DEFAULT_DATA_DIR / "chat_driver" / config.context.session_id else: self.data_dir = Path(config.data_dir) - self.formatter = config.formatter or format_message + self.formatter: MessageFormatter = config.formatter or format_message # Create the messages file if it doesn't exist. if not self.data_dir.exists(): @@ -38,22 +46,49 @@ def __init__(self, config: LocalMessageHistoryProviderConfig) -> None: self.messages_file.write_text("[]") async def get(self) -> list[ChatCompletionMessageParam]: + """ + Get all messages. This method is required for conforming to the + MessageFormatter protocol. + """ return json.loads(self.messages_file.read_text()) async def append(self, message: ChatCompletionMessageParam) -> None: + """ + Append a message to the history. This method is required for conforming + to the MessageFormatter protocol. + """ messages = await self.get() messages.append(message) self.messages_file.write_text(json.dumps(messages, indent=2)) - # Additional methods. - async def extend(self, messages: list[ChatCompletionMessageParam]) -> None: + """ + Append a list of messages to the history. + """ existing_messages = await self.get() existing_messages.extend(messages) self.messages_file.write_text(json.dumps(existing_messages, indent=2)) async def set(self, messages: list[ChatCompletionMessageParam], vars: dict[str, Any]) -> None: + """ + Completely replace the messages with the new messages. + """ self.messages_file.write_text(json.dumps(messages, indent=2)) def delete_all(self) -> None: self.messages_file.write_text("[]") + + async def append_system_message(self, content: str, var: dict[str, Any] | None = None) -> None: + await self.append(system_message(content, var, self.formatter)) + + async def append_user_message(self, content: str, var: dict[str, Any] | None = None) -> None: + await self.append(user_message(content, var, self.formatter)) + + async def append_assistant_message( + self, + content: str, + refusal: str, + tool_calls: Iterable[ChatCompletionMessageToolCallParam] | None = None, + var: dict[str, Any] | None = None, + ) -> None: + await self.append(assistant_message(content, refusal, tool_calls, var, self.formatter)) diff --git a/libraries/python/chat-driver/chat_driver/logger.py b/libraries/python/chat-driver/chat_driver/logger.py deleted file mode 100644 index 0f1503f6..00000000 --- a/libraries/python/chat-driver/chat_driver/logger.py +++ /dev/null @@ -1,43 +0,0 @@ -import json -import logging -from typing import Any - -from context import ContextProtocol - - -class Logger: - def __init__(self, name: str, context: ContextProtocol) -> None: - self.logger = logging.getLogger(name) - self.context = context - - def _extra(self, data: Any) -> dict[str, Any]: - extra = {"session_id": self.context.session_id, "run_id": self.context.run_id} - - # Ensure data is a JSON-serializable object. - try: - data = json.loads(json.dumps(data)) - except Exception: - data = None - - if data: - extra["data"] = data - - return extra - - def info(self, message: str, data: Any = None) -> None: - self.logger.info(message, extra=self._extra(data)) - - def warning(self, message: str, data: Any = None) -> None: - self.logger.warning(message, extra=self._extra(data)) - - def error(self, message: str, data: Any = None) -> None: - self.logger.error(message, extra=self._extra(data)) - - def debug(self, message: str, data: Any = None) -> None: - self.logger.debug(message, extra=self._extra(data)) - - def critical(self, message: str, data: Any = None) -> None: - self.logger.critical(message, extra=self._extra(data)) - - def exception(self, message: str, data: Any = None) -> None: - self.logger.exception(message, extra=self._extra(data)) diff --git a/libraries/python/chat-driver/chat_driver/message_formatter.py b/libraries/python/chat-driver/chat_driver/message_formatter.py deleted file mode 100644 index 69dccf5a..00000000 --- a/libraries/python/chat-driver/chat_driver/message_formatter.py +++ /dev/null @@ -1,16 +0,0 @@ -from typing import Any, Callable - -MessageFormatter = Callable[[str, dict[str, Any]], str] - - -def format_message(message: str, vars: dict[str, Any]) -> str: - """ - Format a message with the given variables. - """ - if message and vars: - for key, value in vars.items(): - try: - message = message.format(**{key: value}) - except KeyError: - pass - return message diff --git a/libraries/python/chat-driver/chat_driver/openai_chat_completion_driver.py b/libraries/python/chat-driver/chat_driver/openai_chat_completion_driver.py deleted file mode 100644 index 61ce85b3..00000000 --- a/libraries/python/chat-driver/chat_driver/openai_chat_completion_driver.py +++ /dev/null @@ -1,289 +0,0 @@ -import json -from dataclasses import dataclass, field -from typing import Any, Callable, Iterable, List - -from context.context import Context, ContextProtocol -from events import BaseEvent, MessageEvent -from function_registry.function_registry import FunctionRegistry -from openai import APIConnectionError, APIStatusError, AsyncOpenAI, NotGiven, RateLimitError -from openai.types.chat import ( - ChatCompletionAssistantMessageParam, - ChatCompletionMessageParam, - ChatCompletionSystemMessageParam, - ChatCompletionToolMessageParam, - ChatCompletionToolParam, - ChatCompletionUserMessageParam, -) -from openai.types.chat.completion_create_params import ResponseFormat - -from .local_message_history_provider import LocalMessageHistoryProvider, LocalMessageHistoryProviderConfig -from .logger import Logger -from .message_formatter import MessageFormatter, format_message -from .message_history_provider import MessageHistoryProviderProtocol - -DEFAULT_MAX_RETRIES = 3 -TEXT_RESPONSE_FORMAT: ResponseFormat = {"type": "text"} - - -# TODO: Make the chat driver handle json and json schema responses. -JSON_OBJECT_RESPONSE_FORMAT: ResponseFormat = {"type": "json_object"} -# {"type": "json_schema", "json_schema": {"name": "test", "schema": {}}} - - -@dataclass -class ChatDriverConfig: - openai_client: AsyncOpenAI - model: str - instructions: str = "You are a helpful assistant." - instruction_formatter: MessageFormatter | None = None - context: ContextProtocol | None = None - message_provider: MessageHistoryProviderProtocol | None = None - commands: list[Callable] = field(default_factory=list) - functions: list[Callable] = field(default_factory=list) - - -class ChatDriver: - def __init__(self, config: ChatDriverConfig) -> None: - # A context object holds information about the current session, such as - # the session ID, the user ID, and the conversation ID. It also provides - # a method to emit events. If you do not supply one, one will be created - # for you with a random session ID. - self.context = config.context or Context() - - # Set up logging. - self.logger = Logger(__name__, self.context) - - # Set up a default message provider. This provider stores messages in a - # local file. You can replace this with your own message provider that - # implements the MessageHistoryProviderProtocol. - self.message_provider = config.message_provider or LocalMessageHistoryProvider( - LocalMessageHistoryProviderConfig(context=self.context) - ) - - self.instructions = config.instructions - self.instruction_formatter = config.instruction_formatter or format_message - - # Now set up the OpenAI client and model. - self.client = config.openai_client - self.model = config.model - - # Functions that you register with the chat driver will be available to - # for GPT to call while generating a response. If the model generates a - # call to a function, the function will be executed, the result passed - # back to the model, and the model will continue generating the - # response. - self.function_registry = FunctionRegistry(self.context, config.functions) - self.functions = self.function_registry.functions - - # Commands are functions that can be called by the user by typing a - # command in the chat. When a command is received, the chat driver will - # execute the corresponding function and return the result to the user - # directly. - self.command_registry = FunctionRegistry(self.context, config.commands) - self.commands = self.command_registry.functions - - def _formatted_instruction(self, vars: dict[str, Any] | None) -> ChatCompletionSystemMessageParam | None: - if not self.instructions: - return - if vars: - formatted_instruction = self.instruction_formatter(self.instructions, vars) - else: - formatted_instruction = self.instructions - return {"role": "system", "content": formatted_instruction} - - async def add_message(self, message: ChatCompletionMessageParam) -> None: - await self.message_provider.append(message) - - async def add_error_message(self, message: str) -> None: - error_message: ChatCompletionSystemMessageParam = { - "role": "system", - "content": f"Error: {message}", - } - await self.add_message(error_message) - - # Commands are available to be run by the user message. - def register_command(self, function: Callable) -> None: - self.command_registry.register_function(function) - - def register_commands(self, functions: list[Callable]) -> None: - self.command_registry.register_functions(functions) - - # Functions are available to be called by the model during response - # generation. - def register_function(self, function: Callable) -> None: - self.function_registry.register_function(function) - - def register_functions(self, functions: list[Callable]) -> None: - self.function_registry.register_functions(functions) - - # Sometimes we want to register a function to be used by both the user and - # the model. - def register_function_and_command(self, function: Callable) -> None: - self.register_command(function) - self.register_function(function) - - def register_functions_and_commands(self, functions: list[Callable]) -> None: - self.register_commands(functions) - self.register_functions(functions) - - def get_functions(self) -> list[Callable]: - return [function.fn for function in self.function_registry.get_functions()] - - def get_commands(self) -> list[Callable]: - commands = [function.fn for function in self.command_registry.get_functions()] - return commands - - def _get_tools(self) -> Iterable[ChatCompletionToolParam]: - # Only the "functions" tool is available in the Chat API. - # https://platform.openai.com/docs/guides/function-calling - - functions: List[ChatCompletionToolParam] = [] - for function in [func.schema for func in self.function_registry.get_functions()]: - functions.append( - ChatCompletionToolParam(**{ - "type": "function", - "function": function, - }) - ) - - return functions - - async def respond( - self, - message: str, - response_format: ResponseFormat = TEXT_RESPONSE_FORMAT, - instruction_parameters: dict[str, Any] | None = None, - ) -> BaseEvent: - """Respond to a user message. - - If the user message is a command, the command will be executed and the - result returned. - - Otherwise, the message will be passed to the chat completion API and the - response returned. - - The api response might be a request to call functions registered with - the chat driver. If so, we execute the functions and give the results - back to the model for the final response generation.""" - - if instruction_parameters is None: - instruction_parameters = {} - - # If the message contains a command, execute it. - if message.startswith("/"): - command_string = message[1:] - try: - results = await self.command_registry.execute_function_string_with_string_response(command_string) - return MessageEvent(message=results) - except Exception as e: - await self.add_error_message(f"Error: {e}") - return MessageEvent(message="Error!", metadata={"error": str(e)}) - - # Otherwise, generate a response. - user_message: ChatCompletionUserMessageParam = { - "role": "user", - "content": message, - } - await self.add_message(user_message) - - completion_args = { - "messages": [self._formatted_instruction(instruction_parameters), *(await self.message_provider.get())], - "model": "gpt-4o", - "tools": self._get_tools(), - "response_format": response_format, - } - metadata: dict[str, Any] = {"completion_args": completion_args} - self.logger.debug("Chat completion args.", data=completion_args) - if not completion_args["tools"]: - completion_args["tools"] = NotGiven() - - try: - completion = await self.client.chat.completions.create(**completion_args) - log_data = { - "messages": completion_args["messages"], - "model": completion_args["model"], - "tools": completion_args["tools"], - "response_format": completion_args["response_format"], - } - metadata["completion_response"] = completion.model_dump() - self.logger.debug("Chat Completion response.", data=log_data) - except APIConnectionError as e: - msg = f"The server could not be reached: {e.__cause__}" - self.logger.error(msg) - await self.add_error_message(msg) - metadata["error"] = str(e) - return MessageEvent(message="The server could not be reached.", metadata=metadata) - except RateLimitError: - msg = "A 429 status code was received; we should back off a bit." - self.logger.error(msg) - await self.add_error_message(msg) - return MessageEvent(message="Rate limit error.", metadata=metadata) - except APIStatusError as e: - msg = f"Another non-200-range status code was received. {e.status_code}: {e.response}" - self.logger.error(msg) - await self.add_error_message(msg) - metadata["error"] = str(e) - return MessageEvent(message="API status error.", metadata=metadata) - - # Get response and add to messages. - response_message = completion.choices[0].message - tool_calls = response_message.tool_calls - assistant_response = ChatCompletionAssistantMessageParam(**response_message.model_dump()) - await self.add_message(assistant_response) - message_for_return = assistant_response - metadata["assistant_response"] = assistant_response - - # If the response includes function tool calls, execute them and pass - # the result back to the API. - if tool_calls: - for tool_call in tool_calls: - function = tool_call.function - if self.function_registry.has_function(function.name): - # Call function. - self.logger.debug("Function call.", data={"name": function.name, "arguments": function.arguments}) - try: - kwargs: dict[str, Any] = json.loads(function.arguments) - value = await self.function_registry.execute_function(function.name, (), kwargs) - except Exception as e: - self.logger.error("Error.", data={"error": e}) - value = f"Error: {e}" - - # Create function message. - content = "" - if response_format["type"] == "text": - content = str(value) - elif response_format["type"] == "json_object": - content = json.dumps(value) - function_call_result_message: ChatCompletionToolMessageParam = { - "role": "tool", - "content": content, - "tool_call_id": tool_call.id, - } - await self.add_message(function_call_result_message) - self.logger.debug("Function response.", data={"content": content}) - metadata["function_call_result_message"] = function_call_result_message - - # Call assistant for final response. - assistant_tool_completion_args = { - "messages": [self._formatted_instruction(instruction_parameters), *(await self.message_provider.get())], - "model": "gpt-4o", - } - self.logger.debug("Calling Completions API with tool response.", data=assistant_tool_completion_args) - metadata["assistant_tool_completion_args"] = assistant_tool_completion_args - completion = await self.client.chat.completions.create(**assistant_tool_completion_args) - - # Add assistant response to messages. - assistant_tool_response = ChatCompletionAssistantMessageParam(**completion.choices[0].message.model_dump()) - await self.add_message(assistant_tool_response) - message_for_return = assistant_tool_response - self.logger.debug("Assistant tool response.", data=assistant_tool_response) - metadata["assistant_tool_response"] = assistant_tool_response - - # TODO: Check if it's another tool call? - - # Return the last message. - if message_for_return.get("role") == "assistant": - content = message_for_return.get("content") - return MessageEvent(message=str(content), metadata=metadata) - - return MessageEvent(message="No response.", metadata=metadata) diff --git a/libraries/python/chat-driver/pyproject.toml b/libraries/python/chat-driver/pyproject.toml index 8d181953..4a8832b1 100644 --- a/libraries/python/chat-driver/pyproject.toml +++ b/libraries/python/chat-driver/pyproject.toml @@ -6,16 +6,17 @@ authors = [{name="MADE:Explorers"}] readme = "README.md" requires-python = ">=3.11" dependencies = [ + "azure-identity>=1.17.1", + "context>=0.1.0", + "events>=0.1.0", + "function-registry>=0.1.0", "openai>=1.16.1", - "pydantic>=2.6.1", + "openai-client>=0.1.0", "pydantic-settings>=2.3.4", + "pydantic>=2.6.1", "python-dotenv>=1.0.1", "requests>=2.32.0", "tiktoken>=0.7.0", - "azure-identity>=1.17.1", - "context>=0.1.0", - "events>=0.1.0", - "function-registry>=0.1.0", ] [tool.uv] @@ -25,6 +26,7 @@ package = true context = { path = "../context", editable = true } events = { path = "../events", editable = true } function-registry = { path = "../function-registry", editable = true } +openai-client = { path = "../openai-client", editable = true } [build-system] requires = ["hatchling"] diff --git a/libraries/python/chat-driver/tests/formatted_instructions_test.py b/libraries/python/chat-driver/tests/formatted_instructions_test.py new file mode 100644 index 00000000..a8331315 --- /dev/null +++ b/libraries/python/chat-driver/tests/formatted_instructions_test.py @@ -0,0 +1,62 @@ +from chat_driver.chat_driver import ChatDriver +from openai_client.messages import format_message + + +def test_formatted_instructions() -> None: + # Set instructions. + instructions = [ + ( + "Generate an outline for the document, including title. The outline should include the key points that will" + " be covered in the document. Consider the attachments, the rationale for why they were uploaded, and the" + " conversation that has taken place. The outline should be a hierarchical structure with multiple levels of" + " detail, and it should be clear and easy to understand. The outline should be generated in a way that is" + " consistent with the document that will be generated from it." + ), + "{{chat_history}}", + "{% for attachment in attachments %}{{attachment.filename}}{{attachment.content}}{% endfor %}", + "{{outline_versions.last}}", + "{{user_feedback}}", + ] + + # Set vars. + attachments = [ + {"filename": "filename1", "content": "content1"}, + {"filename": "filename2", "content": "content2"}, + ] + outline_versions = ["outline1", "outline2"] + user_feedback = "feedback" + chat_history = "history" + formatted_instructions = ChatDriver.format_instructions( + instructions=instructions, + vars={ + "attachments": attachments, + "outline_versions": outline_versions, + "user_feedback": user_feedback, + "chat_history": chat_history, + }, + formatter=format_message, + ) + + expected = [ + { + "role": "system", + "content": "Generate an outline for the document, including title. The outline should include the key points that will be covered in the document. Consider the attachments, the rationale for why they were uploaded, and the conversation that has taken place. The outline should be a hierarchical structure with multiple levels of detail, and it should be clear and easy to understand. The outline should be generated in a way that is consistent with the document that will be generated from it.", + }, + {"role": "system", "content": "history"}, + # { + # "role": "system", + # "content": "filename1content1", + # }, + # { + # "role": "system", + # "content": "filename2content2", + # }, + { + "role": "system", + "content": "filename1content1filename2content2", + }, + {"role": "system", "content": "outline2"}, + {"role": "system", "content": "feedback"}, + ] + + assert formatted_instructions == expected diff --git a/libraries/python/chat-driver/uv.lock b/libraries/python/chat-driver/uv.lock index e847a66c..d185b278 100644 --- a/libraries/python/chat-driver/uv.lock +++ b/libraries/python/chat-driver/uv.lock @@ -5,6 +5,88 @@ resolution-markers = [ "python_full_version >= '3.13'", ] +[[package]] +name = "aiohappyeyeballs" +version = "2.4.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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38d6fe3b..e930c1dc 100644 --- a/libraries/python/function-registry/.vscode/settings.json +++ b/libraries/python/function-registry/.vscode/settings.json @@ -48,7 +48,9 @@ "ruff.nativeServer": "on", "cSpell.words": [ "dotenv", + "elts", "httpx", + "jsonschema", "openai", "pydantic", "pypdf", diff --git a/libraries/python/function-registry/function_registry/function.py b/libraries/python/function-registry/function_registry/function.py index 8cc0865e..39bdbbb7 100644 --- a/libraries/python/function-registry/function_registry/function.py +++ b/libraries/python/function-registry/function_registry/function.py @@ -1,9 +1,10 @@ +import inspect from dataclasses import dataclass from typing import Any, Callable -import inspect + +from context.context import ContextProtocol from pydantic import create_model from pydantic.fields import FieldInfo -from context.context import ContextProtocol @dataclass @@ -15,13 +16,15 @@ class Parameter: class Function: - def __init__(self, name: str, description: str | None, parameters: list[Parameter], fn: Callable) -> None: + def __init__( + self, name: str, description: str | None, parameters: list[Parameter], fn: Callable, strict_schema: bool = False + ) -> None: self.name = name self.description = description or name.replace("_", " ").title() self.parameters = parameters self.fn = fn - self.schema = self._generate_schema() - self.usage = self._generate_usage() + self.schema: dict[str, Any] = self._generate_schema(strict=strict_schema) + self.usage: str = self._generate_usage() async def execute(self, context: ContextProtocol, *args, **kwargs) -> Any: result = self.fn(context, *args, **kwargs) @@ -50,7 +53,7 @@ def _generate_usage(self) -> str: description = self.description return f"{name}({', '.join(param_usages)}): {description}" - def _generate_schema(self) -> dict[str, Any]: + def _generate_schema(self, strict: bool = True) -> dict[str, Any]: """ Generate a JSON schema for a function based on its signature. """ @@ -68,19 +71,20 @@ def _generate_schema(self) -> dict[str, Any]: field_info, ) pydantic_model = create_model(model_name, **fields) + # pydantic_model.model_config = {"field_title_generator": lambda _, _: None} # Generate the JSON schema from the Pydantic model. - basic_schema = pydantic_model.model_json_schema() + parameters_schema = pydantic_model.model_json_schema(mode="serialization") # Remove title attribute from all properties. - properties = basic_schema["properties"] - for property in properties: - if "title" in properties[property]: - del properties[property]["title"] + properties = parameters_schema["properties"] + for property_key in properties.keys(): + if "title" in properties[property_key]: + del properties[property_key]["title"] # And from the top-level object. - if "title" in basic_schema: - del basic_schema["title"] + if "title" in parameters_schema: + del parameters_schema["title"] name = self.fn.__name__ description = inspect.getdoc(self.fn) or name.replace("_", " ").title() @@ -93,15 +97,26 @@ def _generate_schema(self) -> dict[str, Any]: # "$id": f"urn:jsonschema:{name}", "name": name, "description": description, + "strict": strict, "parameters": { "type": "object", - "properties": basic_schema["properties"], + "properties": parameters_schema["properties"], }, } - if "required" in basic_schema: - schema["required"] = basic_schema["required"] + # If this is a strict schema requirement, OpenAI requires + # additionalProperties to be False. + # if strict: + schema["parameters"]["additionalProperties"] = False + + # Add required fields. + if "required" in parameters_schema: + schema["parameters"]["required"] = parameters_schema["required"] + + # Add definitions. + if "$defs" in parameters_schema: + schema["parameters"]["$defs"] = parameters_schema["$defs"] + for key in schema["parameters"]["$defs"]: + schema["parameters"]["$defs"][key]["additionalProperties"] = False - if "$defs" in basic_schema: - schema["$defs"] = basic_schema["$defs"] return schema diff --git a/libraries/python/function-registry/function_registry/function_registry.py b/libraries/python/function-registry/function_registry/function_registry.py index e27ee3db..91459938 100644 --- a/libraries/python/function-registry/function_registry/function_registry.py +++ b/libraries/python/function-registry/function_registry/function_registry.py @@ -1,10 +1,11 @@ -from typing import Any, Callable +import ast import inspect -from pydantic import BaseModel import json import logging +from typing import Any, Callable + from context.context import ContextProtocol -import ast +from pydantic import BaseModel from .function import Function, Parameter @@ -32,13 +33,14 @@ class FunctionRegistry: def __init__(self, context: ContextProtocol, functions: list[Callable] = []) -> None: self.context = context + self.function_map: dict[str, Function] = {} # By default, every registry has a help function. - self.register_function(self.help) + self.register_function(self.help, strict_schema=True) # But the help function can be overridden if you give it another one. - self.register_functions(functions) + self.register_functions(functions, strict_schema=True) # This allows actions to be called as attributes. self.functions = FunctionHandler(self) @@ -61,7 +63,7 @@ def has_function(self, name: str) -> bool: return True return name in self.function_map - def register_function(self, function: Callable) -> None: + def register_function(self, function: Callable, strict_schema: bool = True) -> None: # Ensure the first argument of the function is the context. if not inspect.signature(function).parameters: raise ValueError(f"Function {function.__name__} must have at least one parameter (context: Context).") @@ -87,16 +89,17 @@ def register_function(self, function: Callable) -> None: description=inspect.getdoc(function) or function.__name__.replace("_", " ").title(), fn=function, parameters=params, + strict_schema=strict_schema, ) - def register_functions(self, functions: list[Callable]) -> None: + def register_functions(self, functions: list[Callable], strict_schema: bool = True) -> None: for function in functions: if function.__name__ in self.function_map: logging.warning(f"Function {function.__name__} already registered.") continue if not callable(function): raise ValueError(f"Function {function} is not callable.") - self.register_function(function) + self.register_function(function, strict_schema=strict_schema) async def execute_function(self, name: str, args: tuple, kwargs: dict[str, Any]) -> Any: """Run a registered function by name. Passes the context as the first argument.""" @@ -105,7 +108,7 @@ async def execute_function(self, name: str, args: tuple, kwargs: dict[str, Any]) raise ValueError(f"Function {name} not found in registry.") return await function.execute(self.context, *args, **kwargs) - async def execute_function_with_string_response(self, name: str, *args, **kwargs) -> str: + async def execute_function_with_string_response(self, name: str, args: tuple, kwargs: dict[str, Any]) -> str: """Run a registered function by name and return a string response.""" try: result = await self.execute_function(name, args, kwargs) diff --git a/libraries/python/function-registry/function_registry/tests/test_command_parsing.py b/libraries/python/function-registry/function_registry/tests/test_command_parsing.py index 73da19dd..ded4b454 100644 --- a/libraries/python/function-registry/function_registry/tests/test_command_parsing.py +++ b/libraries/python/function-registry/function_registry/tests/test_command_parsing.py @@ -1,7 +1,8 @@ +from typing import Any, Callable + import pytest -from function_registry.function_registry import FunctionRegistry from context.context import Context -from typing import Callable, Any +from function_registry.function_registry import FunctionRegistry def no_op(context: Context) -> None: diff --git a/libraries/python/openai-client/.vscode/settings.json b/libraries/python/openai-client/.vscode/settings.json index 4f6a3ffd..d393f820 100644 --- a/libraries/python/openai-client/.vscode/settings.json +++ b/libraries/python/openai-client/.vscode/settings.json @@ -35,5 +35,9 @@ "**/.venv": true, "**/.data": true, "**/__pycache__": true - } + }, + "cSpell.words": [ + "openai", + "Pydantic" + ] } diff --git a/libraries/python/openai-client/openai_client/__init__.py b/libraries/python/openai-client/openai_client/__init__.py index a3bffd5b..6543f748 100644 --- a/libraries/python/openai-client/openai_client/__init__.py +++ b/libraries/python/openai-client/openai_client/__init__.py @@ -1,3 +1,5 @@ +import logging + from .client import ( create_client, ) @@ -17,6 +19,9 @@ num_tokens_from_tools_and_messages, ) +logger = logging.getLogger(__name__) + + __all__ = [ "create_client", "truncate_messages_for_logging", @@ -28,4 +33,5 @@ "AzureOpenAIServiceConfig", "OpenAIServiceConfig", "ServiceConfig", + "logger", ] diff --git a/libraries/python/openai-client/openai_client/completion.py b/libraries/python/openai-client/openai_client/completion.py new file mode 100644 index 00000000..b42051e4 --- /dev/null +++ b/libraries/python/openai-client/openai_client/completion.py @@ -0,0 +1,59 @@ +import json +from typing import Any + +from openai.types.chat import ( + ChatCompletionAssistantMessageParam, + ParsedChatCompletion, + ParsedChatCompletionMessage, +) +from openai.types.chat.completion_create_params import ( + ResponseFormat, +) +from pydantic import BaseModel + +DEFAULT_MAX_RETRIES = 3 + +# The response method can return a text response, a JSON object response, or as +# a Pydantic BaseModel. See the `response` method for more details. +TEXT_RESPONSE_FORMAT: ResponseFormat = {"type": "text"} +JSON_OBJECT_RESPONSE_FORMAT: ResponseFormat = {"type": "json_object"} + + +def assistant_message_from_completion(completion: ParsedChatCompletion[None]) -> ChatCompletionAssistantMessageParam: + completion_message: ParsedChatCompletionMessage = completion.choices[0].message + assistant_message = ChatCompletionAssistantMessageParam(role="assistant") + if completion_message.tool_calls: + response_dict = completion_message.model_dump() + assistant_message["tool_calls"] = response_dict["tool_calls"] + if completion_message.content: + assistant_message["content"] = completion_message.content + return assistant_message + + +def completion_message(completion: ParsedChatCompletion) -> ParsedChatCompletionMessage | None: + return completion.choices[0].message if completion and completion.choices else None + + +def completion_message_string(completion: ParsedChatCompletion | None) -> str: + if not completion or not completion.choices or not completion.choices[0].message: + return "" + return completion.choices[0].message.content or "" + + +def completion_message_dict(completion: ParsedChatCompletion) -> dict[str, Any] | None: + message = completion_message(completion) + if message: + if message.parsed: + if isinstance(message.parsed, BaseModel): + return message.parsed.model_dump() + elif isinstance(message.parsed, dict): + return message.parsed + else: + try: # Try to parse the JSON string. + return json.loads(message.parsed) + except json.JSONDecodeError: + return None + try: + return json.loads(message.content or "") + except json.JSONDecodeError: + return None diff --git a/libraries/python/openai-client/openai_client/errors.py b/libraries/python/openai-client/openai_client/errors.py new file mode 100644 index 00000000..d5070768 --- /dev/null +++ b/libraries/python/openai-client/openai_client/errors.py @@ -0,0 +1,74 @@ +from typing import Any + +from openai import ( + APIConnectionError, + APIStatusError, + BadRequestError, + RateLimitError, +) +from openai.types.chat import ( + ParsedChatCompletion, +) + + +class InValidCompletionError(Exception): + def __init__(self, message: str, body: dict[str, Any] | None = None) -> None: + self.message = message + self.body = body + super().__init__(self.message) + + +class CompletionIsNoneError(InValidCompletionError): + def __init__(self) -> None: + super().__init__("The completion response is None.") + + +class CompletionRefusedError(InValidCompletionError): + def __init__(self, refusal: str) -> None: + super().__init__(f"The model refused to complete the response: {refusal}", {"refusal": refusal}) + + +class CompletionWithoutStopError(InValidCompletionError): + def __init__(self, finish_reason: str) -> None: + super().__init__(f"The model did not complete the response: {finish_reason}", {"finish_reason": finish_reason}) + + +class CompletionError(Exception): + def __init__(self, error: Exception) -> None: + if isinstance(error, APIConnectionError): + message = f"The server could not be reached: {error.__cause__}" + body = error.body + elif isinstance(error, RateLimitError): + message = "A 429 status code was received (rate limited); we should back off a bit." + body = error.body + elif isinstance(error, BadRequestError): + message = f"A 400 status code was received. {error.message}" + body = error.body + elif isinstance(error, APIStatusError): + message = f"Another non-200-range status code was received. {error.status_code}: {error.message}" + body = error.body + elif isinstance(error, InValidCompletionError): + message = error.message + body = error.body + else: + message = "An unknown error occurred." + body = str(error) + + self.message = message + self.body = body + super().__init__(message) + + +def validate_completion(completion: ParsedChatCompletion[None]) -> None: + if completion is None: + raise CompletionIsNoneError() + + # Check for refusal. + refusal = completion.choices[0].message.refusal + if refusal: + raise CompletionRefusedError(refusal) + + # Check "finish_reason" for "max_tokens" or "stop" to see if the response is incomplete. + finish_reason = completion.choices[0].finish_reason + if finish_reason not in ["stop", "tool_calls", None]: + raise CompletionWithoutStopError(finish_reason) diff --git a/libraries/python/openai-client/openai_client/logging.py b/libraries/python/openai-client/openai_client/logging.py new file mode 100644 index 00000000..fac8705b --- /dev/null +++ b/libraries/python/openai-client/openai_client/logging.py @@ -0,0 +1,48 @@ +import inspect +import json +from typing import Any + +from openai import ( + NotGiven, +) +from pydantic import BaseModel + + +def serializable_completion_args(completion_args: dict[str, Any]) -> dict[str, Any]: + """ + We put the completion args into logs and messages, so it's important that + they are serializable. This function returns a copy of the completion args + that can be serialized. + """ + sanitized = completion_args.copy() + + # NotGiven type (used by OpenAI) is not serializable. + if isinstance(completion_args.get("tools"), NotGiven): + del sanitized["tools"] + + # A pydantic BaseModel class is not serializable, and we don't want the + # whole class anyway, so we just store the name. + if completion_args.get("response_format"): + response_format = completion_args["response_format"] + if inspect.isclass(response_format) and issubclass(response_format, BaseModel): + sanitized["response_format"] = response_format.__name__ + + return sanitized + + +def extra_data(data: Any) -> dict[str, Any]: + """ + Helper function to add extra data to log messages. + """ + extra = {} + + # Ensure data is a JSON-serializable object. + try: + data = json.loads(json.dumps(data)) + except Exception as e: + data = str(e) + + if data: + extra["data"] = data + + return extra diff --git a/libraries/python/openai-client/openai_client/messages.py b/libraries/python/openai-client/openai_client/messages.py index ec4c069b..2f3e58ff 100644 --- a/libraries/python/openai-client/openai_client/messages.py +++ b/libraries/python/openai-client/openai_client/messages.py @@ -1,6 +1,13 @@ -from typing import Literal +from typing import Any, Callable, Iterable, Literal, Optional -from openai.types.chat import ChatCompletionMessageParam +from liquid import Template +from openai.types.chat import ( + ChatCompletionAssistantMessageParam, + ChatCompletionMessageParam, + ChatCompletionMessageToolCallParam, + ChatCompletionSystemMessageParam, + ChatCompletionUserMessageParam, +) def truncate_messages_for_logging( @@ -71,3 +78,62 @@ def process_dict(dict_: dict, maximum_length: int, filler_text: str) -> dict: case dict(): dict_[key] = process_dict(value, maximum_length, filler_text) return dict_ + + +MessageFormatter = Callable[[str, dict[str, Any]], str] + + +def format_message(message: str, vars: dict[str, Any]) -> str: + """ + Format a message with the given variables using the Python format method. + """ + if message and vars: + for key, value in vars.items(): + try: + message = message.format(**{key: value}) + except KeyError: + pass + return message + + +def liquid_format(message: str, vars: dict[str, Any]) -> str: + """ + Format a message with the given variables using the Liquid template engine. + """ + out = message + if not message: + return message + template = Template(message) + out = template.render(**vars) + return out + + +def system_message( + content: str, var: dict[str, Any] | None = None, formatter: MessageFormatter = format_message +) -> ChatCompletionSystemMessageParam: + if var: + content = formatter(content, var) + return {"role": "system", "content": content} + + +def user_message( + content: str, var: dict[str, Any] | None = None, formatter: MessageFormatter = format_message +) -> ChatCompletionUserMessageParam: + if var: + content = formatter(content, var) + return {"role": "user", "content": content} + + +def assistant_message( + content: str, + refusal: Optional[str] = None, + tool_calls: Iterable[ChatCompletionMessageToolCallParam] | None = None, + var: dict[str, Any] | None = None, + formatter: MessageFormatter = format_message, +) -> ChatCompletionAssistantMessageParam: + if var: + content = formatter(content, var) + message = ChatCompletionAssistantMessageParam(role="assistant", content=content, refusal=refusal) + if tool_calls is not None: + message["tool_calls"] = tool_calls + return message diff --git a/libraries/python/openai-client/openai_client/tools.py b/libraries/python/openai-client/openai_client/tools.py new file mode 100644 index 00000000..05a06032 --- /dev/null +++ b/libraries/python/openai-client/openai_client/tools.py @@ -0,0 +1,161 @@ +import json +from typing import Any, Iterable + +from function_registry import FunctionRegistry +from openai import ( + AsyncAzureOpenAI, + AsyncOpenAI, + NotGiven, +) +from openai.types.chat import ( + ChatCompletionMessageParam, + ChatCompletionToolParam, + ParsedChatCompletion, + ParsedFunctionToolCall, +) + +from . import logger +from .completion import assistant_message_from_completion +from .errors import CompletionError, validate_completion +from .logging import extra_data, serializable_completion_args + + +async def execute_tool_call( + tool_call: ParsedFunctionToolCall, + function_registry: FunctionRegistry, +) -> ChatCompletionMessageParam | None: + """ + Execute a tool call function using a Function Registry and return the response as a message. + """ + function = tool_call.function + if function_registry.has_function(function.name): + logger.debug( + "Function call.", + extra=extra_data({"name": function.name, "arguments": function.arguments}), + ) + try: + kwargs: dict[str, Any] = json.loads(function.arguments) + value = await function_registry.execute_function_with_string_response(function.name, (), kwargs) + except Exception as e: + logger.error("Error.", extra=extra_data({"error": e})) + value = f"Error: {e}" + finally: + logger.debug("Function response.", extra=extra_data({"tool_call_id": tool_call.id, "content": value})) + return { + "role": "tool", + "content": value, + "tool_call_id": tool_call.id, + } + else: + logger.error(f"Function not found: {function.name}") + + +def function_registry_to_tools(function_registry: FunctionRegistry) -> Iterable[ChatCompletionToolParam] | NotGiven: + # Only the "functions" tool is available in the Chat API. + # https://platform.openai.com/docs/guides/function-calling + + # If the only tool is the default function registry help function, then + # we don't want to tell the chat response that we have any tools. + if function_registry.list_functions() == ["help"]: + return NotGiven() + + return [ + ChatCompletionToolParam(**{ + "type": "function", + "function": func.schema, + }) + for func in function_registry.get_functions() + ] + + +def tool_choice(functions: list[str] | None) -> Iterable[ChatCompletionToolParam] | None: + if not functions: + return None + return [ + ChatCompletionToolParam(**{ + "type": "function", + "function": {"name": name}, + }) + for name in functions + ] or None + + +async def complete_with_tool_calls( + async_client: AsyncOpenAI | AsyncAzureOpenAI, + function_registry: FunctionRegistry, + completion_args: dict[str, Any], + metadata: dict[str, Any] = {}, +) -> tuple[ParsedChatCompletion | None, list[ChatCompletionMessageParam]]: + """ + Complete a chat response with tool calls handled by Function Registry-registered functions. + + Parameters: + - async_client: The OpenAI client. + - function_registry: The function registry. + - completion_args: The completion arguments passed onto the OpenAI `parse` call. See the OpenAI API docs for more information. + - metadata: Metadata to be added to the completion response. + """ + # Pull out a reference to the completion args messages. + messages: list[ChatCompletionMessageParam] = completion_args.get("messages", []) + new_messages: list[ChatCompletionMessageParam] = [] + + # Completion call. + logger.debug("Completion call.", extra=extra_data(serializable_completion_args(completion_args))) + metadata["completion_args"] = serializable_completion_args(completion_args) + try: + completion = await async_client.beta.chat.completions.parse( + **completion_args, + ) + validate_completion(completion) + logger.debug("Completion response.", extra=extra_data({"completion": completion.model_dump()})) + metadata["completion"] = completion.model_dump() + except CompletionError as e: + completion_error = CompletionError(e) + metadata["completion_error"] = completion_error.message + logger.error(e.message, extra=extra_data({"completion_error": completion_error.body, "metadata": metadata})) + raise completion_error from e + + # Extract response and add to messages. + assistant_message = assistant_message_from_completion(completion) + if assistant_message: + new_messages.append(assistant_message) + + # If no tool calls, we're done. + completion_message = completion.choices[0].message + if not completion_message.tool_calls: + return completion, new_messages + + # Call all tool functions and generate return messages. + for tool_call in completion_message.tool_calls: + function_call_result_message = await execute_tool_call(tool_call, function_registry) + if function_call_result_message: + new_messages.append(function_call_result_message) + + # Completion call for final response. + final_args = {**completion_args, "messages": [*messages, *new_messages]} + del final_args["tools"] + del final_args["tool_choice"] + logger.debug("Tool completion call.", extra=extra_data(serializable_completion_args(final_args))) + metadata["tool_completion_args"] = serializable_completion_args(final_args) + try: + tool_completion = await async_client.beta.chat.completions.parse( + **final_args, + ) + validate_completion(tool_completion) + logger.debug("Tool completion response.", extra=extra_data({"completion": completion.model_dump()})) + metadata["completion"] = completion.model_dump() + except Exception as e: + tool_completion_error = CompletionError(e) + metadata["tool_completion_error"] = tool_completion_error.message + logger.error( + tool_completion_error.message, + extra=extra_data({"completion_error": tool_completion_error.body, "metadata": metadata}), + ) + raise tool_completion_error from e + + # Add assistant response to messages. + tool_completion_assistant_message = assistant_message_from_completion(tool_completion) + if tool_completion_assistant_message: + new_messages.append(tool_completion_assistant_message) + + return tool_completion, new_messages diff --git a/libraries/python/openai-client/pyproject.toml b/libraries/python/openai-client/pyproject.toml index f48f7e2e..9ad6c499 100644 --- a/libraries/python/openai-client/pyproject.toml +++ b/libraries/python/openai-client/pyproject.toml @@ -9,10 +9,12 @@ dependencies = [ "azure-ai-contentsafety>=1.0.0", "azure-core[aio]>=1.30.0", "azure-identity>=1.17.1", + "function-registry>=0.1.0", "openai>=1.3.9", "pillow>=11.0.0", - "tiktoken>=0.7.0", + "python-liquid>=1.12.1", "semantic-workbench-assistant>=0.1.0", + "tiktoken>=0.7.0", ] [tool.uv] @@ -21,6 +23,7 @@ dev-dependencies = ["pytest>=8.3.3"] [tool.uv.sources] semantic-workbench-assistant = { path = "../semantic-workbench-assistant", editable = true } +function-registry = { path = "../function-registry", editable = true } [build-system] requires = ["hatchling"] diff --git a/libraries/python/openai-client/uv.lock b/libraries/python/openai-client/uv.lock index 9d382c85..17124e1a 100644 --- a/libraries/python/openai-client/uv.lock +++ 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+[package.metadata] +requires-dist = [ + { name = "azure-identity", specifier = ">=1.17.1" }, + { name = "context", editable = "../context" }, + { name = "openai", specifier = ">=1.16.1" }, + { name = "pydantic", specifier = ">=2.6.1" }, + { name = "pydantic-settings", specifier = ">=2.3.4" }, + { name = "python-dotenv", specifier = ">=1.0.1" }, + { name = "requests", specifier = ">=2.32.0" }, + { name = "tiktoken", specifier = ">=0.7.0" }, +] + +[package.metadata.requires-dev] +dev = [ + { name = "pytest", specifier = ">=8.3.1" }, + { name = "pytest-asyncio", specifier = ">=0.23.8" }, + { name = "pytest-repeat", specifier = ">=0.9.3" }, +] + [[package]] name = "h11" version = "0.14.0" @@ -520,6 +583,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442 }, ] +[[package]] +name = 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-758,8 +832,10 @@ requires-dist = [ { name = "azure-ai-contentsafety", specifier = ">=1.0.0" }, { name = "azure-core", extras = ["aio"], specifier = ">=1.30.0" }, { name = "azure-identity", specifier = ">=1.17.1" }, + { name = "function-registry", editable = "../function-registry" }, { name = "openai", specifier = ">=1.3.9" }, { name = "pillow", specifier = ">=11.0.0" }, + { name = "python-liquid", specifier = ">=1.12.1" }, { name = "semantic-workbench-assistant", editable = "../semantic-workbench-assistant" }, { name = "tiktoken", specifier = ">=0.7.0" }, ] @@ -967,6 +1043,18 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/6b/77/7440a06a8ead44c7757a64362dd22df5760f9b12dc5f11b6188cd2fc27a0/pytest-8.3.3-py3-none-any.whl", hash = "sha256:a6853c7375b2663155079443d2e45de913a911a11d669df02a50814944db57b2", size = 342341 }, ] +[[package]] +name = "python-dateutil" +version = "2.9.0.post0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "six" }, 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+dependencies = [ + { name = "importlib-resources" }, + { name = "python-dateutil" }, + { name = "typing-extensions" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/59/b4/c4e39470edf507056333cd688a36bb7fbdb17090105d9f454ecf6ff09845/python_liquid-1.12.1.tar.gz", hash = "sha256:7367e979125859fb4116f360f224a89a52ecb455fb26843c43e4d800b389d325", size = 124636 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/2c/6e/bfd01926e28f6cf355a7a8460271ba135013870f5857b06f35dbf65ab237/python_liquid-1.12.1-py3-none-any.whl", hash = "sha256:2224312944be16c1a44406398eb8a07c7e57398d5c0ef15ff950946dbefe7c33", size = 206592 }, +] + [[package]] name = "python-multipart" version = "0.0.12" diff --git a/libraries/python/skills/notebooks/uv.lock b/libraries/python/skills/notebooks/uv.lock index 51e9cdd2..ee75007c 100644 --- a/libraries/python/skills/notebooks/uv.lock +++ b/libraries/python/skills/notebooks/uv.lock @@ -336,6 +336,7 @@ dependencies = [ { name = "events" }, { name = 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