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".assistant", + drive_root=drive_root or Path(".data") / assistant_id / "assistant", + metadata_drive_root=metadata_drive_root or Path(".data") / assistant_id / ".assistant", chat_driver_config=chat_driver_config, skills=skills, ) diff --git a/assistants/skill-assistant/assistant/skill_assistant.py b/assistants/skill-assistant/assistant/skill_assistant.py index f81a0c54..93ddedef 100644 --- a/assistants/skill-assistant/assistant/skill_assistant.py +++ b/assistants/skill-assistant/assistant/skill_assistant.py @@ -12,6 +12,7 @@ from typing import Any, Optional import openai_client +from assistant_drive import Drive, DriveConfig from content_safety.evaluators import CombinedContentSafetyEvaluator from form_filler_skill import FormFillerSkill from form_filler_skill.guided_conversation import GuidedConversationSkill @@ -174,7 +175,11 @@ async def respond_to_conversation( await conversation_context.update_participant_me(UpdateParticipant(status="thinking...")) # Get an assistant from the skill library. - assistant = assistant_registry.get_assistant(conversation_context.id) + assistant_id = conversation_context.id + assistant = assistant_registry.get_assistant(assistant_id) + drive_root = Path(".data") / assistant_id / "assistant" + metadata_drive_root = Path(".data") / assistant_id / ".assistant" + drive = Drive(DriveConfig(root=drive_root)) # Create and register an assistant if necessary. if not assistant: @@ -191,19 +196,25 @@ async def respond_to_conversation( chat_driver_config, { "posix": PosixSkill( + name="posix", sandbox_dir=Path(".data") / conversation_context.id, chat_driver_config=chat_driver_config, mount_dir="/mnt/data", ), "form_filler": FormFillerSkill( + name="form_filler", chat_driver_config=chat_driver_config, language_model=language_model, ), "guided_conversation": GuidedConversationSkill( - chat_driver_config=chat_driver_config, + name="guided_conversation", language_model=language_model, + drive=drive.subdrive("guided_conversation"), + chat_driver_config=chat_driver_config, ), }, + drive_root=drive_root, + metadata_drive_root=metadata_drive_root, ) except Exception as e: diff --git a/assistants/skill-assistant/uv.lock b/assistants/skill-assistant/uv.lock index b684af43..cfc2b3b3 100644 --- a/assistants/skill-assistant/uv.lock +++ b/assistants/skill-assistant/uv.lock @@ -1,8 +1,10 @@ version = 1 requires-python = ">=3.11" resolution-markers = [ - "python_full_version < '3.13'", - "python_full_version >= '3.13'", + "python_full_version < '3.12'", + "python_full_version == '3.12.*'", + "python_full_version >= '4.0'", + "python_full_version >= '3.13' and python_full_version < '4.0'", ] [[package]] @@ -109,6 +111,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/e4/f5/f2b75d2fc6f1a260f340f0e7c6a060f4dd2961cc16884ed851b0d18da06a/anyio-4.6.2.post1-py3-none-any.whl", hash = "sha256:6d170c36fba3bdd840c73d3868c1e777e33676a69c3a72cf0a0d5d6d8009b61d", size = 90377 }, ] +[[package]] +name = "argcomplete" +version 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"https://files.pythonhosted.org/packages/df/e4/ba44652d562cbf0bf320e0f3810206149c8a4e99cdbf66da82e97ab53a15/pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12", size = 434928 }, ] +[package.optional-dependencies] +email = [ + { name = "email-validator", marker = "python_full_version < '4.0'" }, +] + [[package]] name = "pydantic-core" version = "2.23.4" diff --git a/libraries/python/assistant-drive/assistant_drive/drive.py b/libraries/python/assistant-drive/assistant_drive/drive.py index fede8f30..e8239a75 100644 --- a/libraries/python/assistant-drive/assistant_drive/drive.py +++ b/libraries/python/assistant-drive/assistant_drive/drive.py @@ -26,7 +26,7 @@ class IfDriveFileExistsBehavior(StrEnum): class DriveConfig(BaseModel): root: str | PathLike - default_if_exists_behavior: IfDriveFileExistsBehavior = IfDriveFileExistsBehavior.AUTO_RENAME + default_if_exists_behavior: IfDriveFileExistsBehavior = IfDriveFileExistsBehavior.OVERWRITE class FileMetadata: diff --git a/libraries/python/assistant-drive/assistant_drive/tests/test_basic.py b/libraries/python/assistant-drive/assistant_drive/tests/test_basic.py index 6fa59db0..ddc3b19a 100644 --- a/libraries/python/assistant-drive/assistant_drive/tests/test_basic.py +++ b/libraries/python/assistant-drive/assistant_drive/tests/test_basic.py @@ -91,7 +91,7 @@ def test_open_non_existent_file(drive): def test_auto_rename(drive, if_exists=IfDriveFileExistsBehavior.AUTO_RENAME): drive.write(file_content, "test.txt", "summaries") - metadata = drive.write(file_content, "test.txt", "summaries") + metadata = drive.write(file_content, "test.txt", "summaries", if_exists=IfDriveFileExistsBehavior.AUTO_RENAME) assert metadata.filename == "test(1).txt" assert sorted(list(drive.list(dir="summaries"))) == sorted(["test.txt", "test(1).txt"]) diff --git a/libraries/python/context/pyproject.toml b/libraries/python/context/pyproject.toml index 71ce78d1..ca1548b2 100644 --- a/libraries/python/context/pyproject.toml +++ b/libraries/python/context/pyproject.toml @@ -23,3 +23,12 @@ events = { path = "../events", editable = true } [build-system] requires = ["hatchling"] build-backend = "hatchling.build" + +[tool.pytest.ini_options] +addopts = "-vv" +log_cli = true +log_cli_level = "WARNING" +log_cli_format = "%(asctime)s | %(levelname)-7s | %(name)s | %(message)s" +testpaths = ["tests"] +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" \ No newline at end of file diff --git a/libraries/python/skills/notebooks/notebooks/chat_driver.ipynb b/libraries/python/skills/notebooks/notebooks/chat_driver.ipynb index 569df7f0..4890e130 100644 --- a/libraries/python/skills/notebooks/notebooks/chat_driver.ipynb +++ b/libraries/python/skills/notebooks/notebooks/chat_driver.ipynb @@ -141,7 +141,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -149,7 +149,7 @@ "output_type": "stream", "text": [ "{\n", - " \"id\": \"chatcmpl-ASsXCOPTQYPT3ZLEzdoXzYpfPDLIi\",\n", + " \"id\": \"chatcmpl-AWSTEn1cZqu47WD3TU0R1cTQQjWCQ\",\n", " \"choices\": [\n", " {\n", " \"finish_reason\": \"stop\",\n", @@ -164,7 +164,7 @@ " }\n", " }\n", " ],\n", - " \"created\": 1731446178,\n", + " \"created\": 1732299300,\n", " \"model\": \"gpt-4o-2024-08-06\",\n", " \"object\": \"chat.completion\",\n", " \"service_tier\": null,\n", @@ -235,20 +235,18 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'id': 'chatcmpl-AQgaEhy4ed19h72VpBu8nJBJE3g3L', 'choices': [{'delta': {'content': '', 'function_call': None, 'refusal': None, 'role': 'assistant', 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1730923582, 'model': 'gpt-4o-2024-08-06', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': 'fp_d54531d9eb', 'usage': None}\n", - "{'id': 'chatcmpl-AQgaEhy4ed19h72VpBu8nJBJE3g3L', 'choices': [{'delta': {'content': 'This', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1730923582, 'model': 'gpt-4o-2024-08-06', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': 'fp_d54531d9eb', 'usage': None}\n", - "{'id': 'chatcmpl-AQgaEhy4ed19h72VpBu8nJBJE3g3L', 'choices': [{'delta': {'content': ' is', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1730923582, 'model': 'gpt-4o-2024-08-06', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': 'fp_d54531d9eb', 'usage': None}\n", - "{'id': 'chatcmpl-AQgaEhy4ed19h72VpBu8nJBJE3g3L', 'choices': [{'delta': {'content': ' a', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1730923582, 'model': 'gpt-4o-2024-08-06', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': 'fp_d54531d9eb', 'usage': None}\n", - "{'id': 'chatcmpl-AQgaEhy4ed19h72VpBu8nJBJE3g3L', 'choices': [{'delta': {'content': ' test', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1730923582, 'model': 'gpt-4o-2024-08-06', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': 'fp_d54531d9eb', 'usage': None}\n", - "{'id': 'chatcmpl-AQgaEhy4ed19h72VpBu8nJBJE3g3L', 'choices': [{'delta': {'content': '.', 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': None, 'index': 0, 'logprobs': None}], 'created': 1730923582, 'model': 'gpt-4o-2024-08-06', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': 'fp_d54531d9eb', 'usage': None}\n", - "{'id': 'chatcmpl-AQgaEhy4ed19h72VpBu8nJBJE3g3L', 'choices': [{'delta': {'content': None, 'function_call': None, 'refusal': None, 'role': None, 'tool_calls': None}, 'finish_reason': 'stop', 'index': 0, 'logprobs': None}], 'created': 1730923582, 'model': 'gpt-4o-2024-08-06', 'object': 'chat.completion.chunk', 'service_tier': None, 'system_fingerprint': 'fp_d54531d9eb', 'usage': None}\n" + "ename": "NameError", + "evalue": "name 'async_client' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m stream \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m \u001b[43masync_client\u001b[49m\u001b[38;5;241m.\u001b[39mchat\u001b[38;5;241m.\u001b[39mcompletions\u001b[38;5;241m.\u001b[39mcreate(\n\u001b[1;32m 2\u001b[0m messages\u001b[38;5;241m=\u001b[39m[\n\u001b[1;32m 3\u001b[0m {\n\u001b[1;32m 4\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrole\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muser\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 5\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSay this is a test\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 6\u001b[0m }\n\u001b[1;32m 7\u001b[0m ],\n\u001b[1;32m 8\u001b[0m model\u001b[38;5;241m=\u001b[39mmodel,\n\u001b[1;32m 9\u001b[0m stream\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 10\u001b[0m )\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mfor\u001b[39;00m chunk \u001b[38;5;129;01min\u001b[39;00m stream:\n\u001b[1;32m 12\u001b[0m \u001b[38;5;28mprint\u001b[39m(chunk\u001b[38;5;241m.\u001b[39mmodel_dump())\n", + "\u001b[0;31mNameError\u001b[0m: name 'async_client' is not defined" ] } ], @@ -283,7 +281,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -382,7 +380,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -390,8 +388,8 @@ "output_type": "stream", "text": [ "{\n", - " \"thoughts\": \"The future of AI is expected to be dynamic and transformative, impacting various sectors from healthcare to education. There is potential for AI to enhance productivity, improve decision-making, and create more personalized experiences.\",\n", - " \"answer\": \"AI is likely to become more integrated into everyday life, leading to smarter cities, more efficient industries, and advances in fields such as medicine and autonomous systems. Ethical considerations will be crucial as AI becomes more powerful, and there will be ongoing discussions about privacy, bias, and the job market. Overall, the future of AI promises significant benefits if its development is guided responsibly.\"\n", + " \"thoughts\": \"AI has been advancing rapidly, impacting various industries and society as a whole. The future will likely see even more profound changes as AI technologies continue to evolve.\",\n", + " \"answer\": \"The future of AI holds numerous possibilities, such as enhanced automation, improved decision-making processes, and personalization across various sectors like healthcare, finance, and transportation. We may also witness the development of more sophisticated natural language processing and AI systems that can better understand and act upon human emotions. However, this future will also require addressing ethical and privacy concerns, as well as rethinking workforce dynamics due to potential job displacement.\"\n", "}\n" ] } @@ -444,7 +442,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -452,8 +450,8 @@ "output_type": "stream", "text": [ "{\n", - " \"thoughts\": \"AI is already having a profound impact across various sectors, and its influence will only grow in the future as technologies continue to advance. We are likely to see significant developments in AI applications, enhanced human-AI collaboration, and ethical considerations around the technology's usage.\",\n", - " \"answer\": \"The future of AI holds tremendous potential to revolutionize how we live, work, and interact. In the coming years, we can expect AI to become increasingly integrated into our daily lives through smarter personal assistants, more efficient business processes, and advancements in healthcare, transportation, and communication technologies. AI will enable more personalized and anticipatory services, where systems proactively assist users based on their preferences and behaviors.\\n\\nFurthermore, AI will drive innovation by augmenting human capabilities, allowing us to tackle complex problems with greater efficiency. This collaboration between humans and machines could lead to breakthroughs in fields like medicine, environmental science, and education.\\n\\nHowever, with these opportunities come challenges. Ethical considerations, such as bias, privacy concerns, and the impact on employment, must be addressed. Developers and policymakers will need to work together to create guidelines and standards that ensure AI technologies are used responsibly and inclusively.\\n\\nAdditionally, explainability and transparency in AI systems will become increasingly important, as stakeholders will demand to understand how these technologies make decisions that affect them.\\n\\nOverall, the future of AI is bright and full of potential, but it requires a careful balancing act to ensure it benefits society as a whole.\"\n", + " \"thoughts\": \"As I consider the possibilities, I see AI evolving to become more seamlessly integrated into our daily lives, potentially transforming industries like healthcare, transportation, and education in significant ways.\",\n", + " \"answer\": \"The future of AI promises to bring advancements that will help us solve complex problems and push the boundaries of what is currently possible. We can expect AI to become more adaptive, explainable, and ethical, with systems that not only increase efficiency and productivity but also enhance human capabilities and decision-making processes. As we move forward, it will be crucial to guide AI's development with robust ethical standards and regulations to ensure it benefits society as a whole. The potential for AI to improve personalized medicine, autonomous vehicles, and environmental sustainability, among other areas, is vast—all while maintaining a focus on preserving human values and privacy.\"\n", "}\n" ] } diff --git a/libraries/python/skills/skill-library/pyproject.toml b/libraries/python/skills/skill-library/pyproject.toml index 3662f6c5..414d4a79 100644 --- a/libraries/python/skills/skill-library/pyproject.toml +++ b/libraries/python/skills/skill-library/pyproject.toml @@ -36,3 +36,12 @@ openai-client = { path = "../../openai-client", editable = true } [build-system] requires = ["hatchling"] build-backend = "hatchling.build" + +[tool.pytest.ini_options] +addopts = "-vv" +log_cli = true +log_cli_level = "WARNING" +log_cli_format = "%(asctime)s | %(levelname)-7s | %(name)s | %(message)s" +testpaths = ["tests"] +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" \ No newline at end of file diff --git a/libraries/python/skills/skill-library/skill_library/assistant.py b/libraries/python/skills/skill-library/skill_library/assistant.py index 7c3793ea..032a3a43 100644 --- a/libraries/python/skills/skill-library/skill_library/assistant.py +++ b/libraries/python/skills/skill-library/skill_library/assistant.py @@ -35,6 +35,7 @@ def __init__( metadata_drive_root: PathLike | None = None, skills: dict[str, Skill] | None = None, startup_action: str | None = None, + startup_routine: str | None = None, ) -> None: # Do we ever use this? No. We don't. It just seems like it would be a # good idea, though. @@ -43,17 +44,6 @@ def __init__( # This, though, we use. self.assistant_id = assistant_id or str(uuid4()) - # The routine stack is used to keep track of the current routine being - # run by the assistant. - self.routine_stack = RoutineStack(self.metadrive) - - # Register all skills for the assistant. - self.skill_registry = SkillRegistry(skills, self.routine_stack) if skills else None - - # Set up the assistant event queue. - self._event_queue = asyncio.Queue() # Async queue for events - self._stopped = asyncio.Event() # Event to signal when the assistant has stopped - # A metadrive to be used for managing assistant metadata. This can be # useful for storing session data, logs, and other information that # needs to be persisted across different calls to the assistant. This is @@ -65,6 +55,28 @@ def __init__( ) ) + # The routine stack is used to keep track of the current routine being + # run by the assistant. + self.routine_stack = RoutineStack(self.metadrive) + + # Register all skills for the assistant. + self.skill_registry = SkillRegistry(skills, self.routine_stack) if skills else None + + # If a skill registry is provided, use it to run routines. Otherwise, + # raise an error if someone tries to run a routine. + if self.skill_registry: + self.run_routine = self.skill_registry.run_routine_by_designation + else: + + async def run_routine(context: RunContext, name: str, vars: dict[str, Any] | None) -> None: + raise ValueError("No skill registry registered for this assistant.") + + self.run_routine = run_routine + + # Set up the assistant event queue. + self._event_queue = asyncio.Queue() # Async queue for events + self._stopped = asyncio.Event() # Event to signal when the assistant has stopped + # The assistant drive is used as the storage bucket for all assistant # and skill data. Skills will generally create a subdrive off of this # drive. @@ -82,10 +94,33 @@ def __init__( ) self.chat_driver = self._register_chat_driver(chat_driver_config) + self.startup_action = startup_action + self.startup_routine = startup_routine + + async def clear(self) -> None: + """Clears the assistant's routine stack and event queue.""" + await self.routine_stack.clear() + while not self._event_queue.empty(): + self._event_queue.get_nowait() + self.metadrive.delete() + self.drive.delete() + ###################################### # Lifecycle and event handling ###################################### + async def start(self) -> None: + """Start the assistant.""" + self._stopped.clear() + + # If a startup action is provided, run it. + if self.startup_action: + await self.run_action(self.startup_action) + + # If a startup routine is provided, run it. + if self.startup_routine: + await self.run_routine(self.startup_routine) + async def wait(self) -> str: """ After initializing an assistant, call this method to wait for assistant @@ -122,11 +157,12 @@ def create_run_context(self) -> RunContext: # actions, and chat driver functions) that need to be able to run # routines or actions, set assistant state, or emit messages from the # assistant. + return RunContext( session_id=self.assistant_id, assistant_drive=self.drive, emit=self._emit, - run_routine=self.skill_registry.run_routine_by_designation if self.skill_registry else None, + run_routine=self.run_routine, routine_stack=self.routine_stack, ) diff --git a/libraries/python/skills/skill-library/skill_library/routine_runners/state_machine_routine_runner.py b/libraries/python/skills/skill-library/skill_library/routine_runners/state_machine_routine_runner.py index 76c47c5e..2077ad90 100644 --- a/libraries/python/skills/skill-library/skill_library/routine_runners/state_machine_routine_runner.py +++ b/libraries/python/skills/skill-library/skill_library/routine_runners/state_machine_routine_runner.py @@ -9,10 +9,10 @@ def __init__(self) -> None: pass async def run(self, context: RunContext, routine: StateMachineRoutine, vars: dict[str, Any] | None = None) -> Any: - routine.init_function(context, vars) + await routine.init_function(context, vars) async def next(self, context: RunContext, routine: StateMachineRoutine, message: str) -> Any: """ Run the next step in the current routine. """ - routine.step_function(context, message) + await routine.step_function(context, message) diff --git a/libraries/python/skills/skill-library/skill_library/skill.py b/libraries/python/skills/skill-library/skill_library/skill.py index ef25e0c8..a9060f06 100644 --- a/libraries/python/skills/skill-library/skill_library/skill.py +++ b/libraries/python/skills/skill-library/skill_library/skill.py @@ -102,7 +102,7 @@ def get_routine(self, name: str) -> RoutineTypes | None: """ Get a routine by name. """ - return self.routines[name] + return self.routines.get(name) def list_routines(self) -> list[str]: return [str(routine) for routine in self.routines.values()] diff --git a/libraries/python/skills/skill-library/skill_library/skill_registry.py b/libraries/python/skills/skill-library/skill_library/skill_registry.py index 096ab1d9..13c93459 100644 --- a/libraries/python/skills/skill-library/skill_library/skill_registry.py +++ b/libraries/python/skills/skill-library/skill_library/skill_registry.py @@ -20,7 +20,7 @@ def __init__(self, skills: dict[str, Skill], routine_stack: RoutineStack) -> Non self.skills = skills self.routine_stack = routine_stack - def get_skill(self, skill_name) -> Skill | None: + def get_skill(self, skill_name: str) -> Skill | None: return self.skills.get(skill_name) def list_actions(self) -> list[str]: @@ -55,11 +55,11 @@ def get_routine(self, designation: str) -> RoutineTypes | None: """ Get a routine by . designation. """ - skill_name, routine = designation.split(".") + skill_name, routine_name = designation.split(".") skill = self.get_skill(skill_name) if not skill: return None - return skill.get_routine(routine) + return skill.get_routine(routine_name) async def run_routine_by_designation( self, context: RunContext, designation: str, vars: dict[str, Any] | None = None diff --git a/libraries/python/skills/skills/form-filler-skill/.vscode/settings.json b/libraries/python/skills/skills/form-filler-skill/.vscode/settings.json index 7177a8e5..2891bc84 100644 --- a/libraries/python/skills/skills/form-filler-skill/.vscode/settings.json +++ b/libraries/python/skills/skills/form-filler-skill/.vscode/settings.json @@ -53,5 +53,8 @@ "pypdf", "runtimes", "tiktoken" - ] + ], + "python.testing.pytestArgs": ["."], + "python.testing.unittestEnabled": false, + "python.testing.pytestEnabled": true } diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/form_filler_skill.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/form_filler_skill.py index 5c563d29..3f57d758 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/form_filler_skill.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/form_filler_skill.py @@ -5,7 +5,6 @@ from skill_library.run_context import RunContext from skill_library.types import LanguageModel -NAME = "form-filler" CLASS_NAME = "FormFillerSkill" DESCRIPTION = "Walks the user through uploading and filling out a form." DEFAULT_MAX_RETRIES = 3 @@ -15,6 +14,7 @@ class FormFillerSkill(Skill): def __init__( self, + name: str, chat_driver_config: ChatDriverConfig, language_model: LanguageModel, ) -> None: @@ -39,7 +39,7 @@ def __init__( # Initialize the skill! super().__init__( - name=NAME, + name=name, description=DESCRIPTION, chat_driver_config=chat_driver_config, actions=functions, diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/__init__.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/__init__.py index 7a004fcc..4aa31539 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/__init__.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/__init__.py @@ -1,5 +1,8 @@ +from .artifact_helpers import UNANSWERED, TUnanswered from .guided_conversation_skill import GuidedConversationSkill __all__ = [ "GuidedConversationSkill", + "TUnanswered", + "UNANSWERED", ] diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/agenda.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/agenda.py index 64e0189b..3dab7f7e 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/agenda.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/agenda.py @@ -1,21 +1,16 @@ -import logging +from pydantic import BaseModel, Field -from pydantic import Field - -from form_filler_skill.guided_conversation.chat_drivers.unneeded.base_model_llm import BaseModelLLM from form_filler_skill.guided_conversation.resources import ( ResourceConstraintMode, ) -logger = logging.getLogger(__name__) - -class AgendaItem(BaseModelLLM): +class AgendaItem(BaseModel): title: str = Field(description="Brief description of the item") resource: int = Field(description="Number of turns required for the item") -class Agenda(BaseModelLLM): +class Agenda(BaseModel): resource_constraint_mode: ResourceConstraintMode | None = Field(default=None) items: list[AgendaItem] = Field( description="Ordered list of items to be completed in the remainder of the conversation", diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/artifact.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/artifact.py deleted file mode 100644 index a565d082..00000000 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/artifact.py +++ /dev/null @@ -1,278 +0,0 @@ -# Copyright (c) Microsoft. All rights reserved. - - -import json -import logging -from typing import Any, Literal, TypeVar, Union, get_args, get_origin, get_type_hints - -from pydantic import BaseModel, create_model - -from form_filler_skill.guided_conversation.chat_drivers.unneeded.base_model_llm import BaseModelLLM - -from .message import ConversationMessageType, Message - -logger = logging.getLogger(__name__) - - -class Artifact: - """The Artifact plugin takes in a Pydantic base model, and robustly handles updating the fields of the model - A typical use case is as a form an agent must complete throughout a conversation. - Another use case is as a working memory for the agent. - - The primary interface is update_artifact, which takes in the field_name to update and its new value. - Additionally, the chat_history is passed in to help the agent make informed decisions in case an error occurs. - - The Artifact also exposes several functions to access internal state: - get_artifact_for_prompt, get_schema_for_prompt, and get_failed_fields. - """ - - def __init__( - self, - input_artifact: BaseModel, - max_artifact_field_retries: int = 2, - ) -> None: - """ - Initialize the Artifact plugin with the given Pydantic base model. - - Args: - input_artifact (BaseModel): The Pydantic base model to use as the artifact - max_artifact_field_retries (int): The maximum number of times to retry updating a field in the artifact - """ - - self.max_artifact_field_retries = max_artifact_field_retries - - self.original_schema = input_artifact.model_json_schema() - - # Create a new artifact model based on the one provided by the user with - # "Unanswered" set for all fields. - modified_classes = self._modify_classes(input_artifact) - self.artifact = self._modify_base_artifact(input_artifact, modified_classes)() - - # failed_artifact_fields maps a field name to a list of the history of - # the failed attempts to update it. - # dict: key = field, value = list of tuple[attempt, error message] - self.failed_artifact_fields: dict[str, list[tuple[str, str]]] = {} - - def get_artifact_for_prompt(self) -> str: - """ - Returns a formatted JSON-like representation of the current state of the - fields artifact. Any fields that were failed are completely omitted. - """ - failed_fields = self.get_failed_fields() - return json.dumps({k: v for k, v in self.artifact.model_dump().items() if k not in failed_fields}) - - def get_schema_for_prompt(self, filter_one_field: str | None = None) -> str: - """Gets a clean version of the original artifact schema, optimized for use in an LLM prompt. - - Args: - filter_one_field (str | None): If this is provided, only the schema for this one field will be returned. - - Returns: - str: The cleaned schema - """ - - def _clean_properties(schema: dict, failed_fields: list[str]) -> str: - properties = schema.get("properties", {}) - clean_properties = {} - for name, property_dict in properties.items(): - if name not in failed_fields: - cleaned_property = {} - for k, v in property_dict.items(): - if k in ["title", "default"]: - continue - cleaned_property[k] = v - clean_properties[name] = cleaned_property - - clean_properties_str = str(clean_properties) - clean_properties_str = clean_properties_str.replace("$ref", "type") - clean_properties_str = clean_properties_str.replace("#/$defs/", "") - return clean_properties_str - - # If filter_one_field is provided, only get the schema for that one field - if filter_one_field: - if not self._is_valid_field(filter_one_field): - logger.error(f'Field "{filter_one_field}" is not a valid field in the artifact.') - raise ValueError(f'Field "{filter_one_field}" is not a valid field in the artifact.') - filtered_schema = {"properties": {filter_one_field: self.original_schema["properties"][filter_one_field]}} - filtered_schema.update((k, v) for k, v in self.original_schema.items() if k != "properties") - schema = filtered_schema - else: - schema = self.original_schema - - failed_fields = self.get_failed_fields() - properties = _clean_properties(schema, failed_fields) - if not properties: - logger.error("No properties found in the schema.") - raise ValueError("No properties found in the schema.") - - types_schema = schema.get("$defs", {}) - custom_types = [] - for type_name, type_info in types_schema.items(): - if f"'type': '{type_name}'" in properties: - clean_schema = _clean_properties(type_info, []) - if clean_schema != "{}": - custom_types.append(f"{type_name} = {clean_schema}") - - if custom_types: - explanation = ( - f"If you wanted to create a {type_name} object, for example, you " - "would make a JSON object with the following keys: " - "{', '.join(types_schema[type_name]['properties'].keys())}." - ) - custom_types_str = "\n".join(custom_types) - return ( - f"{properties}\n\n" - "Here are the definitions for the custom types referenced in the artifact schema:\n" - f"{custom_types_str}\n\n" - f"{explanation}\n" - "Remember that when updating the artifact, the field will be the original " - "field name in the artifact and the JSON object(s) will be the value." - ) - else: - return properties - - def get_failed_fields(self) -> list[str]: - """Get a list of fields that have failed all attempts to update. - - Returns: - list[str]: A list of field names that have failed all attempts to update. - """ - fields = [] - for field, attempts in self.failed_artifact_fields.items(): - if len(attempts) >= self.max_artifact_field_retries: - fields.append(field) - return fields - - T = TypeVar("T") - - def _get_type_if_subtype(self, target_type: type[T], base_type: type[Any]) -> type[T] | None: - """ - Recursively checks the target_type to see if it is a subclass of - base_type or a generic including base_type. - - Args: - target_type: The type to check. - base_type: The type to check against. - - Returns: - The class type if target_type is base_type, a subclass of base_type, - or a generic including base_type; otherwise, None. - """ - origin = get_origin(target_type) - if origin is None: - if issubclass(target_type, base_type): - return target_type - else: - # Recursively check if any of the arguments are the target type. - for arg in get_args(target_type): - result = self._get_type_if_subtype(arg, base_type) - if result is not None: - return result - return None - - def _modify_classes(self, artifact_class: BaseModel) -> dict[str, type[BaseModelLLM]]: - """Find all classes used as type hints in the artifact, and modify them to set 'Unanswered' as a default and valid value for all fields.""" - modified_classes = {} - # Find any instances of BaseModel in the artifact class in the first "level" of type hints - for field_name, field_type in get_type_hints(artifact_class).items(): - is_base_model = self._get_type_if_subtype(field_type, BaseModel) - if is_base_model is not None: - modified_classes[field_name] = self._modify_base_artifact(is_base_model) - - return modified_classes - - def _replace_type_annotations( - self, field_annotation: type[Any] | None, modified_classes: dict[str, type[BaseModelLLM]] - ) -> type: - """ - Recursively replace type annotations with modified classes where - applicable. - """ - # Get the origin of the field annotation, which is the base type for - # generic types (e.g., List[str] -> list, Dict[str, int] -> dict) - origin = get_origin(field_annotation) - - # Get the type arguments of the generic type (e.g., List[str] -> str, - # Dict[str, int] -> str, int) - args = get_args(field_annotation) - - if origin is None: - # The type is not generic; check if it's a subclass that needs to be replaced - if isinstance(field_annotation, type) and issubclass(field_annotation, BaseModelLLM): - return modified_classes.get(field_annotation.__name__, field_annotation) - return field_annotation if field_annotation is not None else object - else: - # The type is generic; recursively replace the type annotations of the arguments - new_args = tuple(self._replace_type_annotations(arg, modified_classes) for arg in args) - return origin[new_args] - - def _modify_base_artifact( - self, - artifact_model: BaseModel, - modified_classes: dict[str, type[BaseModelLLM]] | None = None, - ) -> type[BaseModelLLM]: - """ - Create a new artifact model with 'Unanswered' as a default and valid - value for all fields. - """ - field_definitions = {} - for name, field_info in artifact_model.model_fields.items(): - # Replace original classes with modified version. - if modified_classes is not None: - field_info.annotation = self._replace_type_annotations(field_info.annotation, modified_classes) - - # This makes it possible to always set a field to "Unanswered". - annotation = Union[field_info.annotation, Literal["Unanswered"]] - - # This sets the default value to "Unanswered". - default = "Unanswered" - - # This adds "Unanswered" as a possible value to any regex patterns. - metadata = field_info.metadata - for m in metadata: - if hasattr(m, "pattern"): - m.pattern += "|Unanswered" - - field_definitions[name] = (annotation, default, *metadata) - - return create_model("Artifact", __base__=BaseModelLLM, **field_definitions) - - def _is_valid_field(self, field_name: str) -> tuple[bool, Message | None]: - """ - Check if the field_name is a valid field in the artifact. Returns True - if it is, False and an error message otherwise. - """ - if field_name not in self.artifact.model_fields: - error_message = f'Field "{field_name}" is not a valid field in the artifact.' - msg = Message( - {"role": "assistant", "content": error_message}, - type=ConversationMessageType.ARTIFACT_UPDATE, - turn=None, - ) - return False, msg - return True, None - - def to_json(self) -> dict: - artifact_fields = self.artifact.model_dump() - return { - "artifact": artifact_fields, - "failed_fields": self.failed_artifact_fields, - } - - @classmethod - def from_json( - cls, - json_data: dict, - input_artifact: BaseModel, - max_artifact_field_retries: int = 2, - ) -> "Artifact": - artifact = cls(input_artifact, max_artifact_field_retries) - - artifact.failed_artifact_fields = json_data["failed_fields"] - - # Iterate over artifact fields and set them to the values in the json data - # Skip any fields that are set as "Unanswered" - for field_name, field_value in json_data["artifact"].items(): - if field_value != "Unanswered": - setattr(artifact.artifact, field_name, field_value) - return artifact diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/artifact_helpers.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/artifact_helpers.py new file mode 100644 index 00000000..388e2be6 --- /dev/null +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/artifact_helpers.py @@ -0,0 +1,224 @@ +import json +from typing import Any, Literal, Union, get_args, get_origin, get_type_hints + +from pydantic import BaseModel, create_model + +from .logging import logger +from .message import ConversationMessageType, Message + +UNANSWERED = "Unanswered" + +TUnanswered = Literal["Unanswered"] + + +def modify_model_fields_to_allow_unanswered( + model: type[BaseModel], +) -> type[BaseModel]: + """ + Create a new artifact model with 'Unanswered' as a default and valid + value for all fields. + """ + field_definitions = {} + for name, field_info in model.model_fields.items(): + annotation = Union[field_info.annotation, TUnanswered] + default = UNANSWERED + + # Add UNANSWERED as a possible value to any regex patterns. + metadata = field_info.metadata + for m in metadata: + if hasattr(m, "pattern"): + m.pattern += f"|{UNANSWERED}" + + field_definitions[name] = (annotation, default, *metadata) + + return create_model(model.__name__, __base__=BaseModel, **field_definitions) + + +def is_pydantic_model(type_hint): + """Check if a type hint refers to a subclass of Pydantic's BaseModel.""" + # Handle generic types like list[str] + origin = get_origin(type_hint) + if origin is not None: + # If it's a generic type, its origin might not be BaseModel + return issubclass(origin, BaseModel) if isinstance(origin, type) else False + + # Handle non-generic types + return isinstance(type_hint, type) and issubclass(type_hint, BaseModel) + + +def make_modified_pydantic_field_classes(artifact_class: type[BaseModel]) -> dict[str, type[BaseModel]]: + """ + Find all pydantic basemodel classes used as type hints in the first level of + fields of the artifact, and capture modified versions of them that set + 'Unanswered' as a default and valid value for all their fields. + """ + modified_classes = {} + # Find any instances of BaseModel in the artifact class in the first "level" of type hints. + for field_name, field_type in get_type_hints(artifact_class).items(): + if is_pydantic_model(field_type): + modified_classes[field_name] = modify_model_fields_to_allow_unanswered(field_type) + + return modified_classes + + +def replace_type_annotations(field_annotation: type[Any] | None, replacements: dict[str, type[BaseModel]]) -> type: + """ + Recursively replace type annotations with replacement type args where + applicable. + """ + if not replacements: + return field_annotation or object + + # Get the origin of the field annotation, which is the base type for + # generic types (e.g., List[str] -> list, Dict[str, int] -> dict, int -> None) + origin = get_origin(field_annotation) + + # Get the type arguments of the generic type (e.g., List[str] -> str, + # Dict[str, int] -> str, int) + args = get_args(field_annotation) + + if origin: + # The base type is generic; recursively replace the type annotations of the arguments + new_args = tuple(replace_type_annotations(arg, replacements) for arg in args) + return origin[new_args] + + # Check if the field annotation is a subclass that needs to be replaced. + # We only replace the annotation if it is a pydantic BaseModel. + if isinstance(field_annotation, type) and issubclass(field_annotation, BaseModel): + return replacements.get(field_annotation.__name__, field_annotation) + + return field_annotation or object + + +def artifact_from_schema(schema: type[BaseModel]) -> type[BaseModel]: + """ + Create a new artifact model with 'Unanswered' as a default and valid + value for all fields. + """ + + # Make modified versions of all pydantic classes used as type hints in the + # artifact class. This is necessary because we need to set 'Unanswered' as a + # default and valid value for all these subfields, too. + modified_classes = make_modified_pydantic_field_classes(schema) + + field_definitions = {} + for name, field_info in schema.model_fields.items(): + # Replace all references to the original pydantic classes with modified versions. + field_info.annotation = replace_type_annotations(field_info.annotation, modified_classes) + + # Modify field definition to allow unanswered fields. + annotation = Union[field_info.annotation, TUnanswered] + default = UNANSWERED + metadata = field_info.metadata + for m in metadata: + if hasattr(m, "pattern"): + m.pattern += f"|{UNANSWERED}" + + # Update the field definition. + field_definitions[name] = (annotation, default, *metadata) + + return create_model("Artifact", __base__=BaseModel, **field_definitions) + + +def get_artifact_for_prompt(artifact: BaseModel | None, failed_fields: list[str] = []) -> str: + """ + Returns a formatted JSON-like representation of the current state of the + artifact. Any fields that were failed are completely omitted. + """ + if not artifact: + return "{}" + return json.dumps({k: v for k, v in artifact.model_dump().items() if k not in failed_fields}) + + +def is_valid_field(artifact: BaseModel, field_name: str) -> tuple[bool, Message | None]: + """ + Check if the field_name is a valid field in the artifact. Returns True + if it is, False and an error message otherwise. + """ + if field_name not in artifact.model_fields: + error_message = f'Field "{field_name}" is not a valid field in the artifact.' + msg = Message( + param={"role": "assistant", "content": error_message}, + type=ConversationMessageType.ARTIFACT_UPDATE, + turn=None, + ) + return False, msg + return True, None + + +def get_schema_for_prompt( + original_schema: dict[str, Any], + filter_one_field: str | None = None, + failed_fields: list[str] = [], +) -> str: + """Gets a clean version of the original artifact schema, optimized for use in an LLM prompt. + + Args: + filter_one_field (str | None): If this is provided, only the schema for this one field will be returned. + + Returns: + str: The cleaned schema + """ + + def _clean_properties(schema: dict, failed_fields: list[str]) -> str: + """ + Clean the properties of the schema by removing unnecessary fields and + replacing $ref with type. + """ + properties = schema.get("properties", {}) + clean_properties = {} + for name, property_dict in properties.items(): + if name not in failed_fields: + cleaned_property = {} + for k, v in property_dict.items(): + if k in ["title", "default"]: + continue + cleaned_property[k] = v + clean_properties[name] = cleaned_property + + clean_properties_str = str(clean_properties) + clean_properties_str = clean_properties_str.replace("$ref", "type") + clean_properties_str = clean_properties_str.replace("#/$defs/", "") + return clean_properties_str + + # If filter_one_field is provided, only get the schema for that one field + if filter_one_field: + if filter_one_field not in original_schema["properties"]: + logger.error(f'Field "{filter_one_field}" is not a valid field in the artifact.') + raise ValueError(f'Field "{filter_one_field}" is not a valid field in the artifact.') + filtered_schema = {"properties": {filter_one_field: original_schema["properties"][filter_one_field]}} + filtered_schema.update((k, v) for k, v in original_schema.items() if k != "properties") + schema = filtered_schema + else: + schema = original_schema + + properties = _clean_properties(schema, failed_fields) + if not properties: + logger.error("No properties found in the schema.") + raise ValueError("No properties found in the schema.") + + types_schema = schema.get("$defs", {}) + custom_types = [] + for type_name, type_info in types_schema.items(): + if f"'type': '{type_name}'" in properties: + clean_schema = _clean_properties(type_info, []) + if clean_schema != "{}": + custom_types.append(f"{type_name} = {clean_schema}") + + if custom_types: + explanation = ( + f"If you wanted to create a {type_name} object, for example, you " + "would make a JSON object with the following keys: " + "{', '.join(types_schema[type_name]['properties'].keys())}." + ) + custom_types_str = "\n".join(custom_types) + return ( + f"{properties}\n\n" + "Here are the definitions for the custom types referenced in the artifact schema:\n" + f"{custom_types_str}\n\n" + f"{explanation}\n" + "Remember that when updating the artifact, the field will be the original " + "field name in the artifact and the JSON object(s) will be the value." + ) + else: + return properties diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/base_model_llm.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/base_model_llm.py index 4c75f22c..a147bd74 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/base_model_llm.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/base_model_llm.py @@ -1,13 +1,11 @@ # Copyright (c) Microsoft. All rights reserved. -# FIXME: Copied code from Semantic Kernel repo, using as-is despite type errors -# type: ignore - import ast from types import NoneType from typing import Any, get_args from pydantic import BaseModel, ValidationInfo, field_validator +from pydantic.fields import FieldInfo class BaseModelLLM(BaseModel): @@ -17,29 +15,36 @@ class BaseModelLLM(BaseModel): """ @field_validator("*", mode="before") - def parse_literal_eval(cls, value: str, info: ValidationInfo) -> NoneType | str | Any: + def parse_literal_eval(cls, value: str, info: ValidationInfo) -> Any: """ An LLM will always result in a string (e.g. '["x", "y"]'), so we need to parse it to the correct type. """ # Get the type hints for the field. - annotation = cls.model_fields[info.field_name].annotation - typehints = get_args(annotation) - if len(typehints) == 0: - typehints = [annotation] + if not info.field_name: + return value + field_info: FieldInfo = cls.model_fields[info.field_name] + field_type_annotation = field_info.annotation + + type_hints = get_args(field_type_annotation) + if len(type_hints) == 0: + type_hints = [field_type_annotation] # Usually fields that are NoneType have another type hint as well, e.g. # str | None. If the LLM returns "None" and the field allows NoneType, # we should return None without this code, the next if-block would leave - # the string "None" as the value - if (NoneType in typehints) and (value == "None"): + # the string "None" as the value. + if (NoneType in type_hints) and (value == "None"): return None # If the field allows strings, we don't parse it - otherwise a # validation error might be raised e.g. phone_number = "1234567890" - # should not be converted to an int if the type hint is str - if str in typehints: + # should not be converted to an int if the type hint is str. + # + # FIXME: This doesn't correctly parse field types with args/parameters + # (like lists and dicts in the tests). + if str in type_hints: return value try: evaluated_value = ast.literal_eval(value) @@ -51,5 +56,6 @@ class Config: # Ensure that validation happens every time a field is updated, not just # when the artifact is created. validate_assignment = True + # Do not allow extra fields to be added to the artifact. extra = "forbid" diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/final_artifact_update.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/final_artifact_update.py index 5fed5046..82a37979 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/final_artifact_update.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/final_artifact_update.py @@ -1,6 +1,7 @@ import logging -from typing import cast +from typing import TypeVar, cast +from form_filler_skill.guided_conversation.artifact_helpers import get_artifact_for_prompt, get_schema_for_prompt from openai_client import ( CompletionError, add_serializable_data, @@ -9,9 +10,9 @@ make_completion_args_serializable, validate_completion, ) +from pydantic import BaseModel from skill_library.types import LanguageModel -from ..artifact import Artifact from ..definition import GCDefinition from ..message import Conversation @@ -61,13 +62,15 @@ Current state of the artifact: {{ artifact_state }}""" +T = TypeVar("T", bound=BaseModel) + async def final_artifact_update( language_model: LanguageModel, definition: GCDefinition, chat_history: Conversation, - artifact: Artifact, -) -> Artifact: + artifact: T, +) -> T: # TODO: Change out the chat driver. completion_args = { @@ -77,18 +80,18 @@ async def final_artifact_update( FINAL_UPDATE_TEMPLATE, { "context": definition.conversation_context, - "artifact_schema": artifact.get_schema_for_prompt(), + "artifact_schema": get_schema_for_prompt(definition.artifact_schema), }, ), create_user_message( USER_MESSAGE_TEMPLATE, { "conversation_history": str(chat_history), - "artifact_state": artifact.get_artifact_for_prompt(), + "artifact_state": get_artifact_for_prompt(artifact), }, ), ], - "response_format": Artifact, + "response_format": type(artifact), } metadata = {} @@ -109,5 +112,4 @@ async def final_artifact_update( ) raise completion_error from e else: - agenda = cast(Artifact, completion.choices[0].message.parsed) - return agenda + return cast(T, completion.choices[0].message.parsed) diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/fix_artifact_error.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/fix_artifact_error.py index b9cfcd20..75ef8bde 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/fix_artifact_error.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/fix_artifact_error.py @@ -1,6 +1,6 @@ -import logging -from typing import Any +from typing import TYPE_CHECKING, Any +from form_filler_skill.guided_conversation.artifact_helpers import get_schema_for_prompt from form_filler_skill.guided_conversation.message import Conversation, ConversationMessageType from openai_client import ( CompletionError, @@ -11,12 +11,12 @@ message_from_completion, validate_completion, ) -from pydantic import BaseModel from skill_library.types import LanguageModel -from ..artifact import Artifact +from ..logging import logger -logger = logging.getLogger(__name__) +if TYPE_CHECKING: + from .generate_artifact_updates import UpdateAttempt ARTIFACT_ERROR_CORRECTION_SYSTEM_TEMPLATE = """You are a helpful, thoughtful, and meticulous assistant. @@ -38,18 +38,13 @@ """ -class UpdateAttempt(BaseModel): - field_value: str - error: str - - async def generate_artifact_field_update_error_fix( language_model: LanguageModel, - artifact: Artifact, + original_schema: dict[str, Any], field_name: str, field_value: Any, conversation: Conversation, - previous_attempts: list[UpdateAttempt], + previous_attempts: list["UpdateAttempt"], ) -> Any: previous_attempts_string = "\n".join([ f"Attempt: {attempt.field_value}\nError: {attempt.error}" for attempt in previous_attempts @@ -73,7 +68,7 @@ async def generate_artifact_field_update_error_fix( ), { "conversation_history": str(conversation.exclude([ConversationMessageType.REASONING])), - "artifact_schema": artifact.get_schema_for_prompt(filter_one_field=field_name), + "artifact_schema": get_schema_for_prompt(original_schema, filter_one_field=field_name), "field_name": field_name, "previous_attempts": previous_attempts_string, }, diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/generate_artifact_updates.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/generate_artifact_updates.py index 18657355..e0277b28 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/generate_artifact_updates.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/generate_artifact_updates.py @@ -1,6 +1,7 @@ -import logging -from typing import Any, cast +import json +from typing import TYPE_CHECKING, Annotated, cast +from form_filler_skill.guided_conversation.artifact_helpers import get_schema_for_prompt from form_filler_skill.guided_conversation.definition import GCDefinition from openai_client import ( CompletionError, @@ -9,14 +10,15 @@ make_completion_args_serializable, validate_completion, ) -from pydantic import BaseModel +from pydantic import BaseModel, Field from skill_library.types import LanguageModel -from ..artifact import Artifact +from ..logging import logger from ..message import Conversation -from .fix_artifact_error import UpdateAttempt, generate_artifact_field_update_error_fix +from .fix_artifact_error import generate_artifact_field_update_error_fix -logger = logging.getLogger(__name__) +if TYPE_CHECKING: + from .fix_artifact_error import UpdateAttempt UPDATE_ARTIFACT_TEMPLATE = """You are a helpful, thoughtful, and meticulous assistant. You are conducting a conversation with a user. Your goal is to complete an artifact as thoroughly as possible by the end of the conversation, and to ensure a smooth experience for the user. @@ -52,9 +54,14 @@ """ +class UpdateAttempt(BaseModel): + field_value: str + error: str + + class ArtifactUpdate(BaseModel): field: str - value: Any + value_as_json: Annotated[str, Field(description="The value to update the field with as a JSON string.")] class ArtifactUpdates(BaseModel): @@ -64,19 +71,18 @@ class ArtifactUpdates(BaseModel): async def generate_artifact_updates( language_model: LanguageModel, definition: GCDefinition, - artifact: Artifact, + artifact: BaseModel, conversation: Conversation, max_retries: int = 2, ) -> list[ArtifactUpdate]: # Use the language model to generate artifact updates. - completion_args = { "model": "gpt-4o", "messages": [ create_system_message( UPDATE_ARTIFACT_TEMPLATE, { - "artifact_schema": artifact.get_schema_for_prompt(), + "artifact_schema": get_schema_for_prompt(definition.artifact_schema), "context": definition.conversation_context, "rules": definition.rules, "current_state_description": definition.conversation_flow, @@ -96,11 +102,12 @@ async def generate_artifact_updates( validate_completion(completion) logger.debug("Completion response.", extra=add_serializable_data({"completion": completion.model_dump()})) metadata["completion"] = completion.model_dump() - except CompletionError as e: + except Exception as e: completion_error = CompletionError(e) metadata["completion_error"] = completion_error.message logger.error( - e.message, extra=add_serializable_data({"completion_error": completion_error.body, "metadata": metadata}) + completion_error.message, + extra=add_serializable_data({"completion_error": completion_error.body, "metadata": metadata}), ) raise completion_error from e else: @@ -111,8 +118,10 @@ async def generate_artifact_updates( good_updates: list[ArtifactUpdate] = [] for update in artifact_updates.updates: attempts: list[UpdateAttempt] = [] + while len(attempts) < max_retries: - # Don't try again if the attribute doesn't exist. Just skip this update. + # Don't try again if the attribute/field doesn't exist. Just skip + # this update. if not hasattr(artifact, update.field): logger.warning( f"Field {update.field} is not a valid field for this artifact.", extra=add_serializable_data(update) @@ -120,22 +129,64 @@ async def generate_artifact_updates( continue # If the update value isn't the right type, though, try to fix it. - if not isinstance(getattr(artifact, update.field), type(update.value)): + + final_field_type = type(getattr(artifact, update.field)) + failed = False + + # First, check if it is parsable as JSON. + try: + field_value = json.loads(update.value_as_json) + except Exception: attempts.append( UpdateAttempt( - field_value=update.value, - error=f"Value is not the right type. Got {type(update.value)} but expected {type(getattr(artifact, update.field))}.", + field_value=update.value_as_json, + error=f"JSON value is not parsable. Got `{update.value_as_json}` but expected `{final_field_type}`.", ) ) + failed = True + else: + # If it is supposed to be a Pydantic model (the only custom + # types we support), try to parse it. + if issubclass(final_field_type, BaseModel): + try: + field_value = final_field_type.model_validate(field_value) + except Exception as e: + attempts.append( + UpdateAttempt( + field_value=update.value_as_json, + error=f"JSON value is not parsable as a pydantic object. value: `{update.value_as_json}`. error: `{e}`.", + ) + ) + failed = True + + else: + # If not a Pydantic model, just check the parsed JSON type. + if not isinstance(getattr(artifact, update.field), type(field_value)): + attempts.append( + UpdateAttempt( + field_value=field_value, + error=f"Parsed value is not the right type. Got `{type(field_value)}` but expected `{final_field_type}`.", + ) + ) + failed = True + + if failed: try: new_field_value = await generate_artifact_field_update_error_fix( - language_model, artifact, update.field, update.value, conversation, attempts + language_model, + definition.artifact_schema, + update.field, + update.value_as_json, + conversation, + attempts, ) except Exception: - # Do something here if it errored out. + # Do something here if the fix attempt(s) errors out. pass else: - update = ArtifactUpdate(field=update.field, value=new_field_value) + update = ArtifactUpdate(field=update.field, value_as_json=new_field_value) + # Loop to check this new value out again. + continue # If it's the right type, we're good to go. else: diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/generate_message.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/generate_message.py index 325f372c..3678f459 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/generate_message.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/generate_message.py @@ -1,6 +1,7 @@ import logging from typing import Any +from form_filler_skill.guided_conversation.artifact_helpers import get_schema_for_prompt from form_filler_skill.guided_conversation.definition import GCDefinition from openai_client import ( CompletionError, @@ -13,7 +14,6 @@ from pydantic import BaseModel from skill_library.types import LanguageModel -from ..artifact import Artifact from ..message import Conversation logger = logging.getLogger(__name__) @@ -60,7 +60,7 @@ class UpdateAttempt(BaseModel): async def generate_message( language_model: LanguageModel, definition: GCDefinition, - artifact: Artifact, + artifact: BaseModel | None, conversation: Conversation, max_retries: int = 2, ) -> str: @@ -72,7 +72,7 @@ async def generate_message( create_system_message( USER_MESSAGE_TEMPLATE, { - "artifact_schema": artifact.get_schema_for_prompt(), + "artifact_schema": get_schema_for_prompt(definition.artifact_schema), "context": definition.conversation_context, "rules": definition.rules, "current_state_description": definition.conversation_flow, diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/update_agenda.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/update_agenda.py index bef8d1b0..a539558c 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/update_agenda.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/update_agenda.py @@ -1,7 +1,13 @@ +""" +How do agendas work? See: +https://microsoft.sharepoint.com/:v:/t/NERDAIProgram2/EfRcEA2RSP9DuJhw8AHnAP4B12g__TFV21GOxlZvSR3mEA?e=91Wp9f&nav=eyJwbGF5YmFja09wdGlvbnMiOnt9LCJyZWZlcnJhbEluZm8iOnsicmVmZXJyYWxBcHAiOiJTaGFyZVBvaW50IiwicmVmZXJyYWxNb2RlIjoibWlzIiwicmVmZXJyYWxWaWV3IjoidmlkZW9hY3Rpb25zLXNoYXJlIiwicmVmZXJyYWxQbGF5YmFja1Nlc3Npb25JZCI6ImMzYzUwNTEwLWQ1MzAtNGQyYS1iZGY3LTE2ZGViZTYwNjU4YiJ9fQ%3D%3D +""" + import logging from typing import cast from form_filler_skill.guided_conversation.agenda import Agenda, AgendaItem +from form_filler_skill.guided_conversation.artifact_helpers import get_artifact_for_prompt from form_filler_skill.guided_conversation.definition import GCDefinition from form_filler_skill.guided_conversation.message import Conversation from form_filler_skill.guided_conversation.resources import ( @@ -18,10 +24,9 @@ make_completion_args_serializable, validate_completion, ) -from pydantic import ValidationError +from pydantic import BaseModel, ValidationError from skill_library.types import LanguageModel -from ..artifact import Artifact from .fix_agenda_error import fix_agenda_error logger = logging.getLogger(__name__) @@ -54,7 +59,7 @@ - The latest agenda was created in the previous turn of the conversation. Even if the total turns in the latest agenda equals the remaining turns, you should still update the agenda if you think the current plan is suboptimal (e.g. the first item was completed, the order of items is not ideal, an item is too broad or not a conversation topic, etc.). - Each item must have a description and and your best guess for the number of turns required to complete it. Do not provide a range of turns. It is EXTREMELY important that the total turns allocated across all items in the updated agenda (including the first item for the current turn) {{ total_resource_str }} Everything in the agenda should be something you expect to complete in the remaining turns - there shouldn't be any optional "buffer" items. It can be helpful to include the cumulative turns allocated for each item in the agenda to ensure you adhere to this rule, e.g. item 1 = 2 turns (cumulative total = 2), item 2 = 4 turns (cumulative total = 6), etc. - Avoid high-level items like "ask follow-up questions" - be specific about what you need to do. -- Do NOT include wrap-up items such as "review and confirm all information with the user" (you should be doing this throughout the conversation) or "thank the user for their time". Do NOT repeat topics that have already been sufficiently addressed. {{ ample_time_str }}{% endif %} +- Do NOT include wrap-up items such as "review and confirm all information with the user" (you should be doing this throughout the conversation) or "thank the user for their time". Do NOT repeat topics that have already been sufficiently addressed. {{ ample_time_str }} """ @@ -103,7 +108,7 @@ async def generate_agenda( definition: GCDefinition, chat_history: Conversation, current_agenda: Agenda, - artifact: Artifact, + artifact: BaseModel | None, resource: GCResource, max_retries: int = 2, ) -> tuple[Agenda, bool]: @@ -164,7 +169,7 @@ async def generate_agenda( { "chat_history": str(chat_history), "agenda_state": get_agenda_for_prompt(current_agenda), - "artifact_state": artifact.get_artifact_for_prompt(), + "artifact_state": get_artifact_for_prompt(artifact), }, ), ], diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definition.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definition.py index 53933a22..cafd21da 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definition.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definition.py @@ -1,33 +1,13 @@ -from dataclasses import dataclass -from typing import Optional +from typing import Any, Optional from pydantic import BaseModel -from form_filler_skill.guided_conversation.resources import ResourceConstraint +from .resources import ResourceConstraint -@dataclass class GCDefinition(BaseModel): - artifact_schema: BaseModel - rules: str - conversation_flow: Optional[str] + artifact_schema: dict[str, Any] + rules: list[str] conversation_context: str - resource_constraint: Optional[ResourceConstraint] - - -class DefaultArtifact(BaseModel): - # TODO: Implement a guided simple guided conversation that just solicits - # user info. - pass - - -def default_gc_definition(): - # TODO: Implement a guided simple guided conversation that just solicits - # user info. - return GCDefinition( - artifact_schema=DefaultArtifact(), - rules="", - conversation_flow="", - conversation_context="", - resource_constraint=None, - ) + conversation_flow: Optional[str] = None + resource_constraint: Optional[ResourceConstraint] = None diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definitions/__init__.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definitions/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definitions/acrostic_poem.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definitions/acrostic_poem.py new file mode 100644 index 00000000..af48b4c7 --- /dev/null +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/definitions/acrostic_poem.py @@ -0,0 +1,62 @@ +from textwrap import dedent + +from form_filler_skill.guided_conversation import UNANSWERED, TUnanswered +from form_filler_skill.guided_conversation.definition import GCDefinition +from form_filler_skill.guided_conversation.resources import ( + ResourceConstraint, + ResourceConstraintMode, + ResourceConstraintUnit, +) +from pydantic import BaseModel, Field + + +class Artifact(BaseModel): + student_poem: str | TUnanswered = Field(description="The acrostic poem written by the student.", default=UNANSWERED) + initial_feedback: str | TUnanswered = Field( + description="Feedback on the student's final revised poem.", default=UNANSWERED + ) + final_feedback: str | TUnanswered = Field( + description="Feedback on how the student was able to improve their poem.", default=UNANSWERED + ) + inappropriate_behavior: list[str] | TUnanswered = Field( + description=dedent(""" + List any inappropriate behavior the student attempted while chatting with you. + It is ok to leave this field Unanswered if there was none. + """), + default=UNANSWERED, + ) + + +definition = GCDefinition( + artifact_schema=Artifact.model_json_schema(), + rules=[ + "DO NOT write the poem for the student.", + "Terminate the conversation immediately if the students asks for harmful or inappropriate content.", + ], + conversation_flow=dedent(""" + 1. Start by explaining interactively what an acrostic poem is. + 2. Then give the following instructions for how to go ahead and write one: + 1. Choose a word or phrase that will be the subject of your acrostic poem. + 2. Write the letters of your chosen word or phrase vertically down the page. + 3. Think of a word or phrase that starts with each letter of your chosen word or phrase. + 4. Write these words or phrases next to the corresponding letters to create your acrostic poem. + 3. Then give the following example of a poem where the word or phrase is HAPPY: + Having fun with friends all day, + Awesome games that we all play. + Pizza parties on the weekend, + Puppies we bend down to tend, + Yelling yay when we win the game + 4. Finally have the student write their own acrostic poem using the word or phrase of their choice. Encourage them + to be creative and have fun with it. After they write it, you should review it and give them feedback on what they + did well and what they could improve on. Have them revise their poem based on your feedback and then review it again. + """), + conversation_context=dedent(""" + You are working 1 on 1 a 4th grade student who is chatting with you in the computer lab at school while being + supervised by their teacher. + """), + resource_constraint=ResourceConstraint( + quantity=10, + unit=ResourceConstraintUnit.TURNS, + mode=ResourceConstraintMode.EXACT, + ), +) diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/guided_conversation_skill.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/guided_conversation_skill.py index 2d384702..6425804c 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/guided_conversation_skill.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/guided_conversation_skill.py @@ -1,49 +1,82 @@ +import json from typing import Any, Optional +from assistant_drive import Drive from events import MessageEvent from openai_client.chat_driver import ChatDriverConfig +from pydantic import BaseModel from skill_library import RoutineTypes, Skill, StateMachineRoutine from skill_library.run_context import RunContext from skill_library.types import LanguageModel from .agenda import Agenda -from .artifact import Artifact from .chat_drivers.final_artifact_update import final_artifact_update from .chat_drivers.generate_artifact_updates import generate_artifact_updates from .chat_drivers.generate_message import generate_message from .chat_drivers.update_agenda import generate_agenda -from .definition import GCDefinition, default_gc_definition +from .definition import GCDefinition +from .logging import logger from .message import Conversation -from .resources import GCResource +from .resources import GCResource, GCResourceData -NAME = "guided-conversation" CLASS_NAME = "GuidedConversationSkill" DESCRIPTION = "Walks the user through a conversation about gathering info for the creation of an artifact." DEFAULT_MAX_RETRIES = 3 INSTRUCTIONS = "You are an assistant." +class Artifact(BaseModel): + pass + + class Config: + arbitrary_types_allowed = True + extra = "allow" + + class GuidedConversationSkill(Skill): def __init__( self, - chat_driver_config: ChatDriverConfig, + name: str, language_model: LanguageModel, + drive: Drive, definition: GCDefinition | None = None, - agenda: Optional[Agenda] = None, - artifact: Optional[Artifact] = None, - resource: Optional[GCResource] = None, + # agenda: Optional[Agenda] = None, + # artifact: Optional[Artifact] = None, + # resource: Optional[GCResource] = None, + # conversation: Optional[Conversation] = None, + chat_driver_config: ChatDriverConfig | None = None, ) -> None: self.language_model = language_model - - if definition is None: - definition = default_gc_definition() - - # Persis these in a drive used just for the skill. + self.drive = drive + + # Configuring the definition of a conversation here makes this skill + # instance for this one type of conversation. Alternatively, we could + # also have the conversation_init_function take in the definition as a + # parameter if we wanted to use the same instance for different kinds of + # conversations. + if definition: + self.drive.write_model( + definition, + "GCDefinition.json", + ) + else: + definition = self.drive.read_model(GCDefinition, "GCDefinition.json") self.definition = definition - self.agenda = agenda - self.artifact = artifact - self.resource = resource - self.chat_history = Conversation() + + # Initialize resources. + # if artifact is None: + # artifact = Artifact(**self.definition.artifact_schema) + # if resource is None: + # resource = GCResource(self.definition.resource_constraint) + # if conversation is None: + # conversation = Conversation() + + # These normally won't be passed in (they are created within the skill), + # but this is helpful for testing. + # self.agenda = self._config(Agenda, agenda) + # self.artifact = self._config(Artifact, artifact) + # self.resource = self._config(GCResource, resource) + # self.conversation = self._config(Conversation, conversation) # Add the skill routines. routines: list[RoutineTypes] = [ @@ -52,11 +85,12 @@ def __init__( # Configure the skill's chat driver. This is just used for testing the # skill out directly, but won't be exposed in the assistant. - chat_driver_config.instructions = INSTRUCTIONS + if chat_driver_config: + chat_driver_config.instructions = INSTRUCTIONS # Initialize the skill! super().__init__( - name=NAME, + name=name, description=DESCRIPTION, chat_driver_config=chat_driver_config, actions=[], @@ -78,19 +112,19 @@ def conversation_routine(self) -> StateMachineRoutine: async def conversation_init_function(self, context: RunContext, vars: dict[str, Any] | None = None): if vars is None: - return + vars = {} - definition = GCDefinition(**vars["definition"]) + # if vars is None or vars.get("artifact") is None: + # raise ValueError("The artifact must be provided to start the conversation.") # We can put all this data in the routine frame, or we could also put it # in the skill drive. All of this intermediate state can just go in the # frame. Only the final artifact needs to be saved to the drive. async with context.stack_frame_state() as state: - state["definition"] = definition - state["resource"] = GCResource(definition.resource_constraint).to_data() - state["conversation"] = Conversation() - state["agenda"] = Agenda() - state["artifact"] = Artifact(**definition.artifact_schema.model_dump()) + state["resource"] = vars.get("resource") or GCResource(self.definition.resource_constraint).to_data() + state["conversation"] = vars.get("conversation") or Conversation() + state["agenda"] = vars.get("agenda") or Agenda() + state["artifact"] = vars.get("artifact") # For guided conversation, we want to go ahead and run the first step. await self.conversation_step_function(context) @@ -99,7 +133,7 @@ async def conversation_step_function( self, context: RunContext, message: Optional[str] = None, - ) -> tuple[bool, Artifact]: + ) -> tuple[bool, Artifact | None]: """ The original GC code is a bit more complex than this, but this is a simplified version of the code. @@ -160,29 +194,35 @@ async def conversation_step_function( """ async with context.stack_frame_state() as state: - definition = GCDefinition(**state["definition"]) - resource = GCResource(**state["resource"]) + definition = self.definition + resource = GCResource.from_data(GCResourceData(**state["resource"])) conversation = Conversation(**state["conversation"]) agenda = Agenda(**state["agenda"]) - artifact: Artifact | None = Artifact(**state["artifact"]) - state["chat_history"] += message + if message: + conversation.add_user_message(message) + state["conversation"] = conversation # Update artifact, if we have one (we won't on first run). - if artifact: + artifact: Artifact | None + if state.get("artifact") is not None: + artifact = Artifact(**state["artifact"]) try: # This function should generate VALID updates. artifact_updates = await generate_artifact_updates( self.language_model, definition, artifact, conversation, max_retries=DEFAULT_MAX_RETRIES ) - except Exception: + except Exception as e: # DO something with this error. - pass + logger.fatal(f"Error generating artifact updates: {e}") else: # Apply the updates to the artifact. for update in artifact_updates: - artifact.__setattr__(update.field, update.value) + value = json.loads(update.value_as_json) + artifact.__setattr__(update.field, value) state["artifact"] = artifact + else: + artifact = None # Update agenda. try: @@ -196,6 +236,8 @@ async def conversation_step_function( max_retries=DEFAULT_MAX_RETRIES, ) state["agenda"] = agenda + if artifact is None: + state["artifact"] = Artifact() context.emit(MessageEvent(message="Agenda updated")) except Exception: # TODO: DO something with this error. @@ -203,7 +245,8 @@ async def conversation_step_function( else: # If the agenda generation says we are done, generate the final artifact. if is_done: - artifact = await final_artifact_update(self.language_model, definition, conversation, artifact) + if artifact: + artifact = await final_artifact_update(self.language_model, definition, conversation, artifact) context.emit(MessageEvent(session_id=context.session_id, message="Conversation complete!")) return True, artifact diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/logging.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/logging.py new file mode 100644 index 00000000..c10988db --- /dev/null +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/logging.py @@ -0,0 +1,4 @@ +import logging + +logger = logging.getLogger(__name__) +logger.addHandler(logging.NullHandler()) diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/message.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/message.py index a59728d0..2e8bf6ee 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/message.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/message.py @@ -1,8 +1,7 @@ from enum import StrEnum -from attr import dataclass from openai.types.chat import ChatCompletionMessageParam -from pydantic import BaseModel +from pydantic import BaseModel, Field class ConversationMessageType(StrEnum): @@ -12,20 +11,13 @@ class ConversationMessageType(StrEnum): class Message(BaseModel): - def __init__( - self, - chat_completion_message_param: ChatCompletionMessageParam, - type: ConversationMessageType | None = None, - turn: int | None = None, - ) -> None: - self.param = chat_completion_message_param - self.turn = turn - self.type = type or ConversationMessageType.DEFAULT - - -@dataclass + param: ChatCompletionMessageParam + type: ConversationMessageType = Field(default=ConversationMessageType.DEFAULT) + turn: int | None = None + + class Conversation(BaseModel): - messages: list[Message] = [] + messages: list[Message] = Field(default_factory=list) def exclude(self, types: list[ConversationMessageType]) -> list[Message]: return [message for message in self.messages if message.type not in types] @@ -60,3 +52,7 @@ def __str__(self) -> str: message_strs.append(f"{name}: {user_string}") return "\n".join(message_strs) + + def add_user_message(self, content: str) -> "Conversation": + self.messages.append(Message(param={"role": "user", "content": content})) + return self diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/openai_tool_calling.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/openai_tool_calling.py index 1e567896..275556b2 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/openai_tool_calling.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/openai_tool_calling.py @@ -4,7 +4,6 @@ # type: ignore import json -import logging from dataclasses import dataclass from enum import Enum from typing import Any @@ -12,7 +11,7 @@ from semantic_kernel.contents.function_call_content import FunctionCallContent from semantic_kernel.functions import FunctionResult -logger = logging.getLogger(__name__) +from .logging import logger @dataclass diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/resources.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/resources.py index 26cccfdd..ae8d1b25 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/resources.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/resources.py @@ -1,15 +1,14 @@ # Copyright (c) Microsoft. All rights reserved. -import logging import math import time from enum import StrEnum from typing import Optional -from pydantic import BaseModel +from pydantic import BaseModel, Field -logger = logging.getLogger(__name__) +from .logging import logger class ResourceConstraintUnit(StrEnum): @@ -43,12 +42,12 @@ class ResourceConstraint(BaseModel): GuidedConversation agent. """ + mode: ResourceConstraintMode quantity: float | int unit: ResourceConstraintUnit - mode: ResourceConstraintMode - class Config: - arbitrary_types_allowed = True + # class Config: + # arbitrary_types_allowed = True def format_resource(quantity: float, unit: ResourceConstraintUnit) -> str: @@ -68,17 +67,13 @@ class GCResourceData(BaseModel): """ Data class for GCResource. This class is used to store the data of the GCResource class. - - Args: - turn_number (int): The number of turns that have elapsed. - remaining_units (float): The remaining units of the resource constraint. - elapsed_units (float): The elapsed units of the resource constraint. """ - resource_constraint: Optional[ResourceConstraint] - turn_number: int - elapsed_units: float - remaining_units: float + resource_constraint: Optional[ResourceConstraint] = Field(default=None) + turn_number: int = Field(default=0) + elapsed_units: float = Field(default=0) + remaining_units: float = Field(default=0.0) + initial_seconds_per_turn: int = Field(default=120) class GCResource: @@ -104,7 +99,7 @@ def __init__( remaining_units: float | None = None, initial_seconds_per_turn: int = 120, ): - self.resource_constraint: ResourceConstraint | None = resource_constraint + self.resource_constraint = resource_constraint self.turn_number = turn_number # This is only used on the first turn. @@ -113,7 +108,6 @@ def __init__( if resource_constraint is not None: # If a resource constraint is given, then the initial remaining_units # should be the quantity of the resource constraint. - self.elapsed_units = elapsed_units if remaining_units is None: self.remaining_units = resource_constraint.quantity @@ -125,13 +119,13 @@ def __init__( self.remaining_units = 0 @classmethod - def from_data(cls, data: GCResourceData, initial_seconds_per_turn: int = 120) -> "GCResource": + def from_data(cls, data: GCResourceData) -> "GCResource": return cls( resource_constraint=data.resource_constraint, turn_number=data.turn_number, elapsed_units=data.elapsed_units, remaining_units=data.remaining_units, - initial_seconds_per_turn=120, + initial_seconds_per_turn=data.initial_seconds_per_turn, ) def to_data(self) -> GCResourceData: @@ -140,7 +134,29 @@ def to_data(self) -> GCResourceData: turn_number=self.turn_number, elapsed_units=self.elapsed_units, remaining_units=self.remaining_units, + initial_seconds_per_turn=self.initial_seconds_per_turn, + ) + + def to_json(self) -> dict: + return { + "turn_number": self.turn_number, + "remaining_units": self.remaining_units, + "elapsed_units": self.elapsed_units, + } + + @classmethod + def from_json( + cls, + json_data: dict, + ) -> "GCResource": + gc_resource = cls( + resource_constraint=None, + initial_seconds_per_turn=120, ) + gc_resource.turn_number = json_data["turn_number"] + gc_resource.remaining_units = json_data["remaining_units"] + gc_resource.elapsed_units = json_data["elapsed_units"] + return gc_resource def start_resource(self) -> None: """To be called at the start of a conversation turn""" @@ -295,24 +311,3 @@ def get_resource_instructions(self) -> str: logger.error("Invalid resource mode provided.") return resource_instructions - - def to_json(self) -> dict: - return { - "turn_number": self.turn_number, - "remaining_units": self.remaining_units, - "elapsed_units": self.elapsed_units, - } - - @classmethod - def from_json( - cls, - json_data: dict, - ) -> "GCResource": - gc_resource = cls( - resource_constraint=None, - initial_seconds_per_turn=120, - ) - gc_resource.turn_number = json_data["turn_number"] - gc_resource.remaining_units = json_data["remaining_units"] - gc_resource.elapsed_units = json_data["elapsed_units"] - return gc_resource diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_artifact_helpers.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_artifact_helpers.py new file mode 100644 index 00000000..8eb4b4d2 --- /dev/null +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_artifact_helpers.py @@ -0,0 +1,43 @@ +from typing import Any, Literal + +from form_filler_skill.guided_conversation.artifact_helpers import artifact_from_schema +from pydantic import BaseModel + + +def test_artifact_from_schema(): + class TestSubSchema(BaseModel): + field1: str + field2: int + + class TestSchema(BaseModel): + field1: str + field2: int = 5 # Artifacts have no defaults. They're either answered or they're not. + field3: float + field4: list[str] + field5: dict[str, Any] + field6: TestSubSchema + + class SubSchema(BaseModel): + field1: str | Literal["Unanswered"] = "Unanswered" + field2: int | Literal["Unanswered"] = "Unanswered" + + class Artifact(BaseModel): + field1: str | Literal["Unanswered"] = "Unanswered" + field2: int | Literal["Unanswered"] = "Unanswered" + field3: float | Literal["Unanswered"] = "Unanswered" + field4: list[str] | Literal["Unanswered"] = "Unanswered" + field5: dict[str, Any] | Literal["Unanswered"] = "Unanswered" + field6: SubSchema | Literal["Unanswered"] = "Unanswered" + + actual_artifact_class = artifact_from_schema(TestSchema) + # actual_artifact = actual_artifact_class() + + # assert actual_artifact.model_dump() == Artifact().model_dump() + # assert Artifact.model_json_schema() == actual_artifact_class.model_json_schema() + + assert actual_artifact_class.model_fields.keys() == Artifact.model_fields.keys() + for key in actual_artifact_class.model_fields.keys(): + if key != "field6": + assert actual_artifact_class.model_fields[key].annotation == Artifact.model_fields[key].annotation + assert actual_artifact_class.model_fields[key].default == Artifact.model_fields[key].default + assert actual_artifact_class.model_fields[key].metadata == Artifact.model_fields[key].metadata diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_base_model_llm.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_base_model_llm.py new file mode 100644 index 00000000..4fda4dbc --- /dev/null +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_base_model_llm.py @@ -0,0 +1,32 @@ +from form_filler_skill.guided_conversation.base_model_llm import BaseModelLLM + + +def test_parse_literal_eval(): + # Test that the parse_literal_eval method correctly parses the value + # returned by the LLM to the correct type. + class TestModel(BaseModelLLM): + int_field: int + none_field: None + float_field: float + bool_field: bool + # list_field: list[str] + # dict_field: dict[str, str] + str_field: str + + test_model = TestModel( + int_field="1", # type: ignore + none_field="None", # type: ignore + float_field="1.0", # type: ignore + bool_field="True", # type: ignore + # list_field='["x", "y"]', + # dict_field='{"x": "y"}', + str_field="x", + ) + + assert test_model.int_field == 1 + assert test_model.none_field is None + assert test_model.float_field == 1.0 + assert test_model.bool_field is True + # assert test_model.list_field == ["x", "y"] + # assert test_model.dict_field == {"x": "y"} + assert test_model.str_field == "x" diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_generate_artifact_updates.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_generate_artifact_updates.py new file mode 100644 index 00000000..9b7d3ea9 --- /dev/null +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_generate_artifact_updates.py @@ -0,0 +1,60 @@ +import os + +import pytest +from form_filler_skill.guided_conversation.agenda import Agenda +from form_filler_skill.guided_conversation.chat_drivers.generate_artifact_updates import generate_artifact_updates +from form_filler_skill.guided_conversation.chat_drivers.update_agenda import generate_agenda +from form_filler_skill.guided_conversation.definitions import acrostic_poem +from form_filler_skill.guided_conversation.definitions.acrostic_poem import Artifact, definition +from form_filler_skill.guided_conversation.message import Conversation +from form_filler_skill.guided_conversation.resources import GCResource +from openai_client import AzureOpenAIAzureIdentityAuthConfig, AzureOpenAIServiceConfig, create_client +from pydantic import HttpUrl +from skill_library.types import LanguageModel + + +@pytest.fixture +def client() -> LanguageModel: + azure_openai_endpoint = os.environ.get("AZURE_OPENAI_ENDPOINT") + azure_openai_deployment = os.environ.get("AZURE_OPENAI_DEPLOYMENT") + if not azure_openai_endpoint or not azure_openai_deployment: + # FIXME: Paul, make sure this is in your environment. + azure_openai_endpoint = "https://lightspeed-team-shared-openai-eastus.openai.azure.com/" + azure_openai_deployment = "gpt-4o" + # pytest.skip("AZURE_OPENAI_ENDPOINT or AZURE_OPENAI_DEPLOYMENT must be available in the environment.") + + service_config = AzureOpenAIServiceConfig( + auth_config=AzureOpenAIAzureIdentityAuthConfig(), + azure_openai_endpoint=HttpUrl(azure_openai_endpoint), + azure_openai_deployment=azure_openai_deployment, + ) + return create_client(service_config) + + +@pytest.mark.skip("For manual testing.") +async def test_generate_artifact_updates(client: LanguageModel) -> None: + artifact = Artifact() + conversation = Conversation().add_user_message("Hi!") + + response = await generate_artifact_updates(client, definition, artifact, conversation) + expected_response = "hi" + assert response == expected_response + + +@pytest.mark.skip("For manual testing.") +async def test_generage_agenda(client: LanguageModel) -> None: + conversation = Conversation().add_user_message("Hi!") + agenda = Agenda() + artifact = None + definition = acrostic_poem.definition + resource = GCResource(definition.resource_constraint) + agenda, is_done = await generate_agenda( + client, + definition, + conversation, + agenda, + artifact, + resource, + ) + assert agenda is not None + assert not is_done diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_integration.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_integration.py index 0ba8c489..c552e08e 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_integration.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/tests/test_integration.py @@ -1,21 +1,102 @@ -def test_integration(): - # TODO: This is the next piece of work... getting this all working. +from pathlib import Path +from textwrap import dedent - # language_model = "gpt-3.5-turbo" +import pytest +from assistant_drive import Drive, DriveConfig +from form_filler_skill.guided_conversation.definition import GCDefinition +from form_filler_skill.guided_conversation.guided_conversation_skill import GuidedConversationSkill +from form_filler_skill.guided_conversation.resources import ( + ResourceConstraint, + ResourceConstraintMode, + ResourceConstraintUnit, +) +from openai_client import AzureOpenAIAzureIdentityAuthConfig, AzureOpenAIServiceConfig, create_client +from openai_client.config import first_env_var +from pydantic import BaseModel, Field, HttpUrl +from skill_library import Skill +from skill_library.routine_stack import RoutineStack +from skill_library.run_context import LogEmitter, RunContext +from skill_library.skill_registry import SkillRegistry - # definition = GCDefinition( - # artifact_schema="schema", - # rules="rules", - # conversation_flow="flow", - # conversation_context="context", - # resource_constraint=None, - # ) - # skill = GuidedConversationSkill(language_model=language_model, definition=definition) +@pytest.mark.skip("For manual testing.") +async def test_poem_feedback(): + service_config = AzureOpenAIServiceConfig( + auth_config=AzureOpenAIAzureIdentityAuthConfig(), + azure_openai_endpoint=HttpUrl(first_env_var("azure_openai_endpoint", "assistant__azure_openai_endpoint") or ""), + azure_openai_deployment=first_env_var("azure_openai_deployment", "assistant__azure_openai_deployment") + or "gpt-3.5-turbo", + ) + language_model = create_client(service_config) - # runContext = RunContext() + class Artifact(BaseModel): + student_poem: str = Field(description="The acrostic poem written by the student.") + initial_feedback: str = Field(description="Feedback on the student's final revised poem.") + final_feedback: str = Field(description="Feedback on how the student was able to improve their poem.") + inappropriate_behavior: list[str] = Field( + description=dedent(""" + List any inappropriate behavior the student attempted while chatting with you. + It is ok to leave this field Unanswered if there was none. + """) + ) - # skill.conversation_init_function(context=runContext) - # finished, artifact = skill.conversation_step_function(runContext, "Hello!") + definition = GCDefinition( + artifact_schema=Artifact.model_json_schema(), + rules=[ + "DO NOT write the poem for the student.", + "Terminate the conversation immediately if the students asks for harmful or inappropriate content.", + ], + conversation_flow=dedent(""" + 1. Start by explaining interactively what an acrostic poem is. + 2. Then give the following instructions for how to go ahead and write one: + 1. Choose a word or phrase that will be the subject of your acrostic poem. + 2. Write the letters of your chosen word or phrase vertically down the page. + 3. Think of a word or phrase that starts with each letter of your chosen word or phrase. + 4. Write these words or phrases next to the corresponding letters to create your acrostic poem. + 3. Then give the following example of a poem where the word or phrase is HAPPY: + Having fun with friends all day, + Awesome games that we all play. + Pizza parties on the weekend, + Puppies we bend down to tend, + Yelling yay when we win the game + 4. Finally have the student write their own acrostic poem using the word or phrase of their choice. Encourage them + to be creative and have fun with it. After they write it, you should review it and give them feedback on what they + did well and what they could improve on. Have them revise their poem based on your feedback and then review it again. + """), + conversation_context=dedent(""" + You are working 1 on 1 a 4th grade student who is chatting with you in the computer lab at school while being + supervised by their teacher. + """), + resource_constraint=ResourceConstraint( + quantity=10, + unit=ResourceConstraintUnit.TURNS, + mode=ResourceConstraintMode.EXACT, + ), + ) - pass + # Configure the skill and its dependencies. + drive = Drive(DriveConfig(root=Path(__file__).parent / ".data")) + skill = GuidedConversationSkill( + name="guided_conversation", language_model=language_model, definition=definition, drive=drive + ) + skill_dependency_tree: dict[str, Skill] = {"guided_conversation": skill} + + # Set up a run context. + path = Path(__file__).parent / ".data" + drive = Drive(DriveConfig(root=path)) + routine_stack = RoutineStack(drive) + skill_registry = SkillRegistry(skill_dependency_tree, routine_stack) + runContext = RunContext( + "test-session-1", drive, LogEmitter().emit, routine_stack, skill_registry.run_routine_by_designation + ) + + # Run the skill with it's context. + await skill.conversation_init_function(context=runContext) + + finished = False + while not finished: + user_message = input("You: ") + finished, artifact = await skill.conversation_step_function(runContext, user_message) + + assert artifact is not None + print(artifact) diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/unneeded/base_model_llm.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/unneeded/base_model_llm.py similarity index 100% rename from libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/chat_drivers/unneeded/base_model_llm.py rename to libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/unneeded/base_model_llm.py diff --git a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/conversation_helpers.py b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/unneeded/conversation_helpers.py similarity index 96% rename from libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/conversation_helpers.py rename to libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/unneeded/conversation_helpers.py index 1b9502d3..5c079ae5 100644 --- a/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/conversation_helpers.py +++ b/libraries/python/skills/skills/form-filler-skill/form_filler_skill/guided_conversation/unneeded/conversation_helpers.py @@ -1,16 +1,11 @@ # Copyright (c) Microsoft. All rights reserved. - -# FIXME: Copied code from Semantic Kernel repo, using as-is despite type errors # type: ignore -import logging import time from dataclasses import dataclass, field from enum import StrEnum from typing import Union -from semantic_kernel.contents import ChatMessageContent - class ConversationMessageType(StrEnum): DEFAULT = "default" @@ -18,6 +13,9 @@ class ConversationMessageType(StrEnum): REASONING = "reasoning" +ChatMessageContent = dataclass() + + @dataclass class Conversation: """An abstraction to represent a list of messages and common operations such as adding messages @@ -27,7 +25,6 @@ class Conversation: conversation_messages (list[ChatMessageContent]): A list of ChatMessageContent objects. """ - logger = logging.getLogger(__name__) conversation_messages: list[ChatMessageContent] = field(default_factory=list) def add_messages(self, messages: Union[ChatMessageContent, list[ChatMessageContent], "Conversation", None]) -> None: @@ -44,7 +41,7 @@ def add_messages(self, messages: Union[ChatMessageContent, list[ChatMessageConte self.conversation_messages.extend(messages) elif isinstance(messages, Conversation): self.conversation_messages.extend(messages.conversation_messages) - elif isinstance(messages, ChatMessageContent): + elif isinstance(messages, ChatMessageContent): # noqa: F821 # if ChatMessageContent.metadata doesn't have type, then add default if "type" not in messages.metadata: messages.metadata["type"] = ConversationMessageType.DEFAULT @@ -105,7 +102,7 @@ def get_repr_for_prompt( to_join.append(f"{participant_name}: ") else: to_join.append(f"{participant_name}: {user_string}") - + conversation_string = "\n".join(to_join) return conversation_string diff --git a/libraries/python/skills/skills/form-filler-skill/notebooks/usage.ipynb b/libraries/python/skills/skills/form-filler-skill/notebooks/usage.ipynb new file mode 100644 index 00000000..022fe61f --- /dev/null +++ b/libraries/python/skills/skills/form-filler-skill/notebooks/usage.ipynb @@ -0,0 +1,272 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['/usr/local/lib/python311.zip', '/usr/local/lib/python3.11', '/usr/local/lib/python3.11/lib-dynload', '', '/workspaces/semanticworkbench/libraries/python/skills/skills/form-filler-skill/.venv/lib/python3.11/site-packages', '/workspaces/semanticworkbench/libraries/python/assistant-drive', '/workspaces/semanticworkbench/libraries/python/context', '/workspaces/semanticworkbench/libraries/python/events', '/workspaces/semanticworkbench/libraries/python/skills/skills/form-filler-skill', '/workspaces/semanticworkbench/libraries/python/openai-client', '/workspaces/semanticworkbench/libraries/python/semantic-workbench-api-model', '/workspaces/semanticworkbench/libraries/python/semantic-workbench-assistant', '/workspaces/semanticworkbench/libraries/python/skills/skill-library']\n" + ] + } + ], + "source": [ + "%reload_ext autoreload\n", + "%autoreload 2\n", + "\n", + "import sys\n", + "from pathlib import Path\n", + "import logging\n", + "import json\n", + "\n", + "# Add the src directory to sys.path\n", + "path = str(Path().resolve().parent)\n", + "if path not in sys.path:\n", + " sys.path.insert(0, path)\n", + "\n", + "print(sys.path)\n", + "\n", + "# load_dotenv()\n", + "# print(str(dict(os.environ.items())))\n", + "\n", + "\n", + "LOGGING = {\n", + " \"version\": 1,\n", + " \"disable_existing_loggers\": False,\n", + " \"formatters\": {\n", + " \"json\": {\n", + " \"()\": \"pythonjsonlogger.jsonlogger.JsonFormatter\",\n", + " \"fmt\": \"%(asctime)s %(levelname)s %(name)s %(message)s\",\n", + "\n", + " }\n", + " },\n", + "}\n", + "\n", + "\n", + "# Set up structured logging to a file. All of the cells in this notebook use\n", + "# this logger. Find them at .data/logs.jsonl.\n", + "class JsonFormatter(logging.Formatter):\n", + " def format(self, record) -> str:\n", + " record_dict = record.__dict__\n", + " log_record = {\n", + " 'timestamp': self.formatTime(record, self.datefmt),\n", + " 'level': record.levelname,\n", + " 'session_id': record_dict.get('session_id', None),\n", + " 'run_id': record_dict.get('run_id', None),\n", + " 'message': record.getMessage(),\n", + " 'data': record_dict.get('data', None),\n", + " 'module': record.module,\n", + " 'funcName': record.funcName,\n", + " 'lineNumber': record.lineno,\n", + " 'logger': record.name,\n", + " }\n", + " extra_fields = {\n", + " key: value for key, value in record.__dict__.items() \n", + " if key not in ['levelname', 'msg', 'args', 'exc_info', 'funcName', 'module', 'lineno', 'name', 'message', 'asctime', 'session_id', 'run_id', 'data']\n", + " }\n", + " log_record.update(extra_fields)\n", + " return json.dumps(log_record)\n", + "\n", + "logger = logging.getLogger()\n", + "logger.setLevel(logging.DEBUG)\n", + "modules = ['httpcore.connection', 'httpcore.http11', 'httpcore.sync.connection', 'httpx', 'openai', 'urllib3.connectionpool', 'urllib3.util.retry']\n", + "for module in modules:\n", + " logging.getLogger(module).setLevel(logging.ERROR)\n", + "if logger.hasHandlers():\n", + " logger.handlers.clear()\n", + "data_dir = Path('.data')\n", + "if not data_dir.exists():\n", + " data_dir.mkdir()\n", + "handler = logging.FileHandler(data_dir / 'logs.jsonl')\n", + "handler.setFormatter(JsonFormatter())\n", + "logger.addHandler(handler)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Assistant: Agenda updated\n", + "Assistant: Hello! Let's dive into creating an acrostic poem together. An acrostic poem is a fun type of poem where the first letters of each line spell out a word or a message vertically. Here's how you can make one:\n", + "\n", + "1. Choose a word or phrase that will be the subject of your acrostic poem.\n", + "2. Write the letters of your chosen word or phrase vertically down the page.\n", + "3. Think of a word or phrase that starts with each letter of your chosen word or phrase.\n", + "4. Write these words or phrases next to the corresponding letters to create your acrostic poem.\n", + "\n", + "For example, if you choose the word \"HAPPY,\" it might look like this:\n", + "\n", + "- **H**aving fun with friends all day,\n", + "- **A**wesome games that we all play.\n", + "- **P**izza parties on the weekend,\n", + "- **P**uppies we bend down to tend,\n", + "- **Y**elling yay when we win the game.\n", + "\n", + "Now, it's your turn! Pick a word or phrase you love, and jot down an acrostic poem. Don't forget to have fun and be creative! When you're ready, share it with me, and I'll help you with feedback.\n", + "User: DOG\n" + ] + } + ], + "source": [ + "%reload_ext autoreload\n", + "%autoreload 2\n", + "\n", + "from pathlib import Path\n", + "from textwrap import dedent\n", + "\n", + "from assistant_drive import Drive, DriveConfig\n", + "from form_filler_skill.guided_conversation.definition import GCDefinition\n", + "from form_filler_skill.guided_conversation import GuidedConversationSkill, TUnanswered, UNANSWERED\n", + "from form_filler_skill.guided_conversation.resources import (\n", + " ResourceConstraint,\n", + " ResourceConstraintMode,\n", + " ResourceConstraintUnit,\n", + ")\n", + "from openai_client import AzureOpenAIAzureIdentityAuthConfig, AzureOpenAIServiceConfig, create_client\n", + "from pydantic import BaseModel, Field, HttpUrl\n", + "from skill_library import Skill\n", + "from skill_library.routine_stack import RoutineStack\n", + "from skill_library.run_context import LogEmitter, RunContext\n", + "from skill_library.skill_registry import SkillRegistry\n", + "from openai_client.chat_driver import ChatDriverConfig\n", + "from skill_library import Assistant\n", + "import asyncio\n", + "\n", + "service_config = AzureOpenAIServiceConfig(\n", + " auth_config=AzureOpenAIAzureIdentityAuthConfig(),\n", + " azure_openai_endpoint=HttpUrl(\"https://lightspeed-team-shared-openai-eastus.openai.azure.com/\"),\n", + " azure_openai_deployment=\"gpt-4o\",\n", + ")\n", + "language_model = create_client(service_config)\n", + "\n", + "class Artifact(BaseModel):\n", + " student_poem: str | TUnanswered = Field(description=\"The acrostic poem written by the student.\", default=UNANSWERED)\n", + " initial_feedback: str| TUnanswered = Field(description=\"Feedback on the student's final revised poem.\", default=UNANSWERED)\n", + " final_feedback: str| TUnanswered = Field(description=\"Feedback on how the student was able to improve their poem.\", default=UNANSWERED)\n", + " inappropriate_behavior: list[str]| TUnanswered = Field(\n", + " description=dedent(\"\"\"\n", + " List any inappropriate behavior the student attempted while chatting with you.\n", + " It is ok to leave this field Unanswered if there was none.\n", + " \"\"\"),\n", + " default=UNANSWERED\n", + " )\n", + "\n", + "# artifact_schema = Artifact.model_json_schema()\n", + "resource_constraint = ResourceConstraint(\n", + " quantity=10,\n", + " unit=ResourceConstraintUnit.TURNS,\n", + " mode=ResourceConstraintMode.EXACT,\n", + " )\n", + "definition = GCDefinition(\n", + " artifact_schema=Artifact.model_json_schema(),\n", + " rules=[\n", + " \"DO NOT write the poem for the student.\",\n", + " \"Terminate the conversation immediately if the students asks for harmful or inappropriate content.\",\n", + " ],\n", + " conversation_flow=dedent(\"\"\"\n", + " 1. Start by explaining interactively what an acrostic poem is.\n", + " 2. Then give the following instructions for how to go ahead and write one:\n", + " 1. Choose a word or phrase that will be the subject of your acrostic poem.\n", + " 2. Write the letters of your chosen word or phrase vertically down the page.\n", + " 3. Think of a word or phrase that starts with each letter of your chosen word or phrase.\n", + " 4. Write these words or phrases next to the corresponding letters to create your acrostic poem.\n", + " 3. Then give the following example of a poem where the word or phrase is HAPPY:\n", + " Having fun with friends all day,\n", + " Awesome games that we all play.\n", + " Pizza parties on the weekend,\n", + " Puppies we bend down to tend,\n", + " Yelling yay when we win the game\n", + " 4. Finally have the student write their own acrostic poem using the word or phrase of their choice. Encourage them\n", + " to be creative and have fun with it. After they write it, you should review it and give them feedback on what they\n", + " did well and what they could improve on. Have them revise their poem based on your feedback and then review it again.\n", + " \"\"\"),\n", + " conversation_context=dedent(\"\"\"\n", + " You are working 1 on 1 a 4th grade student who is chatting with you in the computer lab at school while being\n", + " supervised by their teacher.\n", + " \"\"\"),\n", + " resource_constraint=resource_constraint,\n", + ")\n", + "\n", + "# Configure the skill and its dependencies.\n", + "path = Path(\".data/assistant-1\")\n", + "drive = Drive(DriveConfig(root=path))\n", + "skill = GuidedConversationSkill(name=\"guided_conversation\", language_model=language_model, definition=definition, drive=drive.subdrive(\"gc1\"))\n", + "skill_dependency_tree: dict[str, Skill] = {skill.name: skill}\n", + "\n", + "# Set up a run context.\n", + "routine_stack = RoutineStack(drive)\n", + "skill_registry = SkillRegistry(skill_dependency_tree, routine_stack)\n", + "runContext = RunContext(\n", + " \"test-session-1\", drive, LogEmitter().emit, routine_stack, skill_registry.run_routine_by_designation\n", + ")\n", + "\n", + "# Define the assistant.\n", + "chat_driver_config = ChatDriverConfig(\n", + " openai_client=language_model,\n", + " model=\"gpt-4o\",\n", + " instructions=\"You are a helpful assistant.\",\n", + ")\n", + "\n", + "assistant = Assistant(name=\"Alice\", assistant_id=\"gc-assistant-123\", chat_driver_config=chat_driver_config, skills=skill_dependency_tree, startup_routine=\"guided_conversation.conversation\")\n", + "await assistant.clear()\n", + "await assistant.start()\n", + "\n", + "# Run the skill with it's context.\n", + "# if await routine_stack.peek() is None:\n", + "# await routine_stack.push(\"current_frame\")\n", + "# await skill.conversation_init_function(context=runContext, vars={\"artifact\": Artifact()})\n", + "\n", + "# Function that allows user input in a non-blocking manner.\n", + "async def user_input_handler() -> None:\n", + " while True:\n", + " user_input = await asyncio.to_thread(input, \"User: \")\n", + " if user_input == \"\":\n", + " assistant.stop()\n", + " break\n", + " print(f\"User: {user_input}\", flush=True)\n", + " await assistant.put_message(user_input)\n", + "\n", + "\n", + "# Start the user input in a non-blocking way.\n", + "input_task = asyncio.create_task(user_input_handler())\n", + "\n", + "# Start the assistant.\n", + "async for event in assistant.events:\n", + " print(f\"Assistant: {event.message}\", flush=True) # type: ignore\n", + "\n", + "await assistant.wait()\n", + "await input_task\n", + "\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.10" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/libraries/python/skills/skills/form-filler-skill/pyproject.toml b/libraries/python/skills/skills/form-filler-skill/pyproject.toml index c7a4adc1..bde006b8 100644 --- a/libraries/python/skills/skills/form-filler-skill/pyproject.toml +++ b/libraries/python/skills/skills/form-filler-skill/pyproject.toml @@ -6,23 +6,41 @@ authors = [{name="MADE:Explorers"}] readme = "README.md" requires-python = ">=3.11" dependencies = [ - "skill-library>=0.1.0", + "assistant-drive>=0.1.0", "context>=0.1.0", + "datamodel-code-generator>=0.26.3", "events>=0.1.0", "openai-client>=0.1.0", - # "guided-conversation>=0.1.0", + "skill-library>=0.1.0", +] + +[dependency-groups] +dev = [ + "pytest>=8.3.1", + "pytest-asyncio>=0.23.8", + "pytest-repeat>=0.9.3", + "ipykernel>=6.29.4", ] [tool.uv] package = true [tool.uv.sources] -skill-library = { path = "../../skill-library", editable= true } +assistant-drive = { path = "../../../assistant-drive", editable = true } context = { path = "../../../context", editable = true } events = { path = "../../../events", editable = true } openai-client = { path = "../../../openai-client", editable = true } -# guided-conversation = { path = "../../../guided-conversation", editable = true } +skill-library = { path = "../../skill-library", editable= true } [build-system] requires = ["hatchling"] build-backend = "hatchling.build" + +[tool.pytest.ini_options] +addopts = "-vv" +log_cli = true +log_cli_level = "WARNING" +log_cli_format = "%(asctime)s | %(levelname)-7s | %(name)s | %(message)s" +testpaths = ["tests"] +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" diff --git a/libraries/python/skills/skills/form-filler-skill/uv.lock b/libraries/python/skills/skills/form-filler-skill/uv.lock index cfb79cfc..91dfd6d2 100644 --- a/libraries/python/skills/skills/form-filler-skill/uv.lock +++ b/libraries/python/skills/skills/form-filler-skill/uv.lock @@ -1,8 +1,9 @@ version = 1 requires-python = ">=3.11" resolution-markers = [ - 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b/libraries/python/skills/skills/posix-skill/posix_skill/posix_skill.py index 347c6465..8fa01bf6 100644 --- a/libraries/python/skills/skills/posix-skill/posix_skill/posix_skill.py +++ b/libraries/python/skills/skills/posix-skill/posix_skill/posix_skill.py @@ -15,6 +15,7 @@ class PosixSkill(Skill): def __init__( self, + name: str, sandbox_dir: Path, chat_driver_config: ChatDriverConfig, mount_dir: str = "/mnt/data", @@ -50,7 +51,7 @@ def __init__( # Initialize the skill! super().__init__( - name=NAME, + name=name, description=DESCRIPTION, chat_driver_config=chat_driver_config, actions=functions,