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7615c7b83b
Rename the `ChatMessage` and `AgentEvent` base classes to `BaseChatMessage` and `BaseAgentEvent`. Bring back the `ChatMessage` and `AgentEvent` as union of built-in concrete types to avoid breaking existing applications that depends on Pydantic serialization. Why? Many existing code uses containers like this: ```python class AppMessage(BaseModel): name: str message: ChatMessage # Serialization is this: m = AppMessage(...) m.model_dump_json() # Fields like HandoffMessage.target will be lost because it is now treated as a base class without content or target fields. ``` The assumption on `ChatMessage` or `AgentEvent` to be a union of concrete types could be in many existing code bases. So this PR brings back the union types, while keep method type hints such as those on `on_messages` to use the `BaseChatMessage` and `BaseAgentEvent` base classes for flexibility.
106 lines
3.8 KiB
Python
106 lines
3.8 KiB
Python
import os
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from typing import List, Sequence
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import pytest
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from autogen_agentchat.agents import AssistantAgent
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from autogen_agentchat.base import TaskResult
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from autogen_agentchat.messages import BaseAgentEvent, BaseChatMessage
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from autogen_agentchat.teams import SelectorGroupChat
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from autogen_agentchat.ui import Console
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from autogen_core.models import ChatCompletionClient
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from autogen_ext.models.openai import OpenAIChatCompletionClient
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async def _test_selector_group_chat(model_client: ChatCompletionClient) -> None:
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assistant = AssistantAgent(
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"assistant",
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description="A helpful assistant agent.",
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model_client=model_client,
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system_message="You are a helpful assistant.",
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)
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critic = AssistantAgent(
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"critic",
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description="A critic agent to provide feedback.",
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model_client=model_client,
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system_message="Provide feedback.",
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)
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team = SelectorGroupChat([assistant, critic], model_client=model_client, max_turns=2)
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await Console(team.run_stream(task="Draft a short email about organizing a holiday party for new year."))
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async def _test_selector_group_chat_with_candidate_func(model_client: ChatCompletionClient) -> None:
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filtered_participants = ["developer", "tester"]
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def dummy_candidate_func(thread: Sequence[BaseAgentEvent | BaseChatMessage]) -> List[str]:
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# Dummy candidate function that will return
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# only return developer and reviewer
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return filtered_participants
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developer = AssistantAgent(
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"developer",
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description="Writes and implements code based on requirements.",
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model_client=model_client,
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system_message="You are a software developer working on a new feature.",
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)
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tester = AssistantAgent(
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"tester",
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description="Writes and executes test cases to validate the implementation.",
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model_client=model_client,
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system_message="You are a software tester ensuring the feature works correctly.",
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)
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project_manager = AssistantAgent(
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"project_manager",
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description="Oversees the project and ensures alignment with the broader goals.",
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model_client=model_client,
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system_message="You are a project manager ensuring the team meets the project goals.",
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)
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team = SelectorGroupChat(
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participants=[developer, tester, project_manager],
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model_client=model_client,
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max_turns=3,
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candidate_func=dummy_candidate_func,
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)
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task = "Create a detailed implementation plan for adding dark mode in a React app and review it for feasibility and improvements."
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async for message in team.run_stream(task=task):
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if not isinstance(message, TaskResult):
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if message.source == "user": # ignore the first 'user' message
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continue
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assert message.source in filtered_participants, "Candidate function didn't filter the participants"
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@pytest.mark.asyncio
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async def test_selector_group_chat_gemini() -> None:
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try:
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api_key = os.environ["GEMINI_API_KEY"]
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except KeyError:
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pytest.skip("GEMINI_API_KEY not set in environment variables.")
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model_client = OpenAIChatCompletionClient(
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model="gemini-1.5-flash",
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api_key=api_key,
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)
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await _test_selector_group_chat(model_client)
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await _test_selector_group_chat_with_candidate_func(model_client)
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@pytest.mark.asyncio
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async def test_selector_group_chat_openai() -> None:
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try:
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api_key = os.environ["OPENAI_API_KEY"]
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except KeyError:
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pytest.skip("OPENAI_API_KEY not set in environment variables.")
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model_client = OpenAIChatCompletionClient(
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model="gpt-4o-mini",
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api_key=api_key,
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)
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await _test_selector_group_chat(model_client)
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await _test_selector_group_chat_with_candidate_func(model_client)
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