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			201 lines
		
	
	
		
			8.5 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			201 lines
		
	
	
		
			8.5 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import asyncio
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| import json
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| import logging
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| from typing import Sequence
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| 
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| import pytest
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| from autogen_agentchat import EVENT_LOGGER_NAME
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| from autogen_agentchat.agents import (
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|     BaseChatAgent,
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| )
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| from autogen_agentchat.base import Response
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| from autogen_agentchat.messages import (
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|     ChatMessage,
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|     TextMessage,
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| )
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| from autogen_agentchat.teams import (
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|     MagenticOneGroupChat,
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| )
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| from autogen_agentchat.teams._group_chat._magentic_one._magentic_one_orchestrator import MagenticOneOrchestrator
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| from autogen_core import AgentId, CancellationToken
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| from autogen_ext.models.replay import ReplayChatCompletionClient
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| from utils import FileLogHandler
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| 
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| logger = logging.getLogger(EVENT_LOGGER_NAME)
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| logger.setLevel(logging.DEBUG)
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| logger.addHandler(FileLogHandler("test_magentic_one_group_chat.log"))
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| 
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| 
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| class _EchoAgent(BaseChatAgent):
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|     def __init__(self, name: str, description: str) -> None:
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|         super().__init__(name, description)
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|         self._last_message: str | None = None
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|         self._total_messages = 0
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| 
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|     @property
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|     def produced_message_types(self) -> Sequence[type[ChatMessage]]:
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|         return (TextMessage,)
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| 
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|     @property
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|     def total_messages(self) -> int:
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|         return self._total_messages
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| 
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|     async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:
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|         if len(messages) > 0:
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|             assert isinstance(messages[0], TextMessage)
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|             self._last_message = messages[0].content
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|             self._total_messages += 1
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|             return Response(chat_message=TextMessage(content=messages[0].content, source=self.name))
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|         else:
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|             assert self._last_message is not None
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|             self._total_messages += 1
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|             return Response(chat_message=TextMessage(content=self._last_message, source=self.name))
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| 
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|     async def on_reset(self, cancellation_token: CancellationToken) -> None:
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|         self._last_message = None
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| 
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| 
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| @pytest.mark.asyncio
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| async def test_magentic_one_group_chat_cancellation() -> None:
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|     agent_1 = _EchoAgent("agent_1", description="echo agent 1")
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|     agent_2 = _EchoAgent("agent_2", description="echo agent 2")
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|     agent_3 = _EchoAgent("agent_3", description="echo agent 3")
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|     agent_4 = _EchoAgent("agent_4", description="echo agent 4")
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| 
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|     model_client = ReplayChatCompletionClient(
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|         chat_completions=["test", "test", json.dumps({"is_request_satisfied": {"answer": True, "reason": "test"}})],
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|     )
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| 
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|     # Set max_turns to a large number to avoid stopping due to max_turns before cancellation.
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|     team = MagenticOneGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], model_client=model_client)
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|     cancellation_token = CancellationToken()
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|     run_task = asyncio.create_task(
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|         team.run(
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|             task="Write a program that prints 'Hello, world!'",
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|             cancellation_token=cancellation_token,
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|         )
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|     )
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| 
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|     # Cancel the task.
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|     cancellation_token.cancel()
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|     with pytest.raises(asyncio.CancelledError):
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|         await run_task
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| 
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| 
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| @pytest.mark.asyncio
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| async def test_magentic_one_group_chat_basic() -> None:
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|     agent_1 = _EchoAgent("agent_1", description="echo agent 1")
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|     agent_2 = _EchoAgent("agent_2", description="echo agent 2")
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|     agent_3 = _EchoAgent("agent_3", description="echo agent 3")
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|     agent_4 = _EchoAgent("agent_4", description="echo agent 4")
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| 
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|     model_client = ReplayChatCompletionClient(
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|         chat_completions=[
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|             "No facts",
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|             "No plan",
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|             json.dumps(
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|                 {
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|                     "is_request_satisfied": {"answer": False, "reason": "test"},
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|                     "is_progress_being_made": {"answer": True, "reason": "test"},
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|                     "is_in_loop": {"answer": False, "reason": "test"},
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|                     "instruction_or_question": {"answer": "Continue task", "reason": "test"},
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|                     "next_speaker": {"answer": "agent_1", "reason": "test"},
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|                 }
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|             ),
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|             json.dumps(
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|                 {
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|                     "is_request_satisfied": {"answer": True, "reason": "Because"},
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|                     "is_progress_being_made": {"answer": True, "reason": "test"},
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|                     "is_in_loop": {"answer": False, "reason": "test"},
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|                     "instruction_or_question": {"answer": "Task completed", "reason": "Because"},
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|                     "next_speaker": {"answer": "agent_1", "reason": "test"},
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|                 }
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|             ),
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|             "print('Hello, world!')",
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|         ],
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|     )
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| 
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|     team = MagenticOneGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], model_client=model_client)
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|     result = await team.run(task="Write a program that prints 'Hello, world!'")
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|     assert len(result.messages) == 5
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|     assert result.messages[2].content == "Continue task"
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|     assert result.messages[4].content == "print('Hello, world!')"
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|     assert result.stop_reason is not None and result.stop_reason == "Because"
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| 
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|     # Test save and load.
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|     state = await team.save_state()
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|     team2 = MagenticOneGroupChat(participants=[agent_1, agent_2, agent_3, agent_4], model_client=model_client)
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|     await team2.load_state(state)
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|     state2 = await team2.save_state()
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|     assert state == state2
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|     manager_1 = await team._runtime.try_get_underlying_agent_instance(  # pyright: ignore
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|         AgentId("group_chat_manager", team._team_id),  # pyright: ignore
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|         MagenticOneOrchestrator,  # pyright: ignore
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|     )  # pyright: ignore
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|     manager_2 = await team2._runtime.try_get_underlying_agent_instance(  # pyright: ignore
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|         AgentId("group_chat_manager", team2._team_id),  # pyright: ignore
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|         MagenticOneOrchestrator,  # pyright: ignore
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|     )  # pyright: ignore
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|     assert manager_1._message_thread == manager_2._message_thread  # pyright: ignore
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|     assert manager_1._task == manager_2._task  # pyright: ignore
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|     assert manager_1._facts == manager_2._facts  # pyright: ignore
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|     assert manager_1._plan == manager_2._plan  # pyright: ignore
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|     assert manager_1._n_rounds == manager_2._n_rounds  # pyright: ignore
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|     assert manager_1._n_stalls == manager_2._n_stalls  # pyright: ignore
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| 
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| 
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| @pytest.mark.asyncio
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| async def test_magentic_one_group_chat_with_stalls() -> None:
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|     agent_1 = _EchoAgent("agent_1", description="echo agent 1")
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|     agent_2 = _EchoAgent("agent_2", description="echo agent 2")
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|     agent_3 = _EchoAgent("agent_3", description="echo agent 3")
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|     agent_4 = _EchoAgent("agent_4", description="echo agent 4")
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| 
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|     model_client = ReplayChatCompletionClient(
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|         chat_completions=[
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|             "No facts",
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|             "No plan",
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|             json.dumps(
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|                 {
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|                     "is_request_satisfied": {"answer": False, "reason": "test"},
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|                     "is_progress_being_made": {"answer": False, "reason": "test"},
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|                     "is_in_loop": {"answer": True, "reason": "test"},
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|                     "instruction_or_question": {"answer": "Stalling", "reason": "test"},
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|                     "next_speaker": {"answer": "agent_1", "reason": "test"},
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|                 }
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|             ),
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|             json.dumps(
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|                 {
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|                     "is_request_satisfied": {"answer": False, "reason": "test"},
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|                     "is_progress_being_made": {"answer": False, "reason": "test"},
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|                     "is_in_loop": {"answer": True, "reason": "test"},
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|                     "instruction_or_question": {"answer": "Stalling again", "reason": "test"},
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|                     "next_speaker": {"answer": "agent_2", "reason": "test"},
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|                 }
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|             ),
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|             "No facts2",
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|             "No plan2",
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|             json.dumps(
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|                 {
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|                     "is_request_satisfied": {"answer": True, "reason": "test"},
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|                     "is_progress_being_made": {"answer": True, "reason": "test"},
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|                     "is_in_loop": {"answer": False, "reason": "test"},
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|                     "instruction_or_question": {"answer": "Task completed", "reason": "test"},
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|                     "next_speaker": {"answer": "agent_3", "reason": "test"},
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|                 }
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|             ),
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|             "print('Hello, world!')",
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|         ],
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|     )
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| 
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|     team = MagenticOneGroupChat(
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|         participants=[agent_1, agent_2, agent_3, agent_4], model_client=model_client, max_stalls=2
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|     )
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|     result = await team.run(task="Write a program that prints 'Hello, world!'")
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|     assert len(result.messages) == 6
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|     assert isinstance(result.messages[1].content, str)
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|     assert result.messages[1].content.startswith("\nWe are working to address the following user request:")
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|     assert isinstance(result.messages[4].content, str)
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|     assert result.messages[4].content.startswith("\nWe are working to address the following user request:")
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|     assert result.stop_reason is not None and result.stop_reason == "test"
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