CoACT initialize (#292)
This commit is contained in:
Linxin Song
237
mm_agents/coact/autogen/agentchat/group/multi_agent_chat.py
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237
mm_agents/coact/autogen/agentchat/group/multi_agent_chat.py
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
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#
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# SPDX-License-Identifier: Apache-2.0
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import asyncio
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import threading
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from typing import TYPE_CHECKING, Any, Union
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from ...doc_utils import export_module
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from ...events.agent_events import ErrorEvent, RunCompletionEvent
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from ...io.base import IOStream
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from ...io.run_response import AsyncRunResponse, AsyncRunResponseProtocol, RunResponse, RunResponseProtocol
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from ...io.thread_io_stream import AsyncThreadIOStream, ThreadIOStream
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from ..chat import ChatResult
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from .context_variables import ContextVariables
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from .group_utils import cleanup_temp_user_messages
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if TYPE_CHECKING:
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from ..agent import Agent
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from .patterns.pattern import Pattern
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__all__ = [
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"a_initiate_group_chat",
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"a_run_group_chat",
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"initiate_group_chat",
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"run_group_chat",
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]
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@export_module("autogen")
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def initiate_group_chat(
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pattern: "Pattern",
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messages: Union[list[dict[str, Any]], str],
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max_rounds: int = 20,
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) -> tuple[ChatResult, ContextVariables, "Agent"]:
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"""Initialize and run a group chat using a pattern for configuration.
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Args:
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pattern: Pattern object that encapsulates the chat configuration.
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messages: Initial message(s).
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max_rounds: Maximum number of conversation rounds.
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Returns:
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ChatResult: Conversations chat history.
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ContextVariables: Updated Context variables.
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"ConversableAgent": Last speaker.
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"""
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# Let the pattern prepare the group chat and all its components
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# Only passing the necessary parameters that aren't already in the pattern
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(
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_, # agents,
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_, # wrapped_agents,
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_, # user_agent,
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context_variables,
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_, # initial_agent,
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_, # group_after_work,
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_, # tool_execution,
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_, # groupchat,
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manager,
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processed_messages,
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last_agent,
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_, # group_agent_names,
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_, # temp_user_list,
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) = pattern.prepare_group_chat(
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max_rounds=max_rounds,
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messages=messages,
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)
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# Start or resume the conversation
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if len(processed_messages) > 1:
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last_agent, last_message = manager.resume(messages=processed_messages)
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clear_history = False
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else:
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last_message = processed_messages[0]
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clear_history = True
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if last_agent is None:
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raise ValueError("No agent selected to start the conversation")
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chat_result = last_agent.initiate_chat(
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manager,
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message=last_message,
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clear_history=clear_history,
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summary_method=pattern.summary_method,
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)
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cleanup_temp_user_messages(chat_result)
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return chat_result, context_variables, manager.last_speaker
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@export_module("autogen.agentchat")
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async def a_initiate_group_chat(
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pattern: "Pattern",
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messages: Union[list[dict[str, Any]], str],
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max_rounds: int = 20,
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) -> tuple[ChatResult, ContextVariables, "Agent"]:
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"""Initialize and run a group chat using a pattern for configuration, asynchronously.
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Args:
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pattern: Pattern object that encapsulates the chat configuration.
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messages: Initial message(s).
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max_rounds: Maximum number of conversation rounds.
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Returns:
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ChatResult: Conversations chat history.
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ContextVariables: Updated Context variables.
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"ConversableAgent": Last speaker.
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"""
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# Let the pattern prepare the group chat and all its components
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# Only passing the necessary parameters that aren't already in the pattern
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(
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_, # agents,
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_, # wrapped_agents,
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_, # user_agent,
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context_variables,
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_, # initial_agent,
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_, # group_after_work,
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_, # tool_execution,
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_, # groupchat,
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manager,
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processed_messages,
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last_agent,
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_, # group_agent_names,
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_, # temp_user_list,
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) = pattern.prepare_group_chat(
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max_rounds=max_rounds,
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messages=messages,
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)
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# Start or resume the conversation
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if len(processed_messages) > 1:
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last_agent, last_message = await manager.a_resume(messages=processed_messages)
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clear_history = False
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else:
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last_message = processed_messages[0]
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clear_history = True
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if last_agent is None:
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raise ValueError("No agent selected to start the conversation")
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chat_result = await last_agent.a_initiate_chat(
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manager,
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message=last_message, # type: ignore[arg-type]
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clear_history=clear_history,
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summary_method=pattern.summary_method,
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)
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cleanup_temp_user_messages(chat_result)
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return chat_result, context_variables, manager.last_speaker
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@export_module("autogen.agentchat")
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def run_group_chat(
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pattern: "Pattern",
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messages: Union[list[dict[str, Any]], str],
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max_rounds: int = 20,
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) -> RunResponseProtocol:
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iostream = ThreadIOStream()
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# todo: add agents
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response = RunResponse(iostream, agents=[])
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def _initiate_group_chat(
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pattern: "Pattern" = pattern,
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messages: Union[list[dict[str, Any]], str] = messages,
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max_rounds: int = max_rounds,
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iostream: ThreadIOStream = iostream,
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response: RunResponse = response,
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) -> None:
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with IOStream.set_default(iostream):
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try:
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chat_result, context_vars, agent = initiate_group_chat(
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pattern=pattern,
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messages=messages,
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max_rounds=max_rounds,
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)
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IOStream.get_default().send(
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RunCompletionEvent( # type: ignore[call-arg]
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history=chat_result.chat_history,
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summary=chat_result.summary,
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cost=chat_result.cost,
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last_speaker=agent.name,
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context_variables=context_vars,
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)
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)
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except Exception as e:
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response.iostream.send(ErrorEvent(error=e)) # type: ignore[call-arg]
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threading.Thread(
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target=_initiate_group_chat,
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).start()
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return response
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@export_module("autogen.agentchat")
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async def a_run_group_chat(
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pattern: "Pattern",
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messages: Union[list[dict[str, Any]], str],
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max_rounds: int = 20,
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) -> AsyncRunResponseProtocol:
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iostream = AsyncThreadIOStream()
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# todo: add agents
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response = AsyncRunResponse(iostream, agents=[])
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async def _initiate_group_chat(
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pattern: "Pattern" = pattern,
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messages: Union[list[dict[str, Any]], str] = messages,
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max_rounds: int = max_rounds,
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iostream: AsyncThreadIOStream = iostream,
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response: AsyncRunResponse = response,
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) -> None:
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with IOStream.set_default(iostream):
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try:
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chat_result, context_vars, agent = await a_initiate_group_chat(
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pattern=pattern,
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messages=messages,
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max_rounds=max_rounds,
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)
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IOStream.get_default().send(
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RunCompletionEvent( # type: ignore[call-arg]
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history=chat_result.chat_history,
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summary=chat_result.summary,
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cost=chat_result.cost,
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last_speaker=agent.name,
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context_variables=context_vars,
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)
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)
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except Exception as e:
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response.iostream.send(ErrorEvent(error=e)) # type: ignore[call-arg]
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asyncio.create_task(_initiate_group_chat())
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return response
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