GroupChatTarget

def can_resolve_for_speaker_selection(self) -> bool:
    """Check if the target can resolve for speaker selection. For GroupChatTarget the chat must be encapsulated into an agent."""
    return False

def resolve(
    self,
    groupchat: "GroupChat",
    current_agent: "ConversableAgent",
    user_agent: Optional["ConversableAgent"],
) -> SpeakerSelectionResult:
    """Resolve to the nested chat configuration."""
    raise NotImplementedError(
        "GroupChatTarget does not support the resolve method. An agent should be used to encapsulate this nested chat and then the target changed to an AgentTarget."
    )

def display_name(self) -> str:
    """Get the display name for the target."""
    return "a group chat"

def normalized_name(self) -> str:
    """Get a normalized name for the target that has no spaces, used for function calling."""
    return "group_chat"

def needs_agent_wrapper(self) -> bool:
    """Check if the target needs to be wrapped in an agent. GroupChatTarget must be wrapped in an agent."""
    return True

def create_wrapper_agent(self, parent_agent: "ConversableAgent", index: int) -> "ConversableAgent":
    """Create a wrapper agent for the group chat."""
    from autogen.agentchat import initiate_group_chat

    from ...conversable_agent import ConversableAgent  # to avoid circular import

    # Create the wrapper agent with a name that identifies it as a wrapped group chat
    group_chat_agent = ConversableAgent(
        name=f"{__AGENT_WRAPPER_PREFIX__}group_{parent_agent.name}_{index + 1}",
        # Copy LLM config from parent agent to ensure it can generate replies if needed
        llm_config=parent_agent.llm_config,
    )

    # Store the config directly on the agent
    group_chat_agent._group_chat_config = self.group_chat_config  # type: ignore[attr-defined]

    # Define the reply function that will run the group chat
    def group_chat_reply(
        agent: "ConversableAgent",
        messages: Optional[list[dict[str, Any]]] = None,
        sender: Optional["Agent"] = None,
        config: Optional[Any] = None,
    ) -> tuple[bool, Optional[dict[str, Any]]]:
        """Run the inner group chat and return its results as a reply."""
        # Get the configuration stored directly on the agent
        group_config = agent._group_chat_config  # type: ignore[attr-defined]

        # Pull through the second last message from the outer chat (the last message will be the handoff message)
        # This may need work to make sure we get the right message(s) from the outer chat
        message = (
            messages[-2]["content"]
            if messages and len(messages) >= 2 and "content" in messages[-2]
            else "No message to pass through."
        )

        try:
            # Run the group chat with direct agent references from the config
            result, _, _ = initiate_group_chat(
                pattern=group_config.pattern,
                messages=message,
                max_rounds=group_config.max_rounds,
            )

            # Return the summary from the chat result summary
            return True, {"content": result.summary}

        except Exception as e:
            # Handle any errors during execution
            return True, {"content": f"Error running group chat: {str(e)}"}

    # Register the reply function with the wrapper agent
    group_chat_agent.register_reply(
        trigger=[ConversableAgent, None],
        reply_func=group_chat_reply,
        remove_other_reply_funcs=True,  # Use only this reply function
    )

    # After the group chat completes, transition back to the parent agent
    group_chat_agent.handoffs.set_after_work(AgentTarget(parent_agent))

    return group_chat_agent