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			<!-- Thank you for your contribution! Please review https://microsoft.github.io/autogen/docs/Contribute before opening a pull request. --> <!-- Please add a reviewer to the assignee section when you create a PR. If you don't have the access to it, we will shortly find a reviewer and assign them to your PR. --> ## Why are these changes needed? <!-- Please give a short summary of the change and the problem this solves. --> This PR makes it clear which agent is speaking per message in the Chainlit team sample. Previously, messages would be exchanged without showing who is communicating. ## Related issue number <!-- For example: "Closes #1234" --> Closes #5609 ## Checks - [x] I've included any doc changes needed for <https://microsoft.github.io/autogen/>. See <https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to build and test documentation locally. - [x] I've added tests (if relevant) corresponding to the changes introduced in this PR. - [x] I've made sure all auto checks have passed. Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
		
			
				
	
	
		
			101 lines
		
	
	
		
			3.9 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			101 lines
		
	
	
		
			3.9 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| from typing import List, cast
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| 
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| import chainlit as cl
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| import yaml
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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.conditions import TextMentionTermination
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| from autogen_agentchat.messages import ModelClientStreamingChunkEvent, TextMessage
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| from autogen_agentchat.teams import RoundRobinGroupChat
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| from autogen_core import CancellationToken
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| from autogen_core.models import ChatCompletionClient
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| 
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| 
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| @cl.on_chat_start  # type: ignore
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| async def start_chat() -> None:
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|     # Load model configuration and create the model client.
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|     with open("model_config.yaml", "r") as f:
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|         model_config = yaml.safe_load(f)
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|     model_client = ChatCompletionClient.load_component(model_config)
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| 
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|     # Create the assistant agent.
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|     assistant = AssistantAgent(
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|         name="assistant",
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|         model_client=model_client,
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|         system_message="You are a helpful assistant.",
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|         model_client_stream=True,  # Enable model client streaming.
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|     )
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| 
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|     # Create the critic agent.
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|     critic = AssistantAgent(
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|         name="critic",
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|         model_client=model_client,
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|         system_message="You are a critic. Provide constructive feedback. "
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|         "Respond with 'APPROVE' if your feedback has been addressed.",
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|         model_client_stream=True,  # Enable model client streaming.
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|     )
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| 
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|     # Termination condition.
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|     termination = TextMentionTermination("APPROVE", sources=["critic"])
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| 
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|     # Chain the assistant and critic agents using RoundRobinGroupChat.
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|     group_chat = RoundRobinGroupChat([assistant, critic], termination_condition=termination)
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| 
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|     # Set the assistant agent in the user session.
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|     cl.user_session.set("prompt_history", "")  # type: ignore
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|     cl.user_session.set("team", group_chat)  # type: ignore
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| 
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| 
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| @cl.set_starters  # type: ignore
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| async def set_starts() -> List[cl.Starter]:
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|     return [
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|         cl.Starter(
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|             label="Poem Writing",
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|             message="Write a poem about the ocean.",
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|         ),
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|         cl.Starter(
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|             label="Story Writing",
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|             message="Write a story about a detective solving a mystery.",
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|         ),
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|         cl.Starter(
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|             label="Write Code",
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|             message="Write a function that merge two list of numbers into single sorted list.",
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|         ),
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|     ]
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| 
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| 
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| @cl.on_message  # type: ignore
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| async def chat(message: cl.Message) -> None:
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|     # Get the team from the user session.
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|     team = cast(RoundRobinGroupChat, cl.user_session.get("team"))  # type: ignore
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|     # Streaming response message.
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|     streaming_response: cl.Message | None = None
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|     # Stream the messages from the team.
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|     async for msg in team.run_stream(
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|         task=[TextMessage(content=message.content, source="user")],
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|         cancellation_token=CancellationToken(),
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|     ):
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|         if isinstance(msg, ModelClientStreamingChunkEvent):
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|             # Stream the model client response to the user.
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|             if streaming_response is None:
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|                 # Start a new streaming response.
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|                 streaming_response = cl.Message(content=msg.source + ": ", author=msg.source)
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|             await streaming_response.stream_token(msg.content)
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|         elif streaming_response is not None:
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|             # Done streaming the model client response.
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|             # We can skip the current message as it is just the complete message
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|             # of the streaming response.
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|             await streaming_response.send()
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|             # Reset the streaming response so we won't enter this block again
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|             # until the next streaming response is complete.
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|             streaming_response = None
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|         elif isinstance(msg, TaskResult):
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|             # Send the task termination message.
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|             final_message = "Task terminated. "
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|             if msg.stop_reason:
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|                 final_message += msg.stop_reason
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|             await cl.Message(content=final_message).send()
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|         else:
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|             # Skip all other message types.
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|             pass
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