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88c895fd48
* Separate agent and team examples * Add streaming output * Refactor to better use the chainlit API * Removed the user proxy example -- this needs a bit more work to improve the presentation on the ChainLit interface. --------- Co-authored-by: Victor Dibia <victordibia@microsoft.com>
69 lines
2.4 KiB
Python
69 lines
2.4 KiB
Python
from typing import List, cast
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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 Response
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from autogen_agentchat.messages import ModelClientStreamingChunkEvent, TextMessage
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from autogen_core import CancellationToken
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from autogen_core.models import ChatCompletionClient
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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="Greetings",
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message="Hello! What can you help me with today?",
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),
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cl.Starter(
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label="Weather",
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message="Find the weather in New York City.",
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),
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]
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@cl.step(type="tool") # type: ignore
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async def get_weather(city: str) -> str:
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return f"The weather in {city} is 73 degrees and Sunny."
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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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# Create the assistant agent with the get_weather tool.
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assistant = AssistantAgent(
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name="assistant",
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tools=[get_weather],
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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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reflect_on_tool_use=True, # Reflect on tool use.
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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("agent", assistant) # type: ignore
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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 assistant agent from the user session.
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agent = cast(AssistantAgent, cl.user_session.get("agent")) # type: ignore
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# Construct the response message.
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response = cl.Message(content="")
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async for msg in agent.on_messages_stream(
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messages=[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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await response.stream_token(msg.content)
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elif isinstance(msg, Response):
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# Done streaming the model client response. Send the message.
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await response.send()
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