213 lines
7.7 KiB
Python
213 lines
7.7 KiB
Python
import json
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import logging
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import os
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from typing import Any, Awaitable, Callable, Optional, Sequence
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import aiofiles
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import yaml
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from autogen_agentchat.agents import AssistantAgent, UserProxyAgent
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from autogen_agentchat.base import TaskResult
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from autogen_agentchat.messages import TextMessage, UserInputRequestedEvent
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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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from fastapi import FastAPI, HTTPException, WebSocket, WebSocketDisconnect
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import FileResponse
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from fastapi.staticfiles import StaticFiles
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from autogen_ext.models.openai import OpenAIChatCompletionClient
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from autogen_agentchat.conditions import MaxMessageTermination, TextMentionTermination
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from autogen_agentchat.teams import SelectorGroupChat, RoundRobinGroupChat
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from autogen_agentchat.messages import AgentEvent, ChatMessage, TextMessage, ToolCallExecutionEvent
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from constant import MODEL, OPENAI_API_KEY, OPENAI_BASE_URL
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from scientist_team import create_scientist_team
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from engineer_team import create_engineer_team
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from robot_platform import create_robot_team
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from analyst_team import create_analyst_team
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from utils import load_agent_configs
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async def get_team(
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user_input_func: Callable[[str, Optional[CancellationToken]], Awaitable[str]],
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) -> RoundRobinGroupChat | SelectorGroupChat:
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# Create the team.
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scientist_team = create_scientist_team(model_client=model_client)
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engineer_team = create_engineer_team()
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robot_platform = create_robot_team()
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analyst_team = create_analyst_team()
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user = UserProxyAgent(
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name="user",
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input_func=user_input_func, # Use the user input function.
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)
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cur_path = os.path.dirname(os.path.abspath(__file__))
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planning_agent_system_message = load_agent_configs(os.path.join(cur_path, "agent_config/planning.yaml"))
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planning_agent = AssistantAgent(
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"PlanningAgent",
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description="An agent for planning tasks, this agent should be the first to engage when given a new task.",
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model_client=model_client,
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system_message=planning_agent_system_message["PlanningAgent"],
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reflect_on_tool_use=False
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)
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# The termination condition is a combination of text mention termination and max message termination.
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text_mention_termination = TextMentionTermination("TERMINATE")
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max_messages_termination = MaxMessageTermination(max_messages=200)
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termination = text_mention_termination | max_messages_termination
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# The selector function is a function that takes the current message thread of the group chat
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# and returns the next speaker's name. If None is returned, the LLM-based selection method will be used.
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def selector_func(messages: Sequence[AgentEvent | ChatMessage]) -> str | None:
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if messages[-1].source != planning_agent.name:
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return planning_agent.name # Always return to the planning agent after the other agents have spoken.
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elif "HUMAN" in messages[-1].content:
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return user.name
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return None
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team = SelectorGroupChat(
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[planning_agent, user, scientist_team, engineer_team, robot_platform, analyst_team],
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model_client=model_client, # Use a smaller model for the selector.
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termination_condition=termination,
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selector_func=selector_func,
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)
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# Load state from file.
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if not os.path.exists(state_path):
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return team
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async with aiofiles.open(state_path, "r") as file:
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state = json.loads(await file.read())
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await team.load_state(state)
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return team
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logger = logging.getLogger(__name__)
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app = FastAPI()
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current_task = None # 用于跟踪当前任务
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# Add CORS middleware
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"], # Allows all origins
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allow_credentials=True,
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allow_methods=["*"], # Allows all methods
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allow_headers=["*"], # Allows all headers
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)
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model_config_path = "model_config.yaml"
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state_path = "team_state.json"
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history_path = "team_history.json"
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# Serve static files
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app.mount("/static", StaticFiles(directory="."), name="static")
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@app.get("/")
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async def root():
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"""Serve the chat interface HTML file."""
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return FileResponse("app_team.html")
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model_client = OpenAIChatCompletionClient(
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model=MODEL,
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base_url=OPENAI_BASE_URL,
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api_key=OPENAI_API_KEY,
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model_info={
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"vision": True,
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"function_calling": True,
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"json_output": True,
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"family": "unknown",
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},
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)
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async def get_history() -> list[dict[str, Any]]:
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"""Get chat history from file."""
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if not os.path.exists(history_path):
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return []
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async with aiofiles.open(history_path, "r") as file:
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return json.loads(await file.read())
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@app.get("/history")
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async def history() -> list[dict[str, Any]]:
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try:
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return await get_history()
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e)) from e
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@app.websocket("/ws/chat")
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async def chat(websocket: WebSocket):
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await websocket.accept()
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# User input function used by the team.
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async def _user_input(prompt: str, cancellation_token: CancellationToken | None) -> str:
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data = await websocket.receive_json()
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# message = TextMessage.model_validate(data)
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# return message.content
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return data['content']
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try:
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while True:
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# Get user message.
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data = await websocket.receive_json()
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# request = TextMessage.model_validate(data)
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request = data['content']
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try:
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# Get the team and respond to the message.
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team = await get_team(_user_input)
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history = await get_history()
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stream = team.run_stream(task=request)
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async for message in stream:
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if isinstance(message, TaskResult):
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continue
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print(f"----------------{message.source}----------------\n {message.content}")
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await websocket.send_json(message.model_dump())
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if not isinstance(message, UserInputRequestedEvent):
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# Don't save user input events to history.
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history.append(message.model_dump())
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# Save team state to file.
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async with aiofiles.open(state_path, "w") as file:
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state = await team.save_state()
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await file.write(json.dumps(state))
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# Save chat history to file.
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async with aiofiles.open(history_path, "w") as file:
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await file.write(json.dumps(history))
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except Exception as e:
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# Send error message to client
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error_message = {
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"type": "error",
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"content": f"Error: {str(e)}",
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"source": "system"
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}
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await websocket.send_json(error_message)
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# Re-enable input after error
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await websocket.send_json({
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"type": "UserInputRequestedEvent",
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"content": "An error occurred. Please try again.",
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"source": "system"
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})
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except WebSocketDisconnect:
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logger.info("Client disconnected")
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except Exception as e:
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logger.error(f"Unexpected error: {str(e)}")
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try:
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await websocket.send_json({
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"type": "error",
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"content": f"Unexpected error: {str(e)}",
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"source": "system"
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})
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except:
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pass
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# Example usage
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000) |