import asyncio from src.agents.assistantagent import TrackableAssistantAgent from src.agents.userproxyagent import TrackableUserProxyAgent import streamlit as st import autogen class MultiAgentCodeExecution: def __init__(self, assistant_name, user_proxy_name, llm_config, problem): self.coder = TrackableAssistantAgent(name=assistant_name[0], system_message="""you are helpful assistant and efficient in writing code in python.""", human_input_mode="NEVER", llm_config=llm_config, ) self.pm = TrackableAssistantAgent(name=assistant_name[1], system_message="""You are efficient in Creative in software product ideas. Reply "TERMINATE" in the end when everything is done """, human_input_mode="NEVER", llm_config=llm_config, ) self.user_proxy = TrackableUserProxyAgent(name=user_proxy_name, system_message="You are human Admin", human_input_mode="NEVER", llm_config=llm_config, code_execution_config={"last_n_messages":2,"work_dir" : "./codegen","use_docker":False}, is_termination_msg=lambda x: x.get("content", "").strip().endswith( "TERMINATE")) self.groupchat = autogen.GroupChat(agents=[self.user_proxy,self.coder,self.pm],messages=[],max_round=2) self.manager = autogen.GroupChatManager(groupchat=self.groupchat,llm_config=llm_config) self.problem = problem self.loop = asyncio.new_event_loop() asyncio.set_event_loop(self.loop) def _reset(self): self.coder.reset() self.pm.reset() async def initiate_chat(self): self._reset() await self.user_proxy.a_initiate_chat(self.manager,max_turns=2, message=self.problem, clear_history=st.session_state["chat_with_history"]) def run(self): self.loop.run_until_complete(self.initiate_chat())