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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())
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