import os import asyncio import websockets import sqlite3 import datetime import fireworks.client import streamlit as st import threading import conteneiro from langchain.agents import load_tools from langchain.agents import initialize_agent from langchain.agents import AgentType from langchain.llms import HuggingFaceHub from langchain.llms.fireworks import Fireworks from langchain.chat_models.fireworks import ChatFireworks client_ports = [] # Define the websocket client class class AgentsGPT: def __init__(self): self.status = st.sidebar.status(label="AgentsGPT", state="complete", expanded=False) async def get_response(self, question): os.environ["GOOGLE_CSE_ID"] = GOOGLE_CSE_ID os.environ["GOOGLE_API_KEY"] = GOOGLE_API_KEY os.environ["FIREWORKS_API_KEY"] = FIREWORKS_API_KEY os.environ["HUGGINGFACEHUB_API_TOKEN"] = HUGGINGFACEHUB_API_TOKEN llm = Fireworks(model="accounts/fireworks/models/llama-v2-70b-chat", model_kwargs={"temperature":0, "max_tokens":1500, "top_p":1.0}, streaming=True) tools = load_tools(["google-search", "llm-math"], llm=llm) agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True, return_intermediate_steps=True) response = agent({"input": question}) output = response["output"] steps = response["intermediate_steps"] serverResponse = f"AgentsGPT: {output}" responseSteps = f"intermediate steps: {steps}" answer = f"Main output: {output}. Intermediate steps: {steps}" print(serverResponse) print(responseSteps) output_Msg = st.chat_message("ai") output_Msg.markdown(serverResponse) output_steps = st.chat_message("assistant") output_steps.markdown(responseSteps) return answer # Define a function that will run the client in a separate thread def run(self): # Create a thread object self.thread = threading.Thread(target=self.run_client) # Start the thread self.thread.start() # Define a function that will run the client using asyncio def run_client(self): # Get the asyncio event loop loop = asyncio.new_event_loop() # Set the event loop as the current one asyncio.set_event_loop(loop) # Run the client until it is stopped loop.run_until_complete(self.client()) # Stop the WebSocket client async def stop_client(): global ws # Close the connection with the server await ws.close() client_ports.pop() print("Stopping WebSocket client...") # Define a coroutine that will connect to the server and exchange messages async def startClient(self, clientPort): self.uri = f'ws://localhost:{clientPort}' self.name = f"Chaindesk client port: {clientPort}" conteneiro.clients.append(self.name) status = self.status # Connect to the server async with websockets.connect(self.uri) as websocket: # Loop forever while True: status.update(label=self.name, state="running", expanded=True) # Listen for messages from the server input_message = await websocket.recv() print(f"Server: {input_message}") input_Msg = st.chat_message("assistant") input_Msg.markdown(input_message) try: response = await self.get_response(input_message) res1 = f"Client: {response}" output_Msg = st.chat_message("ai") output_Msg.markdown(res1) await websocket.send(res1) status.update(label=self.name, state="complete", expanded=True) except websockets.ConnectionClosed: print("client disconnected") continue except Exception as e: print(f"Error: {e}") continue