import asyncio
import websockets
import threading
import sqlite3
import g4f
import streamlit as st

# Define the websocket client class
class WebSocketClient3:
    def __init__(self, clientPort):

        # Initialize the uri attribute
        self.uri = f'ws://localhost:{clientPort}'   
        self.name = f"Bing/Copilot client port: {clientPort}"
        self.status = st.sidebar.status(label=self.name, state="complete", expanded=False)
        st.session_state.clientPort = clientPort

        if "client_ports" not in st.session_state:
            st.session_state['client_ports'] = ""

    async def askQuestion(self, question):
        system_instruction = "You are now integrated with a local websocket server in a project of hierarchical cooperative multi-agent framework called NeuralGPT. Your main job is to coordinate simultaneous work of multiple LLMs connected to you as clients. Each LLM has a model (API) specific ID to help you recognize different clients in a continuous chat thread (template: <NAME>-agent and/or <NAME>-client). Your chat memory module is integrated with a local SQL database with chat history. Your primary objective is to maintain the logical and chronological order while answering incoming messages and to send your answers to the correct clients to maintain synchronization of the question->answer logic. However, please note that you may choose to ignore or not respond to repeating inputs from specific clients as needed to prevent unnecessary traffic."
        try:
            db = sqlite3.connect('chat-hub.db')
            cursor = db.cursor()
            cursor.execute("SELECT * FROM messages ORDER BY timestamp DESC LIMIT 30")
            messages = cursor.fetchall()
            messages.reverse()

            past_user_inputs = []
            generated_responses = []

            for message in messages:
                if message[1] == 'client':
                    past_user_inputs.append(message[2])
                else:
                    generated_responses.append(message[2])
                        
            response = await g4f.ChatCompletion.create_async(
                model="gpt-3.5-turbo",
                provider=g4f.Provider.You,
                messages=[
                {"role": "system", "content": system_instruction},
                *[{"role": "user", "content": message} for message in past_user_inputs],
                *[{"role": "assistant", "content": message} for message in generated_responses],
                {"role": "user", "content": question}
                ])
            
            print(response)
            return response
            
        except Exception as e:
            print(e)

    # 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())

    # Define a coroutine that will connect to the server and exchange messages
    async def startClient(self):

        status = st.sidebar.status(label=self.name, state="complete", expanded=False)               
        async with websockets.connect(self.uri) as websocket:
            # Loop forever
            while True:               
                status.update(label="runs", 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.askQuestion(input_message)
                    res1 = f"Client: {response}"
                    output_Msg = st.chat_message("ai")
                    output_Msg.markdown(res1)
                    await websocket.send(res1)
                    status.update(label="runs", state="complete", expanded=True)

                except websockets.ConnectionClosed:
                    print("client disconnected")
                    continue

                except Exception as e:
                    print(f"Error: {e}")
                    continue