Neural-GPT / clientFlowise.py
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Update clientFlowise.py
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import asyncio
import websockets
import threading
import sqlite3
import g4f
import requests
import streamlit as st
client_ports = []
# Define the websocket client class
class WebSocketClient5:
def __init__(self):
# Initialize the uri attribute
if "client_ports" not in st.session_state:
st.session_state['client_ports'] = ""
async def askQuestion(self, question):
if "flow" not in st.session_state:
st.session_state.flow = ""
flow = st.session_state.flow
API_URL = f"http://localhost:3000/api/v1/prediction/{flow}"
try:
def query(payload):
response = requests.post(API_URL, json=payload)
return response.json()
response = query({
"question": question,
})
print(response)
answer = response["text"]
return answer
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())
# 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):
uri = f'ws://localhost:{clientPort}'
client_ports.append(clientPort)
st.session_state['client_ports'] = client_ports
name = f"Flowise client port: {clientPort}"
status = st.sidebar.status(label=name, state="complete", expanded=False)
# Connect to the server
async with websockets.connect(uri) as websocket:
# Loop forever
while True:
status.update(label=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.askQuestion(input_message)
res1 = f"Client: {response}"
output_Msg = st.chat_message("ai")
output_Msg.markdown(res1)
await websocket.send(res1)
status.update(label=name, state="complete", expanded=True)
continue
except websockets.ConnectionClosed:
print("client disconnected")
continue
except Exception as e:
print(f"Error: {e}")
continue