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import asyncio
import websockets
import threading
import sqlite3
import fireworks.client
import streamlit as st
from forefront import ForefrontClient
# Define the websocket client class
class WebSocketClient4:
def __init__(self, uri):
# Initialize the uri attribute
self.uri = uri
async def chatCompletion(self, question):
if "forefront_api" not in st.session_state:
st.session_state.forefront_api = ""
forefrontAPI = st.session_state.forefront_api
ff = ForefrontClient(api_key=forefrontAPI)
system_instruction = "You are now integrated with a local instance of a hierarchical cooperative multi-agent framework called NeuralGPT"
try:
# Connect to the database and get the last 30 messages
db = sqlite3.connect('chat-hub.db')
cursor = db.cursor()
cursor.execute("SELECT * FROM messages ORDER BY timestamp DESC LIMIT 3")
messages = cursor.fetchall()
messages.reverse()
# Extract user inputs and generated responses from the messages
past_user_inputs = []
generated_responses = []
for message in messages:
if message[1] == 'server':
past_user_inputs.append(message[2])
else:
generated_responses.append(message[2])
last_msg = past_user_inputs[-1]
last_response = generated_responses[-1]
message = f'{{"client input: {last_msg}"}}'
response = f'{{"server answer: {last_response}"}}'
# Construct the message sequence for the chat model
response = ff.chat.completions.create(
messages=[
{"role": "system", "content": system_instruction},
*[{"role": "user", "content": past_user_inputs[-1]}],
*[{"role": "assistant", "content": generated_responses[-1]}],
{"role": "user", "content": question}
],
stream=False,
model="forefront/neural-chat-7b-v3-1-chatml", # Replace with the actual model name
temperature=0.5,
max_tokens=500,
)
response_text = response.choices[0].message # Corrected indexing
print("Extracted message text:", response_text)
return response_text
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="runs", state="complete", expanded=False)
# Connect to the server
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.chatCompletion(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 |