Update main.py

main.py

@@ -1,32 +1,22 @@
-from fastapi import FastAPI
-from pydantic import BaseModel
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import StreamingResponse
 from hugchat import hugchat
 from hugchat.login import Login
-import asyncio
-import os
-from dotenv import load_dotenv
 
-# Load environment variables from .env file
-load_dotenv()
-
-# Read credentials from environment variables
+# Credentials
 EMAIL = os.getenv("EMAIL")
 PASSWD = os.getenv("PASSWD")
-# Cookie storage
-cookie_path_dir = "./cookies/"
-os.makedirs(cookie_path_dir, exist_ok=True)
 
-# HugChat login
+# Path to store cookies
+cookie_path_dir = "./cookies/"  # Make sure this directory exists
+
+# Log in and get cookies
 sign = Login(EMAIL, PASSWD)
 cookies = sign.login(cookie_dir_path=cookie_path_dir, save_cookies=True)
 
-# Create chatbot instance
+# Create ChatBot with cookies
 chatbot = hugchat.ChatBot(cookies=cookies.get_dict())
 
-# Optional: Use assistant ID
-ASSISTANT_ID = "66017fca58d60bd7d5c5c26c"  # Replace if needed
+# 🔁 Create a new conversation with a custom assistant ID
+ASSISTANT_ID = "66017fca58d60bd7d5c5c26c"  # Replace with your actual assistant ID
 chatbot.new_conversation(assistant=ASSISTANT_ID, switch_to=True)
 
 # 🔁 Stream response character-by-character as it generates
@@ -37,4 +27,3 @@ for token in chatbot.chat("Hello, how can I help you today?", stream=True):
 # Optionally: web search example
 # response = chatbot.chat("How many models stored in huggingface?", web_search=True)
 # print("\n\nWeb Search Result:", response.wait_until_done())
-