main.py

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
EMAIL = os.getenv("EMAIL")
PASSWD = os.getenv("PASSWD")
# Cookie storage
cookie_path_dir = "./cookies/"
os.makedirs(cookie_path_dir, exist_ok=True)

# HugChat login
sign = Login(EMAIL, PASSWD)
cookies = sign.login(cookie_dir_path=cookie_path_dir, save_cookies=True)

# Create chatbot instance
chatbot = hugchat.ChatBot(cookies=cookies.get_dict())

# Optional: Use assistant ID
ASSISTANT_ID = "66017fca58d60bd7d5c5c26c"  # Replace if needed
chatbot.new_conversation(assistant=ASSISTANT_ID, switch_to=True)

# 🔁 Stream response character-by-character as it generates
print("Assistant:", end=" ", flush=True)
for token in chatbot.chat("Hello, how can I help you today?", stream=True):
    print(token, end="", flush=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())