app.py

import streamlit as st
import requests
from transformers import pipeline
import urllib3
import os

# Disable warnings
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)

# Create a custom session
session = requests.Session()
session.verify = False  # Disable SSL verification

# Load the token from Hugging Face secrets
HUGGINGFACE_TOKEN = os.getenv("hf_token")  # Set the default to empty if not found

# Set up the text generation pipeline with the token
pipe = pipeline("text-generation", model="meta-llama/Llama-3.1-8B-Instruct", 
                use_auth_token=HUGGINGFACE_TOKEN, request_session=session)

# Streamlit application
st.title("Text Generation with Hugging Face")

# User input
user_input = st.text_input("You: ", "Who are you?")

if st.button("Generate Response"):
    if user_input:
        messages = [{"role": "user", "content": user_input}]
        response = pipe(messages)
        generated_text = response[0]['generated_text']  # Adjust according to the response format
        st.text_area("Bot:", generated_text, height=200)
    else:
        st.warning("Please enter a message.")