import streamlit as st
from transformers import pipeline
from huggingface_hub import login
import os

# 🚨 Replace this with your actual Hugging Face access token
HF_TOKEN = "your_huggingface_access_token_here" # <-- Insert your token here securely

# Login to Hugging Face Hub
login(HF_TOKEN)

# App Title & Description
st.title("🤖📟 Arduino Expert Chatbot")
st.markdown("Get help with Arduino code, circuit diagrams, and projects.")

# Load the model securely
@st.cache_resource
def load_model():
    try:
        return pipeline("text-generation", model="mistralai/Mixtral-8x7B-Instruct-v0.1", token=HF_TOKEN)
    except Exception as e:
        st.error("🚫 Failed to load the model. Using fallback model (GPT-2).")
        return pipeline("text-generation", model="gpt2")  # fallback public model

# Load model once
model = load_model()

# User Input
query = st.text_area("Ask your Arduino question here 👇", height=150)

# Generate Answer
if st.button("Get Answer"):
    if query.strip():
        with st.spinner("Thinking... 🤖"):
            try:
                response = model(query, max_length=512, do_sample=True, temperature=0.7)
                st.success(response[0]['generated_text'])
            except Exception as e:
                st.error(f"❌ Error generating response: {e}")
    else:
        st.warning("Please enter a question about your Arduino project.")

# Footer
st.markdown("---")
st.markdown("Made with ❤️ using Hugging Face and Streamlit")