import streamlit as st
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import os

# Load Hugging Face Token from environment variable
hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")

if hf_token is None:
    st.error("❌ Hugging Face API Token is missing! Add it in Settings → Secrets.")
    st.stop()

# Model name
MODEL_NAME = "google/gemma-2b-it"

# Load tokenizer and model with authentication
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_auth_token=hf_token)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.float16, device_map="auto", use_auth_token=hf_token)

# Streamlit UI
st.title("Gemma-2B Code Assistant")
user_input = st.text_area("Enter your coding query:")

if st.button("Generate Code"):
    if user_input:
        inputs = tokenizer(user_input, return_tensors="pt").to("cuda")
        output = model.generate(**inputs, max_new_tokens=100)
        response = tokenizer.decode(output[0], skip_special_tokens=True)
        st.write(response)
    else:
        st.warning("Please enter a query!")