app.py

import streamlit as st
from transformers import pipeline

# Title
st.title("📘 Quiz Generator from Text")
st.write("Enter a paragraph, and this app will generate MCQs using a Hugging Face model.")

# Load model only once
@st.cache_resource
def load_model():
    return pipeline("e2e-qg", model="valhalla/t5-base-e2e-qg")

qg_pipeline = load_model()

# Text input
text = st.text_area("Enter your paragraph here:", height=200)

if st.button("Generate Quiz"):
    if not text.strip():
        st.warning("Please enter some text first.")
    else:
        with st.spinner("Generating questions..."):
            try:
                result = qg_pipeline(text)
                st.success("Here are your questions:")

                for idx, item in enumerate(result):
                    st.markdown(f"**Q{idx+1}. {item['question']}**")
                    st.markdown(f"- Answer: `{item['answer']}`")
                    st.markdown("---")
            except Exception as e:
                st.error(f"Error: {str(e)}")