app.py

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

# Title of the Streamlit app
st.title("WhiteRabbitNEO Q&A App")

# Hugging Face API token input (only required if the model is private)
token = st.text_input("Enter your Hugging Face token (if required):", type="password")

# Load the model
@st.cache_resource
def load_model():
    try:
        if token:
            login(token=token)
        model = pipeline("question-answering", model="WhiteRabbitNEO")
        return model
    except Exception as e:
        st.error(f"Failed to load model: {e}")
        return None

# Load the model
model = load_model()

if model:
    question = st.text_input("Ask a question:")
    context = st.text_area("Provide context for your question:")

    if st.button("Get Answer"):
        if question and context:
            try:
                answer = model(question=question, context=context)
                st.write("Answer:", answer['answer'])
            except Exception as e:
                st.error(f"Error generating answer: {e}")
        else:
            st.warning("Please provide both a question and context.")
else:
    st.error("Model could not be loaded. Please check your configuration.")