app.py

import streamlit as st
from transformers import RagTokenizer, RagRetriever, RagSequenceForGeneration

# Load RAG components
tokenizer = RagTokenizer.from_pretrained("facebook/rag-sequence-nq")
retriever = RagRetriever.from_pretrained("facebook/rag-sequence-nq", use_dummy_dataset=True)
rag_model = RagSequenceForGeneration.from_pretrained("facebook/rag-sequence-nq", retriever=retriever)

# Streamlit UI
st.title("RAG-based Q&A")

query = st.text_input("Enter your question:")

if st.button("Generate Answer"):
    if query:
        # Process the input query and generate a response
        inputs = tokenizer(query, return_tensors="pt")
        outputs = rag_model.generate(**inputs)
        response = tokenizer.batch_decode(outputs, skip_special_tokens=True)
        st.write(f"Answer: {response[0]}")
    else:
        st.write("Please enter a question to get an answer.")