app.py

import streamlit as st
from rag_pipeline import RAGPipeline

st.set_page_config(page_title="Medical QA Assistant", page_icon="🩺")
st.title("🩺 Medical QA Assistant")
st.markdown("Ask any medical question and get evidence-based answers from PubMed.")

@st.cache_resource
def load_rag():
    return RAGPipeline("data/pubmed_qa_dataset.csv")

rag = load_rag()

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

if st.button("Get Answer"):
    if question:
        with st.spinner("Searching PubMed and generating answer..."):
            answer = rag.generate_answer(question)
            st.success(answer)
    else:
        st.warning("Please enter a question.")