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import streamlit as st
import tempfile
import os
from llm import load_and_process_pdf, create_vectorstore, create_rag_chain, get_response
st.set_page_config(page_title="PDF Q&A Chatbot", page_icon="📚")
st.title("PDF Q&A Chatbot")
# Initialize session state for vector store and chain
if 'vectorstore' not in st.session_state:
st.session_state.vectorstore = None
if 'rag_chain' not in st.session_state:
st.session_state.rag_chain = None
# File uploader
uploaded_file = st.file_uploader("Choose a PDF file", type="pdf")
if uploaded_file is not None and st.session_state.vectorstore is None:
# Save the uploaded file temporarily
with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
tmp_file.write(uploaded_file.getvalue())
tmp_file_path = tmp_file.name
# Process the PDF only once
with st.spinner("Processing PDF..."):
splits = load_and_process_pdf(tmp_file_path)
st.session_state.vectorstore = create_vectorstore(splits)
st.session_state.rag_chain = create_rag_chain()
st.success("PDF processed successfully! Now you can ask questions.")
# Clean up the temporary file
os.unlink(tmp_file_path)
# Question input
if st.session_state.vectorstore is not None:
question = st.text_input("Ask a question about the PDF:")
if question:
with st.spinner("Generating answer..."):
answer = get_response(st.session_state.rag_chain, st.session_state.vectorstore, question)
st.write("Answer:", answer)
else:
st.info("Please upload a PDF file to get started.")
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