|
|
| import streamlit as st |
| from pdf_reader import extract_text_from_pdf |
| from qa_utils import split_text, create_vector_store, answer_question |
|
|
| st.set_page_config(page_title="📄 PDF Q&A App") |
| st.title("📄 Ask Questions from PDF") |
|
|
| |
| uploaded_file = st.file_uploader("Upload a PDF file", type="pdf") |
|
|
| |
| if uploaded_file and "vectorstore" not in st.session_state: |
| with st.spinner("Reading and processing the PDF..."): |
| text = extract_text_from_pdf(uploaded_file) |
| chunks = split_text(text) |
| vectorstore = create_vector_store(chunks) |
| st.session_state.vectorstore = vectorstore |
| st.success("✅ PDF loaded and ready for questions!") |
|
|
| |
| if "vectorstore" in st.session_state: |
| query = st.text_input("Ask a question about the PDF:") |
| if query: |
| with st.spinner("Generating answer..."): |
| answer = answer_question(st.session_state.vectorstore, query) |
| st.write("**Answer:**", answer) |
|
|
