app.py

import streamlit as st
from transformers import pipeline
from PyPDF2 import PdfReader
import tempfile

# Initialize the QA pipeline
qa_pipeline = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")

# Function to extract text from PDF
def extract_text_from_pdf(file_path):
    with open(file_path, "rb") as f:
        reader = PdfReader(f)
        text = [page.extract_text() for page in reader.pages if page.extract_text() is not None]
    return " ".join(text)

# Streamlit interface
st.title('Car Repair Query System')

uploaded_file = st.file_uploader("Choose a PDF file", type="pdf")
if uploaded_file is not None:
    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
        tmp_file.write(uploaded_file.getvalue())
        document_text = extract_text_from_pdf(tmp_file.name)

    st.success('Document uploaded and processed. You can now ask questions.')
    st.write('### Ask a Question')
    question = st.text_input("What is your question?")
    
    if st.button('Answer Question'):
        if question:
            answer = qa_pipeline(question=question, context=document_text)
            st.write("Answer:", answer['answer'])
        else:
            st.write("Please enter a question.")
else:
    st.write("Please upload a PDF document to begin.")

# Run this app with `streamlit run your_script_name.py`