app.py

import streamlit as st
import fitz  # PyMuPDF
from huggingface_hub import snapshot_download
import os
from pdf2image import convert_from_path
from PIL import Image
import tempfile

# Download the model if not already downloaded
model_dir = "./pdf-extract-kit"
if not os.path.exists(model_dir):
    snapshot_download(repo_id="opendatalab/pdf-extract-kit-1.0", local_dir=model_dir, max_workers=20)

st.title("PDF Table Extractor with PDF-Extract-Kit-1.0")

uploaded_file = st.file_uploader("Upload a PDF", type=["pdf"])

if uploaded_file:
    st.write("Converting PDF to images...")
    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_pdf:
        tmp_pdf.write(uploaded_file.read())
        tmp_pdf_path = tmp_pdf.name

    images = convert_from_path(tmp_pdf_path)

    for i, img in enumerate(images):
        st.image(img, caption=f"Page {i+1}", use_column_width=True)

        # Here you would call the table detection model on each image
        st.info("🛠 Table detection model would run here... (to be implemented)")

    st.success("Done processing PDF!")