app.py

import gradio as gr
import tempfile, shutil, os
import pandas as pd
from pipeline import run_pipeline  # your existing pipeline.py

def analyze_pdfs_gradio(files):
    """Process multiple PDFs and return SC API results."""
    with tempfile.TemporaryDirectory() as tmpdirname:
        for file in files:
            dest = os.path.join(tmpdirname, os.path.basename(file))
            shutil.copy(file, dest)

        results = run_pipeline(tmpdirname)
        return results

iface = gr.Interface(
    fn=analyze_pdfs_gradio,
    inputs=gr.File(
        type="filepath",  # <-- must be 'filepath' to work with your pipeline
        file_types=[".pdf"],
        file_count="multiple",
        label="Upload PDF(s)"
    ),
    outputs=gr.Dataframe(type="pandas", label="SC API Results"),
    title="SC API",
    description="Upload PDFs and get SC scores."
)

if __name__ == "__main__":
    iface.queue()  # enables /api/predict endpoint for API calls
    iface.launch(server_name="0.0.0.0", server_port=7860)