Update app.py

app.py

@@ -1,56 +1,2 @@
-
-
-import os
-
 import gradio as gr
-import csv
-import fitz  # PyMuPDF
-
-
-def pdf_to_csv(pdf_file):
-    # Open the uploaded PDF file (pdf_file is a TemporaryFile)
-    # pdf_reader = PyPDF2.PdfReader(pdf_file.name)
-    text_lines = []
-
-    file_name = os.path.basename(pdf_file.name)
-
-    text_lines.append(f"File Name: {file_name}")
-    text_lines.append(' 地区 (Region): 2010\n*   收入/支出金额 (Income/Expense Amount): +10,000.00\n* ')
-    csv_filename = "extracted_text.csv"
-    # Write each line into the CSV file (each line in its own row)
-    with open(csv_filename, "w", newline="", encoding="utf-8-sig") as csvfile:
-        writer = csv.writer(csvfile)
-        for line in text_lines:
-            writer.writerow([line])
- 
-    # Return the CSV file path so Gradio can offer it as a download
-    return csv_filename
-
-
-def pdf_to_pngs(pdf_file): 
-    # Open the PDF
-    doc = fitz.open(pdf_file)
-    pix = None
-    outputs = []
-    # Loop through each page and save as PNG
-    for page_num in range(doc.page_count):
-        page = doc.load_page(page_num)  # Get the page
-        pix = page.get_pixmap()  # Get the image of the page
-    
-        output_path =  f'page_{page_num + 1}.png'
-        pix.save(output_path)  # Save as PNG
-        print(f'Saved {output_path}')
-        outputs.append(output_path)
-    return outputs
-
-# Create a simple single-page Gradio interface
-demo = gr.Interface(
-    fn=pdf_to_pngs,
-    inputs=gr.File(label="Upload PDF", file_types=[".pdf"]),
-    outputs=gr.File(label="Download CSV"),
-    title="PDF to CSV Converter",
-    description="Upload a PDF file, extract its text line-by-line, and download a CSV."
-)
-
-demo.launch()
-
+gr.Interface.load("models/Hidden_GEMINI_extractor/melaura-v1-0").launch()