Update app.py

app.py

@@ -64,14 +64,11 @@ def unzip_and_find_jpgs(file_path):
 def process_images(uploaded_file):
     # Reinitialize the DataFrame each time this function is called
     results_df = pd.DataFrame(columns=["Filename", "Extracted Text", "Translated Text"])
-    print("DataFrame reinitialized:", results_df)  # Debugging statement
 
     file_path = uploaded_file.name  # Gradio provides the file path through the .name attribute
-    print("Processing file:", file_path)  # Debugging statement
 
     try:
         image_files = unzip_and_find_jpgs(file_path)
-        print("Found image files:", image_files)  # Debugging statement
 
         if not image_files:
             return "No JPG files found in the zip."
@@ -84,20 +81,36 @@ def process_images(uploaded_file):
                 "Translated Text": translated_text
             }])
             results_df = pd.concat([results_df, new_row], ignore_index=True)
-        print("Current DataFrame state:", results_df)  # Debugging statement
     except Exception as e:
         return f"An error occurred: {str(e)}"
 
-    return results_df.to_html()
-
-
-interface = gr.Interface(
-    fn=process_images,
-    inputs="file",
-    outputs="html",
-    title="Document AI Translation",
-    description="Upload a ZIP file containing JPEG/JPG images, and the system will extract and translate text from each image."
-)
+    html_output = results_df.to_html()
+
+    # Save DataFrame to a temporary CSV file for download
+    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".csv")  # Create a temp file
+    results_df.to_csv(temp_file.name, index=False)  # Save DataFrame to CSV
+    
+    # Read the contents back to verify
+    temp_file.seek(0)  # Move file pointer to the beginning of the file
+    print(pd.read_csv(temp_file.name))  # Read and print the CSV file to verify its contents
+
+    temp_file.close()  # Close the file
+
+    # Return HTML and the path to the CSV file
+    return html_output, temp_file.name
+
+with gr.Blocks() as interface:
+    with gr.Row():
+        gr.Markdown("# Document AI Translation")
+        gr.Markdown("Upload a ZIP file containing JPEG/JPG images, and the system will extract and translate text from each image.")
+    with gr.Row():
+        file_input = gr.File(label="Upload ZIP File")
+    with gr.Row():
+        html_output = gr.HTML()
+    with gr.Row():
+        file_output = gr.File()
+
+    file_input.change(process_images, inputs=file_input, outputs=[html_output, file_output])
 
 if __name__ == "__main__":
     interface.launch(debug=True)