Update app.py

app.py

@@ -1543,16 +1543,25 @@ with gr.Blocks(title="AI Grading (Pandoc + pdflatex)") as demo:
             else:
                 return error_msg, "", "", None, None
         
-        # Process and upload input files (generates shared timestamp)
-        qp_path, ms_path, ans_path, input_urls, run_timestamp = process_and_upload_input_files(
-            qp_file_obj, ms_file_obj, ans_file_obj
-        )
+        # Only extract local paths 
+        qp_path = qp_file_obj.name
+        ms_path = ms_file_obj.name
+        ans_path = ans_file_obj.name
+        run_timestamp = str(int(time.time()))  # generate timestamp here
 
-        # Run the grading pipeline (pass timestamp to keep all files together)
+        # Run the grading pipeline first
         qpms_text, as_text, grading_text, grading_pdf_path, imprinted_pdf_path, output_urls = align_and_grade_pipeline( 
             qp_path, ms_path, ans_path, subject=subject_choice, imprint=imprint_flag, run_timestamp=run_timestamp
         )
         
+        # Only upload to Supabase if pipeline succeeded (no error string returned)
+        input_urls = {"qp_url": None, "ms_url": None, "ans_url": None}
+        if supabase_client and isinstance(qpms_text, str) and not qpms_text.startswith("❌"):
+            print("\n📤 Uploading input files to Supabase (pipeline succeeded)...")
+            input_urls["qp_url"] = upload_file_to_supabase(qp_path, "qp", run_timestamp)
+            input_urls["ms_url"] = upload_file_to_supabase(ms_path, "ms", run_timestamp)
+            input_urls["ans_url"] = upload_file_to_supabase(ans_path, "ans", run_timestamp)
+        
         # Build URLs summary
         urls_summary = ""
         if supabase_client: