Update app.py

app.py

@@ -3,22 +3,29 @@ import os
 import io
 from google import generativeai as genai
 
-def process_exam_papers(question_paper, marking_scheme, answer_sheet, api_key):
+def process_exam_papers(question_paper, marking_scheme, answer_sheet, api_key, progress=gr.Progress()):
     """
     Process uploaded exam papers and return transcription and grading
     """
     if not api_key:
-        return "Please provide a valid Gemini API key.", ""
+        return "Please provide a valid Gemini API key.", "", "Ready"
+    
+    if not all([question_paper, marking_scheme, answer_sheet]):
+        return "Please upload all three files.", "", "Ready"
     
     try:
         # Configure Gemini API
         genai.configure(api_key=api_key)
         
+        progress(0.1, desc="Uploading files to Gemini...")
+        
         # Upload files to Gemini
         qp_file = genai.upload_file(path=question_paper.name, display_name="Question Paper")
         ms_file = genai.upload_file(path=marking_scheme.name, display_name="Marking Scheme")
         ans_file = genai.upload_file(path=answer_sheet.name, display_name="Answer Sheet")
         
+        progress(0.3, desc="Files uploaded. Starting transcription...")
+        
         # Transcription instructions
         transcription_instructions = """
 Persona:
@@ -79,6 +86,8 @@ $$
             generation_config={"temperature": 0}
         )
         
+        progress(0.4, desc="Transcribing handwritten answers...")
+        
         # Generate transcription
         response = model.generate_content([
             transcription_instructions,
@@ -90,6 +99,11 @@ $$
         if not student_transcription:
             student_transcription = response.candidates[0].content.parts[0].text
         
+        progress(0.7, desc="Transcription complete. Starting grading process...")
+        
+        # Return transcription first, then continue with grading
+        yield student_transcription, "⏳ Grading in progress...", "Grading"
+        
         # Grading system instructions
         grading_system = """
 Instructions to Examiners:
@@ -116,6 +130,7 @@ Error Avoidance:
 - **Follow markscheme logic exactly:** Especially regarding when to withhold accuracy marks if method marks are not earned.
 """
         
+        # Now start grading using the transcribed text
         # Generate grading
         grading_response = model.generate_content([
             f"You are an official examiner. Use the following grading system and rules to assess the answers:\n\n{grading_system}\n\n"
@@ -128,9 +143,11 @@ Error Avoidance:
             "6. Provide a step-by-step reasoning for each mark awarded or withheld, explaining your thought process clearly.\n",
             qp_file,
             ms_file,
-            student_transcription
+            student_transcription  # Use the transcribed text, not the original PDF
         ])
         
+        progress(0.9, desc="Finalizing grading results...")
+        
         # Extract grading safely
         grading_text = getattr(grading_response, "text", None)
         if not grading_text and grading_response.candidates:
@@ -138,10 +155,13 @@ Error Avoidance:
         elif not grading_text:
             grading_text = "No Response"
         
-        return student_transcription, grading_text
+        progress(1.0, desc="Complete!")
+        
+        # Return final results
+        yield student_transcription, grading_text, "Complete"
         
     except Exception as e:
-        return f"Error processing files: {str(e)}", ""
+        yield f"Error processing files: {str(e)}", "", "Error"
 
 # Create Gradio interface
 with gr.Blocks(title="Exam Paper Grading System", theme=gr.themes.Soft()) as demo:
@@ -185,7 +205,8 @@ with gr.Blocks(title="Exam Paper Grading System", theme=gr.themes.Soft()) as dem
                 label="Transcribed Answers",
                 lines=15,
                 max_lines=25,
-                show_copy_button=True
+                show_copy_button=True,
+                placeholder="Transcribed answers will appear here first..."
             )
         
         with gr.Column():
@@ -194,14 +215,24 @@ with gr.Blocks(title="Exam Paper Grading System", theme=gr.themes.Soft()) as dem
                 label="Detailed Grading",
                 lines=15,
                 max_lines=25,
-                show_copy_button=True
+                show_copy_button=True,
+                placeholder="Grading results will appear here after transcription is complete..."
             )
     
+    # Add status indicator
+    with gr.Row():
+        status_display = gr.Textbox(
+            label="Status",
+            value="Ready",
+            interactive=False,
+            show_label=True
+        )
+    
     # Set up the processing function
     process_btn.click(
         fn=process_exam_papers,
         inputs=[question_paper, marking_scheme, answer_sheet, api_key],
-        outputs=[transcription_output, grading_output]
+        outputs=[transcription_output, grading_output, status_display]
     )
     
     gr.Markdown("""