Update app.py

app.py

@@ -366,24 +366,71 @@ Start immediately with Q1. Do not include any introduction or explanation.
 def grade_student_answers(questions, student_answers, grade_level, topic, subject=None):
     """Grade all student answers and provide AI feedback - NO STRICT FORMAT REQUIRED"""
     
-    if not questions or not student_answers:
-        return " No questions or answers to grade."
-    
+    if not questions:
+        return " No questions to grade."
+
     feedback_list = []
-    
+
     for i, question_text in enumerate(questions):
-        student_answer = student_answers.get(i, "") or ""
-        
-        if not student_answer.strip():
-            feedback_list.append(f"Q{i+1}: [NOT ANSWERED]")
+        student_answer = student_answers.get(i, None)
+
+        # No answer submitted for this question
+        if student_answer is None:
+            # Ask AI for a short guidance/hint for this question (best-effort)
+            hint_prompt = f"""You are an experienced UNEB examiner for {grade_level} students.
+
+Question {i+1}: {question_text}
+
+The student did not submit an answer. Provide a very brief (2-3 line) approach or hint that would help the student answer this question."""
+            hint_resp, _ = ask_ai(hint_prompt, temperature=0.3)
+            if not hint_resp or "All AI services failed" in hint_resp:
+                hint_resp = "No answer submitted. Expected: show step-by-step working and final answer; include units where applicable."
+            feedback_list.append(f"Q{i+1}: [NOT ANSWERED]\nGuidance: {hint_resp}\n")
             continue
-        
-        # Create flexible grading prompt - AI evaluates based on question number & content
+
+        # Handle image answers (canvas/uploaded photos)
+        try:
+            from PIL import Image as PILImage
+            is_image = isinstance(student_answer, PILImage.Image)
+        except Exception:
+            is_image = False
+
+        if is_image:
+            grading_prompt = f"""You are an experienced UNEB examiner for {grade_level} students. Subject: {subject or 'General'}
+
+Question {i+1}: {question_text}
+
+The student submitted handwritten work as an image. Analyse the image, extract the student's answer for this question, and then:
+- State whether the answer is correct, partially correct, or incorrect
+- Provide a mark/score
+- Give brief constructive feedback and the correct approach if needed
+
+If you cannot analyse images, state that image analysis requires a vision-capable model."""
+
+            grade_response, _ = ask_ai(grading_prompt, temperature=0.3, image=student_answer)
+            feedback_list.append(f"Q{i+1}:\n{grade_response}\n")
+            continue
+
+        # Treat as text answer
+        text_ans = str(student_answer).strip()
+        if not text_ans:
+            # empty string case
+            hint_prompt = f"""You are an experienced UNEB examiner for {grade_level} students.
+
+Question {i+1}: {question_text}
+
+The student submitted an empty/text-missing answer. Provide a very brief (2-3 line) approach or hint that would help the student answer this question."""
+            hint_resp, _ = ask_ai(hint_prompt, temperature=0.3)
+            if not hint_resp or "All AI services failed" in hint_resp:
+                hint_resp = "No answer submitted. Expected: show step-by-step working and final answer; include units where applicable."
+            feedback_list.append(f"Q{i+1}: [NOT ANSWERED]\nGuidance: {hint_resp}\n")
+            continue
+
         grading_prompt = f"""You are an experienced UNEB examiner for {grade_level} students. Subject: {subject or 'General'}
 
 Question {i+1}: {question_text}
 
-Student's Answer: {student_answer}
+Student's Answer: {text_ans}
 
 Evaluate this answer:
 - Is it correct, partially correct, or incorrect?
@@ -392,10 +439,10 @@ Evaluate this answer:
 - If incorrect, briefly explain the correct approach
 
 Accept answers in ANY format/style as long as they address the question. Be constructive and encouraging."""
-        
+
         grade_response, _ = ask_ai(grading_prompt, temperature=0.3)
         feedback_list.append(f"Q{i+1}:\n{grade_response}\n")
-    
+
     full_feedback = "\n" + "="*60 + "\n".join(feedback_list)
     return full_feedback
 
@@ -408,6 +455,7 @@ class StudentSession:
         self.current_topic = None
         self.current_grade = None
         self.last_feedback = None
+        self.correction_conversation = []  # list of {'role':'user'|'assistant','content':str}
         
     def clear_session(self):
         self.current_questions = []
@@ -640,6 +688,11 @@ with gr.Blocks(title="UNEB Exam Prep - Primary 6 & 7", theme=gr.themes.Soft(), c
     
     # Global state for questions
     questions_state = gr.State(value=[])
+    # Shared question display (visible across tabs so students don't switch panels)
+    questions_display = gr.HTML(
+        value="",
+        elem_classes="question-display"
+    )
     
     # Student name input
     with gr.Group():
@@ -691,10 +744,7 @@ with gr.Blocks(title="UNEB Exam Prep - Primary 6 & 7", theme=gr.themes.Soft(), c
                 num_questions_input = gr.Slider(minimum=1, maximum=100, step=1, value=20, label="Number of Questions")
                 generate_btn = gr.Button(" Generate Questions", variant="primary", size="lg")
             
-            questions_output = gr.HTML(
-                value="",
-                elem_classes="question-display"
-            )
+            # (questions_display is shared above - no local questions_output here)
 
             status_output = gr.Textbox(
                 label="Status",
@@ -727,7 +777,7 @@ with gr.Blocks(title="UNEB Exam Prep - Primary 6 & 7", theme=gr.themes.Soft(), c
             generate_btn.click(
                 fn=generate_and_display,
                 inputs=[grade_input, subject_input, topic_input, num_questions_input],
-                outputs=[questions_output, questions_state, status_output]
+                outputs=[questions_display, questions_state, status_output]
             )            
             # Download handler - returns file path for gr.DownloadButton
             def download_qns():
@@ -850,11 +900,13 @@ with gr.Blocks(title="UNEB Exam Prep - Primary 6 & 7", theme=gr.themes.Soft(), c
                 
                 # Check which method was used
                 if canvas_input is not None:
-                    session.current_answers = {0: "[Canvas drawing - sent to AI for analysis]"}
+                    # Map the same canvas image to all question indices so each question gets graded
+                    session.current_answers = {i: canvas_input for i in range(len(session.current_questions))}
                     return f" Canvas submission received with {len(session.current_questions)} questions. Processing..."
                 
                 elif upload_input is not None:
-                    session.current_answers = {0: "[Uploaded image - sent to AI for analysis]"}
+                    # Map the uploaded image to all question indices so AI can analyse each part
+                    session.current_answers = {i: upload_input for i in range(len(session.current_questions))}
                     return f" Photo submission received with {len(session.current_questions)} questions. Processing..."
                 
                 elif typed_input and typed_input.strip():
@@ -942,6 +994,20 @@ with gr.Blocks(title="UNEB Exam Prep - Primary 6 & 7", theme=gr.themes.Soft(), c
                 lines=20,
                 elem_classes="feedback-box"
             )
+
+            # Conversation area for follow-up questions about feedback
+            conversation_display = gr.Textbox(
+                label="Correction Conversation",
+                lines=12,
+                interactive=False
+            )
+
+            followup_input = gr.Textbox(
+                label="Ask a follow-up question",
+                placeholder="Ask about a specific question or the feedback...",
+                lines=2
+            )
+            followup_btn = gr.Button(" Ask Follow-up")
             
             with gr.Row():
                 download_feedback_btn = gr.DownloadButton(" Download Feedback (TXT)")
@@ -967,6 +1033,8 @@ with gr.Blocks(title="UNEB Exam Prep - Primary 6 & 7", theme=gr.themes.Soft(), c
                 )
                 
                 session.last_feedback = feedback
+                # initialize conversation with assistant feedback
+                session.correction_conversation = [{'role':'assistant', 'content': feedback}]
                 return feedback
             
             correction_btn.click(
@@ -991,6 +1059,40 @@ with gr.Blocks(title="UNEB Exam Prep - Primary 6 & 7", theme=gr.themes.Soft(), c
                 inputs=[],
                 outputs=download_feedback_btn
             )
+
+            # Follow-up handler: student asks a question about the feedback
+            def send_followup(question_text):
+                if not session.last_feedback:
+                    return "Please generate corrections first.", None
+
+                if not question_text or not question_text.strip():
+                    return "Please type a follow-up question.", None
+
+                # Build a conversational prompt referencing the previous feedback
+                convo_context = ''
+                # include last assistant feedback
+                convo_context += session.last_feedback + "\n\n"
+                followup_prompt = f"You are an experienced UNEB examiner. The student received the following feedback:\n\n{convo_context}\nNow the student asks: {question_text}\n\nAnswer concisely, refer to the specific question number if applicable, and be encouraging."
+
+                resp, _ = ask_ai(followup_prompt, temperature=0.4)
+
+                # Append to session conversation
+                session.correction_conversation.append({'role':'user', 'content': question_text})
+                session.correction_conversation.append({'role':'assistant', 'content': resp})
+
+                # Build display text combining conversation
+                display = ''
+                for msg in session.correction_conversation:
+                    prefix = 'Student:' if msg['role']=='user' else 'AI:'
+                    display += f"{prefix} {msg['content']}\n\n"
+
+                return '', display
+
+            followup_btn.click(
+                fn=send_followup,
+                inputs=[followup_input],
+                outputs=[followup_input, conversation_display]
+            )
         
         # ===== TAB 4: START NEW SESSION =====
         with gr.Tab(" New Session"):