Update app.py

app.py

@@ -533,7 +533,9 @@ def get_solution_for_verification(response_text, sympy_correct, final_verificati
         logger.error("Could not find question markers")
         return response_text.strip()
         
+    # Extract question and solution sections
     question = response_text[q_start:q_end].strip()
+    original_solution = response_text[q_end:]
     
     # If no sympy verification was done, treat as correct and use original
     if sympy_correct is None:
@@ -541,7 +543,6 @@ def get_solution_for_verification(response_text, sympy_correct, final_verificati
     
     if sympy_correct:
         # Use original solution - need to extract before SymPy code
-        original_solution = parts[1]
         sympy_start = original_solution.find('```python')
         if sympy_start != -1:
             solution = original_solution[:sympy_start].strip()
@@ -559,10 +560,10 @@ def get_solution_for_verification(response_text, sympy_correct, final_verificati
                 solution = final_verification.strip()
         else:
             # Fallback to original if no final verification
-            solution = parts[1].strip()
+            solution = original_solution.strip()
     
     # Combine question and appropriate solution
-    complete_text = f"{question}\n\nSolution:\n{solution}"
+    complete_text = f"{question}\n\n{solution}"
     return complete_text
 
 def verify_with_chatgpt(question_and_solution):
@@ -585,7 +586,7 @@ Analyze the following aspects:
    - Are edge cases addressed?
    - Are all required steps shown?
 
-3. Clarity and Presentation (20 points):
+3. Clarity and Presentation (10 points):
    - Is the solution well-organized?
    - Are steps clearly explained?
    - Is mathematical notation used correctly?
@@ -608,7 +609,7 @@ Format your response with clear headers and bullet points."""
 
         # Call OpenAI API
         response = openai.ChatCompletion.create(
-            model="gpt-4o",  # Using GPT-4o model
+            model="gpt-4o",  # Using GPT-4 Omega model
             messages=[
                 {"role": "system", "content": "You are an expert mathematics professor grading student solutions."},
                 {"role": "user", "content": verification_prompt}