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app.py

@@ -760,6 +760,7 @@ def extract_marks_from_grading(grading_text):
 def extract_grading_summary_from_report(grading_text):
     """
     Extract the Examiner's Summary Report from grading text and return as DataFrame.
+    Uses the same approach as the provided example code.
     
     Args:
         grading_text (str): Full grading report text
@@ -767,30 +768,23 @@ def extract_grading_summary_from_report(grading_text):
     Returns:
         pd.DataFrame: Summary table with columns [Question, Marks, Remark, Feedback]
     """
-    import pandas as pd
-    
     print("🔎 Extracting Examiner's Summary Report from grading text...")
     
-    # Find the summary section
-    summary_match = re.search(r"### Examiner's Summary Report(.*?)(?=\n\n\*\*Total:|$)", grading_text, re.DOTALL)
-    if not summary_match:
-        print("⚠️ No Examiner's Summary Report found")
-        return pd.DataFrame(columns=["Question", "Marks", "Remark", "Feedback"])
+    # 1. Capture EVERYTHING after the header
+    summary_text = re.search(r"### Examiner's Summary Report(.*)", grading_text, re.DOTALL)
+    if not summary_text:
+        raise ValueError("Examiner's Summary Report not found")
     
-    summary_text = summary_match.group(1)
+    summary_text = summary_text.group(1)
     
-    # Extract table rows
-    row_pattern = re.compile(r"\|\s*(\d+(?:\.\w+)*)\s*\|\s*([\d/]+)\s*\|\s*([A-E])\s*\|\s*(.*?)\s*\|", re.DOTALL)
+    # 2. Extract table rows
+    row_pattern = re.compile(r"\|\s*(\d+)\s*\|\s*([\d/]+)\s*\|\s*([A-D])\s*\|\s*(.*?)\s*\|", re.DOTALL)
     rows = row_pattern.findall(summary_text)
     
-    if not rows:
-        print("⚠️ No table rows found in summary report")
-        return pd.DataFrame(columns=["Question", "Marks", "Remark", "Feedback"])
-    
     df = pd.DataFrame(rows, columns=["Question", "Marks", "Remark", "Feedback"])
     
-    # Extract total
-    total_pattern = re.search(r"\*\*Total:\s*(\d+/\d+)\*\*", grading_text)
+    # 3. Extract TOTAL directly from same block
+    total_pattern = re.search(r"Total:\s*(\d+/\d+)", summary_text)
     if total_pattern:
         df.loc[len(df)] = ["TOTAL", total_pattern.group(1), "", "Overall total score"]