Update app.py

app.py

@@ -238,27 +238,62 @@ Overall Performance Level: [Exemplary (85-100%)/Proficient (70-84%)/Developing (
         return summary
 
     def parse_assessment_scores(self, assessment_text):
-        """Parse assessment text to extract scores"""
-
-        observed_count = assessment_text.lower().count("observed") - assessment_text.lower().count("not observed")
-        total_competencies = 18
-        percentage = (observed_count / total_competencies) * 100
-
-        # Professional color scheme with better contrast
-        if percentage >= 85:
-            level = "Exemplary"
-            color = "#0F766E"  # Deep teal
-        elif percentage >= 70:
-            level = "Proficient"
-            color = "#1E40AF"  # Professional blue
-        elif percentage >= 50:
-            level = "Developing"
-            color = "#EA580C"  # Professional orange
-        else:
-            level = "Needs Improvement"
-            color = "#B91C1C"  # Deep red
-
-        return observed_count, total_competencies, percentage, level, color
+    """Parse assessment text to extract scores"""
+    
+    # Method 1: Look for "Status: OBSERVED" vs "Status: NOT OBSERVED" patterns
+    import re
+    
+    # Find all status lines
+    status_pattern = r'Status:\s*(OBSERVED|NOT OBSERVED)'
+    matches = re.findall(status_pattern, assessment_text, re.IGNORECASE)
+    
+    # Count only "OBSERVED" (not "NOT OBSERVED")
+    observed_count = sum(1 for match in matches if match.upper() == "OBSERVED")
+    
+    # If no matches found with Status: pattern, try alternative parsing
+    if len(matches) == 0:
+        # Alternative: Look for competency lines with OBSERVED/NOT OBSERVED
+        lines = assessment_text.split('\n')
+        observed_count = 0
+        
+        for i, line in enumerate(lines):
+            # Look for competency indicators followed by status
+            if 'Competency' in line and i + 1 < len(lines):
+                next_line = lines[i + 1]
+                # Check if the status line indicates OBSERVED (not NOT OBSERVED)
+                if 'OBSERVED' in next_line.upper() and 'NOT OBSERVED' not in next_line.upper():
+                    observed_count += 1
+        
+        # If still no matches, use a more robust pattern
+        if observed_count == 0:
+            # Count lines that say "OBSERVED" but not "NOT OBSERVED"
+            for line in lines:
+                # Clean line for better matching
+                clean_line = line.strip().upper()
+                if clean_line.startswith('STATUS:'):
+                    if 'NOT OBSERVED' in clean_line:
+                        continue
+                    elif 'OBSERVED' in clean_line:
+                        observed_count += 1
+    
+    total_competencies = 18
+    percentage = (observed_count / total_competencies) * 100 if total_competencies > 0 else 0
+    
+    # Professional color scheme with better contrast
+    if percentage >= 85:
+        level = "Exemplary"
+        color = "#0F766E"  # Deep teal
+    elif percentage >= 70:
+        level = "Proficient"
+        color = "#1E40AF"  # Professional blue
+    elif percentage >= 50:
+        level = "Developing"
+        color = "#EA580C"  # Professional orange
+    else:
+        level = "Needs Improvement"
+        color = "#B91C1C"  # Deep red
+    
+    return observed_count, total_competencies, percentage, level, color
 
     def generate_pdf_report(self, assessment_text):
         """Generate a PDF report from the assessment text"""