Update app.py

app.py

@@ -478,8 +478,9 @@ def generate_abuse_score_chart(dates, scores, patterns):
         x = range(len(scores))
         plt.plot(x, scores, 'bo-', linewidth=2, markersize=8)
         
-        # Add labels for each point
+        # Add labels for each point with highest scoring pattern
         for i, (score, pattern) in enumerate(zip(scores, patterns)):
+            # Get the pattern and its score
             plt.annotate(
                 f'{pattern}\n{score:.0f}%',
                 (i, score),
@@ -503,11 +504,11 @@ def generate_abuse_score_chart(dates, scores, patterns):
         # X-axis labels
         plt.xticks(x, dates, rotation=45)
         
-        # Risk level bands
-        plt.axhspan(0, 50, color='#90EE90', alpha=0.2)   # light green
-        plt.axhspan(50, 70, color='#FFD700', alpha=0.2)  # gold
-        plt.axhspan(70, 85, color='#FFA500', alpha=0.2)  # orange
-        plt.axhspan(85, 100, color='#FF6B6B', alpha=0.2) # light red
+        # Risk level bands with better colors
+        plt.axhspan(0, 50, color='#90EE90', alpha=0.2)   # light green - Low Risk
+        plt.axhspan(50, 70, color='#FFD700', alpha=0.2)  # gold - Moderate Risk
+        plt.axhspan(70, 85, color='#FFA500', alpha=0.2)  # orange - High Risk
+        plt.axhspan(85, 100, color='#FF6B6B', alpha=0.2) # light red - Critical Risk
         
         # Add risk level labels
         plt.text(-0.2, 25, 'Low Risk', rotation=90, va='center')
@@ -529,6 +530,7 @@ def generate_abuse_score_chart(dates, scores, patterns):
         logger.error(f"Error generating abuse score chart: {e}")
         return None
 
+
 def analyze_composite(msg1, msg2, msg3, *answers_and_none):
     """Analyze multiple messages and checklist responses"""
     logger.debug("\n🔄 STARTING NEW ANALYSIS")
@@ -915,10 +917,20 @@ def analyze_composite(msg1, msg2, msg3, *answers_and_none):
 
         # Generate Timeline
         logger.debug("\n📈 Generating Timeline")
-        pattern_labels = [
-            pats[0][0] if (pats := r[0][2]) else "none"
-            for r in results
-        ]
+        pattern_labels = []
+        for result, _ in results:
+            matched_scores = result[2]  # Get the matched_scores from the result tuple
+            if matched_scores:
+                # Sort matched_scores by score and get the highest scoring pattern
+                highest_pattern = max(matched_scores, key=lambda x: x[1])
+                pattern_labels.append(highest_pattern[0])  # Add the pattern name
+            else:
+                pattern_labels.append("none")
+
+        logger.debug("Pattern labels for timeline:")
+        for i, (pattern, score) in enumerate(zip(pattern_labels, abuse_scores)):
+            logger.debug(f"Message {i+1}: {pattern} ({score:.1f}%)")
+
         timeline_image = generate_abuse_score_chart(dates_used, abuse_scores, pattern_labels)
         logger.debug("Timeline generated successfully")