Update app.py

app.py

@@ -174,8 +174,8 @@ def analyze_composite(msg1, msg2, msg3, flags):
     base_score = sum(abuse_scores) / len(abuse_scores)
     label_sets = [[label for label, _ in r[2]] for r in results]
     label_counts = {label: sum(label in s for s in label_sets) for label in set().union(*label_sets)}
-    top_labels = sorted(label_counts.items(), key=lambda x: x[1], reverse=True)[:2]
-    top_explanations = [EXPLANATIONS.get(label, "") for label, _ in top_labels]
+    top_label = max(label_counts.items(), key=lambda x: x[1])
+    top_explanation = EXPLANATIONS.get(top_label[0], "")
 
     # Adjust flag-based weight relative to number of messages
     danger_weight = 5
@@ -197,10 +197,11 @@ def analyze_composite(msg1, msg2, msg3, flags):
     composite_score = round(min(composite_score, 100), 2)  # re-cap just in case
     result = f"These messages show patterns of {', '.join(label for label, _ in top_labels)} and are estimated to be {composite_score}% likely abusive."
 
-# Include pattern explanations
-    for expl in top_explanations:
-        if expl:
-            result += f"\n• {expl}"
+    # Include pattern explanations
+    result = f"These messages show a pattern of **{top_label[0]}** and are estimated to be {composite_score}% likely abusive."
+
+    if top_explanation:
+        result += f"\n• {top_explanation}"
 
 # Show DARVO score
     if average_darvo > 0.25: