Update app.py

app.py

@@ -96,11 +96,11 @@ def analyze_composite(msg1, msg2, msg3, flags):
     flag_multiplier = 1 + (0.1 * len(flags))  # each checked flag increases weight by 10%
     results = [analyze_single_message(m, thresholds, flags) for m in active_messages]
     abuse_scores = [r[0] for r in results]
-    composite_score = round(sum(abuse_scores) / len(abuse_scores), 2)
-    label_sets = [label for result in results for label in result[1]]
-    label_counts = {label: label_sets.count(label) for label in set(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]
+    base_score = sum(abuse_scores) / len(abuse_scores)
+    danger_weight = 5  # or experiment with this
+    adjusted_score = min(base_score + len(flags) * danger_weight, 100)
+    composite_score = round(adjusted_score, 2)
+
 
     result = f"These messages show patterns of {', '.join(label for label, _ in top_labels)} and are estimated to be {composite_score}% likely abusive."
     for expl in top_explanations: