Update app.py

app.py

@@ -143,8 +143,21 @@ def analyze_single_message(text, thresholds):
         reverse=True
     )[:2]
 
-    weighted_scores = [(PATTERN_WEIGHTS.get(label, 1.0) * score) for label, score in top_patterns]
-    abuse_score = min(np.mean(weighted_scores) * 100, 100)
+    # Compute weighted average across all patterns (not just top 2)
+    weighted_total = 0.0
+    weight_sum = 0.0
+for label, score in zip(LABELS, scores):
+    weight = PATTERN_WEIGHTS.get(label, 1.0)
+    weighted_total += score * weight
+    weight_sum += weight
+
+abuse_score_raw = (weighted_total / weight_sum) * 100
+
+# Cap abuse intensity at 100 only if high-threat patterns are present
+if "threat" in threshold_labels or "control" in threshold_labels or "insults" in threshold_labels:
+    abuse_score = min(abuse_score_raw, 100)
+else:
+    abuse_score = min(abuse_score_raw, 95)
 
     stage = get_risk_stage(threshold_labels, sentiment)