Update app.py

app.py

@@ -257,33 +257,19 @@ def analyze_single_message(text, thresholds):
         reverse=True
     )[:2]
 
-    # Compute weighted average across all patterns (not just top 2)
-    # ✅ Only include passed labels in abuse intensity calculation
-    matched_scores = [
-        (label, score, PATTERN_WEIGHTS.get(label, 1.0))
-        for label, score in zip(LABELS, scores)
-        if score > adjusted_thresholds[label]
-]
-
-    if matched_scores:
-        weighted_total = sum(score * weight for _, score, weight in matched_scores)
-        weight_sum = sum(weight for _, _, weight in matched_scores)
-        abuse_score_raw = (weighted_total / weight_sum) * 100
-    else:
-        abuse_score_raw = 0
-
     matched_scores = [
     (label, score, PATTERN_WEIGHTS.get(label, 1.0))
     for label, score in zip(LABELS, scores)
     if score > adjusted_thresholds[label]
 ]
-
     if matched_scores:
         weighted_total = sum(score * weight for _, score, weight in matched_scores)
         weight_sum = sum(weight for _, _, weight in matched_scores)
         abuse_score_raw = (weighted_total / weight_sum) * 100
     else:
         abuse_score_raw = 0
+    print(f"Matched patterns used for abuse scoring: {[(l, round(s, 3)) for l, s, _ in matched_scores]}")
+    print(f"Abuse Score Raw: {round(abuse_score_raw, 1)}")
     if threshold_labels:
         stage = get_risk_stage(threshold_labels, sentiment)
     else: