Update app.py

app.py

@@ -62,9 +62,18 @@ def custom_sentiment(text):
     score = probs[0][label_idx].item()
     return {"label": label, "score": score}
 
-def calculate_abuse_level(scores, thresholds):
-    triggered_scores = [score for label, score in zip(LABELS, scores) if score > thresholds[label]]
-    return round(np.mean(triggered_scores) * 100, 2) if triggered_scores else 0.0
+def calculate_abuse_level(scores, thresholds, motif_hits=None):
+    triggered_scores = [
+        score for label, score in zip(LABELS, scores) if score > thresholds[label]
+    ]
+    base_score = round(np.mean(triggered_scores) * 100, 2) if triggered_scores else 0.0
+
+    # Boost score if high-risk motifs were detected
+    motif_hits = motif_hits or []
+    if any(label in motif_hits for label in {"physical_threat", "suicidal_threat", "extreme_control"}):
+        base_score = max(base_score, 60.0)  # Push to "Severe / Harmful Pattern Present"
+
+    return base_score
 
 def interpret_abuse_level(score):
     if score > 80:
@@ -110,7 +119,7 @@ def analyze_messages(input_text, risk_flags):
     if non_abusive_score > adjusted_thresholds['non_abusive']:
         return "This message is classified as non-abusive."
 
-    abuse_level = calculate_abuse_level(scores, adjusted_thresholds)
+    abuse_level = calculate_abuse_level(scores, adjusted_thresholds, motif_hits=[label for label, _ in matched_phrases])
     abuse_description = interpret_abuse_level(abuse_level)
 
     if danger_flag_count >= 2: