Update app.py

app.py

@@ -40,8 +40,8 @@ THRESHOLDS = {
 }
 
 # Define label groups using slicing (first 14: abuse patterns, last 3: danger cues)
-PATTERN_LABELS = LABELS[:17]
-DANGER_LABELS = LABELS[17:]
+PATTERN_LABELS = LABELS[:14]
+DANGER_LABELS = LABELS[:3]
 
 def calculate_abuse_level(scores, thresholds):
     triggered_scores = [score for label, score in zip(LABELS, scores) if score > thresholds[label]]
@@ -73,8 +73,8 @@ def analyze_messages(input_text):
     scores = torch.sigmoid(outputs.logits.squeeze(0)).numpy()
 
     # Count the number of triggered abuse pattern and danger flags based on thresholds
-    pattern_count = sum(score > THRESHOLDS[label] for label, score in zip(PATTERN_LABELS, scores[:17]))
-    danger_flag_count = sum(score > THRESHOLDS[label] for label, score in zip(DANGER_LABELS, scores[17:]))
+    pattern_count = sum(score > THRESHOLDS[label] for label, score in zip(PATTERN_LABELS, scores[:14]))
+    danger_flag_count = sum(score > THRESHOLDS[label] for label, score in zip(DANGER_LABELS, scores[3:]))
     # Build formatted raw score display
 score_lines = [
     f"{label:25}: {score:.3f}" for label, score in zip(PATTERN_LABELS + DANGER_LABELS, scores)