Update app.py

app.py

@@ -200,7 +200,20 @@ def analyze_single_message(text):
     inp = tokenizer(text, return_tensors='pt', truncation=True, padding=True)
     with torch.no_grad(): logits=model(**inp).logits.squeeze(0)
     probs=torch.sigmoid(logits).numpy()
-    labels=[lab for lab,p in zip(LABELS,probs) if p>THRESHOLDS[lab]]
+    # …run tokenizer, get `probs` and then:
+    labels = [lab for lab,p in zip(LABELS, probs) if p > THRESHOLDS[lab]]
+
+# **NEW**: if absolutely no pattern is detected, force a zero‐abuse “healthy” return:
+    if not labels:
+        return {
+            "abuse_score": 0,
+            "labels": [],
+            "sentiment": "supportive",
+            "stage": 4,
+            "darvo_score": 0.0,
+            "top_patterns": []
+    }
+
     # abuse score
     total_w=sum(PATTERN_WEIGHTS.get(l,1.0) for l in LABELS)
     abuse_score=int(round(sum(probs[i]*PATTERN_WEIGHTS.get(l,1.0)