Update app.py

app.py

@@ -72,7 +72,7 @@ LABELS = [
 ]
 
 THRESHOLDS = {
-    "recovery": 0.75,
+    "recovery": 0.100,
     "control": 0.100,
     "gaslighting": 0.410,
     "dismissiveness": 0.867,
@@ -459,7 +459,10 @@ def analyze_single_message(text, thresholds):
         if score > adjusted_thresholds[label]
     ]
     # Post-threshold validation: strip recovery if it occurs with undermining sentiment
-    if "recovery" in threshold_labels and sentiment == "undermining":
+    # Override top label if recovery was removed
+    if "recovery" in threshold_labels and tone_tag == "forced accountability flip":
+        threshold_labels.remove("recovery")
+        top_patterns = [p for p in top_patterns if p[0] != "recovery"]
         print("⚠️ Removing 'recovery' due to undermining sentiment (not genuine repair)")
         threshold_labels.remove("recovery")
     motifs = [phrase for _, phrase in matched_phrases]