Update app.py

app.py

@@ -72,7 +72,7 @@ LABELS = [
 ]
 
 THRESHOLDS = {
-    "recovery": 0.622,
+    "recovery": 0.75,
     "control": 0.100,
     "gaslighting": 0.410,
     "dismissiveness": 0.867,
@@ -458,7 +458,10 @@ def analyze_single_message(text, thresholds):
         label for label, score in zip(LABELS, scores)
         if score > adjusted_thresholds[label]
     ]
-
+    # Post-threshold validation: strip recovery if it occurs with undermining sentiment
+    if "recovery" in threshold_labels and sentiment == "undermining":
+        print("⚠️ Removing 'recovery' due to undermining sentiment (not genuine repair)")
+        threshold_labels.remove("recovery")
     motifs = [phrase for _, phrase in matched_phrases]
 
     darvo_score = calculate_darvo_score(