Update app.py

app.py

@@ -138,26 +138,26 @@ def detect_contradiction(message):
     return any(re.search(p, message, flags) for p, flags in patterns)
     
 def calculate_darvo_score(patterns, sentiment_before, sentiment_after, motifs_found, contradiction_flag=False):
-    pattern_hits = sum(1 for p in patterns if p in DARVO_PATTERNS or any(d in p.lower() for d in ["blame", "project", "dismiss", "guilt", "contradict"]))
-    pattern_score = pattern_hits / len(DARVO_PATTERNS)
+    # Count all detected DARVO-related patterns
+    pattern_hits = sum(1 for p in patterns if p.lower() in DARVO_PATTERNS)
 
-    # 🎯 New: If 2+ DARVO patterns are hit, ignore sentiment discount
-    if pattern_hits >= 2:
-        sentiment_shift_score = 0.2
-    else:
-        sentiment_shift_score = max(0.0, sentiment_after - sentiment_before)
+    # Sentiment delta
+    sentiment_shift_score = max(0.0, sentiment_after - sentiment_before)
 
-    text_lower = " ".join(motifs_found).lower()
-    motif_hits = len([
-        phrase for phrase in DARVO_MOTIFS
-        if phrase.lower() in text_lower
-    ])
-    motif_score = motif_hits / len(DARVO_MOTIFS)
+    # Match against DARVO motifs more loosely
+    motif_hits = sum(
+        any(phrase.lower() in motif.lower() or motif.lower() in phrase.lower()
+            for phrase in DARVO_MOTIFS)
+        for motif in motifs_found
+    )
+    motif_score = motif_hits / max(len(DARVO_MOTIFS), 1)
 
+    # Contradiction still binary
     contradiction_score = 1.0 if contradiction_flag else 0.0
 
+    # Final DARVO score
     return round(min(
-        0.3 * pattern_score +
+        0.3 * pattern_hits +
         0.3 * sentiment_shift_score +
         0.25 * motif_score +
         0.15 * contradiction_score, 1.0