Update app.py

app.py

@@ -394,11 +394,27 @@ def analyze_single_message(text, thresholds):
         key=lambda x: x[1],
         reverse=True
     )[:2]
+    # Escalation-based top label override
+    ESCALATION_HIERARCHY = [
+        "threat", "insults", "control", "blame shifting", "gaslighting",
+        "guilt tripping", "projection", "dismissiveness", "contradictory statements",
+        "recovery phase", "obscure language"
+]
 
-    matched_scores = [
-        (label, score, PATTERN_WEIGHTS.get(label, 1.0))
-        for label, score in zip(LABELS, scores)
-        if score > adjusted_thresholds[label]
+    label_scores = {label: score for label, score in zip(LABELS, scores)}
+    passed = {label: score for label in threshold_labels if label in label_scores}
+
+    if passed:
+        top_score = max(passed.values())
+        close_matches = {label: score for label, score in passed.items() if (top_score - score) <= 0.05}
+        sorted_close = sorted(close_matches.items(), key=lambda x: ESCALATION_HIERARCHY.index(x[0]))
+        top_pattern_label, top_pattern_score = sorted_close[0]
+    else:
+        top_pattern_label, top_pattern_score = top_patterns[0]
+        matched_scores = [
+            (label, score, PATTERN_WEIGHTS.get(label, 1.0))
+            for label, score in zip(LABELS, scores)
+            if score > adjusted_thresholds[label]
     ]
 
     abuse_score_raw = compute_abuse_score(matched_scores, sentiment)
@@ -434,7 +450,7 @@ def analyze_single_message(text, thresholds):
     print(f"Contradiction: {contradiction_flag}")
     print("------------------\n")
 
-    return abuse_score, threshold_labels, top_patterns, {"label": sentiment}, stage, darvo_score
+    return abuse_score, threshold_labels, top_patterns, {"label": sentiment}, stage, darvo_score, top_pattern_label
 
 def analyze_composite(msg1, date1, msg2, date2, msg3, date3, *answers_and_none):
     none_selected_checked = answers_and_none[-1]
@@ -459,10 +475,10 @@ def analyze_composite(msg1, date1, msg2, date2, msg3, date3, *answers_and_none):
         return "Please enter at least one message."
 
     results = [(analyze_single_message(m, THRESHOLDS.copy()), d) for m, d in active]
+    top_labels = [r[0][6] for r in results]
     for result, date in results:
         assert len(result) == 6, "Unexpected output from analyze_single_message"
     abuse_scores = [r[0][0] for r in results]
-    top_labels = [r[0][1][0] if r[0][1] else r[0][2][0][0] for r in results]
     top_scores = [r[0][2][0][1] for r in results]
     sentiments = [r[0][3]['label'] for r in results]
     stages = [r[0][4] for r in results]