Update app.py

app.py

@@ -576,21 +576,21 @@ def analyze_composite(msg1, date1, msg2, date2, msg3, date3, *answers_and_none):
     responses_checked = any(answers_and_none[:-1])
     none_selected = not responses_checked and none_selected_checked
 
-if none_selected:
-    escalation_score = None
-    risk_level = "unknown"
-else:
-    escalation_score = sum(w for (_, w), a in zip(ESCALATION_QUESTIONS, answers_and_none[:-1]) if a)
+    if none_selected:
+        escalation_score = None
+        risk_level = "unknown"
+    else:
+        escalation_score = sum(w for (_, w), a in zip(ESCALATION_QUESTIONS, answers_and_none[:-1]) if a)
 
     # Abuse label escalation logic
-    high = {'Control'}
-    moderate = {
+        high = {'Control'}
+        moderate = {
         'Gaslighting', 'Dismissiveness', 'Obscure Language',
         'Insults', 'Contradictory Statements', 'Guilt-tripping'
-    }
-    low = {'Blame-shifting', 'Projection', 'Recovery'}
+        }
+        low = {'Blame-shifting', 'Projection', 'Recovery'}
 
-    counts = {'high': 0, 'moderate': 0, 'low': 0}
+        counts = {'high': 0, 'moderate': 0, 'low': 0}
     for label in predicted_labels:
         if label in high:
             counts['high'] += 1