Update app.py

app.py

@@ -168,25 +168,27 @@ class SimplifiedBoundaryAssistant:
         else:
             logger.info(f"No toxicity detected (pred: {toxicity_pred}, conf: {toxicity_conf})")
         
-        # 3. Boundary Health Check (1=healthy, 0=unhealthy)
+        # 3. Boundary Health Check (0=Respected, 1=Violated, 2=Dismissed, 3=Manipulative)
         logger.info("Running boundary health check...")
         boundary_pred, boundary_conf = self.predict_with_model(text, 'boundary')
         if boundary_pred is not None:
-            if boundary_pred == 0 and boundary_conf > 0.7:  # 0 = unhealthy
-                logger.info(f"UNHEALTHY BOUNDARY DETECTED: confidence {boundary_conf:.3f}")
+            if boundary_pred == 0:  # 0 = Respected
+                logger.info(f"HEALTHY BOUNDARY DETECTED: confidence {boundary_conf:.3f}")
+                analysis['is_healthy_boundary'] = True
+            elif boundary_pred in [1, 2, 3] and boundary_conf > 0.7:  # 1=Violated, 2=Dismissed, 3=Manipulative
+                boundary_type = {1: "Violated", 2: "Dismissed", 3: "Manipulative"}[boundary_pred]
+                logger.info(f"UNHEALTHY BOUNDARY DETECTED ({boundary_type}): confidence {boundary_conf:.3f}")
                 analysis['is_healthy_boundary'] = False
                 analysis['issues'].append({
                     'type': 'unhealthy_boundary',
-                    'name': 'Unhealthy Boundary Pattern',
+                    'name': f'{boundary_type} Boundary Pattern',
                     'confidence': boundary_conf,
                     'severity': 2 if boundary_conf > 0.8 else 1
                 })
                 analysis['severity_score'] += 2 if boundary_conf > 0.8 else 1
-            elif boundary_pred == 1:  # 1 = healthy
-                logger.info(f"HEALTHY BOUNDARY DETECTED: confidence {boundary_conf:.3f}")
-                analysis['is_healthy_boundary'] = True
         else:
             logger.info(f"Boundary health check failed")
+
         
         # 4. Fallacy Detection
         logger.info("Running fallacy detection...")