imp part 3

backend/igny8_core/ai/ai_core.py

@@ -591,7 +591,11 @@ class AICore:
                 image_url = image_data.get('url')
                 revised_prompt = image_data.get('revised_prompt')
                 
-                cost = IMAGE_MODEL_RATES.get(model, 0.040) * n
+                # Use ModelRegistry for image cost (with fallback to constants)
+                from igny8_core.ai.model_registry import ModelRegistry
+                cost = float(ModelRegistry.calculate_cost(model, num_images=n))
+                if cost == 0:
+                    cost = IMAGE_MODEL_RATES.get(model, 0.040) * n
                 print(f"[AI][{function_name}] Step 5: Image generated successfully")
                 print(f"[AI][{function_name}] Step 6: Cost: ${cost:.4f}")
                 print(f"[AI][{function_name}][Success] Image generation completed")
@@ -827,15 +831,24 @@ class AICore:
             }
     
     def calculate_cost(self, model: str, input_tokens: int, output_tokens: int, model_type: str = 'text') -> float:
-        """Calculate cost for API call"""
+        """Calculate cost for API call using ModelRegistry with fallback to constants"""
+        from igny8_core.ai.model_registry import ModelRegistry
+        
         if model_type == 'text':
-            rates = MODEL_RATES.get(model, {'input': 2.00, 'output': 8.00})
-            input_cost = (input_tokens / 1_000_000) * rates['input']
-            output_cost = (output_tokens / 1_000_000) * rates['output']
-            return input_cost + output_cost
+            cost = float(ModelRegistry.calculate_cost(model, input_tokens=input_tokens, output_tokens=output_tokens))
+            if cost == 0:
+                # Fallback to constants
+                rates = MODEL_RATES.get(model, {'input': 2.00, 'output': 8.00})
+                input_cost = (input_tokens / 1_000_000) * rates['input']
+                output_cost = (output_tokens / 1_000_000) * rates['output']
+                return input_cost + output_cost
+            return cost
         elif model_type == 'image':
-            rate = IMAGE_MODEL_RATES.get(model, 0.040)
-            return rate * 1
+            cost = float(ModelRegistry.calculate_cost(model, num_images=1))
+            if cost == 0:
+                rate = IMAGE_MODEL_RATES.get(model, 0.040)
+                return rate * 1
+            return cost
         return 0.0
     
     # Legacy method names for backward compatibility

backend/igny8_core/business/planning/models.py

@@ -1,6 +1,9 @@
 from django.db import models
 from igny8_core.auth.models import SiteSectorBaseModel, SeedKeyword
 from igny8_core.common.soft_delete import SoftDeletableModel, SoftDeleteManager
+import logging
+
+logger = logging.getLogger(__name__)
 
 
 class Clusters(SoftDeletableModel, SiteSectorBaseModel):
@@ -39,6 +42,27 @@ class Clusters(SoftDeletableModel, SiteSectorBaseModel):
     
     def __str__(self):
         return self.name
+    
+    def soft_delete(self, user=None, reason=None, retention_days=None):
+        """
+        Override soft_delete to cascade status reset to related Keywords.
+        When a cluster is deleted, its keywords should:
+        - Have their cluster FK set to NULL (handled by SET_NULL)
+        - Have their status reset to 'new' (orphaned keywords)
+        """
+        # Reset related keywords status to 'new' and clear cluster FK
+        keywords_count = self.keywords.filter(is_deleted=False).update(
+            cluster=None,
+            status='new'
+        )
+        
+        logger.info(
+            f"[Clusters.soft_delete] Cluster {self.id} '{self.name}' cascade: "
+            f"reset {keywords_count} keywords to status='new'"
+        )
+        
+        # Call parent soft_delete
+        super().soft_delete(user=user, reason=reason, retention_days=retention_days)
 
 
 class Keywords(SoftDeletableModel, SiteSectorBaseModel):