Hardening follow-up: N+1 elimination, type validation, diversify fix

Additional fixes from parallel hardening streams:

- exercise/serializers: remove unused WorkoutEquipment import, add prefetch docs
- generator/serializers: N+1 fix in GeneratedWorkoutDetailSerializer (inline workout dict, prefetch-aware supersets)
- generator/services/plan_builder: eliminate redundant .save() after .create() via single create_kwargs dict
- generator/services/workout_generator: proper type-match validation for HIIT/cardio/core/flexibility; fix diversify type count to account for removed entry
- generator/views: request-level caching for get_registered_user helper; prefetch chain for accept_workout
- superset/serializers: guard against dangling FK in SupersetExerciseSerializer
- workout/helpers: use prefetched data instead of re-querying per superset

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

generator/serializers.py

@@ -330,18 +330,29 @@ class GeneratedWorkoutDetailSerializer(serializers.ModelSerializer):
 
     def get_workout_detail(self, obj):
         if obj.workout:
-            return WorkoutDetailSerializer(obj.workout).data
+            return {
+                'id': obj.workout.id,
+                'name': obj.workout.name,
+                'description': obj.workout.description,
+                'estimated_time': obj.workout.estimated_time,
+            }
         return None
 
     def get_supersets(self, obj):
-        if obj.workout:
+        if not obj.workout:
+            return []
+        # Use prefetched data if available (via workout__superset_workout prefetch),
+        # otherwise fall back to a query with its own prefetch
+        workout = obj.workout
+        if hasattr(workout, '_prefetched_objects_cache') and 'superset_workout' in workout._prefetched_objects_cache:
+            superset_qs = sorted(workout.superset_workout.all(), key=lambda s: s.order)
+        else:
             superset_qs = Superset.objects.filter(
-                workout=obj.workout
+                workout=workout
             ).prefetch_related(
-                'supersetexercise_set__exercise',
+                'superset_exercises__exercise',
             ).order_by('order')
-            return SupersetSerializer(superset_qs, many=True).data
-        return []
+        return SupersetSerializer(superset_qs, many=True).data
 
 
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