Deep fix: Add comprehensive state validation before logging training cycles to prevent type errors

scripts/feedback_learning_pipeline.py

@@ -327,17 +327,22 @@ class FeedbackLearningPipeline:
                 if after_state and isinstance(after_state, dict):
                     print(f"[Model Versioning] Captured state after training: {after_state.get('version_id', 'unknown')[:8]}...")
                 
-                # Log the training cycle with before/after comparison
-                training_cycle_id = self.version_tracker.log_training_cycle(
-                    before_state=before_state,
-                    after_state=after_state,
-                    feedback_count=len(corrections),
-                    patterns=patterns,
-                    performance_metrics=None  # TODO: Calculate actual metrics
-                )
-                
-                if training_cycle_id:
-                    print(f"[Training History] Logged training cycle: {training_cycle_id[:8]}...")
+                # Only log training cycle if both states are valid dictionaries
+                if (before_state and isinstance(before_state, dict) and 
+                    after_state and isinstance(after_state, dict)):
+                    # Log the training cycle with before/after comparison
+                    training_cycle_id = self.version_tracker.log_training_cycle(
+                        before_state=before_state,
+                        after_state=after_state,
+                        feedback_count=len(corrections),
+                        patterns=patterns,
+                        performance_metrics=None  # TODO: Calculate actual metrics
+                    )
+                    
+                    if training_cycle_id:
+                        print(f"[Training History] Logged training cycle: {training_cycle_id[:8]}...")
+                else:
+                    print(f"[Training History] Skipping cycle logging - invalid state data")
             except Exception as e:
                 print(f"[Model Versioning] Error logging version: {e}")
         

scripts/model_versioning.py

@@ -180,6 +180,11 @@ class ModelVersionTracker:
             Training cycle ID if successful
         """
         try:
+            # Validate inputs - ensure states are dictionaries
+            if not isinstance(before_state, dict) or not isinstance(after_state, dict):
+                print(f"[Training History] Error: Invalid state types - before: {type(before_state)}, after: {type(after_state)}")
+                return None
+            
             cycle_id = str(uuid.uuid4())
             
             # Calculate parameter changes