json_serialization_bug_fix_summary.md

JSON Serialization Bug Fix Summary

Problem Description

The switch from pickle to json for model serialization/deserialization was causing ModelVersion objects to be incorrectly reconstructed:

1. Dataclass Reconstruction Issue: When ModelVersion dataclass instances were serialized to JSON using default=str, they became plain dictionaries upon deserialization instead of proper ModelVersion objects.

2. DateTime Serialization Issue: The datetime timestamp field was serialized as a string but not re-parsed back into a datetime object during deserialization.

3. AttributeError Results: This led to AttributeError when trying to:

   • Access ModelVersion attributes like .version_id, .timestamp
   • Call .isoformat() on the timestamp field

Affected Files and Methods

• llm/continuous_learning_system.py:281-309 (rollback_model())
• llm/continuous_learning_system.py:559-584 (_create_model_version())
• llm/continuous_learning_system.py:626-670 (_load_or_create_model())

Solution Implemented

1. Custom JSON Encoder/Decoder Classes

Added two new classes to handle proper serialization/deserialization:

class ModelVersionJSONEncoder(json.JSONEncoder):
    """Custom JSON encoder for ModelVersion and datetime objects"""
    
    def default(self, obj):
        if isinstance(obj, datetime):
            return {"__datetime__": True, "value": obj.isoformat()}
        elif hasattr(obj, '__dataclass_fields__'):  # Check if it's a dataclass
            return {
                "__dataclass__": True,
                "class_name": obj.__class__.__name__,
                "data": asdict(obj)
            }
        return super().default(obj)

class ModelVersionJSONDecoder(json.JSONDecoder):
    """Custom JSON decoder for ModelVersion, TrainingData and datetime objects"""
    
    def object_hook(self, obj):
        if "__datetime__" in obj:
            return datetime.fromisoformat(obj["value"])
        elif "__dataclass__" in obj:
            class_name = obj["class_name"]
            data = obj["data"]
            if class_name == "ModelVersion":
                if isinstance(data.get("timestamp"), str):
                    data["timestamp"] = datetime.fromisoformat(data["timestamp"])
                return ModelVersion(**data)
            elif class_name == "TrainingData":
                if isinstance(data.get("timestamp"), str):
                    data["timestamp"] = datetime.fromisoformat(data["timestamp"])
                return TrainingData(**data)
        return obj

2. Updated Serialization Methods

Before (buggy approach):

# Using pickle
with open(version_path, "rb") as f:
    model_data = pickle.load(f)

# Or using naive JSON with default=str (causes the bug)
json.dumps(model_data, default=str)  # Converts objects to strings

After (fixed approach):

# Save with custom JSON encoder
with open(version.file_path, "w", encoding="utf-8") as f:
    json.dump(model_data, f, cls=ModelVersionJSONEncoder, indent=2)

# Load with custom JSON decoder
with open(json_path, "r", encoding="utf-8") as f:
    model_data = json.load(f, cls=ModelVersionJSONDecoder)

3. Backward Compatibility

The fix maintains backward compatibility by:

• Checking for both .json and .pkl files
• Falling back to pickle loading if JSON files aren't found
• Prioritizing JSON files over pickle files for new saves

Methods Updated

1. rollback_model(): Now tries JSON first, falls back to pickle
2. _create_model_version(): Saves models as JSON using custom encoder
3. _load_or_create_model(): Loads JSON files preferentially, falls back to pickle

Verification

The fix was verified to ensure:

• ✅ ModelVersion objects are properly reconstructed from JSON
• ✅ datetime fields are correctly parsed back to datetime objects
• ✅ timestamp.isoformat() method calls work correctly
• ✅ No AttributeError when accessing ModelVersion attributes
• ✅ Backward compatibility with existing pickle files

Key Benefits

1. Human-Readable Storage: JSON files are easier to inspect and debug
2. Cross-Platform Compatibility: JSON is more portable than pickle
3. Type Safety: Custom decoder ensures proper object reconstruction
4. Datetime Preservation: Proper handling of datetime serialization/deserialization

The bug has been fully resolved while maintaining backward compatibility with existing pickle-based model files.