SIENTIAPDE-1253: Enforce TrainModelParams object in Training activity and tests, removing dict conversion.

model_manager/activities/training.py

@@ -71,7 +71,7 @@ class Training(BaseActivity):
                 Required keys:
                     - metadata (dict): Workflow execution metadata
                     - uploaded_file (BytesIO): Training data file (already downloaded from MinIO)
-                    - train_params (dict): Training parameters (converted to TrainModelParams)
+                    - train_params (TrainModelParams): Training parameters object
 
         Returns:
             dict: Training result with the following structure:
@@ -86,15 +86,7 @@ class Training(BaseActivity):
             result = await train_model({
                 'metadata': {'workflow_id': 'train-123', 'experiment_run_id': 456},
                 'uploaded_file': BytesIO(csv_data),
-                'train_params': {
-                    'experiment_run_id': 456,
-                    'target_variable': 'price',
-                    'variable_columns': ['feature1', 'feature2'],
-                    'train_size': 80,
-                    'shuffle': True,
-                    'use_scaler': True,
-                    # ... other TrainModelParams fields
-                }
+                'train_params': TrainModelParams(...)  # Already converted object
             })
             # Returns: {'success': True, 'result': TrainModelResult(...), 'error_message': None}
 
@@ -103,21 +95,22 @@ class Training(BaseActivity):
         """
         metadata = input_data.get('metadata', {})
         uploaded_file = input_data['uploaded_file']
-        train_params_dict = input_data['train_params']
+        train_params = input_data['train_params']
 
         try:
-            self.info(
-                f'Starting model training for target: {train_params_dict.get("target_variable")}',
-                metadata,
-            )
-
-            # Convert dict to TrainModelParams
-            train_params = TrainModelParams.from_dict(train_params_dict)
-
             # Validate uploaded_file is BytesIO
             if not isinstance(uploaded_file, BytesIO):
                 raise ValueError(f'uploaded_file must be BytesIO, got {type(uploaded_file)}')
 
+            # Validate train_params is TrainModelParams
+            if not isinstance(train_params, TrainModelParams):
+                raise ValueError(f'train_params must be TrainModelParams, got {type(train_params)}')
+
+            self.info(
+                f'Starting model training for target: {train_params.target_variable}',
+                metadata,
+            )
+
             # Step 1: Train the model
             self.info('Training model with TrainingRepository', metadata)
             train_result = self.training_repository.train(uploaded_file, train_params)
@@ -141,7 +134,12 @@ class Training(BaseActivity):
             }
 
         except Exception as e:  # noqa: BLE001
-            error_msg = f'Error training model - Target: {train_params_dict.get("target_variable", "unknown")}, Error: {str(e)}'
+            target = (
+                train_params.target_variable
+                if hasattr(train_params, 'target_variable')
+                else 'unknown'
+            )
+            error_msg = f'Error training model - Target: {target}, Error: {str(e)}'
             trace = traceback.format_exc()
 
             # Send notification (MongoDB)