SIENTIAPDE-1214

SIENTIAPDE-1214: Refactor MLFlow and model repository methods to use model_config dictionary

- Updated MLFlow class methods to accept model_config instead of model_retention for improved flexibility.
- Modified model_repository methods to handle model_config, extracting necessary parameters for transformation and prediction.
- Adjusted predictions_batch and prediction_process workflows to utilize model_config for better configuration management.
- Commented out the previous sientia-mlops-library dependency in requirements.txt for clarity.

laborious/workflows/predictions_batch.py

@@ -113,7 +113,7 @@ class PredictionsBatch():
                     'POLICY': 'STOP'
                 }
             }),
-            'model_retention': input_data.get('model_retention', 60),
+            'model_config': input_data.get('model_config', {}),
             'path_priority': input_data.get('path_priority', ['STOP', 'CONTINUE', 'REPEAT']),
             'opc_output_config': input_data.get('opc_output_config', {})
         }

laborious/workflows/sub_workflows/prediction_process.py

@@ -79,7 +79,7 @@ class PredictionProcess():
         data = input_data['data']
         model_id = input_data['model_id']
         model_name = input_data['model_name']
-        model_retention = input_data['model_retention']
+        model_config = input_data.get('model_config', {})
 
         # Get last timestamp for incremental processing
         last_timestamp = await workflow.execute_local_activity_method(
@@ -120,7 +120,7 @@ class PredictionProcess():
                 **metadata,
                 'data': data,
                 'model_name': model_name,
-                'model_retention': model_retention
+                'model_config': model_config
             },
             retry_policy=retry_policy,
             start_to_close_timeout=timedelta(minutes=1),
@@ -172,7 +172,7 @@ class PredictionProcess():
                 **metadata,
                 'data': transformed_data,
                 'model_name': model_name,
-                'model_retention': model_retention
+                'model_config': model_config
             },
             retry_policy=retry_policy,
             start_to_close_timeout=timedelta(minutes=1),
@@ -209,7 +209,7 @@ class PredictionProcess():
                 'timestamp': last_timestamp,
                 'model_id': model_id,
                 'model_name': model_name,
-                'model_retention': model_retention,
+                'model_config': model_config,
                 'opc_output_config': input_data['opc_output_config'],
                 'schema': input_data['schema'],
                 'table_name': input_data['table_name'],
@@ -248,7 +248,7 @@ class PredictionProcess():
         table_name = input_data['table_name']
         model_id = input_data['model_id']
         model_name = input_data['model_name']
-        model_retention = input_data['model_retention']
+        model_config = input_data.get('model_config', {})
 
         path_flag = path_flag.upper() if path_flag else ''
 
@@ -282,7 +282,7 @@ class PredictionProcess():
                     'timestamp': last_timestamp,
                     'model_id': model_id,
                     'model_name': model_name,
-                    'model_retention': model_retention,
+                    'model_config': model_config,
                     'schema': schema,
                     'table_name': table_name,
                     'comment': comment,