SIENTIAPDE-1222

SIENTIAPDE-1214: Enhance MLFlow and tests with datetime index handling and logging improvements

- Added a new method in MLFlow to detect and parse datetime indices in DataFrames, ensuring proper format and raising errors for invalid types.
- Updated prediction workflows to utilize the new datetime index handling, improving data integrity during transformations.
- Enhanced logging in model_repository to include detailed data outputs for better traceability.
- Adjusted timeout settings in prediction workflows for improved execution time management.
- Updated tests.ipynb to include additional checks for index types and outputs for better validation of functionality.

laborious/workflows/predictions_batch.py

@@ -87,7 +87,7 @@ class PredictionsBatch():
                 'datetime_columns': input_data.get('datetime_columns', [])
             },
             retry_policy=retry_policy,
-            start_to_close_timeout=timedelta(seconds=60)
+            start_to_close_timeout=timedelta(seconds=300)
         )
 
         # Prepare input for prediction_process workflow

laborious/workflows/sub_workflows/prediction_process.py

@@ -123,7 +123,7 @@ class PredictionProcess():
                 'model_config': model_config
             },
             retry_policy=retry_policy,
-            start_to_close_timeout=timedelta(minutes=1),
+            start_to_close_timeout=timedelta(minutes=5),
         )
 
         # Validate MLFlow transform response
@@ -175,7 +175,7 @@ class PredictionProcess():
                 'model_config': model_config
             },
             retry_policy=retry_policy,
-            start_to_close_timeout=timedelta(minutes=1),
+            start_to_close_timeout=timedelta(minutes=5),
         )
 
         # Validate MLFlow prediction response