SIENTIAPDE-994

Refactor and enhance the laborious workflow and utilities

- Removed outdated test file `test_predictions_batch.py` from workflows.
- Added `input_sample.json` for standardized input configuration.
- Introduced `connectors_config.py` to manage database and service configurations.
- Implemented a logging utility in `logger.py` for consistent logging across the application.
- Created `policies.py` to define retry policies for workflows.
- Developed comprehensive tests for `MLFlowRepository` in `test_model_repository.py`.
- Added extensive tests for `OpcRepository` in `test_opc_repository.py`.
- Updated `test_predictions_batch.py` to reflect new workflow structure and testing methodology.

laborious/activities/mlflow.py

@@ -5,17 +5,16 @@ from temporalio import activity, workflow
 
 with workflow.unsafe.imports_passed_through():
     from laborious.activities.base import BaseActivity
+    from laborious.utils.repository.model_repository import MLFlowRepository
     from typing import Any
     from logging import Logger
     from sientia_do.notifications.handlers import NotificationHandler
-    from laborious.utils.repository.model_repository import MLFlowRepository
-    from sientia_do.notifications.models import NotificationLevel
 
 
 class MLFlow(BaseActivity):
     def __init__(self, mlflow_host: str, mlflow_port: int, mlflow_username: str,
                  mlflow_password: str, logger: Logger, notification_handler: NotificationHandler):
-        super().__init__(logger, notification_handler)
+        BaseActivity.__init__(self, logger, notification_handler)
         self.mlflow_host = mlflow_host
         self.mlflow_port = mlflow_port
         self.mlflow_username = mlflow_username
@@ -33,7 +32,7 @@ class MLFlow(BaseActivity):
             input_data (dict): The input data. Contains:
                 data (dict[str, Any]): The data to transform.
                 model_name (str): The name of the model.
-                model_retention (int): The retention of the model.
+                model_retention (int): The retention of the model in minutes.
         Returns:
             dict[str, Any]: The transformed data.
         """
@@ -54,6 +53,8 @@ class MLFlow(BaseActivity):
         response_data = self.model_monitoring_repository.transform(
             model_name, data, model_retention)
 
+        self.logger.debug(response_data)
+
         return response_data
 
     @activity.defn(name="request_predict")
@@ -80,4 +81,6 @@ class MLFlow(BaseActivity):
         response_data = self.model_monitoring_repository.predict(
             model_name, data, model_retention)
 
+        self.logger.debug(response_data)
+
         return response_data