SIENTIAPDE-1231

Update model retraining and reporting functionality

- Changed the GITHUB_BRANCH value in values.yaml to reflect the latest adjustments for retraining the courier.
- Enhanced the Gates class with a new method `format_retrain_report` to format retraining report data according to storage policies.
- Refactored the MLFlow class to improve error handling during model retraining and return structured output.
- Updated the model_repository to utilize the latest MLFlow API for retrieving model versions and improved logging.
- Modified the minimal_retrain workflow to conditionally update the production model based on retraining success.

laborious/workflows/minimal_retrain.py

@@ -91,13 +91,29 @@ class MinimalRetrain():
             start_to_close_timeout=timedelta(seconds=60)
         )
 
+        if experiment_response['success']:
+
+            update_report = await workflow.execute_activity_method(
+                Activities.update_production_model,
+                {
+                    **metadata,
+                    'model_name': model_name,
+                    **experiment_response
+                },
+                retry_policy=retry_policy,
+                start_to_close_timeout=timedelta(seconds=60)
+            )
+        else:
+            update_report = {}
+
         report = await workflow.execute_activity_method(
-            Activities.update_production_model,
+            Activities.format_retrain_report,
             {
                 **metadata,
-                'model_name': model_name,
+                'experiment_response': experiment_response,
                 'model_id': input_data['model_id'],
-                **experiment_response
+                'model_name': model_name,
+                'update_report': update_report
             },
             retry_policy=retry_policy,
             start_to_close_timeout=timedelta(seconds=60)