SIENTIAPDE-1231

Update model retraining and logging enhancements

- Changed the GITHUB_BRANCH value in values.yaml to 'main' for consistency.
- Refactored MLFlow class to improve timestamp handling and error messaging during model retraining.
- Enhanced MLFlowRepository methods to include metadata logging and improved model version retrieval.
- Updated minimal_retrain workflow to support extended timeout for activities and include model configuration in input data.

laborious/workflows/minimal_retrain.py

@@ -68,6 +68,7 @@ class MinimalRetrain():
         }
 
         model_name = input_data['model_name']
+        model_config = input_data.get('model_config', {})
 
         data = await workflow.execute_local_activity_method(
             Activities.load_custom_query,
@@ -77,7 +78,7 @@ class MinimalRetrain():
                 'datetime_columns': input_data.get('datetime_columns', [])
             },
             retry_policy=retry_policy,
-            start_to_close_timeout=timedelta(seconds=60)
+            start_to_close_timeout=timedelta(seconds=600)
         )
 
         experiment_response = await workflow.execute_activity_method(
@@ -85,10 +86,11 @@ class MinimalRetrain():
             {
                 **metadata,
                 'data': data,
-                'model_name': model_name
+                'model_name': model_name,
+                'model_config': model_config
             },
             retry_policy=retry_policy,
-            start_to_close_timeout=timedelta(seconds=60)
+            start_to_close_timeout=timedelta(seconds=600)
         )
 
         if experiment_response['success']:
@@ -101,7 +103,7 @@ class MinimalRetrain():
                     **experiment_response
                 },
                 retry_policy=retry_policy,
-                start_to_close_timeout=timedelta(seconds=60)
+                start_to_close_timeout=timedelta(seconds=600)
             )
         else:
             update_report = {}
@@ -116,7 +118,7 @@ class MinimalRetrain():
                 'update_report': update_report
             },
             retry_policy=retry_policy,
-            start_to_close_timeout=timedelta(seconds=60)
+            start_to_close_timeout=timedelta(seconds=600)
         )
 
         await workflow.execute_activity_method(
@@ -128,5 +130,5 @@ class MinimalRetrain():
                 'table_name': input_data['table_name']
             },
             retry_policy=retry_policy,
-            start_to_close_timeout=timedelta(seconds=60)
+            start_to_close_timeout=timedelta(seconds=600)
         )