SIENTIAPDE-1171

Refactor model_repository and enhance test coverage for MLFlow functionalities

- Updated model_repository to ensure the 'temp' directory is created if it doesn't exist using `exist_ok=True`.
- Added new tests for retraining and updating production models, including error handling scenarios.
- Improved existing tests for model management workflows to ensure robustness and reliability.

tests/laborious/utils/repository/test_model_repository.py

@@ -164,6 +164,18 @@ def test_get_experiment_last_run(mlflow, mlflow_repository):
     assert output == '2'
 
 
+@patch('laborious.utils.repository.model_repository.mlflow')
+def test_get_experiment_last_run_error(mlflow, mlflow_repository):
+    mlflow.search_runs.return_value = []
+
+    try:
+        mlflow_repository.get_experiment_last_run(0)
+    except ValueError as e:
+        assert str(e) == 'Runs is not a pandas DataFrame'
+    else:
+        assert False
+
+
 @patch('laborious.utils.repository.model_repository.mlflow.sklearn')
 @patch('laborious.utils.repository.model_repository.mlflow.set_experiment')
 def test_create_model_experiment(set_experiment, sklearn, mlflow_repository):
@@ -233,14 +245,6 @@ def test_create_model_experiment(set_experiment, sklearn, mlflow_repository):
 @patch('laborious.utils.repository.model_repository.mlflow.log_artifact')
 def test_perform_model_retrain(log_artifact, log_model, log_param, start_run, mlflow_repository):
 
-    _os_remove = patch(
-        'laborious.utils.repository.model_repository.remove')
-    _os_makedirs = patch(
-        'laborious.utils.repository.model_repository.makedirs')
-    _os_path_exists = patch(
-        'laborious.utils.repository.model_repository.path.exists',
-        MagicMock(return_value=False))
-
     prediction_model_mock = MagicMock()
     data_model_mock = MagicMock()
     experiment = 'test'
@@ -277,6 +281,27 @@ def test_perform_model_retrain(log_artifact, log_model, log_param, start_run, ml
     assert output == ("Model retrained successfully", experiment)
 
 
+def test_retrain_model(mlflow_repository):
+    data = MagicMock()
+    model_name = 'test'
+
+    mlflow_repository.create_model_experiment = MagicMock(
+        return_value=('data_model', 'prediction_model', '0'))
+
+    mlflow_repository.perform_model_retrain = MagicMock(
+        return_value='Model retrained successfully')
+
+    output = mlflow_repository.retrain_model(data, model_name)
+
+    mlflow_repository.create_model_experiment.assert_called_once_with(
+        model_name, data)
+
+    mlflow_repository.perform_model_retrain.assert_called_once_with(
+        'data_model', 'prediction_model', '0', model_name, data)
+
+    assert output == 'Model retrained successfully'
+
+
 @patch('laborious.utils.repository.model_repository.mlflow')
 def test_update_production_model_by_run_id(mlflow, mlflow_repository):
     client_mock = MagicMock()
@@ -312,6 +337,24 @@ def test_update_production_model_by_run_id(mlflow, mlflow_repository):
     }
 
 
+@patch('laborious.utils.repository.model_repository.mlflow')
+def test_update_production_model_by_run_id_error(mlflow, mlflow_repository):
+    mlflow.tracking.MlflowClient.return_value = MagicMock(
+        get_registered_model=MagicMock(
+            return_value=MagicMock(
+                latest_versions={}
+            )
+        )
+    )
+
+    try:
+        mlflow_repository.update_production_model_by_run_id('0', 'test')
+    except Exception as e:
+        assert str(e) == 'Model versions is not a list'
+    else:
+        assert False
+
+
 def test_update_production_model(mlflow_repository):
     connector = mlflow_repository