Updated pr.

Author: lu-ohai

ads/aqua/model/model.py

@@ -170,14 +170,11 @@ def create(
         Union[DataScienceModel, DataScienceModelGroup]
             The instance of DataScienceModel or DataScienceModelGroup.
         """
-        fine_tune_weights = (
-            model_id.fine_tune_weights
-            if isinstance(model_id, AquaMultiModelRef)
-            else []
-        )
-        model_id = (
-            model_id.model_id if isinstance(model_id, AquaMultiModelRef) else model_id
-        )
+        fine_tune_weights = []
+        if isinstance(model_id, AquaMultiModelRef):
+            fine_tune_weights = model_id.fine_tune_weights
+            model_id = model_id.model_id
+
         service_model = DataScienceModel.from_id(model_id)
         target_project = project_id or PROJECT_OCID
         target_compartment = compartment_id or COMPARTMENT_OCID
@@ -194,26 +191,14 @@ def create(
 
         custom_model = None
         if fine_tune_weights:
-            custom_model = (
-                DataScienceModelGroup()
-                .with_compartment_id(target_compartment)
-                .with_project_id(target_project)
-                .with_display_name(service_model.display_name)
-                .with_description(service_model.description)
-                .with_freeform_tags(**combined_freeform_tags)
-                .with_defined_tags(**combined_defined_tags)
-                .with_custom_metadata_list(service_model.custom_metadata_list)
-                .with_base_model_id(model_id)
-                .with_member_models(
-                    [
-                        {
-                            "inference_key": fine_tune_weight.model_name,
-                            "model_id": fine_tune_weight.model_id,
-                        }
-                        for fine_tune_weight in fine_tune_weights
-                    ]
-                )
-                .create()
+            custom_model = self._create_model_group(
+                model_id=model_id,
+                compartment_id=target_compartment,
+                project_id=target_project,
+                freeform_tags=combined_freeform_tags,
+                defined_tags=combined_defined_tags,
+                fine_tune_weights=fine_tune_weights,
+                service_model=service_model,
             )
 
             logger.info(
@@ -233,21 +218,13 @@ def create(
                 )
                 return service_model
 
-            custom_model = (
-                DataScienceModel()
-                .with_compartment_id(target_compartment)
-                .with_project_id(target_project)
-                .with_model_file_description(
-                    json_dict=service_model.model_file_description
-                )
-                .with_display_name(service_model.display_name)
-                .with_description(service_model.description)
-                .with_freeform_tags(**combined_freeform_tags)
-                .with_defined_tags(**combined_defined_tags)
-                .with_custom_metadata_list(service_model.custom_metadata_list)
-                .with_defined_metadata_list(service_model.defined_metadata_list)
-                .with_provenance_metadata(service_model.provenance_metadata)
-                .create(model_by_reference=True, **kwargs)
+            custom_model = self._create_model(
+                compartment_id=target_compartment,
+                project_id=target_project,
+                freeform_tags=combined_freeform_tags,
+                defined_tags=combined_defined_tags,
+                service_model=service_model,
+                **kwargs,
             )
             logger.info(
                 f"Aqua Model {custom_model.id} created with the service model {model_id}."
@@ -262,6 +239,68 @@ def create(
 
         return custom_model
 
+    def _create_model(
+        self,
+        compartment_id: str,
+        project_id: str,
+        freeform_tags: Dict,
+        defined_tags: Dict,
+        service_model: DataScienceModel,
+        **kwargs,
+    ):
+        """Creates a data science model by reference."""
+        custom_model = (
+            DataScienceModel()
+            .with_compartment_id(compartment_id)
+            .with_project_id(project_id)
+            .with_model_file_description(json_dict=service_model.model_file_description)
+            .with_display_name(service_model.display_name)
+            .with_description(service_model.description)
+            .with_freeform_tags(**freeform_tags)
+            .with_defined_tags(**defined_tags)
+            .with_custom_metadata_list(service_model.custom_metadata_list)
+            .with_defined_metadata_list(service_model.defined_metadata_list)
+            .with_provenance_metadata(service_model.provenance_metadata)
+            .create(model_by_reference=True, **kwargs)
+        )
+
+        return custom_model
+
+    def _create_model_group(
+        self,
+        model_id: str,
+        compartment_id: str,
+        project_id: str,
+        freeform_tags: Dict,
+        defined_tags: Dict,
+        fine_tune_weights: List,
+        service_model: DataScienceModel,
+    ):
+        """Creates a data science model group."""
+        custom_model = (
+            DataScienceModelGroup()
+            .with_compartment_id(compartment_id)
+            .with_project_id(project_id)
+            .with_display_name(service_model.display_name)
+            .with_description(service_model.description)
+            .with_freeform_tags(**freeform_tags)
+            .with_defined_tags(**defined_tags)
+            .with_custom_metadata_list(service_model.custom_metadata_list)
+            .with_base_model_id(model_id)
+            .with_member_models(
+                [
+                    {
+                        "inference_key": fine_tune_weight.model_name,
+                        "model_id": fine_tune_weight.model_id,
+                    }
+                    for fine_tune_weight in fine_tune_weights
+                ]
+            )
+            .create()
+        )
+
+        return custom_model
+
     @telemetry(entry_point="plugin=model&action=create", name="aqua")
     def create_multi(
         self,

ads/aqua/modeldeployment/deployment.py

@@ -216,14 +216,18 @@ def create(
         model_app = AquaModelApp()
         if (
             create_deployment_details.model_id
-            or create_deployment_details.deployment_type == DEFAULT_DEPLOYMENT_TYPE
+            or create_deployment_details.deployment_type
         ):
             model_id = create_deployment_details.model_id
             if not model_id:
                 if len(create_deployment_details.models) != 1:
                     raise AquaValueError(
                         "Invalid 'models' provided. Only one base model is required for model stack deployment."
                     )
+                if create_deployment_details.deployment_type != DEFAULT_DEPLOYMENT_TYPE:
+                    raise AquaValueError(
+                        f"Invalid 'deployment_type' provided. Only {DEFAULT_DEPLOYMENT_TYPE} is supported for model stack deployment."
+                    )
                 model_id = create_deployment_details.models[0]
 
             service_model_id = (

ads/model/datascience_model_group.py

@@ -541,6 +541,7 @@ def _build_model_group_details(self) -> dict:
         )
 
         build_model_group_details = copy.deepcopy(self._spec)
+        # pop out the unrequired specs for building `CreateModelGroupDetails` or `UpdateModelGroupDetails`.
         build_model_group_details.pop(self.CONST_CUSTOM_METADATA_LIST, None)
         build_model_group_details.pop(self.CONST_MEMBER_MODELS, None)
         build_model_group_details.pop(self.CONST_BASE_MODEL_ID, None)