Moving config from ADS to UI

Author: kumar-shivam-ranjan

ads/aqua/extension/ui_handler.py

@@ -1,5 +1,4 @@
 #!/usr/bin/env python
-# -*- coding: utf-8 -*-
 # Copyright (c) 2024 Oracle and/or its affiliates.
 # Licensed under the Universal Permissive License v 1.0 as shown at https://oss.oracle.com/licenses/upl/
 
@@ -10,8 +9,8 @@
 
 from ads.aqua.common.decorator import handle_exceptions
 from ads.aqua.common.enums import Tags
-from ads.aqua.extension.errors import Errors
 from ads.aqua.extension.base_handler import AquaAPIhandler
+from ads.aqua.extension.errors import Errors
 from ads.aqua.extension.utils import validate_function_parameters
 from ads.aqua.model.entities import ImportModelDetails
 from ads.aqua.ui import AquaUIApp
@@ -184,7 +183,10 @@ def get_shape_availability(self, **kwargs):
 
         return self.finish(
             AquaUIApp().get_shape_availability(
-                compartment_id=compartment_id, instance_shape=instance_shape, limit_name=limit_name, **kwargs
+                compartment_id=compartment_id,
+                instance_shape=instance_shape,
+                limit_name=limit_name,
+                **kwargs,
             )
         )
 

ads/aqua/finetuning/finetuning.py

@@ -21,7 +21,6 @@
     get_container_image,
     upload_local_to_os,
 )
-from ads.aqua.config.config import get_finetuning_config_defaults
 from ads.aqua.constants import (
     DEFAULT_FT_BATCH_SIZE,
     DEFAULT_FT_BLOCK_STORAGE_SIZE,
@@ -563,7 +562,9 @@ def get_finetuning_config(self, model_id: str) -> Dict:
 
         config = self.get_config(model_id, AQUA_MODEL_FINETUNING_CONFIG)
         if not config:
-            logger.info(f"default fine-tuning config will be used for model: {model_id}")
+            logger.info(
+                f"default fine-tuning config will be used for model: {model_id}"
+            )
         return config
 
     @telemetry(

ads/aqua/modeldeployment/deployment.py

@@ -23,7 +23,6 @@
     get_params_list,
     get_resource_name,
     get_restricted_params_by_container,
-    load_config,
 )
 from ads.aqua.constants import (
     AQUA_MODEL_ARTIFACT_FILE,
@@ -44,11 +43,8 @@
 from ads.common.object_storage_details import ObjectStorageDetails
 from ads.common.utils import get_log_links
 from ads.config import (
-    AQUA_CONFIG_FOLDER,
     AQUA_DEPLOYMENT_CONTAINER_METADATA_NAME,
-    AQUA_DEPLOYMENT_CONTAINER_OVERRIDE_FLAG_METADATA_NAME,
     AQUA_MODEL_DEPLOYMENT_CONFIG,
-    AQUA_MODEL_DEPLOYMENT_CONFIG_DEFAULTS,
     COMPARTMENT_OCID,
 )
 from ads.model.datascience_model import DataScienceModel
@@ -87,26 +83,26 @@ class AquaDeploymentApp(AquaApp):
 
     @telemetry(entry_point="plugin=deployment&action=create", name="aqua")
     def create(
-            self,
-            model_id: str,
-            instance_shape: str,
-            display_name: str,
-            instance_count: int = None,
-            log_group_id: str = None,
-            access_log_id: str = None,
-            predict_log_id: str = None,
-            compartment_id: str = None,
-            project_id: str = None,
-            description: str = None,
-            bandwidth_mbps: int = None,
-            web_concurrency: int = None,
-            server_port: int = None,
-            health_check_port: int = None,
-            env_var: Dict = None,
-            container_family: str = None,
-            memory_in_gbs: Optional[float] = None,
-            ocpus: Optional[float] = None,
-            model_file: Optional[str] = None,
+        self,
+        model_id: str,
+        instance_shape: str,
+        display_name: str,
+        instance_count: int = None,
+        log_group_id: str = None,
+        access_log_id: str = None,
+        predict_log_id: str = None,
+        compartment_id: str = None,
+        project_id: str = None,
+        description: str = None,
+        bandwidth_mbps: int = None,
+        web_concurrency: int = None,
+        server_port: int = None,
+        health_check_port: int = None,
+        env_var: Dict = None,
+        container_family: str = None,
+        memory_in_gbs: Optional[float] = None,
+        ocpus: Optional[float] = None,
+        model_file: Optional[str] = None,
     ) -> "AquaDeployment":
         """
         Creates a new Aqua deployment
@@ -231,8 +227,7 @@ def create(
             env_var.update({"FT_MODEL": f"{fine_tune_output_path}"})
 
         container_type_key = self._get_container_type_key(
-            model=aqua_model,
-            container_family=container_family
+            model=aqua_model, container_family=container_family
         )
 
         # fetch image name from config
@@ -248,7 +243,11 @@ def create(
         model_format = model_formats_str.split(",")
 
         # Figure out a better way to handle this in future release
-        if ModelFormat.GGUF.value in model_format and container_type_key.lower() == InferenceContainerTypeFamily.AQUA_LLAMA_CPP_CONTAINER_FAMILY:
+        if (
+            ModelFormat.GGUF.value in model_format
+            and container_type_key.lower()
+            == InferenceContainerTypeFamily.AQUA_LLAMA_CPP_CONTAINER_FAMILY
+        ):
             if model_file is not None:
                 logger.info(
                     f"Overriding {model_file} as model_file for model {aqua_model.id}."
@@ -299,8 +298,8 @@ def create(
         if user_params:
             # todo: remove this check in the future version, logic to be moved to container_index
             if (
-                    container_type_key.lower()
-                    == InferenceContainerTypeFamily.AQUA_LLAMA_CPP_CONTAINER_FAMILY
+                container_type_key.lower()
+                == InferenceContainerTypeFamily.AQUA_LLAMA_CPP_CONTAINER_FAMILY
             ):
                 # AQUA_LLAMA_CPP_CONTAINER_FAMILY container uses uvicorn that required model/server params
                 # to be set as env vars
@@ -422,9 +421,8 @@ def _get_container_type_key(model: DataScienceModel, container_family: str) -> s
                     f"for model {model.id}. For unverified Aqua models, {AQUA_DEPLOYMENT_CONTAINER_METADATA_NAME} should be"
                     f"set and value can be one of {', '.join(InferenceContainerTypeFamily.values())}."
                 ) from err
-            
+
         return container_type_key
-        
 
     @telemetry(entry_point="plugin=deployment&action=list", name="aqua")
     def list(self, **kwargs) -> List["AquaDeployment"]:
@@ -453,8 +451,8 @@ def list(self, **kwargs) -> List["AquaDeployment"]:
         for model_deployment in model_deployments:
             oci_aqua = (
                 (
-                        Tags.AQUA_TAG in model_deployment.freeform_tags
-                        or Tags.AQUA_TAG.lower() in model_deployment.freeform_tags
+                    Tags.AQUA_TAG in model_deployment.freeform_tags
+                    or Tags.AQUA_TAG.lower() in model_deployment.freeform_tags
                 )
                 if model_deployment.freeform_tags
                 else False
@@ -508,8 +506,8 @@ def get(self, model_deployment_id: str, **kwargs) -> "AquaDeploymentDetail":
 
         oci_aqua = (
             (
-                    Tags.AQUA_TAG in model_deployment.freeform_tags
-                    or Tags.AQUA_TAG.lower() in model_deployment.freeform_tags
+                Tags.AQUA_TAG in model_deployment.freeform_tags
+                or Tags.AQUA_TAG.lower() in model_deployment.freeform_tags
             )
             if model_deployment.freeform_tags
             else False
@@ -526,8 +524,8 @@ def get(self, model_deployment_id: str, **kwargs) -> "AquaDeploymentDetail":
         log_group_name = ""
 
         logs = (
-                model_deployment.category_log_details.access
-                or model_deployment.category_log_details.predict
+            model_deployment.category_log_details.access
+            or model_deployment.category_log_details.predict
         )
         if logs:
             log_id = logs.log_id
@@ -578,9 +576,9 @@ def get_deployment_config(self, model_id: str) -> Dict:
         return config
 
     def get_deployment_default_params(
-            self,
-            model_id: str,
-            instance_shape: str,
+        self,
+        model_id: str,
+        instance_shape: str,
     ) -> List[str]:
         """Gets the default params set in the deployment configs for the given model and instance shape.
 
@@ -612,8 +610,8 @@ def get_deployment_default_params(
             )
 
         if (
-                container_type_key
-                and container_type_key in InferenceContainerTypeFamily.values()
+            container_type_key
+            and container_type_key in InferenceContainerTypeFamily.values()
         ):
             deployment_config = self.get_deployment_config(model_id)
             config_params = (
@@ -636,10 +634,10 @@ def get_deployment_default_params(
         return default_params
 
     def validate_deployment_params(
-            self,
-            model_id: str,
-            params: List[str] = None,
-            container_family: str = None,
+        self,
+        model_id: str,
+        params: List[str] = None,
+        container_family: str = None,
     ) -> Dict:
         """Validate if the deployment parameters passed by the user can be overridden. Parameter values are not
         validated, only param keys are validated.
@@ -662,8 +660,7 @@ def validate_deployment_params(
         if params:
             model = DataScienceModel.from_id(model_id)
             container_type_key = self._get_container_type_key(
-                model=model,
-                container_family=container_family
+                model=model, container_family=container_family
             )
 
             container_config = get_container_config()
@@ -685,9 +682,9 @@ def validate_deployment_params(
 
     @staticmethod
     def _find_restricted_params(
-            default_params: Union[str, List[str]],
-            user_params: Union[str, List[str]],
-            container_family: str,
+        default_params: Union[str, List[str]],
+        user_params: Union[str, List[str]],
+        container_family: str,
     ) -> List[str]:
         """Returns a list of restricted params that user chooses to override when creating an Aqua deployment.
         The default parameters coming from the container index json file cannot be overridden.

ads/aqua/ui.py

@@ -17,14 +17,12 @@
 from ads.aqua.common.entities import ContainerSpec
 from ads.aqua.common.enums import Tags
 from ads.aqua.common.errors import AquaResourceAccessError, AquaValueError
-from ads.aqua.common.utils import get_container_config, load_config, sanitize_response
+from ads.aqua.common.utils import get_container_config, sanitize_response
 from ads.common import oci_client as oc
 from ads.common.auth import default_signer
 from ads.common.object_storage_details import ObjectStorageDetails
 from ads.common.serializer import DataClassSerializable
 from ads.config import (
-    AQUA_CONFIG_FOLDER,
-    AQUA_RESOURCE_LIMIT_NAMES_CONFIG,
     COMPARTMENT_OCID,
     DATA_SCIENCE_SERVICE_NAME,
     TENANCY_OCID,
@@ -572,7 +570,7 @@ def get_shape_availability(self, **kwargs):
         """
         compartment_id = kwargs.pop("compartment_id", COMPARTMENT_OCID)
         instance_shape = kwargs.pop("instance_shape", None)
-        limit_name = kwargs.pop("limit_name",None)
+        limit_name = kwargs.pop("limit_name", None)
 
         if not instance_shape:
             raise AquaValueError("instance_shape argument is required.")