List models using open ai api

ads/aqua/client/client.py

@@ -582,6 +582,19 @@ def embeddings(
         payload = {**(payload or {}), "input": input}
         return self._request(payload=payload, headers=headers)
 
+    def fetch_data(self) -> Union[Dict[str, Any], Iterator[Mapping[str, Any]]]:
+        """Fetch Data in json format by sending a request to the endpoint.
+
+        Args:
+
+        Returns:
+            Union[Dict[str, Any], Iterator[Mapping[str, Any]]]: The server's response, typically including the data in JSON format.
+        """
+        # headers = {"Content-Type", "application/json"}
+        response = self._client.get(self.endpoint)
+        json_response = response.json()
+        return json_response
+
 
 class AsyncClient(BaseClient):
     """

ads/aqua/extension/deployment_handler.py

@@ -373,6 +373,37 @@ def post(self, *args, **kwargs):  # noqa: ARG002
         )
 
 
+class AquaModelListHandler(AquaAPIhandler):
+    """Handler for Aqua model list params REST APIs.
+
+    Methods
+    -------
+    get(self, *args, **kwargs)
+        Validates parameters for the given model id.
+    """
+
+    @handle_exceptions
+    def get(self, model_deployment_id):
+        """
+        Handles get model list for the Active Model Deployment
+        Raises
+        ------
+        HTTPError
+            Raises HTTPError if inputs are missing or are invalid
+        """
+
+        self.set_header("Content-Type", "application/json")
+        endpoint: str = ""
+        model_deployment = AquaDeploymentApp().get(model_deployment_id)
+        endpoint = model_deployment.endpoint.rstrip("/") + "/predict/v1/models"       
+        aqua_client = Client(endpoint=endpoint)
+        try:
+            list_model_result = aqua_client.list_models()
+            return self.finish(list_model_result)
+        except Exception as ex:
+            raise HTTPError(500, str(ex))
+
+
 __handlers__ = [
     ("deployments/?([^/]*)/params", AquaDeploymentParamsHandler),
     ("deployments/config/?([^/]*)", AquaDeploymentHandler),
@@ -381,4 +412,5 @@ def post(self, *args, **kwargs):  # noqa: ARG002
     ("deployments/?([^/]*)/activate", AquaDeploymentHandler),
     ("deployments/?([^/]*)/deactivate", AquaDeploymentHandler),
     ("inference/stream/?([^/]*)", AquaDeploymentStreamingInferenceHandler),
+    ("deployments/models/list/?([^/]*)", AquaModelListHandler),
 ]

tests/unitary/default_setup/model_deployment/test_model_deployment_v2.py

@@ -372,6 +372,7 @@ def test__load_default_properties(self, mock_from_ocid):
             ModelDeploymentInfrastructure.CONST_SHAPE_CONFIG_DETAILS: {
                 "ocpus": 10.0,
                 "memory_in_gbs": 36.0,
+                "cpu_baseline": None,
             },
             ModelDeploymentInfrastructure.CONST_REPLICA: 1,
         }
@@ -886,7 +887,7 @@ def test_model_deployment_from_dict(self):
     def test_update_model_deployment_details(self, mock_create):
         dsc_model = MagicMock()
         dsc_model.id = "fakeid.datasciencemodel.oc1.iad.xxx"
-        mock_create.return_value = dsc_model        
+        mock_create.return_value = dsc_model
         model_deployment = self.initialize_model_deployment()
         update_model_deployment_details = (
             model_deployment._update_model_deployment_details()
@@ -1127,9 +1128,7 @@ def test_from_ocid(self, mock_from_ocid):
         "create_model_deployment",
     )
     @patch.object(DataScienceModel, "create")
-    def test_deploy(
-        self, mock_create, mock_create_model_deployment, mock_sync
-    ):
+    def test_deploy(self, mock_create, mock_create_model_deployment, mock_sync):
         dsc_model = MagicMock()
         dsc_model.id = "fakeid.datasciencemodel.oc1.iad.xxx"
         mock_create.return_value = dsc_model
@@ -1346,44 +1345,35 @@ def test_update_spec(self):
         model_deployment = self.initialize_model_deployment()
         model_deployment._update_spec(
             display_name="test_updated_name",
-            freeform_tags={"test_updated_key":"test_updated_value"},
-            access_log={
-                "log_id": "test_updated_access_log_id"
-            },
-            predict_log={
-                "log_group_id": "test_updated_predict_log_group_id"
-            },
-            shape_config_details={
-                "ocpus": 100,
-                "memoryInGBs": 200
-            },
+            freeform_tags={"test_updated_key": "test_updated_value"},
+            access_log={"log_id": "test_updated_access_log_id"},
+            predict_log={"log_group_id": "test_updated_predict_log_group_id"},
+            shape_config_details={"ocpus": 100, "memoryInGBs": 200},
             replica=20,
             image="test_updated_image",
-            env={
-                "test_updated_env_key":"test_updated_env_value"
-            }
+            env={"test_updated_env_key": "test_updated_env_value"},
         )
 
         assert model_deployment.display_name == "test_updated_name"
         assert model_deployment.freeform_tags == {
-            "test_updated_key":"test_updated_value"
+            "test_updated_key": "test_updated_value"
         }
         assert model_deployment.infrastructure.access_log == {
             "logId": "test_updated_access_log_id",
-            "logGroupId": "fakeid.loggroup.oc1.iad.xxx"
+            "logGroupId": "fakeid.loggroup.oc1.iad.xxx",
         }
         assert model_deployment.infrastructure.predict_log == {
             "logId": "fakeid.log.oc1.iad.xxx",
-            "logGroupId": "test_updated_predict_log_group_id"
+            "logGroupId": "test_updated_predict_log_group_id",
         }
         assert model_deployment.infrastructure.shape_config_details == {
             "ocpus": 100,
-            "memoryInGBs": 200
+            "memoryInGBs": 200,
         }
         assert model_deployment.infrastructure.replica == 20
         assert model_deployment.runtime.image == "test_updated_image"
         assert model_deployment.runtime.env == {
-            "test_updated_env_key":"test_updated_env_value"
+            "test_updated_env_key": "test_updated_env_value"
         }
 
     @patch.object(OCIDataScienceMixin, "sync")
@@ -1393,18 +1383,14 @@ def test_update_spec(self):
     )
     @patch.object(DataScienceModel, "create")
     def test_model_deployment_with_large_size_artifact(
-        self, 
-        mock_create, 
-        mock_create_model_deployment, 
-        mock_sync
+        self, mock_create, mock_create_model_deployment, mock_sync
     ):
         dsc_model = MagicMock()
         dsc_model.id = "fakeid.datasciencemodel.oc1.iad.xxx"
         mock_create.return_value = dsc_model
         model_deployment = self.initialize_model_deployment()
         (
-            model_deployment.runtime
-            .with_auth({"test_key":"test_value"})
+            model_deployment.runtime.with_auth({"test_key": "test_value"})
             .with_region("test_region")
             .with_overwrite_existing_artifact(True)
             .with_remove_existing_artifact(True)
@@ -1425,18 +1411,18 @@ def test_model_deployment_with_large_size_artifact(
         mock_create_model_deployment.return_value = response
         model_deployment = self.initialize_model_deployment()
         model_deployment.set_spec(model_deployment.CONST_ID, "test_model_deployment_id")
-        
+
         create_model_deployment_details = (
             model_deployment._build_model_deployment_details()
         )
         model_deployment.deploy(wait_for_completion=False)
         mock_create.assert_called_with(
             bucket_uri="test_bucket_uri",
-            auth={"test_key":"test_value"},
+            auth={"test_key": "test_value"},
             region="test_region",
             overwrite_existing_artifact=True,
             remove_existing_artifact=True,
-            timeout=100
+            timeout=100,
         )
         mock_create_model_deployment.assert_called_with(create_model_deployment_details)
         mock_sync.assert_called()

tests/unitary/default_setup/pipeline/test_pipeline.py

@@ -32,7 +32,7 @@
     nb_session_ocid="ocid1.datasciencenotebooksession.oc1.iad..<unique_ocid>",
     shape_name="VM.Standard.E3.Flex",
     block_storage_size_in_gbs=100,
-    shape_config_details={"ocpus": 1, "memory_in_gbs": 16},
+    shape_config_details={"ocpus": 1.0, "memory_in_gbs": 16.0, "cpu_baseline": None},
 )
 PIPELINE_OCID = "ocid.xxx.datasciencepipeline.<unique_ocid>"
 
@@ -334,10 +334,8 @@ def test_pipeline_define(self):
                             "jobId": "TestJobIdOne",
                             "description": "Test description one",
                             "commandLineArguments": "ARGUMENT --KEY VALUE",
-                            "environmentVariables": {
-                                "ENV": "VALUE"
-                            },
-                            "maximumRuntimeInMinutes": 20
+                            "environmentVariables": {"ENV": "VALUE"},
+                            "maximumRuntimeInMinutes": 20,
                         },
                     },
                     {
@@ -1066,10 +1064,8 @@ def test_pipeline_to_dict(self):
                             "jobId": "TestJobIdOne",
                             "description": "Test description one",
                             "commandLineArguments": "ARGUMENT --KEY VALUE",
-                            "environmentVariables": {
-                                "ENV": "VALUE"
-                            },
-                            "maximumRuntimeInMinutes": 20
+                            "environmentVariables": {"ENV": "VALUE"},
+                            "maximumRuntimeInMinutes": 20,
                         },
                     },
                     {

tests/unitary/with_extras/aqua/test_deployment_handler.py

@@ -13,11 +13,13 @@
 from parameterized import parameterized
 
 import ads.aqua
+from ads.aqua.modeldeployment.entities import AquaDeploymentDetail
 import ads.config
 from ads.aqua.extension.deployment_handler import (
     AquaDeploymentHandler,
     AquaDeploymentParamsHandler,
     AquaDeploymentStreamingInferenceHandler,
+    AquaModelListHandler,
 )
 
 
@@ -260,3 +262,25 @@ def test_post(self, mock_get_model_deployment_response):
         self.handler.write.assert_any_call("chunk1")
         self.handler.write.assert_any_call("chunk2")
         self.handler.finish.assert_called_once()
+
+
+class AquaModelListHandlerTestCase(unittest.TestCase):
+    default_params = {
+        "data": [{"id": "id", "object": "object", "owned_by": "openAI", "created": 124}]
+    }
+
+    @patch.object(IPythonHandler, "__init__")
+    def setUp(self, ipython_init_mock) -> None:
+        ipython_init_mock.return_value = None
+        self.aqua_model_list_handler = AquaModelListHandler(MagicMock(), MagicMock())
+        self.aqua_model_list_handler._headers = MagicMock()
+
+    @patch("ads.aqua.modeldeployment.AquaDeploymentApp.get")
+    @patch("notebook.base.handlers.APIHandler.finish")
+    def test_get_model_list(self, mock_get, mock_finish):
+        """Test to check the handler get method to return model list."""
+
+        mock_get.return_value = MagicMock(id="test_model_id")
+        mock_finish.side_effect = lambda x: x
+        result = self.aqua_model_list_handler.get(model_id="test_model_id")
+        mock_get.assert_called()