feat: add PredictRequestResponseLoggingConfig to Endpoint in aiplatform v1 endpoint.proto

google/cloud/aiplatform_v1/__init__.py

@@ -93,6 +93,7 @@
 from .types.encryption_spec import EncryptionSpec
 from .types.endpoint import DeployedModel
 from .types.endpoint import Endpoint
+from .types.endpoint import PredictRequestResponseLoggingConfig
 from .types.endpoint import PrivateEndpoints
 from .types.endpoint_service import CreateEndpointOperationMetadata
 from .types.endpoint_service import CreateEndpointRequest
@@ -831,6 +832,7 @@
     "Port",
     "PredefinedSplit",
     "PredictRequest",
+    "PredictRequestResponseLoggingConfig",
     "PredictResponse",
     "PredictSchemata",
     "PredictionServiceClient",

google/cloud/aiplatform_v1/services/migration_service/client.py

@@ -199,32 +199,32 @@ def parse_dataset_path(path: str) -> Dict[str, str]:
         return m.groupdict() if m else {}
 
     @staticmethod
-    def dataset_path(project: str, location: str, dataset: str,) -> str:
+    def dataset_path(project: str, dataset: str,) -> str:
         """Returns a fully-qualified dataset string."""
-        return "projects/{project}/locations/{location}/datasets/{dataset}".format(
-            project=project, location=location, dataset=dataset,
+        return "projects/{project}/datasets/{dataset}".format(
+            project=project, dataset=dataset,
         )
 
     @staticmethod
     def parse_dataset_path(path: str) -> Dict[str, str]:
         """Parses a dataset path into its component segments."""
-        m = re.match(
-            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/datasets/(?P<dataset>.+?)$",
-            path,
-        )
+        m = re.match(r"^projects/(?P<project>.+?)/datasets/(?P<dataset>.+?)$", path)
         return m.groupdict() if m else {}
 
     @staticmethod
-    def dataset_path(project: str, dataset: str,) -> str:
+    def dataset_path(project: str, location: str, dataset: str,) -> str:
         """Returns a fully-qualified dataset string."""
-        return "projects/{project}/datasets/{dataset}".format(
-            project=project, dataset=dataset,
+        return "projects/{project}/locations/{location}/datasets/{dataset}".format(
+            project=project, location=location, dataset=dataset,
         )
 
     @staticmethod
     def parse_dataset_path(path: str) -> Dict[str, str]:
         """Parses a dataset path into its component segments."""
-        m = re.match(r"^projects/(?P<project>.+?)/datasets/(?P<dataset>.+?)$", path)
+        m = re.match(
+            r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/datasets/(?P<dataset>.+?)$",
+            path,
+        )
         return m.groupdict() if m else {}
 
     @staticmethod

google/cloud/aiplatform_v1/types/__init__.py

@@ -65,6 +65,7 @@
 from .endpoint import (
     DeployedModel,
     Endpoint,
+    PredictRequestResponseLoggingConfig,
     PrivateEndpoints,
 )
 from .endpoint_service import (
@@ -546,6 +547,7 @@
     "EncryptionSpec",
     "DeployedModel",
     "Endpoint",
+    "PredictRequestResponseLoggingConfig",
     "PrivateEndpoints",
     "CreateEndpointOperationMetadata",
     "CreateEndpointRequest",

google/cloud/aiplatform_v1/types/endpoint.py

@@ -17,13 +17,19 @@
 
 from google.cloud.aiplatform_v1.types import encryption_spec as gca_encryption_spec
 from google.cloud.aiplatform_v1.types import explanation
+from google.cloud.aiplatform_v1.types import io
 from google.cloud.aiplatform_v1.types import machine_resources
 from google.protobuf import timestamp_pb2  # type: ignore
 
 
 __protobuf__ = proto.module(
     package="google.cloud.aiplatform.v1",
-    manifest={"Endpoint", "DeployedModel", "PrivateEndpoints",},
+    manifest={
+        "Endpoint",
+        "DeployedModel",
+        "PrivateEndpoints",
+        "PredictRequestResponseLoggingConfig",
+    },
 )
 
 
@@ -113,6 +119,9 @@ class Endpoint(proto.Message):
             associated with this Endpoint if monitoring is enabled by
             [CreateModelDeploymentMonitoringJob][]. Format:
             ``projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}``
+        predict_request_response_logging_config (google.cloud.aiplatform_v1.types.PredictRequestResponseLoggingConfig):
+            Configures the request-response logging for
+            online prediction.
     """
 
     name = proto.Field(proto.STRING, number=1,)
@@ -132,6 +141,9 @@ class Endpoint(proto.Message):
     network = proto.Field(proto.STRING, number=13,)
     enable_private_service_connect = proto.Field(proto.BOOL, number=17,)
     model_deployment_monitoring_job = proto.Field(proto.STRING, number=14,)
+    predict_request_response_logging_config = proto.Field(
+        proto.MESSAGE, number=18, message="PredictRequestResponseLoggingConfig",
+    )
 
 
 class DeployedModel(proto.Message):
@@ -286,4 +298,31 @@ class PrivateEndpoints(proto.Message):
     service_attachment = proto.Field(proto.STRING, number=4,)
 
 
+class PredictRequestResponseLoggingConfig(proto.Message):
+    r"""Configuration for logging request-response to a BigQuery
+    table.
+
+    Attributes:
+        enabled (bool):
+            If logging is enabled or not.
+        sampling_rate (float):
+            Percentage of requests to be logged, expressed as a fraction
+            in range(0,1].
+        bigquery_destination (google.cloud.aiplatform_v1.types.BigQueryDestination):
+            BigQuery table for logging. If only given project, a new
+            dataset will be created with name
+            ``logging_<endpoint-display-name>_<endpoint-id>`` where will
+            be made BigQuery-dataset-name compatible (e.g. most special
+            characters will become underscores). If no table name is
+            given, a new table will be created with name
+            ``request_response_logging``
+    """
+
+    enabled = proto.Field(proto.BOOL, number=1,)
+    sampling_rate = proto.Field(proto.DOUBLE, number=2,)
+    bigquery_destination = proto.Field(
+        proto.MESSAGE, number=3, message=io.BigQueryDestination,
+    )
+
+
 __all__ = tuple(sorted(__protobuf__.manifest))

google/cloud/aiplatform_v1/types/model_monitoring.py

@@ -30,7 +30,7 @@
 
 
 class ModelMonitoringObjectiveConfig(proto.Message):
-    r"""Next ID: 6
+    r"""Next ID: 7
 
     Attributes:
         training_dataset (google.cloud.aiplatform_v1.types.ModelMonitoringObjectiveConfig.TrainingDataset):

tests/unit/gapic/aiplatform_v1/test_endpoint_service.py

@@ -48,6 +48,7 @@
 from google.cloud.aiplatform_v1.types import endpoint_service
 from google.cloud.aiplatform_v1.types import explanation
 from google.cloud.aiplatform_v1.types import explanation_metadata
+from google.cloud.aiplatform_v1.types import io
 from google.cloud.aiplatform_v1.types import machine_resources
 from google.cloud.aiplatform_v1.types import operation as gca_operation
 from google.longrunning import operations_pb2

tests/unit/gapic/aiplatform_v1/test_migration_service.py

@@ -1817,20 +1817,18 @@ def test_parse_dataset_path():
 
 def test_dataset_path():
     project = "squid"
-    location = "clam"
-    dataset = "whelk"
-    expected = "projects/{project}/locations/{location}/datasets/{dataset}".format(
-        project=project, location=location, dataset=dataset,
+    dataset = "clam"
+    expected = "projects/{project}/datasets/{dataset}".format(
+        project=project, dataset=dataset,
     )
-    actual = MigrationServiceClient.dataset_path(project, location, dataset)
+    actual = MigrationServiceClient.dataset_path(project, dataset)
     assert expected == actual
 
 
 def test_parse_dataset_path():
     expected = {
-        "project": "octopus",
-        "location": "oyster",
-        "dataset": "nudibranch",
+        "project": "whelk",
+        "dataset": "octopus",
     }
     path = MigrationServiceClient.dataset_path(**expected)
 
@@ -1840,18 +1838,20 @@ def test_parse_dataset_path():
 
 
 def test_dataset_path():
-    project = "cuttlefish"
-    dataset = "mussel"
-    expected = "projects/{project}/datasets/{dataset}".format(
-        project=project, dataset=dataset,
+    project = "oyster"
+    location = "nudibranch"
+    dataset = "cuttlefish"
+    expected = "projects/{project}/locations/{location}/datasets/{dataset}".format(
+        project=project, location=location, dataset=dataset,
     )
-    actual = MigrationServiceClient.dataset_path(project, dataset)
+    actual = MigrationServiceClient.dataset_path(project, location, dataset)
     assert expected == actual
 
 
 def test_parse_dataset_path():
     expected = {
-        "project": "winkle",
+        "project": "mussel",
+        "location": "winkle",
         "dataset": "nautilus",
     }
     path = MigrationServiceClient.dataset_path(**expected)