feat: add PredictRequestResponseLoggingConfig to Endpoint in aiplatform v1 endpoint.proto (#1072)

* feat: add PredictRequestResponseLoggingConfig to Endpoint in aiplatform v1 endpoint.proto PiperOrigin-RevId: 433794371 Source-Link: googleapis/googleapis@e0f0642 Source-Link: googleapis/googleapis-gen@3afc3ec Copy-Tag: eyJwIjoiLmdpdGh1Yi8uT3dsQm90LnlhbWwiLCJoIjoiM2FmYzNlYzE4ZTc5NWM4NTkyMzFhMmMwZjhlZjE3MmE2NTA1NmUwZCJ9 * 🦉 Updates from OwlBot post-processor See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>

Author: gcf-owl-bot[bot]

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)