# frozen_string_literal: true
# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Auto-generated by gapic-generator-ruby. DO NOT EDIT!
module Google
module Cloud
module AIPlatform
module V1
# Models are deployed into it, and afterwards Endpoint is called to obtain
# predictions and explanations.
# @!attribute [r] name
# @return [::String]
# Output only. The resource name of the Endpoint.
# @!attribute [rw] display_name
# @return [::String]
# Required. The display name of the Endpoint.
# The name can be up to 128 characters long and can consist of any UTF-8
# characters.
# @!attribute [rw] description
# @return [::String]
# The description of the Endpoint.
# @!attribute [r] deployed_models
# @return [::Array<::Google::Cloud::AIPlatform::V1::DeployedModel>]
# Output only. The models deployed in this Endpoint.
# To add or remove DeployedModels use
# {::Google::Cloud::AIPlatform::V1::EndpointService::Client#deploy_model EndpointService.DeployModel}
# and
# {::Google::Cloud::AIPlatform::V1::EndpointService::Client#undeploy_model EndpointService.UndeployModel}
# respectively.
# @!attribute [rw] traffic_split
# @return [::Google::Protobuf::Map{::String => ::Integer}]
# A map from a DeployedModel's ID to the percentage of this Endpoint's
# traffic that should be forwarded to that DeployedModel.
#
# If a DeployedModel's ID is not listed in this map, then it receives no
# traffic.
#
# The traffic percentage values must add up to 100, or map must be empty if
# the Endpoint is to not accept any traffic at a moment.
# @!attribute [rw] etag
# @return [::String]
# Used to perform consistent read-modify-write updates. If not set, a blind
# "overwrite" update happens.
# @!attribute [rw] labels
# @return [::Google::Protobuf::Map{::String => ::String}]
# The labels with user-defined metadata to organize your Endpoints.
#
# Label keys and values can be no longer than 64 characters
# (Unicode codepoints), can only contain lowercase letters, numeric
# characters, underscores and dashes. International characters are allowed.
#
# See https://goo.gl/xmQnxf for more information and examples of labels.
# @!attribute [r] create_time
# @return [::Google::Protobuf::Timestamp]
# Output only. Timestamp when this Endpoint was created.
# @!attribute [r] update_time
# @return [::Google::Protobuf::Timestamp]
# Output only. Timestamp when this Endpoint was last updated.
# @!attribute [rw] encryption_spec
# @return [::Google::Cloud::AIPlatform::V1::EncryptionSpec]
# Customer-managed encryption key spec for an Endpoint. If set, this
# Endpoint and all sub-resources of this Endpoint will be secured by
# this key.
# @!attribute [rw] network
# @return [::String]
# Optional. The full name of the Google Compute Engine
# [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)
# to which the Endpoint should be peered.
#
# Private services access must already be configured for the network. If left
# unspecified, the Endpoint is not peered with any network.
#
# Only one of the fields,
# {::Google::Cloud::AIPlatform::V1::Endpoint#network network} or
# {::Google::Cloud::AIPlatform::V1::Endpoint#enable_private_service_connect enable_private_service_connect},
# can be set.
#
# [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert):
# `projects/{project}/global/networks/{network}`.
# Where `{project}` is a project number, as in `12345`, and `{network}` is
# network name.
# @!attribute [rw] enable_private_service_connect
# @deprecated This field is deprecated and may be removed in the next major version update.
# @return [::Boolean]
# Deprecated: If true, expose the Endpoint via private service connect.
#
# Only one of the fields,
# {::Google::Cloud::AIPlatform::V1::Endpoint#network network} or
# {::Google::Cloud::AIPlatform::V1::Endpoint#enable_private_service_connect enable_private_service_connect},
# can be set.
# @!attribute [rw] private_service_connect_config
# @return [::Google::Cloud::AIPlatform::V1::PrivateServiceConnectConfig]
# Optional. Configuration for private service connect.
#
# {::Google::Cloud::AIPlatform::V1::Endpoint#network network} and
# {::Google::Cloud::AIPlatform::V1::Endpoint#private_service_connect_config private_service_connect_config}
# are mutually exclusive.
# @!attribute [r] model_deployment_monitoring_job
# @return [::String]
# Output only. Resource name of the Model Monitoring job associated with this
# Endpoint if monitoring is enabled by
# {::Google::Cloud::AIPlatform::V1::JobService::Client#create_model_deployment_monitoring_job JobService.CreateModelDeploymentMonitoringJob}.
# Format:
# `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`
# @!attribute [rw] predict_request_response_logging_config
# @return [::Google::Cloud::AIPlatform::V1::PredictRequestResponseLoggingConfig]
# Configures the request-response logging for online prediction.
# @!attribute [rw] dedicated_endpoint_enabled
# @return [::Boolean]
# If true, the endpoint will be exposed through a dedicated
# DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS
# will be isolated from other users' traffic and will have better performance
# and reliability.
# Note: Once you enabled dedicated endpoint, you won't be able to send
# request to the shared DNS \\{region}-aiplatform.googleapis.com. The
# limitation will be removed soon.
# @!attribute [r] dedicated_endpoint_dns
# @return [::String]
# Output only. DNS of the dedicated endpoint. Will only be populated if
# dedicated_endpoint_enabled is true.
# Format:
# `https://{endpoint_id}.{region}-{project_number}.prediction.vertexai.goog`.
# @!attribute [rw] client_connection_config
# @return [::Google::Cloud::AIPlatform::V1::ClientConnectionConfig]
# Configurations that are applied to the endpoint for online prediction.
# @!attribute [r] satisfies_pzs
# @return [::Boolean]
# Output only. Reserved for future use.
# @!attribute [r] satisfies_pzi
# @return [::Boolean]
# Output only. Reserved for future use.
class Endpoint
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
# @!attribute [rw] key
# @return [::String]
# @!attribute [rw] value
# @return [::Integer]
class TrafficSplitEntry
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# @!attribute [rw] key
# @return [::String]
# @!attribute [rw] value
# @return [::String]
class LabelsEntry
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
end
# A deployment of a Model. Endpoints contain one or more DeployedModels.
# @!attribute [rw] dedicated_resources
# @return [::Google::Cloud::AIPlatform::V1::DedicatedResources]
# A description of resources that are dedicated to the DeployedModel, and
# that need a higher degree of manual configuration.
# @!attribute [rw] automatic_resources
# @return [::Google::Cloud::AIPlatform::V1::AutomaticResources]
# A description of resources that to large degree are decided by Vertex
# AI, and require only a modest additional configuration.
# @!attribute [rw] shared_resources
# @return [::String]
# The resource name of the shared DeploymentResourcePool to deploy on.
# Format:
# `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
# @!attribute [rw] id
# @return [::String]
# Immutable. The ID of the DeployedModel. If not provided upon deployment,
# Vertex AI will generate a value for this ID.
#
# This value should be 1-10 characters, and valid characters are `/[0-9]/`.
# @!attribute [rw] model
# @return [::String]
# Required. The resource name of the Model that this is the deployment of.
# Note that the Model may be in a different location than the DeployedModel's
# Endpoint.
#
# The resource name may contain version id or version alias to specify the
# version.
# Example: `projects/{project}/locations/{location}/models/{model}@2`
# or
# `projects/{project}/locations/{location}/models/{model}@golden`
# if no version is specified, the default version will be deployed.
# @!attribute [r] model_version_id
# @return [::String]
# Output only. The version ID of the model that is deployed.
# @!attribute [rw] display_name
# @return [::String]
# The display name of the DeployedModel. If not provided upon creation,
# the Model's display_name is used.
# @!attribute [r] create_time
# @return [::Google::Protobuf::Timestamp]
# Output only. Timestamp when the DeployedModel was created.
# @!attribute [rw] explanation_spec
# @return [::Google::Cloud::AIPlatform::V1::ExplanationSpec]
# Explanation configuration for this DeployedModel.
#
# When deploying a Model using
# {::Google::Cloud::AIPlatform::V1::EndpointService::Client#deploy_model EndpointService.DeployModel},
# this value overrides the value of
# {::Google::Cloud::AIPlatform::V1::Model#explanation_spec Model.explanation_spec}.
# All fields of
# {::Google::Cloud::AIPlatform::V1::DeployedModel#explanation_spec explanation_spec}
# are optional in the request. If a field of
# {::Google::Cloud::AIPlatform::V1::DeployedModel#explanation_spec explanation_spec}
# is not populated, the value of the same field of
# {::Google::Cloud::AIPlatform::V1::Model#explanation_spec Model.explanation_spec}
# is inherited. If the corresponding
# {::Google::Cloud::AIPlatform::V1::Model#explanation_spec Model.explanation_spec}
# is not populated, all fields of the
# {::Google::Cloud::AIPlatform::V1::DeployedModel#explanation_spec explanation_spec}
# will be used for the explanation configuration.
# @!attribute [rw] disable_explanations
# @return [::Boolean]
# If true, deploy the model without explainable feature, regardless the
# existence of
# {::Google::Cloud::AIPlatform::V1::Model#explanation_spec Model.explanation_spec}
# or
# {::Google::Cloud::AIPlatform::V1::DeployedModel#explanation_spec explanation_spec}.
# @!attribute [rw] service_account
# @return [::String]
# The service account that the DeployedModel's container runs as. Specify the
# email address of the service account. If this service account is not
# specified, the container runs as a service account that doesn't have access
# to the resource project.
#
# Users deploying the Model must have the `iam.serviceAccounts.actAs`
# permission on this service account.
# @!attribute [rw] disable_container_logging
# @return [::Boolean]
# For custom-trained Models and AutoML Tabular Models, the container of the
# DeployedModel instances will send `stderr` and `stdout` streams to
# Cloud Logging by default. Please note that the logs incur cost,
# which are subject to [Cloud Logging
# pricing](https://cloud.google.com/logging/pricing).
#
# User can disable container logging by setting this flag to true.
# @!attribute [rw] enable_access_logging
# @return [::Boolean]
# If true, online prediction access logs are sent to Cloud
# Logging.
# These logs are like standard server access logs, containing
# information like timestamp and latency for each prediction request.
#
# Note that logs may incur a cost, especially if your project
# receives prediction requests at a high queries per second rate (QPS).
# Estimate your costs before enabling this option.
# @!attribute [r] private_endpoints
# @return [::Google::Cloud::AIPlatform::V1::PrivateEndpoints]
# Output only. Provide paths for users to send predict/explain/health
# requests directly to the deployed model services running on Cloud via
# private services access. This field is populated if
# {::Google::Cloud::AIPlatform::V1::Endpoint#network network} is configured.
# @!attribute [rw] faster_deployment_config
# @return [::Google::Cloud::AIPlatform::V1::FasterDeploymentConfig]
# Configuration for faster model deployment.
# @!attribute [r] status
# @return [::Google::Cloud::AIPlatform::V1::DeployedModel::Status]
# Output only. Runtime status of the deployed model.
# @!attribute [rw] system_labels
# @return [::Google::Protobuf::Map{::String => ::String}]
# System labels to apply to Model Garden deployments.
# System labels are managed by Google for internal use only.
class DeployedModel
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
# Runtime status of the deployed model.
# @!attribute [r] message
# @return [::String]
# Output only. The latest deployed model's status message (if any).
# @!attribute [r] last_update_time
# @return [::Google::Protobuf::Timestamp]
# Output only. The time at which the status was last updated.
# @!attribute [r] available_replica_count
# @return [::Integer]
# Output only. The number of available replicas of the deployed model.
class Status
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# @!attribute [rw] key
# @return [::String]
# @!attribute [rw] value
# @return [::String]
class SystemLabelsEntry
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
end
# PrivateEndpoints proto is used to provide paths for users to send
# requests privately.
# To send request via private service access, use predict_http_uri,
# explain_http_uri or health_http_uri. To send request via private service
# connect, use service_attachment.
# @!attribute [r] predict_http_uri
# @return [::String]
# Output only. Http(s) path to send prediction requests.
# @!attribute [r] explain_http_uri
# @return [::String]
# Output only. Http(s) path to send explain requests.
# @!attribute [r] health_http_uri
# @return [::String]
# Output only. Http(s) path to send health check requests.
# @!attribute [r] service_attachment
# @return [::String]
# Output only. The name of the service attachment resource. Populated if
# private service connect is enabled.
class PrivateEndpoints
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# Configuration for logging request-response to a BigQuery table.
# @!attribute [rw] enabled
# @return [::Boolean]
# If logging is enabled or not.
# @!attribute [rw] sampling_rate
# @return [::Float]
# Percentage of requests to be logged, expressed as a fraction in
# range(0,1].
# @!attribute [rw] bigquery_destination
# @return [::Google::Cloud::AIPlatform::V1::BigQueryDestination]
# BigQuery table for logging.
# If only given a project, a new dataset will be created with name
# `logging_<endpoint-display-name>_<endpoint-id>` where
# <endpoint-display-name> 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`
class PredictRequestResponseLoggingConfig
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# Configuration for faster model deployment.
# @!attribute [rw] fast_tryout_enabled
# @return [::Boolean]
# If true, enable fast tryout feature for this deployed model.
class FasterDeploymentConfig
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# Configurations (e.g. inference timeout) that are applied on your endpoints.
# @!attribute [rw] inference_timeout
# @return [::Google::Protobuf::Duration]
# Customizable online prediction request timeout.
class ClientConnectionConfig
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
end
end
end
end