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feat(all): auto-regenerate discovery clients (#2253)
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aiplatform/v1/aiplatform-api.json

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aiplatform/v1/aiplatform-gen.go

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aiplatform/v1beta1/aiplatform-api.json

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@@ -12089,6 +12089,34 @@
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},
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"pipelineJobs": {
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"methods": {
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"batchDelete": {
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"description": "Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted.",
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"flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs:batchDelete",
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"httpMethod": "POST",
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"id": "aiplatform.projects.locations.pipelineJobs.batchDelete",
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"parameterOrder": [
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"parent"
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],
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"parameters": {
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"parent": {
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"description": "Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}`",
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"location": "path",
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"pattern": "^projects/[^/]+/locations/[^/]+$",
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"required": true,
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"type": "string"
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}
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},
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"path": "v1beta1/{+parent}/pipelineJobs:batchDelete",
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"request": {
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"$ref": "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest"
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},
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"response": {
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"$ref": "GoogleLongrunningOperation"
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},
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"scopes": [
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"https://www.googleapis.com/auth/cloud-platform"
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]
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},
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"cancel": {
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"description": "Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetPipelineJob or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a PipelineJob.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`, and PipelineJob.state is set to `CANCELLED`.",
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"flatPath": "v1beta1/projects/{projectsId}/locations/{locationsId}/pipelineJobs/{pipelineJobsId}:cancel",
@@ -16094,7 +16122,7 @@
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}
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}
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},
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"revision": "20231024",
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"revision": "20231101",
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"rootUrl": "https://aiplatform.googleapis.com/",
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"schemas": {
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"GoogleApiHttpBody": {
@@ -16627,6 +16655,20 @@
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest": {
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"description": "Request message for PipelineService.BatchDeletePipelineJobs.",
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"id": "GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest",
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"properties": {
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"names": {
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"description": "Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}`",
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"items": {
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"type": "string"
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},
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"type": "array"
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}
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest": {
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"description": "Request message for ModelService.BatchImportEvaluatedAnnotations",
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"id": "GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest",
@@ -19373,6 +19415,13 @@
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"description": "Request message for PredictionService.Explain.",
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"id": "GoogleCloudAiplatformV1beta1ExplainRequest",
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"properties": {
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"concurrentExplanationSpecOverride": {
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"additionalProperties": {
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"$ref": "GoogleCloudAiplatformV1beta1ExplanationSpecOverride"
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},
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"description": "Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model.",
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"type": "object"
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},
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"deployedModelId": {
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"description": "If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.",
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"type": "string"
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"description": "Response message for PredictionService.Explain.",
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"id": "GoogleCloudAiplatformV1beta1ExplainResponse",
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"properties": {
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"concurrentExplanations": {
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"additionalProperties": {
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"$ref": "GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation"
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},
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"description": "This field stores the results of the explanations run in parallel with The default explanation strategy/method.",
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"type": "object"
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},
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"deployedModelId": {
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"description": "ID of the Endpoint's DeployedModel that served this explanation.",
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"type": "string"
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation": {
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"description": "This message is a wrapper grouping Concurrent Explanations.",
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"id": "GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation",
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"properties": {
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"explanations": {
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"description": "The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained.",
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"items": {
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"$ref": "GoogleCloudAiplatformV1beta1Explanation"
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},
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"type": "array"
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}
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1Explanation": {
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"description": "Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.",
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"id": "GoogleCloudAiplatformV1beta1Explanation",
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"Used for Feature that is bytes."
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],
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"type": "string"
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},
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"versionColumnName": {
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"description": "Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.",
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"type": "string"
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}
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},
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"type": "object"
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"readOnly": true,
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"type": "string"
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},
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"optimized": {
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"$ref": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized",
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"description": "Contains settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. When choose Optimized storage type, need to set PrivateServiceConnectConfig.enable_private_service_connect to use private endpoint. Otherwise will use public endpoint by default."
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},
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"state": {
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"description": "Output only. State of the featureOnlineStore.",
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"enum": [
@@ -20393,13 +20471,22 @@
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint": {
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"description": "The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type or enable EmbeddingManagement.",
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"description": "The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default.",
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"id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint",
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"properties": {
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"privateServiceConnectConfig": {
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"$ref": "GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig",
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"description": "Optional. Private service connect config. If PrivateServiceConnectConfig.enable_private_service_connect set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint."
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},
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"publicEndpointDomainName": {
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"description": "Output only. This field will be populated with the domain name to use for this FeatureOnlineStore",
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"readOnly": true,
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"type": "string"
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},
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"serviceAttachment": {
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"description": "Output only. The name of the service attachment resource. Populated if private service connect is enabled and after FeatureViewSync is created.",
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"readOnly": true,
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"type": "string"
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}
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},
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"type": "object"
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized": {
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"description": "Optimized storage type to replace lightning",
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"id": "GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized",
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"properties": {},
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1FeatureSelector": {
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"description": "Selector for Features of an EntityType.",
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"id": "GoogleCloudAiplatformV1beta1FeatureSelector",
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},
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"type": "array"
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},
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"numericRestricts": {
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"description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons.",
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"items": {
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"$ref": "GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction"
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},
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"type": "array"
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},
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"restricts": {
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"description": "Optional. List of Restrict of the datapoint, used to perform \"restricted searches\" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering",
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"items": {
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction": {
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"description": "This field allows restricts to be based on numeric comparisons rather than categorical tokens.",
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"id": "GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction",
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"properties": {
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"namespace": {
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"description": "The namespace of this restriction. e.g.: cost.",
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"type": "string"
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},
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"op": {
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"description": "This MUST be specified for queries and must NOT be specified for datapoints.",
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"enum": [
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"OPERATOR_UNSPECIFIED",
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"LESS",
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"LESS_EQUAL",
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"EQUAL",
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"GREATER_EQUAL",
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"GREATER"
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],
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"enumDescriptions": [
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"Default value of the enum.",
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"Datapoints are eligible iff their value is \u003c the query's.",
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"Datapoints are eligible iff their value is \u003c= the query's.",
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"Datapoints are eligible iff their value is == the query's.",
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"Datapoints are eligible iff their value is \u003e= the query's.",
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"Datapoints are eligible iff their value is \u003e the query's."
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],
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"type": "string"
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},
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"valueDouble": {
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"description": "Represents 64 bit float.",
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"format": "double",
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"type": "number"
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},
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"valueFloat": {
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"description": "Represents 32 bit float.",
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"format": "float",
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"type": "number"
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},
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"valueInt": {
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"description": "Represents 64 bit integer.",
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"format": "int64",
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"type": "string"
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}
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1beta1IndexDatapointRestriction": {
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"description": "Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces).",
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"id": "GoogleCloudAiplatformV1beta1IndexDatapointRestriction",

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