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feat(all): auto-regenerate discovery clients (#2561)
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@yoshi-automation
yoshi-automation committed May 1, 2024
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120 changes: 103 additions & 17 deletions aiplatform/v1/aiplatform-api.json
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Original file line number Diff line number Diff line change
Expand Up @@ -3686,7 +3686,7 @@
"type": "string"
},
"parent": {
"description": "Required. The resource name of the Location to create FeatureGroups. Format: `projects/{project}/locations/{location}'`",
"description": "Required. The resource name of the Location to create FeatureGroups. Format: `projects/{project}/locations/{location}`",
"location": "path",
"pattern": "^projects/[^/]+/locations/[^/]+$",
"required": true,
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}
}
},
"revision": "20240424",
"revision": "20240429",
"rootUrl": "https://aiplatform.googleapis.com/",
"schemas": {
"CloudAiLargeModelsVisionEmbedVideoResponse": {
Expand Down Expand Up @@ -22707,7 +22707,7 @@
"description": "The datapoint of the neighbor. Note that full datapoints are returned only when \"return_full_datapoint\" is set to true. Otherwise, only the \"datapoint_id\" and \"crowding_tag\" fields are populated."
},
"distance": {
"description": "The distance between the neighbor and the query vector.",
"description": "The distance between the neighbor and the dense embedding query.",
"format": "double",
"type": "number"
}
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"description": "Metadata returned to client when grounding is enabled.",
"id": "GoogleCloudAiplatformV1GroundingMetadata",
"properties": {
"searchEntryPoint": {
"$ref": "GoogleCloudAiplatformV1SearchEntryPoint",
"description": "Optional. Google search entry for the following-up web searches."
},
"webSearchQueries": {
"description": "Optional. Web search queries for the following-up web search.",
"items": {
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"type": "string"
},
"featureVector": {
"description": "Required. Feature embedding vector. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].",
"description": "Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions].",
"items": {
"format": "float",
"type": "number"
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"type": "integer"
},
"vectorsCount": {
"description": "Output only. The number of vectors in the Index.",
"description": "Output only. The number of dense vectors in the Index.",
"format": "int64",
"readOnly": true,
"type": "string"
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"NVIDIA_H100_80GB",
"TPU_V2",
"TPU_V3",
"TPU_V4_POD"
"TPU_V4_POD",
"TPU_V5_LITEPOD"
],
"enumDescriptions": [
"Unspecified accelerator type, which means no accelerator.",
Expand All @@ -24735,7 +24740,8 @@
"Nvidia H100 80Gb GPU.",
"TPU v2.",
"TPU v3.",
"TPU v4."
"TPU v4.",
"TPU v5."
],
"type": "string"
},
Expand Down Expand Up @@ -26840,7 +26846,8 @@
"OP_IN_DATAPOINT",
"MULTIPLE_VALUES",
"INVALID_NUMERIC_VALUE",
"INVALID_ENCODING"
"INVALID_ENCODING",
"INVALID_TOKEN_VALUE"
],
"enumDescriptions": [
"Default, shall not be used.",
Expand All @@ -26849,14 +26856,15 @@
"Invalid csv format.",
"Invalid avro format.",
"The embedding id is not valid.",
"The size of the embedding vectors does not match with the specified dimension.",
"The size of the dense embedding vectors does not match with the specified dimension.",
"The `namespace` field is missing.",
"Generic catch-all error. Only used for validation failure where the root cause cannot be easily retrieved programmatically.",
"There are multiple restricts with the same `namespace` value.",
"Numeric restrict has operator specified in datapoint.",
"Numeric restrict has multiple values specified.",
"Numeric restrict has invalid numeric value specified.",
"File is not in UTF_8 format."
"File is not in UTF_8 format.",
"Token restrict value is invalid."
],
"type": "string"
},
Expand Down Expand Up @@ -28260,6 +28268,10 @@
"$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionDeployGke",
"description": "Optional. Deploy PublisherModel to Google Kubernetes Engine."
},
"fineTune": {
"$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences",
"description": "Optional. Fine tune the PublisherModel with the third-party model tuning UI."
},
"openEvaluationPipeline": {
"$ref": "GoogleCloudAiplatformV1PublisherModelCallToActionRegionalResourceReferences",
"description": "Optional. Open evaluation pipeline of the PublisherModel."
Expand Down Expand Up @@ -28323,6 +28335,10 @@
"$ref": "GoogleCloudAiplatformV1DedicatedResources",
"description": "A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration."
},
"deployTaskName": {
"description": "Optional. The name of the deploy task (e.g., \"text to image generation\").",
"type": "string"
},
"largeModelReference": {
"$ref": "GoogleCloudAiplatformV1LargeModelReference",
"description": "Optional. Large model reference. When this is set, model_artifact_spec is not needed."
Expand Down Expand Up @@ -31569,6 +31585,10 @@
},
"type": "array"
},
"systemInstructionGcsUri": {
"description": "The Google Cloud Storage URI that stores the system instruction, starting with gs://.",
"type": "string"
},
"temperature": {
"description": "Temperature value used for sampling set when the dataset was saved. This value is used to tune the degree of randomness.",
"format": "float",
Expand Down Expand Up @@ -33413,6 +33433,22 @@
},
"type": "object"
},
"GoogleCloudAiplatformV1SearchEntryPoint": {
"description": "Google search entry point.",
"id": "GoogleCloudAiplatformV1SearchEntryPoint",
"properties": {
"renderedContent": {
"description": "Optional. Web content snippet that can be embedded in a web page or an app webview.",
"type": "string"
},
"sdkBlob": {
"description": "Optional. Base64 encoded JSON representing array of tuple.",
"format": "byte",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudAiplatformV1SearchFeaturesResponse": {
"description": "Response message for FeaturestoreService.SearchFeatures.",
"id": "GoogleCloudAiplatformV1SearchFeaturesResponse",
Expand Down Expand Up @@ -37339,7 +37375,7 @@
"id": "LanguageLabsAidaTrustRecitationProtoSegmentResult",
"properties": {
"attributionDataset": {
"description": "The dataset the segment came from.",
"description": "The dataset the segment came from. Datasets change often as model evolves. Treat this field as informational only and avoid depending on it directly.",
"enum": [
"DATASET_UNSPECIFIED",
"WIKIPEDIA",
Expand Down Expand Up @@ -38047,8 +38083,7 @@
"type": "string"
},
"docAttribution": {
"$ref": "LanguageLabsAidaTrustRecitationProtoDocAttribution",
"description": "populated when recitation_action == CITE"
"$ref": "LanguageLabsAidaTrustRecitationProtoDocAttribution"
},
"docOccurrences": {
"description": "number of documents that contained this segment",
Expand Down Expand Up @@ -38080,6 +38115,32 @@
],
"type": "string"
},
"sourceCategory": {
"description": "The category of the source dataset where the segment came from. This is more stable than Dataset.",
"enum": [
"SOURCE_CATEGORY_UNSPECIFIED",
"SOURCE_CATEGORY_WIKIPEDIA",
"SOURCE_CATEGORY_WEBDOCS",
"SOURCE_CATEGORY_GITHUB",
"SOURCE_CATEGORY_ARXIV",
"SOURCE_CATEGORY_PRIVATE_BOOKS",
"SOURCE_CATEGORY_OTHERS",
"SOURCE_CATEGORY_PUBLIC_BOOKS",
"SOURCE_CATEGORY_GNEWS"
],
"enumDescriptions": [
"",
"",
"",
"",
"",
"",
"",
"",
""
],
"type": "string"
},
"startIndex": {
"description": "The segment boundary start (inclusive) and end index (exclusive) in the given text. In the streaming RPC, the indexes always start from the beginning of the first text in the entire stream. The indexes are measured in UTF-16 code units.",
"format": "int32",
Expand Down Expand Up @@ -38978,7 +39039,7 @@
"id": "LearningGenaiRecitationSegmentResult",
"properties": {
"attributionDataset": {
"description": "The dataset the segment came from.",
"description": "The dataset the segment came from. Datasets change often as model evolves. Treat this field as informational only and avoid depending on it directly.",
"enum": [
"DATASET_UNSPECIFIED",
"WIKIPEDIA",
Expand Down Expand Up @@ -39686,8 +39747,7 @@
"type": "string"
},
"docAttribution": {
"$ref": "LearningGenaiRecitationDocAttribution",
"description": "populated when recitation_action == CITE"
"$ref": "LearningGenaiRecitationDocAttribution"
},
"docOccurrences": {
"description": "number of documents that contained this segment",
Expand Down Expand Up @@ -39719,6 +39779,32 @@
],
"type": "string"
},
"sourceCategory": {
"description": "The category of the source dataset where the segment came from. This is more stable than Dataset.",
"enum": [
"SOURCE_CATEGORY_UNSPECIFIED",
"SOURCE_CATEGORY_WIKIPEDIA",
"SOURCE_CATEGORY_WEBDOCS",
"SOURCE_CATEGORY_GITHUB",
"SOURCE_CATEGORY_ARXIV",
"SOURCE_CATEGORY_PRIVATE_BOOKS",
"SOURCE_CATEGORY_OTHERS",
"SOURCE_CATEGORY_PUBLIC_BOOKS",
"SOURCE_CATEGORY_GNEWS"
],
"enumDescriptions": [
"",
"",
"",
"",
"",
"",
"",
"",
""
],
"type": "string"
},
"startIndex": {
"description": "The segment boundary start (inclusive) and end index (exclusive) in the given text. In the streaming RPC, the indexes always start from the beginning of the first text in the entire stream. The indexes are measured in UTF-16 code units.",
"format": "int32",
Expand Down Expand Up @@ -41309,7 +41395,7 @@
"type": "boolean"
},
"totalDecodedTokenCount": {
"description": "NOT YET IMPLEMENTED. Aggregated number of total tokens decoded so far. For streaming, this is sum of all the tokens decoded so far i.e. aggregated count.",
"description": "Total tokens decoded so far per response_candidate. For streaming: Count of all the tokens decoded so far (aggregated count). For unary: Count of all the tokens decoded per response_candidate.",
"format": "int32",
"type": "integer"
},
Expand Down

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