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feat(all): auto-regenerate discovery clients (#3347)
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‎aiplatform/v1/aiplatform-api.json‎

Lines changed: 220 additions & 5 deletions
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@@ -15697,6 +15697,35 @@
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"https://www.googleapis.com/auth/cloud-platform"
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]
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},
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"embedContent": {
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"description": "Embed content with multimodal inputs.",
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"flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:embedContent",
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"httpMethod": "POST",
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"id": "aiplatform.projects.locations.publishers.models.embedContent",
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"parameterOrder": [
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"model"
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],
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"parameters": {
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"model": {
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"description": "Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`",
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"location": "path",
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"pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$",
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"required": true,
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"type": "string"
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}
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},
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"path": "v1/{+model}:embedContent",
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"request": {
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"$ref": "GoogleCloudAiplatformV1EmbedContentRequest"
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},
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"response": {
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"$ref": "GoogleCloudAiplatformV1EmbedContentResponse"
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},
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"scopes": [
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"https://www.googleapis.com/auth/cloud-platform",
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"https://www.googleapis.com/auth/cloud-platform.read-only"
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]
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},
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"fetchPredictOperation": {
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"description": "Fetch an asynchronous online prediction operation.",
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"flatPath": "v1/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:fetchPredictOperation",
@@ -21198,7 +21227,7 @@
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}
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}
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},
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"revision": "20251003",
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"revision": "20251010",
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"rootUrl": "https://aiplatform.googleapis.com/",
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"schemas": {
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"CloudAiLargeModelsVisionGenerateVideoResponse": {
@@ -24271,7 +24300,9 @@
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"GETTING_CONTAINER_IMAGE",
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"STARTING_MODEL_SERVER",
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"FINISHING_UP",
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"DEPLOYMENT_TERMINATED"
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"DEPLOYMENT_TERMINATED",
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"SUCCESSFULLY_DEPLOYED",
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"FAILED_TO_DEPLOY"
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],
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"enumDescriptions": [
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"Default value. This value is unused.",
@@ -24282,7 +24313,9 @@
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"The deployment is getting the container image for the model server.",
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"The deployment is starting the model server.",
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"The deployment is performing finalization steps.",
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"The deployment has terminated."
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"The deployment has terminated.",
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"The deployment has succeeded.",
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"The deployment has failed."
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],
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"readOnly": true,
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"type": "string"
@@ -25364,7 +25397,9 @@
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"GETTING_CONTAINER_IMAGE",
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"STARTING_MODEL_SERVER",
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"FINISHING_UP",
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"DEPLOYMENT_TERMINATED"
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"DEPLOYMENT_TERMINATED",
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"SUCCESSFULLY_DEPLOYED",
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"FAILED_TO_DEPLOY"
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],
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"enumDescriptions": [
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"Default value. This value is unused.",
@@ -25375,7 +25410,9 @@
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"The deployment is getting the container image for the model server.",
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"The deployment is starting the model server.",
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"The deployment is performing finalization steps.",
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"The deployment has terminated."
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"The deployment has terminated.",
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"The deployment has succeeded.",
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"The deployment has failed."
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],
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"readOnly": true,
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"type": "string"
@@ -26063,6 +26100,90 @@
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1EmbedContentRequest": {
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"description": "Request message for PredictionService.EmbedContent.",
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"id": "GoogleCloudAiplatformV1EmbedContentRequest",
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"properties": {
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"autoTruncate": {
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"description": "Optional. Whether to silently truncate the input content if it's longer than the maximum sequence length.",
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"type": "boolean"
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},
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"content": {
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"$ref": "GoogleCloudAiplatformV1Content",
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"description": "Required. Input content to be embedded. Required."
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},
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"outputDimensionality": {
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"description": "Optional. Optional reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end.",
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"format": "int32",
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"type": "integer"
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},
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"taskType": {
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"description": "Optional. The task type of the embedding.",
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"enum": [
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"UNSPECIFIED",
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"RETRIEVAL_QUERY",
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"RETRIEVAL_DOCUMENT",
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"SEMANTIC_SIMILARITY",
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"CLASSIFICATION",
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"CLUSTERING",
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"QUESTION_ANSWERING",
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"FACT_VERIFICATION",
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"CODE_RETRIEVAL_QUERY"
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],
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"enumDescriptions": [
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"Unset value, which will default to one of the other enum values.",
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"Specifies the given text is a query in a search/retrieval setting.",
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"Specifies the given text is a document from the corpus being searched.",
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"Specifies the given text will be used for STS.",
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"Specifies that the given text will be classified.",
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"Specifies that the embeddings will be used for clustering.",
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"Specifies that the embeddings will be used for question answering.",
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"Specifies that the embeddings will be used for fact verification.",
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"Specifies that the embeddings will be used for code retrieval."
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],
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"type": "string"
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},
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"title": {
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"description": "Optional. An optional title for the text.",
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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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"GoogleCloudAiplatformV1EmbedContentResponse": {
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"description": "Response message for PredictionService.EmbedContent.",
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"id": "GoogleCloudAiplatformV1EmbedContentResponse",
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"properties": {
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"embedding": {
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"$ref": "GoogleCloudAiplatformV1EmbedContentResponseEmbedding",
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"description": "The embedding generated from the input content."
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},
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"truncated": {
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"description": "Whether the input content was truncated before generating the embedding.",
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"type": "boolean"
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},
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"usageMetadata": {
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"$ref": "GoogleCloudAiplatformV1UsageMetadata",
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"description": "Metadata about the response(s)."
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}
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1EmbedContentResponseEmbedding": {
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"description": "A list of floats representing an embedding.",
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"id": "GoogleCloudAiplatformV1EmbedContentResponseEmbedding",
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"properties": {
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"values": {
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"description": "Embedding vector values.",
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"items": {
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"format": "float",
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"type": "number"
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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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"GoogleCloudAiplatformV1EncryptionSpec": {
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"description": "Represents a customer-managed encryption key spec that can be applied to a top-level resource.",
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"id": "GoogleCloudAiplatformV1EncryptionSpec",
@@ -38080,6 +38201,13 @@
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},
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"type": "array"
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},
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"labels": {
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"additionalProperties": {
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"type": "string"
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},
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"description": "Optional. The user labels for Imagen billing usage only. Only Imagen supports labels. For other use cases, it will be ignored.",
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"type": "object"
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},
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"parameters": {
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"description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.",
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"type": "any"
@@ -49940,6 +50068,93 @@
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},
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"type": "object"
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},
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"GoogleCloudAiplatformV1UsageMetadata": {
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"description": "Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics.",
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"id": "GoogleCloudAiplatformV1UsageMetadata",
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"properties": {
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"cacheTokensDetails": {
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"description": "Output only. A detailed breakdown of the token count for each modality in the cached content.",
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"items": {
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"$ref": "GoogleCloudAiplatformV1ModalityTokenCount"
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},
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"readOnly": true,
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"type": "array"
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},
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"cachedContentTokenCount": {
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"description": "Output only. The number of tokens in the cached content that was used for this request.",
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"format": "int32",
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"readOnly": true,
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"type": "integer"
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},
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"candidatesTokenCount": {
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"description": "The total number of tokens in the generated candidates.",
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"format": "int32",
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"type": "integer"
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},
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"candidatesTokensDetails": {
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"description": "Output only. A detailed breakdown of the token count for each modality in the generated candidates.",
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"items": {
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"$ref": "GoogleCloudAiplatformV1ModalityTokenCount"
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},
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"readOnly": true,
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"type": "array"
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},
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"promptTokenCount": {
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"description": "The total number of tokens in the prompt. This includes any text, images, or other media provided in the request. When `cached_content` is set, this also includes the number of tokens in the cached content.",
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"format": "int32",
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"type": "integer"
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},
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"promptTokensDetails": {
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"description": "Output only. A detailed breakdown of the token count for each modality in the prompt.",
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"items": {
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"$ref": "GoogleCloudAiplatformV1ModalityTokenCount"
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},
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"readOnly": true,
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"type": "array"
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},
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"thoughtsTokenCount": {
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"description": "Output only. The number of tokens that were part of the model's generated \"thoughts\" output, if applicable.",
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"format": "int32",
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"readOnly": true,
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"type": "integer"
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},
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"toolUsePromptTokenCount": {
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"description": "Output only. The number of tokens in the results from tool executions, which are provided back to the model as input, if applicable.",
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"format": "int32",
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"readOnly": true,
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"type": "integer"
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},
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"toolUsePromptTokensDetails": {
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"description": "Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input.",
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"items": {
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"$ref": "GoogleCloudAiplatformV1ModalityTokenCount"
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},
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"readOnly": true,
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"type": "array"
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},
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"totalTokenCount": {
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"description": "The total number of tokens for the entire request. This is the sum of `prompt_token_count`, `candidates_token_count`, `tool_use_prompt_token_count`, and `thoughts_token_count`.",
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"format": "int32",
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"type": "integer"
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},
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"trafficType": {
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"description": "Output only. The traffic type for this request.",
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"enum": [
50143+
"TRAFFIC_TYPE_UNSPECIFIED",
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"ON_DEMAND",
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"PROVISIONED_THROUGHPUT"
50146+
],
50147+
"enumDescriptions": [
50148+
"Unspecified request traffic type.",
50149+
"Type for Pay-As-You-Go traffic.",
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"Type for Provisioned Throughput traffic."
50151+
],
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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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},
4994350158
"GoogleCloudAiplatformV1UserActionReference": {
4994450159
"description": "References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.",
4994550160
"id": "GoogleCloudAiplatformV1UserActionReference",

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