G-index

A B C D E F G H I J K L M N O P Q R S T U V W Y Z

G

GcsDestination - class in com.google.genai.types

The Google Cloud Storage location where the output is to be written to.

gcsDestination() - function in com.google.genai.types.OutputConfig

Cloud storage destination for evaluation output.

gcsDestination(com.google.genai.types.GcsDestination) - function in com.google.genai.types.OutputConfig.Builder

Setter for gcsDestination.

gcsDestination(com.google.genai.types.GcsDestination.Builder) - function in com.google.genai.types.OutputConfig.Builder

Setter for gcsDestination builder.

GcsDestination.Builder - class in com.google.genai.types.GcsDestination

Builder for GcsDestination.

gcsOutputDirectory() - function in com.google.genai.types.BatchJobOutputInfo

The full path of the Cloud Storage directory created, into which the prediction output is written.

gcsOutputDirectory(java.lang.String) - function in com.google.genai.types.BatchJobOutputInfo.Builder

Setter for gcsOutputDirectory.

gcsOutputDirectory() - function in com.google.genai.types.OutputInfo

Output only.

gcsOutputDirectory(java.lang.String) - function in com.google.genai.types.OutputInfo.Builder

Setter for gcsOutputDirectory.

gcsSource() - function in com.google.genai.types.EvaluationDataset

Cloud storage source holds the dataset.

gcsSource(com.google.genai.types.GcsSource) - function in com.google.genai.types.EvaluationDataset.Builder

Setter for gcsSource.

gcsSource(com.google.genai.types.GcsSource.Builder) - function in com.google.genai.types.EvaluationDataset.Builder

Setter for gcsSource builder.

GcsSource - class in com.google.genai.types

The Google Cloud Storage location for the input content.

GcsSource.Builder - class in com.google.genai.types.GcsSource

Builder for GcsSource.

gcsUri() - function in com.google.genai.types.BatchJobDestination

The Google Cloud Storage URI to the output file.

gcsUri(java.lang.String) - function in com.google.genai.types.BatchJobDestination.Builder

Setter for gcsUri.

gcsUri() - function in com.google.genai.types.BatchJobSource

The Google Cloud Storage URIs to input files.

gcsUri(kotlin.Array) - function in com.google.genai.types.BatchJobSource.Builder

Setter for gcsUri.

gcsUri(java.util.List) - function in com.google.genai.types.BatchJobSource.Builder

Setter for gcsUri.

gcsUri() - function in com.google.genai.types.Image

The Cloud Storage URI of the image.

gcsUri(java.lang.String) - function in com.google.genai.types.Image.Builder

Setter for gcsUri.

gcsUri() - function in com.google.genai.types.TuningDataset

GCS URI of the file containing training dataset in JSONL format.

gcsUri(java.lang.String) - function in com.google.genai.types.TuningDataset.Builder

Setter for gcsUri.

gcsUri() - function in com.google.genai.types.TuningValidationDataset

GCS URI of the file containing validation dataset in JSONL format.

gcsUri(java.lang.String) - function in com.google.genai.types.TuningValidationDataset.Builder

Setter for gcsUri.

GeminiPreferenceExample - class in com.google.genai.types

Input example for preference optimization.

GeminiPreferenceExample.Builder - class in com.google.genai.types.GeminiPreferenceExample

Builder for GeminiPreferenceExample.

GeminiPreferenceExampleCompletion - class in com.google.genai.types

Completion and its preference score.

GeminiPreferenceExampleCompletion.Builder - class in com.google.genai.types.GeminiPreferenceExampleCompletion

Builder for GeminiPreferenceExampleCompletion.

GenAiIOException - class in com.google.genai.errors

IO exception raised in the GenAI SDK.

generateAudio() - function in com.google.genai.types.GenerateVideosConfig

Whether to generate audio along with the video.

generateAudio(boolean) - function in com.google.genai.types.GenerateVideosConfig.Builder

Setter for generateAudio.

generateContent(java.lang.String,com.google.genai.types.Content,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.AsyncModels

Asynchronously generates content given a GenAI model and a content object.

generateContent(java.lang.String,java.lang.String,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.AsyncModels

Asynchronously generates content given a GenAI model and a text string.

generateContent(java.lang.String,java.util.List,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.AsyncModels

Asynchronously generates content given a GenAI model and a list of content.

generateContent(java.lang.String,com.google.genai.types.Content,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.Models

Generates content given a GenAI model and a content object.

generateContent(java.lang.String,java.lang.String,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.Models

Generates content given a GenAI model and a text string.

generateContent(java.lang.String,java.util.List,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.Models

Generates content given a GenAI model and a list of content.

GenerateContentConfig - class in com.google.genai.types

Optional model configuration parameters.

GenerateContentConfig.Builder - class in com.google.genai.types.GenerateContentConfig

Builder for GenerateContentConfig.

GenerateContentParameters - class in com.google.genai.types

Config for models.generate_content parameters.

GenerateContentParameters.Builder - class in com.google.genai.types.GenerateContentParameters

Builder for GenerateContentParameters.

GenerateContentResponse - class in com.google.genai.types

Response message for PredictionService.GenerateContent.

GenerateContentResponse.Builder - class in com.google.genai.types.GenerateContentResponse

Builder for GenerateContentResponse.

GenerateContentResponsePromptFeedback - class in com.google.genai.types

Content filter results for a prompt sent in the request.

GenerateContentResponsePromptFeedback.Builder - class in com.google.genai.types.GenerateContentResponsePromptFeedback

Builder for GenerateContentResponsePromptFeedback.

GenerateContentResponseUsageMetadata - class in com.google.genai.types

Usage metadata about the content generation request and response.

GenerateContentResponseUsageMetadata.Builder - class in com.google.genai.types.GenerateContentResponseUsageMetadata

Builder for GenerateContentResponseUsageMetadata.

generateContentStream(java.lang.String,com.google.genai.types.Content,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.AsyncModels

Asynchronously generates content with streaming support given a GenAI model and a content object.

generateContentStream(java.lang.String,java.lang.String,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.AsyncModels

Asynchronously generates content with streaming support given a GenAI model and a text string.

generateContentStream(java.lang.String,java.util.List,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.AsyncModels

Asynchronously generates content with streaming support given a GenAI model and a list of content.

generateContentStream(java.lang.String,com.google.genai.types.Content,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.Models

Generates content with streaming support given a GenAI model and a content object.

generateContentStream(java.lang.String,java.lang.String,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.Models

Generates content with streaming support given a GenAI model and a text string.

generateContentStream(java.lang.String,java.util.List,com.google.genai.types.GenerateContentConfig) - function in com.google.genai.Models

Generates content with streaming support given a GenAI model and a list of content.

GENERATED - enum entry in com.google.genai.types.FileSource.Known

GENERATED_AUDIO_SAFETY - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated audio failed safety check.

GENERATED_CONTENT_BLOCKLIST - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated content matched blocklist.

GENERATED_CONTENT_PROHIBITED - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated content is prohibited.

GENERATED_CONTENT_SAFETY - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated content failed safety check.

GENERATED_IMAGE_CELEBRITY - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated image contains celebrity.

GENERATED_IMAGE_IDENTIFIABLE_PEOPLE - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated image contains identifiable people.

GENERATED_IMAGE_MINORS - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated image contains minors.

GENERATED_IMAGE_PROHIBITED - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated image is prohibited.

GENERATED_IMAGE_PROMINENT_PEOPLE_DETECTED_BY_REWRITER - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated image contains prominent people detected by rewriter.

GENERATED_IMAGE_SAFETY - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated image failed safety check.

GENERATED_OTHER - enum entry in com.google.genai.types.TurnCompleteReason.Known

Other generated content issue.

GENERATED_VIDEO_SAFETY - enum entry in com.google.genai.types.TurnCompleteReason.Known

Generated video failed safety check.

GeneratedImage - class in com.google.genai.types

An output image.

GeneratedImage.Builder - class in com.google.genai.types.GeneratedImage

Builder for GeneratedImage.

GeneratedImageMask - class in com.google.genai.types

A generated image mask.

GeneratedImageMask.Builder - class in com.google.genai.types.GeneratedImageMask

Builder for GeneratedImageMask.

generatedImages() - function in com.google.genai.types.EditImageResponse

Generated images.

generatedImages(kotlin.Array) - function in com.google.genai.types.EditImageResponse.Builder

Setter for generatedImages.

generatedImages(kotlin.Array) - function in com.google.genai.types.EditImageResponse.Builder

Setter for generatedImages builder.

generatedImages(java.util.List) - function in com.google.genai.types.EditImageResponse.Builder

Setter for generatedImages.

generatedImages() - function in com.google.genai.types.GenerateImagesResponse

List of generated images.

generatedImages(kotlin.Array) - function in com.google.genai.types.GenerateImagesResponse.Builder

Setter for generatedImages.

generatedImages(kotlin.Array) - function in com.google.genai.types.GenerateImagesResponse.Builder

Setter for generatedImages builder.

generatedImages(java.util.List) - function in com.google.genai.types.GenerateImagesResponse.Builder

Setter for generatedImages.

generatedImages() - function in com.google.genai.types.RecontextImageResponse

List of generated images.

generatedImages(kotlin.Array) - function in com.google.genai.types.RecontextImageResponse.Builder

Setter for generatedImages.

generatedImages(kotlin.Array) - function in com.google.genai.types.RecontextImageResponse.Builder

Setter for generatedImages builder.

generatedImages(java.util.List) - function in com.google.genai.types.RecontextImageResponse.Builder

Setter for generatedImages.

generatedImages() - function in com.google.genai.types.UpscaleImageResponse

Generated images.

generatedImages(kotlin.Array) - function in com.google.genai.types.UpscaleImageResponse.Builder

Setter for generatedImages.

generatedImages(kotlin.Array) - function in com.google.genai.types.UpscaleImageResponse.Builder

Setter for generatedImages builder.

generatedImages(java.util.List) - function in com.google.genai.types.UpscaleImageResponse.Builder

Setter for generatedImages.

generatedMasks() - function in com.google.genai.types.SegmentImageResponse

List of generated image masks.

generatedMasks(kotlin.Array) - function in com.google.genai.types.SegmentImageResponse.Builder

Setter for generatedMasks.

generatedMasks(kotlin.Array) - function in com.google.genai.types.SegmentImageResponse.Builder

Setter for generatedMasks builder.

generatedMasks(java.util.List) - function in com.google.genai.types.SegmentImageResponse.Builder

Setter for generatedMasks.

GeneratedVideo - class in com.google.genai.types

A generated video.

GeneratedVideo.Builder - class in com.google.genai.types.GeneratedVideo

Builder for GeneratedVideo.

generatedVideoFromMldev(com.fasterxml.jackson.databind.JsonNode,com.fasterxml.jackson.databind.node.ObjectNode) - function in com.google.genai.OperationsConverters

generatedVideoFromVertex(com.fasterxml.jackson.databind.JsonNode,com.fasterxml.jackson.databind.node.ObjectNode) - function in com.google.genai.OperationsConverters

generatedVideos() - function in com.google.genai.types.GenerateVideosResponse

List of the generated videos

generatedVideos(kotlin.Array) - function in com.google.genai.types.GenerateVideosResponse.Builder

Setter for generatedVideos.

generatedVideos(kotlin.Array) - function in com.google.genai.types.GenerateVideosResponse.Builder

Setter for generatedVideos builder.

generatedVideos(java.util.List) - function in com.google.genai.types.GenerateVideosResponse.Builder

Setter for generatedVideos.

generateImages(java.lang.String,java.lang.String,com.google.genai.types.GenerateImagesConfig) - function in com.google.genai.AsyncModels

Asynchronously generates images given a GenAI model and a prompt.

generateImages(java.lang.String,java.lang.String,com.google.genai.types.GenerateImagesConfig) - function in com.google.genai.Models

Generates images given a GenAI model and a prompt.

GenerateImagesConfig - class in com.google.genai.types

The config for generating an images.

GenerateImagesConfig.Builder - class in com.google.genai.types.GenerateImagesConfig

Builder for GenerateImagesConfig.

GenerateImagesParameters - class in com.google.genai.types

The parameters for generating images.

GenerateImagesParameters.Builder - class in com.google.genai.types.GenerateImagesParameters

Builder for GenerateImagesParameters.

GenerateImagesResponse - class in com.google.genai.types

The output images response.

GenerateImagesResponse.Builder - class in com.google.genai.types.GenerateImagesResponse

Builder for GenerateImagesResponse.

generateVideos(java.lang.String,com.google.genai.types.GenerateVideosSource,com.google.genai.types.GenerateVideosConfig) - function in com.google.genai.AsyncModels

Asynchronously generates videos given a GenAI model, and a GenerateVideosSource source.

generateVideos(java.lang.String,java.lang.String,com.google.genai.types.Image,com.google.genai.types.GenerateVideosConfig) - function in com.google.genai.AsyncModels

Asynchronously generates videos given a GenAI model, and an input (text, image).

generateVideos(java.lang.String,java.lang.String,com.google.genai.types.Image,com.google.genai.types.Video,com.google.genai.types.GenerateVideosConfig) - function in com.google.genai.AsyncModels

Asynchronously generates videos given a GenAI model, and an input (text, image, or video).

generateVideos(java.lang.String,com.google.genai.types.GenerateVideosSource,com.google.genai.types.GenerateVideosConfig) - function in com.google.genai.Models

Generates videos given a GenAI model, and a GenerateVideosSource source.

generateVideos(java.lang.String,java.lang.String,com.google.genai.types.Image,com.google.genai.types.GenerateVideosConfig) - function in com.google.genai.Models

Generates videos given a GenAI model, and an input (text, image).

generateVideos(java.lang.String,java.lang.String,com.google.genai.types.Image,com.google.genai.types.Video,com.google.genai.types.GenerateVideosConfig) - function in com.google.genai.Models

Generates videos given a GenAI model, and an input (text, image, or video).

GenerateVideosConfig - class in com.google.genai.types

Configuration for generating videos.

GenerateVideosConfig.Builder - class in com.google.genai.types.GenerateVideosConfig

Builder for GenerateVideosConfig.

GenerateVideosOperation - class in com.google.genai.types

A video generation operation.

GenerateVideosOperation.Builder - class in com.google.genai.types.GenerateVideosOperation

Builder for GenerateVideosOperation.

generateVideosOperationFromMldev(com.fasterxml.jackson.databind.JsonNode,com.fasterxml.jackson.databind.node.ObjectNode) - function in com.google.genai.OperationsConverters

generateVideosOperationFromVertex(com.fasterxml.jackson.databind.JsonNode,com.fasterxml.jackson.databind.node.ObjectNode) - function in com.google.genai.OperationsConverters

GenerateVideosParameters - class in com.google.genai.types

Class that represents the parameters for generating videos.

GenerateVideosParameters.Builder - class in com.google.genai.types.GenerateVideosParameters

Builder for GenerateVideosParameters.

GenerateVideosResponse - class in com.google.genai.types

Response with generated videos.

GenerateVideosResponse.Builder - class in com.google.genai.types.GenerateVideosResponse

Builder for GenerateVideosResponse.

generateVideosResponseFromMldev(com.fasterxml.jackson.databind.JsonNode,com.fasterxml.jackson.databind.node.ObjectNode) - function in com.google.genai.OperationsConverters

generateVideosResponseFromVertex(com.fasterxml.jackson.databind.JsonNode,com.fasterxml.jackson.databind.node.ObjectNode) - function in com.google.genai.OperationsConverters

GenerateVideosSource - class in com.google.genai.types

A set of source input(s) for video generation.

GenerateVideosSource.Builder - class in com.google.genai.types.GenerateVideosSource

Builder for GenerateVideosSource.

generationComplete() - function in com.google.genai.types.LiveServerContent

If true, indicates that the model is done generating.

generationComplete(boolean) - function in com.google.genai.types.LiveServerContent.Builder

Setter for generationComplete.

generationConfig() - function in com.google.genai.types.AutoraterConfig

Configuration options for model generation and outputs.

generationConfig(com.google.genai.types.GenerationConfig) - function in com.google.genai.types.AutoraterConfig.Builder

Setter for generationConfig.

generationConfig(com.google.genai.types.GenerationConfig.Builder) - function in com.google.genai.types.AutoraterConfig.Builder

Setter for generationConfig builder.

generationConfig() - function in com.google.genai.types.CountTokensConfig

Configuration that the model uses to generate the response.

generationConfig(com.google.genai.types.GenerationConfig) - function in com.google.genai.types.CountTokensConfig.Builder

Setter for generationConfig.

generationConfig(com.google.genai.types.GenerationConfig.Builder) - function in com.google.genai.types.CountTokensConfig.Builder

Setter for generationConfig builder.

GenerationConfig - class in com.google.genai.types

Generation config.

generationConfig() - function in com.google.genai.types.LiveClientSetup

The generation configuration for the session.

generationConfig(com.google.genai.types.GenerationConfig) - function in com.google.genai.types.LiveClientSetup.Builder

Setter for generationConfig.

generationConfig(com.google.genai.types.GenerationConfig.Builder) - function in com.google.genai.types.LiveClientSetup.Builder

Setter for generationConfig builder.

GenerationConfig.Builder - class in com.google.genai.types.GenerationConfig

Builder for GenerationConfig.

GenerationConfigRoutingConfig - class in com.google.genai.types

The configuration for routing the request to a specific model.

GenerationConfigRoutingConfig.Builder - class in com.google.genai.types.GenerationConfigRoutingConfig

Builder for GenerationConfigRoutingConfig.

GenerationConfigRoutingConfigAutoRoutingMode - class in com.google.genai.types

The configuration for automated routing.

GenerationConfigRoutingConfigAutoRoutingMode.Builder - class in com.google.genai.types.GenerationConfigRoutingConfigAutoRoutingMode

Builder for GenerationConfigRoutingConfigAutoRoutingMode.

GenerationConfigRoutingConfigManualRoutingMode - class in com.google.genai.types

The configuration for manual routing.

GenerationConfigRoutingConfigManualRoutingMode.Builder - class in com.google.genai.types.GenerationConfigRoutingConfigManualRoutingMode

Builder for GenerationConfigRoutingConfigManualRoutingMode.

get(java.lang.String,com.google.genai.types.GetBatchJobConfig) - function in com.google.genai.AsyncBatches

Asynchronously gets a batch job resource.

get(java.lang.String,com.google.genai.types.GetCachedContentConfig) - function in com.google.genai.AsyncCaches

Asynchronously gets a cached content resource.

get(java.lang.String,com.google.genai.types.GetDocumentConfig) - function in com.google.genai.AsyncDocuments

get(java.lang.String,com.google.genai.types.GetFileSearchStoreConfig) - function in com.google.genai.AsyncFileSearchStores

get(java.lang.String,com.google.genai.types.GetFileConfig) - function in com.google.genai.AsyncFiles

Asynchronously retrieves the file information from the service.

get(java.lang.String,com.google.genai.types.GetModelConfig) - function in com.google.genai.AsyncModels

Asynchronously fetches information about a model by name.

get(U,com.google.genai.types.GetOperationConfig) - function in com.google.genai.AsyncOperations

Gets the status of an Operation.

get(java.lang.String,com.google.genai.types.GetTuningJobConfig) - function in com.google.genai.AsyncTunings

Asynchronously makes an API request to get a tuning job.

get(java.lang.String,com.google.genai.types.GetBatchJobConfig) - function in com.google.genai.Batches

Gets a batch job resource.

get(java.lang.String,com.google.genai.types.GetCachedContentConfig) - function in com.google.genai.Caches

Gets a cached content resource.

get(java.lang.String,com.google.genai.types.GetDocumentConfig) - function in com.google.genai.Documents

get(java.lang.String,com.google.genai.types.GetFileSearchStoreConfig) - function in com.google.genai.FileSearchStores

get(java.lang.String,com.google.genai.types.GetFileConfig) - function in com.google.genai.Files

Retrieves the file information from the service.

get(java.lang.String,com.google.genai.types.GetModelConfig) - function in com.google.genai.Models

Fetches information about a model by name.

get(U,com.google.genai.types.GetOperationConfig) - function in com.google.genai.Operations

Gets the status of an Operation.

get(java.lang.String,com.google.genai.types.GetTuningJobConfig) - function in com.google.genai.Tunings

Makes an API request to get a tuning job.

getAcceptLanguage(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguage(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguage(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAcceptLanguageList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

List of the languages this model can accept.
Since the model is language-agnostic, this field is used as a reference.

repeated string accept_language = 5;

getAddDummyPrefix() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

Adds dummy whitespace at the beginning of text in order to
treat "world" in "world" and "hello world" in the same way.

optional bool add_dummy_prefix = 3 [default = true];

getAddDummyPrefix() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

Adds dummy whitespace at the beginning of text in order to
treat "world" in "world" and "hello world" in the same way.

optional bool add_dummy_prefix = 3 [default = true];

getAddDummyPrefix() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpecOrBuilder

Adds dummy whitespace at the beginning of text in order to
treat "world" in "world" and "hello world" in the same way.

optional bool add_dummy_prefix = 3 [default = true];

getAllFields() - function in com.google.protobuf.GeneratedMessageV3

getAllFields() - function in com.google.protobuf.GeneratedMessageV3.Builder

getAllFields() - function in com.google.protobuf.GeneratedMessageV3.ExtendableBuilder

getAllFields() - function in com.google.protobuf.GeneratedMessageV3.ExtendableMessage

getAllFields() - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getAllFields() - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getAllFields() - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getAllFields() - function in com.google.protobuf.SentencepieceModel.SelfTestData.SampleOrBuilder

getAllFields() - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getAllFields() - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getAllFieldsRaw() - function in com.google.protobuf.GeneratedMessageV3.ExtendableMessage

getAllowWhitespaceOnlyPieces() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Allows pieces that only contain whitespaces instead of appearing only as
prefix or suffix of other pieces.

optional bool allow_whitespace_only_pieces = 26 [default = false];

getAllowWhitespaceOnlyPieces() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Allows pieces that only contain whitespaces instead of appearing only as
prefix or suffix of other pieces.

optional bool allow_whitespace_only_pieces = 26 [default = false];

getAllowWhitespaceOnlyPieces() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Allows pieces that only contain whitespaces instead of appearing only as
prefix or suffix of other pieces.

optional bool allow_whitespace_only_pieces = 26 [default = false];

GetBatchJobConfig - class in com.google.genai.types

Optional parameters.

GetBatchJobConfig.Builder - class in com.google.genai.types.GetBatchJobConfig

Builder for GetBatchJobConfig.

GetBatchJobParameters - class in com.google.genai.types

Config for batches.get parameters.

GetBatchJobParameters.Builder - class in com.google.genai.types.GetBatchJobParameters

Builder for GetBatchJobParameters.

getBody() - function in com.google.genai.ApiResponse

Gets the ResponseBody.

getBody() - function in com.google.genai.ReplayApiResponse

Gets the ResponseBody.

getBosId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

<s>

optional int32 bos_id = 41 [default = 1];

getBosId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

<s>

optional int32 bos_id = 41 [default = 1];

getBosId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

<s>

optional int32 bos_id = 41 [default = 1];

getBosPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

optional string bos_piece = 46 [default = "<s>"];

getBosPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

optional string bos_piece = 46 [default = "<s>"];

getBosPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

optional string bos_piece = 46 [default = "<s>"];

getBosPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

optional string bos_piece = 46 [default = "<s>"];

getBosPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

optional string bos_piece = 46 [default = "<s>"];

getBosPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

optional string bos_piece = 46 [default = "<s>"];

getByteFallback() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Decomposes unknown pieces into UTF-8 bytes.

optional bool byte_fallback = 35 [default = false];

getByteFallback() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Decomposes unknown pieces into UTF-8 bytes.

optional bool byte_fallback = 35 [default = false];

getByteFallback() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Decomposes unknown pieces into UTF-8 bytes.

optional bool byte_fallback = 35 [default = false];

GetCachedContentConfig - class in com.google.genai.types

Optional parameters for caches.get method.

GetCachedContentConfig.Builder - class in com.google.genai.types.GetCachedContentConfig

Builder for GetCachedContentConfig.

GetCachedContentParameters - class in com.google.genai.types

Parameters for caches.get method.

GetCachedContentParameters.Builder - class in com.google.genai.types.GetCachedContentParameters

Builder for GetCachedContentParameters.

getCause() - function in java.lang.Throwable

getCharacterCoverage() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
Training parameters.

Uses characters which cover the corpus with the ratio of `chars_coverage`.
This parameter determines the set of basic Alphabet of sentence piece.
1.0 - `chars_coverage` characters are treated as UNK.
See also required_chars field.

optional float character_coverage = 10 [default = 0.9995];

getCharacterCoverage() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
Training parameters.

Uses characters which cover the corpus with the ratio of `chars_coverage`.
This parameter determines the set of basic Alphabet of sentence piece.
1.0 - `chars_coverage` characters are treated as UNK.
See also required_chars field.

optional float character_coverage = 10 [default = 0.9995];

getCharacterCoverage() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
Training parameters.

Uses characters which cover the corpus with the ratio of `chars_coverage`.
This parameter determines the set of basic Alphabet of sentence piece.
1.0 - `chars_coverage` characters are treated as UNK.
See also required_chars field.

optional float character_coverage = 10 [default = 0.9995];

getControlSymbols(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbols(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbols(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getControlSymbolsList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
Vocabulary management

Defines control symbols used as an indicator to
change the behavior of the decoder. <s> and </s> are pre-defined.
We can use this field to encode various meta information,
including language indicator in multilingual model.
These symbols are not visible to users, but visible to
the decoder. Note that when the input sentence contains control symbols,
they are not treated as one token, but segmented into normal pieces.
Control symbols must be inserted independently from the segmentation.

repeated string control_symbols = 30;

getDefaultInstance() - function in com.google.genai.proto.SentencepieceModel.ModelProto

getDefaultInstance() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece

getDefaultInstance() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

getDefaultInstance() - function in com.google.genai.proto.SentencepieceModel.SelfTestData

getDefaultInstance() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample

getDefaultInstance() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece.Builder

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.SelfTestData

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Builder

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample.Builder

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

getDefaultInstanceForType() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

getDefaultInstanceForType() - function in com.google.protobuf.MessageLiteOrBuilder

getDefaultInstanceForType() - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getDefaultInstanceForType() - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getDefaultInstanceForType() - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getDefaultInstanceForType() - function in com.google.protobuf.SentencepieceModel.SelfTestData.SampleOrBuilder

getDefaultInstanceForType() - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getDefaultInstanceForType() - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getDenormalizerSpec() - function in com.google.genai.proto.SentencepieceModel.ModelProto

Spec for text de-normalization.

optional .com.google.genai.proto.NormalizerSpec denormalizer_spec = 5;

getDenormalizerSpec() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Spec for text de-normalization.

optional .com.google.genai.proto.NormalizerSpec denormalizer_spec = 5;

getDenormalizerSpec() - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Spec for text de-normalization.

optional .com.google.genai.proto.NormalizerSpec denormalizer_spec = 5;

getDenormalizerSpecBuilder() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Spec for text de-normalization.

optional .com.google.genai.proto.NormalizerSpec denormalizer_spec = 5;

getDenormalizerSpecOrBuilder() - function in com.google.genai.proto.SentencepieceModel.ModelProto

Spec for text de-normalization.

optional .com.google.genai.proto.NormalizerSpec denormalizer_spec = 5;

getDenormalizerSpecOrBuilder() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Spec for text de-normalization.

optional .com.google.genai.proto.NormalizerSpec denormalizer_spec = 5;

getDenormalizerSpecOrBuilder() - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Spec for text de-normalization.

optional .com.google.genai.proto.NormalizerSpec denormalizer_spec = 5;

getDescriptor() - function in com.google.genai.proto.SentencepieceModel

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.ModelProto

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece.Builder

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece.Type

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.SelfTestData

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Builder

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample.Builder

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

getDescriptor() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.ModelType

getDescriptorForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

getDescriptorForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece.Builder

getDescriptorForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece.Type

getDescriptorForType() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

getDescriptorForType() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Builder

getDescriptorForType() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample.Builder

getDescriptorForType() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

getDescriptorForType() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.ModelType

getDescriptorForType() - function in com.google.protobuf.GeneratedMessageV3

getDescriptorForType() - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getDescriptorForType() - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getDescriptorForType() - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getDescriptorForType() - function in com.google.protobuf.SentencepieceModel.SelfTestData.SampleOrBuilder

getDescriptorForType() - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getDescriptorForType() - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getDifferentialPrivacyClippingThreshold() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Clipping threshold to apply after adding noise. All the words with
frequency less than this value are dropped.

optional uint64 differential_privacy_clipping_threshold = 52 [default = 0];

getDifferentialPrivacyClippingThreshold() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Clipping threshold to apply after adding noise. All the words with
frequency less than this value are dropped.

optional uint64 differential_privacy_clipping_threshold = 52 [default = 0];

getDifferentialPrivacyClippingThreshold() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Clipping threshold to apply after adding noise. All the words with
frequency less than this value are dropped.

optional uint64 differential_privacy_clipping_threshold = 52 [default = 0];

getDifferentialPrivacyNoiseLevel() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Set these parameters if you need DP version of sentencepiece.
std of noise to add.

optional float differential_privacy_noise_level = 51 [default = 0];

getDifferentialPrivacyNoiseLevel() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Set these parameters if you need DP version of sentencepiece.
std of noise to add.

optional float differential_privacy_noise_level = 51 [default = 0];

getDifferentialPrivacyNoiseLevel() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Set these parameters if you need DP version of sentencepiece.
std of noise to add.

optional float differential_privacy_noise_level = 51 [default = 0];

GetDocumentConfig - class in com.google.genai.types

Optional Config.

GetDocumentConfig.Builder - class in com.google.genai.types.GetDocumentConfig

Builder for GetDocumentConfig.

GetDocumentParameters - class in com.google.genai.types

Parameters for documents.get.

GetDocumentParameters.Builder - class in com.google.genai.types.GetDocumentParameters

Builder for GetDocumentParameters.

getEnableDifferentialPrivacy() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Whether to use DP version of sentencepiece. Use it with TSV input format
(requires precomputed word tab counts to work).

optional bool enable_differential_privacy = 50 [default = false];

getEnableDifferentialPrivacy() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Whether to use DP version of sentencepiece. Use it with TSV input format
(requires precomputed word tab counts to work).

optional bool enable_differential_privacy = 50 [default = false];

getEnableDifferentialPrivacy() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Whether to use DP version of sentencepiece. Use it with TSV input format
(requires precomputed word tab counts to work).

optional bool enable_differential_privacy = 50 [default = false];

getEosId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

</s>

optional int32 eos_id = 42 [default = 2];

getEosId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

</s>

optional int32 eos_id = 42 [default = 2];

getEosId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

</s>

optional int32 eos_id = 42 [default = 2];

getEosPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

optional string eos_piece = 47 [default = "</s>"];

getEosPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

optional string eos_piece = 47 [default = "</s>"];

getEosPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

optional string eos_piece = 47 [default = "</s>"];

getEosPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

optional string eos_piece = 47 [default = "</s>"];

getEosPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

optional string eos_piece = 47 [default = "</s>"];

getEosPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

optional string eos_piece = 47 [default = "</s>"];

getEscapeWhitespaces() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

Replaces whitespace with meta symbol.
This field must be true to train sentence piece model.

optional bool escape_whitespaces = 5 [default = true];

getEscapeWhitespaces() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

Replaces whitespace with meta symbol.
This field must be true to train sentence piece model.

optional bool escape_whitespaces = 5 [default = true];

getEscapeWhitespaces() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpecOrBuilder

Replaces whitespace with meta symbol.
This field must be true to train sentence piece model.

optional bool escape_whitespaces = 5 [default = true];

getExpected() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample

optional string expected = 2;

getExpected() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample.Builder

optional string expected = 2;

getExpected() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.SampleOrBuilder

optional string expected = 2;

getExpectedBytes() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample

optional string expected = 2;

getExpectedBytes() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample.Builder

optional string expected = 2;

getExpectedBytes() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.SampleOrBuilder

optional string expected = 2;

getExtension(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.GeneratedMessageV3.ExtendableBuilder

getExtension(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.GeneratedMessageV3.ExtendableMessage

getExtension(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getExtension(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getExtension(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getExtension(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getExtension(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getExtensionCount(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.GeneratedMessageV3.ExtendableBuilder

getExtensionCount(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.GeneratedMessageV3.ExtendableMessage

getExtensionCount(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getExtensionCount(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getExtensionCount(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getExtensionCount(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getExtensionCount(com.google.protobuf.ExtensionLite) - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3.Builder

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3.ExtendableBuilder

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3.ExtendableMessage

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.SelfTestData.SampleOrBuilder

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getField(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getFieldBuilder(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3.Builder

getFieldBuilder(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3.ExtendableBuilder

GetFileConfig - class in com.google.genai.types

Used to override the default configuration.

GetFileConfig.Builder - class in com.google.genai.types.GetFileConfig

Builder for GetFileConfig.

GetFileParameters - class in com.google.genai.types

Generates the parameters for the get method.

GetFileParameters.Builder - class in com.google.genai.types.GetFileParameters

Builder for GetFileParameters.

GetFileSearchStoreConfig - class in com.google.genai.types

Optional parameters for getting a FileSearchStore.

GetFileSearchStoreConfig.Builder - class in com.google.genai.types.GetFileSearchStoreConfig

Builder for GetFileSearchStoreConfig.

GetFileSearchStoreParameters - class in com.google.genai.types

Config for file_search_stores.get parameters.

GetFileSearchStoreParameters.Builder - class in com.google.genai.types.GetFileSearchStoreParameters

Builder for GetFileSearchStoreParameters.

getHardVocabLimit() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

`vocab_size` is treated as hard limit. Crash if
the model can not produce the vocab of size `vocab_size`,
When `hard_vocab_limit` is false, vocab_size is treated
as soft limit. Note that when model_type=char,
always assumes hard_vocab_limit = false.

optional bool hard_vocab_limit = 33 [default = true];

getHardVocabLimit() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

`vocab_size` is treated as hard limit. Crash if
the model can not produce the vocab of size `vocab_size`,
When `hard_vocab_limit` is false, vocab_size is treated
as soft limit. Note that when model_type=char,
always assumes hard_vocab_limit = false.

optional bool hard_vocab_limit = 33 [default = true];

getHardVocabLimit() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

`vocab_size` is treated as hard limit. Crash if
the model can not produce the vocab of size `vocab_size`,
When `hard_vocab_limit` is false, vocab_size is treated
as soft limit. Note that when model_type=char,
always assumes hard_vocab_limit = false.

optional bool hard_vocab_limit = 33 [default = true];

getHeaders() - function in com.google.genai.ApiResponse

Returns all of the headers from the response.

getHeaders() - function in com.google.genai.ReplayApiResponse

Returns all of the headers from the response.

getHistory(boolean) - function in com.google.genai.ChatBase

Returns the chat history.

getInitializationErrorString() - function in com.google.protobuf.AbstractMessage

getInitializationErrorString() - function in com.google.protobuf.AbstractMessage.Builder

getInitializationErrorString() - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getInitializationErrorString() - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getInitializationErrorString() - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getInitializationErrorString() - function in com.google.protobuf.SentencepieceModel.SelfTestData.SampleOrBuilder

getInitializationErrorString() - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getInitializationErrorString() - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getInput() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample

optional string input = 1;

getInput() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample.Builder

optional string input = 1;

getInput() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.SampleOrBuilder

optional string input = 1;

getInput(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInput(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInput(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputBytes() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample

optional string input = 1;

getInputBytes() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample.Builder

optional string input = 1;

getInputBytes() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.SampleOrBuilder

optional string input = 1;

getInputBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputBytes(int) - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputCount() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputFormat() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Input corpus format:
"text": one-sentence-per-line text format (default)
"tsv":  sentence <tab> freq

optional string input_format = 7;

getInputFormat() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Input corpus format:
"text": one-sentence-per-line text format (default)
"tsv":  sentence <tab> freq

optional string input_format = 7;

getInputFormat() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Input corpus format:
"text": one-sentence-per-line text format (default)
"tsv":  sentence <tab> freq

optional string input_format = 7;

getInputFormatBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Input corpus format:
"text": one-sentence-per-line text format (default)
"tsv":  sentence <tab> freq

optional string input_format = 7;

getInputFormatBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Input corpus format:
"text": one-sentence-per-line text format (default)
"tsv":  sentence <tab> freq

optional string input_format = 7;

getInputFormatBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Input corpus format:
"text": one-sentence-per-line text format (default)
"tsv":  sentence <tab> freq

optional string input_format = 7;

getInputList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputList() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
General parameters

Input corpus files.
 Trainer accepts the following two formats:
 A) Monolingual: plain text, one sentence per line.
 B) Bilingual:   TSV, source sentence <tab> target sentence
 When bilingual data is passed, shared vocabulary model is built.
 Note that the input file must be raw corpus, not a preprocessed corpus.
 Trainer only loads the first `input_sentence_size` sentences specified
 with this parameter.

repeated string input = 1;

getInputSentenceSize() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Maximum size of sentences the trainer loads from `input` parameter.
Trainer simply loads the `input` files in sequence.
It is better to shuffle the input corpus randomly.

optional uint64 input_sentence_size = 11 [default = 0];

getInputSentenceSize() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Maximum size of sentences the trainer loads from `input` parameter.
Trainer simply loads the `input` files in sequence.
It is better to shuffle the input corpus randomly.

optional uint64 input_sentence_size = 11 [default = 0];

getInputSentenceSize() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Maximum size of sentences the trainer loads from `input` parameter.
Trainer simply loads the `input` files in sequence.
It is better to shuffle the input corpus randomly.

optional uint64 input_sentence_size = 11 [default = 0];

getLocalizedMessage() - function in java.lang.Throwable

getMaxSentenceLength() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

The maximum sentence length in byte. The sentences with the length
larger than `max_sentence_length` is simply ignored.
Longer input tends to bring the following risks:
 * Overflow during EM training (unigram language model only)
 * Performance drop because of O(n log n) cost in BPE.

optional int32 max_sentence_length = 18 [default = 4192];

getMaxSentenceLength() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

The maximum sentence length in byte. The sentences with the length
larger than `max_sentence_length` is simply ignored.
Longer input tends to bring the following risks:
 * Overflow during EM training (unigram language model only)
 * Performance drop because of O(n log n) cost in BPE.

optional int32 max_sentence_length = 18 [default = 4192];

getMaxSentenceLength() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

The maximum sentence length in byte. The sentences with the length
larger than `max_sentence_length` is simply ignored.
Longer input tends to bring the following risks:
 * Overflow during EM training (unigram language model only)
 * Performance drop because of O(n log n) cost in BPE.

optional int32 max_sentence_length = 18 [default = 4192];

getMaxSentencepieceLength() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

/////////////////////////////////////////////////////////////////
SentencePiece parameters which control the shapes of sentence piece.

Maximum length of sentencepiece.

optional int32 max_sentencepiece_length = 20 [default = 16];

getMaxSentencepieceLength() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

/////////////////////////////////////////////////////////////////
SentencePiece parameters which control the shapes of sentence piece.

Maximum length of sentencepiece.

optional int32 max_sentencepiece_length = 20 [default = 16];

getMaxSentencepieceLength() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

/////////////////////////////////////////////////////////////////
SentencePiece parameters which control the shapes of sentence piece.

Maximum length of sentencepiece.

optional int32 max_sentencepiece_length = 20 [default = 16];

getMessage() - function in java.lang.Throwable

getMiningSentenceSize() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Maximum size of sentences to make seed sentence pieces.
Extended suffix array is constructed to extract frequent
sub-strings from the corpus. This uses 20N working space,
where N is the size of corpus.

optional int32 mining_sentence_size = 12 [deprecated = true];

getMiningSentenceSize() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Maximum size of sentences to make seed sentence pieces.
Extended suffix array is constructed to extract frequent
sub-strings from the corpus. This uses 20N working space,
where N is the size of corpus.

optional int32 mining_sentence_size = 12 [deprecated = true];

getMiningSentenceSize() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Maximum size of sentences to make seed sentence pieces.
Extended suffix array is constructed to extract frequent
sub-strings from the corpus. This uses 20N working space,
where N is the size of corpus.

optional int32 mining_sentence_size = 12 [deprecated = true];

GetModelConfig - class in com.google.genai.types

Optional parameters for models.get method.

GetModelConfig.Builder - class in com.google.genai.types.GetModelConfig

Builder for GetModelConfig.

GetModelParameters - class in com.google.genai.types

None

GetModelParameters.Builder - class in com.google.genai.types.GetModelParameters

Builder for GetModelParameters.

getModelPrefix() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Output model file prefix.
<model_prefix>.model and <model_prefix>.vocab are generated.

optional string model_prefix = 2;

getModelPrefix() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Output model file prefix.
<model_prefix>.model and <model_prefix>.vocab are generated.

optional string model_prefix = 2;

getModelPrefix() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Output model file prefix.
<model_prefix>.model and <model_prefix>.vocab are generated.

optional string model_prefix = 2;

getModelPrefixBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Output model file prefix.
<model_prefix>.model and <model_prefix>.vocab are generated.

optional string model_prefix = 2;

getModelPrefixBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Output model file prefix.
<model_prefix>.model and <model_prefix>.vocab are generated.

optional string model_prefix = 2;

getModelPrefixBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Output model file prefix.
<model_prefix>.model and <model_prefix>.vocab are generated.

optional string model_prefix = 2;

getModelType() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

optional .com.google.genai.proto.TrainerSpec.ModelType model_type = 3 [default = UNIGRAM];

getModelType() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

optional .com.google.genai.proto.TrainerSpec.ModelType model_type = 3 [default = UNIGRAM];

getModelType() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

optional .com.google.genai.proto.TrainerSpec.ModelType model_type = 3 [default = UNIGRAM];

getName() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

name of normalization rule.

optional string name = 1;

getName() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

name of normalization rule.

optional string name = 1;

getName() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpecOrBuilder

name of normalization rule.

optional string name = 1;

getNameBytes() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

name of normalization rule.

optional string name = 1;

getNameBytes() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

name of normalization rule.

optional string name = 1;

getNameBytes() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpecOrBuilder

name of normalization rule.

optional string name = 1;

getNormalizationRuleTsv() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

Custom normalization rule file in TSV format.
https://github.com/google/sentencepiece/blob/master/doc/normalization.md
This field is only used in SentencePieceTrainer::Train() method, which
compiles the rule into the binary rule stored in `precompiled_charsmap`.

optional string normalization_rule_tsv = 6;

getNormalizationRuleTsv() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

Custom normalization rule file in TSV format.
https://github.com/google/sentencepiece/blob/master/doc/normalization.md
This field is only used in SentencePieceTrainer::Train() method, which
compiles the rule into the binary rule stored in `precompiled_charsmap`.

optional string normalization_rule_tsv = 6;

getNormalizationRuleTsv() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpecOrBuilder

Custom normalization rule file in TSV format.
https://github.com/google/sentencepiece/blob/master/doc/normalization.md
This field is only used in SentencePieceTrainer::Train() method, which
compiles the rule into the binary rule stored in `precompiled_charsmap`.

optional string normalization_rule_tsv = 6;

getNormalizationRuleTsvBytes() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

Custom normalization rule file in TSV format.
https://github.com/google/sentencepiece/blob/master/doc/normalization.md
This field is only used in SentencePieceTrainer::Train() method, which
compiles the rule into the binary rule stored in `precompiled_charsmap`.

optional string normalization_rule_tsv = 6;

getNormalizationRuleTsvBytes() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

Custom normalization rule file in TSV format.
https://github.com/google/sentencepiece/blob/master/doc/normalization.md
This field is only used in SentencePieceTrainer::Train() method, which
compiles the rule into the binary rule stored in `precompiled_charsmap`.

optional string normalization_rule_tsv = 6;

getNormalizationRuleTsvBytes() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpecOrBuilder

Custom normalization rule file in TSV format.
https://github.com/google/sentencepiece/blob/master/doc/normalization.md
This field is only used in SentencePieceTrainer::Train() method, which
compiles the rule into the binary rule stored in `precompiled_charsmap`.

optional string normalization_rule_tsv = 6;

getNormalizerSpec() - function in com.google.genai.proto.SentencepieceModel.ModelProto

Spec for text normalization.

optional .com.google.genai.proto.NormalizerSpec normalizer_spec = 3;

getNormalizerSpec() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Spec for text normalization.

optional .com.google.genai.proto.NormalizerSpec normalizer_spec = 3;

getNormalizerSpec() - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Spec for text normalization.

optional .com.google.genai.proto.NormalizerSpec normalizer_spec = 3;

getNormalizerSpecBuilder() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Spec for text normalization.

optional .com.google.genai.proto.NormalizerSpec normalizer_spec = 3;

getNormalizerSpecOrBuilder() - function in com.google.genai.proto.SentencepieceModel.ModelProto

Spec for text normalization.

optional .com.google.genai.proto.NormalizerSpec normalizer_spec = 3;

getNormalizerSpecOrBuilder() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Spec for text normalization.

optional .com.google.genai.proto.NormalizerSpec normalizer_spec = 3;

getNormalizerSpecOrBuilder() - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Spec for text normalization.

optional .com.google.genai.proto.NormalizerSpec normalizer_spec = 3;

getNumber() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece.Type

getNumber() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.ModelType

getNumSubIterations() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Number of EM sub iterations.

optional int32 num_sub_iterations = 17 [default = 2];

getNumSubIterations() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Number of EM sub iterations.

optional int32 num_sub_iterations = 17 [default = 2];

getNumSubIterations() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Number of EM sub iterations.

optional int32 num_sub_iterations = 17 [default = 2];

getNumThreads() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Number of threads in the training.

optional int32 num_threads = 16 [default = 16];

getNumThreads() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Number of threads in the training.

optional int32 num_threads = 16 [default = 16];

getNumThreads() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Number of threads in the training.

optional int32 num_threads = 16 [default = 16];

getOneofFieldDescriptor(com.google.protobuf.Descriptors.OneofDescriptor) - function in com.google.protobuf.GeneratedMessageV3

getOneofFieldDescriptor(com.google.protobuf.Descriptors.OneofDescriptor) - function in com.google.protobuf.GeneratedMessageV3.Builder

getOneofFieldDescriptor(com.google.protobuf.Descriptors.OneofDescriptor) - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getOneofFieldDescriptor(com.google.protobuf.Descriptors.OneofDescriptor) - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getOneofFieldDescriptor(com.google.protobuf.Descriptors.OneofDescriptor) - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getOneofFieldDescriptor(com.google.protobuf.Descriptors.OneofDescriptor) - function in com.google.protobuf.SentencepieceModel.SelfTestData.SampleOrBuilder

getOneofFieldDescriptor(com.google.protobuf.Descriptors.OneofDescriptor) - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getOneofFieldDescriptor(com.google.protobuf.Descriptors.OneofDescriptor) - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

GetOperationConfig - class in com.google.genai.types

None

GetOperationConfig.Builder - class in com.google.genai.types.GetOperationConfig

Builder for GetOperationConfig.

GetOperationParameters - class in com.google.genai.types

Parameters for the GET method.

GetOperationParameters.Builder - class in com.google.genai.types.GetOperationParameters

Builder for GetOperationParameters.

getOperationParametersToMldev(com.fasterxml.jackson.databind.JsonNode,com.fasterxml.jackson.databind.node.ObjectNode) - function in com.google.genai.OperationsConverters

getOperationParametersToVertex(com.fasterxml.jackson.databind.JsonNode,com.fasterxml.jackson.databind.node.ObjectNode) - function in com.google.genai.OperationsConverters

getPadId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

<pad> (padding)

optional int32 pad_id = 43 [default = -1];

getPadId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

<pad> (padding)

optional int32 pad_id = 43 [default = -1];

getPadId() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

<pad> (padding)

optional int32 pad_id = 43 [default = -1];

getPadPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

optional string pad_piece = 48 [default = "<pad>"];

getPadPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

optional string pad_piece = 48 [default = "<pad>"];

getPadPiece() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

optional string pad_piece = 48 [default = "<pad>"];

getPadPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

optional string pad_piece = 48 [default = "<pad>"];

getPadPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

optional string pad_piece = 48 [default = "<pad>"];

getPadPieceBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

optional string pad_piece = 48 [default = "<pad>"];

getParserForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto

getParserForType() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece

getParserForType() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

getParserForType() - function in com.google.genai.proto.SentencepieceModel.SelfTestData

getParserForType() - function in com.google.genai.proto.SentencepieceModel.SelfTestData.Sample

getParserForType() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

getParserForType() - function in com.google.protobuf.Message

getParserForType() - function in com.google.protobuf.MessageLite

getPiece() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece

piece must not be empty.

optional string piece = 1;

getPiece() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece.Builder

piece must not be empty.

optional string piece = 1;

getPiece() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePieceOrBuilder

piece must not be empty.

optional string piece = 1;

getPieceBytes() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece

piece must not be empty.

optional string piece = 1;

getPieceBytes() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePiece.Builder

piece must not be empty.

optional string piece = 1;

getPieceBytes() - function in com.google.genai.proto.SentencepieceModel.ModelProto.SentencePieceOrBuilder

piece must not be empty.

optional string piece = 1;

getPieces(int) - function in com.google.genai.proto.SentencepieceModel.ModelProto

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPieces(int) - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPieces(int) - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesBuilder(int) - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesBuilderList() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesCount() - function in com.google.genai.proto.SentencepieceModel.ModelProto

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesCount() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesCount() - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesList() - function in com.google.genai.proto.SentencepieceModel.ModelProto

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesList() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesList() - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesOrBuilder(int) - function in com.google.genai.proto.SentencepieceModel.ModelProto

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesOrBuilder(int) - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesOrBuilder(int) - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesOrBuilderList() - function in com.google.genai.proto.SentencepieceModel.ModelProto

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesOrBuilderList() - function in com.google.genai.proto.SentencepieceModel.ModelProto.Builder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPiecesOrBuilderList() - function in com.google.genai.proto.SentencepieceModel.ModelProtoOrBuilder

Sentence pieces with scores.

repeated .com.google.genai.proto.ModelProto.SentencePiece pieces = 1;

getPrecompiledCharsmap() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

Pre-compiled normalization rule created by
Builder::GetPrecompiledCharsMap() or Builder::CompileCharsMap() method.
Usually this field is set by Builder::GetNormalizerSpec() method.

optional bytes precompiled_charsmap = 2;

getPrecompiledCharsmap() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

Pre-compiled normalization rule created by
Builder::GetPrecompiledCharsMap() or Builder::CompileCharsMap() method.
Usually this field is set by Builder::GetNormalizerSpec() method.

optional bytes precompiled_charsmap = 2;

getPrecompiledCharsmap() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpecOrBuilder

Pre-compiled normalization rule created by
Builder::GetPrecompiledCharsMap() or Builder::CompileCharsMap() method.
Usually this field is set by Builder::GetNormalizerSpec() method.

optional bytes precompiled_charsmap = 2;

getPretokenizationDelimiter() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Defines the pre-tokenization delimiter.
When specified, no pieces crossing this delimiter is not included
in the vocab. Then the delimiter string is virtually ignored
during the training. This field can allows constraints on the vocabulary
selection. Note that this field is available on unigram mode.

optional string pretokenization_delimiter = 53 [default = ""];

getPretokenizationDelimiter() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Defines the pre-tokenization delimiter.
When specified, no pieces crossing this delimiter is not included
in the vocab. Then the delimiter string is virtually ignored
during the training. This field can allows constraints on the vocabulary
selection. Note that this field is available on unigram mode.

optional string pretokenization_delimiter = 53 [default = ""];

getPretokenizationDelimiter() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Defines the pre-tokenization delimiter.
When specified, no pieces crossing this delimiter is not included
in the vocab. Then the delimiter string is virtually ignored
during the training. This field can allows constraints on the vocabulary
selection. Note that this field is available on unigram mode.

optional string pretokenization_delimiter = 53 [default = ""];

getPretokenizationDelimiterBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Defines the pre-tokenization delimiter.
When specified, no pieces crossing this delimiter is not included
in the vocab. Then the delimiter string is virtually ignored
during the training. This field can allows constraints on the vocabulary
selection. Note that this field is available on unigram mode.

optional string pretokenization_delimiter = 53 [default = ""];

getPretokenizationDelimiterBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Defines the pre-tokenization delimiter.
When specified, no pieces crossing this delimiter is not included
in the vocab. Then the delimiter string is virtually ignored
during the training. This field can allows constraints on the vocabulary
selection. Note that this field is available on unigram mode.

optional string pretokenization_delimiter = 53 [default = ""];

getPretokenizationDelimiterBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Defines the pre-tokenization delimiter.
When specified, no pieces crossing this delimiter is not included
in the vocab. Then the delimiter string is virtually ignored
during the training. This field can allows constraints on the vocabulary
selection. Note that this field is available on unigram mode.

optional string pretokenization_delimiter = 53 [default = ""];

getRemoveExtraWhitespaces() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec

Removes leading, trailing, and duplicate internal whitespace.

optional bool remove_extra_whitespaces = 4 [default = true];

getRemoveExtraWhitespaces() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpec.Builder

Removes leading, trailing, and duplicate internal whitespace.

optional bool remove_extra_whitespaces = 4 [default = true];

getRemoveExtraWhitespaces() - function in com.google.genai.proto.SentencepieceModel.NormalizerSpecOrBuilder

Removes leading, trailing, and duplicate internal whitespace.

optional bool remove_extra_whitespaces = 4 [default = true];

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.GeneratedMessageV3

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.GeneratedMessageV3.Builder

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.GeneratedMessageV3.ExtendableBuilder

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.GeneratedMessageV3.ExtendableMessage

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.SentencepieceModel.SelfTestData.SampleOrBuilder

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getRepeatedFieldBuilder(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.GeneratedMessageV3.Builder

getRepeatedFieldBuilder(com.google.protobuf.Descriptors.FieldDescriptor,int) - function in com.google.protobuf.GeneratedMessageV3.ExtendableBuilder

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3.Builder

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3.ExtendableBuilder

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.GeneratedMessageV3.ExtendableMessage

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.ModelProto.SentencePieceOrBuilder

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.ModelProtoOrBuilder

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.NormalizerSpecOrBuilder

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.SelfTestData.SampleOrBuilder

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.SelfTestDataOrBuilder

getRepeatedFieldCount(com.google.protobuf.Descriptors.FieldDescriptor) - function in com.google.protobuf.SentencepieceModel.TrainerSpecOrBuilder

getRequiredChars() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Defines required characters. Each UTF8 character in this string is included
in the character set regardless of character_coverage value. Unlike
user_defined_symbols, these characters have scores based on the frequency
on input sentences, and the model can form subwords using characters
in this field.

optional string required_chars = 36;

getRequiredChars() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Defines required characters. Each UTF8 character in this string is included
in the character set regardless of character_coverage value. Unlike
user_defined_symbols, these characters have scores based on the frequency
on input sentences, and the model can form subwords using characters
in this field.

optional string required_chars = 36;

getRequiredChars() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Defines required characters. Each UTF8 character in this string is included
in the character set regardless of character_coverage value. Unlike
user_defined_symbols, these characters have scores based on the frequency
on input sentences, and the model can form subwords using characters
in this field.

optional string required_chars = 36;

getRequiredCharsBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec

Defines required characters. Each UTF8 character in this string is included
in the character set regardless of character_coverage value. Unlike
user_defined_symbols, these characters have scores based on the frequency
on input sentences, and the model can form subwords using characters
in this field.

optional string required_chars = 36;

getRequiredCharsBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpec.Builder

Defines required characters. Each UTF8 character in this string is included
in the character set regardless of character_coverage value. Unlike
user_defined_symbols, these characters have scores based on the frequency
on input sentences, and the model can form subwords using characters
in this field.

optional string required_chars = 36;

getRequiredCharsBytes() - function in com.google.genai.proto.SentencepieceModel.TrainerSpecOrBuilder

Defines required characters. Each UTF8 character in this string is included
in the character set regardless of character_coverage value. Unlike
user_defined_symbols, these characters have scores based on the frequency
on input sentences, and the model can form subwords using characters
in this field.

optional string required_chars = 36;

getSamples(int) - function in com.google.genai.proto.SentencepieceModel.SelfTestData