Package-level declarations
Types used in the Google GenAI SDK.
Types
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Marks the end of user activity.
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The different ways of handling user activity.
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Marks the start of user activity.
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Adapter size for tuning.
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Aggregation metric.
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The aggregation result for the entire dataset and all metrics.
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The aggregation result for a single metric.
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The generic reusable api auth config.
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The API secret.
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Config for authentication with API key.
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The audio transcription configuration in Setup.
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The authentication config to access the API.
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Config for Google Service Account Authentication.
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Config for HTTP Basic Authentication.
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Config for user oauth.
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Config for user OIDC auth.
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Config for auth_tokens.create parameters.
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Configures automatic detection of activity.
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The configuration for automatic function calling.
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Autorater config used for evaluation.
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Configures the avatar to be used in the session.
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Config for batches.create return value.
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Config for `des` parameter.
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Represents the `output_info` field in batch jobs.
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Config for `src` parameter.
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The BigQuery location for the input content.
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Bleu metric value for an instance.
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Spec for bleu metric.
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A content blob.
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Output only.
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A resource used in LLM queries for users to explicitly specify what to cache.
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Metadata on the usage of the cached content.
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Optional parameters.
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Config for batches.cancel parameters.
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Optional parameters for tunings.cancel method.
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Parameters for the cancel method.
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Empty response for tunings.cancel method.
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A response candidate generated from the model.
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Describes the machine learning model version checkpoint.
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Config for telling the service how to chunk the file.
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A citation for a piece of generatedcontent.
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Citation information when the model quotes another source.
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Client options to be used in the client instantiation.
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Result of executing the `ExecutableCode`.
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Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
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Specification for a computation based metric.
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Represents the type of the computation based metric.
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Tool to support computer use.
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Optional parameters for computing tokens.
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Parameters for computing tokens.
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Response for computing tokens.
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Local tokenizer compute tokens result.
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Contains the multi-part content of a message.
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The embedding generated from an input content.
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Statistics of the input text associated with the result of content embedding.
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A content reference image.
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Enables context window compression -- mechanism managing model context window so it does not exceed given length.
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Configuration for a Control reference image.
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A control reference image.
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Enum representing the control type of a control reference image.
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Config for the count_tokens method.
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Parameters for counting tokens.
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Response for counting tokens.
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Local tokenizer count tokens result.
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Optional parameters.
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Config for auth_tokens.create parameters.
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Config for optional parameters.
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Config for batches.create parameters.
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Optional configuration for cached content creation.
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Parameters for caches.create method.
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Config for optional parameters.
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Config for batches.create parameters.
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Used to override the default configuration.
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Generates the parameters for the private _create method.
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Response for the create file method.
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Optional parameters for creating a file search store.
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Config for file_search_stores.create parameters.
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Fine-tuning job creation request - optional fields.
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Fine-tuning job creation parameters - optional fields.
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Fine-tuning job creation parameters - optional fields.
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Result for custom code execution metric.
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Specificies a metric that is computed by running user-defined Python functions remotely.
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Configures the customized avatar to be used in the session.
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User provided metadata stored as key-value pairs.
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Spec for custom output.
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Config for custom output format.
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Distribution computed over a tuning dataset.
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Dataset bucket used to create a histogram for the distribution given a population of values.
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Statistics computed over a tuning dataset.
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Optional parameters for models.get method.
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Config for batches.delete parameters.
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Optional parameters for caches.delete method.
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Parameters for caches.delete method.
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Empty response for caches.delete method.
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Config for optional parameters.
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Config for documents.delete parameters.
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Used to override the default configuration.
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Generates the parameters for the get method.
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Response for the delete file method.
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Optional parameters for deleting a FileSearchStore.
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Config for file_search_stores.delete parameters.
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Configuration for deleting a tuned model.
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Parameters for deleting a tuned model.
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None
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The return value of delete operation.
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Statistics for distillation prompt dataset.
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Hyperparameters for distillation.
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Spec for creating a distilled dataset in Vertex Dataset.
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Distillation tuning spec for tuning.
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A Document is a collection of Chunks.
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Output only.
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Used to override the default configuration.
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Used to override the default configuration.
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Describes the options to customize dynamic retrieval.
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The mode of the predictor to be used in dynamic retrieval.
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Configuration for editing an image.
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Parameters for the request to edit an image.
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Response for the request to edit an image.
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Parameters for the embed_content method.
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Optional parameters for the embed_content method.
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Request-level metadata for the Gemini Enterprise Agent Platform Embed Content API.
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Parameters for the embed_content method.
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Parameters for the _embed_content method.
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Response for the embed_content method.
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Enum representing the Gemini Enterprise Agent Platform embedding API to use.
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None
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Represents a customer-managed encryption key specification that can be applied to a Vertex AI resource.
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An endpoint where you deploy models.
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End of speech sensitivity.
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Tool to search public web data, powered by Vertex AI Search and Sec4 compliance.
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An entity representing the segmented area.
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The environment being operated.
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The results from an evaluation run performed by the EvaluationService.
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Evaluate Dataset Run Result for Tuning Job.
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Evaluation config for tuning.
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The dataset used for evaluation.
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Exact match metric value for an instance.
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Model-generated code executed server-side, results returned to the model.
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Retrieve from data source powered by external API for grounding.
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The search parameters to use for the ELASTIC_SEARCH spec.
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The search parameters to use for SIMPLE_SEARCH spec.
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Options for feature selection preference.
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None
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Parameters for the fetchPredictOperation method.
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A file uploaded to the API.
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URI-based data.
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The FileSearch tool that retrieves knowledge from Semantic Retrieval corpora.
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A collection of Documents.
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Source of the File.
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Status of a File that uses a common error model.
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Output only.
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Tuning Spec for Full Fine Tuning.
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A function call.
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Function calling config.
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Function calling mode.
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Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3).
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A function response.
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Raw media bytes for function response.
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URI based data for function response.
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A datatype containing media that is part of a `FunctionResponse` message.
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Specifies how the response should be scheduled in the conversation.
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The Google Cloud Storage location where the output is to be written to.
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The Google Cloud Storage location for the input content.
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Input example for preference optimization.
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Completion and its preference score.
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Optional model configuration parameters.
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Config for models.generate_content parameters.
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Response message for PredictionService.GenerateContent.
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Content filter results for a prompt sent in the request.
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Usage metadata about the content generation request and response.
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An output image.
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A generated image mask.
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A generated video.
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The config for generating an images.
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The parameters for generating images.
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The output images response.
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Configuration for generating videos.
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A video generation operation.
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Class that represents the parameters for generating videos.
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Response with generated videos.
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A set of source input(s) for video generation.
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Generation config.
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The configuration for routing the request to a specific model.
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The configuration for automated routing.
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The configuration for manual routing.
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Optional parameters.
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Config for batches.get parameters.
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Optional parameters for caches.get method.
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Parameters for caches.get method.
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Optional Config.
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Parameters for documents.get.
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Used to override the default configuration.
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Generates the parameters for the get method.
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Optional parameters for getting a FileSearchStore.
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Config for file_search_stores.get parameters.
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Optional parameters for models.get method.
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None
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None
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Parameters for the GET method.
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Optional parameters for tunings.get method.
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Parameters for the get method.
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Tool to retrieve knowledge from Google Maps.
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The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs.
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GoogleSearch tool type.
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Tool to retrieve public web data for grounding, powered by Google.
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Represents a whole or partial calendar date, such as a birthday.
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A piece of evidence that supports a claim made by the model.
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User provided metadata about the GroundingFact.
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An `Image` chunk is a piece of evidence that comes from an image search result.
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A `Maps` chunk is a piece of evidence that comes from Google Maps.
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The sources that were used to generate the place answer.
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public abstract class GroundingChunkMapsPlaceAnswerSourcesAuthorAttribution extends JsonSerializable
Author attribution for a photo or review.
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Encapsulates a review snippet.
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Route information from Google Maps.
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Context retrieved from a data source to ground the model's response.
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A list of string values.
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A `Web` chunk is a piece of evidence that comes from a web page.
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Information for various kinds of grounding.
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A URI that can be used to flag a place or review for inappropriate content.
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Grounding support.
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The method for blocking content.
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The threshold for blocking content.
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The harm category to be blocked.
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Output only.
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Output only.
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The location of the API key.
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HTTP options to be used in each of the requests.
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A wrapper class for the http response.
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HTTP retry options to be used in each of the requests.
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An image.
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The image generation configuration to be used in GenerateContentConfig.
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The image output format for generated images.
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Enum that specifies the language of the text in the prompt.
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Resize mode for the image input for video generation.
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Image search for grounding and related configurations.
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Optional parameters for importing a file.
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Long-running operation for importing a file to a FileSearchStore.
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Config for file_search_stores.import_file parameters.
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Response for ImportFile to import a File API file with a file search store.
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Config for `inlined_embedding_responses` parameter.
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Config for inlined request.
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Config for `inlined_responses` parameter.
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Parameters for the private _Register method.
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Represents a time interval, encoded as a Timestamp start (inclusive) and a Timestamp end (exclusive).
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Job error.
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An object that represents a latitude/longitude pair.
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Config for optional parameters.
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Config for batches.list parameters.
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Config for batches.list return value.
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Config for caches.list method.
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Parameters for caches.list method.
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None
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Config for optional parameters.
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Config for documents.list parameters.
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Config for documents.list return value.
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Used to override the default configuration.
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Optional parameters for listing FileSearchStore.
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Config for file_search_stores.list parameters.
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Config for file_search_stores.list return value.
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Generates the parameters for the list method.
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Response for the list files method.
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None
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None
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None
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Configuration for the list tuning jobs method.
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Parameters for the list tuning jobs method.
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Response for the list tuning jobs method.
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Incremental update of the current conversation delivered from the client.
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Messages sent by the client in the API call.
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User input that is sent in real time.
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Message contains configuration that will apply for the duration of the streaming session.
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Client generated response to a `ToolCall` received from the server.
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Session config for the API connection.
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Config for LiveConnectConstraints for Auth Token creation.
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Parameters for connecting to the live API.
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Parameters for sending client content to the live API.
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Parameters for sending realtime input to the live API.
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Parameters for sending tool responses to the live API.
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Incremental server update generated by the model in response to client messages.
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Server will not be able to service client soon.
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Response message for API call.
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Update of the session resumption state.
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Sent in response to a `LiveGenerateContentSetup` message from the client.
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Request for the client to execute the `function_calls` and return the responses with the matching `id`s.
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Notification for the client that a previously issued `ToolCallMessage` with the specified `id`s should have been not executed and should be cancelled.
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Specification for an LLM based metric.
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The log probabilities of the tokens generated by the model.
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A single token and its associated log probability.
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A list of the top candidate tokens and their log probabilities at each decoding step.
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Configuration for a Mask reference image.
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A mask reference image.
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Enum representing the mask mode of a mask reference image.
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A MCPServer is a server that can be called by the model to perform actions.
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Server content modalities.
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The media resolution to use.
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The metric used for evaluation.
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Represents token counting info for a single modality.
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A trained machine learning model.
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Configuration for Model Armor.
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The model routing preference.
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Config for model selection.
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The stage of the underlying model.
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The status of the underlying model.
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Configuration for a multi-speaker text-to-speech request.
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Config for evaluation output.
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Describes the info for output of EvaluationService.
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Output only.
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Spec for pairwise metric result.
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Spec for pairwise metric.
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A datatype containing media content.
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Partial argument value of the function call.
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Media resolution for the input media.
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The tokenization quality used for given media.
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Tuning spec for Partner models.
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Enum that controls the generation of people.
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Sites with confidence level chosen &above this value will be blocked from the search results.
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Spec for pointwise metric result.
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Spec for pointwise metric.
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Configuration for a prebuilt voice.
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The spec for a pre-defined metric.
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Statistics computed for datasets used for preference optimization.
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Hyperparameters for Preference Optimization.
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Preference optimization tuning spec for tuning.
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A pre-tuned model for continuous tuning.
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Config for proactivity features.
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An image of the product.
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Controls whether prominent people (celebrities) generation is allowed.
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Proxy configuration for the client.
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A RagChunk includes the content of a chunk of a RagFile, and associated metadata.
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Represents where the chunk starts and ends in the document.
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Specifies the context retrieval config.
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Config for filters.
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Config for Hybrid Search.
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Config for ranking and reranking.
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Config for LlmRanker.
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Config for Rank Service.
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Raw output.
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A raw reference image.
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Marks the end of user activity.
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Configuration for recontextualizing an image.
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The parameters for recontextualizing an image.
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The output images response.
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A set of source input(s) for image recontextualization.
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An interface for a Reference image.
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Private class that represents a Reference image that is sent to API.
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Used to override the default configuration.
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Response for the _register file method.
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Represents a recorded session.
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Represents a single interaction, request and response in a replay.
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Represents a single request in a replay.
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Represents a single response in a replay.
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The configuration for the replicated voice to use.
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Resource scope.
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Defines a retrieval tool that model can call to access external knowledge.
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Retrieval config.
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Metadata returned to client when grounding is enabled.
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Rouge metric value for an instance.
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Spec for rouge metric.
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The type of rubric content to be generated.
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Specification for how rubrics should be generated.
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Safety attributes of a GeneratedImage or the user-provided prompt.
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Enum that controls the safety filter level for objectionable content.
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A safety rating for a piece of content.
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A safety setting that affects the safety-blocking behavior.
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Schema is used to define the format of input/output data.
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An image mask representing a brush scribble.
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The entry point used to search for grounding sources.
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Different types of search that can be enabled on the GoogleSearch tool.
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Segment of the content this support belongs to.
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Configuration for segmenting an image.
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The parameters for segmenting an image.
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The output images response.
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A set of source input(s) for image segmentation.
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Enum that represents the segmentation mode.
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Pricing and performance service tier.
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Configuration of session resumption mechanism.
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Config for `response` parameter.
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Context window will be truncated by keeping only suffix of it.
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Configuration for a single speaker in a multi-speaker setup.
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Config for speech generation and transcription.
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Start of speech sensitivity.
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A transport that can stream HTTP requests and responses.
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Config for stream translation.
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User provided string values assigned to a single metadata key.
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Configuration for a Style reference image.
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A style reference image.
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Configuration for a Subject reference image.
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A subject reference image.
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Enum representing the subject type of a subject reference image.
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Hyperparameters for SFT.
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Dataset distribution for Supervised Tuning.
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Dataset bucket used to create a histogram for the distribution given a population of values.
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Tuning data statistics for Supervised Tuning.
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Supervised tuning spec for tuning.
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None
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None
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The thinking features configuration.
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The number of thoughts tokens that the model should generate.
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Tokens info with a list of tokens and the corresponding list of token ids.
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Tool details of a tool that the model may use to generate a response.
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A predicted server-side `ToolCall` returned from the model.
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Tool that executes code generated by the model, and automatically returns the result to the model.
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Tool config.
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ParallelAiSearch tool type.
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The output from a server-side `ToolCall` execution.
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Output only.
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Audio transcription in Server Conent.
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TunedModel for the Tuned Model of a Tuning Job.
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TunedModelCheckpoint for the Tuned Model of a Tuning Job.
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A tuned machine learning model.
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Supervised fine-tuning training dataset.
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The tuning data statistic values for TuningJob.
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A single example for tuning.
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A tuning job.
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Tuning job metadata.
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Output only.
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Enum representing the tuning method.
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Tuning mode.
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A long-running operation.
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The tuning task.
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None
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The reason why the turn is complete.
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Options about which input is included in the user's turn.
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The unified metric used for evaluation.
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Optional parameters for caches.update method.
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None
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Configuration for updating a tuned model.
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Configuration for updating a tuned model.
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Used to override the default configuration.
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Optional parameters for uploading a file to a FileSearchStore.
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Long-running operation for uploading a file to a FileSearchStore.
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Generates the parameters for the private _upload_to_file_search_store method.
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The response when long-running operation for uploading a file to a FileSearchStore complete.
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Response for the resumable upload method.
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Internal API config for UpscaleImage.
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API parameters for UpscaleImage.
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Configuration for upscaling an image.
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User-facing config UpscaleImageParameters.
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None
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Tool to support URL context.
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Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL.
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The metadata for a single URL retrieval.
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The status of the URL retrieval.
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Usage metadata about response(s).
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The type of the VAD signal.
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Hyperparameters for Veo.
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Tuning Spec for Veo Model Tuning.
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Retrieve from Vertex AI Search datastore or engine for grounding.
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Define data stores within engine to filter on in a search call and configurations for those data stores.
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This class is experimental and may change in future versions.
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Retrieve from Vertex RAG Store for grounding.
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The definition of the Rag resource.
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A generated video.
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Enum that controls the compression quality of the generated videos.
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A mask for video generation.
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Enum for the mask mode of a video generation mask.
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A reference image for video generation.
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Enum for the reference type of a video generation reference image.
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Provides metadata for a video, including the start and end offsets for clipping and the frame rate.
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Voice activity signal.
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None
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The type of the voice activity signal.
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The configuration for the voice to use.
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Configuration for webhook notifications.
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Standard web search for grounding and related configurations.
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Configuration for a white space chunking algorithm.