Struct ModelService 

pub struct ModelService { /* private fields */ }

Implements a client for the Vertex AI Search for commerce API.

Example

let client = ModelService::builder().build().await?;
// use `client` to make requests to the Vertex AI Search for commerce API.

Service Description

Service for performing CRUD operations on models. Recommendation models contain all the metadata necessary to generate a set of models for the Predict() API. A model is queried indirectly via a ServingConfig, which associates a model with a given Placement (e.g. Frequently Bought Together on Home Page).

This service allows you to do the following:

• Initiate training of a model.
• Pause training of an existing model.
• List all the available models along with their metadata.
• Control their tuning schedule.

Configuration

To configure ModelService use the with_* methods in the type returned by builder(). The default configuration should work for most applications. Common configuration changes include

• with_endpoint(): by default this client uses the global default endpoint (https://retail.googleapis.com). Applications using regional endpoints or running in restricted networks (e.g. a network configured override this default.
• with_credentials(): by default this client uses Application Default Credentials. Applications using custom authentication may need to override this default.

Pooling and Cloning

ModelService holds a connection pool internally, it is advised to create one and the reuse it. You do not need to wrap ModelService in an Rc or Arc to reuse it, because it already uses an Arc internally.

Implementations

impl ModelService

pub fn builder() -> ClientBuilder

Returns a builder for ModelService.

let client = ModelService::builder().build().await?;

pub fn from_stub<T>(stub: T) -> Self

where T: ModelService + 'static,

Creates a new client from the provided stub.

The most common case for calling this function is in tests mocking the client’s behavior.

pub fn create_model(&self) -> CreateModel

Creates a new model.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

pub fn get_model(&self) -> GetModel

Gets a model.

pub fn pause_model(&self) -> PauseModel

Pauses the training of an existing model.

pub fn resume_model(&self) -> ResumeModel

Resumes the training of an existing model.

pub fn delete_model(&self) -> DeleteModel

Deletes an existing model.

pub fn list_models(&self) -> ListModels

Lists all the models linked to this event store.

pub fn update_model(&self) -> UpdateModel

Update of model metadata. Only fields that currently can be updated are: filtering_option and periodic_tuning_state. If other values are provided, this API method ignores them.

pub fn tune_model(&self) -> TuneModel

Tunes an existing model.

Long running operations

This method is used to start, and/or poll a long-running Operation. The Working with long-running operations chapter in the user guide covers these operations in detail.

pub fn list_operations(&self) -> ListOperations

Provides the Operations service functionality in this service.

pub fn get_operation(&self) -> GetOperation

Provides the Operations service functionality in this service.

Trait Implementations

impl Clone for ModelService

fn clone(&self) -> ModelService

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ModelService

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.