Package com.google.genai

Class AsyncTunings

java.lang.Object

com.google.genai.AsyncTunings

public final class AsyncTunings
extends Object

Async module of Tunings

Constructor Summary

Constructors

Constructor	Description
AsyncTunings(com.google.genai.ApiClient apiClient)

Method Summary

Modifier and Type	Method	Description
CompletableFuture<TuningJob>	get(String name, GetTuningJobConfig config)	Asynchronously makes an API request to get a tuning job.
CompletableFuture<AsyncPager<TuningJob>>	list(ListTuningJobsConfig config)	Asynchronously makes an API request to list the available tuning jobs.
CompletableFuture<TuningJob>	tune(String baseModel, TuningDataset trainingDataset, CreateTuningJobConfig config)	Asynchronously makes an API request to create a supervised fine-tuning job.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

AsyncTunings

public AsyncTunings(com.google.genai.ApiClient apiClient)

Method Details

get

public CompletableFuture<TuningJob> get(String name,
 GetTuningJobConfig config)

Asynchronously makes an API request to get a tuning job.

Parameters:

name - The resource name of the tuning job.

config - A GetTuningJobConfig for configuring the get request.

Returns:

A CompletableFuture that resolves to a TuningJob object.

list

public CompletableFuture<AsyncPager<TuningJob>> list(ListTuningJobsConfig config)

Asynchronously makes an API request to list the available tuning jobs.

Parameters:

config - A ListTuningJobsConfig for configuring the list request.

Returns:

A CompletableFuture that resolves to a AsyncPager. The AsyncPager has a `forEach` method that can be used to asynchronously process items in the page and automatically query the next page once the current page is exhausted.

tune

public CompletableFuture<TuningJob> tune(String baseModel,
 TuningDataset trainingDataset,
 CreateTuningJobConfig config)

Asynchronously makes an API request to create a supervised fine-tuning job.

This method is experimental.

Parameters:

baseModel - The base model to tune.

trainingDataset - The training dataset to use for tuning.

config - A CreateTuningJobConfig for configuring the create request.

Returns:

A CompletableFuture that resolves to a TuningJob object.