Struct Client 

pub struct Client { /* private fields */ }

Unified Gemini API client.

Mirrors the GoogleGenAI class from @google/genai (js-genai). Provides access to both Live (WebSocket) and REST APIs through a single authenticated entry point.

Construction

use gemini_genai_rs::Client;

// From API key (Google AI)
let client = Client::from_api_key("your-api-key");

// From Vertex AI credentials
let client = Client::from_vertex("project-id", "us-central1", "access-token");

// Live WebSocket session on the platform's default Live model
let session = client.live(None).connect().await?;

Implementations

impl Client

pub async fn list_batch_jobs( &self, ) -> Result<ListBatchJobsResponse, BatchesError>

List batch jobs.

pub async fn create_batch_job( &self, config: CreateBatchJobConfig, ) -> Result<BatchJob, BatchesError>

Create a batch prediction job.

pub async fn create_batch_embeddings( &self, config: CreateBatchJobConfig, ) -> Result<BatchJob, BatchesError>

Create a batch embeddings job.

pub async fn get_batch_job(&self, name: &str) -> Result<BatchJob, BatchesError>

Get a batch job by name.

pub async fn cancel_batch_job(&self, name: &str) -> Result<(), BatchesError>

Cancel a batch job by name.

pub async fn delete_batch_job(&self, name: &str) -> Result<(), BatchesError>

Delete a batch job by name.

impl Client

pub async fn list_cached_contents( &self, ) -> Result<ListCachedContentsResponse, CachesError>

List cached contents.

pub async fn create_cached_content( &self, config: CreateCachedContentConfig, ) -> Result<CachedContent, CachesError>

Create a new cached content.

pub async fn get_cached_content( &self, name: &str, ) -> Result<CachedContent, CachesError>

Get a cached content by name.

pub async fn update_cached_content( &self, name: &str, updates: UpdateCachedContentRequest, ) -> Result<CachedContent, CachesError>

Update a cached content (TTL or expiration time).

pub async fn delete_cached_content(&self, name: &str) -> Result<(), CachesError>

Delete a cached content by name.

impl Client

pub fn chat(&self) -> ChatSessionBuilder<'_>

Start a new chat session with the default model.

impl Client

pub fn from_api_key(api_key: impl Into<String>) -> Self

Create a client with Google AI API key authentication.

pub fn from_access_token(access_token: impl Into<String>) -> Self

Create a client with Google AI OAuth2 token authentication.

pub fn from_vertex( project: impl Into<String>, location: impl Into<String>, access_token: impl Into<String>, ) -> Self

Create a client with Vertex AI authentication.

pub fn from_vertex_refreshable( project: impl Into<String>, location: impl Into<String>, refresher: impl Fn() -> String + Send + Sync + 'static, ) -> Self

Create a client with Vertex AI authentication and dynamic token refresh.

The refresher closure is called on every REST API request and on every Live connection attempt (including reconnects) to obtain a fresh Bearer token. It should cache internally (see GcloudTokenProvider in gemini-adk-rs for an example).

This is the right constructor for anything that outlives a token’s ~1 h lifetime.

pub fn model(self, model: impl Into<ModelId>) -> Self

Set the default model for all API calls.

pub fn http_config(self, config: HttpConfig) -> Self

Configure the HTTP client (timeouts, retries, etc.).

pub fn auth(&self) -> &dyn AuthProvider

Get a reference to the underlying auth provider.

pub fn default_model(&self) -> &ModelId

Get the default model.

pub fn rest_url(&self, endpoint: ServiceEndpoint) -> String

Build the REST URL for a given service endpoint, using the default model.

pub fn rest_url_for(&self, endpoint: ServiceEndpoint, model: &ModelId) -> String

Build the REST URL for a given service endpoint with a specific model.

pub async fn auth_headers(&self) -> Result<Vec<(String, String)>, AuthError>

Get auth headers for REST API calls.

pub fn live(&self, model: Option<ModelId>) -> ConnectBuilder

A Live session on this client’s credentials.

None connects to the platform’s default Live model (the REST default model is a text model and would not do). Tune the session with ConnectBuilder::configure, then .connect().await.

pub fn http_client(&self) -> &HttpClient

Get a reference to the HTTP client for making REST API calls.

pub async fn rest_request( &self, endpoint: ServiceEndpoint, body: &impl Serialize, ) -> Result<Value, HttpError>

Make a raw REST API request (low-level).

Higher-level module methods (e.g., generate_content()) should be preferred.

impl Client

pub async fn embed_content( &self, text: impl Into<String>, ) -> Result<EmbedContentResponse, EmbedError>

Embed text content using the default model.

pub async fn embed_content_with( &self, config: EmbedContentConfig, model: Option<&ModelId>, ) -> Result<EmbedContentResponse, EmbedError>

Embed content with full configuration.

impl Client

pub async fn list_files(&self) -> Result<ListFilesResponse, FilesError>

List files.

pub async fn get_file(&self, name: &str) -> Result<File, FilesError>

Get a file by name.

pub async fn delete_file(&self, name: &str) -> Result<(), FilesError>

Delete a file by name.

pub async fn upload_file( &self, data: Vec<u8>, config: UploadFileConfig, ) -> Result<File, FilesError>

Upload a file from a byte buffer.

pub async fn download_file(&self, name: &str) -> Result<Vec<u8>, FilesError>

Download a file’s content by name.

pub async fn register_files( &self, sources: Vec<FileSource>, ) -> Result<Vec<File>, FilesError>

Register external files by URI (Vertex AI only).

impl Client

pub async fn generate_content( &self, prompt: impl Into<String>, ) -> Result<GenerateContentResponse, GenerateError>

Generate content from a text prompt using the default model.

pub async fn generate_content_with( &self, config: GenerateContentConfig, model: Option<&ModelId>, ) -> Result<GenerateContentResponse, GenerateError>

Generate content with full configuration and optional model override.

impl Client

pub async fn list_models(&self) -> Result<ListModelsResponse, ModelsError>

List available models.

pub async fn get_model(&self, model: &ModelId) -> Result<ModelInfo, ModelsError>

Get metadata for a specific model.

impl Client

pub async fn count_tokens( &self, text: impl Into<String>, ) -> Result<CountTokensResponse, TokensError>

Count tokens for text content.

pub async fn count_tokens_for( &self, contents: Vec<Content>, model: Option<&ModelId>, ) -> Result<CountTokensResponse, TokensError>

Count tokens for content with optional model override.

impl Client

pub async fn list_tuning_jobs( &self, ) -> Result<ListTuningJobsResponse, TuningsError>

List tuning jobs.

pub async fn get_tuning_job( &self, name: &str, ) -> Result<TuningJob, TuningsError>

Get a tuning job by name.

pub async fn create_tuning_job( &self, config: CreateTuningJobConfig, ) -> Result<TuningJob, TuningsError>

Create a new tuning job.

pub async fn cancel_tuning_job(&self, name: &str) -> Result<(), TuningsError>

Cancel a tuning job by name.