Struct google_api_proto::google::ai::generativelanguage::v1::generative_service_client::GenerativeServiceClient

pub struct GenerativeServiceClient<T> { /* private fields */ }

API for using Large Models that generate multimodal content and have additional capabilities beyond text generation.

Implementations

impl<T> GenerativeServiceClient<T>

where T: GrpcService<BoxBody>, T::Error: Into<StdError>, T::ResponseBody: Body<Data = Bytes> + Send + 'static, <T::ResponseBody as Body>::Error: Into<StdError> + Send,

pub fn new(inner: T) -> Self

pub fn with_origin(inner: T, origin: Uri) -> Self

pub fn with_interceptor<F>( inner: T, interceptor: F, ) -> GenerativeServiceClient<InterceptedService<T, F>>

where F: Interceptor, T::ResponseBody: Default, T: Service<Request<BoxBody>, Response = Response<<T as GrpcService<BoxBody>>::ResponseBody>>, <T as Service<Request<BoxBody>>>::Error: Into<StdError> + Send + Sync,

pub fn send_compressed(self, encoding: CompressionEncoding) -> Self

Compress requests with the given encoding.

This requires the server to support it otherwise it might respond with an error.

pub fn accept_compressed(self, encoding: CompressionEncoding) -> Self

Enable decompressing responses.

pub fn max_decoding_message_size(self, limit: usize) -> Self

Limits the maximum size of a decoded message.

Default: 4MB

pub fn max_encoding_message_size(self, limit: usize) -> Self

Limits the maximum size of an encoded message.

Default: usize::MAX

pub async fn generate_content( &mut self, request: impl IntoRequest<GenerateContentRequest>, ) -> Result<Response<GenerateContentResponse>, Status>

Generates a model response given an input GenerateContentRequest. Refer to the text generation guide for detailed usage information. Input capabilities differ between models, including tuned models. Refer to the model guide and tuning guide for details.

pub async fn stream_generate_content( &mut self, request: impl IntoRequest<GenerateContentRequest>, ) -> Result<Response<Streaming<GenerateContentResponse>>, Status>

Generates a streamed response from the model given an input GenerateContentRequest.

pub async fn embed_content( &mut self, request: impl IntoRequest<EmbedContentRequest>, ) -> Result<Response<EmbedContentResponse>, Status>

Generates a text embedding vector from the input Content using the specified Gemini Embedding model.

pub async fn batch_embed_contents( &mut self, request: impl IntoRequest<BatchEmbedContentsRequest>, ) -> Result<Response<BatchEmbedContentsResponse>, Status>

Generates multiple embedding vectors from the input Content which consists of a batch of strings represented as EmbedContentRequest objects.

pub async fn count_tokens( &mut self, request: impl IntoRequest<CountTokensRequest>, ) -> Result<Response<CountTokensResponse>, Status>

Runs a model’s tokenizer on input Content and returns the token count. Refer to the tokens guide to learn more about tokens.

Trait Implementations

impl<T: Clone> Clone for GenerativeServiceClient<T>

fn clone(&self) -> GenerativeServiceClient<T>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T: Debug> Debug for GenerativeServiceClient<T>

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

Formats the value using the given formatter.