Struct Client 

pub struct Client<T = Client> { /* private fields */ }

Implementations

impl Client<Client>

pub fn builder(api_key: &str) -> ClientBuilder<'_, Client>

Create a new OpenAI client builder.

Example

use rig::providers::openai::{ClientBuilder, self};

// Initialize the OpenAI client
let openai_client = Client::builder("your-open-ai-api-key")
   .build()

pub fn new(api_key: &str) -> Self

Create a new OpenAI client. For more control, use the builder method.

pub fn from_env() -> Self

impl<T> Client<T>

where T: HttpClientExt + Clone + Debug + Default + Send + 'static,

pub fn extractor_completions_api<U>( &self, model: &str, ) -> ExtractorBuilder<CompletionModel<T>, U>

where U: JsonSchema + for<'a> Deserialize<'a> + Serialize + Send + Sync, CompletionModel<T>: CompletionModel,

Create an extractor builder with the given completion model. Intended for use exclusively with the Chat Completions API. Useful for using extractors with Chat Completion compliant APIs.

Trait Implementations

impl<T> AudioGenerationClient for Client<T>

where T: HttpClientExt + Clone + Debug + Send + Default + 'static,

Available on crate feature audio only.

fn audio_generation_model(&self, model: &str) -> Self::AudioGenerationModel

Create an audio generation model with the given name.

Example

use rig::providers::openai::{Client, self};

// Initialize the OpenAI client
let openai = Client::new("your-open-ai-api-key");

let gpt4 = openai.audio_generation_model(openai::TTS_1);

type AudioGenerationModel = AudioGenerationModel<T>

The AudioGenerationModel used by the Client

impl<T: Clone> Clone for Client<T>

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

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T> CompletionClient for Client<T>

where T: HttpClientExt + Debug + Clone + Default + Send + 'static,

fn completion_model(&self, model: &str) -> Self::CompletionModel

Create a completion model with the given name.

Example

use rig::providers::openai::{Client, self};

// Initialize the OpenAI client
let openai = Client::new("your-open-ai-api-key");

let gpt4 = openai.completion_model(openai::GPT_4);

type CompletionModel = ResponsesCompletionModel<T>

The type of CompletionModel used by the client.

fn agent(&self, model: &str) -> AgentBuilder<Self::CompletionModel>

Create an agent builder with the given completion model.

fn extractor<T>( &self, model: &str, ) -> ExtractorBuilder<Self::CompletionModel, T>

where T: JsonSchema + for<'a> Deserialize<'a> + Serialize + Send + Sync,

Create an extractor builder with the given completion model.

impl<T> Debug for Client<T>

where T: Debug,

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

Formats the value using the given formatter.

impl<T> EmbeddingsClient for Client<T>

where T: HttpClientExt + Debug + Clone + Default + Send + 'static,

type EmbeddingModel = EmbeddingModel<T>

The type of EmbeddingModel used by the Client

fn embedding_model(&self, model: &str) -> Self::EmbeddingModel

Create an embedding model with the given name. Note: default embedding dimension of 0 will be used if model is not known. If this is the case, it’s better to use function embedding_model_with_ndims

fn embedding_model_with_ndims( &self, model: &str, ndims: usize, ) -> Self::EmbeddingModel

Create an embedding model with the given name and the number of dimensions in the embedding generated by the model.

fn embeddings<D: Embed>( &self, model: &str, ) -> EmbeddingsBuilder<Self::EmbeddingModel, D>

Create an embedding builder with the given embedding model.

fn embeddings_with_ndims<D: Embed>( &self, model: &str, ndims: usize, ) -> EmbeddingsBuilder<Self::EmbeddingModel, D>

Create an embedding builder with the given name and the number of dimensions in the embedding generated by the model.

impl<T> ImageGenerationClient for Client<T>

where T: HttpClientExt + Clone + Debug + Default + Send + 'static,

Available on crate feature image only.

fn image_generation_model(&self, model: &str) -> Self::ImageGenerationModel

Create an image generation model with the given name.

Example

use rig::providers::openai::{Client, self};

// Initialize the OpenAI client
let openai = Client::new("your-open-ai-api-key");

let gpt4 = openai.image_generation_model(openai::DALL_E_3);

type ImageGenerationModel = ImageGenerationModel<T>

The ImageGenerationModel used by the Client

impl<T> ProviderClient for Client<T>

where T: HttpClientExt + Clone + Debug + Default + Send + 'static,

fn from_env() -> Self

Create a new OpenAI client from the OPENAI_API_KEY environment variable. Panics if the environment variable is not set.

fn from_val(input: ProviderValue) -> Self

fn boxed(self) -> Box<dyn ProviderClient>

where Self: Sized + 'static,

A helper method to box the client.

fn from_env_boxed<'a>() -> Box<dyn ProviderClient + 'a>

where Self: Sized + 'a,

Create a boxed client from the process’s environment. Panics if an environment is improperly configured.

fn from_val_boxed<'a>(input: ProviderValue) -> Box<dyn ProviderClient + 'a>

where Self: Sized + 'a,

Create a boxed client from the process’s environment. Panics if an environment is improperly configured.

impl<T> TranscriptionClient for Client<T>

where T: HttpClientExt + Clone + Debug + Default + Send + 'static,

fn transcription_model(&self, model: &str) -> Self::TranscriptionModel

Create a transcription model with the given name.

Example

use rig::providers::openai::{Client, self};

// Initialize the OpenAI client
let openai = Client::new("your-open-ai-api-key");

let gpt4 = openai.transcription_model(openai::WHISPER_1);

type TranscriptionModel = TranscriptionModel<T>

The type of TranscriptionModel used by the Client

impl<T> VerifyClient for Client<T>

where T: HttpClientExt + Clone + Debug + Send + Default + 'static,

async fn verify(&self) -> Result<(), VerifyError>

Verify the configuration.