Struct Client

pub struct Client { /* private fields */ }

Implementations

impl Client

pub fn new( auth: impl Into<AzureOpenAIAuth>, api_version: &str, azure_endpoint: &str, ) -> Self

Creates a new Azure OpenAI client.

Arguments

• auth - Azure OpenAI API key or token required for authentication
• api_version - API version to use (e.g., “2024-10-21” for GA, “2024-10-01-preview” for preview)
• azure_endpoint - Azure OpenAI endpoint URL, for example: https://{your-resource-name}.openai.azure.com

pub fn from_api_key( api_key: &str, api_version: &str, azure_endpoint: &str, ) -> Self

Creates a new Azure OpenAI client from an API key.

Arguments

• api_key - Azure OpenAI API key required for authentication
• api_version - API version to use (e.g., “2024-10-21” for GA, “2024-10-01-preview” for preview)
• azure_endpoint - Azure OpenAI endpoint URL

pub fn from_token(token: &str, api_version: &str, azure_endpoint: &str) -> Self

Creates a new Azure OpenAI client from a token.

Arguments

• token - Azure OpenAI token required for authentication
• api_version - API version to use (e.g., “2024-10-21” for GA, “2024-10-01-preview” for preview)
• azure_endpoint - Azure OpenAI endpoint URL

pub fn from_env() -> Self

Create a new Azure OpenAI client from the AZURE_API_KEY or AZURE_TOKEN, AZURE_API_VERSION, and AZURE_ENDPOINT environment variables.

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

Example

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

// Initialize the Azure OpenAI client
let azure = Client::new("YOUR_API_KEY", "YOUR_API_VERSION", "YOUR_ENDPOINT");

let embedding_model = azure.embedding_model(azure::TEXT_EMBEDDING_3_LARGE);

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

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

Example

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

// Initialize the Azure OpenAI client
let azure = Client::new("YOUR_API_KEY", "YOUR_API_VERSION", "YOUR_ENDPOINT");

let embedding_model = azure.embedding_model("model-unknown-to-rig", 3072);

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

Create an embedding builder with the given embedding model.

Example

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

// Initialize the Azure OpenAI client
let azure = Client::new("YOUR_API_KEY", "YOUR_API_VERSION", "YOUR_ENDPOINT");

let embeddings = azure.embeddings(azure::TEXT_EMBEDDING_3_LARGE)
    .simple_document("doc0", "Hello, world!")
    .simple_document("doc1", "Goodbye, world!")
    .build()
    .await
    .expect("Failed to embed documents");

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

Create a completion model with the given name.

Example

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

// Initialize the Azure OpenAI client
let azure = Client::new("YOUR_API_KEY", "YOUR_API_VERSION", "YOUR_ENDPOINT");

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

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

Create a transcription model with the given name.

Example

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

// Initialize the Azure OpenAI client
let azure = Client::new("YOUR_API_KEY", "YOUR_API_VERSION", "YOUR_ENDPOINT");

let whisper = azure.transcription_model("model-unknown-to-rig");

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

Create an agent builder with the given completion model.

Example

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

// Initialize the Azure OpenAI client
let azure = Client::new("YOUR_API_KEY", "YOUR_API_VERSION", "YOUR_ENDPOINT");

let agent = azure.agent(azure::GPT_4)
   .preamble("You are comedian AI with a mission to make people laugh.")
   .temperature(0.0)
   .build();

pub fn extractor<T: JsonSchema + for<'a> Deserialize<'a> + Serialize + Send + Sync>( &self, model: &str, ) -> ExtractorBuilder<T, CompletionModel>

Create an extractor builder with the given completion model.

Trait Implementations

impl Clone for Client

fn clone(&self) -> Client

Returns a copy of the value.

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

Performs copy-assignment from source.