Struct OpenAiEmbeddingProvider 

pub struct OpenAiEmbeddingProvider { /* private fields */ }

Embedding provider backed by the OpenAI embeddings API.

Stores the API key, model, and dimension configuration. Calling [embed()] performs a real HTTP request when the http-embeddings feature is enabled. Without the feature, it returns an error. For local/offline embeddings, use LocalEmbedding.

Implementations

impl OpenAiEmbeddingProvider

pub fn new(api_key: impl Into<String>, model: Option<String>) -> Self

Create a new OpenAI embedding provider.

model defaults to "text-embedding-3-small" when None.

pub fn with_base_url( api_key: impl Into<String>, model: Option<String>, base_url: impl Into<String>, ) -> Self

Create with a custom base URL (e.g. Azure OpenAI endpoint).

pub fn with_dimensions(self, dimensions: usize) -> Self

Override the output dimension count.

pub fn model(&self) -> &str

Returns the model name this provider is configured with.

Trait Implementations

impl EmbeddingProvider for OpenAiEmbeddingProvider

fn embed<'life0, 'life1, 'async_trait>( &'life0 self, _text: &'life1 str, ) -> Pin<Box<dyn Future<Output = ArgentorResult<Vec<f32>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait,

Compute embedding vector for a single text.

fn dimension(&self) -> usize

Dimension of the embedding vectors produced by this provider.

fn embed_batch<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, texts: &'life1 [&'life2 str], ) -> Pin<Box<dyn Future<Output = ArgentorResult<Vec<Vec<f32>>>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Compute embeddings for a batch of texts.