Struct EmbeddingsBuilder 

#[non_exhaustive]
pub struct EmbeddingsBuilder<M, T>
where
    M: EmbeddingModel,
    T: Embed,
{ /* private fields */ }

Builder for creating embeddings from one or more documents of type T. Note: T can be any type that implements the Embed trait.

Using the builder is preferred over using EmbeddingModel::embed_text directly as it will batch the documents in a single request to the model provider.

Example

use rig_core::{
    client::{EmbeddingsClient, ProviderClient},
    embeddings::EmbeddingsBuilder,
    providers::openai,
};

// Create OpenAI client
let openai_client = openai::Client::from_env()?;

let model = openai_client.embedding_model(openai::TEXT_EMBEDDING_3_SMALL);

let embeddings = EmbeddingsBuilder::new(model.clone())
    .documents(vec![
        "1. *flurbo* (noun): A green alien that lives on cold planets.".to_string(),
        "2. *flurbo* (noun): A fictional digital currency.".to_string(),
        "1. *glarb-glarb* (noun): An ancient tool used by the ancestors of the inhabitants of planet Jiro to farm the land.".to_string(),
        "2. *glarb-glarb* (noun): A fictional creature from marshlands.".to_string(),
        "1. *linlingdong* (noun): A term used by inhabitants of the sombrero galaxy to describe humans.".to_string(),
        "2. *linlingdong* (noun): A rare instrument.".to_string(),
    ])?
    .build()
    .await?;

Implementations

impl<M, T> EmbeddingsBuilder<M, T>

where M: EmbeddingModel, T: Embed,

pub fn new(model: M) -> EmbeddingsBuilder<M, T>

Create a new embedding builder with the given embedding model

pub fn document( self, document: T, ) -> Result<EmbeddingsBuilder<M, T>, EmbedError>

Add a document to be embedded to the builder. document must implement the Embed trait.

pub fn documents( self, documents: impl IntoIterator<Item = T>, ) -> Result<EmbeddingsBuilder<M, T>, EmbedError>

Add multiple documents to be embedded to the builder. documents must be iterable with items that implement the Embed trait.

impl<M, T> EmbeddingsBuilder<M, T>

where M: EmbeddingModel, T: Embed + Send,

pub async fn build( self, ) -> Result<Vec<(T, OneOrMany<Embedding>)>, EmbeddingError>

Generate embeddings for all documents in the builder.

Returns (document, embeddings) pairs. A document may produce one or many embeddings depending on how its Embed implementation uses TextEmbedder.

pub async fn build_with_usage( self, ) -> Result<(Vec<(T, OneOrMany<Embedding>)>, Usage), EmbeddingError>

Generate embeddings for all documents in the builder and return accumulated token usage.

Returns (document, embeddings) pairs and the total token usage across all batches. A document may produce one or many embeddings depending on how its Embed implementation uses TextEmbedder.