VoyageAI

Chroma also provides a convenient wrapper around VoyageAI’s embedding API. This embedding function runs remotely on VoyageAI’s servers, and requires an API key. You can get an API key by signing up for an account at VoyageAI.

Python
TypeScript

This embedding function relies on the voyageai python package, which you can install with pip install voyageai.

import chromadb.utils.embedding_functions as embedding_functions
voyageai_ef  = embedding_functions.VoyageAIEmbeddingFunction(api_key="YOUR_API_KEY",  model_name="voyage-3-large")
voyageai_ef(input=["document1","document2"])

// npm install @chroma-core/voyageai

import { VoyageAIEmbeddingFunction } from "@chroma-core/voyageai";

const embedder = new VoyageAIEmbeddingFunction({
    apiKey: "apiKey",
    modelName: "model_name",
});

// use directly
const embeddings = embedder.generate(["document1", "document2"]);

// pass documents to query for .add and .query
const collection = await client.createCollection({
    name: "name",
    embeddingFunction: embedder,
});
const collectionGet = await client.getCollection({
    name: "name",
    embeddingFunction: embedder,
});

Multilingual model example

voyageai_ef  = embedding_functions.VoyageAIEmbeddingFunction(
    api_key="YOUR_API_KEY",
    model_name="voyage-3-large"
)

multilingual_texts  = [
    'Hello from VoyageAI!', 'مرحباً من VoyageAI!!',
    'Hallo von VoyageAI!', 'Bonjour de VoyageAI!',
    '¡Hola desde VoyageAI!', 'Olá do VoyageAI!',
    'Ciao da VoyageAI!', '您好，来自 VoyageAI！',
    'कोहिअर से VoyageAI!'
]

voyageai_ef(input=multilingual_texts)

For further details on VoyageAI’s models check the documentation and the blogs.

Dense Embedding Models

Sparse Embedding Models

Frameworks

Multilingual model example

Dense Embedding Models

Sparse Embedding Models

Frameworks

​Multilingual model example

Multilingual model example