@chroma-core/voyageai v0.1.7

Voyage AI Embedding Function for Chroma

This package provides a Voyage AI embedding provider for Chroma.

Installation

npm install @chroma-core/voyageai

Usage

import { ChromaClient } from 'chromadb';
import { VoyageAIEmbeddingFunction } from '@chroma-core/voyageai';

// Initialize the embedder
const embedder = new VoyageAIEmbeddingFunction({
  apiKey: 'your-api-key', // Or set VOYAGE_API_KEY env var
  modelName: 'voyage-2',
});

// Create a new ChromaClient
const client = new ChromaClient({
  path: 'http://localhost:8000',
});

// Create a collection with the embedder
const collection = await client.createCollection({
  name: 'my-collection',
  embeddingFunction: embedder,
});

// Add documents
await collection.add({
  ids: ["1", "2", "3"],
  documents: ["Document 1", "Document 2", "Document 3"],
});

// Query documents
const results = await collection.query({
  queryTexts: ["Sample query"],
  nResults: 2,
});

Configuration

Set your Voyage AI API key as an environment variable:

export VOYAGE_API_KEY=your-api-key

Get your API key from Voyage AI.

Configuration Options

• apiKey: Your Voyage AI API key (or set via environment variable)
• apiKeyEnvVar: Environment variable name for API key (default: VOYAGE_API_KEY)
• modelName: Model to use for embeddings (required)

Supported Models

Voyage AI offers high-quality embedding models:

• voyage-2 - Latest and most capable model
• voyage-large-2 - Larger model for maximum performance
• voyage-code-2 - Optimized for code and technical content
• voyage-lite-02-instruct - Lightweight instruction-following model

Check the Voyage AI documentation for the complete list of available models and their specifications.

Features

• State-of-the-Art Quality: High-performance embedding models optimized for retrieval
• Domain-Specific Models: Specialized models for code, legal, and other domains
• Efficient: Competitive pricing and fast inference times