@chroma-core/huggingface-server
v0.1.8
Published
Huggingface Server embedding provider for Chroma
Readme
Hugging Face Server Embedding Function for Chroma
This package provides a Hugging Face Inference Server embedding provider for Chroma.
Installation
npm install @chroma-core/huggingface-serverUsage
import { ChromaClient } from 'chromadb';
import { HuggingfaceServerEmbeddingFunction } from '@chroma-core/huggingface-server';
// Initialize the embedder
const embedder = new HuggingfaceServerEmbeddingFunction({
url: 'https://your-inference-server.com/embed', // Your inference server endpoint
apiKey: 'your-api-key', // Optional, for authenticated servers
// Or use environment variable
apiKeyEnvVar: 'HF_API_KEY',
});
// 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
For authenticated servers, set your API key as an environment variable:
export HF_API_KEY=your-api-keyConfiguration Options
- url: URL of your Hugging Face inference server endpoint (required)
- apiKey: API key for authenticated servers (optional)
- apiKeyEnvVar: Environment variable name for API key (default:
HF_API_KEY)
Use Cases
This embedding function is ideal for:
- Self-hosted Models: Connect to your own Hugging Face Inference Server
- Custom Endpoints: Use specialized embedding models deployed on your infrastructure
- Enterprise Deployments: Maintain data privacy with on-premises inference servers
- Hugging Face Inference Endpoints: Connect to paid Hugging Face Inference Endpoints
Server Requirements
Your Hugging Face inference server should:
- Accept POST requests with JSON payload containing text inputs
- Return embeddings as arrays of numbers
- Follow the standard Hugging Face Inference API format
For more information on setting up a Hugging Face Inference Server, see the Hugging Face documentation.
