Chroma plugin

The Chroma plugin provides indexer and retriever implementations that use the Chroma vector database in client/server mode.

Installation

npm install genkitx-chromadb

Configuration

To use this plugin, specify it when you initialize Genkit:

import { genkit } from 'genkit';
import { chroma } from 'genkitx-chromadb';

const ai = genkit({
  plugins: [
    chroma([
      {
        collectionName: 'bob_collection',
        embedder: textEmbedding004,
      },
    ]),
  ],
});

You must specify a Chroma collection and the embedding model you want to use. In addition, there are two optional parameters:

• clientParams: If you’re not running your Chroma server on the same machine as your Genkit flow, you need to specify auth options, or you’re otherwise not running a default Chroma server configuration, you can specify a Chroma ChromaClientParams object to pass to the Chroma client:

  clientParams: {
    path: "http://192.168.10.42:8000",
  }

• embedderOptions: Use this parameter to pass options to the embedder:

  embedderOptions: { taskType: 'RETRIEVAL_DOCUMENT' },

Usage

Import retriever and indexer references like so:

import { chromaRetrieverRef } from 'genkitx-chromadb';
import { chromaIndexerRef } from 'genkitx-chromadb';

Then, use the references with ai.retrieve() and ai.index():

// To use the index you configured when you loaded the plugin:
let docs = await ai.retrieve({ retriever: chromaRetrieverRef, query });

// To specify an index:
export const bobFactsRetriever = chromaRetrieverRef({
  collectionName: 'bob-facts',
});
docs = await ai.retrieve({ retriever: bobFactsRetriever, query });

// To use the index you configured when you loaded the plugin:
await ai.index({ indexer: chromaIndexerRef, documents });

// To specify an index:
export const bobFactsIndexer = chromaIndexerRef({
  collectionName: 'bob-facts',
});
await ai.index({ indexer: bobFactsIndexer, documents });

See the Retrieval-augmented generation page for a general discussion on indexers and retrievers.