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Chroma

Chroma is an open-source Apache 2.0 embedding database.

Setup​

  1. Run chroma with Docker on your computer docs
  2. Install the Chroma JS SDK.
npm install -S chromadb

Usage, Index and query Documents​

import { Chroma } from "langchain/vectorstores/chroma";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";
import { TextLoader } from "langchain/document_loaders/fs/text";

// Create docs with a loader
const loader = new TextLoader("src/document_loaders/example_data/example.txt");
const docs = await loader.load();

// Create vector store and index the docs
const vectorStore = await Chroma.fromDocuments(docs, new OpenAIEmbeddings(), {
  collectionName: "a-test-collection",
});

// Search for the most similar document
const response = await vectorStore.similaritySearch("hello", 1);

console.log(response);
/*
[
  Document {
    pageContent: 'Foo\nBar\nBaz\n\n',
    metadata: { source: 'src/document_loaders/example_data/example.txt' }
  }
]
*/

API Reference:

Usage, Index and query texts​

import { Chroma } from "langchain/vectorstores/chroma";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";

// text sample from Godel, Escher, Bach
const vectorStore = await Chroma.fromTexts(
  [
    `Tortoise: Labyrinth? Labyrinth? Could it Are we in the notorious Little
        Harmonic Labyrinth of the dreaded Majotaur?`,
    "Achilles: Yiikes! What is that?",
    `Tortoise: They say-although I person never believed it myself-that an I
        Majotaur has created a tiny labyrinth sits in a pit in the middle of
        it, waiting innocent victims to get lost in its fears complexity.
        Then, when they wander and dazed into the center, he laughs and
        laughs at them-so hard, that he laughs them to death!`,
    "Achilles: Oh, no!",
    "Tortoise: But it's only a myth. Courage, Achilles.",
  ],
  [{ id: 2 }, { id: 1 }, { id: 3 }],
  new OpenAIEmbeddings(),
  {
    collectionName: "godel-escher-bach",
  }
);

const response = await vectorStore.similaritySearch("scared", 2);

console.log(response);
/*
[
  Document { pageContent: 'Achilles: Oh, no!', metadata: {} },
  Document {
    pageContent: 'Achilles: Yiikes! What is that?',
    metadata: { id: 1 }
  }
]
*/

// You can also filter by metadata
const filteredResponse = await vectorStore.similaritySearch("scared", 2, {
  id: 1,
});

console.log(filteredResponse);
/*
[
  Document {
    pageContent: 'Achilles: Yiikes! What is that?',
    metadata: { id: 1 }
  }
]
*/

API Reference:

Usage, Query docs from existing collection​

import { Chroma } from "langchain/vectorstores/chroma";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";

const vectorStore = await Chroma.fromExistingCollection(
  new OpenAIEmbeddings(),
  { collectionName: "godel-escher-bach" }
);

const response = await vectorStore.similaritySearch("scared", 2);
console.log(response);
/*
[
  Document { pageContent: 'Achilles: Oh, no!', metadata: {} },
  Document {
    pageContent: 'Achilles: Yiikes! What is that?',
    metadata: { id: 1 }
  }
]
*/

API Reference: