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Dart Client for the Chroma open-source embedding database API.

Chroma Dart Client #

tests chromadb MIT

Dart client for Chroma embedding database.

Features #

  • Create, list, get, modify and delete collections.
  • Add, upsert, get, update, query, count, peek and delete items.
  • Get version and heartbeat.
  • Reset database.

Usage #

Note: this is a quick overview of the client. For full API docs, see the official documentation.

Run the server #

Run docker-compose up -d --build to run a backend in Docker on your local
computer.

Initialize client #

final client = ChromaClient();

By default, the client expect the server to be running on http://localhost:8000. You can change this by passing the host parameter.

Methods on Client #

Collections are similar to AWS s3 buckets in their naming requirements because they are used in URLs in the REST API. Here's the full list.

// list all collections
await client.listCollections();

// make a new collection
final collection = await client.createCollection(name: 'testname');

// get an existing collection
final collection = await client.getCollection(name: 'testname');

// delete a collection
await client.deleteCollection(name: 'testname');

Utilities methods

// get Chroma version
final version = await client.version();

// get Chroma heartbeat
final heartbeat = await client.heartbeat();

// resets entire database - this *cant* be undone!
await client.reset();

Methods on Collection #

// get the number of items in a collection
await collection.count();

// add new items to a collection
// either one at a time
await collection.add(
  ids: ['id1'],
  embeddings: [[1.5, 2.9, 3.4]],
  metadatas: [{'source': 'my_source'}],
);

// or many, up to 100k+!
await collection.add(
  ids: ['uri9', 'uri10'],
  embeddings: [[1.5, 2.9, 3.4], [9.8, 2.3, 2.9]],
  metadatas: [{'style': 'style1'}, {'style': 'style2'}],
);

// including just documents 
// (you need to provide an EmbeddingFunction to the collection to be able
// to embed documents) 
await collection.add(
  ids: ['uri9', 'uri10'],
  documents: ['doc1000101', 'doc288822'],
  metadatas: [{'style': 'style1'}, {'style': 'style2'}],
);

// or use upsert, so records will be updated if they already exist
// (instead of throwing an error)
await collection.upsert(
  ids: ['id1'],
  embeddings: [[1.5, 2.9, 3.4]],
  metadatas: [{'source': 'my_source'}],
  documents: ['This is a document'],
);

// get items from a collection
final res = await collection.get();

// convenience, get first 5 items from a collection
await collection.peek();

// do nearest neighbor search to find similar embeddings or documents, supports filtering
await collection.query(
  queryEmbeddings: [[1.1, 2.3, 3.2], [5.1, 4.3, 2.2]],
  nResults: 2,
  where: {'style': 'style2'},
);

// delete items
await collection.delete();

License #

Chroma Dart Client is licensed under the MIT License.

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Publisher

verified publisherlangchaindart.dev

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Dart Client for the Chroma open-source embedding database API.

Homepage
Repository (GitHub)
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Topics

#ai #nlp #vector-db

Documentation

Documentation

License

unknown (license)

Dependencies

freezed_annotation, http, json_annotation, meta

More

Packages that depend on chromadb