remote::chromadb

Description

Chroma is an inline and remote vector database provider for Llama Stack. It allows you to store and query vectors directly within a Chroma database. That means you’re not limited to storing vectors in memory or in a separate service.

Features

Chroma supports:

  • Store embeddings and their metadata

  • Vector search

  • Full-text search

  • Document storage

  • Metadata filtering

  • Multi-modal retrieval

Usage

To use Chrome in your Llama Stack project, follow these steps:

  1. Install the necessary dependencies.

  2. Configure your Llama Stack project to use chroma.

  3. Start storing and querying vectors.

Installation

You can install chroma using pip:

pip install chromadb

Documentation

See Chroma’s documentation for more details about Chroma in general.

Configuration

Field

Type

Required

Default

Description

url

str | None

No

kvstore

utils.kvstore.config.RedisKVStoreConfig | utils.kvstore.config.SqliteKVStoreConfig | utils.kvstore.config.PostgresKVStoreConfig | utils.kvstore.config.MongoDBKVStoreConfig

No

sqlite

Config for KV store backend

Sample Configuration

url: ${env.CHROMADB_URL}
kvstore:
  type: sqlite
  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/chroma_remote_registry.db