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llama-stack-mirror/docs/source/providers/vector_io/inline_chromadb.md
Sébastien Han c9a49a80e8
docs: auto generated documentation for providers (#2543) 
# What does this PR do?

Simple approach to get some provider pages in the docs.

Add or update description fields in the provider configuration class
using Pydantic’s Field, ensuring these descriptions are clear and
complete, as they will be used to auto-generate provider documentation
via ./scripts/distro_codegen.py instead of editing the docs manually.

Signed-off-by: Sébastien Han <seb@redhat.com>
2025-06-30 15:13:20 +02:00

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inline::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
db_path <class 'str'> No PydanticUndefined

Sample Configuration

db_path: ${env.CHROMADB_PATH}