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llama-stack-mirror/docs/source/providers/vector_io/inline_faiss.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::faiss

Description

Faiss is an inline vector database provider for Llama Stack. It allows you to store and query vectors directly in memory. That means you'll get fast and efficient vector retrieval.

Features

  • Lightweight and easy to use
  • Fully integrated with Llama Stack
  • GPU support

Usage

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

  1. Install the necessary dependencies.
  2. Configure your Llama Stack project to use Faiss.
  3. Start storing and querying vectors.

Installation

You can install Faiss using pip:

pip install faiss-cpu

Documentation

See Faiss' documentation or the Faiss Wiki for more details about Faiss in general.

Configuration

Field Type Required Default Description
kvstore utils.kvstore.config.RedisKVStoreConfig | utils.kvstore.config.SqliteKVStoreConfig | utils.kvstore.config.PostgresKVStoreConfig | utils.kvstore.config.MongoDBKVStoreConfig No sqlite

Sample Configuration

kvstore:
  type: sqlite
  namespace: null
  db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/faiss_store.db