mirror of https://github.com/meta-llama/llama-stack.git synced 2025-07-04 13:15:24 +00:00

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

1.3 KiB

Raw Blame History

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:

Install the necessary dependencies.
Configure your Llama Stack project to use Faiss.
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

1.3 KiB Raw Blame History