llama-stack-mirror/docs/source/providers/vector_io/faiss.md
Francisco Arceo 19ae4b35d9
docs: Adding Provider sections to docs (#1195)
# What does this PR do?
Adding Provider sections to docs (some of these will be empty and need
updating).


This PR is still a draft while I seek feedback from other contributors.
I opened it to make the structure visible in the linked GitHub Issue.

# Closes https://github.com/meta-llama/llama-stack/issues/1189

- Providers Overview Page
![Screenshot 2025-02-21 at 12 15
09 PM](https://github.com/user-attachments/assets/e83e5a17-0d96-4de0-8251-68161799a054)

- SQLite-Vec specific page
![Screenshot 2025-02-21 at 12 15
34 PM](https://github.com/user-attachments/assets/14773900-fc8f-49e9-832a-b060b7ca010a)

## Test Plan
N/A

[//]: # (## Documentation)

---------

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
2025-02-22 11:59:34 -08:00

814 B

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Faiss

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.