forked from phoenix-oss/llama-stack-mirror
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# 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  - SQLite-Vec specific page  ## Test Plan N/A [//]: # (## Documentation) --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
33 lines
814 B
Markdown
33 lines
814 B
Markdown
---
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orphan: true
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---
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# Faiss
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[Faiss](https://github.com/facebookresearch/faiss) is an inline vector database provider for Llama Stack. It
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allows you to store and query vectors directly in memory.
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That means you'll get fast and efficient vector retrieval.
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## Features
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- Lightweight and easy to use
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- Fully integrated with Llama Stack
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- GPU support
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## Usage
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To use Faiss in your Llama Stack project, follow these steps:
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1. Install the necessary dependencies.
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2. Configure your Llama Stack project to use Faiss.
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3. Start storing and querying vectors.
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## Installation
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You can install Faiss using pip:
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```bash
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pip install faiss-cpu
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```
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## Documentation
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See [Faiss' documentation](https://faiss.ai/) or the [Faiss Wiki](https://github.com/facebookresearch/faiss/wiki) for
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more details about Faiss in general.
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