forked from phoenix-oss/llama-stack-mirror
19ae4b35d9
# 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
942 B
Markdown
33 lines
942 B
Markdown
---
|
|
orphan: true
|
|
---
|
|
# Weaviate
|
|
|
|
[Weaviate](https://weaviate.io/) is a vector database provider for Llama Stack.
|
|
It allows you to store and query vectors directly within a Weaviate database.
|
|
That means you're not limited to storing vectors in memory or in a separate service.
|
|
|
|
## Features
|
|
Weaviate supports:
|
|
- Store embeddings and their metadata
|
|
- Vector search
|
|
- Full-text search
|
|
- Hybrid search
|
|
- Document storage
|
|
- Metadata filtering
|
|
- Multi-modal retrieval
|
|
|
|
## Usage
|
|
|
|
To use Weaviate 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
|
|
|
|
To install Weaviate see the [Weaviate quickstart documentation](https://weaviate.io/developers/weaviate/quickstart).
|
|
|
|
## Documentation
|
|
See [Weaviate's documentation](https://weaviate.io/developers/weaviate) for more details about Weaviate in general.
|