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# 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.
