llama-stack-mirror/docs/source/providers/vector_io/weaviate.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

942 B

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Weaviate

Weaviate 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.

Documentation

See Weaviate's documentation for more details about Weaviate in general.