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llama-stack-mirror/docs/source/providers/vector_io/remote_weaviate.md
Sébastien Han c9a49a80e8
docs: auto generated documentation for providers (#2543) 
# What does this PR do?

Simple approach to get some provider pages in the docs.

Add or update description fields in the provider configuration class
using Pydantic’s Field, ensuring these descriptions are clear and
complete, as they will be used to auto-generate provider documentation
via ./scripts/distro_codegen.py instead of editing the docs manually.

Signed-off-by: Sébastien Han <seb@redhat.com>
2025-06-30 15:13:20 +02:00

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remote::weaviate

Description

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.

Sample Configuration

{}