LlamaIndex Readers Integration: Weaviate

Overview

The Weaviate Reader retrieves documents from Weaviate through vector lookup. It allows you to specify a class name and properties to retrieve from documents, or to provide a custom GraphQL query. You can choose to receive separate Document objects per document or concatenate retrieved documents into one Document.

Installation

You can install the Weaviate Reader via pip:

pip install llama-index-readers-weaviate

Usage

from llama_index.readers.weaviate import WeaviateReader

# Initialize WeaviateReader with host and optional authentication
reader = WeaviateReader(
    host="<Weaviate Host>", auth_client_secret="<Authentication Client Secret>"
)

# Load data from Weaviate
documents = reader.load_data(
    class_name="<Class Name>", properties=["property 1", "property 2"]
)

You can follow this tutorial to learn more on how to use Weaviate Reader

This loader is designed to be used as a way to load data into LlamaIndex and/or subsequently used as a Tool in a LangChain Agent.