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.
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