LlamaIndex Readers Integration: Metal
Overview
Metal Reader is designed to load data from the Metal Vector store, which provides search functionality based on query embeddings and filters. It retrieves documents from the Metal index associated with the provided API key, client ID, and index ID.
Installation
You can install Metal Reader via pip:
pip install llama-index-readers-metal
To use Metal Reader, you must have a vector store first. Follow this to create a metal vector store, Setup Metal Vector Store
Usage
from llama_index.readers.metal import MetalReader
# Initialize MetalReader
reader = MetalReader(
api_key="<Metal API Key>",
client_id="<Metal Client ID>",
index_id="<Metal Index ID>",
)
# Load data from Metal
documents = reader.load_data(
limit=10, # Number of results to return
query_embedding=[0.1, 0.2, 0.3], # Query embedding for search
filters={"field": "value"}, # Filters to apply to the search
separate_documents=True, # Whether to return separate documents
)
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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