Skip to main content

llama-index readers metal integration

Project description

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llama_index_readers_metal-0.2.0.tar.gz (2.9 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file llama_index_readers_metal-0.2.0.tar.gz.

File metadata

  • Download URL: llama_index_readers_metal-0.2.0.tar.gz
  • Upload date:
  • Size: 2.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.1 CPython/3.10.13 Darwin/23.6.0

File hashes

Hashes for llama_index_readers_metal-0.2.0.tar.gz
Algorithm Hash digest
SHA256 0ed23d3d3384014925b8d3a5d4de30331eeb4fa20e68a31ef616b80c6ae5528e
MD5 b7f94891f88f74d1f7d364d31abd80f9
BLAKE2b-256 a408dbeec8e14c632a2031a5af6c679c1eb1627d9fdbfa65f3a6ee2aa704e7fa

See more details on using hashes here.

File details

Details for the file llama_index_readers_metal-0.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for llama_index_readers_metal-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a44ac35a118a948621ce799d786b58d51159faa5331ffa66e3f1082c0e3c3009
MD5 3e46389163293090ac2901d6d6ae2617
BLAKE2b-256 f70045737b3b78e7363be657d549904db3ec83240e95f24ef19a8f93f18fd33b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page