hyperDB

HyperDB

A hyper-fast local vector database for use with LLM Agents. Not entirely a joke.

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Advantages

• Simple interface compatible with all large language model agents.
• Highly optimized C++ backend vector store with HW accelerated operations via MKL BLAS.
• Enables users to index documents with advanced features such as ids and metadata.

Installation

Install the package from PyPI:

pip install hyperdb-python

Optional dependency for locally embedding

If you want to use Hugging Face models with this package, you need to install the sentence-transformers package:

pip install sentence-transformers

Usage

Here's an example of using HyperDB to store and query documents with information about all 151 original pokemon in an instant:

import json
from hyperdb import HyperDB

# Load documents from the JSONL file
documents = []

with open("demo/pokemon.jsonl", "r") as f:
    for line in f:
        documents.append(json.loads(line))

# Instantiate HyperDB with the list of documents
db = HyperDB(documents, key="info.description")

# Save the HyperDB instance to a file
db.save("demo/pokemon_hyperdb.pickle.gz")

# Load the HyperDB instance from the save file
db.load("demo/pokemon_hyperdb.pickle.gz")

# Query the HyperDB instance with a text input
results = db.query("Likes to sleep.", top_k=5)

Returns

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*Benchmark Credit: Benim Kıçım