HyperDB is a high-performance, local vector database designed for seamless integration with Large Language Model (LLM) agents. It offers a simplified interface for indexing documents with metadata and querying them using natural language, aiming to accelerate LLM agent development.

How It Works

HyperDB leverages a C++ backend for its vector store, incorporating hardware acceleration via MKL BLAS for optimized operations. This approach prioritizes speed and efficiency in indexing and retrieval, making it suitable for real-time agent interactions. The database supports advanced features like document IDs and metadata, enhancing the context available to LLM agents.

Quick Start & Requirements

• Install via pip: pip install hyperdb-python
• Optional dependency for local embedding: pip install sentence-transformers
• Example usage and demo files are available in the repository.

Highlighted Details

• Optimized C++ backend with MKL BLAS hardware acceleration.
• Simple interface compatible with various LLM agents.
• Supports indexing documents with IDs and metadata.
• Benchmarked for high performance.

Maintenance & Community

The project is actively seeking investment and has a Discord server for community engagement.

Licensing & Compatibility

The licensing details are not explicitly stated in the README, but the project is open-source.

Limitations & Caveats

The project is presented with a humorous tone regarding investment, and its stability or production readiness for critical applications may require further evaluation. The README does not specify the exact license.