Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai

MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW

Lightweight Nearest Neighbors with Flexible Backends

⚡ A fast embedded library for approximate nearest neighbor search

HNSW tutorial

(distributed) vector database

S3 vector database for LLM Agents and RAG.

facenet recognition and retrieve by using hnswlib and flask, convert tensorflow model to caffe

TiDB AI SDK: Unified Multi-Modal Data Platform for AI Apps & Agents - https://pingcap.github.io/ai/

A specialized implementation of the Hierarchical Navigable Small World (HNSW) data structure adapted for efficient nearest neighbor lookup of approximate matching hashes

High-performance database management system

LangChain integration for ZeusDB, a high-performance Rust-powered vector database with lightning-fast search, metadata-aware filtering, and scalable RAG pipelines.

The thesis presents the parallelisation of a state-of-the art clustering algorithm, FISHDBC. This objective has been achived by improving the main data structures and components of the algorithm: HNSW, MST and HDBSCAN. My contribution is based on a lock-free strategy, completely wrote in Python.

KNN Search Algorithm Comparison – This project compares the performance of different K-Nearest Neighbors (KNN) search algorithms across various dataset sizes and dimensions.

Optimized RAG Retrieval with Indexing, Quantization, Hybrid Search and Caching

ZeusDB vector database integration for LlamaIndex. Connect LlamaIndex's RAG framework with enterprise-grade vector database capabilities.

This is a lightweight reverse image search engine built on TinyCLIP and HNSWlib, designed for low-spec and resource-constrained environments.

Local in-memory vector database

Easily manage MongoDB Atlas vector search with LangChain using OpenAI or HuggingFace embeddings.

Comparison of IVFFlat and HNSW Algorithms