Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

AI-powered Dropbox search tool for private documents

Roy: A lightweight, model-agnostic framework for crafting advanced multi-agent systems using large language models.

Approximate Nearest Neighbor search using reduced-rank regression, with extremely fast queries, tiny memory usage, and rapid indexing on modern vector embeddings.

Vector Index Benchmark for Embeddings (VIBE) is an extensible benchmark for approximate nearest neighbor search methods, or vector indexes, using modern embedding datasets.

A Rust binding for the VSAG -- vector indexing and search library.

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

A lightweight, in-memory vector index for approximate nearest-neighbor (ANN) search

Streamlit app for a Blender Helper Bot using a pre-built TiDB vector store

Semantic Desktop Search - search for answers not the file names

Simple, High Quality, RAG application using TiDB vector store

A prototype for visualizing and exploring vector document indexes

Semantic Hybrid Search with Sentence-Transformers + FAISS. Ask any question in plain English. Get the most relevant Wikipedia passages back — ranked by meaning, not just keywords.