vector-search

Vector search demo with the arXiv paper dataset, RedisVL, HuggingFace, OpenAI, Cohere, FastAPI, React, and Redis.

Fast similarity search using DuckDB

Open-source document chat platform with semantic search, RAG (Retrieval Augmented Generation), and multi-provider AI support (OpenRouter, OpenAI, ImageRouter).

A low-latency, billion-scale, and updatable graph-based vector store on SSD.

A curated list of open source repositories for AI Engineers

Official repository of the Seismic library.

A Vector Store written in Go - Supports hybrid retrieval over BM25, Flat, HNSW, IVF, PQ and IVFPQ Index with Quantization, Metadata Filtering, Reranking, Reciprocal Rank Fusion, Soft Deletes, Index Rebuilds and much much more

A complete collection of RAG interview questions, answers (548 questions & 41 RAG types), system design scenarios, architecture patterns, and production-ready concepts.

Timescale Vector Cookbook. A collection of recipes to build applications with LLMs using PostgreSQL and Timescale Vector.

The documentation for SurrealDB, powered by Astro

Advanced document extraction and chunking techniques for retrieval augmented generation that is aware of the layout of documents. Increases knowledge retrieval accuracy and provides control for retrieved knowledge context management

A Python CLI to test, benchmark, and find the best RAG chunking strategy for your Markdown documents.

Shared memory MCP server — persistent, searchable, cross-client Claude, Opencode

This repository is home to all the Jupyter Notebooks required for MongoDB's GenAI Developer Day.

Engineering deterministic, production-grade systems around non-deterministic LLMs — FSM, durable execution, retries, DAGs, agent runtimes, model routing, edge inference, RAG, memory, multi-agent orchestration, security, and observability. 14 runnable proof-of-concept phases.

Local AI-powered document search and editing with first-in-class hybrid retrieval, LLM answers, WebUI, REST API and MCP support for AI clients.

Self-hosted RAG platform for AI document search across GitHub, Notion, Google Drive, local files, and web sources with citations.

Self-hosted RAG search engine — 34 formats, BM25+hybrid search, multi-LLM (Gemini/OpenAI/Claude/Ollama), FastAPI + Docker, production-ready in 3 min

Local code search combining BM25, vector similarity, and cross-encoder reranking. Parses 60+ languages with tree-sitter, runs entirely offline, and returns structured results with file paths, line ranges, and symbol metadata. Built in Rust.

Go implementation of @qdrant/fastembed.