vector-database

A tool for summarizing search results and website content using FAISS, LLMs, and the Retrieval-Augmented Generation (RAG) technique.

Production-ready RAG framework for Python — multi-tenant chatbots with streaming, tool calling, agent mode (LangGraph), vector search (FAISS), and persistent MongoDB memory. Built on LangChain.

A Rust-based cursor like chat with your codebase tool.

High-Throughput, Cost-Effective Billion-Scale Vector Search with a Single GPU [SIGMOD'26]

🗄 A Rust library designed as a specialized database for AI Agents, focusing on knowledge memory.

Multi-Modal RAG for .NET — query databases, documents, images and audio in natural language. Production-ready with multi-AI support, vector storage, and multi-database coordination.

A minimalistic vector database that can be used to search for similar vectors in logarithmic time.

Rust-based retrieval system with hybrid search (vector + BM25), async ingestion, and gRPC-first API

A hex-native embedded database for Go. Morton keys, native ring scans, seams (contradictions), MVCC, provenance, and optional HNSW embeddings. Built from scratch for lattice-addressed memory.

[SIGMOD 2026] DARTH: Declarative Recall Through Early Termination for Approximate Nearest Neighbor Search.

Self-hosted multitenant platform for AI agents and Telegram bots with event-driven architecture

ContextAtlas — context infrastructure for AI coding agents: hybrid retrieval, project memory and retrieval observability via CLI, MCP server or embeddable library. Tree-sitter indexing, LanceDB vector search, FTS5 and token-aware context packing.

Absurdly fast embedded graph database with built-in vector search. Rust core, Node.js and Python connectors, GQL, graph algorithms, all in-process with no server.

OLD Resume Matcher Website (Not used anymore)

Use OpenAI, Redis, and streamlit to recommend hotels using Large Language Models

Simple, High Quality, Open Source RAG solution for chatting with your documents

A curated list of vector database solutions, libraries, and resources for AI applications - https://vectordb.ever.works

A semantic code search tool for intelligent, cross-repo context retrieval.

Embed anything.

High-performance infrastructure libraries built in Rust, with seamless bindings for Python, Node.js, and WebAssembly.