semantic-search

VortexDB - A lightweight, vector database built from scratch in Rust 🦀

Modern ChromaDB web UI for browsing collections, inspecting records, running queries, and editing documents, metadata, and embeddings

OpenClaw memory plugin backed by a self-hosted Mem0 REST API

A high-performance vector database library for Python that provides efficient storage, indexing, and search capabilities for high-dimensional vectors

A vector database for querying meaningfully similar data.

KoutenDB: locality-aware NoSQL document/vector database built around rings and orbit-inspired retrieval

Production-ready Retrieval Augmented Generation (RAG) system with hybrid retrieval, advanced evaluation metrics, and monitoring. Build enterprise LLM applications with reduced hallucinations, better context management, and comprehensive observability.

Explore cutting-edge Redis capabilities for Vector Similarity Search, Hybrid Search (Vector Similarity + Meta Search), Semantic Caching, and an advanced RAG model integrated with a Language Model (LLM) Chatbot. Unlock the full potential of Redis as a vector database with this comprehensive showcase of powerful features.

Embeddable vector database for Rust and Python. HNSW indexing, metadata filtering, hybrid search, and snapshots. The SQLite of vector search.

The in-browser vector store that remembers — a Rust→WASM HNSW engine that persists to OPFS and stays consistent across tabs. Private, offline semantic search in 3 lines.

🔒 Privacy-first MCP server for Claude using PostgreSQL + Ollama. Local alternative to cloud-based code context with full data sovereignty. No API keys, no external calls, 100% local.

A self-hosted omni-modal agentic retrieval platform that understands, searches, and explores documents, images, audio, and video through semantic routing, hybrid retrieval, adaptive agents, and traceable citations.

Local RAG app with zero-config Docker setup. FastAPI + Streamlit + Qdrant + Ollama. Just run `docker-compose up --build`! 🚀

🧠 Personal knowledge MCP server with vector database for Opencode. Store and retrieve knowledge using semantic search, powered by local embeddings.

Search on your images via text or image to image search. Uses OpenAI CLIP embedding and LanceDB

Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.

Persistent semantic memory for AI agents on Raspberry Pi 5 — local Qdrant + MCP, no cloud, ~3s per query

Harvest-first Rust toolkit for open data metadata: sync 300+ portals (CKAN, DCAT, SPARQL, data.json, Socrata, OpenDataSoft, ArcGIS, CSW, STAC ) into PostgreSQL, add optional local embeddings and semantic search. Ceres Open Data Index (2M+ datasets) on Hugging Face.

🧠 Enterprise AI-Enhanced Development Platform with GraphRAG, LlamaIndex, Multi-Tenant Architecture, and Advanced Security & Compliance. Transform your development workflow with persistent memory, intelligent automation, and 99.9% uptime.

Decentralized vector database on Bittensor — content-addressed semantic memory for AI