vector-database

Examples of my tutorial on how to use Neo4j for empowering AI RAG systems

Object storage for the AI age

Deploy production-ready AI services in minutes. One YAML file for agents, RAG pipelines, and MCP servers — run anywhere. Inspired by docker-compose.

RAG boilerplate with semantic/propositional chunking, hybrid search (BM25 + dense), LLM reranking, query enhancement agents, CrewAI orchestration, Qdrant vector search, Redis/Mongo sessioning, Celery ingestion pipeline, Gradio UI, and an evaluation suite (Hit-Rate, MRR, hybrid configs).

Official repository of the kANNolo library.

AI-powered platform for OSINT intelligence analysis. Features archive discovery with hypothesis-driven investigation, GLiNER entity extraction, Mapbox geospatial visualization, network analysis, and document processing. Built with FastAPI, Next.js, Weaviate, and DSPy.

ChronoMind: Redefining Vector Intelligence Through Time.

Predictive memory layer for AI agents. MongoDB + Qdrant + Neo4j with multi-tier caching, custom schema support & GraphQL. 91% Stanford STARK accuracy, <100ms on-device retrieval

Three examples of recommendation system pipelines with NVIDIA Merlin and Redis

完整的RAG技术教程 - 从基础概念到生产部署，系统化掌握检索增强生成技术。包含4个模块、20章内容、17个Jupyter Notebooks、6个企业级实战案例

Research framework that quantifies how steganographic obfuscation of embeddings defeats off-the-shelf statistical detection in RAG pipelines, paired with the VectorPin cryptographic-provenance defense

The repo has been moved to https://github.com/VectorDB-NTU/RaBitQ-Library. [SIGMOD 2025] Practical and Asymptotically Optimal Quantization of High-Dimensional Vectors in Euclidean Space for Approximate Nearest Neighbor Search

An Amazon S3 service implementation based on Netty.

Sentence Transformers API: An OpenAI compatible embedding API server

High level library for batched embeddings generation, blazingly-fast web-based RAG and quantized indexes processing ⚡

Pinecone.io Golang Client

This project aims to introduce and demonstrate the practical applications of RAG using Python code in a Jupyter Notebook environment.

The official Pinecone marketplace for Claude Code Plugins

Fast search engine on object storage, with full text search, vectors, and SQL, natively on Parquet.

Cloud-native vector similarity search and storage with efficient, serverless scale-out