Tag: #hybrid-search
17 packages • ⭐ 51,911 total stars
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a c
SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and
Endee.io – A high-performance vector database, designed to handle up to 1B vectors on a single node, delivering significant performance gains through optimized indexing and execution. Also available i
Official Repo of Moss
Local-first RAG server for developers. Semantic + keyword search for code and technical docs. Works with MCP or CLI. Fully private, zero setup.
Production-ready RAG Framework (Python/FastAPI). 1-line config swaps: 6 Vector DBs (Weaviate, Pinecone, Qdrant, ChromaDB, pgvector, MongoDB), 5 LLMs (Gemini, OpenAI, Claude, Ollama, OpenRouter). OpenA
On-device context engine and memory for AI agents. Claude Code, Hermes and OpenClaw. Hooks + MCP server + hybrid RAG search.
Website for the Weaviate vector database
Your Very Own Agent: The Ultimate, Complete Edition
The memory system your AI agent deserves. 4-stage hybrid retrieval — Vector + BM25 + Knowledge Graph + Neural Reranker — in <150ms. Self-hosted, $0/query, built for agents that need to actually rememb
Local-first Agentic Memory Layer for MCP Agents • 25 tools • Hybrid search (FTS5 + vector + MMR) • GDPR • 100% local
🧠 Store and search your notes effectively with Git-native memory storage, enhancing productivity for Claude Code users.
Deploy a local, multi-user RAG system to query PDF and DOCX documents using a local LLM without cloud or API dependencies.
🤖 Implement hybrid human-AI orchestration patterns in Python to coordinate agents, manage sessions, and enable smooth AI-human handoffs.
🚀 Build memory and retrieval infrastructure for ReasonKit, enhancing data management and access for your applications with ease and efficiency.