vector-search

ruvnet/ruflo

A meta-harness evolving Claude Flow's multi-agent swarm tooling — Ruflo is an agent meta-harness for Claude Code and Codex, tracing its lineage to the original Claude Flow project. It adds adaptive memory, self-learning behavior, federation, and vector RAG support, installable as Claude Code plugins for developers building multi-agent swarms and conversational AI systems.

milvus-io/milvus

A scalable vector database built to back LLM and RAG pipelines — Milvus is a cloud-native vector database written in Go and C++ for large-scale ANN search across text, image, and multi-modal embeddings. It supports multiple index types like HNSW and DiskANN, and suits teams building LLM, RAG, or similarity-search applications needing distributed, production-grade scale.

Tencent/WeKnora

Tencent's Go-based platform turns documents into RAG, agents and wikis — WeKnora is a Tencent open-source framework that converts raw documents into a queryable knowledge base, combining RAG retrieval, an autonomous reasoning agent, and a self-updating wiki. It ships with Chrome extension and WeChat Dialog integrations, aimed at teams building Q&A chatbots and internal knowledge tools.

seaweedfs/seaweedfs

One Go binary unifying S3, POSIX, and Iceberg lakehouse storage — SeaweedFS combines an S3 object store, a POSIX file system, and a lakehouse with S3 Tables in a single 'weed' binary over shared data. It targets billions of files with O(1) disk access, horizontal scaling via extra volume servers, and transparent tiering to cloud storage.

qdrant/qdrant

Rust-built vector search engine for production AI workloads — Qdrant is a Rust-based vector database with extended filtering support, built for semantic search, recommendations, and neural-network matching at scale. It offers a production-ready API and a managed cloud option, aimed at developers building AI apps that need fast, reliable similarity search under heavy load.

onyx-dot-app/onyx

A self-hosted context layer that connects LLMs to your team's apps — Onyx indexes knowledge from 50+ applications and exposes it to any LLM, aiming to act as an AI coworker rather than a generic chatbot. It runs self-hosted for data control and adds features like web search, sandboxes, and skills on top of RAG search. Useful for enterprise teams wanting an internal knowledge/search layer without vendor lock-in.

TencentCloud/TencentDB-Agent-Memory

A shared, governed memory hub that lets whole agent teams remember — This TypeScript project turns chats, docs, and code into four reusable memory types—Chat Memory, Skill, LLM-Wiki, Code-Graph—shared across agents and frameworks like Claude Code. It installs as a local-first service stack (memory-core, memory-hub, proxy) in one command, suiting teams building multi-agent setups needing persistent, governed long-term memory.

xerj-org/xerj

A single Rust binary that gives AI coding agents real search — XERJ indexes code, docs, logs and PDFs locally for BM25, vector and hybrid search behind an Elasticsearch-compatible API. Its reference-coding feature lets agents like Claude Code or Cursor find and reuse solutions from similar open-source repos instead of re-reading files, cutting output tokens by up to 2.7x in testing.

RyanCodrai/turbovec

TurboQuant-based vector index that beats FAISS on speed and size — turbovec compresses embeddings to 2-4 bits using Google Research's TurboQuant and searches the compressed form with SIMD kernels, claiming 4.4x FAISS FastScan speed and up to 15.5x smaller memory at matching recall. No training or rebuild step is needed, making it suited for RAG and agent systems needing online, in-process ANN search from Python or Rust.

neuml/txtai

A Single Framework Combining Vector Search, Graphs and LLM Agents — txtai bundles vector indexes, graph networks and relational databases into one embeddings database that powers semantic search, RAG and multi-model workflows. Rather than stitching together separate vector DB, graph and LLM tools, developers get a unified foundation for building autonomous agents and search-driven AI applications in Python.

yoanbernabeu/grepai

Semantic Search & Call Graphs for AI Agents (100% Local)

kividbio/kividb

A Rust-built Redis alternative that claims 9x the throughput — KiviDB is a multi-threaded, Redis-protocol-compatible server written in Rust with built-in full-text and vector search. Its benchmarks claim 21M pipelined GETs/sec on 32 cores—about 9x Redis 8 and 2.3x Dragonfly, with lower p99 latency. Useful for teams wanting a drop-in Redis/Valkey replacement with search features baked in.