ИИ-агенты
weaviate
Vector search plus structured filtering in one database.
★ 16,9 тыс. звёздNOASSERTION
Смотреть руководство →milvus — проект с открытым исходным кодом из категории «ИИ-агенты» от milvus-io (milvus-io/milvus на GitHub). У него 46 337 звёзд на GitHub и 4 282 форка, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 8 октября 2026.
The cloud-native vector database for planet-scale similarity search.
Write down the job you will use the project for before touching any code.
Download the source and read the README's setup section first.
Run the install steps and add any required API keys or config.
Follow the example in the docs to confirm everything works.
Built to scale horizontally across clusters.
Approximate nearest neighbor search over huge vector sets.
Designed for containerized, elastic deployments.
Purpose-built for embedding similarity workloads.
Efficient, concurrency-friendly core.
Permissive open-source licensing.
Download the source and move into the project folder.
git clone https://github.com/milvus-io/milvus.git
cd milvusCompile the Go services.
go build ./...Milvus is typically run via Docker or Kubernetes — follow the official deployment guide.
# see the deployment docs for the supported install pathsIt is maintained by the milvus-io organization at milvus-io/milvus, with 4,282 forks. Check the release notes for the current stable version.
Yes. It is released under the Apache-2.0 license, which permits commercial use, modification, and redistribution. Read the LICENSE file for the exact terms.
Self-hosted Milvus is free; a managed cloud offering also exists if you prefer not to operate it yourself.
Compare with Qdrant, Weaviate, or Chroma on scale, operational burden, and filtering needs.
Read the deployment docs, start with the Docker-based quickstart, and load a small embedding set first.
Vector search plus structured filtering in one database.
A high-performance vector search engine for next-gen AI.
Deep research that stays on your machine — local or cloud LLMs, 10+ search engines, encrypted and private.
AI-native search that indexes code, docs, and PDFs with 40x fewer tokens than grep.
MCP server, CLI and skills for searching and downloading academic papers from arXiv, PubMed and 20+ sources
Simple desktop AI assistant with knowledge bases, agents, and web search.
Другие проекты из категории «ИИ-агенты» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если milvus вам не подходит.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Соседние проекты из категории «ИИ-агенты» в каталоге, ближайшие по числу звёзд к milvus — продолжайте изучать полку по обе стороны от него.
An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间，让人与智能体在此协作
High-performance code intelligence MCP server: your codebase as a persistent knowledge graph
Agent memory that learns — so your agents get smarter over time.
A one-of-a-kind resume builder that keeps your privacy in mind. Completely secure, customizable, portable, open-source and free forever. Try it out today!
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat…
A fast browser-automation CLI built for AI agents.
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.