ИИ-агенты
AppFlowy
Bring projects, wikis, and teams together with AI. AppFlowy is the AI collaborative workspace where you achieve more without losing control of your data. The…
★ 77,1 тыс. звёздAGPL-3.0
Смотреть руководство →koog — проект с открытым исходным кодом из категории «ИИ-агенты» от JetBrains (JetBrains/koog на GitHub). У него 4 600 звёзд на GitHub и 483 форка, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 2 октября 2026.
Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend service…
Research, coding, browsing, or ops — agents work best with a clear goal.
From no-code builders to code-first SDKs, match complexity to the task.
Web search, code execution, and APIs are what make agents useful.
Watch the trace, approve consequential actions, iterate.
Traces show exactly what the agent did and why.
Approval gates for actions that matter.
Long-term memory across sessions, not goldfish chat.
Specialized agents collaborate on bigger jobs.
Agents call real tools: browsers, terminals, APIs.
Benchmarks keep agent quality measurable.
Download the source and move into the project folder.
git clone https://github.com/JetBrains/koog.git
cd koogEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at JetBrains/koog with 483 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Apache 2.0 licensed — commercial use allowed with attribution.
Sandboxing, approval gates, and least-privilege credentials.
Builders exist, but code-first frameworks go further.
Model API bills dominate; self-hosted stacks cut that sharply.
Bring projects, wikis, and teams together with AI. AppFlowy is the AI collaborative workspace where you achieve more without losing control of your data. The…
Make humans and AI agents work as one team — open-source and self-hostable.
An agentic skills framework & software development methodology that works.
Uber's ADR: discover, observe, benchmark, and detect threats across enterprise AI agents, deployed at Uber.
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and…
A visual all-in-one platform for building, debugging, and deploying AI agents.
Другие проекты из категории «ИИ-агенты» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если koog 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 koog — продолжайте изучать полку по обе стороны от него.
Deep Research with any LLM: in-depth reports in minutes, with an SSE API and MCP server built in
Microsoft's open framework for red-teaming generative AI systems.
Rivet is Ironclad's visual IDE and TypeScript library for building complex AI agents and prompt chains
Convene 18 legendary thinkers as an AI council that debates your hardest questions — inside Claude Code
A team workspace for building AI agents together.
LongMemory: local-first memory for AI agents with temporal truth, provenance, and hybrid recall
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.