Ferramentas de desenvolvimento
pentest-ai-agents
AI subagents that turn Claude Code into an authorized penetration-testing assistant.
★ 2,3 mil estrelasMIT
Ver o guia →backend.ai é um projeto de ferramentas de desenvolvimento de código aberto de lablup (lablup/backend.ai no GitHub). Tem 674 estrelas no GitHub e 185 forks, é publicado sob a licença LGPL-3.0 e foi atualizado pela última vez no GitHub em 4 de outubro de 2026.
Backend.AI is a streamlined, container-based computing cluster platform.
Decide what you want backend.ai to do first — backend.AI is a streamlined, container-based computing cluster platfor.
Change the config to match your workflow, then run it daily.
Pull the latest changes to stay current with fixes.
The README documents setup; start with the install section.
Programmatic access to its features.
Working backendai support built in.
Working cloud computing support built in.
Working containers support built in.
Readable code that is easy to modify.
Free to use; library linking stays open.
Download the source and move into the project folder.
git clone https://github.com/lablup/backend.ai.git
cd backend-aiInstall the Python dependencies from the project.
pip install -r requirements.txtLaunch with the project entry point — check the README for the exact command.
python main.py # see README for the exact entry pointYes, but note the copyleft: it is LGPL-3.0 licensed, so distributed derivatives must stay open.
No. It is a self-run project — clone it and run it on your own machine. Some features may optionally call external APIs; check the README.
Yes, that is the point. The code is public, so you can run, modify, and host it yourself.
It is released under LGPL-3.0. Read the LICENSE file in the repo for the exact terms.
The repo shows activity as of 2026-10-04. Check the commit history and open issues on GitHub to judge how active maintenance is right now.
AI subagents that turn Claude Code into an authorized penetration-testing assistant.
Open source, self-hosted AI code review. Bring your own LLM.
Prompt-as-code for enterprises — version, audit and deploy AI instructions.
Open, event-based protocol that connects AI agents to user-facing apps with streaming and shared state.
rmcp: the official Rust SDK for the Model Context Protocol — tokio-based servers and clients
Google's cross-platform framework for on-device ML perception: vision, text and audio pipelines
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Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.