Développement
toon
TOON: a compact, human-readable serialization of JSON that saves tokens in LLM prompts
★ 25,5 k étoilesMIT
Voir le guide →headroom est un projet de développement open source, créé par headroomlabs-ai (headroomlabs-ai/headroom sur GitHub). Il compte 74 736 étoiles sur GitHub et 5 785 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.
Compress tool outputs, logs and RAG chunks before they reach the LLM — same answers, fewer tokens
Decide what you want from headroom and check the README and requirements to confirm it fits your setup and Python environment.
Clone the repository from GitHub (github.com/headroomlabs-ai/headroom) or use the documented install channel if you do not need the source.
Follow the README quickstart to install dependencies and set any required configuration or credentials.
Work through the README's first example end to end, then adapt it to your own project or data.
Compresses tool outputs, logs, files and RAG chunks before they enter the context window.
The project reports 60-95% fewer tokens for JSON payloads while keeping answers the same.
Usable as a Python/TypeScript library, a proxy, or an MCP server.
Works with coding agents such as Claude Code and Cursor and frameworks like LangChain.
`headroom learn` adapts compression to your workload, per the README.
The proxy is built on FastAPI for easy self-hosting.
Start by getting the source and entering the project directory.
git clone https://github.com/headroomlabs-ai/headroom.git
cd headroomThe README recommends a uv tool install for the CLI, or pip for the Python package.
pip install "headroom-ai[all]"Start the proxy or MCP server and point your agent at it, per the 60-second get-started guide.
headroom # see README for the exact commandIt is maintained by headroomlabs-ai and contributors on GitHub, where the repository github.com/headroomlabs-ai/headroom is the canonical home for code, issues and releases.
Yes — it is open source under the Apache-2.0 license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.
No key of its own — it sits in front of your existing LLM provider, which still uses your own key.
Compared with manual context pruning: Headroom compresses content automatically as a proxy or MCP server instead of developers hand-trimming every payload.
Clone github.com/headroomlabs-ai/headroom, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.
TOON: a compact, human-readable serialization of JSON that saves tokens in LLM prompts
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.