AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
Small HTTP services as JavaScript modules, with a database, files, jobs and realtime included. Deployed by your agents, on Zeroko Cloud or your own machine.
Developer toolsTypeScript · CSSGitHub @zeroko-ioOnlineOwner unconfirmed
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The open source panel for a Zeroko runner: services, deployments, logs, data and tokens, and the skill your agents read to deploy. Self-hosted next to the runner.
Taken from the repository README
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Read the full README ↗The open source panel of Zeroko: a web app to manage one runner, and the skill agents read to deploy services on it. Self-hosted next to the runner.
cp .env.example .env # set the token and the password
docker compose up -d # then put a reverse proxy with TLS in front
Or in one container, the panel with the runner inside (panel:latest-aio):
cp .env.aio.example .env # set the password
docker compose -f docker-compose-aio.yml up -d
The docs are at zeroko.space/docs: installing, the panel, the runner and the API. What changed is in the changelog.
Run a runner, then put its token in .env.local
(ZEROKO_TOKEN, ZEROKO_PANEL_PASSWORD, ZEROKO_RUNNER_URL):
npm install
npm run dev # the panel at http://localhost:3000
npm run typecheck && npm run lint && npm run build
MIT licensed.