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AI 에이전트를 만들고 클라우드에서 실행합니다
저장소와 레퍼런스, 목적을 지정하면 됩니다
Give it a repository, a ref and a purpose. It builds a disposable LXC on your Proxmox host, starts a Claude Code agent inside it, and streams the whole thing to your browser.
개발 도구TypeScript · CSSGitHub @ndom91온라인운영자 미확인
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아직 감지된 업데이트가 없습니다. GitHub 릴리스가 나오면 여기에 보입니다.
개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
로그인한 뒤 확인 파일을 만들어 이 저장소의 기본 브랜치에 30분 안에 커밋해 주세요. 다른 브랜치나 포크의 파일은 인정하지 않습니다. 파일을 올린 뒤 아래에서 확인하면 관리자 승인 없이 관리할 수 있습니다. 자격을 유지하려면 파일을 남겨 두세요.
로그인이 필요하면 로그인 화면으로 이동합니다. 로그인 후 이곳으로 돌아와 원하는 확인 버튼을 다시 눌러 주세요.
프로젝트 폴더에서 /nomorevibe verify를 실행하면 소유권을 확인하고 소개를 직접 관리할 수 있습니다.
1분 만에 확인하기Disposable coding agents on your own Proxmox host
README 전체를 불러오는 중입니다.
README 전문 보기 ↗Disposable coding agents on your own Proxmox host.
Give it a repository, a ref, and a purpose. It clones a golden template, boots an LXC, checks the repository out, starts your selected agent inside it and hands it the purpose. The web UI streams that agent's transcript, takes prompts, answers its permission dialogs, shows what it changed, and pushes or discards the result. When a workspace has outlived its usefulness the controller destroys it — unless it is holding work nobody kept.
The controller owns the lifecycle, the policy and the UI. Proxmox owns the containers. Your agent owns the actual work.
pve-agents/<hostname> or
discard the lot.ghostty-web, for the
things a transcript cannot do.pnpm install
cp .env.example .env
pnpm dev # http://127.0.0.1:3000
State lands in ./data/controller.db. CONTROLLER_HOST and CONTROLLER_PORT move the listener.
Nothing touches Proxmox until you ask it to. PROVISIONING_ENABLED is off by default, and with
it off a request queues a durable operation and builds nothing. That is the intended way to try the
UI, the API and the whole state machine without a hypervisor anywhere near it.
To go past the queue and build real containers:
deploy/build-workspace-template.shCopy .env.example to .env. Thirty variables, of which these decide whether anything happens:
CONTROLLER_AUTH_SECRET | Turns authentication on. Unset means the controller answers anyone who can reach it. Set it. |
PROVISIONING_ENABLED | Gates every Proxmox write. Off by default. |
PROXMOX_* | URL, token, node, pool, template VMID, bridge, VMID floor. |
GITHUB_APP_* | Id, installation id and key path. How the controller clones and pushes. Distinct from GITHUB_CLIENT_*, which is only how you sign in. |
WORKSPACE_CLAUDE_OAUTH_TOKEN | From claude setup-token. Without it a workspace builds and the agent step fails. |
WORKER_ENABLED | Runs the operation worker in the server process. Off by default, so the first clone and destroy can be stepped by hand with pnpm worker:tick. |
docs/production-runbook.md has the rest.
./bin/deploy.sh # deploy
./bin/deploy.sh --dry-run # show what would be sent and removed, change nothing
Not by hand. The controller's checkout is an rsync target rather than a git clone, and several steps fail silently when skipped — the runbook says which.
Destruction is the only path that loses something irreversibly, so it is the one with the most said about it.
pve-agents.sh is the full documentation: setup, concepts, operations, reference and troubleshooting, with search. Start at Proxmox setup to get from a bare hypervisor to a template you can clone.
AGENTS.md | Start here to work on the code. Conventions, and the rules this codebase learned the hard way. |
docs/architecture.md | The system as built, including where an earlier intention was abandoned and why. |
docs/http-api.md | The HTTP API, for scripting the controller. |
docs/seed-files.md | Files every workspace is built with, and how MCP servers reach one. |
docs/production-runbook.md | Deploying and operating it. |
docs/proxmox-lifecycle.md | Clone, boot, address, destroy, and reconcile. |
docs/security-and-networking.md | Network shape, credentials, and what is deliberately not trusted. |
pnpm check && pnpm typecheck && pnpm test && pnpm build
None of those load a page. After anything touching routing or SSR, open the site and look at it.
This project was developed with significant assistance from LLMs. Architecture decisions, implementation and documentation were all shaped through human-AI collaboration.