SEC.01

The playbook

The run starts read-only: the recon probes decide what happens next. The steps that follow are adapted to the distribution and state found — a real machine is rarely clean.

1. 01recondistro, version and package manager (apt or dnf)
2. 02reconDocker Engine + compose plugin present and running? (otherwise, docker step)
3. 03reconOpen WebUI already deployed (container, volume)? healthy → verify and skip
4. 04recondoes Ollama respond on 127.0.0.1:11434 (expected backend)?
5. 05reconport 3000 free?
6. 06reconRAM ≥ 2 GB and ≥ 10 GB of free disk (large image)
7. 07actInstall Docker Engine + Compose (only if missing)verify
8. 08actStart Open WebUIverify
9. 09actResponds over HTTPverify

SEC.02

What it verifies

Each step ships its own check. The run only moves on when the check passes, so what the recipe reports as done is what is actually on the server.

1. 01verifyInstall Docker Engine + Compose (only if missing)Verified bysystemctl is-active docker && docker compose version
2. 02verifyStart Open WebUIVerified bydocker inspect -f '{{.State.Status}}' open-webui
3. 03verifyResponds over HTTPVerified bytimeout 240 bash -c 'until curl -sf -o /dev/null http://127.0.0.1:3000/health; do sleep 5; done'; curl -s -o /dev/null -w '%{http_code}' http://127.0.0.1:3000/health

SEC.03

Guardrails

Non-negotiable instructions the run must respect, whatever it finds on the server.

SEC.04

How a recipe runs in Servor

Servor is zero-knowledge: the platform cannot execute anything on its own. When you launch this recipe, a run reads the reconnaissance, plans the steps and asks for your approval. Each approved command is signed by your browser — with a key the server never sees — then relayed verbatim to the agent, which verifies the signature locally before executing.

SEC.05

Deploy on Servor button

Maintain Open WebUI or a project that needs it? Put this button in your README or on your site: one click and your users install it on their own server.

SEC.06

More ai / ml recipes

1. 01OllamaOllama to run local LLMs (NVIDIA GPU if present, CPU otherwise), API on 127.0.0.1, optional model pull.
2. 02JupyterLabJupyterLab via Docker, on 127.0.0.1 with a generated access token (access through an SSH tunnel).
3. 03NVIDIA drivers + CUDANVIDIA driver, CUDA toolkit and Docker Container Toolkit from the official repositories. Destructive: kernel modules, restart likely.
4. 04ComfyUI (Stable Diffusion)ComfyUI for image generation, installed from the official repository as a systemd service (NVIDIA GPU recommended, CPU possible).
5. 05vLLM inference servervLLM to serve an LLM through an OpenAI-compatible API on 127.0.0.1, protected by a generated key. NVIDIA GPU required.