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. 01reconDocker present?
2. 02reconAlready deployed?
3. 03actStart JupyterLabverify
4. 04actGet the tokenverify

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. 01verifyStart JupyterLabVerified bydocker ps --filter name=jupyter --format "{{.Status}}" | grep -c Up
2. 02verifyGet the tokenVerified bydocker logs jupyter 2>&1 | grep -c "token="

SEC.03

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.04

More ai / ml recipes

1. 01OllamaOllama to run local LLMs (optional model pull).
2. 02Open WebUIOpen WebUI, a web interface for LLMs (Ollama) via Docker.
3. 03NVIDIA drivers + CUDANVIDIA drivers and CUDA toolkit. Destructive: kernel modules, reboot likely.
4. 04ComfyUI (Stable Diffusion)ComfyUI for image generation via Docker (GPU recommended).
5. 05vLLM inference servervLLM to serve an LLM through an OpenAI-compatible API. GPU required.