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For development (CPU)
Build and test a client on any machine, with no GPU. The CPU stand-in serves every route of decisio from a small model.
Start it from a clone of the release, on any machine.
git clone --branch v0.18.1 https://github.com/aminry/decisiocd decisiouv sync --extra dev --frozenuv run python -m decisio.serve.vllm_engine --backend hf --model Qwen/Qwen3-0.6B-BaseRun against the CPU stand-in at v0.18.1 on 2026-10-19: the clone is the pinned release, as the check has it; the install and the server start.
1. What you get
Section titled “1. What you get”- Every route the real server has, so a client, a task registration and its tests run against it unchanged.
- Answers from
Qwen/Qwen3-0.6B-Base, a small model for development; they are not decisio’s measured answers. - A server that is ready 4 to 8 seconds after it starts, once the model is downloaded, and answers a first question in about 0.3 seconds on top (on Apple silicon, 2026-10-14).
The first start downloads the model, about 1.2 GB, once.
2. Send it a request
Section titled “2. Send it a request”It is ready when /health answers:
curl -s http://127.0.0.1:8000/healthRun against the CPU stand-in at v0.18.1 on 2026-10-19. It printed, trimmed to the fields this page uses:
{
"ok": true,
"base": "qwen3.6-35b-a3b"
}
The request from Get started works as it is; only the numbers in the answer differ. Call it from your code has the same request from Python, JavaScript and TypeScript.
3. Teach it a task
Section titled “3. Teach it a task”The walk-through of Teach a task runs on the stand-in, end to end: register a task, ask it, list it and remove it. The site checks every one of its commands this way.
What next
Section titled “What next”- On a cloud GPU: serve the default model, Gemma 4 31B, for real answers.
- On a Mac or a laptop: run a real model on Apple silicon or with Ollama.
- Call it from your code: the same request from your language.