Install & setup¶
Prerequisites¶
- git on your
PATH— the CLI shells out to git to snapshot and push your code. git ≥ 2.38 is recommended (the control node needs it for clean experiment merges). - Python 3.11+ — for the CLI itself. The installer bootstraps
uvto manage it. - Your project's own toolchain (PyTorch, CUDA,
uv/pip, …) on whatever machine runs the experiments. The CLI is dependency-light and stays out of the way.
Install¶
The installer bootstraps uv (a single static binary — no system Python needed)
and installs the slim autolab CLI as an isolated uv tool. Verify:
autolab: command not found?
The CLI installs to uv's tool bin. If your shell can't find it yet, add it to
your PATH:
Install with uv directly
The installer just runs uv tool install autolab, so if you already have uv:
Sign in¶
autolab login # opens a browser, stores a token for this host
autolab whoami # show the active host and signed-in user
Tokens are stored per host in ~/.config/autolab/credentials.json (owner-only,
mode 0600), so a local-dev login and a production login can coexist. To sign in
without a browser — on a remote or CI box — pass a token:
See Tokens & API keys for minting and revoking tokens.
Choosing a control node¶
By default the CLI talks to https://app.autolab.ai. Override the host when
you need to — for local development or a self-hosted control node:
autolab --url http://localhost:8080 status # one-off
export AUTOLAB_URL=http://localhost:8080 # whole shell
Or define named profiles in ~/.config/autolab/config.toml:
default_profile = "prod"
[profiles.prod]
url = "https://app.autolab.ai"
[profiles.local]
url = "http://localhost:8080"
Resolution order is --url → AUTOLAB_URL → active profile → https://app.autolab.ai.
Full details in Configuration & environment.
Update & uninstall¶
Next: the Quickstart, or Core concepts to understand the model before you dive in.