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starforge-core

Client for StarForge. You get the sf command and a Python package named starforge.

Use this to scaffold a lab, lock a post-training method, and submit jobs to a StarForge console. The control plane is not on PyPI: it ships as a container image and a Helm chart. Training images do not need this whole package; the server injects a runner that carries the kernel only.

Install

uv tool install starforge-core
# or, without uv
pip install starforge-core

sf --help

uv tool install is recommended: it gives sf its own environment, and it is the installation sf update can upgrade. Installed into a system Python, sf update refuses rather than risk disturbing other tools there.

Upgrade with sf update — it detects how sf was installed and runs the right command, or names the one you should run when upgrading in place would break something.

Python 3.12 or newer. Import name is starforge, not starforge_core.

uv tool install "starforge-core[data]" adds HuggingFace datasets for local prepare scripts.

Start a lab

Do not clone the platform repo. This package writes a project for you:

sf init my-lab --yes
cd my-lab
sf login --server https://<your-console>
sf new my-grpo --method nemo-rl/grpo
sf validate my-grpo
sf submit my-grpo --profile h200:8
sf job logs

sf methods lists the catalog on the server you logged into. Methods look like nemo-rl/grpo, verl/sft, trl/kto, openrlhf/ppo, evalkit/benchmark, custom/custom.

Examples live in starforge-tutorial. Day-to-day work should be your own sf init tree.

Python

Catalog methods already forward framework logs. Custom train.sh jobs that want console curves call:

from starforge.report import init, log, finish

init()
log({"loss": 0.12}, step=1)
finish()

starforge.spec_to_env is the JobSpec to environment mapping used on both the client and the job. starforge.get_recipe / starforge.recipe_names read the bundled catalog.

What this package contains

  • sf CLI: init, login, experiments, submit, sweep, jobs, datasets, plugins, bench, serve
  • JobSpec types and spec_to_env
  • Recipe catalog and framework adapters (NeMo-RL, verl, TRL, OpenRLHF, evalkit, custom)
  • Job-side reporter (starforge.report)

Cluster credentials stay on the server. Your laptop keeps an access token under ~/.forge/.

Docs and source

Metadata

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