ENGINEERING

Warn the engineer in Slack when a model license is non-commercial

On a PR that adds a Hugging Face model, it checks the license and, if it is non-commercial or research-only, sends the PR author a direct Slack message explaining the restriction…

CategoryEngineering
Enginesim
Difficultybeginner
Triggerevent
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPull request opened or updatedGitHubGitHub
  • ActionExtract added HF model IDs from diffGitHubGitHub
  • ActionFetch model card licenseHugging FaceHugging Face
  • LogicDetect non-commercial or research-only license
  • OutputDM the PR author in SlackSlack

What it does

Gives engineers fast, friendly feedback the moment they add a model with a usage-restricted license. Rather than a silent CI failure, the author gets a Slack DM that names the model, the exact license, why it is a problem for a commercial product, and a nudge toward compliant options.

When to use it

Use it on teams that prefer coaching over gatekeeping, where most license mistakes are honest and a quick heads-up resolves them before review. It reduces back-and-forth in PR comments and educates engineers on license policy in context.

How it works

  1. 1A GitHub pull request event starts the workflow.
  2. 2The diff is parsed for newly added Hugging Face model IDs.
  3. 3Each model's license is fetched from its Hugging Face model card.
  4. 4A logic step matches licenses against a non-commercial and research-only set (for example cc-by-nc, openrail with use restrictions, llama-community terms).
  5. 5When a match is found, a Slack direct message goes to the PR author with the model, license, plain-English restriction, and permissive alternatives to consider.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect Hugging FaceModels, datasets, spaces — the open-source hub.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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