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What you can do with Fde Gym

FDE Gym is an open online judge where each case is a simulated customer delivery that you work with a coding agent and are scored on once your system is live.

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4 use cases

  • Practise customer delivery cases on your own machine

    Run FDE Gym locally and work the three open cases with a coding agent.

    View prompt
    In the fde-gym repository at <path>, follow the README quick start to download the three open cases into cases/ and start the site with docker compose. Report the URL the site answers on and the names of the case folders present. Verify that cases/ contains the three downloaded cases before reporting success.
  • Run a private FDE Gym site for your team's engineers

    Host the judge for your own people, with an admin console for cases and members.

    View prompt
    In the fde-gym repository at <path>, read docs/self-hosting.md and list the settings a team needs to change before sharing the site. Output the list as bullet points with the setting name and what it controls. Verify each item appears in that document before listing it.
  • Work an FDE Gym case from the command line with the harness

    Use the Python harness to work a case without the browser workbench.

    View prompt
    In the fde-gym repository at <path>, run `python3 harness/run.py --version` and read harness/README.md. Report the harness version and the exact command the README gives for working a case. Verify the version string comes from the command output, not from the README.
  • Add extra runner machines to a self-hosted FDE Gym site

    Attach more machines to run cases, on any network that reaches the site.

    View prompt
    In the fde-gym repository at <path>, read the runner section of docs/self-hosting.md and list the network and setup requirements for an extra runner. Output a numbered checklist. Verify each item is stated in that document before adding it.

How to use Fde Gym

  1. Check you have what it needs: Docker; Python 3.9 or later; An OpenRouter key, stored in a file outside the repository.
  2. Open deeplethe/fde-gym on GitHub and read the README and license.
  3. Install Docker and Python 3.9 or later, then create an OpenRouter key and keep it in a file outside the repository.
  4. git clone https://github.com/deeplethe/fde-gym.git && cd fde-gym
  5. mkdir -p ~/.fdegym && echo "sk-or-..." > ~/.fdegym/openrouter_key
  6. python3 scripts/fetch_cases.py

These steps come from our top use case, Practise customer delivery cases on your own machine, which also has a copy-paste agent prompt.

Fde Gym alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forEngineers and forward deployed engineers who want to practise customer delivery work, and teams who want to run a private version of the judge for their own people.
  • Why it is hot
  • LanguageTypeScript
  • Sourcegithub.com/deeplethe/fde-gym · Back to Hot repos

Requirements

  • Docker
  • Python 3.9 or later
  • An OpenRouter key, stored in a file outside the repository
  • Git
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Questions about Fde Gym

What is Fde Gym?

FDE Gym is an open online judge where each case is a simulated customer delivery that you work with a coding agent and are scored on once your system is live. It is an open-source project on GitHub: https://github.com/deeplethe/fde-gym.

Who is Fde Gym for?

Engineers and forward deployed engineers who want to practise customer delivery work, and teams who want to run a private version of the judge for their own people.

What can I do with Fde Gym?

4 use cases so far, for example: Practise customer delivery cases on your own machine; Run a private FDE Gym site for your team's engineers; Work an FDE Gym case from the command line with the harness. Each has steps and a copy-paste agent prompt.

What do I need to run Fde Gym?

Docker; Python 3.9 or later; An OpenRouter key, stored in a file outside the repository; Git.

What are alternatives to Fde Gym?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is Fde Gym safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.