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How to validate the 60-task benchmark catalog locally with Simreal ML Bench

Check the public task catalog and protocol config before building on the benchmark.

  • Top pick
  • Research
  • Intermediate
  • 30 minutes
  • From the README
  • Any agent

Who it is forAn ML engineer or benchmark maintainer who wants to confirm the public catalog is well-formed before adding an agent or a fork.

The problemBenchmark definitions drift or break silently, and it is hard to know whether a local copy still matches the published protocol.

The outcomeA local confirmation that the task catalog and protocol configuration validate, with no credentials or model calls needed.

What you need first

  • Python 3.11 or newer (Python 3.12 is the locally tested version)
  • A local copy of the repository from github.com/Simreal-AI/Simreal-MLBench
  • A terminal with a shell that supports the commands in the README
  • For full agent evaluation only: contact with [email protected] to get access to the Simreal evaluation service

Steps

  1. Create a virtual environment with python3 -m venv .venv.
  2. Activate it with source .venv/bin/activate.
  3. Install the package and test extras with python -m pip install -e '.[test]'.
  4. Validate the catalog with mleb validate configs/catalog.json.

Prompt for your agent

In the Simreal-MLBench repository, create a virtual environment, install the package with `python -m pip install -e '.[test]'`, and run `mleb validate configs/catalog.json`. Report whether validation passed and how many tasks the catalog lists. Confirm the count is 60 before reporting success.

Caveat. This only validates the public catalog and protocol config; it does not run any agent or touch the original competition datasets, which are acquired separately.

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