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How to script repeat experiments with the Python SDK with Dynolab

Run saved experiments from code and collect results as jobs and artifacts.

  • Research
  • Advanced
  • 2 hours
  • From the README
  • Any agent

Authorization notice. Dynolab is dual-use. Only use it on software, sites and systems you own or have explicit permission to test.

Who it is forA developer who needs to rerun the same interpretability experiment across many prompts or settings.

The problemClicking through the app for each variant is slow and hard to repeat exactly.

The outcomeA script that submits experiments through the SDK and saves their results as artifacts you can reopen.

What you need first

  • An Apple Silicon Mac running macOS 14 or later
  • The Dyno app downloaded from the latest GitHub release
  • An MLX model downloaded through Discover in the app

Steps

  1. Install the Python package named in the README with pip install mlx-dyno. (inferred, check the README)
  2. Open docs/sdk-guide.md and read the sections on jobs and artifacts.
  3. Write a script that starts a model, submits an activation or probe job and waits for it to finish.
  4. Save the returned artifacts and check that they match the run you ran in the app.

Prompt for your agent

In the canivel/dynolab repo, read docs/sdk-guide.md and write a Python script that submits an activation job for the model <model-name>. Expected output: a job result and its saved artifacts. Verify the artifact paths and that the job finished without error.

Caveat. The README gives the SDK distribution name mlx-dyno but no install command, so the pip step is an inference to confirm in docs/sdk-guide.md.

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