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How to preview benchmark tasks before spending model quota with Rsi Eval

Check which tasks, candidate hash, and settings a run would use, with no Docker or model calls.

Who it is forA developer or researcher who wants to confirm a benchmark selection before committing to a paid or slow evaluation.

The problemBenchmark runs can be large and consume model quota, so it is hard to verify task selection and settings first.

The outcomeA printed preview of resolved task references, candidate hash, and run settings, without starting any execution.

What you need first

  • Python 3.12 or newer and git
  • Docker Engine with Compose and Buildx, or Docker Desktop, for benchmark runs
  • Codex CLI on PATH and access to a model for candidate runs
  • Harbor 0.18.0 installed through the harbor extra for benchmark runs

Steps

  1. git clone https://github.com/Danielxu0208/rsi_eval.git
  2. cd rsi_eval
  3. python3.12 -m venv .venv
  4. source .venv/bin/activate
  5. python -m pip install -e .
  6. rsi-eval list
  7. rsi-eval preview --config examples/evaluate.json

Prompt for your agent

Clone https://github.com/Danielxu0208/rsi_eval, install it with `python -m pip install -e .` in a Python 3.12 virtual environment, then run `rsi-eval preview --config <config-path>` for the benchmark config I choose. Report the resolved task references and candidate hash. Verify that the preview ran without Docker or a model call.

Caveat. Preview only confirms the plan; real evaluations still need Docker, the Harbor extra, and Codex setup described in the README.

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