Datasets:
FireWorldBench v2 evaluation toolkit
This is a copy of the FireWorldBench-ICLR evaluation code, task contracts, and schemas. Source repository and commit are recorded in UPSTREAM.md. The code license is in LICENSE; the bundled dataset license is at ../../DATA_LICENSE.md.
Install
From the FireWorldBench v2 repository root:
python -m pip install -r evaluation/FireWorldBench-ICLR/requirements.txt
Python 3.8 or newer is required. The included runner uses an OpenAI-compatible HTTP endpoint; configure OPENAI_BASE_URL, OPENAI_API_KEY, and OPENAI_MODEL in the environment.
Run the bundled benchmark
From the FireWorldBench v2 repository root:
python evaluation/FireWorldBench-ICLR/scripts/run_eval.py --split main_synthetic --data-dir .
The v2 package root is the data directory because it contains main_synthetic/full_test_A/. The runner reads questions and referenced images, never gold. After inference, the scorer reads matching gold rows by qa_id and writes six metrics under results/.
Use --track S for text-only models or --track I for vision models; omit --track to run both. Add --max-requests 2 for a small endpoint connectivity check.
The scripts in scripts/contracts/ contain the frozen task contracts. The direct API runner accepts an optional --task-contract file for contract-controlled runs. See python evaluation/FireWorldBench-ICLR/scripts/run_eval.py --help and python evaluation/FireWorldBench-ICLR/scripts/run_api.py --help for all options.