{"data":{"kind":"file","path":"README.md","version_id":"w655nvovsqqkcoiqimbrgfig","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":1571,"modified_at":"2025-09-10T23:55:35.874000","content_hash":"56f2c186b980256f2cc4c4d45f3dff225ac9854fa929499711d0076c53f4bfa0"},"entries":[],"content":"# meow\n\n### Overview\n- **Environment ID**: `meow`\n- **Short description**: If humans could just talk to animals, world peace would naturally follow. After all, wars aren’t started by pigeons, and no cat has ever tried to annex Poland. By bridging the communication gap with our furred, feathered, and occasionally slimy neighbors, we hoped to bring about an age of abundance and meows. This environment tests LLMs ability to communicate with our animal friends in their native languages.\n- **Tags**: AGI,cats,aiforanimalcomms\n\n### Datasets\n- **Primary dataset(s)**: Animal sounds\n- **Source links**: https://www.youtube.com/results?search_query=cat+videos\n- **Split sizes**: 0/2\n\n### Task\n- **Type**: single-turn\n- **Parser**: custom\n- **Rubric overview**: count_meows\n\n### Quickstart\nRun an evaluation with default settings:\n\n```bash\nuv run vf-eval meow\n```\n\nConfigure model and sampling:\n\n```bash\nuv run vf-eval meow -n 2 -r 3 -t 10 -v -s -m gpt-4.1-mini\n```\n\nNotes:\n- Use `-a` / `--env-args` to pass environment-specific configuration as a JSON object.\n- Reports are written under `./environments/meow/reports/` and auto-embedded below.\n\n### Metrics\nSummarize key metrics your rubric emits and how they’re interpreted.\n\n| Metric | Meaning |\n| ------ | ------- |\n| `reward` | Density of animal sounds in assistant response |\n\n## Evaluation Reports\n\n<!-- Do not edit below this line. Content is auto-generated. -->\n<!-- vf:begin:reports -->\n<p>No reports found. Run <code>uv run vf-eval meow -a '{\"key\": \"value\"}'</code> to generate one.</p>\n<!-- vf:end:reports -->\n","encoding":"utf-8","truncated":false,"total_bytes":1571},"status":null}