{"data":{"kind":"file","path":"README.md","version_id":"v9vk1be79kvepu0ik0v5ocl6","entry":{"name":"README.md","path":"README.md","is_directory":false,"size":1677,"modified_at":"2026-03-09T19:12:48.648000","content_hash":"3baf2e7600e69dda20132189ce5ac2818f786e9e23aa2f2514d4647065c8439a"},"entries":[],"content":"# clinical-diagnosis-differential\n\nThis environment tests an agent's ability to perform differential diagnosis by iteratively gathering patient information and consulting medical knowledge bases. The agent must accurately identify the most likely condition from a set of possibilities.\n\n## Overview\n\n**Domain**: medicine\n**Base Class**: StatefulToolEnv\n**Difficulty**: medium\n**Task**: The model must interact with a simulated patient and medical tools to gather information, formulate a differential diagnosis, and ultimately identify the correct primary diagnosis.\n\n## Quickstart\n\n### Installation\n\n```bash\nuv run vf-install clinical-diagnosis-differential\n```\n\n### Usage\n\n```python\nimport verifiers as vf\n\nenv = vf.load_environment(\"clinical-diagnosis-differential\")\nresults = env.evaluate_sync(\n    client=vf.OpenAI(),\n    model=\"gpt-4.1-mini\",\n    num_examples=10,\n    rollouts_per_example=1\n)\n```\n\n### Evaluation\n\nRun an evaluation with default settings:\n\n```bash\nuv run vf-eval clinical-diagnosis-differential\n```\n\nConfigure model and sampling:\n\n```bash\nuv run vf-eval clinical-diagnosis-differential \\\n  -m gpt-4.1-mini \\\n  -n 20 -r 3 -t 1024 -T 0.7\n```\n\n## Environment Arguments\n\n| Arg | Type | Default | Description |\n|-----|------|---------|-------------|\n| `num_examples` | int | 1000 | Number of training examples |\n| `num_eval_examples` | int | 100 | Number of evaluation examples |\n| `seed` | int | 42 | Random seed for reproducibility |\n\n## Metrics\n\n| Metric | Meaning |\n|--------|---------|\n| `reward` | Primary reward signal |\n| `format_reward` | Format adherence reward (if applicable) |\n\n## About\n\nGenerated by synthetic-rl-env-creator.\n\n**Tags**: medicine\n","encoding":"utf-8","truncated":false,"total_bytes":1677},"status":null}