{
 "schema_version": 1,
 "generated": "2026-10-26",
 "id": "mll-lab-nu-embodied-first-exam--test-safety-suite-without-gpu",
 "repo": "mll-lab-nu/embodied-first-exam",
 "repo_url": "https://github.com/mll-lab-nu/embodied-first-exam",
 "repo_slug": "mll-lab-nu-embodied-first-exam",
 "title": "Test an agent on the Embodied Safety Exam without a GPU",
 "page_title": "How to test an agent on the Embodied Safety Exam without a GPU with Embodied First Exam",
 "summary": "Run the Embodied Safety Exam, which the README lists as needing no GPU, to test agent behavior on robot tasks.",
 "who": "A safety-minded engineer on a machine with no GPU who wants to see how a code agent handles safety-focused robot tasks.",
 "problem": "Many suites need a GPU, which blocks people who only have a CPU machine from testing agent safety on robot tasks.",
 "outcome": "A run of the safety suite on a CPU-only host, with per-task results from the Harbor output.",
 "steps": [
  "Install Harbor as in the core exam: `uv tool install --force -e . --with-executables-from harbor`",
  "Confirm your host has Docker Engine with Compose v2 and BuildKit, since the README lists no GPU needed for Embodied Safety Exam",
  "Run the safety suite by pointing -p at its folder under tasks/: `harbor run -d embodied-first-exam@all -p tasks/<safety suite folder> -a codex -m openai/gpt-6-astra` (inferred, check the README)"
 ],
 "agent_prompt": "In the repo mll-lab-nu/embodied-first-exam, run the Embodied Safety Exam suite with the agent codex and the model <model id> on a host without a GPU. Report which tasks passed and which failed, and any safety-related failures. Verify that no GPU was requested in the run output.",
 "agents": [
  "codex",
  "claude-code"
 ],
 "difficulty": "Intermediate",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "The exact folder name for the safety suite is not given in the README excerpt, so confirm it under tasks/ before running the inferred command.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Linux x86_64 host with git, uv, and Docker Engine with Compose v2 and BuildKit (or rootless podman with -e podman)",
  "NVIDIA driver and NVIDIA Container Toolkit for any GPU task",
  "An API key for the agent's model in .env, or a ChatGPT or Claude subscription",
  "Enough free disk for the benchmark images (1 to 150 GB depending on the suite)"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/mll-lab-nu-embodied-first-exam/test-safety-suite-without-gpu/",
 "md": "https://dedupedai.com/use-cases/mll-lab-nu-embodied-first-exam/test-safety-suite-without-gpu/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/mll-lab-nu-embodied-first-exam--test-safety-suite-without-gpu.json",
 "api_version": "v1"
}