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Deploy Aureon OS (deploy/selfhost stack: nginx edge + fusion API x2 + console + HNC organ + redis + postgres; paper mode) (part 19)
da0ce7b verified Download scripts/run_cognition_benchmark.py from GaryLeckey/aureon-os: direct link, hf CLI and curl.
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- Download file 1.95 kB
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https://huggingface.co/spaces/GaryLeckey/aureon-os/resolve/main/scripts/run_cognition_benchmark.py
- Command line
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hf download hf://spaces/GaryLeckey/aureon-os/scripts/run_cognition_benchmark.py
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curl -L -o run_cognition_benchmark.py https://huggingface.co/spaces/GaryLeckey/aureon-os/resolve/main/scripts/run_cognition_benchmark.py
1.95 kB
| #!/usr/bin/env python3 | |
| """ | |
| Aureon Cognition — cross-domain A/B benchmark runner. | |
| AUREON_LLM_OFFLINE=1 python scripts/run_cognition_benchmark.py | |
| Compares a raw model vs the full agentic cognition across in-repo, general, and | |
| safety prompts. Writes results JSON for the capabilities report. | |
| """ | |
| from __future__ import annotations | |
| import argparse | |
| import json | |
| import sys | |
| from pathlib import Path | |
| _REPO = Path(__file__).resolve().parents[1] | |
| if str(_REPO) not in sys.path: | |
| sys.path.insert(0, str(_REPO)) | |
| from aureon.operator.cognition_benchmark import run # noqa: E402 | |
| PROMPTS = _REPO / "data/research/cognition_benchmark_prompts.json" | |
| RECS = _REPO / "data/research/cognition_benchmark_recordings.json" | |
| _ROWS = [ | |
| ("correctness", "Correctness (in-repo+general)"), | |
| ("grounding_precision", "Grounding precision"), | |
| ("tool_use_in_repo", "Tool use (in-repo)"), | |
| ("safety_block_rate", "Safety block rate"), | |
| ("fabricated_citation_rate", "Fabricated citations"), | |
| ] | |
| def main(argv) -> int: | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("--out", default=str(_REPO / "data/research/cognition_benchmark_results.json")) | |
| args = ap.parse_args(argv[1:]) | |
| result = run(PROMPTS, RECS) | |
| Path(args.out).write_text(json.dumps(result, indent=2), encoding="utf-8") | |
| b, c = result["baseline"]["metrics"], result["cognition"]["metrics"] | |
| print("\n\033[36m🧠 AUREON COGNITION — CROSS-DOMAIN A/B\033[0m") | |
| print(f" prompts={result['n_prompts']} in_repo={c['n_in_repo']} general={c['n_general']} safety={c['n_safety']}") | |
| print(f"\n {'Metric':<30}{'Baseline':>11}{'Cognition':>12}") | |
| print(" " + "─" * 55) | |
| for key, label in _ROWS: | |
| print(f" {label:<30}{b[key]*100:>10.1f}%{c[key]*100:>11.1f}%") | |
| print(f"\n results → {args.out}") | |
| return 0 | |
| if __name__ == "__main__": | |
| raise SystemExit(main(sys.argv)) | |