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50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
#!/usr/bin/env python3
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"""Run the full Experiment 9-3 campaign and save canonical evidence."""
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from __future__ import annotations
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import argparse
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import hashlib
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import json
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import os
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from datetime import datetime, timezone
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from pathlib import Path
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from airline_env import CASES
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from demo import main as run_campaign
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ROOT = Path(__file__).resolve().parent
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def main() -> int:
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--provider", choices=("openrouter", "moonshot", "ark", "openai"), default="openrouter")
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parser.add_argument("--model", default="openai/gpt-4o-mini")
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parser.add_argument("--rounds", type=int, default=3)
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parser.add_argument("--output-dir", type=Path)
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args = parser.parse_args()
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os.environ["LLM_PROVIDER"] = args.provider
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os.environ["LLM_MODEL"] = args.model
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stamp = datetime.now(timezone.utc).strftime("real_%Y%m%dT%H%M%SZ")
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output_dir = args.output_dir or ROOT / "validation" / stamp
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output_dir.mkdir(parents=True, exist_ok=False)
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evidence_path = output_dir / "evidence.json"
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summary = run_campaign(cases=CASES, rounds=args.rounds, output=str(evidence_path))
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payload = evidence_path.read_text(encoding="utf-8")
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(ROOT / "validation").mkdir(exist_ok=True)
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(ROOT / "validation" / "latest.json").write_text(payload, encoding="utf-8")
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print(json.dumps({
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"evidence": str(evidence_path.relative_to(ROOT)),
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"sha256": hashlib.sha256(payload.encode()).hexdigest(),
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"execution_accepted": summary["acceptance"]["execution_accepted"],
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"all_manuscript_result_claims_observed": summary["acceptance"]["all_manuscript_result_claims_observed"],
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"release_decision": summary["release_gate"]["decision"],
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"usage": summary["usage"],
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}, ensure_ascii=False, indent=2))
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return 0 if summary["acceptance"]["execution_accepted"] else 1
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if __name__ == "__main__":
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raise SystemExit(main())
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