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Checkpoint experiments through SWE pilot v2
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#!/usr/bin/env python3
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"""Preview or freeze the separate 24-episode adaptive prompt-E plan.
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This command never loads a dataset, starts Docker, or calls a model.
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"""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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from messageboardbench.prompt_e_calibration import build_manifest, write_manifest
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def parser() -> argparse.ArgumentParser:
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value = argparse.ArgumentParser(description=__doc__)
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value.add_argument("--dataset-revision", required=True)
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value.add_argument("--seed", type=int, default=1919)
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value.add_argument("--model", default="openrouter/z-ai/glm-5.3-flash")
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value.add_argument("--messages", type=int, default=90)
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value.add_argument("--tokens", type=int, default=1_000_000)
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value.add_argument("--sample-seconds", type=int, default=1_800)
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value.add_argument("--temperature", type=float, default=1)
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value.add_argument("--reasoning-effort",
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choices=("none", "minimal", "low", "medium", "high", "xhigh"),
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default="high")
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value.add_argument("--out", type=Path)
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return value
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def configuration(args: argparse.Namespace) -> dict:
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return build_manifest(
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dataset_revision=args.dataset_revision,
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seed=args.seed,
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model=args.model,
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message_limit=args.messages,
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token_limit=args.tokens,
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time_limit_seconds=args.sample_seconds,
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temperature=args.temperature,
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reasoning_effort=args.reasoning_effort,
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)
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def main() -> None:
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args = parser().parse_args()
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manifest = configuration(args)
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print(json.dumps(manifest, indent=2))
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if args.out is None:
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print("Preview only; no file, dataset, Docker container, or model request was created.")
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return
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write_manifest(args.out, manifest)
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print(f"Wrote frozen prompt-E calibration plan to {args.out}")
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if __name__ == "__main__":
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main()
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