#!/usr/bin/env python3
"""Run both RE-1 executions and write the capsule metrics file.

This is the single published top-level command for the experiment:
  python3 scripts/run_capsule.py --output-dir /path/to/out

It shells out to scripts/run_one.sh twice (fresh containers, same commands),
then runs harness/analyze.py and reduces the analysis to metrics.json.
"""

from __future__ import annotations

import argparse
import json
import os
import shutil
import subprocess
import sys
from pathlib import Path

HERE = Path(__file__).resolve().parent.parent


def main() -> int:
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("--output-dir", required=True, type=Path)
    parser.add_argument(
        "--evidence-dir",
        type=Path,
        default=Path(os.environ.get("RE1_EVIDENCE_DIR", str(Path.cwd() / "evidence"))),
    )
    args = parser.parse_args()

    out = args.output_dir.resolve()
    out.mkdir(parents=True, exist_ok=True)
    env = {**os.environ, "RE1_EVIDENCE_DIR": str(args.evidence_dir)}

    for run_id in ("r1", "r2"):
        print(f"== {run_id} ==", flush=True)
        subprocess.run(["bash", str(HERE / "scripts" / "run_one.sh"), run_id], check=True, env=env)

    runs = args.evidence_dir / "runs"
    proc = subprocess.run(
        [
            sys.executable,
            str(HERE / "harness" / "analyze.py"),
            "--run1", str(runs / "r1"),
            "--run2", str(runs / "r2"),
            "--out", str(out / "analysis.json"),
            "--md", str(out / "analysis.md"),
        ]
    )
    analysis = json.loads((out / "analysis.json").read_text())

    for run_id in ("r1", "r2"):
        dest = out / run_id
        dest.mkdir(parents=True, exist_ok=True)
        shutil.copy2(runs / run_id / "results.json", dest / "results.json")
        shutil.copy2(runs / run_id / "run_status.json", dest / "run_status.json")

    def repro(key: str) -> float:
        return analysis["quantities"].get(key, {}).get("rel_diff", 1.0)

    metrics = {
        "decision": analysis["decision"],
        "max_relative_deviation": max(
            (row["rel_diff"] for row in analysis["quantities"].values()), default=1.0
        )
        if not analysis["missing"]
        else 1.0,
        "missing_quantities": len(analysis["missing"]),
        "failing_quantities": len(analysis["failing"]),
        "quantities_checked": len(analysis["quantities"]),
        "qwen_ppl_delta_repro": repro("qwen2.5-0.5b-instruct.ppl_delta"),
        "qwen_hellaswag_delta_repro": repro("qwen2.5-0.5b-instruct.hellaswag_delta_pct"),
        "smollm_ppl_delta_repro": repro("smollm2-360m-instruct.ppl_delta"),
        "smollm_hellaswag_delta_repro": repro("smollm2-360m-instruct.hellaswag_delta_pct"),
    }
    (out / "metrics.json").write_text(json.dumps(metrics, indent=2, sort_keys=True) + "\n")
    print(json.dumps(metrics, indent=2))
    return proc.returncode


if __name__ == "__main__":
    raise SystemExit(main())