scorer.py

from dataclasses import dataclass
from typing import Dict, Any, List

@dataclass
class ScoreResult:
    score: float
    details: Dict[str, Any]

def score(sample: Dict[str, Any], prediction: str) -> ScoreResult:
    # Expect a single float coherence_score in [0,1]
    try:
        pred = float((prediction or "").strip())
    except Exception:
        pred = -1.0

    true_raw = sample.get("coherence_score", "")
    try:
        true = float(true_raw) if true_raw not in ("", None) else None
    except Exception:
        true = None

    if true is None:
        ok = 0.0 <= pred <= 1.0
        return ScoreResult(1.0 if ok else 0.0, {"mode": "format_only", "id": sample.get("id"), "pred": pred})

    err = abs(true - pred)
    return ScoreResult(max(0.0, 1.0 - err), {"id": sample.get("id"), "pred": pred, "true": true, "abs_error": err})

def aggregate(results: List[ScoreResult]) -> Dict[str, Any]:
    if not results:
        return {"mean": 0.0, "n": 0}
    return {"mean": sum(r.score for r in results)/len(results), "n": len(results)}