scorer.py

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

REQ = ["coherence", "risk", "pitting", "surface", "protect"]

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

def score(sample: Dict[str, Any], prediction: str) -> ScoreResult:
    p = (prediction or "").lower()
    words_ok = len(p.split()) <= 900

    hits = sum(1 for k in REQ if k in p)
    has_numeric = any(c.isdigit() for c in p)

    raw = (
        0.25 * int(words_ok) +
        0.45 * (hits / len(REQ)) +
        0.20 * int(has_numeric) +
        0.10 * int("time" in p or "horizon" in p)
    )

    return ScoreResult(score=min(1.0, raw), details={"id": sample.get("id"), "hits": hits})

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)}