"""LLM-as-judge grading: one semantic judge for every question type and axis."""
from __future__ import annotations

import logging

from .llm_client import MAX_ATTEMPTS
from .prompts import JUDGE_SYS, JUDGE_USER, qtext

logger = logging.getLogger(__name__)


def gold_text(q_raw: dict) -> str:
    """Return the question's `answer`, or the correct options of a multiple-choice question."""
    if q_raw.get("answer"):
        return q_raw["answer"]
    cor = [o for o in q_raw.get("options", []) if o.get("is_correct")]
    return "; ".join(f"{o['label']}. {o['content']}" for o in cor) if cor else str(q_raw.get("correct_option", ""))


def score(client, q, cand: str):
    """(ok, verdict, detail) of one answer; the verdict is 'match', 'no_match', or '?' after MAX_ATTEMPTS failed
    judge calls."""
    msg = JUDGE_USER.format(question=qtext(q.raw), gold=gold_text(q.raw), cand=cand)
    last_err = "no exception recorded"
    for _ in range(MAX_ATTEMPTS):
        try:
            v = client.complete_json(JUDGE_SYS, msg).get("match")
            if isinstance(v, str):
                v = v.strip().lower() in ("true", "yes", "1")
            if v is None:
                continue
            return bool(v), ("match" if v else "no_match"), {}
        except Exception as e:
            last_err = f"{type(e).__name__}: {e}"[:200]
            logger.warning("[judge] attempt failed (%s), retrying", last_err)
    logger.error("[judge] gave up after %d attempts; scoring as verdict '?': %s", MAX_ATTEMPTS, last_err)
    return False, "?", {"judge_error": last_err}