"""Shared response-parsing helpers for LLM providers."""

from __future__ import annotations

import json
import re

from physcom.models.domain import MetricBound


def parse_verdict(text: str) -> bool:
    """Extract VERDICT: PLAUSIBLE/IMPLAUSIBLE from response; default to True."""
    m = re.search(r"VERDICT:\s*(PLAUSIBLE|IMPLAUSIBLE)", text, re.IGNORECASE)
    if m:
        return m.group(1).upper() == "PLAUSIBLE"
    return True


def parse_rating(text: str) -> str | None:
    """Extract RATING: LOW/MEDIUM/HIGH from response; None if absent (older
    reviews saved before this existed, or a malformed response)."""
    m = re.search(r"RATING:\s*(LOW|MEDIUM|HIGH)", text, re.IGNORECASE)
    return m.group(1).upper() if m else None


def parse_metric_json(text: str, metrics: list[MetricBound]) -> dict[str, float]:
    """Strip markdown fences and parse JSON; fall back to each metric's own
    norm_min/norm_max midpoint on error — a flat constant like 0.5 is
    guaranteed wrong-magnitude for at least some metrics regardless of unit.
    """
    names = {mb.metric_name for mb in metrics}
    text = re.sub(r"```(?:json)?\s*", "", text).strip().rstrip("`").strip()
    try:
        data = json.loads(text)
        return {k: float(v) for k, v in data.items() if k in names}
    except (json.JSONDecodeError, ValueError, TypeError):
        return {mb.metric_name: (mb.norm_min + mb.norm_max) / 2 for mb in metrics}