"""지역명으로 맛집 후보 이름을 찾는다."""
import json

from common.logger import LOG
from services.llm.perplexity import DEFAULT_MAX_TOKENS, DEFAULT_MODEL, PerplexityError, call, read_usage
from services.prompts.restaurant_search import RESPONSE_SCHEMA, SYSTEM_PROMPT, build_prompt

MAX_RESULTS = 10


def _parse_names(payload: dict) -> list[str]:
    choices = payload.get("choices") or []
    if not choices or not isinstance(choices[0], dict):
        return []
    content = ((choices[0].get("message") or {}).get("content")) or ""
    try:
        doc = json.loads(content)
    except (json.JSONDecodeError, TypeError):
        LOG.w("[restaurant_discovery] 구조화 출력 파싱 실패")
        return []
    names = doc.get("restaurants")
    if not isinstance(names, list):
        return []
    return [str(n).strip() for n in names if str(n or "").strip()][:MAX_RESULTS]


async def search_region_restaurants(
    region_label: str, *, model: str = DEFAULT_MODEL, client=None,
) -> list[str]:
    """지역명으로 맛집 상위 10곳의 이름만 받는다."""
    if not (region_label or "").strip():
        return []
    body = {
        "model": model,
        "messages": [
            {"role": "system", "content": SYSTEM_PROMPT},
            {"role": "user", "content": build_prompt(region_label)},
        ],
        "max_tokens": DEFAULT_MAX_TOKENS,
        "temperature": 0,
        "response_format": RESPONSE_SCHEMA,
    }
    try:
        payload = await call(body, client=client)
    except PerplexityError as ex:
        LOG.w(f"[restaurant_discovery] '{region_label}' 검색 실패: {ex}")
        return []
    names = _parse_names(payload)
    usage = read_usage(payload)
    LOG.i(
        f"[restaurant_discovery] '{region_label}' {len(names)}곳 · "
        f"tokens in={usage.input_tokens} out={usage.output_tokens} · 약 ${usage.cost}"
    )
    return names