from __future__ import annotations

from app.normalization import normalize_text, tokenize
from app.typo import word_similarity

SERVICE_INTENTS = {
    "opening_hours": [
        ("до", "скольки", "работаете"),
        ("режим", "работы"),
        ("график", "работы"),
    ],
    "payment": [
        ("оплата", "картой"),
        ("оплатить", "картой"),
        ("наличными", "при", "получении"),
    ],
    "location": [
        ("где", "магазин"),
        ("адрес", "магазина"),
        ("как", "доехать"),
    ],
    "order_status": [
        ("статус", "заказа"),
        ("где", "мой", "заказ"),
    ],
    "thanks": [
        ("спасибо", "заказ", "получил"),
        ("все", "отлично"),
    ],
}


def _token_present(expected: str, tokens: tuple[str, ...]) -> bool:
    for token in tokens:
        if token == expected:
            return True
        if min(len(token), len(expected)) >= 5 and word_similarity(token, expected) >= 0.72:
            return True
    return False


def detect_service_intent(text: str) -> str | None:
    """Detect a known non-product intent after product evidence has failed.

    This is deliberately phrase/token based rather than a blacklist of words
    such as ``подскажите``: those words are valid in product requests too.
    """

    tokens = tokenize(normalize_text(text), already_normalized=True)
    for intent, phrases in SERVICE_INTENTS.items():
        for phrase in phrases:
            if all(_token_present(expected, tokens) for expected in phrase):
                return intent
    return None