from __future__ import annotations

from .schemas import PlanRecommendationRequest, PoiCandidate


THEME_TAGS: dict[str, set[str]] = {
    "亲子": {"family_friendly", "science_learning", "indoor_venue"},
    "情侣": {"photo_spot", "nature_view", "pastoral_scenery"},
    "朋友": {"outdoor_leisure", "photo_spot", "culture_experience"},
    "银发": {"walking", "city_park", "culture_experience", "indoor_venue"},
    "研学": {"science_learning", "culture_experience", "nature_view"},
}

INTEREST_TAGS: dict[str, set[str]] = {
    "自然风光": {"nature_view", "pastoral_scenery", "city_park", "outdoor_leisure"},
    "文化场馆": {"culture_experience", "indoor_venue"},
    "生态科普": {"science_learning", "nature_view", "pastoral_scenery"},
    "美食": set(),
    "摄影": {"photo_spot", "nature_view", "pastoral_scenery"},
}


def _score(candidate: PoiCandidate, request: PlanRecommendationRequest) -> int:
    score = candidate.recommendation_index * 10
    desired_tags: set[str] = set()
    for theme in request.preferences.themes:
        desired_tags.update(THEME_TAGS.get(theme, set()))
    for interest in request.preferences.interests:
        desired_tags.update(INTEREST_TAGS.get(interest, set()))
    score += len(desired_tags.intersection(candidate.tag_codes)) * 8
    return score


def ranked_candidates(request: PlanRecommendationRequest) -> list[PoiCandidate]:
    """Provide a deterministic mock ranking without storing a second POI catalog."""

    return sorted(
        request.candidates,
        key=lambda candidate: (-_score(candidate, request), candidate.id),
    )