"""SmartAssetSelector — 智能素材选择服务.

根据多维度评分从素材库中自动选择最优视频素材，
用于一键生成等需要自动选取素材的场景。

评分维度（加权求和，总分 0-1）：
  - 质量分（quality_score）：权重 0.5 — 来自人工或AI的质量评分
  - 分辨率适配：权重 0.2 — 分辨率越接近 1080p 得分越高
  - 时长合理性：权重 0.2 — 3-30 秒区间最佳，过短/过长扣分
  - 码率质量：权重 0.1 — 用文件大小/时长估算，码率适中得分高

特性：
  - 最低质量分门槛：自动过滤低质量素材
  - 时长多样性：保证选出的素材时长分布均匀（短/中/长各占一定比例）
  - 兼容全部模式：素材库模式和项目模式都可用

纯逻辑部分已抽离到 packages.domain.asset_scoring。
"""

from __future__ import annotations

import logging

from packages.domain.asset_scoring import MEDIUM_BUCKET_MAX as _MEDIUM_BUCKET_MAX  # noqa: F401 - re-export for tests
from packages.domain.asset_scoring import SHORT_BUCKET_MAX as _SHORT_BUCKET_MAX  # noqa: F401 - re-export for tests
from packages.domain.asset_scoring import (
    AssetScoreDetail,
    SmartSelectResult,
    diverse_selection,
    filter_candidates,
    score_asset_detail,
)

logger = logging.getLogger(__name__)


class SmartAssetSelector:
    """智能素材选择器.

    从一组素材中按综合评分选择最优的 N 个，
    同时保证时长分布的多样性。
    """

    def __init__(
        self,
        min_quality_score: float = 30.0,
        target_width: int = 1920,
        target_height: int = 1080,
    ):
        self.min_quality_score = min_quality_score
        self.target_width = target_width
        self.target_height = target_height

    # ── 公开方法 ──────────────────────────────────────────────────────────────

    def select(
        self,
        assets: list,
        count: int = 0,
        *,
        ensure_diversity: bool = True,
    ) -> SmartSelectResult:
        """从素材列表中智能选择最优素材.

        Args:
            assets: Asset 实体列表（需要有 id/quality_score/width/height/duration/file_size 属性）
            count: 选取数量，0 表示全部符合条件的
            ensure_diversity: 是否保证时长多样性（默认开启）

        Returns:
            SmartSelectResult 选择结果
        """
        # 1. 过滤：只保留 ready 状态的视频素材 + 最低质量分门槛
        candidates, filtered_out = filter_candidates(assets, self.min_quality_score)

        if not candidates:
            return SmartSelectResult(
                selected_ids=[],
                total_candidates=0,
                filtered_out=filtered_out,
                avg_score=0.0,
                details=[],
            )

        # 2. 对每个候选素材评分
        scored: list[AssetScoreDetail] = []
        for asset in candidates:
            detail = score_asset_detail(
                asset_id=asset.id,
                quality=getattr(asset, "quality_score", None),
                width=getattr(asset, "width", None),
                height=getattr(asset, "height", None),
                duration=getattr(asset, "duration", None),
                file_size=getattr(asset, "file_size", 0) or 0,
                target_width=self.target_width,
                target_height=self.target_height,
            )
            scored.append(detail)

        # 3. 按总分降序排列
        scored.sort(key=lambda d: d.total_score, reverse=True)

        # 4. 多样性选择（如果需要且数量有限制）
        if ensure_diversity and count > 0 and len(scored) > count:
            selected = diverse_selection(scored, count)
        else:
            # 无数量限制或不要求多样性，直接按排名取
            selected = scored if count <= 0 else scored[:count]

        avg_score = sum(d.total_score for d in selected) / len(selected) if selected else 0.0

        result = SmartSelectResult(
            selected_ids=[d.asset_id for d in selected],
            total_candidates=len(candidates),
            filtered_out=filtered_out,
            avg_score=avg_score,
            details=selected,
        )

        logger.info(
            "智能素材选择完成: 候选=%d, 过滤=%d, 选中=%d, 平均分=%.3f",
            result.total_candidates,
            result.filtered_out,
            len(result.selected_ids),
            result.avg_score,
        )
        return result

    # ── 向后兼容：私有方法别名（委托给 asset_scoring 纯函数） ────────────────

    def _score_asset(self, asset) -> AssetScoreDetail:
        """对单个素材进行多维度评分（向后兼容）."""
        return score_asset_detail(
            asset_id=asset.id,
            quality=getattr(asset, "quality_score", None),
            width=getattr(asset, "width", None),
            height=getattr(asset, "height", None),
            duration=getattr(asset, "duration", None),
            file_size=getattr(asset, "file_size", 0) or 0,
            target_width=self.target_width,
            target_height=self.target_height,
        )

    def _score_resolution(self, width: int | None, height: int | None) -> float:
        """分辨率评分（向后兼容）."""
        from packages.domain.asset_scoring import score_resolution

        return score_resolution(width, height, self.target_width, self.target_height)

    def _score_duration(self, duration: float | None) -> float:
        """时长评分（向后兼容）."""
        from packages.domain.asset_scoring import score_duration

        return score_duration(duration)

    def _score_bitrate(self, file_size: int, duration: float | None) -> float:
        """码率评分（向后兼容）."""
        from packages.domain.asset_scoring import score_bitrate

        return score_bitrate(file_size, duration)

    def _diverse_selection(self, scored: list[AssetScoreDetail], count: int) -> list[AssetScoreDetail]:
        """多样性选择（向后兼容）."""
        return diverse_selection(scored, count)