"""深度诊断（全面报告）文案的纯逻辑：十二季色板规则映射、结构化输出 schema 与降级模板。

与 basic 报告共用同一条「LLM 不可信任」纪律，分工如下：

- **色板不出 LLM**：季型 → 色板的映射是本模块的预定义常量（规则引擎口径，
  与 kb_color 同源的确定性数据），LLM 只写季型解析文案。色值交给模型编
  是幻觉高发区，校验器拦得住但每次都多花一次重试——结构上不让它碰更省。
- **LLM 产出四块结构化内容**：总评 summary + 正文章节（与 basic 同构，保证
  ReportResultPage / PDF 导出的现有渲染零改动）、季型解析、4 场景穿搭、
  30 天计划。
- **降级模板**：持续违规时按规则直出拼全量内容（含场景与计划的兜底版本），
  对齐 validation_stage 的「任何出口要么 passed 要么抛错」。
"""

from __future__ import annotations

from collections.abc import Mapping, Sequence
from typing import Any

from pydantic import BaseModel

from packages.report.copy import CopySection, ReportCopy, dimension_label

# ── 十二季色板规则映射（常量，色值不交给 LLM） ─────────────────────────────

#: 十二季自研描述性命名（TD-18：对外不得使用「四季色彩 / CMB」商标名）。
TWELVE_SEASONS: tuple[str, ...] = (
    "浅春",
    "暖春",
    "亮春",
    "浅夏",
    "柔夏",
    "冷夏",
    "柔秋",
    "暖秋",
    "深秋",
    "亮冬",
    "冷冬",
    "深冬",
)

#: 四季粗判（season_code）→ 十二季默认细分：视觉缺 season_detailed 时的兜底，
#: 取该季最中位的细分型，宁保守不冒进。
SEASON_CODE_FALLBACK: Mapping[str, str] = {
    "spring": "暖春",
    "summer": "柔夏",
    "autumn": "暖秋",
    "winter": "冷冬",
}

#: 中性色按冷暖倾向分两档，各季直接引用（白/黑/灰/米/驼/卡其口径，需求 §2.3 篇章二）。
_NEUTRAL_WARM: tuple[tuple[str, str], ...] = (
    ("米白", "#F5EFE0"),
    ("象牙白", "#F8F0DC"),
    ("燕麦色", "#D9C9A8"),
    ("浅驼", "#C8A97E"),
    ("卡其", "#B89B6A"),
    ("暖灰", "#A89F8D"),
    ("深棕", "#5C4633"),
)

_NEUTRAL_COOL: tuple[tuple[str, str], ...] = (
    ("纯白", "#FFFFFF"),
    ("浅灰", "#D9D9D9"),
    ("中灰", "#9AA0A6"),
    ("炭灰", "#4A4A4A"),
    ("藏蓝", "#1F2A4A"),
    ("灰米", "#CFC9BD"),
    ("蓝黑", "#16213A"),
)

#: 季型 → (最佳色≥12, 避雷色≥6)，中性色按季型冷暖引用上面两档。
#: 色值为内测期规则引擎录入口径，后续统一迁至 kb_color 后此处仅作兜底。
_SEASON_COLORS: Mapping[str, tuple[tuple[tuple[str, str], ...], tuple[tuple[str, str], ...]]] = {
    "浅春": (
        (
            ("蜜桃粉", "#FFC8B4"), ("浅杏色", "#FFE0C7"), ("薄荷绿", "#B8E6C8"),
            ("浅水蓝", "#AFDDE9"), ("鹅黄", "#FFE9A8"), ("浅珊瑚", "#FFB59E"),
            ("嫩草绿", "#CFE8A9"), ("浅金棕", "#E8C79A"), ("樱花粉", "#FFD1DC"),
            ("浅松石", "#A3E0D4"), ("淡奶油", "#FFF3D6"), ("浅橙", "#FFCF9E"),
        ),
        (
            ("纯黑", "#1A1A1A"), ("炭灰", "#3A3A3A"), ("藏青", "#14213D"),
            ("酒红", "#6E1423"), ("深紫", "#3B1F47"), ("墨绿", "#1F3D2B"),
        ),
    ),
    "暖春": (
        (
            ("珊瑚橙", "#FF8C69"), ("番茄红", "#E8553D"), ("金盏菊黄", "#FFB92E"),
            ("橄榄绿", "#7A8B3D"), ("暖松石", "#2EB8A6"), ("焦糖", "#B9713B"),
            ("杏色", "#F2B880"), ("苹果绿", "#8FC45A"), ("暖粉", "#F49AC1"),
            ("蜂蜜金", "#D9A441"), ("铜色", "#B0653A"), ("暖米白", "#F7E7CE"),
        ),
        (
            ("冷灰蓝", "#708090"), ("粉紫", "#C8A2C8"), ("冰粉", "#F2D7E0"),
            ("银灰", "#C0C0C0"), ("藏蓝", "#1B2A4A"), ("冷白", "#F4F8FB"),
        ),
    ),
    "亮春": (
        (
            ("明黄", "#FFD93B"), ("亮橙", "#FF7A1A"), ("西瓜红", "#FF4D5E"),
            ("翠绿", "#1FB573"), ("湖蓝", "#1FA8C9"), ("亮松石", "#14C4B2"),
            ("亮粉", "#FF5E9C"), ("紫罗兰", "#7A4FD0"), ("柠檬黄", "#F5E642"),
            ("亮苹果绿", "#7AC74F"), ("朱红", "#E63946"), ("宝蓝", "#2B5FCE"),
        ),
        (
            ("暗驼", "#A68A64"), ("灰绿", "#8A9A5B"), ("暗玫瑰", "#A76A73"),
            ("深棕", "#4A3525"), ("灰蓝", "#6B7B8C"), ("暗紫", "#5A4A6B"),
        ),
    ),
    "浅夏": (
        (
            ("雾粉", "#F3D5DC"), ("浅薰衣草", "#D8CBE8"), ("粉蓝", "#BFD7EA"),
            ("浅玫瑰", "#E8B4C4"), ("珍珠白", "#F2F0EB"), ("浅灰绿", "#C9D8C5"),
            ("淡紫", "#CDBFE0"), ("浅青", "#BFE0E0"), ("雾蓝", "#C3D2E0"),
            ("浅桃粉", "#F6D2D8"), ("灰粉", "#E3C6CE"), ("浅蓝紫", "#BFC6E8"),
        ),
        (
            ("亮橙", "#FF7A1A"), ("明黄", "#FFD93B"), ("番茄红", "#E8553D"),
            ("翠绿", "#1FB573"), ("焦糖", "#B9713B"), ("纯黑", "#1A1A1A"),
        ),
    ),
    "柔夏": (
        (
            ("雾霾蓝", "#8FA8BF"), ("豆沙粉", "#C4909A"), ("灰玫瑰", "#B08E96"),
            ("鼠尾草绿", "#9CAF88"), ("灰紫", "#9B8AA5"), ("燕麦", "#C7BBA8"),
            ("灰松石", "#7FA8A0"), ("烟粉", "#CFA9B2"), ("蓝灰", "#7C93A8"),
            ("藕荷", "#BFA4BC"), ("灰卡其", "#A8A18C"), ("深灰玫瑰", "#96757F"),
        ),
        (
            ("明黄", "#FFD93B"), ("亮橙", "#FF7A1A"), ("西瓜红", "#FF4D5E"),
            ("翠绿", "#1FB573"), ("纯黑", "#1A1A1A"), ("亮粉", "#FF5E9C"),
        ),
    ),
    "冷夏": (
        (
            ("玫瑰粉", "#D46A92"), ("蓝调正红", "#C23B4E"), ("覆盆子", "#A62651"),
            ("天蓝", "#5B9BD5"), ("皇家蓝", "#3B5FC0"), ("冷薄荷", "#9FD8D8"),
            ("薰衣草", "#A78BC9"), ("松绿", "#2E7D6B"), ("玉兰白", "#F6F4F0"),
            ("冷粉", "#E08AAF"), ("钢蓝", "#4F7396"), ("深玫瑰", "#8E3A5B"),
        ),
        (
            ("珊瑚橙", "#FF8C69"), ("金盏菊黄", "#FFB92E"), ("焦糖", "#B9713B"),
            ("橄榄绿", "#7A8B3D"), ("番茄红", "#E8553D"), ("暖驼", "#C19A6B"),
        ),
    ),
    "柔秋": (
        (
            ("陶土", "#B4714F"), ("橄榄", "#8A8B4D"), ("芥末黄", "#C9A227"),
            ("砖红", "#A65B43"), ("灰绿", "#8FA382"), ("驼棕", "#A98A63"),
            ("暗松石", "#5F8B7E"), ("南瓜", "#C07840"), ("栗棕", "#7C5540"),
            ("暗玫瑰", "#A97E7E"), ("麦色", "#CBB37A"), ("苔绿", "#75804F"),
        ),
        (
            ("冰粉", "#F2D7E0"), ("亮蓝", "#2B5FCE"), ("纯黑", "#1A1A1A"),
            ("亮绿", "#35D07F"), ("冰紫", "#D8CBE8"), ("亮粉", "#FF5E9C"),
        ),
    ),
    "暖秋": (
        (
            ("铁锈红", "#A6472E"), ("南瓜橙", "#C77B2E"), ("深橄榄", "#6B7038"),
            ("芥末", "#B9932B"), ("深驼", "#8F6B45"), ("番茄棕", "#9C4A32"),
            ("森林绿", "#3E5E3E"), ("蜂蜜", "#C99A3C"), ("赤陶", "#B2593D"),
            ("暖棕", "#7A5236"), ("暗金", "#A8842F"), ("深松石", "#3F7A6B"),
        ),
        (
            ("冰蓝", "#BFE3F0"), ("冷粉", "#E08AAF"), ("银灰", "#C0C0C0"),
            ("薰衣草", "#A78BC9"), ("冰白", "#F4F8FB"), ("紫罗兰", "#7A4FD0"),
        ),
    ),
    "深秋": (
        (
            ("深棕", "#4A3525"), ("黑橄榄", "#4A4A26"), ("深铁锈", "#7E3B26"),
            ("墨绿", "#274435"), ("深驼", "#6B4E30"), ("深橙棕", "#8A4A24"),
            ("深酒红", "#5E2432"), ("深松绿", "#2E4A3B"), ("焦糖棕", "#7A4A28"),
            ("深芥末", "#8A7220"), ("深铜", "#6E452A"), ("黑棕", "#33261C"),
        ),
        (
            ("冰粉", "#F2D7E0"), ("浅蓝", "#BFD7EA"), ("浅薰衣草", "#D8CBE8"),
            ("珍珠白", "#F2F0EB"), ("浅灰绿", "#C9D8C5"), ("浅桃粉", "#F6D2D8"),
        ),
    ),
    "亮冬": (
        (
            ("洋红", "#D01A7A"), ("宝蓝", "#2040C8"), ("翠绿", "#0E9F6E"),
            ("正红", "#DE1A3A"), ("亮松石", "#0FA8B8"), ("柠檬黄", "#F2E13C"),
            ("紫红", "#A8126B"), ("亮蓝", "#2B7DE0"), ("纯黑", "#1A1A1A"),
            ("纯白", "#FFFFFF"), ("银灰", "#C0C0C0"), ("冰粉", "#F2A7C8"),
        ),
        (
            ("驼色", "#C19A6B"), ("芥末黄", "#C9A227"), ("橄榄绿", "#7A8B3D"),
            ("陶土", "#B4714F"), ("南瓜橙", "#C77B2E"), ("暖棕", "#7A5236"),
        ),
    ),
    "冷冬": (
        (
            ("纯黑", "#1A1A1A"), ("纯白", "#FFFFFF"), ("正红", "#C8102E"),
            ("宝石蓝", "#1D4ED8"), ("深紫红", "#7A1245"), ("冰蓝", "#A8D8F0"),
            ("冷粉", "#D86AA8"), ("翡翠绿", "#0E7A5F"), ("藏蓝", "#14264A"),
            ("银灰", "#C0C0C0"), ("紫罗兰", "#6D28A8"), ("樱桃红", "#A8123B"),
        ),
        (
            ("珊瑚橙", "#FF8C69"), ("金盏菊黄", "#FFB92E"), ("驼色", "#C19A6B"),
            ("焦糖", "#B9713B"), ("橄榄绿", "#7A8B3D"), ("暖杏", "#F2B880"),
        ),
    ),
    "深冬": (
        (
            ("黑棕", "#2B201A"), ("深酒红", "#571C2B"), ("深宝石蓝", "#1A2E6E"),
            ("深紫", "#3F1D5E"), ("墨绿", "#1E3A2E"), ("炭黑", "#141414"),
            ("深樱桃", "#6E1230"), ("深松绿", "#1F4438"), ("深灰", "#2E2E2E"),
            ("深钴蓝", "#16295C"), ("深紫红", "#4A0E33"), ("深橄榄黑", "#2E2E1A"),
        ),
        (
            ("浅杏色", "#FFE0C7"), ("鹅黄", "#FFE9A8"), ("蜜桃粉", "#FFC8B4"),
            ("浅珊瑚", "#FFB59E"), ("薄荷绿", "#B8E6C8"), ("浅金棕", "#E8C79A"),
        ),
    ),
}

#: 暖调季型集合（决定中性色引用哪一档）。
_WARM_SEASONS: frozenset[str] = frozenset(
    {"浅春", "暖春", "亮春", "柔秋", "暖秋", "深秋"}
)


def resolve_season(derived_features: Mapping[str, Any]) -> str | None:
    """派生特征 → 十二季细分名；无细分值时按四季粗判取默认细分（见 SEASON_CODE_FALLBACK）。"""
    detailed = derived_features.get("season_detailed")
    if isinstance(detailed, str) and detailed in TWELVE_SEASONS:
        return detailed
    code = derived_features.get("season_code")
    if isinstance(code, str):
        return SEASON_CODE_FALLBACK.get(code)
    return None


def palette_for(season_detailed: str) -> dict[str, list[dict[str, str]]]:
    """季型 → 结构化色板（best/neutral/avoid，每色 name+hex）。未收录季型给空板。"""
    if season_detailed not in _SEASON_COLORS:
        return {"best": [], "neutral": [], "avoid": []}
    best, avoid = _SEASON_COLORS[season_detailed]
    neutral = _NEUTRAL_WARM if season_detailed in _WARM_SEASONS else _NEUTRAL_COOL

    def entries(pairs: Sequence[tuple[str, str]]) -> list[dict[str, str]]:
        return [{"name": name, "hex": hex_value} for name, hex_value in pairs]

    return {"best": entries(best), "neutral": entries(neutral), "avoid": entries(avoid)}


# ── LLM 结构化输出 schema ──────────────────────────────────────────────────

#: 场景固定四个（需求 §2.3 篇章六：通勤职场/休闲日常/约会聚会/正式场合）。
SCENE_DEFINITIONS: tuple[tuple[str, str], ...] = (
    ("commute", "日常通勤"),
    ("weekend", "休闲周末"),
    ("formal", "正式场合"),
    ("date", "约会聚会"),
)


class FullOutfit(BaseModel):
    """一套搭配：名称 + 要点列表（上装/下装/鞋/配饰、配色、材质都在要点里）。"""

    name: str
    points: list[str]


class FullScene(BaseModel):
    """一个场景的穿搭方案包：2~3 套搭配。"""

    key: str
    title: str
    outfits: list[FullOutfit]


class PlanWeek(BaseModel):
    """30 天计划的一周：3~5 条可执行任务。"""

    week: int
    title: str
    tasks: list[str]


class FullReportCopy(BaseModel):
    """FULL_REPORT_COPY 场景的结构化输出。

    summary/sections 与 basic 的 ReportCopy 同构——ReportResultPage 与 PDF
    导出按 result.copy 渲染的部分对两种 tier 零改动；深度诊断的增量内容全在
    后三个字段，落库时进 result.full（色板由规则映射补齐，不经 LLM）。
    """

    summary: str
    sections: list[CopySection]
    season_analysis: str
    scenes: list[FullScene]
    plan30: list[PlanWeek]

    def as_report_copy(self) -> ReportCopy:
        """折成 ReportCopy 视图供生成后校验：全部自由文本都进 full_text 扫描范围。"""
        sections = list(self.sections)
        sections.append(CopySection(title="季型解析", paragraphs=[self.season_analysis]))
        for scene in self.scenes:
            paragraphs = [scene.title]
            for outfit in scene.outfits:
                paragraphs.append(outfit.name)
                paragraphs.extend(outfit.points)
            sections.append(CopySection(title=scene.title, paragraphs=paragraphs))
        for week in self.plan30:
            sections.append(CopySection(title=week.title, paragraphs=list(week.tasks)))
        return ReportCopy(summary=self.summary, sections=sections)


def build_full_result(
    copy: FullReportCopy,
    *,
    season_detailed: str | None,
    season_code: str | None,
    palette: Mapping[str, list[dict[str, str]]] | None,
) -> dict[str, Any]:
    """组装 result["full"]：LLM 内容 + 规则色板（App 按此结构渲染三个新区块）。"""
    season: dict[str, Any] = {
        "code": season_code,
        "detailed": season_detailed,
        "name_cn": f"{season_detailed}型" if season_detailed else None,
        "analysis": copy.season_analysis,
    }
    return {
        "season": season,
        "palette": dict(palette) if palette else {"best": [], "neutral": [], "avoid": []},
        "scenes": [scene.model_dump() for scene in copy.scenes],
        "plan30": [week.model_dump() for week in copy.plan30],
    }


# ── 降级模板（持续违规时的零 LLM 出口） ────────────────────────────────────

_FALLBACK_FULL_SUMMARY = (
    "以下为深度诊断内容，根据本次分析的结构化结论整理，"
    "每条结论都来自规则引擎对诊断值的直接匹配。"
)

#: 各场景的兜底搭配要点模板：{best}=最佳色名前三个、{neutral}=中性色名前两个。
#: 措辞刻意避开「建议/推荐」句式（校验规则③要求建议句有规则命中支撑，
#: 降级模板没有命中链，干脆不用建议句式——受控拼接不做超出数据的断言）。
_FALLBACK_SCENE_POINTS: Mapping[str, tuple[str, ...]] = {
    "commute": (
        "上装选{best}之一的衬衫或针织衫，下装配{neutral}直筒裤",
        "整体以{neutral}为基调，{best}之一用于内搭提亮",
        "鞋包选{neutral}，保持通勤场合的利落感",
    ),
    "weekend": (
        "上装选{best}之一的卫衣或休闲衬衫，下装配{neutral}休闲裤",
        "可用{best}之一的单品做主色，其余用{neutral}压住",
        "鞋选{neutral}休闲鞋，包袋同色系呼应",
    ),
    "formal": (
        "外套选{neutral}的西装或大衣，内搭{best}之一的衬衫",
        "下装与外套同色系，形成纵向线条",
        "配饰控制在{neutral}范围内，点缀可用{best}之一",
    ),
    "date": (
        "上装选{best}之一的针织衫或连衣裙，突出柔和气色",
        "下装配{neutral}半身裙或长裤，鞋选同色系",
        "配饰以小巧精致为先，颜色落在{best}范围内",
    ),
}

_FALLBACK_PLAN: tuple[tuple[str, tuple[str, ...]], ...] = (
    ("第 1 周：整理衣柜", (
        "把衣柜里的单品按适合色、中性色、避雷色分成三堆",
        "挑 2 件中性色基础款作为本周固定搭配底版",
        "记录本周每天穿的配色，对照色板找偏差",
    )),
    ("第 2 周：引入适合色", (
        "用适合色中的一件上衣替换惯常穿的避雷色上衣",
        "尝试「中性色为主、适合色点缀」的配色方式 3 次",
        "对照镜子确认提亮效果，记下表现出色的一件",
    )),
    ("第 3 周：场景演练", (
        "按报告里的通勤方案完整穿一次，记录感受",
        "按报告里的休闲方案穿一次周末出行搭配",
        "从配饰入手，为一套固定搭配加一件色板内的配饰",
    )),
    ("第 4 周：固化习惯", (
        "把前 3 周效果好的 3 套搭配拍照存档",
        "补齐衣柜里缺位的中性色基础款清单",
        "对照报告复盘整月变化，圈出下个月想尝试的新色",
    )),
)


def _fallback_outfit_points(key: str, palette: Mapping[str, list[dict[str, str]]]) -> list[str]:
    best = "、".join(c["name"] for c in palette.get("best", [])[:3]) or "适合色"
    neutral = "、".join(c["name"] for c in palette.get("neutral", [])[:2]) or "中性色"
    return [
        point.format(best=best, neutral=neutral)
        for point in _FALLBACK_SCENE_POINTS.get(key, ())
    ]


def render_fallback_full_copy(
    dimensions: Sequence[Any],
    *,
    season_detailed: str | None,
    palette: Mapping[str, list[dict[str, str]]] | None,
) -> FullReportCopy:
    """深度诊断降级模板：全量内容规则直出（含场景与 30 天计划），零 LLM。

    措辞纪律与 render_fallback_copy 相同——只做受控拼接、逐字复述诊断值，
    天然通过三重校验；FullValidationStage 仍会再校验一遍做 fail-close 自证。
    """
    ok_dims = [d for d in dimensions if isinstance(d, Mapping) and d.get("status") == "ok"]
    board = dict(palette) if palette else {"best": [], "neutral": [], "avoid": []}

    conclusion_paragraphs = []
    for dim in ok_dims:
        value = dim.get("value") or ""
        if isinstance(value, (list, dict)):
            continue  # 复合值不复述进段落（色板等结构化值由 full.palette 呈现）
        conclusion_paragraphs.append(f"你的{dimension_label(dim)}结论为「{value}」。")
    sections: list[CopySection] = []
    if conclusion_paragraphs:
        sections.append(CopySection(title="诊断结论", paragraphs=conclusion_paragraphs))
    else:
        sections.append(CopySection(title="说明", paragraphs=["本次分析暂无可用结论。"]))

    if season_detailed:
        season_analysis = (
            f"你的十二季色彩定位为「{season_detailed}型」。"
            f"适合色板共 {len(board.get('best', []))} 色，"
            f"中性色 {len(board.get('neutral', []))} 色，"
            f"避雷色 {len(board.get('avoid', []))} 色，完整色板见下方色卡区。"
        )
    else:
        season_analysis = "本次分析未产出十二季定位，色板区暂无内容。"

    scenes = [
        FullScene(
            key=key,
            title=title,
            outfits=[
                FullOutfit(name=f"{title} · 色板方案", points=_fallback_outfit_points(key, board))
            ],
        )
        for key, title in SCENE_DEFINITIONS
    ]
    plan30 = [
        PlanWeek(week=index + 1, title=title, tasks=list(tasks))
        for index, (title, tasks) in enumerate(_FALLBACK_PLAN)
    ]
    return FullReportCopy(
        summary=_FALLBACK_FULL_SUMMARY,
        sections=sections,
        season_analysis=season_analysis,
        scenes=scenes,
        plan30=plan30,
    )