# -*- coding: utf-8 -*-
import html
from typing import Any, Dict, List

from markupsafe import Markup

from utils.html_template_renderer import HtmlTemplateRenderer


def _escape(value: Any) -> str:
    return html.escape(str(value or ""))


def _clean_bullet_text(line: str) -> str:
    """
    统一清洗模型输出里的 bullet 前缀。
    这样做的目的有两个：
    1. 兼容 `-`、`•`、`1.` 这类常见列表格式；
    2. 让模板层只拿到干净文本，避免在 HTML 里再做重复判断。
    """
    text = str(line or "").strip()
    if not text:
        return ""
    if text.startswith("- "):
        return text[2:].strip()
    if text.startswith("•"):
        return text[1:].strip()
    if len(text) > 2 and text[0].isdigit() and text[1] in {".", "、"}:
        return text[2:].strip()
    return text


def _render_metric_card(label: str, value: Any, hint: str = "") -> str:
    return (
        '<div class="metric-card">'
        f'<div class="metric-label">{_escape(label)}</div>'
        f'<div class="metric-value">{_escape(value)}</div>'
        f'<div class="metric-hint">{_escape(hint)}</div>'
        "</div>"
    )


def _render_list(items: List[str], item_class: str = "bullet-list") -> str:
    if not items:
        return ""
    lis = "".join(f'<li>{_escape(item)}</li>' for item in items if str(item or "").strip())
    return f'<ul class="{item_class}">{lis}</ul>' if lis else ""


def _split_summary_blocks(danmu_summary: str) -> tuple[str, List[str], List[str]]:
    # 这里把 LLM 返回的弹幕总结拆成三部分：
    # 1) lead: 顶部总述段落
    # 2) insight_items: 常规的复盘要点（运营/观察视角）
    # 3) fans_extract_items: 专门给粉丝看的“弹幕萃取”要点
    # 约定：当检测到“【粉丝向弹幕萃取】”或同义标记后，后续条目归入 fans_extract_items。
    lead_parts = []
    insight_items = []
    fans_extract_items = []
    in_fans_extract_block = False
    for line in str(danmu_summary or "").splitlines():
        stripped = line.strip()
        if not stripped:
            continue
        # 兼容不同模型可能产出的标题样式，尽量把粉丝向内容稳定识别出来。
        if stripped.startswith("【粉丝向弹幕萃取】") or stripped.startswith("粉丝向弹幕萃取") or stripped.startswith("给粉丝看的弹幕萃取"):
            in_fans_extract_block = True
            continue
        if stripped.startswith("- "):
            if in_fans_extract_block:
                fans_extract_items.append(stripped[2:].strip())
            else:
                insight_items.append(stripped[2:].strip())
        else:
            # 非 bullet 文本在粉丝区块中也保留，避免模型偶发输出短段落导致信息丢失。
            if in_fans_extract_block:
                fans_extract_items.append(stripped)
            else:
                lead_parts.append(stripped)
    lead = " ".join(lead_parts).strip()
    return lead, insight_items, fans_extract_items


def _split_fans_report_blocks(report_text: str) -> Dict[str, Any]:
    """
    将“粉丝向恶搞日报”文本拆成模板需要的结构化区块。
    约定模型尽量输出如下标题：
    - 【今日笑点】
    - 【弹幕名场面】
    - 【梗王榜】
    - 【收尾播报】
    即便模型没有完全按约定输出，这里也会尽量兜底，保证页面不空。
    """
    header_alias_map = {
        "今日重点信息": "key_info",
        "重点信息": "key_info",
        "有效信息": "key_info",
        "核心讨论话题": "topic_focus",
        "讨论话题": "topic_focus",
        "核心话题": "topic_focus",
        "英雄与对局焦点": "hero_focus",
        "对局焦点": "hero_focus",
        "英雄焦点": "hero_focus",
        "今日笑点": "laugh_points",
        "笑点": "laugh_points",
        "欢乐总结": "laugh_points",
        "弹幕名场面": "famous_scenes",
        "名场面": "famous_scenes",
        "现场整活": "famous_scenes",
        "梗王榜": "meme_rank",
        "梗榜": "meme_rank",
        "复读冠军": "meme_rank",
        "收尾播报": "closing",
        "结尾播报": "closing",
        "结尾": "closing",
    }
    sections = {
        "lead": "",
        "key_info": [],
        "topic_focus": [],
        "hero_focus": [],
        "laugh_points": [],
        "famous_scenes": [],
        "meme_rank": [],
        "closing": [],
    }
    current_key = "lead"
    lead_parts: List[str] = []

    for raw_line in str(report_text or "").splitlines():
        stripped = raw_line.strip()
        if not stripped:
            continue
        normalized_title = stripped.strip("【】:#： ").replace("：", "").replace(":", "")
        if normalized_title in header_alias_map:
            current_key = header_alias_map[normalized_title]
            continue
        clean_text = _clean_bullet_text(stripped)
        if not clean_text:
            continue
        if current_key == "lead":
            lead_parts.append(clean_text)
        else:
            sections[current_key].append(clean_text)

    sections["lead"] = " ".join(lead_parts).strip()
    return sections


def _normalize_summary_bullets(payload: Dict[str, Any], items: List[str], target_count: int = 5) -> List[str]:
    normalized = [str(item or "").strip() for item in items if str(item or "").strip()]
    if len(normalized) >= target_count:
        return normalized[:target_count]

    top_terms = [str(item.get("term") or "").strip() for item in (payload.get("top_terms", []) or []) if str(item.get("term") or "").strip()]
    merged_templates = [str(item.get("text") or "").strip() for item in (payload.get("merged_templates", []) or []) if str(item.get("text") or "").strip()]
    peak_buckets = payload.get("peak_buckets", []) or []
    representative_messages = payload.get("representative_messages", []) or []

    supplements: List[str] = []
    if top_terms:
        supplements.append(f"讨论焦点比较集中，弹幕反复围绕 {'、'.join(top_terms[:5])} 展开。")
    if merged_templates:
        sample_templates = "；".join(text[:24] for text in merged_templates[:3])
        supplements.append(f"复读和共识梗比较强，重复内容主要集中在 {sample_templates}。")
    if peak_buckets:
        top_bucket = peak_buckets[0]
        bucket_terms = [str(term.get('term') or '').strip() for term in (top_bucket.get("top_terms", []) or []) if str(term.get('term') or '').strip()]
        if bucket_terms:
            supplements.append(
                f"高峰时段出现在 {str(top_bucket.get('start_time') or '')[-8:-3]} 前后，话题明显偏向 {'、'.join(bucket_terms[:4])}。"
            )
    if representative_messages:
        supplements.append("代表性发言里既有操作反馈，也有玩梗调侃和情绪宣泄，互动意愿比较强。")

    existing = set(normalized)
    for item in supplements:
        if item not in existing:
            normalized.append(item)
            existing.add(item)
        if len(normalized) >= target_count:
            break
    return normalized[:target_count]


def _normalize_fans_extract_bullets(payload: Dict[str, Any], items: List[str], target_count: int = 6) -> List[str]:
    # 粉丝向萃取强调“现场感”，优先保留模型给出的条目；
    # 不足时再从代表弹幕/重复梗中补齐，避免页面出现空区块。
    normalized = [str(item or "").strip() for item in items if str(item or "").strip()]
    if len(normalized) >= target_count:
        return normalized[:target_count]

    supplements: List[str] = []
    representative_messages = payload.get("representative_messages", []) or []
    repeated_messages = payload.get("repeated_messages", []) or []
    burst_terms = payload.get("burst_terms", []) or []

    for item in representative_messages[:8]:
        nickname = str(item.get("nickname") or "").strip() or "观众"
        content = str(item.get("content") or "").strip()
        if not content:
            continue
        supplements.append(f"{nickname}：{content[:46]}")

    for item in repeated_messages[:6]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            supplements.append(f"复读梗「{text[:34]}」出现 {count} 次。")

    for item in burst_terms[:4]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            supplements.append(f"情绪短词「{text}」集中刷了 {count} 次。")

    existing = set(normalized)
    for item in supplements:
        if item not in existing:
            normalized.append(item)
            existing.add(item)
        if len(normalized) >= target_count:
            break
    return normalized[:target_count]


def _normalize_funny_bullets(payload: Dict[str, Any], items: List[str], target_count: int = 4) -> List[str]:
    """
    “今日笑点”优先保留模型自己写的梗概；
    如果模型输出偏保守，就从高频梗、爆发词里补出几条更有现场感的句子。
    """
    normalized = [str(item or "").strip() for item in items if str(item or "").strip()]
    if len(normalized) >= target_count:
        return normalized[:target_count]

    supplements: List[str] = []
    for item in (payload.get("merged_templates", []) or [])[:4]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            supplements.append(f"同一句梗反复刷了 {count} 次，直播间默认进入复读机模式：{text[:30]}。")

    for item in (payload.get("burst_terms", []) or [])[:4]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            supplements.append(f"情绪词「{text}」高频刷屏 {count} 次，说明这一段大家已经集体上头。")

    existing = set(normalized)
    for item in supplements:
        if item not in existing:
            normalized.append(item)
            existing.add(item)
        if len(normalized) >= target_count:
            break
    return normalized[:target_count]


def _normalize_scene_bullets(payload: Dict[str, Any], items: List[str], target_count: int = 5) -> List[str]:
    """
    “弹幕名场面”强调像直播间回放，因此优先从代表弹幕中补句子，
    让最终成品看起来更像观众之间的接龙，而不是纯数据总结。
    """
    normalized = [str(item or "").strip() for item in items if str(item or "").strip()]
    if len(normalized) >= target_count:
        return normalized[:target_count]

    supplements: List[str] = []
    for item in (payload.get("representative_messages", []) or [])[:10]:
        nickname = str(item.get("nickname") or "").strip() or "观众"
        content = str(item.get("content") or "").strip()
        if content:
            supplements.append(f"{nickname}：{content[:42]}")

    existing = set(normalized)
    for item in supplements:
        if item not in existing:
            normalized.append(item)
            existing.add(item)
        if len(normalized) >= target_count:
            break
    return normalized[:target_count]


def _normalize_rank_bullets(payload: Dict[str, Any], items: List[str], target_count: int = 3) -> List[str]:
    """
    “梗王榜”兜底来源按优先级走：
    1. 已聚合的长模板梗；
    2. 重复短句；
    3. 爆发情绪词。
    这样即便模型漏写榜单，页面也能稳定展示“今天到底大家在刷什么”。
    """
    normalized = [str(item or "").strip() for item in items if str(item or "").strip()]
    if len(normalized) >= target_count:
        return normalized[:target_count]

    supplements: List[str] = []
    for item in (payload.get("merged_templates", []) or [])[:3]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            supplements.append(f"{text[:30]}｜全场 {count} 次")

    for item in (payload.get("repeated_messages", []) or [])[:3]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            supplements.append(f"{text[:30]}｜复读 {count} 次")

    for item in (payload.get("burst_terms", []) or [])[:3]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            supplements.append(f"{text}｜情绪爆发 {count} 次")

    existing = set(normalized)
    for item in supplements:
        if item not in existing:
            normalized.append(item)
            existing.add(item)
        if len(normalized) >= target_count:
            break
    return normalized[:target_count]


def _normalize_closing_text(payload: Dict[str, Any], closing_items: List[str]) -> str:
    """
    收尾句只有一句，优先保留模型原话；
    如果模型没给，就用当天最高峰时段和热词拼一个轻松结尾。
    """
    for item in closing_items:
        value = str(item or "").strip()
        if value:
            return value

    peak_buckets = payload.get("peak_buckets", []) or []
    if peak_buckets:
        top_bucket = peak_buckets[0]
        top_terms = [
            str(term.get("term") or "").strip()
            for term in (top_bucket.get("top_terms", []) or [])[:3]
            if str(term.get("term") or "").strip()
        ]
        return (
            f"今晚最佳观影时段锁定 {str(top_bucket.get('start_time') or '')[-8:-3]}，"
            f"大家围着 {'、'.join(top_terms) or '节目效果'} 一起起哄，收工时空气里都还是梗。"
        )
    return "今天的直播结论很简单：操作未必全记住了，但弹幕梗已经自动住进群友脑回路。"


def _build_template_items(payload: Dict[str, Any], limit: int = 8) -> List[str]:
    items: List[str] = []
    seen = set()

    def push(text: str, suffix: str = "") -> None:
        value = str(text or "").strip()
        if not value:
            return
        normalized_key = value
        if normalized_key in seen:
            return
        seen.add(normalized_key)
        items.append(f"{value}{suffix}".strip())

    for item in (payload.get("merged_templates", []) or [])[:6]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            push(text[:72], f"（{count}次）")

    for item in (payload.get("repeated_messages", []) or [])[:6]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            push(text[:72], f"（{count}次）")

    for item in (payload.get("burst_terms", []) or [])[:6]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            push(text[:36], f"（爆发 {count} 次）")

    for item in (payload.get("top_terms", []) or [])[:6]:
        term = str(item.get("term") or "").strip()
        count = int(item.get("count", 0) or 0)
        if term:
            push(term, f"（{count}次提及）")

    return items[:limit]


def _render_insight_cards(items: List[str]) -> str:
    labels = ["主线", "情绪", "梗点", "节奏", "反馈", "补充"]
    blocks = []
    for idx, item in enumerate(items[:6]):
        extra_class = " full-span" if len(items[:6]) % 2 == 1 and idx == len(items[:6]) - 1 else ""
        blocks.append(
            f'<div class="insight-card{extra_class}">'
            f'<div class="insight-kicker">{_escape(labels[idx] if idx < len(labels) else "观察")}</div>'
            f'<div class="insight-text">{_escape(item)}</div>'
            "</div>"
        )
    return "".join(blocks)


def _render_fans_scene_cards(items: List[str]) -> str:
    blocks = []
    for item in items[:6]:
        blocks.append(
            '<div class="fans-scene-card">'
            f'<div class="fans-scene-quote">{_escape(item)}</div>'
            "</div>"
        )
    return "".join(blocks)


def _render_rank_cards(items: List[str]) -> str:
    blocks = []
    for idx, item in enumerate(items[:3], start=1):
        blocks.append(
            '<div class="meme-rank-card">'
            f'<div class="meme-rank-no">TOP {idx}</div>'
            f'<div class="meme-rank-text">{_escape(item)}</div>'
            "</div>"
        )
    return "".join(blocks)


def _build_fans_fun_metrics(payload: Dict[str, Any]) -> List[Dict[str, str]]:
    """
    粉丝版避免直接沿用“运营指标”命名，改成更轻松的展示口径。
    底层仍然来自同一份 payload，所以既分风格，又不损失真实性。
    """
    meta = payload.get("report_meta", {}) or {}
    peak_buckets = payload.get("peak_buckets", []) or []
    repeated_messages = payload.get("repeated_messages", []) or []
    burst_terms = payload.get("burst_terms", []) or []
    top_bucket = peak_buckets[0] if peak_buckets else {}
    top_repeat = repeated_messages[0] if repeated_messages else {}
    top_burst = burst_terms[0] if burst_terms else {}
    return [
        {
            "label": "今日弹幕量",
            "value": str(meta.get("message_count", 0) or 0),
            "hint": "今天一共刷了多少句",
        },
        {
            "label": "围观群众",
            "value": str(meta.get("unique_user_count", 0) or 0),
            "hint": "参与一起起哄的人数",
        },
        {
            "label": "最高能时段",
            "value": str(top_bucket.get("start_time") or "")[-8:-3] or "--:--",
            "hint": "弹幕最炸裂的时间点",
        },
        {
            "label": "今日爆词",
            "value": str(top_burst.get("text") or top_repeat.get("text") or "乐"),
            "hint": "刷得最凶的那句",
        },
    ]


def _render_fans_metric_cards(metrics: List[Dict[str, str]]) -> str:
    blocks = []
    for item in metrics:
        blocks.append(
            '<div class="fans-metric-card">'
            f'<div class="fans-metric-label">{_escape(item.get("label", ""))}</div>'
            f'<div class="fans-metric-value">{_escape(item.get("value", ""))}</div>'
            f'<div class="fans-metric-hint">{_escape(item.get("hint", ""))}</div>'
            "</div>"
        )
    return "".join(blocks)


def _get_compact_scene_material(payload: Dict[str, Any]) -> Dict[str, Any]:
    """
    兼容两种来源的粉丝日报载荷：
    1. 新版 prompt 材料已经预先组装好的 compact_scene_material；
    2. 正式渲染链路里仍然保留在 llm_compact 下的压缩材料。
    这样模板层可以向后兼容，不会因为字段尚未完全迁移就出现空版块。
    """
    compact = payload.get("compact_scene_material", {}) or {}
    if compact:
        return compact
    return payload.get("llm_compact", {}) or {}


def _get_topic_evidence_clusters(payload: Dict[str, Any]) -> List[Dict[str, Any]]:
    """
    兼容“已展开主题簇”和“仍放在 llm_compact.semantic_fact_hints.topic_clusters”两种结构。
    """
    clusters = payload.get("topic_evidence_clusters", []) or []
    if clusters:
        return clusters
    compact = _get_compact_scene_material(payload)
    fact_hints = compact.get("semantic_fact_hints", {}) or {}
    normalized = []
    for item in (fact_hints.get("topic_clusters", []) or [])[:6]:
        normalized.append({
            "label": str(item.get("label") or "").strip(),
            "count": int(item.get("match_count", item.get("count", 0)) or 0),
            "user_count": int(item.get("user_count", 0) or 0),
            "time_range": (
                f"{str(item.get('first_hm') or '').strip()}-{str(item.get('last_hm') or '').strip()}"
            ).strip("-"),
            "keywords": item.get("keywords", []) or [],
            "samples": item.get("samples", []) or [],
        })
    return normalized


def _get_hero_mentions(payload: Dict[str, Any]) -> List[Dict[str, Any]]:
    compact = _get_compact_scene_material(payload)
    return (
        compact.get("semantic_fact_hints", {})
        .get("hero_mentions", [])
        or []
    )


def _build_local_stats(payload: Dict[str, Any]) -> Dict[str, Any]:
    """
    兼容新旧载荷的本地统计字段。
    如果没有 top-level local_stats，就从 peak_buckets / repeated_messages / burst_terms / content_cues 临时拼一份，
    保证“热点窗口与共识梗”始终有内容可用。
    """
    local_stats = payload.get("local_stats", {}) or {}
    if local_stats:
        return local_stats

    compact = _get_compact_scene_material(payload)
    content_cues = compact.get("content_cues", []) or []
    return {
        "message_count": int((payload.get("report_meta", {}) or {}).get("message_count", 0) or 0),
        "unique_user_count": int((payload.get("report_meta", {}) or {}).get("unique_user_count", 0) or 0),
        "top_emotion_bursts": [
            {
                "text": str(item.get("text") or "").strip(),
                "count": int(item.get("count", 0) or 0),
            }
            for item in content_cues
            if str(item.get("kind") or "").strip() == "emotion" and str(item.get("text") or "").strip()
        ][:8],
        "top_repeated_messages": [
            {
                "text": str(item.get("text") or "").strip(),
                "count": int(item.get("count", 0) or 0),
                "user_count": int(item.get("user_count", 0) or 0),
            }
            for item in (payload.get("repeated_messages", []) or [])[:8]
            if str(item.get("text") or "").strip()
        ],
        "peak_windows": [
            {
                "start_time": str(item.get("start_time") or "").strip(),
                "message_count": int(item.get("message_count", 0) or 0),
                "user_count": int(item.get("user_count", 0) or 0),
            }
            for item in (payload.get("peak_buckets", []) or [])[:6]
        ],
    }


def _build_fans_effective_info_lines(payload: Dict[str, Any], limit: int = 6) -> List[str]:
    """
    为粉丝日报补一层“有效信息速览”。
    这里优先从本地提纯后的主题证据簇中拿事实，不依赖 LLM 自己归纳，
    这样模板本身就能稳定承载更多有效信息。
    """
    lines: List[str] = []
    seen = set()

    def push(text: str) -> None:
        value = str(text or "").strip()
        if not value or value in seen:
            return
        seen.add(value)
        lines.append(value)

    for item in _get_topic_evidence_clusters(payload)[:6]:
        label = str(item.get("label") or "").strip()
        count = int(item.get("count", 0) or 0)
        time_range = str(item.get("time_range") or "").strip()
        samples = item.get("samples", []) or []
        sample_text = ""
        if samples:
            first_sample = samples[0]
            sample_text = str(first_sample.get("content") or "").strip()[:42]
        if label and sample_text:
            push(f"{label}在 {time_range or '全场'} 持续被讨论，相关弹幕约 {count} 条，代表内容是「{sample_text}」。")
        elif label:
            push(f"{label}是今天的高关注话题之一，相关弹幕约 {count} 条。")
        if len(lines) >= limit:
            return lines[:limit]

    hero_mentions = _get_hero_mentions(payload)
    if hero_mentions:
        hero_names = [str(item.get("hero") or "").strip() for item in hero_mentions[:4] if str(item.get("hero") or "").strip()]
        if hero_names:
            push(f"英雄讨论主要集中在 {'、'.join(hero_names)}。")

    hot_windows = _build_local_stats(payload).get("peak_windows", []) or []
    if hot_windows:
        top_window = hot_windows[0]
        push(
            f"最热窗口出现在 {str(top_window.get('start_time') or '')[-8:-3]}，"
            f"该时段累计弹幕 {int(top_window.get('message_count', 0) or 0)} 条。"
        )
    return lines[:limit]


def _build_local_topic_focus_lines(payload: Dict[str, Any], limit: int = 4) -> List[str]:
    """
    为“核心讨论话题”补充本地可直接确定的摘要句。
    这里故意不让模型自己重新发明事实，而是把主题簇已经聚好的结果转成人能读懂的话。
    """
    lines: List[str] = []
    seen = set()

    def push(text: str) -> None:
        value = str(text or "").strip()
        if not value or value in seen:
            return
        seen.add(value)
        lines.append(value)

    for item in _get_topic_evidence_clusters(payload)[:4]:
        label = str(item.get("label") or "").strip()
        keywords = [str(keyword).strip() for keyword in (item.get("keywords", []) or [])[:5] if str(keyword).strip()]
        count = int(item.get("count", 0) or 0)
        if label and keywords:
            push(f"{label}是高频主线，相关讨论约 {count} 条，关键词集中在 {'、'.join(keywords)}。")
        elif label:
            push(f"{label}是今天反复被拉出来聊的主线之一，相关讨论约 {count} 条。")
        if len(lines) >= limit:
            return lines[:limit]
    return lines[:limit]


def _build_local_hero_focus_lines(payload: Dict[str, Any], limit: int = 4) -> List[str]:
    """
    为“英雄与对局焦点”准备本地兜底。
    这部分直接复用英雄提及聚类，优先强调出现频次和代表发言，方便粉丝快速看懂今天在聊什么英雄。
    """
    hero_mentions = _get_hero_mentions(payload)
    lines: List[str] = []
    seen = set()

    def push(text: str) -> None:
        value = str(text or "").strip()
        if not value or value in seen:
            return
        seen.add(value)
        lines.append(value)

    for item in hero_mentions[:4]:
        hero_name = str(item.get("hero") or "").strip()
        mention_count = int(item.get("mention_count", 0) or 0)
        samples = item.get("samples", []) or []
        sample_text = ""
        if samples:
            sample_text = str(samples[0].get("content") or "").strip()[:36]
        if hero_name and sample_text:
            push(f"{hero_name}被提到 {mention_count} 次，现场典型弹幕是「{sample_text}」。")
        elif hero_name:
            push(f"{hero_name}是今天的主要英雄讨论点之一，被提到 {mention_count} 次。")
        if len(lines) >= limit:
            return lines[:limit]
    return lines[:limit]


def _normalize_information_section_items(
    llm_items: List[str],
    local_items: List[str],
    target_count: int,
) -> List[str]:
    """
    将模型提炼结果与本地事实兜底合并。
    设计目标：
    1. 先尊重模型已经总结好的“可读句子”；
    2. 如果模型漏了，就用本地证据补足；
    3. 始终保证最终区块有信息量，而不是空标题。
    """
    normalized: List[str] = []
    seen = set()
    for source in (llm_items, local_items):
        for item in source:
            value = str(item or "").strip()
            if not value or value in seen:
                continue
            seen.add(value)
            normalized.append(value)
            if len(normalized) >= target_count:
                return normalized[:target_count]
    return normalized[:target_count]


def _render_fans_info_cards(items: List[str]) -> str:
    blocks = []
    for item in items[:6]:
        blocks.append(
            '<div class="fans-info-card">'
            f'<div class="fans-info-text">{_escape(item)}</div>'
            '</div>'
        )
    return "".join(blocks)


def _render_topic_clusters(topic_clusters: List[Dict[str, Any]]) -> str:
    blocks = []
    for item in topic_clusters[:5]:
        label = str(item.get("label") or "").strip()
        if not label:
            continue
        count = int(item.get("count", 0) or 0)
        user_count = int(item.get("user_count", 0) or 0)
        time_range = str(item.get("time_range") or "").strip()
        samples = item.get("samples", []) or []
        sample_lines = []
        for sample in samples[:3]:
            content = str(sample.get("content") or "").strip()
            nickname = str(sample.get("nickname") or "").strip() or "观众"
            hm = str(sample.get("hm") or "").strip()
            if content:
                sample_lines.append(f"{hm} {nickname}：{content[:42]}")
        sample_html = "".join(f'<li>{_escape(line)}</li>' for line in sample_lines)
        blocks.append(
            '<div class="topic-cluster-card">'
            f'<div class="topic-cluster-title">{_escape(label)}</div>'
            f'<div class="topic-cluster-meta">{_escape(time_range or "全场")} · {count} 条讨论 · {user_count} 人参与</div>'
            f'<ul class="topic-cluster-list">{sample_html}</ul>'
            '</div>'
        )
    return "".join(blocks)


def _render_hero_mentions(hero_mentions: List[Dict[str, Any]]) -> str:
    blocks = []
    for item in hero_mentions[:4]:
        hero_name = str(item.get("hero") or "").strip()
        if not hero_name:
            continue
        mention_count = int(item.get("mention_count", 0) or 0)
        user_count = int(item.get("user_count", 0) or 0)
        sample_text = ""
        samples = item.get("samples", []) or []
        if samples:
            sample = samples[0]
            sample_text = str(sample.get("content") or "").strip()[:46]
        blocks.append(
            '<div class="hero-mention-card">'
            f'<div class="hero-mention-name">{_escape(hero_name)}</div>'
            f'<div class="hero-mention-meta">{mention_count} 次提及 / {user_count} 人讨论</div>'
            f'<div class="hero-mention-sample">{_escape(sample_text)}</div>'
            '</div>'
        )
    return "".join(blocks)


def _render_hot_window_cards(hot_windows: List[Dict[str, Any]]) -> str:
    blocks = []
    for item in hot_windows[:4]:
        start_time = str(item.get("start_time") or "")[-8:-3]
        message_count = int(item.get("message_count", 0) or 0)
        user_count = int(item.get("user_count", 0) or 0)
        blocks.append(
            '<div class="fans-hot-window-card">'
            f'<div class="fans-hot-window-time">{_escape(start_time)}</div>'
            f'<div class="fans-hot-window-meta">{message_count} 条弹幕 / {user_count} 人参与</div>'
            '</div>'
        )
    # 页面层兜底：
    # 如果热窗没有任何卡片，也返回一个说明块，避免整个区域看起来像渲染坏了。
    if not blocks:
        blocks.append(
            '<div class="fans-hot-window-card">'
            '<div class="fans-hot-window-time">--:--</div>'
            '<div class="fans-hot-window-meta">当前载荷里没有可展示的热点窗口数据</div>'
            '</div>'
        )
    return "".join(blocks)


def _render_repeat_digest(payload: Dict[str, Any]) -> str:
    local_stats = _build_local_stats(payload)
    repeated_messages = local_stats.get("top_repeated_messages", []) or []
    emotion_bursts = local_stats.get("top_emotion_bursts", []) or []
    blocks = []
    for item in repeated_messages[:4]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            blocks.append(
                '<div class="repeat-chip">'
                f'<span class="repeat-chip-text">{_escape(text[:28])}</span>'
                f'<span class="repeat-chip-count">{count} 次</span>'
                '</div>'
            )
    for item in emotion_bursts[:4]:
        text = str(item.get("text") or "").strip()
        count = int(item.get("count", 0) or 0)
        if text:
            blocks.append(
                '<div class="repeat-chip emotion">'
                f'<span class="repeat-chip-text">{_escape(text[:18])}</span>'
                f'<span class="repeat-chip-count">{count} 次</span>'
                '</div>'
            )
    if not blocks:
        blocks.append(
            '<div class="repeat-chip">'
            '<span class="repeat-chip-text">暂无共识梗数据</span>'
            '<span class="repeat-chip-count">0 次</span>'
            '</div>'
        )
    return "".join(blocks)


def _render_badges(top_badges: List[Dict[str, Any]]) -> str:
    blocks = []
    for item in top_badges[:6]:
        badge_name = str(item.get("badge_name") or "").strip()
        if not badge_name:
            continue
        blocks.append(
            '<div class="badge-chip">'
            f'<span class="badge-name">{_escape(badge_name)}</span>'
            f'<span class="badge-meta">{_escape(item.get("user_count", 0))}人 / {_escape(item.get("message_count", 0))}条</span>'
            "</div>"
        )
    return "".join(blocks)


def _render_hot_times(peak_buckets: List[Dict[str, Any]]) -> str:
    blocks = []
    for item in peak_buckets[:3]:
        start_time = str(item.get("start_time") or "")[-8:-3]
        terms = [str(term.get("term") or "").strip() for term in (item.get("top_terms", []) or [])[:4]]
        terms = [term for term in terms if term]
        blocks.append(
            '<div class="hot-card">'
            f'<div class="hot-time">{_escape(start_time)}</div>'
            f'<div class="hot-count">{_escape(item.get("message_count", 0))} 条弹幕</div>'
            f'<div class="hot-terms">{_escape(" / ".join(terms))}</div>'
            "</div>"
        )
    return "".join(blocks)


def _render_active_users(top_active_users: List[Dict[str, Any]]) -> str:
    blocks = []
    for item in top_active_users[:10]:
        nickname = str(item.get("nickname") or item.get("uid") or "").strip()
        fans_name = str(item.get("fans_name") or "").strip()
        fans_level = int(item.get("fans_level", 0) or 0)
        room_level = int(item.get("room_level", 0) or 0)
        message_count = int(item.get("message_count", 0) or 0)

        chips = []
        if fans_name:
            fans_label = f"{fans_name} Lv{fans_level}" if fans_level > 0 else fans_name
            chips.append(f'<span class="user-chip fans">{_escape(fans_label)}</span>')
        if room_level > 0:
            chips.append(f'<span class="user-chip room">{_escape(f"平台 Lv{room_level}")}</span>')
        meta_html = "".join(chips) if chips else '<span class="user-chip plain">普通观众</span>'

        blocks.append(
            '<div class="active-user-card">'
            '<div class="active-user-top">'
            f'<div class="active-user-name">{_escape(nickname)}</div>'
            f'<div class="active-user-count">{_escape(message_count)}<span>条</span></div>'
            '</div>'
            f'<div class="active-user-meta">{meta_html}</div>'
            '</div>'
        )
    return "".join(blocks)


def _render_audience_trend_chart(audience_trend: Dict[str, Any]) -> str:
    points = audience_trend.get("points", []) or []
    if len(points) < 2:
        return (
            '<div class="chart-empty">'
            '<div class="chart-empty-title">人数趋势</div>'
            '<div class="chart-empty-desc">当前直播场次还没有足够的 WS 采样点，暂时无法绘制趋势图。</div>'
            '</div>'
        )

    width = 820
    height = 276
    padding_left = 62
    padding_right = 64
    padding_top = 24
    padding_bottom = 38
    plot_width = width - padding_left - padding_right
    plot_height = height - padding_top - padding_bottom

    summary = audience_trend.get("summary", {}) or {}

    def _compress_chart_points(raw_points: List[Dict[str, Any]], max_points: int = 36) -> List[Dict[str, Any]]:
        if len(raw_points) <= max_points:
            return list(raw_points)
        bucket_size = max(len(raw_points) / max_points, 1)
        compressed: List[Dict[str, Any]] = []
        for idx in range(max_points):
            start = int(round(idx * bucket_size))
            end = int(round((idx + 1) * bucket_size))
            bucket = raw_points[start:end] or raw_points[start:start + 1]
            if not bucket:
                continue
            compressed.append(dict(bucket[-1]))
        first = raw_points[0]
        last = raw_points[-1]
        if compressed:
            compressed[0] = dict(first)
            compressed[-1] = dict(last)
        return compressed

    chart_points = _compress_chart_points(points, max_points=36)
    vip_values = [int(item.get("vip_count", 0) or 0) for item in chart_points]
    diamond_values = [int(item.get("diamond_count", 0) or 0) for item in chart_points]
    labels = [str(item.get("timestamp") or "")[-8:-3] for item in chart_points]

    vip_min = min(vip_values)
    vip_max = max(vip_values)
    diamond_min = min(diamond_values)
    diamond_max = max(diamond_values)
    vip_padding = max(int((vip_max - vip_min) * 0.12), 60)
    diamond_padding = 1 if diamond_max - diamond_min <= 2 else max(int((diamond_max - diamond_min) * 0.2), 1)
    vip_display_min = max(vip_min - vip_padding, 0)
    vip_display_max = vip_max + vip_padding
    diamond_display_min = max(diamond_min - diamond_padding, 0)
    diamond_display_max = diamond_max + diamond_padding
    vip_span = max(vip_display_max - vip_display_min, 1)
    diamond_span = max(diamond_display_max - diamond_display_min, 1)
    step_x = plot_width / max(len(chart_points) - 1, 1)
    bar_width = max(min(step_x * 0.58, 18), 6)

    def x_at(index: int) -> float:
        return padding_left + step_x * index

    def y_vip(value: int) -> float:
        ratio = (value - vip_display_min) / vip_span if vip_span else 0
        return padding_top + plot_height - ratio * plot_height

    def y_diamond(value: int) -> float:
        ratio = (value - diamond_display_min) / diamond_span if diamond_span else 0
        return padding_top + plot_height - ratio * plot_height

    grid_lines = []
    left_ticks = []
    right_ticks = []
    for idx in range(5):
        ratio = idx / 4
        y = padding_top + plot_height - ratio * plot_height
        vip_tick = round(vip_display_min + vip_span * ratio)
        diamond_tick = round(diamond_display_min + diamond_span * ratio)
        grid_lines.append(
            f'<line x1="{padding_left}" y1="{y:.1f}" x2="{width - padding_right}" y2="{y:.1f}" class="chart-grid" />'
        )
        left_ticks.append(
            f'<text x="{padding_left - 10}" y="{y + 4:.1f}" text-anchor="end" class="axis-label axis-left">{vip_tick}</text>'
        )
        right_ticks.append(
            f'<text x="{width - padding_right + 10}" y="{y + 4:.1f}" text-anchor="start" class="axis-label axis-right">{diamond_tick}</text>'
        )

    bars = []
    line_points = []
    dot_points = []
    label_marks = []
    annotations = []
    if len(chart_points) <= 12:
        label_indexes = list(range(len(chart_points)))
    else:
        label_indexes = sorted(set([0, len(chart_points) - 1] + [int(round((len(chart_points) - 1) * i / 6)) for i in range(1, 6)]))
    vip_peak_index = vip_values.index(vip_max)
    vip_valley_index = vip_values.index(vip_min)
    diamond_latest_index = len(chart_points) - 1
    for idx, item in enumerate(chart_points):
        x = x_at(idx)
        vip_y = y_vip(int(item.get("vip_count", 0) or 0))
        diamond_y = y_diamond(int(item.get("diamond_count", 0) or 0))
        bar_height = padding_top + plot_height - vip_y
        bars.append(
            f'<rect x="{x - bar_width / 2:.1f}" y="{vip_y:.1f}" width="{bar_width:.1f}" height="{bar_height:.1f}" rx="7" class="vip-bar" />'
        )
        line_points.append(f"{x:.1f},{diamond_y:.1f}")
        dot_points.append(f'<circle cx="{x:.1f}" cy="{diamond_y:.1f}" r="3.5" class="diamond-dot" />')
        if idx in label_indexes:
            label_marks.append(
                f'<text x="{x:.1f}" y="{height - 16}" text-anchor="middle" class="time-label">{_escape(labels[idx])}</text>'
            )
        if idx == vip_peak_index:
            annotations.append(
                f'<g class="chart-annotation">'
                f'<text x="{x:.1f}" y="{max(vip_y - 16, 18):.1f}" text-anchor="middle" class="value-label vip">峰值 {vip_max}</text>'
                f'<text x="{x:.1f}" y="{max(vip_y - 2, 30):.1f}" text-anchor="middle" class="value-sub-label vip">{_escape(labels[idx])}</text>'
                f'</g>'
            )
        elif idx == vip_valley_index and vip_min != vip_max:
            annotations.append(
                f'<g class="chart-annotation">'
                f'<text x="{x:.1f}" y="{min(vip_y + 18, padding_top + plot_height - 18):.1f}" text-anchor="middle" class="value-label vip soft">低点 {vip_min}</text>'
                f'<text x="{x:.1f}" y="{min(vip_y + 32, padding_top + plot_height - 6):.1f}" text-anchor="middle" class="value-sub-label vip soft">{_escape(labels[idx])}</text>'
                f'</g>'
            )
        if idx == diamond_latest_index:
            annotations.append(
                f'<g class="chart-annotation">'
                f'<text x="{min(x + 10, width - padding_right - 6):.1f}" y="{max(diamond_y - 14, 18):.1f}" text-anchor="start" class="value-label diamond">最新 {int(item.get("diamond_count", 0) or 0)}</text>'
                f'<text x="{min(x + 10, width - padding_right - 6):.1f}" y="{max(diamond_y, 30):.1f}" text-anchor="start" class="value-sub-label diamond">{_escape(labels[idx])}</text>'
                f'</g>'
            )

    polyline = f'<polyline points="{" ".join(line_points)}" class="diamond-line" />'
    vip_latest = int(summary.get("vip_latest", vip_values[-1]) or 0)
    diamond_latest = int(summary.get("diamond_latest", diamond_values[-1]) or 0)
    session_start = str(summary.get("session_start") or "")
    first_point_time = str(summary.get("first_point_time") or "")
    leading_gap_minutes = int(summary.get("leading_gap_minutes", 0) or 0)
    note_text = ""
    if session_start and first_point_time and leading_gap_minutes >= 20:
        note_text = f"采样起点 {first_point_time[-8:-3]}，早于该时段的人数数据未记录"

    return f"""
    <div class="chart-wrap">
        <div class="chart-head">
            <div class="chart-title">贵宾 / 钻粉趋势</div>
            <div class="chart-legend">
                <span class="legend-item"><span class="legend-swatch vip"></span>贵宾柱状</span>
                <span class="legend-item"><span class="legend-swatch diamond"></span>钻粉折线</span>
                <span class="legend-meta">最新：贵宾 {_escape(vip_latest)} / 钻粉 {_escape(diamond_latest)}</span>
            </div>
        </div>
        {'<div class="chart-note">' + _escape(note_text) + '</div>' if note_text else ''}
        <svg viewBox="0 0 {width} {height}" class="audience-chart" role="img" aria-label="贵宾与钻粉趋势图">
            <defs>
                <linearGradient id="vipBarGradient" x1="0" y1="0" x2="0" y2="1">
                    <stop offset="0%" stop-color="#2b59ff" stop-opacity="0.95" />
                    <stop offset="100%" stop-color="#7aa2ff" stop-opacity="0.72" />
                </linearGradient>
                <linearGradient id="diamondLineGradient" x1="0" y1="0" x2="1" y2="0">
                    <stop offset="0%" stop-color="#f59e0b" />
                    <stop offset="100%" stop-color="#ffd166" />
                </linearGradient>
            </defs>
            <rect x="0" y="0" width="{width}" height="{height}" rx="24" class="chart-bg" />
            {''.join(grid_lines)}
            <line x1="{padding_left}" y1="{padding_top + plot_height:.1f}" x2="{width - padding_right}" y2="{padding_top + plot_height:.1f}" class="chart-axis" />
            <line x1="{padding_left}" y1="{padding_top}" x2="{padding_left}" y2="{padding_top + plot_height:.1f}" class="chart-axis soft" />
            <line x1="{width - padding_right}" y1="{padding_top}" x2="{width - padding_right}" y2="{padding_top + plot_height:.1f}" class="chart-axis soft" />
            {''.join(left_ticks)}
            {''.join(right_ticks)}
            {''.join(bars)}
            {polyline}
            {''.join(dot_points)}
            {''.join(annotations)}
            {''.join(label_marks)}
        </svg>
    </div>
    """


def render_daily_report_html(
    payload: Dict[str, Any],
    danmu_summary: str,
    operator_summary_lines: List[str],
) -> str:
    meta = payload.get("report_meta", {}) or {}
    operator = payload.get("operator_metrics", {}) or {}
    title_name = str(meta.get("nickname") or meta.get("room_name") or meta.get("room_id") or "主播")
    subtitle = (
        f"{meta.get('anchor_day', '')}  |  场次 {meta.get('session_count', 0)}"
        f"  |  弹幕 {meta.get('message_count', 0)}  |  活跃用户 {meta.get('unique_user_count', 0)}"
    )

    metrics_html = "".join([
        _render_metric_card("活跃用户", meta.get("unique_user_count", 0), "当天参与弹幕的去重人数"),
        _render_metric_card("带牌活跃", operator.get("fans_badge_user_count", 0), "带粉丝牌发言用户"),
        _render_metric_card("10+粉丝牌", operator.get("high_fans_level_user_count", 0), "高粘性活跃用户"),
        _render_metric_card("30+等级用户", operator.get("high_room_level_user_count", 0), "高等级老观众"),
    ])

    template_items = _build_template_items(payload)
    top_active_users = payload.get("operator_metrics", {}).get("top_active_users", []) or []
    audience_trend = payload.get("audience_trend", {}) or {}

    lead_summary, danmu_bullets, fans_extract_bullets = _split_summary_blocks(danmu_summary)
    danmu_bullets = _normalize_summary_bullets(payload, danmu_bullets, target_count=5)
    fans_extract_bullets = _normalize_fans_extract_bullets(payload, fans_extract_bullets, target_count=6)

    # 模板化渲染：
    # 1. 报告样式和结构迁移到独立 HTML 模板文件；
    # 2. Python 仅负责准备数据与片段，后续改 UI 只改模板即可。
    renderer = HtmlTemplateRenderer()
    return renderer.render(
        "plugins/douyu/templates/daily_report.html",
        {
            "title_name": title_name,
            "subtitle": subtitle,
            # 下列片段由当前函数内辅助方法生成，文本内容已做转义，可安全注入模板。
            "metrics_html": Markup(metrics_html),
            "lead_summary": lead_summary,
            "danmu_insights_html": Markup(_render_insight_cards(danmu_bullets)),
            "fans_extract_html": Markup(_render_list(fans_extract_bullets, item_class="fans-list")),
            "template_items_html": Markup(_render_list(template_items)),
            "hot_times_html": Markup(_render_hot_times(payload.get("peak_buckets", []) or [])),
            "audience_trend_html": Markup(_render_audience_trend_chart(audience_trend)),
            "operator_summary_html": Markup(_render_list(operator_summary_lines)),
            "badges_html": Markup(_render_badges(operator.get("top_badges", []) or [])),
            "active_users_html": Markup(_render_active_users(top_active_users)),
        },
    )


def render_fans_daily_report_html(
    payload: Dict[str, Any],
    fans_report_text: str,
) -> str:
    """
    渲染“粉丝向恶搞日报”。
    这份报告的设计重点不是运营洞察，而是把当天最有节目效果的弹幕氛围单独做成一页，
    方便群里直接转发、看图找乐子。
    """
    meta = payload.get("report_meta", {}) or {}
    title_name = str(meta.get("nickname") or meta.get("room_name") or meta.get("room_id") or "主播")
    subtitle = (
        f"{meta.get('anchor_day', '')}  |  弹幕 {meta.get('message_count', 0)} 条"
        f"  |  围观群众 {meta.get('unique_user_count', 0)} 人"
    )
    sections = _split_fans_report_blocks(fans_report_text)
    effective_info_lines = _normalize_information_section_items(
        sections.get("key_info", []),
        _build_fans_effective_info_lines(payload),
        target_count=6,
    )
    topic_focus_lines = _normalize_information_section_items(
        sections.get("topic_focus", []),
        _build_local_topic_focus_lines(payload),
        target_count=4,
    )
    hero_focus_lines = _normalize_information_section_items(
        sections.get("hero_focus", []),
        _build_local_hero_focus_lines(payload),
        target_count=4,
    )
    laugh_points = _normalize_funny_bullets(payload, sections.get("laugh_points", []), target_count=4)
    famous_scenes = _normalize_scene_bullets(payload, sections.get("famous_scenes", []), target_count=5)
    meme_rank = _normalize_rank_bullets(payload, sections.get("meme_rank", []), target_count=3)
    closing_text = _normalize_closing_text(payload, sections.get("closing", []))
    lead_text = str(sections.get("lead") or "").strip()
    if not lead_text:
        lead_text = "今天这场直播的弹幕主打一个集体上头，观众一边盯着画面，一边忙着把梗越刷越离谱。"
    topic_clusters = _get_topic_evidence_clusters(payload)
    hero_mentions = _get_hero_mentions(payload)
    local_stats = _build_local_stats(payload)

    renderer = HtmlTemplateRenderer()
    return renderer.render(
        "plugins/douyu/templates/daily_fans_report.html",
        {
            "title_name": title_name,
            "subtitle": subtitle,
            "lead_text": lead_text,
            # 粉丝版不再只做“乐子文案展示”，而是补进本地提纯后的有效信息区。
            "fans_metrics_html": Markup(_render_fans_metric_cards(_build_fans_fun_metrics(payload))),
            "effective_info_html": Markup(_render_fans_info_cards(effective_info_lines)),
            "topic_focus_html": Markup(_render_list(topic_focus_lines, item_class="section-summary-list")),
            "topic_clusters_html": Markup(_render_topic_clusters(topic_clusters)),
            "hero_focus_html": Markup(_render_list(hero_focus_lines, item_class="section-summary-list")),
            "hero_mentions_html": Markup(_render_hero_mentions(hero_mentions)),
            "hot_windows_html": Markup(_render_hot_window_cards(local_stats.get("peak_windows", []) or [])),
            "repeat_digest_html": Markup(_render_repeat_digest(payload)),
            "laugh_points_html": Markup(_render_list(laugh_points, item_class="funny-list")),
            "famous_scenes_html": Markup(_render_fans_scene_cards(famous_scenes)),
            "meme_rank_html": Markup(_render_rank_cards(meme_rank)),
            "closing_text": closing_text,
        },
    )