补充斗鱼粉丝日报本地预览脚本并压缩版面

1. 为本地测试脚本增加粉丝日报 HTML 预览输出，统一映射新版模板需要的数据结构\n2. 内置稳定的预览文案拼装逻辑，方便不依赖LLM也能本地验收页面效果\n3. 压缩粉丝日报模板的卡片间距、字号、行高和高度，让同样的信息更紧凑简约地展示

plugins/douyu/local_test_runner.py

@@ -12,6 +12,7 @@
 import importlib.util
 import json
 import os
+import sys
 from datetime import datetime
 from pathlib import Path
 from typing import Any, Dict, List
@@ -27,6 +28,25 @@ def _load_helper():
     return module.DouyuDanmuSummaryHelper
 
 
+def _load_report_template_module():
+    """
+    单独按文件路径加载模板模块。
+    这样本地预览不需要完整初始化插件，也不依赖 Redis 或其他运行时对象。
+    """
+    current_dir = Path(__file__).resolve().parent
+    project_root = current_dir.parent.parent
+    project_root_str = str(project_root)
+    # 把项目根目录补进 sys.path，保证 report_template.py 内部引用 utils 等项目模块时可正常导入。
+    if project_root_str not in sys.path:
+        sys.path.insert(0, project_root_str)
+    module_path = current_dir / "report_template.py"
+    spec = importlib.util.spec_from_file_location("douyu_report_template_local", module_path)
+    module = importlib.util.module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return module
+
+
 def _build_session(room_id: str, anchor_day: str, messages: List[Dict[str, Any]]) -> Dict[str, Any]:
     ordered = sorted(messages, key=lambda item: item.get("timestamp") or datetime.min)
     if not ordered:
@@ -51,6 +71,181 @@ def _build_session(room_id: str, anchor_day: str, messages: List[Dict[str, Any]]
     }
 
 
+def _build_preview_template_payload(local_result: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    将本地测试结果转成粉丝日报模板真正需要的结构。
+    这样预览链路和正式模板共用同一套字段命名，后续查问题更直观。
+    """
+    session_meta = local_result.get("session_meta", {}) or {}
+    local_stats_preview = local_result.get("local_stats_preview", {}) or {}
+    topic_clusters = local_result.get("topic_evidence_clusters", []) or []
+    hero_mentions = local_result.get("hero_mentions", []) or []
+    content_cues = local_result.get("content_cues", []) or []
+    timeline_digest = local_result.get("timeline_digest", []) or []
+    representative_messages = local_result.get("representative_messages", []) or []
+
+    return {
+        "report_meta": {
+            "room_id": str(session_meta.get("room_id") or "").strip(),
+            "anchor_day": str(session_meta.get("anchor_day") or "").strip(),
+            "nickname": str(session_meta.get("nickname") or "").strip(),
+            "room_name": str(session_meta.get("room_name") or "").strip(),
+            "session_count": 1,
+            "message_count": int(session_meta.get("message_count", 0) or 0),
+            "unique_user_count": int(session_meta.get("unique_user_count", 0) or 0),
+        },
+        "local_stats": {
+            "message_count": int(session_meta.get("message_count", 0) or 0),
+            "unique_user_count": int(session_meta.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"
+            ][: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 local_stats_preview.get("top_repeated_messages", [])[:8]
+            ],
+            "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 local_stats_preview.get("peak_buckets", [])[:6]
+            ],
+        },
+        "topic_evidence_clusters": [
+            {
+                "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 [],
+            }
+            for item in topic_clusters[:6]
+        ],
+        "compact_scene_material": {
+            "semantic_fact_hints": {
+                "hero_mentions": hero_mentions[:6],
+            },
+            "content_cues": content_cues[:18],
+            "timeline_digest": timeline_digest[:20],
+        },
+        "representative_messages": representative_messages[:12],
+        "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 local_stats_preview.get("top_repeated_messages", [])[:12]
+        ],
+        "burst_terms": [
+            {
+                "text": str(item.get("text") or "").strip(),
+                "count": int(item.get("count", 0) or 0),
+            }
+            for item in local_stats_preview.get("top_burst_terms", [])[:12]
+        ],
+        "peak_buckets": local_stats_preview.get("peak_buckets", [])[:6],
+        "top_terms": [
+            {"term": str(keyword).strip(), "count": 0}
+            for item in topic_clusters[:4]
+            for keyword in (item.get("keywords", []) or [])[:2]
+            if str(keyword).strip()
+        ],
+    }
+
+
+def _build_preview_report_text(payload: Dict[str, Any]) -> str:
+    """
+    为本地模板预览提供一份稳定的示例文本。
+    这里不依赖真实 LLM，只用已经提纯好的结果拼装固定结构，
+    方便我们快速检查模板是否把关键信息展示完整。
+    """
+    meta = payload.get("report_meta", {}) or {}
+    topic_clusters = payload.get("topic_evidence_clusters", []) or []
+    hero_mentions = (
+        payload.get("compact_scene_material", {})
+        .get("semantic_fact_hints", {})
+        .get("hero_mentions", [])
+        or []
+    )
+    repeated_messages = payload.get("repeated_messages", []) or []
+    burst_terms = payload.get("burst_terms", []) or []
+    peak_buckets = payload.get("peak_buckets", []) or []
+    representative_messages = payload.get("representative_messages", []) or []
+    anchor_day = str(meta.get("anchor_day") or "").strip()
+
+    lines = [
+        f"{anchor_day} 这场直播的弹幕不只是热闹，核心信息也很密：赛事、位置、英雄、团播人物和摄像头梗都有人追着聊。",
+        "【今日重点信息】",
+    ]
+    for item in topic_clusters[:5]:
+        label = str(item.get("label") or "").strip()
+        time_range = str(item.get("time_range") or "").strip()
+        count = int(item.get("count", 0) or 0)
+        samples = item.get("samples", []) or []
+        sample_text = str(samples[0].get("content") or "").strip()[:42] if samples else ""
+        if label and sample_text:
+            lines.append(f"- {label}从 {time_range or '全场'} 一直有人聊，相关弹幕约 {count} 条，代表说法是「{sample_text}」。")
+
+    lines.append("【核心讨论话题】")
+    for item in topic_clusters[:4]:
+        label = str(item.get("label") or "").strip()
+        keywords = [str(keyword).strip() for keyword in (item.get("keywords", []) or [])[:5] if str(keyword).strip()]
+        if label and keywords:
+            lines.append(f"- 大家围着 {label} 打转，关键词主要是 {'、'.join(keywords)}。")
+
+    lines.append("【英雄与对局焦点】")
+    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 = str(samples[0].get("content") or "").strip()[:36] if samples else ""
+        if hero_name and sample_text:
+            lines.append(f"- {hero_name}被点名 {mention_count} 次，弹幕现场直接聊到「{sample_text}」。")
+
+    lines.append("【今日笑点】")
+    if peak_buckets:
+        top_bucket = peak_buckets[0]
+        lines.append(
+            f"- {str(top_bucket.get('start_time') or '')[-8:-3]} 前后是最热窗口，弹幕量直接冲到 {int(top_bucket.get('message_count', 0) or 0)} 条。"
+        )
+    if repeated_messages:
+        item = repeated_messages[0]
+        lines.append(f"- 复读冠军是「{str(item.get('text') or '').strip()[:24]}」，一天被刷了 {int(item.get('count', 0) or 0)} 次。")
+    if burst_terms:
+        item = burst_terms[0]
+        lines.append(f"- 情绪词「{str(item.get('text') or '').strip()}」集中爆了 {int(item.get('count', 0) or 0)} 次。")
+
+    lines.append("【弹幕名场面】")
+    for item in representative_messages[:5]:
+        nickname = str(item.get("nickname") or "").strip() or "观众"
+        content = str(item.get("content") or "").strip()
+        if content:
+            lines.append(f"- {nickname}：{content[:44]}")
+
+    lines.append("【梗王榜】")
+    for item in repeated_messages[:3]:
+        lines.append(f"- {str(item.get('text') or '').strip()[:28]}｜复读 {int(item.get('count', 0) or 0)} 次")
+
+    lines.append("【收尾播报】")
+    lines.append("- 本地预览版已经把有效信息和乐子一起塞进同一张图里了。")
+    return "\n".join(lines)
+
+
 def run_local_test(file_path: str) -> str:
     helper = _load_helper()
     resolved_path = str(Path(file_path).resolve())
@@ -85,11 +280,36 @@ def run_local_test(file_path: str) -> str:
     return str(output_path)
 
 
+def render_fans_preview_from_file(file_path: str) -> str:
+    """
+    读取本地弹幕文件并直接产出新版粉丝日报 HTML 预览。
+    这样我们每次调整提纯逻辑或模板后，都能用同一条命令快速验收最终展示效果。
+    """
+    local_result_path = Path(run_local_test(file_path))
+    local_result = json.loads(local_result_path.read_text(encoding="utf-8"))
+    payload = _build_preview_template_payload(local_result)
+    report_text = _build_preview_report_text(payload)
+    report_template = _load_report_template_module()
+    html_content = report_template.render_fans_daily_report_html(
+        payload=payload,
+        fans_report_text=report_text,
+    )
+
+    output_dir = Path(os.getcwd()) / "temp" / "douyu_materials"
+    output_dir.mkdir(parents=True, exist_ok=True)
+    file_name = Path(file_path).stem
+    output_path = output_dir / f"{file_name}_fans_template_preview.html"
+    output_path.write_text(html_content, encoding="utf-8")
+    return str(output_path)
+
+
 if __name__ == "__main__":
     sample_files = [
         r"plugins\douyu\danmu_test\52876_20260428.txt",
         r"plugins\douyu\danmu_test\52876_20260429.txt",
     ]
     for sample in sample_files:
-        path = run_local_test(sample)
+        result_path = run_local_test(sample)
-        print(path)
+        preview_path = render_fans_preview_from_file(sample)
+        print(result_path)
+        print(preview_path)

plugins/douyu/templates/daily_fans_report.html

@@ -105,12 +105,12 @@
     .fans-metric-grid {
         display: grid;
         grid-template-columns: repeat(4, minmax(0, 1fr));
-        gap: 14px;
+        gap: 10px;
-        margin-top: 16px;
+        margin-top: 12px;
     }
     .fans-metric-card {
-        padding: 18px 18px 16px;
+        padding: 14px 15px 12px;
-        border-radius: 20px;
+        border-radius: 16px;
         background: linear-gradient(180deg, rgba(255,255,255,.96), rgba(255,245,239,.92));
         border: 1px solid rgba(219,95,65,.12);
     }
@@ -120,48 +120,48 @@
         margin-bottom: 8px;
     }
     .fans-metric-value {
-        font-size: 28px;
+        font-size: 24px;
         line-height: 1;
         font-weight: 900;
         color: #cf593e;
         word-break: break-all;
     }
     .fans-metric-hint {
-        margin-top: 8px;
+        margin-top: 6px;
-        font-size: 12px;
+        font-size: 11px;
         color: #8f7368;
-        line-height: 1.5;
+        line-height: 1.4;
     }
     .section {
-        margin-top: 18px;
+        margin-top: 14px;
-        padding: 22px;
+        padding: 16px 18px;
-        border-radius: 26px;
+        border-radius: 20px;
         background: linear-gradient(180deg, rgba(255,255,255,.96), rgba(255,249,244,.94));
         border: 1px solid var(--line);
     }
     .section-summary-list {
-        margin: 0 0 14px;
+        margin: 0 0 10px;
-        padding-left: 22px;
+        padding-left: 18px;
     }
     .section-summary-list li {
-        margin: 8px 0;
+        margin: 5px 0;
         color: #5a3e37;
-        font-size: 15px;
+        font-size: 14px;
-        line-height: 1.76;
+        line-height: 1.58;
         font-weight: 600;
     }
     .section-title {
         display: flex;
         align-items: center;
-        gap: 10px;
+        gap: 8px;
-        margin-bottom: 16px;
+        margin-bottom: 12px;
-        font-size: 24px;
+        font-size: 21px;
         font-weight: 900;
         color: #5b2d23;
     }
     .section-title .icon {
-        width: 14px;
+        width: 12px;
-        height: 28px;
+        height: 22px;
         border-radius: 999px;
         background: linear-gradient(180deg, var(--accent), var(--accent-2));
         box-shadow: 0 6px 14px rgba(219,95,65,.2);
@@ -169,108 +169,108 @@
     .info-grid {
         display: grid;
         grid-template-columns: repeat(3, minmax(0, 1fr));
-        gap: 12px;
+        gap: 10px;
     }
     .fans-info-card {
-        padding: 16px 16px 15px;
+        padding: 12px 13px;
-        border-radius: 18px;
+        border-radius: 14px;
         background: linear-gradient(180deg, rgba(255,255,255,.98), rgba(255,245,240,.94));
         border: 1px solid rgba(219,95,65,.12);
-        min-height: 112px;
+        min-height: 84px;
     }
     .fans-info-text {
-        font-size: 15px;
+        font-size: 14px;
-        line-height: 1.76;
+        line-height: 1.58;
         color: #523935;
         font-weight: 600;
     }
     .topic-grid {
         display: grid;
         grid-template-columns: repeat(2, minmax(0, 1fr));
-        gap: 14px;
+        gap: 10px;
     }
     .topic-cluster-card {
-        padding: 18px 18px 14px;
+        padding: 13px 14px 11px;
-        border-radius: 20px;
+        border-radius: 16px;
         background: linear-gradient(180deg, rgba(255,255,255,.98), rgba(255,244,237,.94));
         border: 1px solid rgba(219,95,65,.12);
     }
     .topic-cluster-title {
-        font-size: 18px;
+        font-size: 16px;
         font-weight: 900;
         color: #6d2f22;
-        margin-bottom: 8px;
+        margin-bottom: 5px;
     }
     .topic-cluster-meta {
-        font-size: 12px;
+        font-size: 11px;
         color: #8d6c61;
-        margin-bottom: 10px;
+        margin-bottom: 7px;
     }
     .topic-cluster-list {
         margin: 0;
-        padding-left: 18px;
+        padding-left: 16px;
     }
     .topic-cluster-list li {
-        margin: 8px 0;
+        margin: 5px 0;
-        font-size: 14px;
+        font-size: 13px;
-        line-height: 1.66;
+        line-height: 1.52;
         color: #4d3832;
     }
     .hero-grid {
         display: grid;
         grid-template-columns: repeat(4, minmax(0, 1fr));
-        gap: 12px;
+        gap: 10px;
     }
     .hero-mention-card {
-        padding: 16px;
+        padding: 12px 13px;
-        border-radius: 18px;
+        border-radius: 14px;
         background: linear-gradient(135deg, rgba(255,255,255,.98), rgba(255,241,232,.94));
         border: 1px solid rgba(243,164,71,.22);
     }
     .hero-mention-name {
-        font-size: 17px;
+        font-size: 15px;
         line-height: 1.4;
         font-weight: 900;
         color: #6b311f;
-        margin-bottom: 6px;
+        margin-bottom: 4px;
     }
     .hero-mention-meta {
-        font-size: 12px;
+        font-size: 11px;
         color: #8c6d61;
-        margin-bottom: 8px;
+        margin-bottom: 6px;
     }
     .hero-mention-sample {
-        font-size: 14px;
+        font-size: 13px;
-        line-height: 1.65;
+        line-height: 1.5;
         color: #533833;
     }
     .timeline-layout {
         display: grid;
         grid-template-columns: minmax(0, .95fr) minmax(0, 1.05fr);
-        gap: 14px;
+        gap: 10px;
     }
     .hot-window-stack,
     .repeat-chip-wrap,
     .meme-rank-stack {
         display: grid;
-        gap: 10px;
+        gap: 8px;
     }
     .fans-hot-window-card,
     .repeat-digest-panel,
     .rank-panel {
-        padding: 14px 16px;
+        padding: 11px 12px;
-        border-radius: 18px;
+        border-radius: 14px;
         background: linear-gradient(180deg, rgba(255,255,255,.98), rgba(255,245,239,.94));
         border: 1px solid rgba(219,95,65,.12);
     }
     .fans-hot-window-time {
-        font-size: 18px;
+        font-size: 16px;
         font-weight: 900;
         color: #c84f3f;
-        margin-bottom: 6px;
+        margin-bottom: 4px;
     }
     .fans-hot-window-meta {
-        font-size: 14px;
+        font-size: 12px;
         color: #5c433b;
     }
     .repeat-chip-wrap {
@@ -280,9 +280,9 @@
         display: flex;
         align-items: center;
         justify-content: space-between;
-        gap: 10px;
+        gap: 8px;
-        padding: 12px 14px;
+        padding: 9px 11px;
-        border-radius: 14px;
+        border-radius: 12px;
         background: rgba(255,255,255,.9);
         border: 1px solid rgba(219,95,65,.1);
     }
@@ -290,35 +290,35 @@
         background: rgba(255,247,236,.94);
     }
     .repeat-chip-text {
-        font-size: 14px;
+        font-size: 12px;
-        line-height: 1.5;
+        line-height: 1.4;
         color: #4d3932;
         font-weight: 700;
     }
     .repeat-chip-count {
         flex-shrink: 0;
-        font-size: 12px;
+        font-size: 11px;
         color: #a05441;
         font-weight: 800;
     }
     .two-col {
         display: grid;
         grid-template-columns: minmax(0, 1.08fr) minmax(280px, .92fr);
-        gap: 16px;
+        gap: 12px;
     }
     .funny-list {
         margin: 0;
-        padding-left: 22px;
+        padding-left: 18px;
     }
     .funny-list li {
-        margin: 10px 0;
+        margin: 6px 0;
         color: #533835;
-        font-size: 15px;
+        font-size: 14px;
-        line-height: 1.76;
+        line-height: 1.58;
     }
     .meme-rank-card {
-        padding: 14px 16px;
+        padding: 11px 12px;
-        border-radius: 16px;
+        border-radius: 13px;
         background: linear-gradient(135deg, rgba(255,255,255,.98), rgba(255,240,232,.95));
         border: 1px solid rgba(242,95,92,.18);
     }
@@ -327,35 +327,35 @@
         font-size: 12px;
         letter-spacing: .08em;
         font-weight: 900;
-        margin-bottom: 8px;
+        margin-bottom: 5px;
     }
     .meme-rank-text {
         color: #4b2e2b;
-        font-size: 15px;
+        font-size: 13px;
-        line-height: 1.66;
+        line-height: 1.5;
         font-weight: 700;
     }
     .scene-grid {
         display: grid;
         grid-template-columns: repeat(2, minmax(0, 1fr));
-        gap: 12px;
+        gap: 10px;
     }
     .fans-scene-card {
-        padding: 16px 16px 15px;
+        padding: 12px 13px;
-        border-radius: 18px;
+        border-radius: 14px;
         background: linear-gradient(180deg, rgba(255,255,255,.98), rgba(255,245,240,.95));
         border: 1px solid rgba(255,138,61,.16);
-        min-height: 102px;
+        min-height: 78px;
     }
     .fans-scene-quote {
         color: #5b3c37;
-        font-size: 15px;
+        font-size: 13px;
-        line-height: 1.75;
+        line-height: 1.54;
     }
     .closing-box {
-        margin-top: 16px;
+        margin-top: 14px;
-        padding: 20px 22px;
+        padding: 15px 17px;
-        border-radius: 24px;
+        border-radius: 18px;
         background: linear-gradient(135deg, rgba(255,126,103,.1), rgba(243,164,71,.14));
         border: 1px solid rgba(255,126,103,.16);
     }
@@ -364,16 +364,16 @@
         font-size: 13px;
         letter-spacing: .08em;
         font-weight: 900;
-        margin-bottom: 10px;
+        margin-bottom: 6px;
     }
     .closing-text {
         color: #613b34;
-        font-size: 18px;
+        font-size: 15px;
-        line-height: 1.8;
+        line-height: 1.6;
         font-weight: 700;
     }
     .footer-note {
-        margin-top: 18px;
+        margin-top: 14px;
         text-align: right;
         color: #8f736c;
         font-size: 12px;