diff --git a/plugins/douyu/main.py b/plugins/douyu/main.py
index a745dd7..15233a3 100644
--- a/plugins/douyu/main.py
+++ b/plugins/douyu/main.py
@@ -462,7 +462,8 @@ class DouyuRedisManager:
class DouyuPlugin(MessagePluginInterface):
- _DAILY_REPORT_CACHE_VERSION = 3
+ # 报告结构有新增（粉丝向弹幕萃取区块），提升缓存版本以触发重新生成。
+ _DAILY_REPORT_CACHE_VERSION = 4
FEATURE_KEY = "DOUYU_MONITOR"
FEATURE_DESCRIPTION = "🎮 斗鱼开播提醒 [订阅斗鱼 房间号, 取消订阅斗鱼 房间号]"
@@ -1538,14 +1539,70 @@ class DouyuPlugin(MessagePluginInterface):
"请输出一段适合放在日报图片上半部分的弹幕总结，要求：\n"
"1. 先用 1 段总述直播氛围与主线。\n"
"2. 再用 5 条要点总结观众关注点、情绪变化、反复出现的梗、节奏变化和额外反馈，每条只写一句。\n"
- "3. 语言像运营复盘，简洁自然。\n"
- "4. 不要写标题，不要写“根据数据”。\n\n"
+ "3. 另起一行固定写标题：`【粉丝向弹幕萃取】`。\n"
+ "4. 在该标题下输出 4-6 条短句，尽量保留弹幕原话风格（可以保留口头语、玩梗、情绪词）。\n"
+ "5. 整体语气要像“直播间现场记录”，不要写成运营复盘。\n"
+ "6. 不要写“根据数据”“建议”“策略”等词。\n\n"
f"主播：{meta.get('nickname') or meta.get('room_name') or meta.get('room_id')}\n"
f"日期：{meta.get('anchor_day', '')}\n"
f"材料：\n{json.dumps(payload, ensure_ascii=False, indent=2)}"
)
return system_prompt, user_prompt
+ def _build_fans_extract_lines(self, payload: Dict[str, Any], limit: int = 6) -> List[str]:
+ # 粉丝向萃取强调“可读、像现场弹幕”，优先取代表发言，再补充重复梗与情绪短词。
+ representative_messages = payload.get("representative_messages", []) or []
+ repeated_messages = payload.get("repeated_messages", []) or []
+ merged_templates = payload.get("merged_templates", []) or []
+ burst_terms = payload.get("burst_terms", []) or []
+
+ lines: List[str] = []
+ seen = set()
+
+ def push(text: str) -> None:
+ value = str(text or "").strip()
+ if not value:
+ return
+ key = value.lower()
+ if key in seen:
+ return
+ seen.add(key)
+ lines.append(value)
+
+ for item in representative_messages[:10]:
+ nickname = str(item.get("nickname") or "").strip() or "观众"
+ content = str(item.get("content") or "").strip()
+ if content:
+ push(f"{nickname}：{content[:56]}")
+ if len(lines) >= limit:
+ return lines[:limit]
+
+ for item in repeated_messages[:6]:
+ text = str(item.get("text") or "").strip()
+ count = int(item.get("count", 0) or 0)
+ if text:
+ push(f"复读梗「{text[:36]}」刷了 {count} 次。")
+ if len(lines) >= limit:
+ return lines[:limit]
+
+ for item in merged_templates[:6]:
+ text = str(item.get("text") or "").strip()
+ count = int(item.get("count", 0) or 0)
+ if text:
+ push(f"共识弹幕「{text[:36]}」出现 {count} 次。")
+ if len(lines) >= limit:
+ return lines[:limit]
+
+ for item in burst_terms[:4]:
+ text = str(item.get("text") or "").strip()
+ count = int(item.get("count", 0) or 0)
+ if text:
+ push(f"情绪短词「{text}」集中出现 {count} 次。")
+ if len(lines) >= limit:
+ return lines[:limit]
+
+ return lines[:limit]
+
def _build_fallback_daily_report(self, payload: Dict[str, Any]) -> str:
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")
@@ -1671,6 +1728,12 @@ class DouyuPlugin(MessagePluginInterface):
lines.append("- 情绪特点：代表性发言里既有对操作和决策的即时反馈，也有大量玩梗、调侃和情绪宣泄。")
if top_terms:
lines.append(f"- 关注焦点：高频词主要落在 {'、'.join(top_terms[:6])}，说明观众注意力相对集中。")
+ # 在兜底模式下也强制补出“粉丝向弹幕萃取”，避免图片模板出现空区块。
+ fans_extract_lines = self._build_fans_extract_lines(payload, limit=6)
+ if fans_extract_lines:
+ lines.append("【粉丝向弹幕萃取】")
+ for item in fans_extract_lines:
+ lines.append(f"- {item}")
return "\n".join(lines).strip()
def _build_operator_summary_text(self, payload: Dict[str, Any]) -> str:
diff --git a/plugins/douyu/report_template.py b/plugins/douyu/report_template.py
index 16dc80f..4e2f206 100644
--- a/plugins/douyu/report_template.py
+++ b/plugins/douyu/report_template.py
@@ -24,19 +24,37 @@ def _render_list(items: List[str], item_class: str = "bullet-list") -> str:
return f'' if lis else ""
-def _split_summary_blocks(danmu_summary: str) -> tuple[str, List[str]]:
+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("- "):
- insight_items.append(stripped[2:].strip())
+ if in_fans_extract_block:
+ fans_extract_items.append(stripped[2:].strip())
+ else:
+ insight_items.append(stripped[2:].strip())
else:
- lead_parts.append(stripped)
+ # 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
+ return lead, insight_items, fans_extract_items
def _normalize_summary_bullets(payload: Dict[str, Any], items: List[str], target_count: int = 5) -> List[str]:
@@ -75,6 +93,47 @@ def _normalize_summary_bullets(payload: Dict[str, Any], items: List[str], target
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 _build_template_items(payload: Dict[str, Any], limit: int = 8) -> List[str]:
items: List[str] = []
seen = set()
@@ -400,8 +459,9 @@ def render_daily_report_html(
top_active_users = payload.get("operator_metrics", {}).get("top_active_users", []) or []
audience_trend = payload.get("audience_trend", {}) or {}
- lead_summary, danmu_bullets = _split_summary_blocks(danmu_summary)
+ 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)
html_doc = f"""
@@ -589,6 +649,30 @@ def render_daily_report_html(
grid-template-columns: repeat(2, minmax(0, 1fr));
gap: 12px;
}}
+ .fans-panel {{
+ margin-top: 14px;
+ padding: 14px 15px 12px;
+ border-radius: 18px;
+ background: linear-gradient(180deg, rgba(255,255,255,0.96), rgba(245,250,255,0.94));
+ border: 1px solid rgba(73, 136, 224, 0.18);
+ }}
+ .fans-title {{
+ color: #1d4ed8;
+ font-size: 13px;
+ letter-spacing: .06em;
+ font-weight: 700;
+ margin-bottom: 8px;
+ }}
+ .fans-list {{
+ margin: 0;
+ padding-left: 18px;
+ }}
+ .fans-list li {{
+ color: #1e3a5f;
+ margin: 8px 0;
+ line-height: 1.65;
+ font-size: 14px;
+ }}
.insight-card {{
padding: 15px 16px;
border-radius: 18px;
@@ -946,6 +1030,10 @@ def render_daily_report_html(
{_render_insight_cards(danmu_bullets)}
+
+
给粉丝看的弹幕萃取
+ {_render_list(fans_extract_bullets, item_class="fans-list")}
+