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优化斗鱼弹幕总结：新增粉丝向弹幕萃取区块并调整提示词语气

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liuwei
2026-04-17 11:17:16 +08:00
parent e56c0069cc
commit 5098c191de
2 changed files with 159 additions and 8 deletions
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69
plugins/douyu/main.py
View File

@@ -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:

98
plugins/douyu/report_template.py
View File

@@ -24,19 +24,37 @@ def _render_list(items: List[str], item_class: str = "bullet-list") -> str:
return f'<ul class="{item_class}">{lis}</ul>' 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"""<html>
<head>
@@ -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(
<div class="insight-grid">
{_render_insight_cards(danmu_bullets)}
</div>
<div class="fans-panel">
<div class="fans-title">给粉丝看的弹幕萃取</div>
{_render_list(fans_extract_bullets, item_class="fans-list")}
</div>
</div>
<div class="aside-card">
<div class="aside-title">高频梗</div>