feat(affinity-flow): 通过标签扩展与提及分类增强兴趣匹配
- 实施扩展标签描述以实现更精确的语义匹配 - 增加强/弱提及分类，并附带独立的兴趣评分 - 重构机器人兴趣管理器，采用动态嵌入生成与缓存机制 - 通过增强的@提及处理功能优化消息处理 - 更新配置以支持回帖提升机制 - 将亲和力流量聊天重新组织为模块化结构，包含核心、规划器、主动响应和工具子模块 - 移除已弃用的规划器组件并整合功能 - 为napcat适配器插件添加数据库表初始化功能 - 修复元事件处理器中的心跳监控
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Windpicker-owo
@@ -49,23 +49,22 @@ def is_mentioned_bot_in_message(message) -> tuple[bool, float]:
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message: DatabaseMessages 消息对象
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Returns:
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tuple[bool, float]: (是否提及, 提及概率)
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tuple[bool, float]: (是否提及, 提及类型)
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提及类型: 0=未提及, 1=弱提及（文本匹配）, 2=强提及（@/回复/私聊）
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"""
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keywords = [global_config.bot.nickname]
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nicknames = global_config.bot.alias_names
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reply_probability = 0.0
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is_at = False
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is_mentioned = False
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mention_type = 0 # 0=未提及, 1=弱提及, 2=强提及
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# 检查 is_mentioned 属性
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# 检查 is_mentioned 属性（保持向后兼容）
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mentioned_attr = getattr(message, "is_mentioned", None)
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if mentioned_attr is not None:
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try:
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return bool(mentioned_attr), float(mentioned_attr)
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# 如果已有 is_mentioned，直接返回（假设是强提及）
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return bool(mentioned_attr), 2.0 if mentioned_attr else 0.0
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except (ValueError, TypeError):
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pass
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# 检查 additional_config
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# 检查 additional_config（保持向后兼容）
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additional_config = None
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# DatabaseMessages: additional_config 是 JSON 字符串
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@@ -78,62 +77,66 @@ def is_mentioned_bot_in_message(message) -> tuple[bool, float]:
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if additional_config and additional_config.get("is_mentioned") is not None:
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try:
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reply_probability = float(additional_config.get("is_mentioned")) # type: ignore
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is_mentioned = True
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return is_mentioned, reply_probability
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mentioned_value = float(additional_config.get("is_mentioned")) # type: ignore
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# 如果配置中有提及值，假设是强提及
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return True, 2.0 if mentioned_value > 0 else 0.0
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except Exception as e:
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logger.warning(str(e))
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logger.warning(
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f"消息中包含不合理的设置 is_mentioned: {additional_config.get('is_mentioned')}"
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)
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# 检查消息文本内容
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processed_text = message.processed_plain_text or ""
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if global_config.bot.nickname in processed_text:
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is_mentioned = True
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for alias_name in global_config.bot.alias_names:
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if alias_name in processed_text:
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is_mentioned = True
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# 判断是否被@
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if re.search(rf"@<(.+?):{global_config.bot.qq_account}>", message.processed_plain_text):
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# 1. 判断是否为私聊（强提及）
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group_info = getattr(message, "group_info", None)
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if not group_info or not getattr(group_info, "group_id", None):
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is_private = True
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mention_type = 2
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logger.debug("检测到私聊消息 - 强提及")
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# 2. 判断是否被@（强提及）
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if re.search(rf"@<(.+?):{global_config.bot.qq_account}>", processed_text):
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is_at = True
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is_mentioned = True
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# print(f"message.processed_plain_text: {message.processed_plain_text}")
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# print(f"is_mentioned: {is_mentioned}")
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# print(f"is_at: {is_at}")
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if is_at and global_config.chat.at_bot_inevitable_reply:
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reply_probability = 1.0
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logger.debug("被@，回复概率设置为100%")
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else:
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if not is_mentioned:
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# 判断是否被回复
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if re.match(
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rf"\[回复 (.+?)\({global_config.bot.qq_account!s}\)：(.+?)\]，说：", message.processed_plain_text
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) or re.match(
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rf"\[回复<(.+?)(?=:{global_config.bot.qq_account!s}>)\:{global_config.bot.qq_account!s}>：(.+?)\]，说：",
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message.processed_plain_text,
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):
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is_mentioned = True
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else:
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# 判断内容中是否被提及
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message_content = re.sub(r"@(.+?)（(\d+)）", "", message.processed_plain_text)
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message_content = re.sub(r"@<(.+?)(?=:(\d+))\:(\d+)>", "", message_content)
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message_content = re.sub(r"\[回复 (.+?)\(((\d+)|未知id)\)：(.+?)\]，说：", "", message_content)
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message_content = re.sub(r"\[回复<(.+?)(?=:(\d+))\:(\d+)>：(.+?)\]，说：", "", message_content)
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for keyword in keywords:
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if keyword in message_content:
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is_mentioned = True
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for nickname in nicknames:
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if nickname in message_content:
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is_mentioned = True
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if is_mentioned and global_config.chat.mentioned_bot_inevitable_reply:
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reply_probability = 1.0
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logger.debug("被提及，回复概率设置为100%")
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return is_mentioned, reply_probability
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mention_type = 2
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logger.debug("检测到@提及 - 强提及")
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# 3. 判断是否被回复（强提及）
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if re.match(
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rf"\[回复 (.+?)\({global_config.bot.qq_account!s}\)：(.+?)\]，说：", processed_text
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) or re.match(
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rf"\[回复<(.+?)(?=:{global_config.bot.qq_account!s}>)\:{global_config.bot.qq_account!s}>：(.+?)\]，说：",
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processed_text,
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):
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is_replied = True
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mention_type = 2
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logger.debug("检测到回复消息 - 强提及")
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# 4. 判断文本中是否提及bot名字或别名（弱提及）
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if mention_type == 0: # 只有在没有强提及时才检查弱提及
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# 移除@和回复标记后再检查
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message_content = re.sub(r"@(.+?)（(\d+)）", "", processed_text)
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message_content = re.sub(r"@<(.+?)(?=:(\d+))\:(\d+)>", "", message_content)
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message_content = re.sub(r"\[回复 (.+?)\(((\d+)|未知id)\)：(.+?)\]，说：", "", message_content)
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message_content = re.sub(r"\[回复<(.+?)(?=:(\d+))\:(\d+)>：(.+?)\]，说：", "", message_content)
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# 检查bot主名字
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if global_config.bot.nickname in message_content:
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is_text_mentioned = True
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mention_type = 1
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logger.debug(f"检测到文本提及bot主名字 '{global_config.bot.nickname}' - 弱提及")
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# 如果主名字没匹配，再检查别名
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elif nicknames:
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for alias_name in nicknames:
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if alias_name in message_content:
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is_text_mentioned = True
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mention_type = 1
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logger.debug(f"检测到文本提及bot别名 '{alias_name}' - 弱提及")
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break
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# 返回结果
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is_mentioned = mention_type > 0
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return is_mentioned, float(mention_type)
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async def get_embedding(text, request_type="embedding") -> list[float] | None:
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"""获取文本的embedding向量"""
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