feat: 通过FastScorer与批处理功能增强关联兴趣计算器
- 集成FastScorer用于优化评分，绕过sklearn以提升性能。 - 新增批量处理功能，以应对高频聊天场景。 - 实现了一个全局线程池以避免重复创建执行器。 - 将评分操作的超时时间缩短至2秒。 - 重构了ChatterActionPlanner以利用新的利息计算器。 - 引入了一个基准测试脚本，用于比较原始sklearn与FastScorer之间的性能差异。 开发了一款优化后的评分器，具备权重剪枝和异步评分等功能。
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Windpicker-owo
@@ -12,7 +12,6 @@ from typing import Any
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from src.common.logger import get_logger
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from src.person_info.person_info import PersonInfoManager, get_person_info_manager
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from src.plugin_system.services.interest_service import interest_service
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from src.plugin_system.services.relationship_service import relationship_service
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logger = get_logger("person_api")
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@@ -169,37 +168,6 @@ async def update_user_relationship(user_id: str, relationship_score: float, rela
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await relationship_service.update_user_relationship(user_id, relationship_score, relationship_text, user_name)
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# =============================================================================
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# 兴趣系统API
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# =============================================================================
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async def initialize_smart_interests(personality_description: str, personality_id: str = "default"):
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"""
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初始化智能兴趣系统
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Args:
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personality_description: 机器人性格描述
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personality_id: 性格ID
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"""
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await interest_service.initialize_smart_interests(personality_description, personality_id)
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async def calculate_interest_match(
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content: str, keywords: list[str] | None = None, message_embedding: list[float] | None = None
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):
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"""计算消息兴趣匹配，返回匹配结果"""
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if not content:
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logger.warning("[PersonAPI] 请求兴趣匹配时 content 为空")
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return None
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try:
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return await interest_service.calculate_interest_match(content, keywords, message_embedding)
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except Exception as e:
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logger.error(f"[PersonAPI] 计算消息兴趣匹配失败: {e}")
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return None
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# =============================================================================
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# 系统状态与缓存API
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# =============================================================================
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@@ -214,7 +182,6 @@ def get_system_stats() -> dict[str, Any]:
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"""
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return {
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"relationship_service": relationship_service.get_cache_stats(),
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"interest_service": interest_service.get_interest_stats(),
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}
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@@ -1,108 +0,0 @@
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"""
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兴趣系统服务
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提供独立的兴趣管理功能，不依赖任何插件
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"""
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from src.chat.interest_system import bot_interest_manager
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from src.common.logger import get_logger
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logger = get_logger("interest_service")
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class InterestService:
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"""兴趣系统服务 - 独立于插件的兴趣管理"""
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def __init__(self):
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self.is_initialized = bot_interest_manager.is_initialized
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async def initialize_smart_interests(self, personality_description: str, personality_id: str = "default"):
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"""
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初始化智能兴趣系统
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Args:
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personality_description: 机器人性格描述
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personality_id: 性格ID
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"""
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try:
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logger.info("开始初始化智能兴趣系统...")
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await bot_interest_manager.initialize(personality_description, personality_id)
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self.is_initialized = True
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logger.info("智能兴趣系统初始化完成。")
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# 显示初始化后的统计信息
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stats = bot_interest_manager.get_interest_stats()
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logger.debug(f"兴趣系统统计: {stats}")
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except Exception as e:
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logger.error(f"初始化智能兴趣系统失败: {e}")
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self.is_initialized = False
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async def calculate_interest_match(
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self, content: str, keywords: list[str] | None = None, message_embedding: list[float] | None = None
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):
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"""
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计算消息与兴趣的匹配度
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Args:
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content: 消息内容
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keywords: 关键字列表
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message_embedding: 已经生成的消息embedding，可选
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Returns:
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匹配结果
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"""
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if not self.is_initialized:
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logger.warning("兴趣系统未初始化，无法计算匹配度")
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return None
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try:
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if not keywords:
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# 如果没有关键字，则从内容中提取
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keywords = self._extract_keywords_from_content(content)
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return await bot_interest_manager.calculate_interest_match(content, keywords, message_embedding)
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except Exception as e:
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logger.error(f"计算兴趣匹配失败: {e}")
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return None
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def _extract_keywords_from_content(self, content: str) -> list[str]:
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"""从内容中提取关键词"""
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import re
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# 清理文本
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content = re.sub(r"[^\w\s\u4e00-\u9fff]", " ", content) # 保留中文、英文、数字
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words = content.split()
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# 过滤和关键词提取
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keywords = []
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for word in words:
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word = word.strip()
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if (
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len(word) >= 2 # 至少2个字符
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and word.isalnum() # 字母数字
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and not word.isdigit()
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): # 不是纯数字
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keywords.append(word.lower())
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# 去重并限制数量
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unique_keywords = list(set(keywords))
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return unique_keywords[:10] # 返回前10个唯一关键词
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def get_interest_stats(self) -> dict:
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"""获取兴趣系统统计信息"""
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if not self.is_initialized:
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return {"initialized": False}
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try:
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return {
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"initialized": True,
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**bot_interest_manager.get_interest_stats()
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}
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except Exception as e:
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logger.error(f"获取兴趣系统统计失败: {e}")
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return {"initialized": True, "error": str(e)}
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# 创建全局实例
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interest_service = InterestService()
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