1f2d7d9ee5
- 新增灵活匹配模式(flexible_mode)，支持2/4项匹配即可的记忆检索策略 - 删除冗余的memory_formatter模块，简化记忆系统架构 - 增强枚举值解析机制，支持字符串、整数和枚举实例的自动转换 - 优化元数据索引搜索逻辑，分离严格模式和灵活模式的实现路径 - 改进向量存储的搜索回退机制，当元数据筛选无结果时自动回退到全量搜索 - 统一记忆类型映射管理，避免重复的格式化函数定义 这些变更提升了记忆检索的准确性和灵活性，同时简化了代码结构，提高了系统可维护性。
109 lines
2.8 KiB
Python
109 lines
2.8 KiB
Python
# -*- coding: utf-8 -*-
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"""
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记忆系统相关的映射表和工具函数
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提供记忆类型、置信度、重要性等的中文标签映射
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"""
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# 记忆类型到中文标签的完整映射表
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MEMORY_TYPE_CHINESE_MAPPING = {
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"personal_fact": "个人事实",
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"preference": "偏好",
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"event": "事件",
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"opinion": "观点",
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"relationship": "人际关系",
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"emotion": "情感状态",
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"knowledge": "知识信息",
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"skill": "技能能力",
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"goal": "目标计划",
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"experience": "经验教训",
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"contextual": "上下文信息",
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"unknown": "未知"
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}
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# 置信度等级到中文标签的映射表
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CONFIDENCE_LEVEL_CHINESE_MAPPING = {
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1: "低置信度",
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2: "中等置信度",
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3: "高置信度",
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4: "已验证",
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"LOW": "低置信度",
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"MEDIUM": "中等置信度",
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"HIGH": "高置信度",
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"VERIFIED": "已验证",
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"unknown": "未知"
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}
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# 重要性等级到中文标签的映射表
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IMPORTANCE_LEVEL_CHINESE_MAPPING = {
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1: "低重要性",
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2: "一般重要性",
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3: "高重要性",
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4: "关键重要性",
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"LOW": "低重要性",
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"NORMAL": "一般重要性",
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"HIGH": "高重要性",
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"CRITICAL": "关键重要性",
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"unknown": "未知"
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}
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def get_memory_type_chinese_label(memory_type: str) -> str:
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"""获取记忆类型的中文标签
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Args:
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memory_type: 记忆类型字符串
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Returns:
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str: 对应的中文标签，如果找不到则返回"未知"
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"""
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return MEMORY_TYPE_CHINESE_MAPPING.get(memory_type, "未知")
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def get_confidence_level_chinese_label(level) -> str:
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"""获取置信度等级的中文标签
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Args:
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level: 置信度等级（可以是数字、字符串或枚举实例）
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Returns:
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str: 对应的中文标签，如果找不到则返回"未知"
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"""
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# 处理枚举实例
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if hasattr(level, 'value'):
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level = level.value
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# 处理数字
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if isinstance(level, int):
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return CONFIDENCE_LEVEL_CHINESE_MAPPING.get(level, "未知")
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# 处理字符串
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if isinstance(level, str):
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level_upper = level.upper()
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return CONFIDENCE_LEVEL_CHINESE_MAPPING.get(level_upper, "未知")
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return "未知"
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def get_importance_level_chinese_label(level) -> str:
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"""获取重要性等级的中文标签
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Args:
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level: 重要性等级（可以是数字、字符串或枚举实例）
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Returns:
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str: 对应的中文标签，如果找不到则返回"未知"
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"""
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# 处理枚举实例
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if hasattr(level, 'value'):
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level = level.value
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# 处理数字
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if isinstance(level, int):
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return IMPORTANCE_LEVEL_CHINESE_MAPPING.get(level, "未知")
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# 处理字符串
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if isinstance(level, str):
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level_upper = level.upper()
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return IMPORTANCE_LEVEL_CHINESE_MAPPING.get(level_upper, "未知")
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return "未知" |