520 lines
13 KiB
Python
520 lines
13 KiB
Python
from dataclasses import dataclass, field
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from typing import Any, Literal
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import re
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from src.config.config_base import ConfigBase
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"""
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须知：
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1. 本文件中记录了所有的配置项
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2. 所有新增的class都需要继承自ConfigBase
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3. 所有新增的class都应在config.py中的Config类中添加字段
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4. 对于新增的字段，若为可选项，则应在其后添加field()并设置default_factory或default
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"""
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@dataclass
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class BotConfig(ConfigBase):
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"""QQ机器人配置类"""
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qq_account: str
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"""QQ账号"""
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nickname: str
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"""昵称"""
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alias_names: list[str] = field(default_factory=lambda: [])
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"""别名列表"""
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@dataclass
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class PersonalityConfig(ConfigBase):
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"""人格配置类"""
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personality_core: str
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"""核心人格"""
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personality_sides: list[str] = field(default_factory=lambda: [])
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"""人格侧写"""
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@dataclass
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class IdentityConfig(ConfigBase):
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"""个体特征配置类"""
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identity_detail: list[str] = field(default_factory=lambda: [])
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"""身份特征"""
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@dataclass
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class RelationshipConfig(ConfigBase):
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"""关系配置类"""
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enable_relationship: bool = True
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give_name: bool = False
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"""是否给其他人取名"""
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build_relationship_interval: int = 600
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"""构建关系间隔 单位秒，如果为0则不构建关系"""
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relation_frequency: int = 1
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"""关系频率，麦麦构建关系的速度，仅在normal_chat模式下有效"""
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@dataclass
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class ChatConfig(ConfigBase):
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"""聊天配置类"""
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chat_mode: str = "normal"
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"""聊天模式"""
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auto_focus_threshold: float = 1.0
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"""自动切换到专注聊天的阈值，越低越容易进入专注聊天"""
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exit_focus_threshold: float = 1.0
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"""自动退出专注聊天的阈值，越低越容易退出专注聊天"""
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@dataclass
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class MessageReceiveConfig(ConfigBase):
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"""消息接收配置类"""
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ban_words: set[str] = field(default_factory=lambda: set())
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"""过滤词列表"""
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ban_msgs_regex: set[str] = field(default_factory=lambda: set())
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"""过滤正则表达式列表"""
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@dataclass
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class NormalChatConfig(ConfigBase):
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"""普通聊天配置类"""
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normal_chat_first_probability: float = 0.3
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"""
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发言时选择推理模型的概率（0-1之间）
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选择普通模型的概率为 1 - reasoning_normal_model_probability
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"""
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max_context_size: int = 15
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"""上下文长度"""
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message_buffer: bool = False
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"""消息缓冲器"""
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emoji_chance: float = 0.2
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"""发送表情包的基础概率"""
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thinking_timeout: int = 120
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"""最长思考时间"""
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willing_mode: str = "classical"
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"""意愿模式"""
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talk_frequency: float = 1
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"""回复频率阈值"""
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response_interested_rate_amplifier: float = 1.0
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"""回复兴趣度放大系数"""
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talk_frequency_down_groups: list[str] = field(default_factory=lambda: [])
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"""降低回复频率的群组"""
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down_frequency_rate: float = 3.0
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"""降低回复频率的群组回复意愿降低系数"""
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emoji_response_penalty: float = 0.0
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"""表情包回复惩罚系数"""
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mentioned_bot_inevitable_reply: bool = False
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"""提及 bot 必然回复"""
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at_bot_inevitable_reply: bool = False
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"""@bot 必然回复"""
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enable_planner: bool = False
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"""是否启用动作规划器"""
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@dataclass
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class FocusChatConfig(ConfigBase):
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"""专注聊天配置类"""
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observation_context_size: int = 12
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"""可观察到的最长上下文大小，超过这个值的上下文会被压缩"""
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compressed_length: int = 5
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"""心流上下文压缩的最短压缩长度，超过心流观察到的上下文长度，会压缩，最短压缩长度为5"""
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compress_length_limit: int = 5
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"""最多压缩份数，超过该数值的压缩上下文会被删除"""
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think_interval: float = 1
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"""思考间隔（秒）"""
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consecutive_replies: float = 1
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"""连续回复能力，值越高，麦麦连续回复的概率越高"""
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parallel_processing: bool = False
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"""是否允许处理器阶段和回忆阶段并行执行"""
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processor_max_time: int = 25
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"""处理器最大时间，单位秒，如果超过这个时间，处理器会自动停止"""
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@dataclass
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class FocusChatProcessorConfig(ConfigBase):
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"""专注聊天处理器配置类"""
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person_impression_processor: bool = True
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"""是否启用关系识别处理器"""
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tool_use_processor: bool = True
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"""是否启用工具使用处理器"""
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working_memory_processor: bool = True
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"""是否启用工作记忆处理器"""
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expression_selector_processor: bool = True
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"""是否启用表达方式选择处理器"""
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@dataclass
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class ExpressionConfig(ConfigBase):
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"""表达配置类"""
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expression_style: str = ""
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"""表达风格"""
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learning_interval: int = 300
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"""学习间隔（秒）"""
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enable_expression_learning: bool = True
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"""是否启用表达学习"""
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expression_groups: list[list[str]] = field(default_factory=list)
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"""
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表达学习互通组
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格式: [["qq:12345:group", "qq:67890:private"]]
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"""
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@dataclass
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class EmojiConfig(ConfigBase):
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"""表情包配置类"""
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max_reg_num: int = 200
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"""表情包最大注册数量"""
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do_replace: bool = True
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"""达到最大注册数量时替换旧表情包"""
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check_interval: int = 120
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"""表情包检查间隔（分钟）"""
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steal_emoji: bool = True
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"""是否偷取表情包，让麦麦可以发送她保存的这些表情包"""
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content_filtration: bool = False
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"""是否开启表情包过滤"""
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filtration_prompt: str = "符合公序良俗"
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"""表情包过滤要求"""
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@dataclass
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class MemoryConfig(ConfigBase):
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"""记忆配置类"""
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enable_memory: bool = True
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memory_build_interval: int = 600
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"""记忆构建间隔（秒）"""
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memory_build_distribution: tuple[
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float,
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float,
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float,
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float,
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float,
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float,
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] = field(default_factory=lambda: (6.0, 3.0, 0.6, 32.0, 12.0, 0.4))
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"""记忆构建分布，参数：分布1均值，标准差，权重，分布2均值，标准差，权重"""
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memory_build_sample_num: int = 8
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"""记忆构建采样数量"""
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memory_build_sample_length: int = 40
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"""记忆构建采样长度"""
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memory_compress_rate: float = 0.1
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"""记忆压缩率"""
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forget_memory_interval: int = 1000
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"""记忆遗忘间隔（秒）"""
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memory_forget_time: int = 24
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"""记忆遗忘时间（小时）"""
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memory_forget_percentage: float = 0.01
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"""记忆遗忘比例"""
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consolidate_memory_interval: int = 1000
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"""记忆整合间隔（秒）"""
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consolidation_similarity_threshold: float = 0.7
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"""整合相似度阈值"""
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consolidate_memory_percentage: float = 0.01
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"""整合检查节点比例"""
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memory_ban_words: list[str] = field(default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"])
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"""不允许记忆的词列表"""
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@dataclass
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class MoodConfig(ConfigBase):
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"""情绪配置类"""
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mood_update_interval: int = 1
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"""情绪更新间隔（秒）"""
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mood_decay_rate: float = 0.95
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"""情绪衰减率"""
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mood_intensity_factor: float = 0.7
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"""情绪强度因子"""
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@dataclass
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class KeywordRuleConfig(ConfigBase):
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"""关键词规则配置类"""
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keywords: list[str] = field(default_factory=lambda: [])
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"""关键词列表"""
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regex: list[str] = field(default_factory=lambda: [])
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"""正则表达式列表"""
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reaction: str = ""
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"""关键词触发的反应"""
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def __post_init__(self):
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"""验证配置"""
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if not self.keywords and not self.regex:
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raise ValueError("关键词规则必须至少包含keywords或regex中的一个")
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if not self.reaction:
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raise ValueError("关键词规则必须包含reaction")
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# 验证正则表达式
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for pattern in self.regex:
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try:
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re.compile(pattern)
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except re.error as e:
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raise ValueError(f"无效的正则表达式 '{pattern}': {str(e)}") from e
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@dataclass
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class KeywordReactionConfig(ConfigBase):
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"""关键词配置类"""
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keyword_rules: list[KeywordRuleConfig] = field(default_factory=lambda: [])
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"""关键词规则列表"""
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regex_rules: list[KeywordRuleConfig] = field(default_factory=lambda: [])
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"""正则表达式规则列表"""
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def __post_init__(self):
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"""验证配置"""
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# 验证所有规则
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for rule in self.keyword_rules + self.regex_rules:
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if not isinstance(rule, KeywordRuleConfig):
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raise ValueError(f"规则必须是KeywordRuleConfig类型，而不是{type(rule).__name__}")
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@dataclass
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class ResponsePostProcessConfig(ConfigBase):
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"""回复后处理配置类"""
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enable_response_post_process: bool = True
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"""是否启用回复后处理，包括错别字生成器，回复分割器"""
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@dataclass
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class ChineseTypoConfig(ConfigBase):
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"""中文错别字配置类"""
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enable: bool = True
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"""是否启用中文错别字生成器"""
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error_rate: float = 0.01
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"""单字替换概率"""
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min_freq: int = 9
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"""最小字频阈值"""
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tone_error_rate: float = 0.1
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"""声调错误概率"""
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word_replace_rate: float = 0.006
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"""整词替换概率"""
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@dataclass
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class ResponseSplitterConfig(ConfigBase):
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"""回复分割器配置类"""
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enable: bool = True
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"""是否启用回复分割器"""
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max_length: int = 256
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"""回复允许的最大长度"""
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max_sentence_num: int = 3
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"""回复允许的最大句子数"""
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enable_kaomoji_protection: bool = False
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"""是否启用颜文字保护"""
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@dataclass
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class TelemetryConfig(ConfigBase):
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"""遥测配置类"""
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enable: bool = True
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"""是否启用遥测"""
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@dataclass
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class ExperimentalConfig(ConfigBase):
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"""实验功能配置类"""
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debug_show_chat_mode: bool = False
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"""是否在回复后显示当前聊天模式"""
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enable_friend_chat: bool = False
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"""是否启用好友聊天"""
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pfc_chatting: bool = False
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"""是否启用PFC"""
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@dataclass
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class MaimMessageConfig(ConfigBase):
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"""maim_message配置类"""
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use_custom: bool = False
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"""是否使用自定义的maim_message配置"""
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host: str = "127.0.0.1"
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"""主机地址"""
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port: int = 8090
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""""端口号"""
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mode: Literal["ws", "tcp"] = "ws"
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"""连接模式，支持ws和tcp"""
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use_wss: bool = False
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"""是否使用WSS安全连接"""
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cert_file: str = ""
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"""SSL证书文件路径，仅在use_wss=True时有效"""
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key_file: str = ""
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"""SSL密钥文件路径，仅在use_wss=True时有效"""
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auth_token: list[str] = field(default_factory=lambda: [])
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"""认证令牌，用于API验证，为空则不启用验证"""
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@dataclass
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class LPMMKnowledgeConfig(ConfigBase):
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"""LPMM知识库配置类"""
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enable: bool = True
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"""是否启用LPMM知识库"""
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rag_synonym_search_top_k: int = 10
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"""RAG同义词搜索的Top K数量"""
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rag_synonym_threshold: float = 0.8
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"""RAG同义词搜索的相似度阈值"""
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info_extraction_workers: int = 3
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"""信息提取工作线程数"""
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qa_relation_search_top_k: int = 10
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"""QA关系搜索的Top K数量"""
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qa_relation_threshold: float = 0.75
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"""QA关系搜索的相似度阈值"""
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qa_paragraph_search_top_k: int = 1000
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"""QA段落搜索的Top K数量"""
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qa_paragraph_node_weight: float = 0.05
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"""QA段落节点权重"""
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qa_ent_filter_top_k: int = 10
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"""QA实体过滤的Top K数量"""
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qa_ppr_damping: float = 0.8
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"""QA PageRank阻尼系数"""
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qa_res_top_k: int = 10
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"""QA最终结果的Top K数量"""
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@dataclass
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class ModelConfig(ConfigBase):
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"""模型配置类"""
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model_max_output_length: int = 800 # 最大回复长度
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utils: dict[str, Any] = field(default_factory=lambda: {})
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"""组件模型配置"""
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utils_small: dict[str, Any] = field(default_factory=lambda: {})
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"""组件小模型配置"""
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replyer_1: dict[str, Any] = field(default_factory=lambda: {})
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"""normal_chat首要回复模型模型配置"""
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replyer_2: dict[str, Any] = field(default_factory=lambda: {})
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"""normal_chat次要回复模型配置"""
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memory_summary: dict[str, Any] = field(default_factory=lambda: {})
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"""记忆的概括模型配置"""
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vlm: dict[str, Any] = field(default_factory=lambda: {})
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"""视觉语言模型配置"""
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focus_working_memory: dict[str, Any] = field(default_factory=lambda: {})
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"""专注工作记忆模型配置"""
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focus_tool_use: dict[str, Any] = field(default_factory=lambda: {})
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"""专注工具使用模型配置"""
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planner: dict[str, Any] = field(default_factory=lambda: {})
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"""规划模型配置"""
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relation: dict[str, Any] = field(default_factory=lambda: {})
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"""关系模型配置"""
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embedding: dict[str, Any] = field(default_factory=lambda: {})
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"""嵌入模型配置"""
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pfc_action_planner: dict[str, Any] = field(default_factory=lambda: {})
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"""PFC动作规划模型配置"""
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pfc_chat: dict[str, Any] = field(default_factory=lambda: {})
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"""PFC聊天模型配置"""
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pfc_reply_checker: dict[str, Any] = field(default_factory=lambda: {})
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"""PFC回复检查模型配置"""
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