from typing import Literal, Optional, List from pydantic import Field from src.config.config_base import ValidatedConfigBase """ 须知： 1. 本文件中记录了所有的配置项 2. 重要的配置类继承自ValidatedConfigBase进行Pydantic验证 3. 所有新增的class都应在config.py中的Config类中添加字段 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 """ class DatabaseConfig(ValidatedConfigBase): """数据库配置类""" database_type: Literal["sqlite", "mysql"] = Field(default="sqlite", description="数据库类型") sqlite_path: str = Field(default="data/MaiBot.db", description="SQLite数据库文件路径") mysql_host: str = Field(default="localhost", description="MySQL服务器地址") mysql_port: int = Field(default=3306, ge=1, le=65535, description="MySQL服务器端口") mysql_database: str = Field(default="maibot", description="MySQL数据库名") mysql_user: str = Field(default="root", description="MySQL用户名") mysql_password: str = Field(default="", description="MySQL密码") mysql_charset: str = Field(default="utf8mb4", description="MySQL字符集") mysql_unix_socket: str = Field(default="", description="MySQL Unix套接字路径") mysql_ssl_mode: Literal["DISABLED", "PREFERRED", "REQUIRED", "VERIFY_CA", "VERIFY_IDENTITY"] = Field(default="DISABLED", description="SSL模式") mysql_ssl_ca: str = Field(default="", description="SSL CA证书路径") mysql_ssl_cert: str = Field(default="", description="SSL客户端证书路径") mysql_ssl_key: str = Field(default="", description="SSL客户端密钥路径") mysql_autocommit: bool = Field(default=True, description="自动提交事务") mysql_sql_mode: str = Field(default="TRADITIONAL", description="SQL模式") connection_pool_size: int = Field(default=10, ge=1, description="连接池大小") connection_timeout: int = Field(default=10, ge=1, description="连接超时时间") class BotConfig(ValidatedConfigBase): """QQ机器人配置类""" platform: str = Field(..., description="平台") qq_account: int = Field(..., description="QQ账号") nickname: str = Field(..., description="昵称") alias_names: List[str] = Field(default_factory=list, description="别名列表") class PersonalityConfig(ValidatedConfigBase): """人格配置类""" personality_core: str = Field(..., description="核心人格") personality_side: str = Field(..., description="人格侧写") identity: str = Field(default="", description="身份特征") reply_style: str = Field(default="", description="表达风格") prompt_mode: Literal["s4u", "normal"] = Field(default="s4u", description="Prompt模式") compress_personality: bool = Field(default=True, description="是否压缩人格") compress_identity: bool = Field(default=True, description="是否压缩身份") class RelationshipConfig(ValidatedConfigBase): """关系配置类""" enable_relationship: bool = Field(default=True, description="是否启用关系") relation_frequency: float = Field(default=1.0, description="关系频率") class ChatConfig(ValidatedConfigBase): """聊天配置类""" max_context_size: int = Field(default=18, description="最大上下文大小") replyer_random_probability: float = Field(default=0.5, description="回复者随机概率") thinking_timeout: int = Field(default=40, description="思考超时时间") talk_frequency: float = Field(default=1.0, description="聊天频率") mentioned_bot_inevitable_reply: bool = Field(default=False, description="提到机器人的必然回复") at_bot_inevitable_reply: bool = Field(default=False, description="@机器人的必然回复") talk_frequency_adjust: list[list[str]] = Field(default_factory=lambda: [], description="聊天频率调整") focus_value: float = Field(default=1.0, description="专注值") force_focus_private: bool = Field(default=False, description="强制专注私聊") group_chat_mode: Literal["auto", "normal", "focus"] = Field(default="auto", description="群聊模式") timestamp_display_mode: Literal["normal", "normal_no_YMD", "relative"] = Field(default="normal_no_YMD", description="时间戳显示模式") enable_proactive_thinking: bool = Field(default=False, description="启用主动思考") proactive_thinking_interval: int = Field(default=1500, description="主动思考间隔") The_scope_that_proactive_thinking_can_trigger: str = Field(default="all", description="主动思考可以触发的范围") proactive_thinking_in_private: bool = Field(default=True, description="主动思考可以在私聊里面启用") proactive_thinking_in_group: bool = Field(default=True, description="主动思考可以在群聊里面启用") proactive_thinking_enable_in_private: List[str] = Field(default_factory=list, description="启用主动思考的私聊范围，格式：platform:user_id，为空则不限制") proactive_thinking_enable_in_groups: List[str] = Field(default_factory=list, description="启用主动思考的群聊范围，格式：platform:group_id，为空则不限制") delta_sigma: int = Field(default=120, description="采用正态分布随机时间间隔") def get_current_talk_frequency(self, chat_stream_id: Optional[str] = None) -> float: """ 根据当前时间和聊天流获取对应的 talk_frequency Args: chat_stream_id: 聊天流ID，格式为 "platform:chat_id:type" Returns: float: 对应的频率值 """ if not self.talk_frequency_adjust: return self.talk_frequency # 优先检查聊天流特定的配置 if chat_stream_id: stream_frequency = self._get_stream_specific_frequency(chat_stream_id) if stream_frequency is not None: return stream_frequency # 检查全局时段配置（第一个元素为空字符串的配置） global_frequency = self._get_global_frequency() if global_frequency is not None: return global_frequency # 如果都没有匹配，返回默认值 return self.talk_frequency def _get_time_based_frequency(self, time_freq_list: list[str]) -> Optional[float]: """ 根据时间配置列表获取当前时段的频率 Args: time_freq_list: 时间频率配置列表，格式为 ["HH:MM,frequency", ...] Returns: float: 频率值，如果没有配置则返回 None """ from datetime import datetime current_time = datetime.now().strftime("%H:%M") current_hour, current_minute = map(int, current_time.split(":")) current_minutes = current_hour * 60 + current_minute # 解析时间频率配置 time_freq_pairs = [] for time_freq_str in time_freq_list: try: time_str, freq_str = time_freq_str.split(",") hour, minute = map(int, time_str.split(":")) frequency = float(freq_str) minutes = hour * 60 + minute time_freq_pairs.append((minutes, frequency)) except (ValueError, IndexError): continue if not time_freq_pairs: return None # 按时间排序 time_freq_pairs.sort(key=lambda x: x[0]) # 查找当前时间对应的频率 current_frequency = None for minutes, frequency in time_freq_pairs: if current_minutes >= minutes: current_frequency = frequency else: break # 如果当前时间在所有配置时间之前，使用最后一个时间段的频率（跨天逻辑） if current_frequency is None and time_freq_pairs: current_frequency = time_freq_pairs[-1][1] return current_frequency def _get_stream_specific_frequency(self, chat_stream_id: str): """ 获取特定聊天流在当前时间的频率 Args: chat_stream_id: 聊天流ID（哈希值） Returns: float: 频率值，如果没有配置则返回 None """ # 查找匹配的聊天流配置 for config_item in self.talk_frequency_adjust: if not config_item or len(config_item) < 2: continue stream_config_str = config_item[0] # 例如 "qq:1026294844:group" # 解析配置字符串并生成对应的 chat_id config_chat_id = self._parse_stream_config_to_chat_id(stream_config_str) if config_chat_id is None: continue # 比较生成的 chat_id if config_chat_id != chat_stream_id: continue # 使用通用的时间频率解析方法 return self._get_time_based_frequency(config_item[1:]) return None def _parse_stream_config_to_chat_id(self, stream_config_str: str) -> Optional[str]: """ 解析流配置字符串并生成对应的 chat_id Args: stream_config_str: 格式为 "platform:id:type" 的字符串 Returns: str: 生成的 chat_id，如果解析失败则返回 None """ try: parts = stream_config_str.split(":") if len(parts) != 3: return None platform = parts[0] id_str = parts[1] stream_type = parts[2] # 判断是否为群聊 is_group = stream_type == "group" # 使用与 ChatStream.get_stream_id 相同的逻辑生成 chat_id import hashlib if is_group: components = [platform, str(id_str)] else: components = [platform, str(id_str), "private"] key = "_".join(components) return hashlib.md5(key.encode()).hexdigest() except (ValueError, IndexError): return None def _get_global_frequency(self) -> Optional[float]: """ 获取全局默认频率配置 Returns: float: 频率值，如果没有配置则返回 None """ for config_item in self.talk_frequency_adjust: if not config_item or len(config_item) < 2: continue # 检查是否为全局默认配置（第一个元素为空字符串） if config_item[0] == "": return self._get_time_based_frequency(config_item[1:]) return None class MessageReceiveConfig(ValidatedConfigBase): """消息接收配置类""" ban_words: List[str] = Field(default_factory=lambda: list(), description="禁用词列表") ban_msgs_regex: List[str] = Field(default_factory=lambda: list(), description="禁用消息正则列表") class NormalChatConfig(ValidatedConfigBase): """普通聊天配置类""" willing_mode: str = Field(default="classical", description="意愿模式") class ExpressionRule(ValidatedConfigBase): """表达学习规则""" chat_stream_id: str = Field(..., description="聊天流ID，空字符串表示全局") use_expression: bool = Field(default=True, description="是否使用学到的表达") learn_expression: bool = Field(default=True, description="是否学习表达") learning_strength: float = Field(default=1.0, description="学习强度") group: Optional[str] = Field(default=None, description="表达共享组") class ExpressionConfig(ValidatedConfigBase): """表达配置类""" rules: List[ExpressionRule] = Field(default_factory=list, description="表达学习规则") def _parse_stream_config_to_chat_id(self, stream_config_str: str) -> Optional[str]: """ 解析流配置字符串并生成对应的 chat_id Args: stream_config_str: 格式为 "platform:id:type" 的字符串 Returns: str: 生成的 chat_id，如果解析失败则返回 None """ try: parts = stream_config_str.split(":") if len(parts) != 3: return None platform = parts[0] id_str = parts[1] stream_type = parts[2] # 判断是否为群聊 is_group = stream_type == "group" # 使用与 ChatStream.get_stream_id 相同的逻辑生成 chat_id import hashlib if is_group: components = [platform, str(id_str)] else: components = [platform, str(id_str), "private"] key = "_".join(components) return hashlib.md5(key.encode()).hexdigest() except (ValueError, IndexError): return None def get_expression_config_for_chat(self, chat_stream_id: Optional[str] = None) -> tuple[bool, bool, float]: """ 根据聊天流ID获取表达配置 Args: chat_stream_id: 聊天流ID，格式为哈希值 Returns: tuple: (是否使用表达, 是否学习表达, 学习间隔) """ if not self.rules: # 如果没有配置，使用默认值：启用表达，启用学习，强度1.0 return True, True, 1.0 # 优先检查聊天流特定的配置 if chat_stream_id: for rule in self.rules: if rule.chat_stream_id and self._parse_stream_config_to_chat_id(rule.chat_stream_id) == chat_stream_id: return rule.use_expression, rule.learn_expression, rule.learning_strength # 检查全局配置（chat_stream_id为空字符串的配置） for rule in self.rules: if rule.chat_stream_id == "": return rule.use_expression, rule.learn_expression, rule.learning_strength # 如果都没有匹配，返回默认值 return True, True, 1.0 class ToolHistoryConfig(ValidatedConfigBase): """工具历史记录配置类""" enable_history: bool = True """是否启用工具历史记录""" enable_prompt_history: bool = True """是否在提示词中加入工具历史记录""" max_history: int = 5 """注入到提示词中的最大工具历史记录数量""" data_dir: str = "data/tool_history" """历史记录保存目录""" class ToolConfig(ValidatedConfigBase): """工具配置类""" enable_tool: bool = Field(default=False, description="启用工具") history: ToolHistoryConfig = Field(default_factory=ToolHistoryConfig) """工具历史记录配置""" class VoiceConfig(ValidatedConfigBase): """语音识别配置类""" enable_asr: bool = Field(default=False, description="启用语音识别") class EmojiConfig(ValidatedConfigBase): """表情包配置类""" emoji_chance: float = Field(default=0.6, description="表情包出现概率") emoji_activate_type: str = Field(default="random", description="表情包激活类型") max_reg_num: int = Field(default=200, description="最大表情包数量") do_replace: bool = Field(default=True, description="是否替换表情包") check_interval: int = Field(default=120, description="检查间隔") steal_emoji: bool = Field(default=True, description="是否偷取表情包") content_filtration: bool = Field(default=False, description="内容过滤") filtration_prompt: str = Field(default="符合公序良俗", description="过滤提示") enable_emotion_analysis: bool = Field(default=True, description="启用情感分析") class MemoryConfig(ValidatedConfigBase): """记忆配置类""" enable_memory: bool = Field(default=True, description="启用记忆") memory_build_interval: int = Field(default=600, description="记忆构建间隔") memory_build_distribution: list[float] = Field(default_factory=lambda: [6.0, 3.0, 0.6, 32.0, 12.0, 0.4], description="记忆构建分布") memory_build_sample_num: int = Field(default=8, description="记忆构建样本数量") memory_build_sample_length: int = Field(default=40, description="记忆构建样本长度") memory_compress_rate: float = Field(default=0.1, description="记忆压缩率") forget_memory_interval: int = Field(default=1000, description="遗忘记忆间隔") memory_forget_time: int = Field(default=24, description="记忆遗忘时间") memory_forget_percentage: float = Field(default=0.01, description="记忆遗忘百分比") consolidate_memory_interval: int = Field(default=1000, description="记忆巩固间隔") consolidation_similarity_threshold: float = Field(default=0.7, description="巩固相似性阈值") consolidate_memory_percentage: float = Field(default=0.01, description="巩固记忆百分比") memory_ban_words: list[str] = Field(default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"], description="记忆禁用词") enable_instant_memory: bool = Field(default=True, description="启用即时记忆") enable_llm_instant_memory: bool = Field(default=True, description="启用基于LLM的瞬时记忆") enable_vector_instant_memory: bool = Field(default=True, description="启用基于向量的瞬时记忆") class MoodConfig(ValidatedConfigBase): """情绪配置类""" enable_mood: bool = Field(default=False, description="启用情绪") mood_update_threshold: float = Field(default=1.0, description="情绪更新阈值") class KeywordRuleConfig(ValidatedConfigBase): """关键词规则配置类""" keywords: list[str] = Field(default_factory=lambda: [], description="关键词列表") regex: list[str] = Field(default_factory=lambda: [], description="正则表达式列表") reaction: str = Field(default="", description="反应内容") def __post_init__(self): import re if not self.keywords and not self.regex: raise ValueError("关键词规则必须至少包含keywords或regex中的一个") if not self.reaction: raise ValueError("关键词规则必须包含reaction") for pattern in self.regex: try: re.compile(pattern) except re.error as e: raise ValueError(f"无效的正则表达式 '{pattern}': {str(e)}") from e class KeywordReactionConfig(ValidatedConfigBase): """关键词配置类""" keyword_rules: list[KeywordRuleConfig] = Field(default_factory=lambda: [], description="关键词规则列表") regex_rules: list[KeywordRuleConfig] = Field(default_factory=lambda: [], description="正则表达式规则列表") class CustomPromptConfig(ValidatedConfigBase): """自定义提示词配置类""" image_prompt: str = Field(default="", description="图片提示词") planner_custom_prompt_enable: bool = Field(default=False, description="启用规划器自定义提示词") planner_custom_prompt_content: str = Field(default="", description="规划器自定义提示词内容") class ResponsePostProcessConfig(ValidatedConfigBase): """回复后处理配置类""" enable_response_post_process: bool = Field(default=True, description="启用回复后处理") class ChineseTypoConfig(ValidatedConfigBase): """中文错别字配置类""" enable: bool = Field(default=True, description="启用") error_rate: float = Field(default=0.01, description="错误率") min_freq: int = Field(default=9, description="最小频率") tone_error_rate: float = Field(default=0.1, description="语调错误率") word_replace_rate: float = Field(default=0.006, description="词语替换率") class ResponseSplitterConfig(ValidatedConfigBase): """回复分割器配置类""" enable: bool = Field(default=True, description="启用") max_length: int = Field(default=256, description="最大长度") max_sentence_num: int = Field(default=3, description="最大句子数") enable_kaomoji_protection: bool = Field(default=False, description="启用颜文字保护") class DebugConfig(ValidatedConfigBase): """调试配置类""" show_prompt: bool = Field(default=False, description="显示提示") class ExperimentalConfig(ValidatedConfigBase): """实验功能配置类""" pfc_chatting: bool = Field(default=False, description="启用PFC聊天") class MaimMessageConfig(ValidatedConfigBase): """maim_message配置类""" use_custom: bool = Field(default=False, description="启用自定义") host: str = Field(default="127.0.0.1", description="主机") port: int = Field(default=8090, description="端口") mode: Literal["ws", "tcp"] = Field(default="ws", description="模式") use_wss: bool = Field(default=False, description="启用WSS") cert_file: str = Field(default="", description="证书文件") key_file: str = Field(default="", description="密钥文件") auth_token: list[str] = Field(default_factory=lambda: [], description="认证令牌列表") class LPMMKnowledgeConfig(ValidatedConfigBase): """LPMM知识库配置类""" enable: bool = Field(default=True, description="启用") rag_synonym_search_top_k: int = Field(default=10, description="RAG同义词搜索Top K") rag_synonym_threshold: float = Field(default=0.8, description="RAG同义词阈值") info_extraction_workers: int = Field(default=3, description="信息提取工作线程数") qa_relation_search_top_k: int = Field(default=10, description="QA关系搜索Top K") qa_relation_threshold: float = Field(default=0.75, description="QA关系阈值") qa_paragraph_search_top_k: int = Field(default=1000, description="QA段落搜索Top K") qa_paragraph_node_weight: float = Field(default=0.05, description="QA段落节点权重") qa_ent_filter_top_k: int = Field(default=10, description="QA实体过滤Top K") qa_ppr_damping: float = Field(default=0.8, description="QA PPR阻尼系数") qa_res_top_k: int = Field(default=10, description="QA结果Top K") embedding_dimension: int = Field(default=1024, description="嵌入维度") class ScheduleConfig(ValidatedConfigBase): """日程配置类""" enable: bool = Field(default=True, description="启用") guidelines: Optional[str] = Field(default=None, description="指导方针") class DependencyManagementConfig(ValidatedConfigBase): """插件Python依赖管理配置类""" auto_install: bool = Field(default=True, description="启用自动安装") auto_install_timeout: int = Field(default=300, description="自动安装超时时间") use_mirror: bool = Field(default=False, description="使用镜像") mirror_url: str = Field(default="", description="镜像URL") use_proxy: bool = Field(default=False, description="使用代理") proxy_url: str = Field(default="", description="代理URL") pip_options: list[str] = Field(default_factory=lambda: ["--no-warn-script-location", "--disable-pip-version-check"], description="Pip选项") prompt_before_install: bool = Field(default=False, description="安装前提示") install_log_level: str = Field(default="INFO", description="安装日志级别") class VideoAnalysisConfig(ValidatedConfigBase): """视频分析配置类""" enable: bool = Field(default=True, description="启用") analysis_mode: str = Field(default="batch_frames", description="分析模式") frame_extraction_mode: str = Field(default="keyframe", description="抽帧模式：keyframe(关键帧), fixed_number(固定数量), time_interval(时间间隔)") frame_interval_seconds: float = Field(default=2.0, description="抽帧时间间隔") max_frames: int = Field(default=8, description="最大帧数") frame_quality: int = Field(default=85, description="帧质量") max_image_size: int = Field(default=800, description="最大图像大小") enable_frame_timing: bool = Field(default=True, description="启用帧时间") batch_analysis_prompt: str = Field(default="", description="批量分析提示") # Rust模块相关配置 rust_keyframe_threshold: float = Field(default=2.0, description="关键帧检测阈值") rust_use_simd: bool = Field(default=True, description="启用SIMD优化") rust_block_size: int = Field(default=8192, description="Rust处理块大小") rust_threads: int = Field(default=0, description="Rust线程数，0表示自动检测") ffmpeg_path: str = Field(default="ffmpeg", description="FFmpeg可执行文件路径") class WebSearchConfig(ValidatedConfigBase): """联网搜索组件配置类""" enable_web_search_tool: bool = Field(default=True, description="启用网络搜索工具") enable_url_tool: bool = Field(default=True, description="启用URL工具") tavily_api_keys: list[str] = Field(default_factory=lambda: [], description="Tavily API密钥列表，支持轮询机制") exa_api_keys: list[str] = Field(default_factory=lambda: [], description="exa API密钥列表，支持轮询机制") enabled_engines: list[str] = Field(default_factory=lambda: ["ddg"], description="启用的搜索引擎") search_strategy: Literal["fallback","single","parallel"] = Field(default="single", description="搜索策略") class AntiPromptInjectionConfig(ValidatedConfigBase): """LLM反注入系统配置类""" enabled: bool = Field(default=True, description="启用") enabled_LLM: bool = Field(default=True, description="启用LLM") enabled_rules: bool = Field(default=True, description="启用规则") process_mode: str = Field(default="lenient", description="处理模式") whitelist: list[list[str]] = Field(default_factory=list, description="白名单") llm_detection_enabled: bool = Field(default=True, description="启用LLM检测") llm_model_name: str = Field(default="anti_injection", description="LLM模型名称") llm_detection_threshold: float = Field(default=0.7, description="LLM检测阈值") cache_enabled: bool = Field(default=True, description="启用缓存") cache_ttl: int = Field(default=3600, description="缓存TTL") max_message_length: int = Field(default=4096, description="最大消息长度") stats_enabled: bool = Field(default=True, description="启用统计信息") auto_ban_enabled: bool = Field(default=True, description="启用自动禁用") auto_ban_violation_threshold: int = Field(default=3, description="自动禁用违规阈值") auto_ban_duration_hours: int = Field(default=2, description="自动禁用持续时间（小时）") shield_prefix: str = Field(default="🛡️ ", description="保护前缀") shield_suffix: str = Field(default=" 🛡️", description="保护后缀") class PluginsConfig(ValidatedConfigBase): """插件配置""" centralized_config: bool = Field(default=True, description="是否启用插件配置集中化管理") class SleepSystemConfig(ValidatedConfigBase): """睡眠系统配置类""" enable: bool = Field(default=True, description="是否启用睡眠系统") wakeup_threshold: float = Field(default=15.0, ge=1.0, description="唤醒阈值，达到此值时会被唤醒") private_message_increment: float = Field(default=3.0, ge=0.1, description="私聊消息增加的唤醒度") group_mention_increment: float = Field(default=2.0, ge=0.1, description="群聊艾特增加的唤醒度") decay_rate: float = Field(default=0.2, ge=0.0, description="每次衰减的唤醒度数值") decay_interval: float = Field(default=30.0, ge=1.0, description="唤醒度衰减间隔(秒)") angry_duration: float = Field(default=300.0, ge=10.0, description="愤怒状态持续时间(秒)") angry_prompt: str = Field(default="你被人吵醒了非常生气，说话带着怒气", description="被吵醒后的愤怒提示词") re_sleep_delay_minutes: int = Field(default=5, ge=1, description="被唤醒后，如果多久没有新消息则尝试重新入睡（分钟）") # --- 失眠机制相关参数 --- enable_insomnia_system: bool = Field(default=True, description="是否启用失眠系统") insomnia_duration_minutes: int = Field(default=30, ge=1, description="单次失眠状态的持续时间（分钟）") sleep_pressure_threshold: float = Field(default=30.0, description="触发“压力不足型失眠”的睡眠压力阈值") deep_sleep_threshold: float = Field(default=80.0, description="进入“深度睡眠”的睡眠压力阈值") insomnia_chance_low_pressure: float = Field(default=0.6, ge=0.0, le=1.0, description="压力不足时的失眠基础概率") insomnia_chance_normal_pressure: float = Field(default=0.1, ge=0.0, le=1.0, description="压力正常时的失眠基础概率") sleep_pressure_increment: float = Field(default=1.5, ge=0.0, description="每次AI执行动作后，增加的睡眠压力值") sleep_pressure_decay_rate: float = Field(default=1.5, ge=0.0, description="睡眠时，每分钟衰减的睡眠压力值") # --- 弹性睡眠与睡前消息 --- enable_flexible_sleep: bool = Field(default=True, description="是否启用弹性睡眠") flexible_sleep_pressure_threshold: float = Field(default=40.0, description="触发弹性睡眠的睡眠压力阈值，低于该值可能延迟入睡") max_sleep_delay_minutes: int = Field(default=60, description="单日最大延迟入睡分钟数") enable_pre_sleep_notification: bool = Field(default=True, description="是否启用睡前消息") pre_sleep_notification_groups: List[str] = Field(default_factory=list, description="接收睡前消息的群号列表, 格式: [\"platform:group_id1\", \"platform:group_id2\"]") pre_sleep_prompt: str = Field(default="我准备睡觉了，请生成一句简短自然的晚安问候。", description="用于生成睡前消息的提示") class MonthlyPlanSystemConfig(ValidatedConfigBase): """月度计划系统配置类""" enable: bool = Field(default=True, description="是否启用本功能") max_plans_per_month: int = Field(default=20, ge=1, description="每个月允许存在的最大计划数量") completion_threshold: int = Field(default=3, ge=1, description="计划使用多少次后自动标记为已完成") avoid_repetition_days: int = Field(default=7, ge=1, description="多少天内不重复抽取同一个计划") guidelines: Optional[str] = Field(default=None, description="月度计划生成的指导原则") class ContextGroup(ValidatedConfigBase): """上下文共享组配置""" name: str = Field(..., description="共享组的名称") chat_ids: List[str] = Field(..., description="属于该组的聊天ID列表") class CrossContextConfig(ValidatedConfigBase): """跨群聊上下文共享配置""" enable: bool = Field(default=False, description="是否启用跨群聊上下文共享功能") groups: List[ContextGroup] = Field(default_factory=list, description="上下文共享组列表") class MaizoneIntercomConfig(ValidatedConfigBase): """Maizone互通组配置""" enable: bool = Field(default=False, description="是否启用Maizone互通组功能") groups: List[ContextGroup] = Field(default_factory=list, description="Maizone互通组列表") class CommandConfig(ValidatedConfigBase): """命令系统配置类""" command_prefixes: List[str] = Field(default_factory=lambda: ['/', '!', '.', '#'], description="支持的命令前缀列表") class PermissionConfig(ValidatedConfigBase): """权限系统配置类""" # Master用户配置（拥有最高权限，无视所有权限节点） master_users: List[List[str]] = Field(default_factory=list, description="Master用户列表，格式: [[platform, user_id], ...]")