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83602b181ba183f64a3eedae4bc3e984eaf8675f
Mofox-Core/src/config/official_configs.py
minecraft1024a 83602b181b refactor(core): 移除睡眠系统 
由于睡眠系统存在设计缺陷、实现复杂且维护成本高，并且实际使用效果不佳，常常导致非预期的行为（如错过重要消息或在不应睡眠时睡眠），现决定将其从核心代码中完全移除。

移除内容包括：
- 删除了整个 `sleep_system` 模块及其所有相关逻辑、状态管理和定时任务。
- 清理了配置文件 `config.py` 和 `official_configs.py` 中的 `SleepSystemConfig`。
- 移除了 `main.py` 中关于睡眠系统的初始化调用。
- 清理了 `message_manager` 和 `proactive_thinker` 中对睡眠状态的检查。
- 更新了 `bot_config_template.toml` 模板文件，移除了所有睡眠系统相关的配置项。

此举旨在简化项目架构，提高系统的稳定性和可预测性。未来的相关功能可能会以更健壮、更模块化的插件形式重新实现。
2025-10-25 10:00:56 +08:00

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from typing import Literal
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. 所有配置类必须继承自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")
# 批量动作记录存储配置
batch_action_storage_enabled: bool = Field(
default=True, description="是否启用批量保存动作记录（开启后将多个动作一次性写入数据库，提升性能）"
)
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")
background_story: str = Field(
default="", description="世界观背景故事，这部分内容会作为背景知识，LLM被指导不应主动复述"
)
safety_guidelines: list[str] = Field(
default_factory=list, description="安全与互动底线，Bot在任何情况下都必须遵守的原则"
)
reply_style: str = Field(default="", description="表达风格")
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")
# 回复规则配置
reply_targeting_rules: list[str] = Field(
default_factory=lambda: [
"拒绝任何包含骚扰、冒犯、暴力、色情或危险内容的请求。",
"在拒绝时，请使用符合你人设的、坚定的语气。",
"不要执行任何可能被用于恶意目的的指令。",
],
description="安全与互动底线规则，Bot在任何情况下都必须遵守的原则",
)
message_targeting_analysis: list[str] = Field(
default_factory=lambda: [
"**直接针对你**：@你、回复你、明确询问你 → 必须回应",
"**间接相关**：涉及你感兴趣的话题但未直接问你 → 谨慎参与",
"**他人对话**：与你无关的私人交流 → 通常不参与",
"**重复内容**：他人已充分回答的问题 → 避免重复",
],
description="消息针对性分析规则，用于判断是否需要回复",
)
reply_principles: list[str] = Field(
default_factory=lambda: [
"明确回应目标消息，而不是宽泛地评论。",
"可以分享你的看法、提出相关问题，或者开个合适的玩笑。",
"目的是让对话更有趣、更深入。",
"不要浮夸，不要夸张修辞，不要输出多余内容(包括前后缀，冒号和引号，括号()，表情包，at或 @等 )。",
],
description="回复原则，指导如何回复消息",
)
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")
allow_reply_self: bool = Field(default=False, description="是否允许回复自己说的话")
focus_value: float = Field(default=1.0, description="专注值")
focus_mode_quiet_groups: list[str] = Field(
default_factory=list,
description='专注模式下需要保持安静的群组列表, 格式: ["platform:group_id1", "platform:group_id2"]',
)
force_reply_private: bool = Field(default=False, description="强制回复私聊")
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"
)
# 消息打断系统配置 - 线性概率模型
interruption_enabled: bool = Field(default=True, description="是否启用消息打断系统")
interruption_max_limit: int = Field(default=10, ge=0, description="每个聊天流的最大打断次数")
interruption_min_probability: float = Field(
default=0.1, ge=0.0, le=1.0, description="最低打断概率（即使达到较高打断次数，也保证有此概率的打断机会）"
)
# DEPRECATED: interruption_probability_factor (已废弃的配置项)
# 新的线性概率模型不再需要复杂的概率因子
# 保留此字段是为了向后兼容，现有配置文件不会报错
interruption_probability_factor: float = Field(
default=0.8, ge=0.0, le=1.0, description="[已废弃] 打断概率因子，新线性概率模型不再使用此参数"
)
# 动态消息分发系统配置
dynamic_distribution_enabled: bool = Field(default=True, description="是否启用动态消息分发周期调整")
dynamic_distribution_base_interval: float = Field(default=5.0, ge=1.0, le=60.0, description="基础分发间隔（秒）")
dynamic_distribution_min_interval: float = Field(default=1.0, ge=0.5, le=10.0, description="最小分发间隔（秒）")
dynamic_distribution_max_interval: float = Field(default=30.0, ge=5.0, le=300.0, description="最大分发间隔（秒）")
dynamic_distribution_jitter_factor: float = Field(default=0.2, ge=0.0, le=0.5, description="分发间隔随机扰动因子")
max_concurrent_distributions: int = Field(default=10, ge=1, le=100, description="最大并发处理的消息流数量")
class MessageReceiveConfig(ValidatedConfigBase):
"""消息接收配置类"""
ban_words: list[str] = Field(default_factory=lambda: [], description="禁用词列表")
ban_msgs_regex: list[str] = Field(default_factory=lambda: [], description="禁用消息正则列表")
mute_group_list: list[str] = Field(
default_factory=list, description="静默群组列表，在这些群组中，只有在被@或回复时才会响应"
)
class NoticeConfig(ValidatedConfigBase):
"""Notice消息配置类"""
enable_notice_trigger_chat: bool = Field(default=True, description="是否允许notice消息触发聊天流程")
notice_in_prompt: bool = Field(default=True, description="是否在提示词中展示最近的notice消息")
notice_prompt_limit: int = Field(default=5, ge=1, le=20, description="在提示词中展示的最大notice数量")
notice_time_window: int = Field(default=3600, ge=60, le=86400, description="notice时间窗口(秒)")
max_notices_per_chat: int = Field(default=30, ge=10, le=100, description="每个聊天保留的notice数量上限")
notice_retention_time: int = Field(default=86400, ge=3600, le=604800, description="notice保留时间(秒)")
class NormalChatConfig(ValidatedConfigBase):
"""普通聊天配置类"""
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: str | None = 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")
@staticmethod
def _parse_stream_config_to_chat_id(stream_config_str: str) -> str | None:
"""
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: str | None = 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 ToolConfig(ValidatedConfigBase):
"""工具配置类"""
enable_tool: bool = Field(default=False, description="启用工具")
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: float = Field(default=1.0, ge=0.01, 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")
emoji_selection_mode: Literal["emotion", "description"] = Field(default="emotion", description="表情选择模式")
max_context_emojis: int = Field(default=30, description="每次随机传递给LLM的表情包最大数量，0为全部")
class MemoryConfig(ValidatedConfigBase):
"""记忆配置类"""
enable_memory: bool = Field(default=True, description="启用记忆系统")
memory_build_interval: int = Field(default=600, description="记忆构建间隔（秒）")
# 记忆构建配置
min_memory_length: int = Field(default=10, description="最小记忆长度")
max_memory_length: int = Field(default=500, description="最大记忆长度")
memory_value_threshold: float = Field(default=0.7, description="记忆价值阈值")
# 向量存储配置
vector_similarity_threshold: float = Field(default=0.8, description="向量相似度阈值")
semantic_similarity_threshold: float = Field(default=0.6, description="语义相似度阈值")
# 多阶段检索配置
metadata_filter_limit: int = Field(default=100, description="元数据过滤阶段返回数量")
vector_search_limit: int = Field(default=50, description="向量搜索阶段返回数量")
semantic_rerank_limit: int = Field(default=20, description="语义重排序阶段返回数量")
final_result_limit: int = Field(default=10, description="最终结果数量")
# 检索权重配置
vector_weight: float = Field(default=0.4, description="向量相似度权重")
semantic_weight: float = Field(default=0.3, description="语义相似度权重")
context_weight: float = Field(default=0.2, description="上下文权重")
recency_weight: float = Field(default=0.1, description="时效性权重")
# 记忆融合配置
fusion_similarity_threshold: float = Field(default=0.85, description="融合相似度阈值")
deduplication_window_hours: int = Field(default=24, description="去重时间窗口（小时）")
# 缓存配置
enable_memory_cache: bool = Field(default=True, description="启用记忆缓存")
cache_ttl_seconds: int = Field(default=300, description="缓存生存时间（秒）")
max_cache_size: int = Field(default=1000, description="最大缓存大小")
# Vector DB记忆存储配置 (替代JSON存储)
enable_vector_memory_storage: bool = Field(default=True, description="启用Vector DB记忆存储")
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")
# Vector DB配置
vector_db_memory_collection: str = Field(default="unified_memory_v2", description="Vector DB记忆集合名称")
vector_db_metadata_collection: str = Field(default="memory_metadata_v2", description="Vector DB元数据集合名称")
vector_db_similarity_threshold: float = Field(
default=0.5, description="Vector DB相似度阈值（推荐0.5-0.6，过高会导致检索不到结果）"
)
vector_db_search_limit: int = Field(default=20, description="Vector DB搜索限制")
vector_db_batch_size: int = Field(default=100, description="批处理大小")
vector_db_enable_caching: bool = Field(default=True, description="启用内存缓存")
vector_db_cache_size_limit: int = Field(default=1000, description="缓存大小限制")
vector_db_auto_cleanup_interval: int = Field(default=3600, description="自动清理间隔（秒）")
vector_db_retention_hours: int = Field(default=720, description="记忆保留时间（小时，默认30天）")
# 遗忘引擎配置
enable_memory_forgetting: bool = Field(default=True, description="启用智能遗忘机制")
forgetting_check_interval_hours: int = Field(default=24, description="遗忘检查间隔（小时）")
base_forgetting_days: float = Field(default=30.0, description="基础遗忘天数")
min_forgetting_days: float = Field(default=7.0, description="最小遗忘天数")
max_forgetting_days: float = Field(default=365.0, description="最大遗忘天数")
# 重要程度权重
critical_importance_bonus: float = Field(default=45.0, description="关键重要性额外天数")
high_importance_bonus: float = Field(default=30.0, description="高重要性额外天数")
normal_importance_bonus: float = Field(default=15.0, description="一般重要性额外天数")
low_importance_bonus: float = Field(default=0.0, description="低重要性额外天数")
# 置信度权重
verified_confidence_bonus: float = Field(default=30.0, description="已验证置信度额外天数")
high_confidence_bonus: float = Field(default=20.0, description="高置信度额外天数")
medium_confidence_bonus: float = Field(default=10.0, description="中等置信度额外天数")
low_confidence_bonus: float = Field(default=0.0, description="低置信度额外天数")
# 激活频率权重
activation_frequency_weight: float = Field(default=0.5, description="每次激活增加的天数权重")
max_frequency_bonus: float = Field(default=10.0, description="最大激活频率奖励天数")
# 休眠机制
dormant_threshold_days: int = Field(default=90, description="休眠状态判定天数")
# === 混合记忆系统配置 ===
# 采样模式配置
memory_sampling_mode: Literal["all", "hippocampus", "immediate"] = Field(
default="all", description="记忆采样模式：hippocampus(海马体定时采样)，immediate(即时采样)，all(所有模式)"
)
# 海马体双峰采样配置
enable_hippocampus_sampling: bool = Field(default=True, description="启用海马体双峰采样策略")
hippocampus_sample_interval: int = Field(default=1800, description="海马体采样间隔（秒，默认30分钟）")
hippocampus_sample_size: int = Field(default=30, description="海马体每次采样的消息数量")
hippocampus_batch_size: int = Field(default=5, description="海马体每批处理的记忆数量")
# 双峰分布配置 [近期均值, 近期标准差, 近期权重, 远期均值, 远期标准差, 远期权重]
hippocampus_distribution_config: list[float] = Field(
default=[12.0, 8.0, 0.7, 48.0, 24.0, 0.3],
description="海马体双峰分布配置：[近期均值(h), 近期标准差(h), 近期权重, 远期均值(h), 远期标准差(h), 远期权重]",
)
# 自适应采样配置
adaptive_sampling_enabled: bool = Field(default=True, description="启用自适应采样策略")
adaptive_sampling_threshold: float = Field(default=0.8, description="自适应采样负载阈值（0-1）")
adaptive_sampling_check_interval: int = Field(default=300, description="自适应采样检查间隔（秒）")
adaptive_sampling_max_concurrent_builds: int = Field(default=3, description="自适应采样最大并发记忆构建数")
# 精准记忆配置（现有系统的增强版本）
precision_memory_reply_threshold: float = Field(
default=0.6, description="精准记忆回复触发阈值（对话价值评分超过此值时触发记忆构建）"
)
precision_memory_max_builds_per_hour: int = Field(default=10, description="精准记忆每小时最大构建数量")
# 混合系统优化配置
memory_system_load_balancing: bool = Field(default=True, description="启用记忆系统负载均衡")
memory_build_throttling: bool = Field(default=True, description="启用记忆构建节流")
memory_priority_queue_enabled: bool = Field(default=True, description="启用记忆优先级队列")
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}': {e!s}") 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")
split_mode: str = Field(default="llm", description="分割模式: 'llm' 或 'punctuation'")
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_threshold: float = Field(default=0.3, description="QA段落阈值")
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 PlanningSystemConfig(ValidatedConfigBase):
"""规划系统配置 (日程与月度计划)"""
# --- 日程生成 (原 ScheduleConfig) ---
schedule_enable: bool = Field(True, description="是否启用每日日程生成功能")
schedule_guidelines: str = Field("", description="日程生成指导原则")
# --- 月度计划 (原 MonthlyPlanSystemConfig) ---
monthly_plan_enable: bool = Field(True, description="是否启用月度计划系统")
monthly_plan_guidelines: str = Field("", description="月度计划生成指导原则")
max_plans_per_month: int = Field(10, description="每月最多生成的计划数量")
avoid_repetition_days: int = Field(7, description="避免在多少天内重复使用同一个月度计划")
completion_threshold: int = Field(3, description="一个月度计划被使用多少次后算作完成")
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")
searxng_instances: list[str] = Field(default_factory=list, description="SearXNG 实例 URL 列表")
searxng_api_keys: list[str] = Field(default_factory=list, description="SearXNG 实例 API 密钥列表")
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 ContextGroup(ValidatedConfigBase):
"""
上下文共享组配置
定义了一个聊天上下文的共享范围和规则。
"""
name: str = Field(..., description="共享组的名称，用于唯一标识一个共享组")
mode: Literal["whitelist", "blacklist"] = Field(
default="whitelist",
description="共享模式。'whitelist'表示仅共享chat_ids中列出的聊天；'blacklist'表示共享除chat_ids中列出的所有聊天。",
)
default_limit: int = Field(
default=5,
description="在'blacklist'模式下，对于未明确指定数量的聊天，默认获取的消息条数。",
)
chat_ids: list[list[str]] = Field(
...,
description='定义组内成员的列表。格式为 [["type", "id", "limit"(可选)]]。type为"group"或"private"，id为群号或用户ID，limit为可选的消息条数。',
)
class MaizoneContextGroup(ValidatedConfigBase):
"""QQ空间专用互通组配置"""
name: str = Field(..., description="QQ空间互通组的名称")
chat_ids: list[list[str]] = Field(
...,
description='定义组内成员的列表。格式为 [["type", "id"]]。type为"group"或"private"，id为群号或用户ID。',
)
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")
# --- Normal模式: 共享组配置 ---
groups: list[ContextGroup] = Field(default_factory=list, description="上下文共享组列表")
# --- S4U模式: 用户中心上下文检索 ---
s4u_mode: Literal["whitelist", "blacklist"] = Field(
default="whitelist",
description="S4U模式的白名单/黑名单模式",
)
s4u_limit: int = Field(default=5, description="S4U模式下，每个聊天获取的消息条数")
s4u_stream_limit: int = Field(default=3, description="S4U模式下，最多检索多少个不同的聊天流")
s4u_whitelist_chats: list[str] = Field(
default_factory=list,
description='S4U模式的白名单列表。格式: ["platform:type:id", ...]',
)
s4u_blacklist_chats: list[str] = Field(
default_factory=list,
description='S4U模式的黑名单列表。格式: ["platform:type:id", ...]',
)
# --- QQ空间专用互通组 ---
maizone_context_group: list[MaizoneContextGroup] = Field(default_factory=list, description="QQ空间专用互通组列表")
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], ...]"
)
class AffinityFlowConfig(ValidatedConfigBase):
"""亲和流配置类（兴趣度评分和人物关系系统）"""
# 兴趣评分系统参数
reply_action_interest_threshold: float = Field(default=0.4, description="回复动作兴趣阈值")
non_reply_action_interest_threshold: float = Field(default=0.2, description="非回复动作兴趣阈值")
high_match_interest_threshold: float = Field(default=0.8, description="高匹配兴趣阈值")
medium_match_interest_threshold: float = Field(default=0.5, description="中匹配兴趣阈值")
low_match_interest_threshold: float = Field(default=0.2, description="低匹配兴趣阈值")
high_match_keyword_multiplier: float = Field(default=1.5, description="高匹配关键词兴趣倍率")
medium_match_keyword_multiplier: float = Field(default=1.2, description="中匹配关键词兴趣倍率")
low_match_keyword_multiplier: float = Field(default=1.0, description="低匹配关键词兴趣倍率")
match_count_bonus: float = Field(default=0.1, description="匹配数关键词加成值")
max_match_bonus: float = Field(default=0.5, description="最大匹配数加成值")
# 回复决策系统参数
no_reply_threshold_adjustment: float = Field(default=0.1, description="不回复兴趣阈值调整值")
reply_cooldown_reduction: int = Field(default=2, description="回复后减少的不回复计数")
max_no_reply_count: int = Field(default=5, description="最大不回复计数次数")
# 综合评分权重
keyword_match_weight: float = Field(default=0.4, description="兴趣关键词匹配度权重")
mention_bot_weight: float = Field(default=0.3, description="提及bot分数权重")
relationship_weight: float = Field(default=0.3, description="人物关系分数权重")
# 提及bot相关参数
mention_bot_adjustment_threshold: float = Field(default=0.3, description="提及bot后的调整阈值")
mention_bot_interest_score: float = Field(default=0.6, description="提及bot的兴趣分")
base_relationship_score: float = Field(default=0.5, description="基础人物关系分")
# 关系追踪系统参数
enable_relationship_tracking: bool = Field(default=True, description="是否启用关系追踪系统")
relationship_tracking_probability: float = Field(default=0.7, description="关系追踪执行概率 (0.0-1.0)，用于减少API调用压力")
relationship_tracking_interval_min: int = Field(default=300, description="关系追踪最小间隔时间（秒）")
relationship_tracking_cooldown_hours: float = Field(default=1.0, description="同一用户关系追踪冷却时间（小时）")
class ProactiveThinkingConfig(ValidatedConfigBase):
"""主动思考（主动发起对话）功能配置"""
# --- 总开关 ---
enable: bool = Field(default=False, description="是否启用主动发起对话功能")
# --- 触发时机 ---
interval: int = Field(default=1500, description="基础触发间隔（秒），AI会围绕这个时间点主动发起对话")
interval_sigma: int = Field(
default=120, description="间隔随机化标准差（秒），让触发时间更自然。设为0则为固定间隔。"
)
talk_frequency_adjust: list[list[str]] = Field(
default_factory=lambda: [["", "8:00,1", "12:00,1.2", "18:00,1.5", "01:00,0.6"]],
description='每日活跃度调整，格式：[["", "HH:MM,factor", ...], ["stream_id", ...]]',
)
# --- 作用范围 ---
enable_in_private: bool = Field(default=True, description="是否允许在私聊中主动发起对话")
enable_in_group: bool = Field(default=True, description="是否允许在群聊中主动发起对话")
enabled_private_chats: list[str] = Field(
default_factory=list, description='私聊白名单，为空则对所有私聊生效。格式: ["platform:user_id", ...]'
)
enabled_group_chats: list[str] = Field(
default_factory=list, description='群聊白名单，为空则对所有群聊生效。格式: ["platform:group_id", ...]'
)
# --- 冷启动配置 (针对私聊) ---
enable_cold_start: bool = Field(default=True, description="对于白名单中不活跃的私聊，是否允许进行一次“冷启动”问候")
cold_start_cooldown: int = Field(
default=86400, description="冷启动后，该私聊的下一次主动思考需要等待的最小时间（秒）"
)
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