完成请求推送，但组装mes还有问题
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@@ -141,7 +141,14 @@ class CharacterCard(BaseModel):
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outputSchema: Optional[List[OutputSchemaField]] = Field(None, description="输出 schema 定义 (结构化输出)")
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avatarPath: Optional[str] = Field(None, description="角色头像路径")
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alternate_greetings: Optional[List[str]] = Field(None, description="替代问候语数组")
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tags: Optional[List[str]] = Field(None, description="标签数组")
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# TODO: 拓展提示词设置（插件/拓展系统预留接口）
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# - tableMaintenancePrompt: 用于指导 AI 维护动态表格（RPG状态、任务追踪等）
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# - imageGenerationPrompt: 用于指导 AI 生成图片描述提示词
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# 当前状态：字段已定义，默认值为 None，等待插件系统实现
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tableMaintenancePrompt: Optional[str] = Field(None, description="动态表格维护提示词 - 指导 AI 如何更新表格数据")
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imageGenerationPrompt: Optional[str] = Field(None, description="生图提示词模板 - 指导 AI 如何生成图片描述")
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createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
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updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
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lastChatAt: Optional[int] = Field(None, description="最后聊天时间戳")
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@@ -300,3 +307,84 @@ class ChatRAGConfig(BaseModel):
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indexConfig: Optional[Dict[str, Any]] = Field(None, description="索引配置")
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createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
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updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
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# ==================== Token 统计 ====================
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class TokenUsageStatus(str, Enum):
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"""Token 使用状态"""
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COMPLETED = 'completed' # 成功完成
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INTERRUPTED = 'interrupted' # 被用户中断
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FAILED = 'failed' # 请求失败（API错误等）
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class TokenUsageRecord(BaseModel):
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"""
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Token 使用记录
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记录每次 LLM 调用的 token 使用情况，支持按时间、角色、聊天维度统计
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"""
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id: str = Field(..., description="记录唯一标识符 (UUID)")
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chatId: str = Field(..., description="聊天ID (role_name/chat_name)")
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roleName: str = Field(..., description="角色名称")
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chatName: str = Field(..., description="聊天名称")
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messageId: Optional[str] = Field(None, description="关联的消息ID")
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floor: Optional[int] = Field(None, description="楼层号")
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# Token 统计
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promptTokens: int = Field(0, description="输入 token 数")
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completionTokens: int = Field(0, description="输出 token 数")
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totalTokens: int = Field(0, description="总 token 数")
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# 状态信息
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status: TokenUsageStatus = Field(TokenUsageStatus.COMPLETED, description="请求状态")
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errorMessage: Optional[str] = Field(None, description="错误信息（如果失败）")
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# 时间信息
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timestamp: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="请求时间戳")
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duration: Optional[float] = Field(None, description="请求耗时（秒）")
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# API 信息
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model: Optional[str] = Field(None, description="使用的模型")
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apiProvider: Optional[str] = Field(None, description="API 提供商")
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apiUrl: Optional[str] = Field(None, description="API URL地址")
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# ==================== 图片元数据 ====================
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class ImageMetadata(BaseModel):
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"""
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图片元数据
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记录生成的图片信息，绑定到角色/聊天的特定楼层
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"""
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id: str = Field(..., description="图片唯一标识符 (UUID)")
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chatId: str = Field(..., description="聊天ID (role_name/chat_name)")
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roleName: str = Field(..., description="角色名称")
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chatName: str = Field(..., description="聊天名称")
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floor: int = Field(..., description="楼层号")
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# 图片信息
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filename: str = Field(..., description="文件名")
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filepath: str = Field(..., description="文件相对路径")
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width: Optional[int] = Field(None, description="图片宽度")
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height: Optional[int] = Field(None, description="图片高度")
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fileSize: Optional[int] = Field(None, description="文件大小（字节）")
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# Swipe 支持
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swipeIndex: int = Field(0, description="Swipe 索引（同一楼层多张图片）")
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isCurrentSwipe: bool = Field(True, description="是否为当前显示的 swipe")
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# 生成信息
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prompt: Optional[str] = Field(None, description="生成使用的提示词")
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negativePrompt: Optional[str] = Field(None, description="负面提示词")
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seed: Optional[int] = Field(None, description="随机种子")
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model: Optional[str] = Field(None, description="使用的模型/checkpoint")
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workflowName: Optional[str] = Field(None, description="使用的工作流名称")
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# 任务信息
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taskId: Optional[str] = Field(None, description="关联的任务ID")
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generationTime: Optional[float] = Field(None, description="生成耗时（秒）")
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# 时间信息
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createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
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164
backend/models/regex_rules.py
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164
backend/models/regex_rules.py
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@@ -0,0 +1,164 @@
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"""
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正则替换规则模型
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兼容 SillyTavern 的正则系统，支持全局、角色卡、预设三种作用域。
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"""
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from enum import Enum
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from typing import List, Optional, Dict, Any
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from pydantic import BaseModel, Field
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from datetime import datetime
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class RegexPlacement(int, Enum):
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"""
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正则应用位置（对应 SillyTavern 的 placement 数组）
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0: System Prompt - 系统提示词
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1: User Input - 用户输入
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2: AI Output - AI 输出
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3: Quick Reply - 快捷回复
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4: World Info - 世界书信息
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5: Reasoning/Thinking - 推理/思考内容
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"""
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SYSTEM_PROMPT = 0
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USER_INPUT = 1
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AI_OUTPUT = 2
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QUICK_REPLY = 3
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WORLD_INFO = 4
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REASONING = 5
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class RegexScope(str, Enum):
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"""
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正则规则作用域
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- GLOBAL: 全局生效，对所有聊天应用
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- CHARACTER: 绑定到特定角色卡
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- PRESET: 绑定到特定预设
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"""
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GLOBAL = 'global'
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CHARACTER = 'character'
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PRESET = 'preset'
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class SubstituteMode(int, Enum):
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"""
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替换模式
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对应 SillyTavern 的 substituteRegex 字段
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"""
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REPLACE_ALL = 0 # 替换所有匹配
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REPLACE_FIRST = 1 # 仅替换首次匹配
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REPLACE_CAPTURED = 2 # 替换捕获组
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class RegexRule(BaseModel):
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"""
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单条正则替换规则
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完全兼容 SillyTavern 的正则规则格式
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"""
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id: str = Field(..., description="规则唯一标识符 (UUID)")
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scriptName: str = Field(..., description="脚本名称（用于显示）")
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# 核心正则配置
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findRegex: str = Field(..., description="查找正则表达式（如：/<thinking>[\\s\\S]*?<\\/thinking>/gi）")
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replaceString: str = Field("", description="替换字符串（支持捕获组引用 $1, $2 等）")
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trimStrings: List[str] = Field(default_factory=list, description="要额外修剪的字符串数组")
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# 应用位置（关键！对应 SillyTavern 的 placement 数组）
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placement: List[RegexPlacement] = Field(
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default_factory=lambda: [RegexPlacement.AI_OUTPUT],
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description="应用位置数组：0=系统提示词, 1=用户输入, 2=AI输出, 3=快捷回复, 4=世界书, 5=推理内容"
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)
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# 替换模式
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substituteRegex: SubstituteMode = Field(
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SubstituteMode.REPLACE_ALL,
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description="替换模式：0=全部，1=首次，2=捕获组"
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)
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# 作用范围控制
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markdownOnly: bool = Field(False, description="是否仅应用于 Markdown 渲染后的内容")
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promptOnly: bool = Field(False, description="是否仅应用于发送给 LLM 的提示词")
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runOnEdit: bool = Field(True, description="用户编辑消息时是否重新应用")
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# 消息深度控制
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minDepth: int = Field(0, ge=0, description="最小消息深度（从最新消息开始计数）")
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maxDepth: Optional[int] = Field(None, ge=0, description="最大消息深度（None 表示无限制）")
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# 作用域配置
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scope: RegexScope = Field(RegexScope.GLOBAL, description="规则作用域")
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characterName: Optional[str] = Field(None, description="绑定的角色卡名称（scope=CHARACTER 时使用）")
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presetName: Optional[str] = Field(None, description="绑定的预设名称（scope=PRESET 时使用）")
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# 启用状态
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disabled: bool = Field(False, description="是否禁用此规则（与 enabled 相反，为了兼容 ST）")
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# 执行顺序
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order: int = Field(0, description="执行顺序（数值越小越先执行）")
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# 元数据
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createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
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updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
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description: Optional[str] = Field(None, description="规则描述（可选）")
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class RegexRuleset(BaseModel):
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"""
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正则规则集
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一组正则规则的集合，可以整体导入/导出，兼容 SillyTavern 格式
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"""
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id: str = Field(..., description="规则集唯一标识符 (UUID)")
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name: str = Field(..., description="规则集名称")
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description: Optional[str] = Field(None, description="规则集描述")
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rules: List[RegexRule] = Field(default_factory=list, description="规则列表")
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# 元数据
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createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
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updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
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version: int = Field(1, description="版本号（用于数据迁移）")
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# SillyTavern 兼容性标记
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isSillyTavernFormat: bool = Field(False, description="是否为 SillyTavern 导入格式")
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# ==================== 使用示例 ====================
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if __name__ == '__main__':
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import json
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# 创建一条规则
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rule = RegexRule(
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id="example-hide-thinking-001",
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scriptName="隐藏思考标签",
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findRegex=r"<thinking>[\s\S]*?<\/thinking>",
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replaceString="",
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trimStrings=[],
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placement=[RegexPlacement.AI_OUTPUT],
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substituteRegex=SubstituteMode.REPLACE_ALL,
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markdownOnly=False,
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promptOnly=False,
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runOnEdit=True,
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minDepth=0,
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maxDepth=None,
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scope=RegexScope.GLOBAL,
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characterName=None,
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presetName=None,
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disabled=False,
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order=1,
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description="隐藏 AI 回复中的 <thinking> 标签及其内容"
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)
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# 创建规则集
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ruleset = RegexRuleset(
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id="ruleset-001",
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name="默认正则规则集",
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description="包含常用的文本处理规则",
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rules=[rule]
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)
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# 导出为 JSON（兼容 SillyTavern）
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print(json.dumps(ruleset.dict(), indent=2, ensure_ascii=False))
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49
backend/models/system_settings.py
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49
backend/models/system_settings.py
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@@ -0,0 +1,49 @@
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"""
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系统设置模型
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包含全局配置，如思考标签前后缀等。
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"""
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from typing import Optional
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from pydantic import BaseModel, Field
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from datetime import datetime
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class SystemSettings(BaseModel):
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"""
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系统全局设置
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持久化存储到 data/system_settings.json
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"""
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# ==================== 思考标签配置 ====================
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thinkingTagPrefix: str = Field(
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"<thinking>",
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description="思考标签前缀（默认：<thinking>）"
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)
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thinkingTagSuffix: str = Field(
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"</thinking>",
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description="思考标签后缀（默认：</thinking>）"
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)
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# ==================== 当前选中的预设 ====================
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currentPresetName: Optional[str] = Field(
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None,
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description="当前选中的预设名称（用于确定全局正则的作用域）"
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)
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# ==================== 元数据 ====================
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updatedAt: int = Field(
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default_factory=lambda: int(datetime.now().timestamp()),
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description="最后更新时间戳"
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)
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version: int = Field(1, description="版本号")
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# ==================== 默认设置 ====================
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DEFAULT_SYSTEM_SETTINGS = SystemSettings()
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if __name__ == '__main__':
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import json
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print(json.dumps(DEFAULT_SYSTEM_SETTINGS.dict(), indent=2, ensure_ascii=False))
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