4 Commits

Author SHA1 Message Date
f0e7e75ffb 完成大量美化 2026-05-01 15:44:14 +08:00
6b65b24b0f 完成大量美化 2026-05-01 14:44:18 +08:00
1d0f0ae0ef feat: sync latest local code 2026-04-30 01:38:53 +08:00
ba9b925c32 完成世界书、骰子、apiconfig页面处理 2026-04-30 01:35:10 +08:00
4637 changed files with 781617 additions and 60 deletions

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# 全局世界书数据同步问题修复
## 🐛 问题描述
**现象**: 当世界书文件被删除后LocalStorage中仍然保存着该世界书的全局状态导致前端显示一个不存在的"幽灵"世界书。
**原因**: `fetchWorldBooks` 函数从LocalStorage加载全局世界书后没有清理那些已经不存在于后端的世界书。
---
## ✅ 解决方案
### 修复位置
**文件**: `frontend/src/Store/SideBarLeft/WorldBookSlice.jsx`
**函数**: `fetchWorldBooks` (第132-165行)
### 修复逻辑
```javascript
// 从 LocalStorage 获取全局世界书列表
let globalBooks = loadGlobalWorldBooks();
// 清理 LocalStorage 中已不存在的世界书
const existingWorldBookNames = new Set(data.map(wb => wb.name));
const cleanedGlobalBooks = globalBooks.filter(wb => existingWorldBookNames.has(wb.name));
// 如果有被清理的项,更新 LocalStorage
if (cleanedGlobalBooks.length !== globalBooks.length) {
console.log(`清理了 ${globalBooks.length - cleanedGlobalBooks.length} 个不存在的全局世界书`);
saveGlobalWorldBooks(cleanedGlobalBooks);
globalBooks = cleanedGlobalBooks;
}
```
### 工作流程
1. **获取后端数据**: 调用 `GET /api/worldbooks/` 获取所有存在的世界书
2. **加载LocalStorage**: 从LocalStorage读取全局世界书列表
3. **对比清理**: 过滤掉LocalStorage中存在但后端不存在的世界书
4. **更新存储**: 如果发现有被清理的项更新LocalStorage
5. **更新State**: 将清理后的列表设置到State中
---
## 🧪 测试场景
### 场景1: 正常情况
**步骤**:
1. 创建世界书A和B
2. 将A和B都设为全局
3. 刷新页面
**预期结果**:
- ✅ 全局区域显示A和B
- ✅ LocalStorage中有A和B
### 场景2: 文件被删除
**步骤**:
1. 创建世界书A和B
2. 将A和B都设为全局
3. 手动删除世界书A的文件或其他方式删除
4. 刷新页面
**预期结果**:
- ✅ 全局区域只显示B
- ✅ LocalStorage中只保留B
- ✅ 控制台输出: "清理了 1 个不存在的全局世界书"
### 场景3: 通过UI删除
**步骤**:
1. 创建世界书A和B
2. 将A和B都设为全局
3. 在前端UI中删除世界书A
4. 刷新页面
**预期结果**:
- ✅ 全局区域只显示B
- ✅ LocalStorage中只保留B
- ✅ 无错误信息
---
## 📊 数据流图
```
┌─────────────────┐
│ 页面加载/切换 │
└────────┬────────┘
┌─────────────────┐
│ fetchWorldBooks │
└────────┬────────┘
├──► GET /api/worldbooks/ ──► 后端返回现有世界书列表
├──► loadGlobalWorldBooks() ──► 从LocalStorage读取
├──► 对比两个列表
│ ├─ 存在于LocalStorage但不存在于后端 → 清理
│ └─ 存在于两者 → 保留
├──► saveGlobalWorldBooks() ──► 更新LocalStorage如有变化
└──► set state ──► 更新UI
```
---
## 🔍 关键代码说明
### 1. 使用Set提高查找效率
```javascript
const existingWorldBookNames = new Set(data.map(wb => wb.name));
```
- 将后端返回的世界书名称转换为Set
- Set的查找时间复杂度为O(1)比数组的O(n)更高效
### 2. 过滤清理
```javascript
const cleanedGlobalBooks = globalBooks.filter(wb =>
existingWorldBookNames.has(wb.name)
);
```
- 只保留那些在后端也存在的世界书
- 自动移除"幽灵"世界书
### 3. 条件更新
```javascript
if (cleanedGlobalBooks.length !== globalBooks.length) {
console.log(`清理了 ${globalBooks.length - cleanedGlobalBooks.length} 个不存在的全局世界书`);
saveGlobalWorldBooks(cleanedGlobalBooks);
globalBooks = cleanedGlobalBooks;
}
```
- 只有在确实有变化时才更新LocalStorage
- 避免不必要的写入操作
- 提供调试信息
---
## ✨ 优势
1. **自动清理**: 无需手动干预自动同步LocalStorage和后端数据
2. **性能优化**: 使用Set提高查找效率
3. **用户友好**: 静默清理,只在控制台输出日志
4. **数据一致性**: 确保LocalStorage中的数据始终与后端保持一致
5. **无副作用**: 不影响正常的业务流程
---
## 📝 相关代码位置
### LocalStorage操作函数
```javascript
// 辅助函数:从 LocalStorage 加载全局世界书
const loadGlobalWorldBooks = () => {
try {
const stored = localStorage.getItem(GLOBAL_WORLDBOOKS_KEY);
return stored ? JSON.parse(stored) : [];
} catch (error) {
console.error('加载全局世界书失败:', error);
return [];
}
};
// 辅助函数:保存全局世界书到 LocalStorage
const saveGlobalWorldBooks = (globalBooks) => {
try {
localStorage.setItem(GLOBAL_WORLDBOOKS_KEY, JSON.stringify(globalBooks));
} catch (error) {
console.error('保存全局世界书失败:', error);
}
};
```
### 删除世界书时的清理
```javascript
// deleteWorldBook 函数中已经有清理逻辑
deleteWorldBook: async (name) => {
// ...
const filteredGlobalBooks = state.globalWorldBooks.filter(wb => wb.name !== name);
saveGlobalWorldBooks(filteredGlobalBooks);
// ...
}
```
---
## 🎯 总结
**问题已修复**: 全局世界书现在会自动清理不存在的项
**数据同步**: LocalStorage与后端数据保持一致
**用户体验**: 不再显示"幽灵"世界书
**代码健壮**: 增加了数据一致性检查机制

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# LLM Workflow Engine
一个基于 React + TypeScript + FastAPI 的 AI 聊天工作流引擎,支持流式对话、动态表格生成、图片生成等功能。
## 🚀 技术栈
### 前端
- **React 18** - 用户界面框架
- **TypeScript** - 类型安全的 JavaScript
- **Vite** - 现代化的前端构建工具
- **Zustand** - 轻量级状态管理
- **React Markdown** - Markdown 渲染
- **Tailwind CSS** - 实用优先的 CSS 框架
### 后端
- **FastAPI** - 现代化的 Python Web 框架
- **Python 3.11** - 编程语言
- **Uvicorn** - ASGI 服务器
- **WebSockets** - 实时通信
## 📁 项目结构
```
llm_workflow_engine/
├── backend/ # 后端服务
│ ├── api/ # API 路由
│ ├── core/ # 核心模型和配置
│ ├── tools/ # 工具函数
│ ├── workflows/ # 工作流定义
│ ├── Dockerfile # 后端 Docker 配置
│ ├── main.py # 后端入口
│ └── requirements.txt # Python 依赖
├── frontend/ # 前端服务
│ ├── src/
│ │ ├── components/ # React 组件
│ │ ├── Store/ # 状态管理
│ │ ├── services/ # API 服务
│ │ ├── types/ # TypeScript 类型定义
│ │ ├── App.tsx # 主应用组件
│ │ └── main.tsx # 入口文件
│ ├── Dockerfile # 前端 Docker 配置
│ ├── nginx.conf # Nginx 配置(生产环境)
│ ├── package.json # Node.js 依赖
│ └── tsconfig.json # TypeScript 配置
├── data/ # 数据存储
├── docker-compose.yml # Docker Compose 配置
└── README.md # 项目文档
```
## 🛠️ 安装和运行
### 使用 Docker Compose推荐
这是最简单的运行方式,适合开发和生产环境。
1. **克隆项目**
```bash
git clone <repository-url>
cd llm_workflow_engine
```
2. **配置环境变量**
```bash
# 复制环境变量模板
cp .env.example .env
# 根据需要编辑 .env 文件
```
3. **启动服务**
```bash
# 构建并启动所有服务
docker-compose up --build
# 或者在后台运行
docker-compose up -d --build
```
4. **访问应用**
- 前端界面: http://localhost:23338
- 后端 API: http://localhost:23337
- API 文档: http://localhost:23337/docs
5. **停止服务**
```bash
docker-compose down
```
### 本地开发
如果你想分别运行前后端进行开发:
#### 后端开发
1. **安装 Python 依赖**
```bash
cd backend
pip install -r requirements.txt
```
2. **启动后端服务**
```bash
python -m uvicorn backend.main:app --host 0.0.0.0 --port 8000 --reload
```
#### 前端开发
1. **安装 Node.js 依赖**
```bash
cd frontend
npm install
```
2. **启动前端开发服务器**
```bash
npm run dev
```
3. **访问应用**
- 前端界面: http://localhost:5173
- 确保后端在 http://localhost:8000 运行
## 🔧 配置说明
### 环境变量
#### 前端环境变量 (frontend/.env)
```
VITE_API_URL=http://localhost:23337/api
VITE_WS_URL=ws://localhost:23337/api
```
#### 后端环境变量
```
PYTHONUNBUFFERED=1
PYTHONDONTWRITEBYTECODE=1
```
### API 配置
在前端界面中配置你的 API 密钥和端点:
1. 打开左侧栏的 "API 配置" 标签
2. 添加你的 API 配置URL 和密钥)
3. 选择要使用的 API
## 📖 功能特性
-**流式对话** - 实时显示 AI 回复
-**多角色支持** - 支持多个聊天角色和会话
-**消息编辑** - 可以编辑和删除历史消息
-**HTML 渲染** - 支持 Markdown 和 HTML 渲染
-**动态表格** - 自动生成和更新数据表格
-**图片生成** - 集成图片生成工作流
-**世界书** - 管理角色和世界设定
-**预设管理** - 保存和加载不同的对话预设
## 🐳 Docker 命令参考
```bash
# 构建并启动
docker-compose up --build
# 后台运行
docker-compose up -d
# 查看日志
docker-compose logs -f
# 停止服务
docker-compose down
# 重启服务
docker-compose restart
# 进入容器
docker-compose exec backend bash
docker-compose exec frontend sh
# 清理所有容器和卷
docker-compose down -v
```
## 🔍 开发工具
### 前端
```bash
# 类型检查
npm run type-check
# 构建
npm run build
# 预览生产构建
npm run preview
```
### 后端
```bash
# 运行测试(如果有的话)
cd backend
pytest
# 代码格式化
black .
```
## 📝 待办事项
- [ ] 添加单元测试
- [ ] 完善错误处理
- [ ] 添加用户认证
- [ ] 优化性能
- [ ] 添加更多语言支持
- [ ] 完善文档
## 🤝 贡献
欢迎提交 Issue 和 Pull Request
## 📄 许可证
MIT License
## 📞 联系方式
如有问题,请提交 Issue 或联系维护者。

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# 世界书删除确认弹窗移除
## 📋 修改内容
移除了世界书模块中所有的浏览器级别确认弹窗(`confirm`),改为直接执行删除操作。
---
## ✅ 已移除的确认弹窗
### 1. 删除世界书条目
**位置**: `WorldBook.jsx` 第338-349行
**修改前**:
```javascript
const handleDeleteEntry = async () => {
if (!currentEntry || !currentWorldBook) return;
if (confirm('确定要删除此条目吗?')) {
try {
await deleteWorldBookEntry(currentWorldBook.name, currentEntry.uid);
setShowEditPanel(false);
setCurrentEntry(null);
await fetchWorldBookEntries(currentWorldBook.name, currentPage, pageSize);
} catch (err) {
console.error('删除条目失败:', err);
}
}
};
```
**修改后**:
```javascript
const handleDeleteEntry = async () => {
if (!currentEntry || !currentWorldBook) return;
try {
await deleteWorldBookEntry(currentWorldBook.name, currentEntry.uid);
setShowEditPanel(false);
setCurrentEntry(null);
await fetchWorldBookEntries(currentWorldBook.name, currentPage, pageSize);
} catch (err) {
console.error('删除条目失败:', err);
}
};
```
---
### 2. 删除世界书
**位置**: `WorldBook.jsx` 第354-365行
**修改前**:
```javascript
const handleDeleteWorldBook = async () => {
if (!currentWorldBook) return;
if (confirm(`确定要删除世界书 "${currentWorldBook.name}" 吗?`)) {
try {
await deleteWorldBook(currentWorldBook.name);
resetCurrentWorldBook();
} catch (err) {
console.error('删除世界书失败:', err);
}
}
};
```
**修改后**:
```javascript
const handleDeleteWorldBook = async () => {
if (!currentWorldBook) return;
try {
await deleteWorldBook(currentWorldBook.name);
resetCurrentWorldBook();
} catch (err) {
console.error('删除世界书失败:', err);
}
};
```
---
### 3. 编辑面板中的删除按钮
**位置**: `WorldBook.jsx` 第1086-1096行
**修改前**:
```jsx
<button
className="btn btn-danger"
onClick={() => {
if (window.confirm('确定要删除这个条目吗?')) {
handleDeleteEntry();
}
}}
>
删除条目
</button>
```
**修改后**:
```jsx
<button
className="btn btn-danger"
onClick={handleDeleteEntry}
>
删除条目
</button>
```
---
## 🎯 影响范围
### 用户交互变化
**之前**:
1. 点击删除按钮
2. 弹出浏览器确认对话框
3. 用户点击"确定"或"取消"
4. 根据选择执行或删除操作
**现在**:
1. 点击删除按钮
2. 立即执行删除操作
3. 通过错误处理捕获异常
---
## ✨ 优势
1. **更流畅的用户体验**: 减少交互步骤,操作更快捷
2. **更现代的UI**: 避免使用浏览器原生弹窗更符合现代Web应用风格
3. **代码简化**: 减少了条件判断和嵌套层级
4. **一致性**: 与其他删除操作保持一致如果有其他模块也移除了confirm
---
## ⚠️ 注意事项
### 潜在风险
- 用户可能误操作删除重要数据
- 没有二次确认机制
### 建议的替代方案(可选)
如果未来需要添加确认机制,可以考虑:
1. **自定义模态框**: 使用项目统一的Modal组件
2. **Toast提示 + 撤销**: 删除后显示提示,提供短暂的撤销机会
3. **软删除**: 先标记为删除,稍后真正删除
---
## 🧪 测试建议
### 手动测试清单
- [ ] 在世界书列表中选择一个世界书
- [ ] 点击"删除"按钮,检查是否立即删除(无确认弹窗)
- [ ] 在条目编辑面板中点击"删除条目"按钮,检查是否立即删除
- [ ] 检查删除后的控制台是否有错误信息
- [ ] 检查删除后UI是否正确更新
### 边界情况测试
- [ ] 删除不存在的世界书(应该被前端校验拦截)
- [ ] 删除不存在的条目(应该被前端校验拦截)
- [ ] 网络请求失败时的错误处理
---
## 📝 相关代码位置
### 主要文件
- `frontend/src/components/SideBarLeft/tabs/WorldBook/WorldBook.jsx`
### 相关函数
- `handleDeleteEntry()` - 删除条目
- `handleDeleteWorldBook()` - 删除世界书
### Store函数
- `deleteWorldBookEntry()` - WorldBookSlice.jsx
- `deleteWorldBook()` - WorldBookSlice.jsx
---
## 🎯 总结
**所有浏览器级别的确认弹窗已移除**
**删除操作更加流畅和现代化**
**代码结构更简洁**
**用户体验得到提升**
如果需要添加更优雅的确认机制建议使用项目统一的UI组件而非浏览器原生弹窗。

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# 🧪 API 配置功能测试指南
## 📋 测试前准备
### **1. 启动后端服务**
```bash
cd backend
uvicorn main:app --reload --port 8000
```
确保看到:
```
INFO: Application startup complete.
INFO: Uvicorn running on http://127.0.0.1:8000
```
---
### **2. (可选)启动 ComfyUI**
如果要测试 ComfyUI 连接:
```bash
# 本地运行
python comfyui/main.py --listen 0.0.0.0 --port 8188
# 或 Docker
docker-compose up -d comfyui
```
---
## 🚀 运行测试
### **方法 1: 使用 Python 脚本(推荐)**
```bash
# 在项目根目录运行
python test_api_config.py
```
**预期输出**
```
============================================================
ComfyUI API 配置测试
============================================================
============================================================
测试 1: 列出工作流
============================================================
✅ 成功获取 1 个工作流
📄 default_txt2img.json
节点数: 7, 大小: 1234 bytes
...
============================================================
测试总结
============================================================
✅ 通过 - 列出工作流
✅ 通过 - 获取工作流详情
✅ 通过 - 上传工作流
✅ 通过 - 删除工作流
✅ 通过 - 测试 ComfyUI 连接
✅ 通过 - 测试云端 API 连接
总计: 6/6 通过
🎉 所有测试通过!
```
---
### **方法 2: 使用 cURL 手动测试**
#### **测试 1: 列出工作流**
```bash
curl http://localhost:8000/api/api-config/comfyui/workflows | jq
```
**预期响应**
```json
[
{
"filename": "default_txt2img.json",
"name": "default_txt2img",
"nodes_count": 7,
"size": 1234
}
]
```
---
#### **测试 2: 获取工作流详情**
```bash
curl http://localhost:8000/api/api-config/comfyui/workflows/default_txt2img.json | jq
```
**预期响应**
```json
{
"3": {
"inputs": {...},
"class_type": "KSampler",
"_meta": {"title": "K采样器"}
},
...
}
```
---
#### **测试 3: 上传工作流**
创建一个测试文件 `test_workflow.json`
```bash
cat > test_workflow.json << 'EOF'
{
"3": {
"inputs": {
"seed": 42,
"steps": 20,
"cfg": 8,
"sampler_name": "euler",
"scheduler": "normal",
"denoise": 1,
"model": ["4", 0],
"positive": ["6", 0],
"negative": ["7", 0],
"latent_image": ["5", 0]
},
"class_type": "KSampler"
},
"4": {
"inputs": {"ckpt_name": "test.safetensors"},
"class_type": "CheckpointLoaderSimple"
},
"5": {
"inputs": {"width": 512, "height": 512, "batch_size": 1},
"class_type": "EmptyLatentImage"
},
"6": {
"inputs": {"text": "test", "clip": ["4", 1]},
"class_type": "CLIPTextEncode"
},
"7": {
"inputs": {"text": "bad", "clip": ["4", 1]},
"class_type": "CLIPTextEncode"
},
"8": {
"inputs": {"samples": ["3", 0], "vae": ["4", 2]},
"class_type": "VAEDecode"
},
"9": {
"inputs": {"images": ["8", 0], "filename_prefix": "Test"},
"class_type": "SaveImage"
}
}
EOF
```
上传:
```bash
curl -X POST http://localhost:8000/api/api-config/comfyui/workflows/upload \
-F "file=@test_workflow.json" | jq
```
**预期响应**
```json
{
"message": "Workflow uploaded successfully",
"filename": "test_workflow.json",
"size": 1234
}
```
---
#### **测试 4: 删除工作流**
```bash
curl -X DELETE http://localhost:8000/api/api-config/comfyui/workflows/test_workflow.json | jq
```
**预期响应**
```json
{
"message": "Workflow 'test_workflow.json' deleted successfully"
}
```
---
#### **测试 5: 测试 ComfyUI 连接**
```bash
curl -X POST http://localhost:8000/api/api-config/test-comfyui-connection \
-H "Content-Type: application/json" \
-d '{"apiUrl": "http://localhost:8188"}' | jq
```
**如果 ComfyUI 正在运行**
```json
{
"success": true,
"message": "连接成功",
"stats": {
"vram_total": 25769803776,
"vram_free": 24696061952,
"torch_version": "2.1.0+cu121",
"device": "cuda"
}
}
```
**如果 ComfyUI 未运行**
```json
{
"success": false,
"message": "无法连接到 ComfyUI请检查地址和端口"
}
```
---
#### **测试 6: 测试云端 API 连接**
```bash
curl -X POST http://localhost:8000/api/api-config/test-cloud-connection \
-H "Content-Type: application/json" \
-d '{
"provider": "dall-e",
"apiKey": "sk-your-api-key-here",
"model": "dall-e-3"
}' | jq
```
**预期响应**(如果 API Key 有效):
```json
{
"success": true,
"message": "连接成功,模型 dall-e-3 可用"
}
```
---
## ✅ 测试检查清单
### **后端 API**
- [ ] 列出工作流返回正确的列表
- [ ] 获取工作流详情返回完整的 JSON
- [ ] 上传工作流成功保存文件
- [ ] 上传的工作流可以通过列表看到
- [ ] 删除工作流成功移除文件
- [ ] 默认工作流不可删除(返回 403
- [ ] ComfyUI 连接测试正确检测状态
- [ ] 云端 API 连接测试验证 Key
### **前端 UI**
- [ ] 可以切换到"🎨 生图"标签
- [ ] 模式切换卡片正常显示
- [ ] 点击"本地 ComfyUI"显示本地配置
- [ ] 点击"在线 API"显示云端配置
- [ ] 表单输入正常工作
- [ ] 工作流管理器显示默认工作流
- [ ] 可以上传工作流文件
- [ ] 可以删除工作流(非默认)
- [ ] 测试连接按钮正常工作
- [ ] 保存配置功能正常
### **响应式设计**
- [ ] 大屏幕(>768px双列布局
- [ ] 小屏幕(<768px单列布局
- [ ] 无页面级滚动条
- [ ] 侧边栏可独立滚动
- [ ] 无横向滚动
---
## 🐛 常见问题
### **Q1: 测试脚本提示"Connection refused"**
**原因**:后端服务未启动
**解决**
```bash
cd backend
uvicorn main:app --reload --port 8000
```
---
### **Q2: 上传工作流提示"Invalid ComfyUI workflow"**
**原因**JSON 格式不正确或缺少必要节点
**解决**
- 确保包含 `KSampler` 节点
- 使用 ComfyUI 的 "Save (API Format)" 导出
- 检查 JSON 语法是否正确
---
### **Q3: 删除工作流提示"Cannot delete default workflow"**
**这是正常的**!默认工作流受保护,不可删除。
要测试删除功能,请先上传一个自定义工作流,然后删除它。
---
### **Q4: ComfyUI 连接测试失败**
**可能原因**
1. ComfyUI 未启动
2. 地址或端口错误
3. Docker 网络问题
**解决**
```bash
# 检查 ComfyUI 是否运行
curl http://localhost:8188/system_stats
# Docker 环境下
docker ps | grep comfyui
docker logs comfyui
```
---
## 📊 测试结果解读
### **全部通过** ✅
```
总计: 6/6 通过
🎉 所有测试通过!
```
→ API 配置功能完全正常,可以开始使用
### **部分失败** ⚠️
```
总计: 4/6 通过
⚠️ 2 个测试失败,请检查日志
```
→ 查看失败的测试项,根据错误信息排查
### **全部失败** ❌
```
总计: 0/6 通过
```
→ 检查后端服务是否正常运行
→ 检查端口是否正确8000
→ 查看后端日志
---
## 🎯 下一步
测试通过后,你可以:
1. **启动前端**
```bash
cd frontend
npm run dev
```
2. **访问应用**
- 打开浏览器访问 `http://localhost:5173`
- 进入 API 配置页面
- 配置你的生图服务
3. **开始生图**
- 配置完成后
- 在聊天界面输入生图请求
- 等待图片生成
---
## 📝 附录
### **工作流文件格式**
必须是 ComfyUI API 格式的 JSON
```json
{
"node_id": {
"inputs": {...},
"class_type": "NodeType",
"_meta": {"title": "Display Name"}
}
}
```
### **必需的节点类型**
- `KSampler` - 采样器(必需)
- `CheckpointLoaderSimple` - 模型加载器
- `EmptyLatentImage` - 潜变量图像
- `CLIPTextEncode` - 文本编码器(正向和负向)
- `VAEDecode` - VAE 解码器
- `SaveImage` - 保存图像
### **API 端点列表**
| 方法 | 路径 | 说明 |
|------|------|------|
| GET | `/api/api-config/comfyui/workflows` | 列出工作流 |
| POST | `/api/api-config/comfyui/workflows/upload` | 上传工作流 |
| DELETE | `/api/api-config/comfyui/workflows/{filename}` | 删除工作流 |
| GET | `/api/api-config/comfyui/workflows/{filename}` | 获取工作流详情 |
| POST | `/api/api-config/test-comfyui-connection` | 测试 ComfyUI |
| POST | `/api/api-config/test-cloud-connection` | 测试云端 API |
---
**祝测试顺利!** 🎉

217
WORLDBOOK_API_CHECK.md Normal file
View File

@@ -0,0 +1,217 @@
# 世界书分页功能 - 前端API调用检查报告
## ✅ 检查结果
**所有前端世界书分页功能都能正确发出请求到后端API**
---
## 📋 完整API映射表
### 1. 世界书管理
| 功能 | 前端Store函数 | HTTP方法 | API路径 | 后端路由函数 | 状态 |
|------|--------------|----------|---------|-------------|------|
| 获取世界书列表 | `fetchWorldBooks` | GET | `/api/worldbooks/` | `list_worldbooks` | ✅ |
| 获取指定世界书 | `fetchWorldBook` | GET | `/api/worldbooks/{name}` | `get_worldbook` | ✅ |
| 创建世界书 | `createWorldBook` | POST | `/api/worldbooks/` | `create_worldbook` | ✅ |
| 更新世界书 | `updateWorldBook` | PUT | `/api/worldbooks/{name}` | `update_worldbook` | ✅ |
| 删除世界书 | `deleteWorldBook` | DELETE | `/api/worldbooks/{name}` | `delete_worldbook` | ✅ |
### 2. 条目管理(含分页)
| 功能 | 前端Store函数 | HTTP方法 | API路径 | 后端路由函数 | 状态 |
|------|--------------|----------|---------|-------------|------|
| 获取条目列表(分页) | `fetchWorldBookEntries` | GET | `/api/worldbooks/{name}/entries?page={page}&page_size={page_size}` | `list_worldbook_entries` | ✅ |
| 获取指定条目 | `fetchWorldBookEntry` | GET | `/api/worldbooks/{name}/entries/{uid}` | `get_worldbook_entry` | ✅ |
| 创建条目 | `createWorldBookEntry` | POST | `/api/worldbooks/{name}/entries` | `create_worldbook_entry` | ✅ |
| 更新条目 | `updateWorldBookEntry` | PUT | `/api/worldbooks/{name}/entries/{uid}` | `update_worldbook_entry` | ✅ |
| 删除条目 | `deleteWorldBookEntry` | DELETE | `/api/worldbooks/{name}/entries/{uid}` | `delete_worldbook_entry` | ✅ |
### 3. 导入导出
| 功能 | 前端Store函数 | HTTP方法 | API路径 | 后端路由函数 | 状态 |
|------|--------------|----------|---------|-------------|------|
| 导入世界书 | `importWorldBook` | POST | `/api/worldbooks/{name}/import` | `import_worldbook` | ✅ |
| 导出世界书 | `exportWorldBook` | GET | `/api/worldbooks/{name}/export?format={format}` | `export_worldbook` | ✅ |
---
## 🔍 关键功能验证
### ✅ 下拉框读取所有世界书
**位置**: `WorldBook.jsx` 第547行
```jsx
{worldBooks.map(book => (
<div key={book.name} className="dropdown-item">
...
</div>
))}
```
**数据来源**:
- `worldBooks` 来自 Store (第8行)
- 通过 `fetchWorldBooks()` 加载 (第85行和第95行)
**加载时机**:
1. ✅ 组件挂载时立即加载(如果列表为空)
2. ✅ 切换到世界书标签页时重新加载
**API调用**:
```javascript
// WorldBookSlice.jsx 第135行
const response = await fetch(`/api/worldbooks/`);
```
**后端路由**:
```python
# worldbooksRoute.py 第28行
@router.get("/", response_model=List[Dict[str, Any]])
async def list_worldbooks():
```
---
## 🎯 分页功能验证
### 前端实现
**Store函数** (`WorldBookSlice.jsx` 第343-374行):
```javascript
fetchWorldBookEntries: async (name, page = 1, page_size = 20) => {
const response = await fetch(
`/api/worldbooks/${name}/entries?page=${page}&page_size=${page_size}`
);
// 解析响应并更新 state
}
```
**组件调用**:
- 选择世界书时: `fetchWorldBookEntries(book.name, 1, pageSize)` (第141行)
- 切换页码时: `fetchWorldBookEntries(currentWorldBook.name, newPage, pageSize)` (第247行)
- 改变每页数量: `fetchWorldBookEntries(currentWorldBook.name, 1, newPageSize)` (第259行)
**分页状态**:
```javascript
entriesPagination: {
total: data.total || 0,
page: data.page || 1,
page_size: data.page_size || 20,
total_pages: data.total_pages || 0
}
```
### 后端实现
**API路由** (`worldbooksRoute.py` 第108-128行):
```python
@router.get("/{name}/entries", response_model=Dict[str, Any])
async def list_worldbook_entries(
name: str,
page: int = 1,
page_size: int = 20
):
return worldbook_service.list_entries(name, page, page_size)
```
**服务层** (`worldbook_service.py` 第168-198行):
```python
def list_entries(name: str, page: int = 1, page_size: int = 20) -> Dict[str, Any]:
all_entries = data.get("entries", [])
total = len(all_entries)
start_idx = (page - 1) * page_size
end_idx = start_idx + page_size
paginated_entries = all_entries[start_idx:end_idx]
return {
"entries": paginated_entries,
"total": total,
"page": page,
"page_size": page_size,
"total_pages": (total + page_size - 1) // page_size
}
```
---
## 📊 数据格式
### 后端返回格式(分页)
```json
{
"entries": [...],
"total": 30,
"page": 1,
"page_size": 20,
"total_pages": 2
}
```
### 前端State结构
```javascript
{
worldBooks: [], // 世界书列表
currentWorldBook: null, // 当前选中的世界书
currentEntries: [], // 当前页的条目列表
entriesPagination: { // 分页信息
total: 0,
page: 1,
page_size: 20,
total_pages: 0
}
}
```
---
## ✨ 优化记录
### 已完成的优化
1.**组件初始化加载**: 添加 `useEffect` 在组件挂载时立即加载世界书列表
2.**格式统一**: 所有世界书文件转换为内部格式存储
3.**代码简化**: 移除服务层的SillyTavern格式运行时兼容逻辑
4.**分页控件**: 添加完整的分页UI上一页、下一页、每页数量选择
5.**自动刷新**: 添加/更新/删除条目后自动刷新当前页
---
## 🧪 测试建议
### 手动测试清单
- [ ] 打开世界书页面,检查下拉框是否显示所有世界书
- [ ] 选择一个世界书,检查是否正确加载第一页条目
- [ ] 点击"下一页",检查是否加载第二页
- [ ] 改变每页数量10/20/50/100检查是否正确刷新
- [ ] 创建新条目,检查是否刷新当前页
- [ ] 更新条目,检查是否刷新当前页
- [ ] 删除条目,检查是否刷新当前页
- [ ] 切换到其他世界书,检查是否重置到第一页
### API测试
```bash
# 获取世界书列表
curl http://localhost:8000/api/worldbooks/
# 获取条目(分页)
curl "http://localhost:8000/api/worldbooks/卡立创-v5/entries?page=1&page_size=5"
```
---
## 📝 结论
**前端世界书分页的所有功能都能正确发出请求到后端API**
- 下拉框正确读取所有世界书
- 分页参数正确传递
- 数据格式匹配
- 错误处理完善
- 用户体验流畅

View File

@@ -12,7 +12,10 @@ ENV PYTHONDONTWRITEBYTECODE=1
COPY requirements.txt . COPY requirements.txt .
# 安装依赖 # 安装依赖
RUN pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt RUN pip install --no-cache-dir -r requirements.txt
# 安装 Pillow使用阿里云镜像源
RUN pip install --no-cache-dir Pillow -i https://mirrors.aliyun.com/pypi/simple/ --trusted-host mirrors.aliyun.com || echo "Pillow installation failed, will install manually"
# 复制所有代码 # 复制所有代码
COPY . . COPY . .

View File

@@ -1,5 +1,5 @@
from fastapi import APIRouter from fastapi import APIRouter
from .routes import presetsRoute, chatsRoute, worldbooksRoute, apiConfigRoute from .routes import presetsRoute, chatsRoute, worldbooksRoute, apiConfigRoute, charactersRoute
from utils.file_utils import get_all_roles_and_chats from utils.file_utils import get_all_roles_and_chats
from core.config import settings from core.config import settings
from pathlib import Path from pathlib import Path
@@ -11,6 +11,7 @@ router.include_router(presetsRoute.router)
router.include_router(chatsRoute.router) router.include_router(chatsRoute.router)
router.include_router(worldbooksRoute.router) router.include_router(worldbooksRoute.router)
router.include_router(apiConfigRoute.router) router.include_router(apiConfigRoute.router)
router.include_router(charactersRoute.router)
# 保留原有的其他路由 # 保留原有的其他路由

View File

@@ -0,0 +1,389 @@
from fastapi import APIRouter, HTTPException, UploadFile, File
from pydantic import BaseModel, Field
from typing import Dict, Optional, List, Any
import json
import os
from pathlib import Path
from core.config import settings
from cryptography.fernet import Fernet
import base64
from services.comfyui_workflow_manager import workflow_manager
from services.llm_model_service import LLMModelService
router = APIRouter(prefix="/api-config", tags=["API Configuration"])
# 加密密钥(实际项目中应该从环境变量读取)
ENCRYPTION_KEY = os.getenv('API_ENCRYPTION_KEY', Fernet.generate_key().decode())
fernet = Fernet(ENCRYPTION_KEY.encode() if isinstance(ENCRYPTION_KEY, str) else ENCRYPTION_KEY)
# 配置文件路径
CONFIG_DIR = Path(settings.DATA_PATH) / "apiconfig"
CONFIG_DIR.mkdir(parents=True, exist_ok=True)
class ApiConfigItem(BaseModel):
"""单个 API 配置项"""
id: Optional[str] = None
name: Optional[str] = ""
category: Optional[str] = None # mainLLM, imageModel, secondaryLLM, ragEmbedding
apiUrl: Optional[str] = ""
apiKey: Optional[str] = None # 前端传入的可能是明文或空
model: Optional[str] = ""
# 生图模型的特殊字段
mode: Optional[str] = None # 'local' | 'cloud'
local: Optional[dict] = None
cloud: Optional[dict] = None
class ProfileSaveRequest(BaseModel):
"""保存配置文件的请求"""
profileId: str
name: Optional[str] = None
apis: Dict[str, ApiConfigItem] # key 是 categoryvalue 是配置
class ProfileResponse(BaseModel):
"""配置文件响应(不包含明文 API Key"""
id: str
name: str
apis: Dict[str, dict] # apiKey 字段会被移除或脱敏
def encrypt_api_key(api_key: str) -> str:
"""加密 API Key"""
if not api_key:
return ""
encrypted = fernet.encrypt(api_key.encode())
return base64.urlsafe_b64encode(encrypted).decode()
def decrypt_api_key(encrypted_key: str) -> str:
"""解密 API Key仅在后端内部使用"""
if not encrypted_key:
return ""
try:
decoded = base64.urlsafe_b64decode(encrypted_key.encode())
decrypted = fernet.decrypt(decoded)
return decrypted.decode()
except Exception:
return ""
def mask_api_key(api_key: str) -> str:
"""脱敏 API Key返回给前端"""
if not api_key or len(api_key) < 8:
return "****"
return api_key[:4] + "****" + api_key[-4:]
def load_profile(profile_id: str) -> Optional[dict]:
"""加载配置文件"""
config_file = CONFIG_DIR / f"{profile_id}.json"
if not config_file.exists():
return None
with open(config_file, 'r', encoding='utf-8') as f:
return json.load(f)
def save_profile(profile_id: str, profile_data: dict):
"""保存配置文件"""
config_file = CONFIG_DIR / f"{profile_id}.json"
with open(config_file, 'w', encoding='utf-8') as f:
json.dump(profile_data, f, ensure_ascii=False, indent=2)
def list_profiles() -> List[dict]:
"""列出所有配置文件"""
profiles = []
for config_file in CONFIG_DIR.glob("*.json"):
try:
with open(config_file, 'r', encoding='utf-8') as f:
profile = json.load(f)
profiles.append({
"id": profile.get("id", config_file.stem),
"name": profile.get("name", config_file.stem),
"createdAt": profile.get("createdAt", "")
})
except Exception:
continue
return profiles
@router.get("/profiles", response_model=List[dict])
def get_all_profiles():
"""获取所有配置文件列表"""
return list_profiles()
@router.get("/profiles/{profile_id}", response_model=ProfileResponse)
def get_profile(profile_id: str):
"""获取单个配置文件API Key 已脱敏)"""
profile = load_profile(profile_id)
if not profile:
raise HTTPException(status_code=404, detail="配置文件不存在")
# 脱敏所有 API Key
masked_apis = {}
for category, api_config in profile.get("apis", {}).items():
masked_config = api_config.copy()
if "apiKey" in masked_config and masked_config["apiKey"]:
masked_config["apiKey"] = mask_api_key(masked_config["apiKey"])
masked_apis[category] = masked_config
return {
"id": profile.get("id", profile_id),
"name": profile.get("name", profile_id),
"apis": masked_apis
}
@router.post("/profiles", response_model=ProfileResponse)
def create_or_update_profile(request: ProfileSaveRequest):
"""创建或更新配置文件(增量更新)"""
# 加载现有配置
existing_profile = load_profile(request.profileId)
if existing_profile:
# 更新现有配置:只更新提供的 API 配置
for category, api_config in request.apis.items():
api_config_dict = api_config.dict(exclude_none=True)
# 处理 API Key 加密
if api_config.apiKey and api_config.apiKey != "****":
# 如果是新的明文 key加密它
api_config_dict["apiKey"] = encrypt_api_key(api_config.apiKey)
elif api_config.apiKey == "****":
# 如果是脱敏的 key保留原有的加密 key
if category in existing_profile.get("apis", {}):
api_config_dict["apiKey"] = existing_profile["apis"][category].get("apiKey", "")
else:
api_config_dict.pop("apiKey", None)
# 更新配置
if "apis" not in existing_profile:
existing_profile["apis"] = {}
existing_profile["apis"][category] = api_config_dict
profile_data = existing_profile
else:
# 新建配置文件
from datetime import datetime
profile_data = {
"id": request.profileId,
"name": request.name or request.profileId,
"createdAt": datetime.now().isoformat(),
"apis": {}
}
# 添加所有 API 配置
for category, api_config in request.apis.items():
api_config_dict = api_config.dict(exclude_none=True)
if api_config_dict.get("apiKey"):
api_config_dict["apiKey"] = encrypt_api_key(api_config_dict["apiKey"])
profile_data["apis"][category] = api_config_dict
# 保存配置文件
save_profile(request.profileId, profile_data)
# 返回脱敏后的数据
masked_apis = {}
for category, api_config in profile_data.get("apis", {}).items():
masked_config = api_config.copy()
if "apiKey" in masked_config and masked_config["apiKey"]:
masked_config["apiKey"] = mask_api_key(masked_config["apiKey"])
masked_apis[category] = masked_config
return {
"id": profile_data.get("id", request.profileId),
"name": profile_data.get("name", request.profileId),
"apis": masked_apis
}
@router.delete("/profiles/{profile_id}")
def delete_profile(profile_id: str):
"""删除配置文件"""
config_file = CONFIG_DIR / f"{profile_id}.json"
if not config_file.exists():
raise HTTPException(status_code=404, detail="配置文件不存在")
config_file.unlink()
return {"message": "配置文件已删除"}
@router.post("/test-connection")
def test_connection(api_config: ApiConfigItem):
"""测试 API 连接并获取模型列表"""
try:
# 检测提供商类型
provider = LLMModelService.detect_provider(api_config.apiUrl)
# 获取模型列表
models = LLMModelService.get_models_by_provider(
provider=provider,
api_key=api_config.apiKey or "",
api_url=api_config.apiUrl
)
return {
"success": True,
"models": models,
"provider": provider,
"message": f"成功获取 {len(models)} 个模型"
}
except Exception as e:
raise HTTPException(
status_code=500,
detail=f"获取模型列表失败: {str(e)}"
)
# ==================== ComfyUI Workflow Management ====================
@router.get("/comfyui/workflows", response_model=List[Dict[str, Any]])
def get_comfyui_workflows():
"""获取所有可用的 ComfyUI 工作流列表"""
return workflow_manager.list_workflows()
@router.post("/comfyui/workflows/upload")
async def upload_comfyui_workflow(file: UploadFile = File(...)):
"""上传 ComfyUI 工作流 JSON 文件"""
return await workflow_manager.upload_workflow(file)
@router.delete("/comfyui/workflows/{filename}")
def delete_comfyui_workflow(filename: str):
"""删除 ComfyUI 工作流文件"""
return workflow_manager.delete_workflow(filename)
@router.get("/comfyui/workflows/{filename}")
def get_comfyui_workflow(filename: str):
"""获取指定工作流的详细内容"""
return workflow_manager.load_workflow(filename)
# ==================== Connection Testing ====================
@router.post("/test-comfyui-connection")
def test_comfyui_connection(request: dict):
"""测试 ComfyUI 连接"""
import requests as req
api_url = request.get("apiUrl", "http://comfyui:8188")
try:
# 测试基本连通性
response = req.get(f"{api_url}/system_stats", timeout=5)
if response.status_code != 200:
return {
"success": False,
"message": f"HTTP {response.status_code}"
}
stats = response.json()
return {
"success": True,
"message": "连接成功",
"stats": {
"vram_total": stats.get("vram_total", 0),
"vram_free": stats.get("vram_free", 0),
"torch_version": stats.get("torch_version", ""),
"device": stats.get("device", "")
}
}
except req.exceptions.ConnectionError:
return {
"success": False,
"message": "无法连接到 ComfyUI请检查地址和端口"
}
except req.exceptions.Timeout:
return {
"success": False,
"message": "连接超时,请检查 ComfyUI 是否正常运行"
}
except Exception as e:
return {
"success": False,
"message": f"错误: {str(e)}"
}
@router.post("/test-cloud-connection")
def test_cloud_connection(request: dict):
"""测试云端 API 连接"""
import openai
provider = request.get("provider", "dall-e")
api_key = request.get("apiKey", "")
model = request.get("model", "dall-e-3")
if not api_key:
return {
"success": False,
"message": "API Key 不能为空"
}
try:
if provider == "dall-e":
# 测试 DALL-E
client = openai.OpenAI(api_key=api_key)
# 尝试获取模型列表(轻量级测试)
models = client.models.list()
# 检查指定的模型是否存在
model_exists = any(m.id == model for m in models.data)
if model_exists:
return {
"success": True,
"message": f"连接成功,模型 {model} 可用"
}
else:
return {
"success": False,
"message": f"模型 {model} 不可用"
}
elif provider == "stability":
# 测试 Stability AI
import requests as req
response = req.get(
"https://api.stability.ai/v1/engines/list",
headers={
"Authorization": f"Bearer {api_key}"
},
timeout=5
)
if response.status_code == 200:
return {
"success": True,
"message": "连接成功"
}
else:
return {
"success": False,
"message": f"HTTP {response.status_code}: {response.text}"
}
else:
return {
"success": False,
"message": f"不支持的提供商: {provider}"
}
except Exception as e:
return {
"success": False,
"message": f"连接失败: {str(e)}"
}

View File

@@ -0,0 +1,292 @@
"""
角色卡 API 路由
"""
from fastapi import APIRouter, HTTPException, UploadFile, File
from fastapi.responses import FileResponse, StreamingResponse
from typing import List
from pathlib import Path
import io
try:
from backend.services.character_service import CharacterService
except ImportError:
from services.character_service import CharacterService
router = APIRouter(prefix="/characters", tags=["characters"])
character_service = CharacterService()
@router.get("/", response_model=List[dict])
async def list_characters():
"""
获取所有角色卡列表
Returns:
按最后聊天时间排序的角色卡列表
"""
characters = character_service.scan_all_characters()
return [c.dict() for c in characters]
@router.get("/{name}", response_model=dict)
async def get_character(name: str):
"""
获取指定角色卡
Args:
name: 角色名URL编码
"""
character = character_service.get_character_by_name(name)
if not character:
raise HTTPException(status_code=404, detail=f"角色 '{name}' 不存在")
return character.dict()
@router.post("/", response_model=dict)
async def create_character(character_data: dict):
"""
创建新角色卡
Request Body:
{
"name": "角色名",
"description": "描述",
"personality": "性格",
"scenario": "场景",
"first_mes": "开场白",
"categories": ["分类1", "分类2"],
"tags": ["tag1", "tag2"]
}
"""
try:
character = character_service.create_character(character_data)
return {
"success": True,
"character": character.dict()
}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@router.put("/{name}", response_model=dict)
async def update_character(name: str, updates: dict):
"""
更新角色卡
Args:
name: 角色名
updates: 要更新的字段
"""
try:
character = character_service.update_character(name, updates)
return {
"success": True,
"character": character.dict()
}
except FileNotFoundError:
raise HTTPException(status_code=404, detail=f"角色 '{name}' 不存在")
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@router.delete("/{name}")
async def delete_character(name: str):
"""
删除角色卡及其所有聊天记录
"""
success = character_service.delete_character(name)
if not success:
raise HTTPException(status_code=404, detail=f"角色 '{name}' 不存在")
return {"success": True, "message": f"角色 '{name}' 已删除"}
@router.get("/{name}/avatar")
async def get_avatar(name: str):
"""
获取角色头像
Returns:
PNG 图片文件或 404
"""
char_folder = character_service.characters_dir / name
avatar_file = char_folder / "avatar.png"
if not avatar_file.exists():
# 返回默认头像
default_avatar = Path("data/images/avatars/fallback.png")
if default_avatar.exists():
return FileResponse(default_avatar, media_type="image/png")
raise HTTPException(status_code=404, detail="头像不存在")
return FileResponse(avatar_file, media_type="image/png")
@router.post("/{name}/avatar")
async def upload_avatar(name: str, file: UploadFile = File(...)):
"""
上传角色头像
Args:
name: 角色名
file: PNG 图片文件
"""
# 验证文件类型
if not file.content_type.startswith('image/'):
raise HTTPException(status_code=400, detail="只支持图片文件")
# 检查角色是否存在
character = character_service.get_character_by_name(name)
if not character:
raise HTTPException(status_code=404, detail=f"角色 '{name}' 不存在")
# 保存图片
image_data = await file.read()
avatar_path = character_service.save_avatar(name, image_data)
return {
"success": True,
"avatar_path": avatar_path
}
@router.get("/{name}/chats")
async def list_chats(name: str):
"""
获取角色的所有聊天列表
Returns:
聊天文件列表(包含最后一条消息预览)
"""
char_folder = character_service.characters_dir / name
chats_dir = char_folder / "chats"
if not chats_dir.exists():
return {"chats": []}
import json
from datetime import datetime
chats = []
for chat_file in chats_dir.glob("*.jsonl"):
try:
with open(chat_file, 'r', encoding='utf-8') as f:
lines = f.readlines()
if not lines:
continue
# 第一行是header
header = json.loads(lines[0])
# 计算消息数量排除header
message_count = len(lines) - 1
# 获取最后修改时间
last_modified = datetime.fromtimestamp(
chat_file.stat().st_mtime
).isoformat()
# 获取最后一条消息预览
last_message = ""
if message_count > 0:
try:
last_msg_data = json.loads(lines[-1])
last_message = last_msg_data.get("mes", "")
except:
pass
chats.append({
"chat_name": chat_file.stem,
"user_name": header.get("user_name", "User"),
"character_name": header.get("character_name", ""),
"last_modified": last_modified,
"message_count": message_count,
"last_message": last_message
})
except Exception as e:
# 如果解析失败,使用基本信息
chats.append({
"chat_name": chat_file.stem,
"last_modified": datetime.fromtimestamp(chat_file.stat().st_mtime).isoformat(),
"message_count": 0,
"last_message": ""
})
# 按修改时间排序
chats.sort(key=lambda c: c.get('last_modified', ''), reverse=True)
return {"chats": chats}
@router.post("/import")
async def import_character(file: UploadFile = File(...)):
"""
导入角色卡(支持 PNG 或 JSON
- PNG: 自动提取嵌入数据,创建文件夹
- JSON: 创建文件夹并保存
"""
content = await file.read()
filename = file.filename
if filename.endswith('.png'):
# 导入 PNG
try:
character = character_service.import_from_png(content, filename)
return {
"success": True,
"character": character.dict(),
"format": "png_embedded"
}
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
raise HTTPException(status_code=500, detail=f"导入失败: {str(e)}")
elif filename.endswith('.json'):
# 导入 JSON
try:
import json
data = json.loads(content.decode('utf-8'))
character = character_service.create_character(data)
return {
"success": True,
"character": character.dict(),
"format": "json"
}
except Exception as e:
raise HTTPException(status_code=500, detail=f"导入失败: {str(e)}")
else:
raise HTTPException(status_code=400, detail="不支持的文件格式")
@router.post("/{name}/export/png")
async def export_character_as_png(name: str):
"""
导出角色为 SillyTavern PNG 格式
Returns:
PNG 文件下载
"""
try:
png_data = character_service.export_as_png(name)
return StreamingResponse(
io.BytesIO(png_data),
media_type="image/png",
headers={
"Content-Disposition": f"attachment; filename={name}.png"
}
)
except FileNotFoundError:
raise HTTPException(status_code=404, detail=f"角色 '{name}' 不存在")
except Exception as e:
raise HTTPException(status_code=500, detail=f"导出失败: {str(e)}")

View File

@@ -1,56 +1,112 @@
from fastapi import APIRouter, HTTPException, status from fastapi import APIRouter, HTTPException, status
# TODO: 实现 ChatService 来替代旧的 ChatHistory 逻辑 from pathlib import Path
# from services.chat_service import ChatService try:
from backend.services.chat_service import ChatService
from backend.core.config import settings
except ImportError:
# Docker环境直接从当前目录导入
from services.chat_service import ChatService
from core.config import settings
router = APIRouter(prefix="/chat", tags=["chat"]) router = APIRouter(prefix="/chat", tags=["chat"])
# 初始化聊天服务
data_path = Path(settings.DATA_PATH) if hasattr(settings, 'DATA_PATH') else Path("data")
chat_service = ChatService(data_path)
@router.get("", response_model=dict) @router.get("", response_model=dict)
async def list_all_chats(): async def list_all_chats():
"""获取所有角色的所有聊天列表""" """获取所有角色的所有聊天列表"""
# return await ChatService.list_all_chats() return chat_service.list_all_chats()
return {"chats": []}
@router.get("/{role_name}")
async def list_role_chats(role_name: str):
"""获取指定角色的所有聊天列表"""
try:
all_chats = chat_service.list_all_chats()
# 从所有聊天中筛选出该角色的聊天
role_chats = all_chats.get(role_name, [])
return role_chats
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@router.get("/{role_name}/{chat_name}") @router.get("/{role_name}/{chat_name}")
async def get_chat(role_name: str, chat_name: str): async def get_chat(role_name: str, chat_name: str):
"""获取指定聊天的完整内容""" """获取指定聊天的完整内容"""
raise HTTPException(status_code=501, detail="Not Implemented") try:
return chat_service.get_chat(role_name, chat_name)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
@router.post("/{role_name}", status_code=status.HTTP_201_CREATED) @router.post("/{role_name}", status_code=status.HTTP_201_CREATED)
async def create_chat(role_name: str, chat_name: str, metadata: dict = None): async def create_chat(role_name: str, chat_data: dict):
"""创建新聊天""" """创建新聊天"""
raise HTTPException(status_code=501, detail="Not Implemented") try:
chat_name = chat_data.get("chat_name", "新聊天")
metadata = chat_data.get("metadata", {})
return chat_service.create_chat(role_name, chat_name, metadata)
except FileExistsError as e:
raise HTTPException(status_code=400, detail=str(e))
@router.put("/{role_name}/{chat_name}") @router.put("/{role_name}/{chat_name}")
async def update_chat(role_name: str, chat_name: str, update_data: dict): async def update_chat(role_name: str, chat_name: str, update_data: dict):
"""更新聊天元数据""" """更新聊天元数据"""
# TODO: 实现更新聊天元数据功能
raise HTTPException(status_code=501, detail="Not Implemented") raise HTTPException(status_code=501, detail="Not Implemented")
@router.delete("/{role_name}/{chat_name}") @router.delete("/{role_name}/{chat_name}")
async def delete_chat(role_name: str, chat_name: str): async def delete_chat(role_name: str, chat_name: str):
"""删除指定聊天""" """删除指定聊天"""
# TODO: 实现删除聊天功能
raise HTTPException(status_code=501, detail="Not Implemented") raise HTTPException(status_code=501, detail="Not Implemented")
@router.get("/{role_name}/{chat_name}/messages") @router.get("/{role_name}/{chat_name}/messages")
async def list_messages(role_name: str, chat_name: str): async def list_messages(role_name: str, chat_name: str):
"""获取聊天的所有消息""" """获取聊天的所有消息"""
raise HTTPException(status_code=501, detail="Not Implemented") try:
chat_data = chat_service.get_chat(role_name, chat_name)
return {"messages": chat_data["messages"]}
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
@router.get("/{role_name}/{chat_name}/messages/{floor}") @router.get("/{role_name}/{chat_name}/messages/{floor}")
async def get_message(role_name: str, chat_name: str, floor: int): async def get_message(role_name: str, chat_name: str, floor: int):
"""获取指定楼层的消息""" """获取指定楼层的消息"""
raise HTTPException(status_code=501, detail="Not Implemented") try:
chat_data = chat_service.get_chat(role_name, chat_name)
for msg in chat_data["messages"]:
if msg.get("floor") == floor:
return msg
raise HTTPException(status_code=404, detail=f"Message at floor {floor} not found")
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
@router.post("/{role_name}/{chat_name}/messages", status_code=status.HTTP_201_CREATED) @router.post("/{role_name}/{chat_name}/messages", status_code=status.HTTP_201_CREATED)
async def add_message(role_name: str, chat_name: str, message_data: dict): async def add_message(role_name: str, chat_name: str, message_data: dict):
"""向聊天添加新消息""" """向聊天添加新消息"""
raise HTTPException(status_code=501, detail="Not Implemented") try:
return chat_service.add_message(role_name, chat_name, message_data)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
@router.put("/{role_name}/{chat_name}/messages/{floor}") @router.put("/{role_name}/{chat_name}/messages/{floor}")
async def update_message(role_name: str, chat_name: str, floor: int, update_data: dict): async def update_message(role_name: str, chat_name: str, floor: int, update_data: dict):
"""更新指定楼层的消息""" """更新指定楼层的消息"""
raise HTTPException(status_code=501, detail="Not Implemented") try:
return chat_service.update_message(role_name, chat_name, floor, update_data)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
raise HTTPException(status_code=404, detail=str(e))
@router.delete("/{role_name}/{chat_name}/messages/{floor}") @router.delete("/{role_name}/{chat_name}/messages/{floor}")
async def delete_message(role_name: str, chat_name: str, floor: int): async def delete_message(role_name: str, chat_name: str, floor: int):
"""删除指定楼层的消息""" """删除指定楼层的消息"""
raise HTTPException(status_code=501, detail="Not Implemented") try:
return chat_service.delete_message(role_name, chat_name, floor)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
raise HTTPException(status_code=404, detail=str(e))

View File

@@ -1,5 +1,6 @@
3# 标准库导入 # 标准库导入
import os import os
import json
import shutil import shutil
import logging import logging
from pathlib import Path from pathlib import Path
@@ -12,6 +13,7 @@ from fastapi.responses import JSONResponse, FileResponse
# 本地模块导入 # 本地模块导入
from models.internal import WorldInfo, WorldInfoEntry from models.internal import WorldInfo, WorldInfoEntry
from core.config import settings from core.config import settings
from services.worldbook_service import worldbook_service
# 配置日志 # 配置日志
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@@ -30,88 +32,222 @@ async def list_worldbooks():
Returns: Returns:
List[Dict[str, Any]]: 世界书列表 List[Dict[str, Any]]: 世界书列表
""" """
# TODO: 实现 WorldBookService try:
return [] return worldbook_service.list_worldbooks()
except Exception as e:
logger.error(f"Failed to list worldbooks: {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.get("/{name}", response_model=Dict[str, Any]) @router.get("/{name}", response_model=Dict[str, Any])
async def get_worldbook(name: str): async def get_worldbook(name: str):
""" """
获取指定名称的世界书 获取指定名称的世界书
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
return worldbook_service.get_worldbook(name)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to get worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.post("/", response_model=Dict[str, Any]) @router.post("/", response_model=Dict[str, Any])
async def create_worldbook( async def create_worldbook(
name: str = Form(...), name: str = Form(...),
description: str = Form(""),
file: Optional[UploadFile] = File(None) file: Optional[UploadFile] = File(None)
): ):
""" """
创建新世界书 创建新世界书(可选择导入文件)
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
# 如果提供了文件,从 SillyTavern 格式导入
if file:
content = await file.read()
st_data = json.loads(content.decode('utf-8'))
return worldbook_service.import_from_sillytavern(name, st_data)
else:
# 创建空世界书
return worldbook_service.create_worldbook(name, description)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error(f"Failed to create worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.put("/{name}", response_model=Dict[str, Any]) @router.put("/{name}", response_model=Dict[str, Any])
async def update_worldbook( async def update_worldbook(
name: str, name: str,
file: Optional[UploadFile] = File(None) description: Optional[str] = Form(None)
): ):
""" """
更新世界书 更新世界书基本信息
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
return worldbook_service.update_worldbook(name, description)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to update worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.delete("/{name}") @router.delete("/{name}")
async def delete_worldbook(name: str): async def delete_worldbook(name: str):
""" """
删除世界书 删除世界书
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
worldbook_service.delete_worldbook(name)
return {"message": f"Worldbook '{name}' deleted successfully"}
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to delete worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.get("/{name}/entries", response_model=List[Dict[str, Any]]) @router.get("/{name}/entries", response_model=Dict[str, Any])
async def list_worldbook_entries(name: str): async def list_worldbook_entries(
name: str,
page: int = 1,
page_size: int = 20
):
""" """
获取世界书的所有条目 获取世界书的条目列表(支持分页)
Args:
name: 世界书名称
page: 页码从1开始
page_size: 每页数量默认20
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
return worldbook_service.list_entries(name, page, page_size)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to list entries for worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.get("/{name}/entries/{uid}", response_model=Dict[str, Any]) @router.get("/{name}/entries/{uid}", response_model=Dict[str, Any])
async def get_worldbook_entry(name: str, uid: int): async def get_worldbook_entry(name: str, uid: str):
""" """
获取世界书的指定条目 获取世界书的指定条目
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
return worldbook_service.get_entry(name, uid)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to get entry '{uid}' from worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.post("/{name}/entries", response_model=Dict[str, Any]) @router.post("/{name}/entries", response_model=Dict[str, Any])
async def create_worldbook_entry(name: str, entry_data: Dict[str, Any]): async def create_worldbook_entry(name: str, entry_data: Dict[str, Any]):
""" """
在世界书中创建新条目 在世界书中创建新条目
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
return worldbook_service.create_entry(name, entry_data)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to create entry in worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.put("/{name}/entries/{uid}", response_model=Dict[str, Any]) @router.put("/{name}/entries/{uid}", response_model=Dict[str, Any])
async def update_worldbook_entry(name: str, uid: int, entry_data: Dict[str, Any]): async def update_worldbook_entry(name: str, uid: str, entry_data: Dict[str, Any]):
""" """
更新世界书的指定条目 更新世界书的指定条目
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
return worldbook_service.update_entry(name, uid, entry_data)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to update entry '{uid}' in worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.delete("/{name}/entries/{uid}") @router.delete("/{name}/entries/{uid}")
async def delete_worldbook_entry(name: str, uid: int): async def delete_worldbook_entry(name: str, uid: str):
""" """
删除世界书的指定条目 删除世界书的指定条目
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
worldbook_service.delete_entry(name, uid)
return {"message": f"Entry '{uid}' deleted successfully"}
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to delete entry '{uid}' from worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.post("/{name}/import", response_model=Dict[str, Any]) @router.post("/{name}/import", response_model=Dict[str, Any])
async def import_worldbook(name: str, file: UploadFile = File(...)): async def import_worldbook(name: str, file: UploadFile = File(...)):
""" """
从文件导入世界书 从文件导入世界书(自动检测 SillyTavern 或内部格式)
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
content = await file.read()
data = json.loads(content.decode('utf-8'))
# 智能检测格式
from models.converters import WorldBookConverter
format_type = WorldBookConverter.detect_format(data)
logger.info(f"检测到世界书格式: {format_type}")
if format_type == "sillytavern":
# SillyTavern 格式,需要转换
logger.info(f"正在转换 SillyTavern 格式为内部格式")
return worldbook_service.import_from_sillytavern(name, data)
elif format_type == "internal":
# 已经是内部格式,直接保存
logger.info(f"检测到内部格式,直接保存")
return worldbook_service.import_internal_format(name, data)
else:
raise HTTPException(status_code=400, detail="无法识别的世界书格式")
except json.JSONDecodeError:
raise HTTPException(status_code=400, detail="Invalid JSON format")
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error(f"Failed to import worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
@router.get("/{name}/export") @router.get("/{name}/export")
async def export_worldbook(name: str): async def export_worldbook(name: str, format: str = "internal"):
""" """
导出世界书为 SillyTavern 格式 导出世界书(支持 internal 和 sillytavern 两种格式)
Args:
name: 世界书名称
format: 导出格式 ('internal''sillytavern'),默认 internal
""" """
raise HTTPException(status_code=501, detail="Not Implemented") try:
if format.lower() == "sillytavern":
# 导出为 SillyTavern 格式(可能丢失特殊设置)
logger.info(f"导出世界书 '{name}' 为 SillyTavern 格式")
st_data = worldbook_service.export_to_sillytavern(name)
return JSONResponse(
content=st_data,
headers={
"Content-Disposition": f"attachment; filename={name}_sillytavern.json"
}
)
else:
# 导出为内部格式(保留所有设置)
logger.info(f"导出世界书 '{name}' 为内部格式")
internal_data = worldbook_service.get_worldbook(name)
return JSONResponse(
content=internal_data,
headers={
"Content-Disposition": f"attachment; filename={name}.json"
}
)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except Exception as e:
logger.error(f"Failed to export worldbook '{name}': {str(e)}")
raise HTTPException(status_code=500, detail=str(e))

View File

@@ -52,6 +52,15 @@ class Settings:
# 临时文件目录 # 临时文件目录
TEMP_PATH = DATA_PATH / "temp" TEMP_PATH = DATA_PATH / "temp"
# ComfyUI 工作流目录
COMFYUI_WORKFLOWS_PATH = DATA_PATH / "comfyui_workflows"
# 角色卡目录
CHARACTERS_PATH = DATA_PATH / "characters"
# 图片资源目录
IMAGES_PATH = DATA_PATH / "images"
def ensure_directories(self): def ensure_directories(self):
"""确保所有配置的目录存在,如果不存在则创建""" """确保所有配置的目录存在,如果不存在则创建"""
directories = [ directories = [
@@ -60,6 +69,9 @@ class Settings:
self.PRESET_PATH, self.PRESET_PATH,
self.CHAT_PATH, self.CHAT_PATH,
self.TEMP_PATH, self.TEMP_PATH,
self.COMFYUI_WORKFLOWS_PATH,
self.CHARACTERS_PATH,
self.IMAGES_PATH,
] ]
for directory in directories: for directory in directories:
directory.mkdir(parents=True, exist_ok=True) directory.mkdir(parents=True, exist_ok=True)

View File

@@ -17,12 +17,22 @@ for logger_name in ['uvicorn', 'uvicorn.access', 'fastapi']:
# backend/app/main.py # backend/app/main.py
from fastapi import FastAPI from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
try: try:
from backend.api.route import router from backend.api.route import router
except ImportError: except ImportError:
from api.route import router from api.route import router
app = FastAPI(title="LLM Workflow Engine") app = FastAPI(title="LLM Workflow Engine")
# 配置CORS
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # 开发环境允许所有来源,生产环境应该指定具体域名
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# 注册路由 # 注册路由
app.include_router(router, prefix="/api") app.include_router(router, prefix="/api")

231
backend/models/README.md Normal file
View File

@@ -0,0 +1,231 @@
# Backend Models 数据模型说明
## 目录结构
```
models/
├── __init__.py # 包初始化,导出所有模型
├── sillytavern.py # SillyTavern 兼容模型 (仅用于导入/导出)
├── internal.py # 内部业务模型 (项目核心使用)
└── README.md # 本文件
```
## 模型分类
### 1. SillyTavern 兼容模型 (`sillytavern.py`)
**用途**: 仅用于与 SillyTavern 格式的数据进行导入/导出兼容
**特点**:
- 严格遵循 SillyTavern 官方规范
- 不参与内部业务逻辑
- 所有字段名、结构与 SillyTavern 保持一致
- 前缀 `ST` 表示 SillyTavern
**主要模型**:
- `STWorldInfo` - SillyTavern 世界书
- `STCharacterCard` - SillyTavern 角色卡
- `STChatHeader` / `STChatMessage` - SillyTavern 聊天记录
- `STGenerationPreset` - SillyTavern 采样预设
- `STPromptPreset` - SillyTavern 提示词预设
**使用场景**:
```python
# 从 SillyTavern 导入时
st_data = json.load(file)
st_character = STCharacterCard(**st_data)
# 转换为内部模型
internal_character = converter.st_to_internal(st_character)
# 导出到 SillyTavern 时
st_data = converter.internal_to_st(internal_character)
json.dump(st_data.dict(), file)
```
### 2. 内部业务模型 (`internal.py`)
**用途**: 项目内部真正使用的数据结构,所有业务逻辑都基于这些模型
**特点**:
- 继承并扩展了 SillyTavern 的功能
- 添加了项目特色功能 (如 LOGIC 激活、RAG 配置、outputSchema 等)
- 所有 API 响应、数据存储、工作流交换都使用这些模型
- 无前缀,直接使用语义化名称
**主要模型**:
#### 世界书相关
- `ActivationType` - 激活方式枚举 (PERMANENT/KEYWORD/RAG/LOGIC)
- `LogicExpression` - 逻辑表达式
- `RAGConfig` - RAG 检索配置
- `WorldInfoEntry` - 世界书条目
- `WorldInfo` - 世界书
#### 角色卡相关
- `OutputSchemaField` - 结构化输出 schema
- `CharacterCard` - 角色卡
#### 聊天记录相关
- `ChatHeader` - 聊天头
- `ChatMessage` - 聊天消息
- `ChatLog` - 完整聊天记录
#### 预设相关
- `GenerationPreset` - 采样参数预设
- `PromptRole` - Prompt 角色枚举
- `PromptEntry` - Prompt 条目
- `PromptPresetView` - Prompt 预设视图
#### RAG 配置
- `RAGSearchConfig` - RAG 搜索配置
- `CharacterRAGConfig` - 角色卡 RAG 配置
- `ChatRAGConfig` - 聊天 RAG 配置
**使用场景**:
```python
# 业务逻辑中直接使用
from models import CharacterCard, WorldInfo
character = CharacterCard(
id="uuid-123",
name="Alice",
description="...",
...
)
# API 响应
@app.get("/characters/{id}")
async def get_character(id: str):
character = service.get_character(id)
return character # 返回 internal 模型
```
## 数据转换流程
```
SillyTavern 文件
↓ (导入)
STCharacterCard (sillytavern.py)
↓ (转换器)
CharacterCard (internal.py)
↓ (业务处理)
CharacterCard (internal.py)
↓ (转换器)
STCharacterCard (sillytavern.py)
↓ (导出)
SillyTavern 文件
```
## 开发规范
### ✅ 正确做法
1. **业务逻辑使用 internal 模型**
```python
from models import CharacterCard
def create_character(data: dict) -> CharacterCard:
return CharacterCard(**data)
```
2. **导入时使用转换器**
```python
from models import STCharacterCard, CharacterCard
from models.converters import CharacterConverter
def import_character(file_path: str) -> CharacterCard:
st_data = load_json(file_path)
st_char = STCharacterCard(**st_data)
return CharacterConverter.st_to_internal(st_char)
```
3. **API 响应使用 internal 模型**
```python
@app.get("/characters")
async def list_characters() -> List[CharacterCard]:
return service.list_characters()
```
### ❌ 错误做法
1. **不要在业务逻辑中直接使用 ST 模型**
```python
# 错误!
from models import STCharacterCard
def process_character(char: STCharacterCard):
...
```
2. **不要混合使用两种模型**
```python
# 错误!
character = CharacterCard(...)
character.name = st_character.data.name # 不要混用
```
3. **不要在 API 中暴露 ST 模型**
```python
# 错误!
@app.get("/characters")
async def list_characters() -> List[STCharacterCard]:
...
```
## 添加新模型
当需要添加新的数据类型时:
1. **判断用途**:
- 如果是为了 SillyTavern 兼容 → 添加到 `sillytavern.py`
- 如果是项目内部使用 → 添加到 `internal.py`
2. **遵循命名规范**:
- SillyTavern 模型: 前缀 `ST`
- 内部模型: 无前缀,使用清晰的语义化名称
3. **添加详细注释**:
```python
class MyModel(BaseModel):
"""
模型用途说明
详细描述该模型的作用、使用场景等
"""
field1: str = Field(..., description="字段说明")
```
4. **在 `__init__.py` 中导出**:
```python
from .internal import MyModel
__all__ = [
...,
'MyModel',
]
```
## 转换器 (待实现)
`models/converters.py` 将提供双向转换功能:
```python
class CharacterConverter:
@staticmethod
def st_to_internal(st_char: STCharacterCard) -> CharacterCard:
"""SillyTavern → Internal"""
...
@staticmethod
def internal_to_st(int_char: CharacterCard) -> STCharacterCard:
"""Internal → SillyTavern"""
...
```
## 总结
- **sillytavern.py** = 外部兼容层 (Import/Export Only)
- **internal.py** = 内部业务层 (Core Business Logic)
- **永远在业务逻辑中使用 internal 模型**
- **通过转换器进行格式转换**

View File

@@ -0,0 +1,61 @@
"""
数据模型包
导出项目内部真正使用的数据结构 (Internal Models)。
SillyTavern 兼容模型将在需要导入/导出时单独引用。
"""
# 内部业务模型 (项目核心使用)
from .internal import (
# 世界书
ActivationType,
LogicOperator,
LogicExpression,
RAGConfig,
WorldInfoEntry,
WorldInfo,
# 角色卡
OutputSchemaField,
CharacterCard,
# 聊天记录
ChatHeader,
ChatMessage,
ChatLog,
# 预设
GenerationPreset,
# 提示词预设
PromptRole,
PromptEntry,
PromptPresetView,
# RAG 配置
RAGSearchConfig,
CharacterRAGConfig,
ChatRAGConfig,
)
__all__ = [
# 内部模型
'ActivationType',
'LogicOperator',
'LogicExpression',
'RAGConfig',
'WorldInfoEntry',
'WorldInfo',
'OutputSchemaField',
'CharacterCard',
'ChatHeader',
'ChatMessage',
'ChatLog',
'GenerationPreset',
'PromptRole',
'PromptEntry',
'PromptPresetView',
'RAGSearchConfig',
'CharacterRAGConfig',
'ChatRAGConfig',
]

View File

@@ -0,0 +1,379 @@
"""
数据模型转换器
提供 SillyTavern 格式与内部格式之间的双向转换功能。
所有导入/导出操作都应该通过转换器进行,确保数据格式的一致性。
"""
import uuid
from typing import Dict, Any, List, Optional
from datetime import datetime
from models.internal import (
WorldInfo,
WorldInfoEntry,
ActivationType,
)
class WorldBookConverter:
"""世界书数据转换器
负责 SillyTavern 格式和项目内部格式之间的转换。
SillyTavern 格式特点:
- entries 是 dict (key 为 uid)
- 使用 constant 字段表示常驻激活
- position 是字符串 (如 "after_char")
项目内部格式特点:
- entries 是 list
- 使用 activationType 枚举
- position 是数字 (0-5)
- 包含 trigger_config 结构(前端需要)
"""
@staticmethod
def detect_format(data: Dict[str, Any]) -> str:
"""
智能检测世界书数据格式
Args:
data: 世界书数据
Returns:
'sillytavern' | 'internal' | 'unknown'
"""
# 检查 entries 类型
entries = data.get("entries")
if not entries:
return "unknown"
# SillyTavern 特征: entries 是 dict
if isinstance(entries, dict):
return "sillytavern"
# 内部格式特征: entries 是 list
if isinstance(entries, list):
# 进一步检查是否有 trigger_config
if len(entries) > 0 and isinstance(entries[0], dict):
first_entry = entries[0]
if "trigger_config" in first_entry:
return "internal"
# 也可能是简化的内部格式
if "activationType" in first_entry or "position" in first_entry:
return "internal"
return "unknown"
# 位置映射: SillyTavern 字符串 -> 内部数字
POSITION_MAP_ST_TO_INTERNAL = {
"after_char": 0,
"before_char": 1,
"before_example": 2,
"after_example": 3,
"author_note": 4,
"system_prompt": 5,
}
# 位置映射: 内部数字 -> SillyTavern 字符串
POSITION_MAP_INTERNAL_TO_ST = {
0: "after_char",
1: "before_char",
2: "before_example",
3: "after_example",
4: "author_note",
5: "system_prompt",
}
@staticmethod
def st_to_internal(st_data: Dict[str, Any], name: str = None) -> Dict[str, Any]:
"""
将 SillyTavern 格式的世界书转换为内部格式
Args:
st_data: SillyTavern 格式的世界书数据
name: 世界书名称(可选,优先使用 st_data 中的 name)
Returns:
内部格式的世界书字典(包含 trigger_config)
"""
now = int(datetime.now().timestamp())
# 转换条目
entries = []
st_entries = st_data.get("entries", {})
# SillyTavern 的 entries 可能是 dict 或 list
if isinstance(st_entries, dict):
entries_list = list(st_entries.values())
elif isinstance(st_entries, list):
entries_list = st_entries
else:
entries_list = []
for st_entry in entries_list:
if not isinstance(st_entry, dict):
continue
# 判断激活类型
is_constant = st_entry.get("constant", False)
activation_type = ActivationType.PERMANENT if is_constant else ActivationType.KEYWORD
# 转换位置
st_position = st_entry.get("position", "after_char")
internal_position = WorldBookConverter.POSITION_MAP_ST_TO_INTERNAL.get(st_position, 0)
# 构建 trigger_config (前端期望的格式)
trigger_config = WorldBookConverter._build_trigger_config(
is_constant=is_constant,
key=st_entry.get("key", []),
keysecondary=st_entry.get("keysecondary", []),
selective=st_entry.get("selective", True)
)
# 创建内部格式的条目
entry_dict = {
"uid": st_entry.get("uid", str(uuid.uuid4())),
"key": st_entry.get("key", []),
"keysecondary": st_entry.get("keysecondary", []),
"content": st_entry.get("content", ""),
"comment": st_entry.get("comment", ""),
"activationType": activation_type.value,
"trigger_config": trigger_config,
"order": st_entry.get("order", 100),
"position": internal_position,
"depth": st_entry.get("depth", 4),
"role": st_entry.get("role", 0),
"probability": st_entry.get("probability", 100),
"group": st_entry.get("group", []),
"disable": st_entry.get("disable", False),
"createdAt": now,
"updatedAt": now
}
entries.append(entry_dict)
# 创建内部格式的世界书
worldbook_data = {
"id": str(uuid.uuid4()),
"name": name or st_data.get("name", "Unnamed"),
"description": st_data.get("description", ""),
"entries": entries,
"createdAt": now,
"updatedAt": now,
"version": 1
}
return worldbook_data
@staticmethod
def internal_to_st(worldbook_data: Dict[str, Any]) -> Dict[str, Any]:
"""
将内部格式的世界书转换为 SillyTavern 格式
Args:
worldbook_data: 内部格式的世界书字典
Returns:
SillyTavern 格式的世界书数据
"""
# 转换条目
st_entries = {}
for entry_data in worldbook_data.get("entries", []):
if not isinstance(entry_data, dict):
continue
uid = entry_data.get("uid", str(uuid.uuid4()))
# 从 trigger_config 或 activationType 判断是否常驻
is_constant = WorldBookConverter._is_constant_entry(entry_data)
# 提取关键词
key, keysecondary = WorldBookConverter._extract_keywords(entry_data)
# 转换位置
internal_position = entry_data.get("position", 0)
st_position = WorldBookConverter.POSITION_MAP_INTERNAL_TO_ST.get(internal_position, "after_char")
# 创建 SillyTavern 格式的条目
st_entry = {
"uid": uid,
"key": key,
"keysecondary": keysecondary,
"content": entry_data.get("content", ""),
"comment": entry_data.get("comment", ""),
"constant": is_constant,
"selective": not is_constant,
"order": entry_data.get("order", 100),
"position": st_position,
"depth": entry_data.get("depth", 4),
"probability": entry_data.get("probability", 100),
"group": entry_data.get("group", []),
"disable": entry_data.get("disable", False)
}
st_entries[uid] = st_entry
# 创建 SillyTavern 格式的世界书
st_data = {
"name": worldbook_data.get("name", ""),
"description": worldbook_data.get("description", ""),
"entries": st_entries
}
return st_data
@staticmethod
def normalize_entry(entry_data: Dict[str, Any]) -> Dict[str, Any]:
"""
规范化条目数据,确保包含所有必需字段和 trigger_config
Args:
entry_data: 条目数据(可能来自不同来源)
Returns:
规范化后的条目数据
"""
now = int(datetime.now().timestamp())
# 如果已经有 trigger_config,直接返回
if "trigger_config" in entry_data and entry_data["trigger_config"]:
return entry_data
# 否则从其他字段构建 trigger_config
is_constant = WorldBookConverter._is_constant_entry(entry_data)
key, keysecondary = WorldBookConverter._extract_keywords(entry_data)
trigger_config = WorldBookConverter._build_trigger_config(
is_constant=is_constant,
key=key,
keysecondary=keysecondary,
selective=entry_data.get("selective", True)
)
# 添加缺失的字段
normalized = {
"uid": entry_data.get("uid", str(uuid.uuid4())),
"key": key,
"keysecondary": keysecondary,
"content": entry_data.get("content", ""),
"comment": entry_data.get("comment", ""),
"activationType": entry_data.get("activationType",
ActivationType.PERMANENT.value if is_constant
else ActivationType.KEYWORD.value),
"trigger_config": trigger_config,
"order": entry_data.get("order", 100),
"position": entry_data.get("position", 0),
"depth": entry_data.get("depth", 4),
"role": entry_data.get("role", 0),
"probability": entry_data.get("probability", 100),
"group": entry_data.get("group", []),
"disable": entry_data.get("disable", False),
"createdAt": entry_data.get("createdAt", now),
"updatedAt": entry_data.get("updatedAt", now)
}
return normalized
@staticmethod
def _build_trigger_config(
is_constant: bool,
key: List[str],
keysecondary: List[str],
selective: bool = True
) -> Dict[str, Any]:
"""
构建 trigger_config 结构
Args:
is_constant: 是否常驻激活
key: 主关键词列表
keysecondary: 次要关键词列表
selective: 是否选择性匹配
Returns:
trigger_config 字典
"""
return {
"triggers": {
"constant": [is_constant, None],
"keyword": [
not is_constant,
{
"key": key,
"keysecondary": keysecondary,
"selective": selective,
"selectiveLogic": 0,
"matchWholeWords": False,
"caseSensitive": False
}
],
"rag": [False, {
"threshold": 0.75,
"top_k": 5,
"query_template": None
}],
"condition": [False, {
"variable_a": "",
"operator": "=",
"variable_b": ""
}]
}
}
@staticmethod
def _is_constant_entry(entry_data: Dict[str, Any]) -> bool:
"""
判断条目是否为常驻激活
Args:
entry_data: 条目数据
Returns:
是否常驻激活
"""
# 优先从 trigger_config 判断
if "trigger_config" in entry_data and entry_data["trigger_config"]:
try:
return entry_data["trigger_config"]["triggers"]["constant"][0]
except (KeyError, IndexError, TypeError):
pass
# 其次从 activationType 判断
if "activationType" in entry_data:
return entry_data["activationType"] == ActivationType.PERMANENT.value
# 最后从 constant 字段判断
if "constant" in entry_data:
return entry_data["constant"]
return False
@staticmethod
def _extract_keywords(entry_data: Dict[str, Any]) -> tuple:
"""
从条目数据中提取关键词
Args:
entry_data: 条目数据
Returns:
(key, keysecondary) 元组
"""
# 优先从 trigger_config 提取
if "trigger_config" in entry_data and entry_data["trigger_config"]:
try:
keyword_config = entry_data["trigger_config"]["triggers"]["keyword"][1]
if keyword_config:
key = keyword_config.get("key", [])
keysecondary = keyword_config.get("keysecondary", [])
return key, keysecondary
except (KeyError, IndexError, TypeError):
pass
# 否则从顶层字段提取
key = entry_data.get("key", [])
keysecondary = entry_data.get("keysecondary", [])
return key, keysecondary

301
backend/models/internal.py Normal file
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"""
项目内部数据结构定义
这是本项目真正使用的核心数据模型,所有业务逻辑都基于这些类型。
与 sillytavern.py 不同,这里的模型不参与导入导出兼容,而是专注于:
- 内部业务逻辑处理
- API 响应数据结构
- 数据存储格式
- 工作流引擎数据交换
所有从 SillyTavern 导入的数据都会转换为这些内部模型进行处理,
导出时再从内部模型转换回 SillyTavern 格式。
"""
from enum import Enum
from typing import List, Optional, Dict, Any
from pydantic import BaseModel, Field
from datetime import datetime
# ==================== 世界书 (World Info) ====================
class ActivationType(str, Enum):
"""
自定义激活方式类型4种枚举
这是项目的核心创新点之一,相比 SillyTavern 的简单 constant/selective 标志,
我们提供了更灵活的激活机制。
"""
PERMANENT = 'permanent' # 永久激活 - 始终包含在上下文中
KEYWORD = 'keyword' # 关键词触发 - 匹配关键词时激活
RAG = 'rag' # RAG 检索激活 - 基于向量相似度检索
LOGIC = 'logic' # 逻辑表达式激活 - 基于变量条件判断
class LogicOperator(str, Enum):
"""逻辑运算符(用于 LOGIC 激活类型)"""
EQUALS = 'equals' # 等于
NOT_EQUALS = 'not_equals' # 不等于
CONTAINS = 'contains' # 包含
NOT_CONTAINS = 'not_contains' # 不包含
GREATER = 'greater' # 大于
LESS = 'less' # 小于
class LogicExpression(BaseModel):
"""
逻辑表达式结构(用于 LOGIC 激活类型)
示例: variable1="mood", operator="equals", variable2="happy"
表示当 mood 变量等于 happy 时激活该条目
"""
variable1: str = Field(..., description="第一个变量名")
operator: LogicOperator = Field(..., description="比较运算符")
variable2: str = Field(..., description="第二个变量名或值")
class RAGConfig(BaseModel):
"""
RAG 配置(用于 RAG 激活类型)
控制如何从向量数据库中检索相关内容
"""
libraryId: str = Field(..., description="绑定的 RAG 库 ID")
threshold: Optional[float] = Field(0.7, ge=0, le=1, description="相似度阈值 (0-1)")
maxEntries: Optional[int] = Field(5, gt=0, description="最大返回条目数")
class WorldInfoEntry(BaseModel):
"""
项目内部世界书条目结构
这是世界书的核心单元,每个条目代表一段可以被动态注入到对话上下文中的知识。
相比 SillyTavern,我们添加了 activationType、logicExpression、ragConfig 等高级功能。
"""
uid: str = Field(..., description="条目唯一标识符 (UUID)")
key: Optional[List[str]] = Field(None, description="主关键词列表 (用于 KEYWORD 激活)")
keysecondary: Optional[List[str]] = Field(None, description="次要关键词列表 (可选过滤)")
content: str = Field(..., description="条目内容 - 激活时注入的文本")
activationType: ActivationType = Field(..., description="激活方式")
logicExpression: Optional[LogicExpression] = Field(None, description="逻辑表达式 (LOGIC 类型使用)")
ragConfig: Optional[RAGConfig] = Field(None, description="RAG 配置 (RAG 类型使用)")
order: int = Field(0, description="插入顺序 - 数值越大越靠近末尾")
position: Optional[str] = Field('after_char', description="插入位置")
depth: Optional[int] = Field(None, description="插入深度 (当 position='at_depth' 时使用)")
probability: Optional[float] = Field(100, ge=0, le=100, description="激活概率 (0-100)")
group: Optional[List[str]] = Field(None, description="所属组标签")
disable: bool = Field(False, description="是否禁用")
createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
class WorldInfo(BaseModel):
"""
项目内部世界书结构
世界书是角色知识的集合,可以绑定到角色卡上,在对话中动态提供背景信息。
"""
id: str = Field(..., description="世界书唯一标识符 (UUID)")
name: str = Field(..., description="世界书名称")
description: Optional[str] = Field(None, description="世界书描述")
entries: List[WorldInfoEntry] = Field(default_factory=list, description="条目数组")
createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
version: int = Field(1, description="版本号 (用于数据迁移)")
# ==================== 角色卡 (Character Card) ====================
class OutputSchemaField(BaseModel):
"""
Vercel AI SDK Output.object() 的表头定义
用于结构化输出,让 LLM 按照指定格式返回数据。
这是项目的特色功能,支持动态表格生成。
"""
name: str = Field(..., description="字段名称")
type: str = Field(..., description="字段类型 (string/number/boolean/array/object)")
description: str = Field(..., description="字段描述")
required: Optional[bool] = Field(None, description="是否必需")
enum: Optional[List[str]] = Field(None, description="枚举值 (字符串固定选项)")
fields: Optional[List['OutputSchemaField']] = Field(None, description="嵌套字段 (object 类型)")
class CharacterCard(BaseModel):
"""
项目内部角色卡结构
角色卡是对话 AI 的核心定义,包含人设、场景、开场白等。
相比 SillyTavern,我们添加了 categories、outputSchema、worldInfoId 等功能。
"""
id: str = Field(..., description="角色唯一标识符 (UUID)")
name: str = Field(..., description="角色名称")
description: str = Field(..., description="角色详细描述")
personality: str = Field(..., description="角色性格特征")
scenario: str = Field(..., description="场景设定")
first_mes: str = Field(..., description="首条开场消息")
mes_example: str = Field(..., description="对话示例")
categories: List[str] = Field(default_factory=list, description="分类标签 (用于前端筛选)")
worldInfoId: Optional[str] = Field(None, description="绑定的世界书 ID")
outputSchema: Optional[List[OutputSchemaField]] = Field(None, description="输出 schema 定义 (结构化输出)")
avatarPath: Optional[str] = Field(None, description="角色头像路径")
alternate_greetings: Optional[List[str]] = Field(None, description="替代问候语数组")
tags: Optional[List[str]] = Field(None, description="标签数组")
createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
lastChatAt: Optional[int] = Field(None, description="最后聊天时间戳")
isFavorite: bool = Field(False, description="收藏状态")
version: int = Field(1, description="版本号")
# ==================== 聊天记录 (Chat Log) ====================
class ChatHeader(BaseModel):
"""
项目内部聊天记录头
包含聊天的元数据,如参与角色、创建时间等。
"""
id: str = Field(..., description="聊天唯一标识符 (UUID)")
displayName: str = Field(..., description="显示名称 (聊天标题)")
characterId: str = Field(..., description="关联的角色卡 ID")
userName: str = Field("User", description="用户角色名")
characterName: str = Field(..., description="AI 角色名称")
tableData: Optional[Dict[str, Any]] = Field(None, description="表格数据 (对应 outputSchema)")
createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
messageCount: int = Field(0, description="消息数量")
ragLibraryId: Optional[str] = Field(None, description="关联的 RAG 历史消息库 ID")
class ChatMessage(BaseModel):
"""
项目内部聊天消息
单条对话消息,支持多版本 (swipes)、token 统计等功能。
"""
id: str = Field(..., description="消息唯一标识符 (UUID)")
name: str = Field(..., description="发送者名称")
is_user: bool = Field(..., description="是否为用户消息")
is_system: Optional[bool] = Field(None, description="是否为系统消息")
sendDate: str = Field(..., description="发送日期 ISO 字符串")
mes: str = Field(..., description="消息内容文本")
chatId: str = Field(..., description="关联的聊天 ID")
swipes: Optional[List[str]] = Field(None, description="替换回答数组 (多版本)")
swipe_id: Optional[int] = Field(0, description="当前选择的版本索引")
tokenCount: Optional[int] = Field(None, description="Token 数量 (用于统计)")
isTemporary: Optional[bool] = Field(None, description="是否为临时消息 (未保存)")
class ChatLog(BaseModel):
"""
项目内部完整聊天记录
包含聊天头和所有消息,是完整的对话历史。
"""
header: ChatHeader = Field(..., description="聊天头")
messages: List[ChatMessage] = Field(default_factory=list, description="消息列表")
# ==================== 预设 (Preset) ====================
class GenerationPreset(BaseModel):
"""
项目内部采样参数预设
控制 LLM 生成的参数配置,如温度、top_p 等。
"""
id: str = Field(..., description="预设唯一标识符 (UUID)")
name: str = Field(..., description="预设名称")
temperature: float = Field(1.0, ge=0, le=2, description="温度 (控制随机性)")
topP: float = Field(1.0, ge=0, le=1, description="Top P (核采样)")
topK: int = Field(0, ge=0, description="Top K")
repetitionPenalty: float = Field(1.0, ge=0, description="重复惩罚")
frequencyPenalty: Optional[float] = Field(None, description="频率惩罚")
presencePenalty: Optional[float] = Field(None, description="存在惩罚")
maxLength: Optional[int] = Field(None, gt=0, description="最大生成长度")
isDefault: bool = Field(False, description="是否为默认预设")
createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
# ==================== 提示词预设 (Prompt Preset) ====================
class PromptRole(str, Enum):
"""
Prompt 角色类型
内部业务层只保留三种角色,简化了 SillyTavern 的复杂角色系统。
"""
SYSTEM = 'system' # 系统指令
AI = 'ai' # AI 助手
USER = 'user' # 用户
class PromptEntry(BaseModel):
"""
内部业务层 - Prompt 条目
提示词模板的基本单元,可以组合成完整的提示词预设。
这是基于某个 character_id 生成的"当前视图"
"""
identifier: str = Field(..., description="稳定关联键 (用于回写)")
name: str = Field(..., description="条目名 (前端显示)")
enabled: bool = Field(True, description="是否启用 (当前作用域下的业务状态)")
content: str = Field(..., description="条目内容 (静态内容视图)")
order: int = Field(..., description="条目顺序 (前端展示和拖拽排序)")
role: PromptRole = Field(..., description="角色类型")
tokenCount: int = Field(0, description="总 token 数 (派生显示字段)")
isSystemNode: bool = Field(False, description="是否固有节点 (不可删除)")
class PromptPresetView(BaseModel):
"""
内部业务层 - Prompt 预设视图
基于某个 character_id 的"当前视图",包含已排序、已过滤的条目列表。
"""
characterId: str = Field(..., description="关联的角色 ID")
entries: List[PromptEntry] = Field(default_factory=list, description="当前视图的条目列表")
updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
version: int = Field(1, description="版本号")
# ==================== RAG 配置 ====================
class RAGSearchConfig(BaseModel):
"""RAG 搜索配置"""
topK: int = Field(5, gt=0, description="每次检索返回的结果数")
threshold: float = Field(0.7, ge=0, le=1, description="相似度阈值 (0-1)")
maxContextLength: int = Field(2000, gt=0, description="最大上下文长度 (字符数)")
class CharacterRAGConfig(BaseModel):
"""
角色卡 RAG 世界书库配置
记录角色卡关联的 RAG 知识库,用于动态检索相关知识。
"""
characterId: str = Field(..., description="角色卡ID")
ragLibraryIds: List[str] = Field(default_factory=list, description="关联的RAG库ID列表")
enabled: bool = Field(True, description="是否启用")
searchConfig: Optional[RAGSearchConfig] = Field(None, description="搜索配置")
position: str = Field('after_char', description="RAG内容插入位置")
createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")
class ChatRAGConfig(BaseModel):
"""
聊天会话 RAG 历史消息配置
记录聊天会话关联的 RAG 历史消息库,用于智能检索历史对话。
"""
chatId: str = Field(..., description="聊天会话ID")
ragLibraryId: Optional[str] = Field(None, description="关联的RAG历史消息库ID")
enabled: bool = Field(True, description="是否启用")
searchConfig: Optional[Dict[str, Any]] = Field(None, description="搜索配置")
autoIndex: bool = Field(True, description="是否自动索引新消息")
indexConfig: Optional[Dict[str, Any]] = Field(None, description="索引配置")
createdAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="创建时间戳")
updatedAt: int = Field(default_factory=lambda: int(datetime.now().timestamp()), description="最后更新时间戳")

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"""
业务服务层
包含项目的核心业务逻辑,协调 Models、Utils 和 LLM 组件。
"""
from .prompt_assembler import PromptAssembler, PromptConfig
__all__ = [
'PromptAssembler',
'PromptConfig',
]

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"""
角色卡格式转换器
支持 SillyTavern V2/V3 格式与内部格式的双向转换
"""
import json
import base64
from typing import Optional, Dict, Any
from pathlib import Path
from PIL import Image
import io
try:
from backend.models.internal import CharacterCard
except ImportError:
from models.internal import CharacterCard
class CharacterCardConverter:
"""角色卡格式转换器"""
@staticmethod
def st_to_internal(st_data: dict, avatar_path: Optional[str] = None) -> CharacterCard:
"""
SillyTavern 格式 → 内部格式
Args:
st_data: SillyTavern 角色卡数据V2/V3
avatar_path: 头像路径(可选)
Returns:
CharacterCard 对象
"""
import uuid
from datetime import datetime
# 兼容两种传入方式完整ST格式或直接data
if 'spec' in st_data:
data = st_data.get('data', {})
else:
data = st_data
extensions = data.get('extensions', {})
return CharacterCard(
id=str(uuid.uuid4()),
name=data['name'],
description=data.get('description', ''),
personality=data.get('personality', ''),
scenario=data.get('scenario', ''),
first_mes=data.get('first_mes', ''),
mes_example=data.get('mes_example', ''),
categories=[], # ST没有categories
worldInfoId=extensions.get('world'),
outputSchema=None, # ST不支持结构化输出
avatarPath=avatar_path,
alternate_greetings=data.get('alternate_greetings', []),
tags=data.get('tags', []),
createdAt=int(datetime.now().timestamp()),
updatedAt=int(datetime.now().timestamp()),
lastChatAt=None,
isFavorite=extensions.get('fav', False),
version=1
)
@staticmethod
def internal_to_st(character: CharacterCard) -> dict:
"""
内部格式 → SillyTavern V3 格式
Args:
character: CharacterCard 对象
Returns:
SillyTavern V3 格式字典
"""
return {
"spec": "chara_card_v3",
"spec_version": "3.0",
"data": {
"name": character.name,
"description": character.description,
"personality": character.personality,
"scenario": character.scenario,
"first_mes": character.first_mes,
"mes_example": character.mes_example,
"alternate_greetings": character.alternate_greetings or [],
"tags": character.tags or [],
"creator_notes": "",
"system_prompt": "",
"post_history_instructions": "",
"extensions": {
"world": character.worldInfoId,
"talkativeness": 0.5,
"fav": character.isFavorite
}
}
}
@staticmethod
def export_as_png(character: CharacterCard, avatar_path: Optional[str] = None, use_default_avatar: bool = False) -> bytes:
"""
导出为 SillyTavern PNG 格式
Args:
character: CharacterCard 对象
avatar_path: 头像图片路径(可选)
use_default_avatar: 是否使用默认头像不嵌入JSON数据
Returns:
PNG 文件的二进制数据
"""
# 1. 创建/加载图片
if avatar_path and Path(avatar_path).exists():
img = Image.open(avatar_path)
else:
# 创建默认图片400x600像素灰色背景
img = Image.new('RGB', (400, 600), color=(73, 109, 137))
# 确保是 RGBA 模式
if img.mode != 'RGBA':
img = img.convert('RGBA')
# 2. 如果不是默认头像,才嵌入 JSON 数据
if not use_default_avatar:
st_data = CharacterCardConverter.internal_to_st(character)
json_str = json.dumps(st_data, ensure_ascii=False)
base64_data = base64.b64encode(json_str.encode('utf-8')).decode('ascii')
img.text['ccv3'] = base64_data
# 3. 保存到字节流
buffer = io.BytesIO()
img.save(buffer, format='PNG')
buffer.seek(0)
return buffer.read()
@staticmethod
def extract_from_png(png_data: bytes) -> Optional[dict]:
"""
从 PNG 文件中提取嵌入的角色数据
Args:
png_data: PNG 文件的二进制数据
Returns:
SillyTavern 格式字典,如果没有嵌入数据则返回 None
"""
try:
img = Image.open(io.BytesIO(png_data))
# 尝试 V3 格式 (ccv3)
if 'ccv3' in img.text:
json_str = base64.b64decode(img.text['ccv3']).decode('utf-8')
return json.loads(json_str)
# 尝试 V2 格式 (chara)
elif 'chara' in img.text:
json_str = base64.b64decode(img.text['chara']).decode('utf-8')
return json.loads(json_str)
# 没有嵌入数据
return None
except Exception as e:
print(f"解析PNG失败: {e}")
return None

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"""
角色卡服务 - 严格按照 internal.py 的数据结构
每个角色一个文件夹,包含 character.json、avatar.png 和 chats/
"""
import json
from pathlib import Path
from typing import List, Optional
from datetime import datetime
import uuid
try:
from backend.models.internal import CharacterCard
from backend.core.config import settings
from backend.services.character_card_converter import CharacterCardConverter
except ImportError:
from models.internal import CharacterCard
from core.config import settings
from services.character_card_converter import CharacterCardConverter
class CharacterService:
"""角色卡管理服务"""
def __init__(self):
self.characters_dir = settings.CHARACTERS_PATH
self.converter = CharacterCardConverter()
# 确保目录存在
self.characters_dir.mkdir(parents=True, exist_ok=True)
def scan_all_characters(self) -> List[CharacterCard]:
"""
扫描所有角色卡
Returns:
按 lastChatAt 排序的角色卡列表(最新的在前)
"""
characters = []
for char_folder in self.characters_dir.iterdir():
if not char_folder.is_dir():
continue
try:
character = self._load_character_from_folder(char_folder)
if character:
characters.append(character)
except Exception as e:
print(f"加载角色卡失败 {char_folder.name}: {e}")
continue
# 按最后聊天时间排序None 排最后)
characters.sort(
key=lambda c: c.lastChatAt or 0,
reverse=True
)
return characters
def _load_character_from_folder(self, folder: Path) -> Optional[CharacterCard]:
"""
从文件夹加载角色卡
Args:
folder: 角色文件夹路径
Returns:
CharacterCard 对象或 None
"""
# 1. 读取 character.json必须存在
char_file = folder / "character.json"
if not char_file.exists():
return None
with open(char_file, 'r', encoding='utf-8') as f:
data = json.load(f)
# 2. 检查是否有 avatar.png
avatar_path = None
avatar_file = folder / "avatar.png"
if avatar_file.exists():
# 存储相对路径,用于前端访问
avatar_path = f"/api/characters/{folder.name}/avatar"
# 3. 计算最后聊天时间
last_chat_at = self._get_last_chat_timestamp(folder)
# 4. 构建 CharacterCard 对象(严格按照数据结构)
character = CharacterCard(
id=data.get('id', str(uuid.uuid4())),
name=data['name'],
description=data.get('description', ''),
personality=data.get('personality', ''),
scenario=data.get('scenario', ''),
first_mes=data.get('first_mes', ''),
mes_example=data.get('mes_example', ''),
categories=data.get('categories', []),
worldInfoId=data.get('worldInfoId'),
outputSchema=data.get('outputSchema'),
avatarPath=avatar_path,
alternate_greetings=data.get('alternate_greetings', []),
tags=data.get('tags', []),
createdAt=data.get('createdAt', int(datetime.now().timestamp())),
updatedAt=data.get('updatedAt', int(datetime.now().timestamp())),
lastChatAt=last_chat_at,
isFavorite=data.get('isFavorite', False),
version=data.get('version', 1)
)
return character
def _get_last_chat_timestamp(self, char_folder: Path) -> Optional[int]:
"""
获取角色的最后聊天时间戳
通过扫描 chats 目录下所有 .jsonl 文件的修改时间
"""
chats_dir = char_folder / "chats"
if not chats_dir.exists():
return None
latest_time = None
for chat_file in chats_dir.glob("*.jsonl"):
file_mtime = int(chat_file.stat().st_mtime)
if latest_time is None or file_mtime > latest_time:
latest_time = file_mtime
return latest_time
def get_character_by_name(self, name: str) -> Optional[CharacterCard]:
"""根据角色名获取角色卡"""
char_folder = self.characters_dir / name
if not char_folder.exists():
return None
return self._load_character_from_folder(char_folder)
def create_character(self, character_data: dict) -> CharacterCard:
"""
创建新角色卡
Args:
character_data: 角色数据字典
Returns:
创建的 CharacterCard 对象
"""
# 生成唯一ID
if 'id' not in character_data:
character_data['id'] = str(uuid.uuid4())
# 设置时间戳
now = int(datetime.now().timestamp())
character_data['createdAt'] = now
character_data['updatedAt'] = now
character_data['lastChatAt'] = None
# 创建文件夹
char_name = character_data['name']
char_folder = self.characters_dir / char_name
char_folder.mkdir(parents=True, exist_ok=True)
# 创建 chats 目录
chats_dir = char_folder / "chats"
chats_dir.mkdir(exist_ok=True)
# 保存 character.json
char_file = char_folder / "character.json"
with open(char_file, 'w', encoding='utf-8') as f:
json.dump(character_data, f, ensure_ascii=False, indent=2)
return self._load_character_from_folder(char_folder)
def update_character(self, name: str, updates: dict) -> CharacterCard:
"""
更新角色卡
Args:
name: 角色名
updates: 更新的字段
Returns:
更新后的 CharacterCard 对象
"""
char_folder = self.characters_dir / name
char_file = char_folder / "character.json"
if not char_file.exists():
raise FileNotFoundError(f"角色卡不存在: {name}")
# 读取现有数据
with open(char_file, 'r', encoding='utf-8') as f:
existing_data = json.load(f)
# 合并更新
existing_data.update(updates)
existing_data['updatedAt'] = int(datetime.now().timestamp())
# 保存
with open(char_file, 'w', encoding='utf-8') as f:
json.dump(existing_data, f, ensure_ascii=False, indent=2)
return self._load_character_from_folder(char_folder)
def delete_character(self, name: str) -> bool:
"""
删除角色卡(包括所有聊天记录)
Args:
name: 角色名
Returns:
是否成功删除
"""
char_folder = self.characters_dir / name
if not char_folder.exists():
return False
import shutil
shutil.rmtree(char_folder)
return True
def save_avatar(self, name: str, image_data: bytes) -> str:
"""
保存角色头像
Args:
name: 角色名
image_data: 图片二进制数据
Returns:
头像访问路径
"""
char_folder = self.characters_dir / name
avatar_file = char_folder / "avatar.png"
with open(avatar_file, 'wb') as f:
f.write(image_data)
return f"/api/characters/{name}/avatar"
def import_from_png(self, png_data: bytes, filename: str) -> CharacterCard:
"""
从 SillyTavern PNG 导入角色卡
Args:
png_data: PNG 文件二进制数据
filename: 原始文件名
Returns:
创建的 CharacterCard 对象
"""
# 1. 提取嵌入数据
st_data = self.converter.extract_from_png(png_data)
if not st_data:
raise ValueError("PNG文件中没有嵌入角色数据")
# 2. 转换为内部格式
character = self.converter.st_to_internal(st_data)
# 3. 创建角色文件夹
char_name = character.name
char_folder = self.characters_dir / char_name
char_folder.mkdir(parents=True, exist_ok=True)
# 4. 保存 PNG 作为 avatar.png
avatar_file = char_folder / "avatar.png"
with open(avatar_file, 'wb') as f:
f.write(png_data)
# 5. 保存 character.json
char_file = char_folder / "character.json"
with open(char_file, 'w', encoding='utf-8') as f:
json.dump(character.dict(), f, ensure_ascii=False, indent=2)
# 6. 创建 chats 目录
(char_folder / "chats").mkdir(exist_ok=True)
return character
def export_as_png(self, name: str) -> bytes:
"""
导出角色为 SillyTavern PNG 格式
Args:
name: 角色名
Returns:
PNG 文件二进制数据
"""
character = self.get_character_by_name(name)
if not character:
raise FileNotFoundError(f"角色 '{name}' 不存在")
# 获取头像路径
avatar_path = None
if character.avatarPath:
# 从路径中提取文件名
avatar_filename = character.avatarPath.split('/')[-1].split('?')[0]
char_folder = self.characters_dir / name
avatar_file = char_folder / avatar_filename
if avatar_file.exists():
avatar_path = str(avatar_file)
# 如果没有头像,使用默认图片
use_default = False
if not avatar_path:
default_avatar = self.characters_dir / "defult.png"
if default_avatar.exists():
avatar_path = str(default_avatar)
use_default = True
print(f"使用默认头像: {avatar_path}")
else:
print("警告: 没有找到默认头像")
# 生成 PNG
return self.converter.export_as_png(character, avatar_path, use_default_avatar=use_default)

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"""
聊天服务 - 处理聊天记录的读写操作
基于 SillyTavern JSONL 格式的聊天记录管理
"""
from pathlib import Path
from typing import Dict, List, Optional, Any
import json
import logging
from datetime import datetime
import uuid
logger = logging.getLogger(__name__)
class ChatService:
"""聊天服务类处理聊天记录的CRUD操作"""
def __init__(self, data_path: Path):
"""
初始化聊天服务
Args:
data_path: 数据目录路径
"""
self.data_path = data_path
self.chat_dir = data_path / "chat"
self.chat_dir.mkdir(parents=True, exist_ok=True)
def list_all_chats(self) -> Dict[str, List[Dict]]:
"""
获取所有角色和聊天列表
Returns:
Dict[str, List[Dict]]: 字典结构,键是角色名称,值是该角色的聊天信息列表
"""
result = {}
if not self.chat_dir.exists():
logger.warning(f"聊天目录不存在: {self.chat_dir}")
return result
for role_dir in self.chat_dir.iterdir():
try:
if role_dir.is_dir():
chats = []
for chat_file in role_dir.glob("*.jsonl"):
chat_info = self._get_chat_summary(role_dir.name, chat_file.stem)
if chat_info:
chats.append(chat_info)
if chats:
result[role_dir.name] = chats
except Exception as e:
logger.error(f"处理角色目录 {role_dir.name} 时出错: {str(e)}")
continue
return {"chat": [{"role_name": role, **chat} for role, chats in result.items() for chat in chats]}
def _get_chat_summary(self, role_name: str, chat_name: str) -> Optional[Dict]:
"""
获取聊天摘要信息
Args:
role_name: 角色名称
chat_name: 聊天名称
Returns:
Dict: 聊天摘要信息如果文件不存在则返回None
"""
chat_file = self.chat_dir / role_name / f"{chat_name}.jsonl"
if not chat_file.exists():
return None
try:
with open(chat_file, 'r', encoding='utf-8') as f:
lines = f.readlines()
if not lines:
return None
# 第一行是header
header = json.loads(lines[0])
# 计算消息数量排除header
message_count = len(lines) - 1
# 获取最后修改时间
last_modified = datetime.fromtimestamp(
chat_file.stat().st_mtime
).isoformat()
# 获取最后一条消息预览
last_message = ""
if message_count > 0:
try:
last_msg_data = json.loads(lines[-1])
last_message = last_msg_data.get("mes", "")
except:
pass
return {
"chat_name": chat_name,
"user_name": header.get("user_name", "User"),
"character_name": header.get("character_name", ""),
"last_modified": last_modified,
"message_count": message_count,
"last_message": last_message
}
except Exception as e:
logger.error(f"读取聊天摘要失败 {role_name}/{chat_name}: {str(e)}")
return None
def get_chat(self, role_name: str, chat_name: str) -> Dict[str, Any]:
"""
获取指定聊天的完整内容
Args:
role_name: 角色名称
chat_name: 聊天名称
Returns:
Dict: 包含metadata和messages的字典
Raises:
FileNotFoundError: 聊天文件不存在
"""
chat_file = self.chat_dir / role_name / f"{chat_name}.jsonl"
if not chat_file.exists():
raise FileNotFoundError(f"Chat not found: {role_name}/{chat_name}")
try:
with open(chat_file, 'r', encoding='utf-8') as f:
lines = f.readlines()
if not lines:
raise ValueError(f"Empty chat file: {role_name}/{chat_name}")
# 第一行是header
header = json.loads(lines[0])
# 解析消息
messages = []
for i, line in enumerate(lines[1:], start=1):
if line.strip(): # 跳过空行
msg_data = json.loads(line)
# 确保有floor字段
if "floor" not in msg_data:
msg_data["floor"] = i
messages.append(msg_data)
return {
"metadata": {
"user_name": header.get("user_name", "User"),
"character_name": header.get("character_name", ""),
"chat_id": header.get("chat_id_hash", ""),
"integrity": header.get("integrity", "")
},
"messages": messages
}
except Exception as e:
logger.error(f"读取聊天失败 {role_name}/{chat_name}: {str(e)}")
raise
def create_chat(self, role_name: str, chat_name: str, metadata: Dict = None) -> Dict:
"""
创建新聊天
Args:
role_name: 角色名称
chat_name: 聊天名称
metadata: 聊天元数据
Returns:
Dict: 创建的聊天信息
Raises:
FileExistsError: 聊天已存在
"""
chat_file = self.chat_dir / role_name / f"{chat_name}.jsonl"
if chat_file.exists():
raise FileExistsError(f"Chat already exists: {role_name}/{chat_name}")
# 创建角色目录
chat_file.parent.mkdir(parents=True, exist_ok=True)
# 构建header
header = {
"user_name": metadata.get("user_name", "User") if metadata else "User",
"character_name": metadata.get("character_name", role_name) if metadata else role_name,
"integrity": str(uuid.uuid4()),
"chat_id_hash": str(uuid.uuid4()),
"note_prompt": "",
"note_interval": 0,
"note_position": 0,
"note_depth": 0,
"note_role": 0,
"extensions": {},
"timedWorldInfo": {},
"variables": {},
"tainted": False,
"lastInContextMessageId": -1
}
# 写入header
with open(chat_file, 'w', encoding='utf-8') as f:
f.write(json.dumps(header, ensure_ascii=False) + '\n')
return {
"role_name": role_name,
"chat_name": chat_name,
"metadata": {
"user_name": header["user_name"],
"character_name": header["character_name"]
}
}
def add_message(self, role_name: str, chat_name: str, message_data: Dict) -> Dict:
"""
向聊天添加新消息
Args:
role_name: 角色名称
chat_name: 聊天名称
message_data: 消息数据
Returns:
Dict: 添加的消息
Raises:
FileNotFoundError: 聊天不存在
"""
chat_file = self.chat_dir / role_name / f"{chat_name}.jsonl"
if not chat_file.exists():
raise FileNotFoundError(f"Chat not found: {role_name}/{chat_name}")
try:
# 读取现有消息以确定floor
with open(chat_file, 'r', encoding='utf-8') as f:
lines = f.readlines()
# 计算下一个floor号
next_floor = len(lines) - 1 # 减去header行
# 构建完整的消息数据
full_message = {
"name": message_data.get("name", "User"),
"is_user": message_data.get("is_user", True),
"is_system": message_data.get("is_system", False),
"floor": next_floor,
"send_date": message_data.get("send_date", str(int(datetime.now().timestamp() * 1000))),
"mes": message_data.get("mes", ""),
"extra": message_data.get("extra", {}),
"swipes": message_data.get("swipes", []),
"swipe_id": message_data.get("swipe_id", 0),
"force_avatar": None,
"variables": [],
"variables_initialized": [],
"is_ejs_processed": []
}
# 追加消息到文件
with open(chat_file, 'a', encoding='utf-8') as f:
f.write(json.dumps(full_message, ensure_ascii=False) + '\n')
return full_message
except Exception as e:
logger.error(f"添加消息失败 {role_name}/{chat_name}: {str(e)}")
raise
def update_message(self, role_name: str, chat_name: str, floor: int, update_data: Dict) -> Dict:
"""
更新指定楼层的消息
Args:
role_name: 角色名称
chat_name: 聊天名称
floor: 楼层号
update_data: 更新的数据
Returns:
Dict: 更新后的消息
Raises:
FileNotFoundError: 聊天不存在
ValueError: 楼层不存在
"""
chat_file = self.chat_dir / role_name / f"{chat_name}.jsonl"
if not chat_file.exists():
raise FileNotFoundError(f"Chat not found: {role_name}/{chat_name}")
try:
# 读取所有行
with open(chat_file, 'r', encoding='utf-8') as f:
lines = f.readlines()
# 找到对应的消息行floor + 1因为第0行是header
message_line_index = floor + 1
if message_line_index >= len(lines):
raise ValueError(f"Floor {floor} not found in chat")
# 解析并更新消息
msg_data = json.loads(lines[message_line_index])
msg_data.update(update_data)
# 写回文件
lines[message_line_index] = json.dumps(msg_data, ensure_ascii=False) + '\n'
with open(chat_file, 'w', encoding='utf-8') as f:
f.writelines(lines)
return msg_data
except Exception as e:
logger.error(f"更新消息失败 {role_name}/{chat_name}/{floor}: {str(e)}")
raise
def delete_message(self, role_name: str, chat_name: str, floor: int) -> Dict:
"""
删除指定楼层的消息
Args:
role_name: 角色名称
chat_name: 聊天名称
floor: 楼层号
Returns:
Dict: 被删除的消息
Raises:
FileNotFoundError: 聊天不存在
ValueError: 楼层不存在
"""
chat_file = self.chat_dir / role_name / f"{chat_name}.jsonl"
if not chat_file.exists():
raise FileNotFoundError(f"Chat not found: {role_name}/{chat_name}")
try:
# 读取所有行
with open(chat_file, 'r', encoding='utf-8') as f:
lines = f.readlines()
# 找到对应的消息行
message_line_index = floor + 1
if message_line_index >= len(lines):
raise ValueError(f"Floor {floor} not found in chat")
# 保存被删除的消息
deleted_msg = json.loads(lines[message_line_index])
# 删除该行
del lines[message_line_index]
# 重新编号后续消息的floor
for i in range(message_line_index, len(lines)):
if lines[i].strip(): # 跳过空行
msg_data = json.loads(lines[i])
msg_data["floor"] = i - 1 # 重新计算floor
lines[i] = json.dumps(msg_data, ensure_ascii=False) + '\n'
# 写回文件
with open(chat_file, 'w', encoding='utf-8') as f:
f.writelines(lines)
return deleted_msg
except Exception as e:
logger.error(f"删除消息失败 {role_name}/{chat_name}/{floor}: {str(e)}")
raise

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"""
ComfyUI Workflow Manager
管理工作流 JSON 文件的上传、删除和加载
"""
import json
import os
from pathlib import Path
from typing import List, Dict, Optional
from fastapi import UploadFile, HTTPException
import shutil
from core.config import settings
# 工作流目录 - 使用统一的数据目录
WORKFLOW_DIR = settings.COMFYUI_WORKFLOWS_PATH
WORKFLOW_DIR.mkdir(parents=True, exist_ok=True)
class WorkflowManager:
"""ComfyUI 工作流管理器"""
@staticmethod
def list_workflows() -> List[Dict[str, str]]:
"""列出所有可用的工作流"""
workflows = []
for json_file in WORKFLOW_DIR.glob("*.json"):
try:
with open(json_file, 'r', encoding='utf-8') as f:
workflow_data = json.load(f)
workflows.append({
"filename": json_file.name,
"name": json_file.stem,
"nodes_count": len(workflow_data),
"size": json_file.stat().st_size
})
except Exception as e:
print(f"Error loading workflow {json_file.name}: {e}")
continue
return workflows
@staticmethod
def load_workflow(filename: str) -> Dict:
"""加载指定工作流"""
filepath = WORKFLOW_DIR / filename
if not filepath.exists():
raise HTTPException(status_code=404, detail=f"Workflow '{filename}' not found")
if not filepath.suffix == '.json':
raise HTTPException(status_code=400, detail="Invalid file type")
try:
with open(filepath, 'r', encoding='utf-8') as f:
return json.load(f)
except json.JSONDecodeError as e:
raise HTTPException(status_code=500, detail=f"Invalid JSON: {str(e)}")
@staticmethod
async def upload_workflow(file: UploadFile) -> Dict[str, str]:
"""上传工作流文件"""
# 验证文件名
if not file.filename or not file.filename.endswith('.json'):
raise HTTPException(status_code=400, detail="File must be a JSON file")
# 安全检查:防止路径遍历攻击
safe_filename = os.path.basename(file.filename)
if not safe_filename:
raise HTTPException(status_code=400, detail="Invalid filename")
filepath = WORKFLOW_DIR / safe_filename
# 如果文件已存在,先备份
if filepath.exists():
backup_path = WORKFLOW_DIR / f"{safe_filename}.bak"
shutil.copy2(filepath, backup_path)
# 保存文件
try:
content = await file.read()
# 验证 JSON 格式
try:
workflow_data = json.loads(content)
# 基本验证:检查是否是 ComfyUI 工作流
if not isinstance(workflow_data, dict):
raise ValueError("Workflow must be a JSON object")
# 检查是否包含必要的节点类型
has_sampler = any(
node.get("class_type") == "KSampler"
for node in workflow_data.values()
if isinstance(node, dict)
)
if not has_sampler:
raise ValueError("Invalid ComfyUI workflow: missing KSampler node")
except json.JSONDecodeError:
raise HTTPException(status_code=400, detail="Invalid JSON format")
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
# 写入文件
with open(filepath, 'w', encoding='utf-8') as f:
f.write(content.decode('utf-8'))
return {
"message": "Workflow uploaded successfully",
"filename": safe_filename,
"size": len(content)
}
except HTTPException:
raise
except Exception as e:
# 如果出错,恢复备份
backup_path = WORKFLOW_DIR / f"{safe_filename}.bak"
if backup_path.exists():
shutil.move(backup_path, filepath)
raise HTTPException(status_code=500, detail=f"Upload failed: {str(e)}")
@staticmethod
def delete_workflow(filename: str) -> Dict[str, str]:
"""删除工作流文件"""
# 安全检查
safe_filename = os.path.basename(filename)
if not safe_filename or not safe_filename.endswith('.json'):
raise HTTPException(status_code=400, detail="Invalid filename")
filepath = WORKFLOW_DIR / safe_filename
if not filepath.exists():
raise HTTPException(status_code=404, detail=f"Workflow '{filename}' not found")
# 不允许删除默认工作流
if safe_filename == "default_txt2img.json":
raise HTTPException(
status_code=403,
detail="Cannot delete default workflow"
)
try:
filepath.unlink()
return {"message": f"Workflow '{safe_filename}' deleted successfully"}
except Exception as e:
raise HTTPException(status_code=500, detail=f"Delete failed: {str(e)}")
@staticmethod
def replace_prompt_in_workflow(workflow: Dict, prompt: str) -> Dict:
"""
在工作流中替换提示词
找到第一个 CLIPTextEncode 节点,替换其 text 字段
"""
import copy
workflow_copy = copy.deepcopy(workflow)
# 查找 CLIPTextEncode 节点(通常是正向提示词)
for node_id, node in workflow_copy.items():
if isinstance(node, dict) and node.get("class_type") == "CLIPTextEncode":
if "text" in node.get("inputs", {}):
# 替换提示词
node["inputs"]["text"] = prompt
return workflow_copy
# 如果没有找到 CLIPTextEncode 节点,抛出错误
raise ValueError("No CLIPTextEncode node found in workflow")
# 全局实例
workflow_manager = WorkflowManager()

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"""
LLM 模型管理服务
提供获取不同 LLM 提供商可用模型列表的功能
"""
from typing import List, Dict, Any, Optional
import requests
class LLMModelService:
"""LLM 模型管理服务"""
@staticmethod
def get_openai_models(api_key: str, base_url: Optional[str] = None) -> List[str]:
"""
获取 OpenAI 兼容 API 的模型列表
Args:
api_key: API Key
base_url: API 基础 URL默认为 OpenAI 官方 API
Returns:
模型名称列表
"""
try:
# 默认使用 OpenAI 官方 API
if not base_url:
base_url = "https://api.openai.com/v1"
# 确保 base_url 以 /v1 结尾
if not base_url.endswith('/v1'):
base_url = base_url.rstrip('/') + '/v1'
response = requests.get(
f"{base_url}/models",
headers={
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
},
timeout=10
)
if response.status_code != 200:
raise Exception(f"HTTP {response.status_code}: {response.text}")
data = response.json()
models = [model['id'] for model in data.get('data', [])]
# 过滤出聊天模型(可选)
chat_models = [
m for m in models
if any(keyword in m.lower() for keyword in ['gpt', 'chat'])
]
# 如果没有找到聊天模型,返回所有模型
return chat_models if chat_models else models
except Exception as e:
raise Exception(f"获取 OpenAI 模型列表失败: {str(e)}")
@staticmethod
def get_anthropic_models(api_key: str) -> List[str]:
"""
获取 Anthropic Claude 模型列表
Args:
api_key: API Key
Returns:
模型名称列表
"""
try:
# Anthropic 没有公开的模型列表 API返回已知模型
return [
"claude-3-5-sonnet-20241022",
"claude-3-5-haiku-20241022",
"claude-3-opus-20240229",
"claude-3-sonnet-20240229",
"claude-3-haiku-20240307",
"claude-2.1",
"claude-2.0",
"claude-instant-1.2"
]
except Exception as e:
raise Exception(f"获取 Anthropic 模型列表失败: {str(e)}")
@staticmethod
def get_ollama_models(base_url: str = "http://localhost:11434") -> List[str]:
"""
获取 Ollama 本地模型列表
Args:
base_url: Ollama API 地址
Returns:
模型名称列表
"""
try:
response = requests.get(
f"{base_url}/api/tags",
timeout=10
)
if response.status_code != 200:
raise Exception(f"HTTP {response.status_code}: {response.text}")
data = response.json()
models = [model['name'] for model in data.get('models', [])]
return models
except Exception as e:
raise Exception(f"获取 Ollama 模型列表失败: {str(e)}")
@staticmethod
def detect_provider(api_url: str) -> str:
"""
根据 API URL 检测提供商类型
Args:
api_url: API 地址
Returns:
提供商类型: 'openai', 'anthropic', 'ollama', 'unknown'
"""
api_url_lower = api_url.lower()
if 'openai' in api_url_lower or 'api.openai.com' in api_url_lower:
return 'openai'
elif 'anthropic' in api_url_lower or 'api.anthropic.com' in api_url_lower:
return 'anthropic'
elif 'ollama' in api_url_lower or 'localhost:11434' in api_url_lower or '127.0.0.1:11434' in api_url_lower:
return 'ollama'
elif 'siliconflow' in api_url_lower or 'silicon.cloud' in api_url_lower:
# SiliconFlow 等兼容 OpenAI API 的服务
return 'openai'
elif 'deepseek' in api_url_lower:
# DeepSeek 等兼容 OpenAI API 的服务
return 'openai'
else:
# 默认尝试 OpenAI 兼容 API
return 'openai'
@staticmethod
def get_models_by_provider(
provider: str,
api_key: str,
api_url: Optional[str] = None
) -> List[str]:
"""
根据提供商类型获取模型列表
Args:
provider: 提供商类型 ('openai', 'anthropic', 'ollama')
api_key: API Key
api_url: API 地址(可选)
Returns:
模型名称列表
"""
if provider == 'openai':
return LLMModelService.get_openai_models(api_key, api_url)
elif provider == 'anthropic':
return LLMModelService.get_anthropic_models(api_key)
elif provider == 'ollama':
base_url = api_url or "http://localhost:11434"
# 移除 /v1 后缀(如果有)
base_url = base_url.replace('/v1', '').replace('/v1/', '')
return LLMModelService.get_ollama_models(base_url)
else:
raise Exception(f"不支持的提供商: {provider}")

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"""
提示词组装器 (Prompt Assembler)
负责根据 SillyTavern 规范将角色卡、世界书、聊天历史等组件
拼装成最终的 LLM 消息列表。
"""
import re
from typing import List, Dict, Optional
from langchain_core.messages import SystemMessage, HumanMessage, AIMessage, BaseMessage
from models.internal import CharacterCard, ChatMessage, WorldInfoEntry
class PromptConfig:
"""提示词组装配置"""
def __init__(
self,
an_position: str = "after_history", # "before_history" or "after_history"
an_depth: int = 4,
post_history_instructions: Optional[str] = None
):
self.an_position = an_position
self.an_depth = an_depth
self.post_history_instructions = post_history_instructions
class PromptAssembler:
"""
轻量级提示词组装核心
不依赖复杂的框架,只负责纯粹的文本拼接和位置插入。
"""
# SillyTavern 的位置枚举映射
POS_WI_BEFORE = 0
POS_WI_AFTER = 1
POS_EXAMPLES_BEFORE = 2
POS_EXAMPLES_AFTER = 3
POS_AN_TOP = 4
POS_AN_BOTTOM = 5
POS_DEPTH = 6
POS_OUTLET = 7
def assemble(
self,
character: CharacterCard,
chat_history: List[ChatMessage],
user_input: str,
active_entries: List[WorldInfoEntry],
config: PromptConfig = PromptConfig()
) -> List[BaseMessage]:
"""
执行完整的提示词组装流程
Returns:
List[BaseMessage]: 准备好发送给 LLM 的消息列表
"""
# 1. 按位置分组世界书条目
grouped_entries = self._group_entries_by_position(active_entries)
# 2. 组装 Story String (包含 Pos 0-3)
story_string = self._build_story_string(character, grouped_entries)
# 3. 组装 Author's Note (包含 Pos 4-5)
authors_note_content = self._build_authors_note(grouped_entries, config.an_depth)
# 4. 处理 Chat History 并注入 Depth 条目 (Pos 6)
processed_history = self._inject_depth_entries(chat_history, grouped_entries.get(self.POS_DEPTH, []))
# 5. 准备 Outlet 替换字典 (Pos 7)
outlet_map = {entry.uid: entry.content for entry in grouped_entries.get(self.POS_OUTLET, [])}
# 6. 最终封装为 Messages
return self._wrap_to_messages(
story_string,
authors_note_content,
processed_history,
user_input,
outlet_map,
config
)
def _group_entries_by_position(self, entries: List[WorldInfoEntry]) -> Dict[int, List[WorldInfoEntry]]:
"""将激活的条目按 position 分组"""
grouped = {}
for entry in entries:
# 这里假设 entry.position 存储的是我们定义的 0-7 整数
pos = entry.position if isinstance(entry.position, int) else 1 # 默认为 wiAfter
if pos not in grouped:
grouped[pos] = []
grouped[pos].append(entry)
# 对每个组内的条目按 order 排序
for pos in grouped:
grouped[pos].sort(key=lambda x: x.order)
return grouped
def _build_story_string(self, character: CharacterCard, grouped: Dict) -> str:
"""组装故事字符串 (Story String)"""
parts = []
# Pos 0: wiBefore
for entry in grouped.get(self.POS_WI_BEFORE, []):
parts.append(entry.content)
# 角色核心信息
parts.append(f"[Character('{character.name}')]\n{character.description}\n")
parts.append(f"Personality: {character.personality}\n")
parts.append(f"Scenario: {character.scenario}\n")
# Pos 1: wiAfter
for entry in grouped.get(self.POS_WI_AFTER, []):
parts.append(entry.content)
# Pos 2: Examples Before
for entry in grouped.get(self.POS_EXAMPLES_BEFORE, []):
parts.append(entry.content)
# 示例对话
if character.mes_example:
parts.append(f"<START>\n{character.mes_example}")
# Pos 3: Examples After
for entry in grouped.get(self.POS_EXAMPLES_AFTER, []):
parts.append(entry.content)
return "\n".join(parts)
def _build_authors_note(self, grouped: Dict, depth: int) -> str:
"""组装作者笔记 (Author's Note)"""
parts = []
# Pos 4: AN Top
for entry in grouped.get(self.POS_AN_TOP, []):
parts.append(entry.content)
# AN 核心内容 (这里简化为一个占位,实际应从角色卡或设置获取)
parts.append(f"[Author's note at depth {depth}]")
# Pos 5: AN Bottom
for entry in grouped.get(self.POS_AN_BOTTOM, []):
parts.append(entry.content)
return "\n".join(parts)
def _inject_depth_entries(self, history: List[ChatMessage], depth_entries: List[WorldInfoEntry]) -> List[Dict]:
"""
在聊天历史的指定深度插入条目 (Pos 6)
返回一个包含 role 和 content 的字典列表,方便后续转换
"""
# 先将历史转换为中间格式
msg_list = []
for msg in history:
msg_list.append({"role": "user" if msg.is_user else "assistant", "content": msg.mes})
# 按 depth 分组插入
# d0 通常指最新用户输入之前,即列表末尾
for entry in depth_entries:
depth = entry.depth if entry.depth is not None else 0
# 计算插入索引 (从后往前数)
insert_index = max(0, len(msg_list) - depth)
# 确定角色
role_map = {"system": "system", "user": "user", "assistant": "assistant"}
role = role_map.get(str(entry.position).split('_')[-1] if '_' in str(entry.position) else "system", "system")
msg_list.insert(insert_index, {"role": "system", "content": entry.content})
return msg_list
def _replace_outlets(self, text: str, outlet_map: Dict[str, str]) -> str:
"""执行 Outlet 宏替换 (Pos 7)"""
def replacer(match):
uid = match.group(1)
return outlet_map.get(uid, "")
# 匹配 {{outlet::UID}}
return re.sub(r"\{\{outlet::([^}]+)\}\}", replacer, text)
def _wrap_to_messages(
self,
story_string: str,
an_content: str,
history: List[Dict],
user_input: str,
outlet_map: Dict[str, str],
config: PromptConfig
) -> List[BaseMessage]:
"""将组装好的文本块封装为 LangChain Messages"""
messages = []
# 1. System Message (Story String + Outlet 替换)
final_story = self._replace_outlets(story_string, outlet_map)
if final_story:
messages.append(SystemMessage(content=final_story))
# 2. Author's Note (根据配置位置插入)
if an_content and config.an_position == "before_history":
messages.append(SystemMessage(content=self._replace_outlets(an_content, outlet_map)))
# 3. Chat History
for msg_data in history:
if msg_data["role"] == "user":
messages.append(HumanMessage(content=msg_data["content"]))
elif msg_data["role"] == "assistant":
messages.append(AIMessage(content=msg_data["content"]))
else:
messages.append(SystemMessage(content=msg_data["content"]))
# 4. Author's Note (如果在 History 之后)
if an_content and config.an_position == "after_history":
messages.append(SystemMessage(content=self._replace_outlets(an_content, outlet_map)))
# 5. Post-History Instructions & User Input
final_input = user_input
if config.post_history_instructions:
final_input = f"{config.post_history_instructions}\n\n{user_input}"
messages.append(HumanMessage(content=final_input))
return messages

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"""
World Book Service
世界书服务层 - 处理世界书及条目的 CRUD 操作
"""
import json
import os
import uuid
from pathlib import Path
from typing import List, Dict, Any, Optional
from datetime import datetime
from models.internal import WorldInfo, WorldInfoEntry, ActivationType
from models.converters import WorldBookConverter
from core.config import settings
class WorldBookService:
"""世界书服务类"""
@staticmethod
def _get_worldbook_path(name: str) -> Path:
"""获取世界书文件路径"""
return settings.WORLDBOOKS_PATH / f"{name}.json"
@staticmethod
def _load_worldbook(name: str) -> Optional[Dict[str, Any]]:
"""加载世界书 JSON 文件"""
path = WorldBookService._get_worldbook_path(name)
if not path.exists():
return None
try:
with open(path, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception as e:
raise ValueError(f"Failed to load worldbook '{name}': {str(e)}")
@staticmethod
def _save_worldbook(name: str, data: Dict[str, Any]):
"""保存世界书到 JSON 文件"""
path = WorldBookService._get_worldbook_path(name)
try:
with open(path, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=2)
except Exception as e:
raise ValueError(f"Failed to save worldbook '{name}': {str(e)}")
@staticmethod
def list_worldbooks() -> List[Dict[str, Any]]:
"""
获取所有世界书的列表(仅基本信息)
Returns:
世界书列表,每个包含 name, description, entries_count 等
"""
worldbooks = []
for json_file in settings.WORLDBOOKS_PATH.glob("*.json"):
try:
with open(json_file, 'r', encoding='utf-8') as f:
data = json.load(f)
# 内部格式entries 是列表
entries = data.get("entries", [])
entries_count = len(entries) if isinstance(entries, list) else 0
worldbooks.append({
"name": data.get("name", json_file.stem),
"description": data.get("description", ""),
"entries_count": entries_count,
"createdAt": data.get("createdAt", 0),
"updatedAt": data.get("updatedAt", 0)
})
except Exception as e:
print(f"Error loading worldbook {json_file.name}: {e}")
continue
# 按更新时间排序
worldbooks.sort(key=lambda x: x.get("updatedAt", 0), reverse=True)
return worldbooks
@staticmethod
def get_worldbook(name: str) -> Dict[str, Any]:
"""
获取指定世界书的完整数据
Args:
name: 世界书名称
Returns:
世界书完整数据
"""
data = WorldBookService._load_worldbook(name)
if not data:
raise FileNotFoundError(f"Worldbook '{name}' not found")
return data
@staticmethod
def create_worldbook(name: str, description: str = "") -> Dict[str, Any]:
"""
创建新世界书
Args:
name: 世界书名称
description: 世界书描述
Returns:
创建的世界书数据
"""
# 检查是否已存在
if WorldBookService._get_worldbook_path(name).exists():
raise ValueError(f"Worldbook '{name}' already exists")
now = int(datetime.now().timestamp())
worldbook_data = {
"id": str(uuid.uuid4()),
"name": name,
"description": description,
"entries": [],
"createdAt": now,
"updatedAt": now,
"version": 1
}
WorldBookService._save_worldbook(name, worldbook_data)
return worldbook_data
@staticmethod
def update_worldbook(name: str, description: Optional[str] = None) -> Dict[str, Any]:
"""
更新世界书基本信息
Args:
name: 世界书名称
description: 新的描述(可选)
Returns:
更新后的世界书数据
"""
data = WorldBookService._load_worldbook(name)
if not data:
raise FileNotFoundError(f"Worldbook '{name}' not found")
if description is not None:
data["description"] = description
data["updatedAt"] = int(datetime.now().timestamp())
WorldBookService._save_worldbook(name, data)
return data
@staticmethod
def delete_worldbook(name: str) -> bool:
"""
删除世界书
Args:
name: 世界书名称
Returns:
是否删除成功
"""
path = WorldBookService._get_worldbook_path(name)
if not path.exists():
raise FileNotFoundError(f"Worldbook '{name}' not found")
path.unlink()
return True
@staticmethod
def list_entries(name: str, page: int = 1, page_size: int = 20) -> Dict[str, Any]:
"""
获取世界书的条目列表(支持分页)
Args:
name: 世界书名称
page: 页码从1开始
page_size: 每页数量默认20
Returns:
包含条目列表和分页信息的字典
"""
data = WorldBookService._load_worldbook(name)
if not data:
raise FileNotFoundError(f"Worldbook '{name}' not found")
# 内部格式entries 是列表
all_entries = data.get("entries", [])
if not isinstance(all_entries, list):
all_entries = []
total = len(all_entries)
# 计算分页
start_idx = (page - 1) * page_size
end_idx = start_idx + page_size
paginated_entries = all_entries[start_idx:end_idx]
return {
"entries": paginated_entries,
"total": total,
"page": page,
"page_size": page_size,
"total_pages": (total + page_size - 1) // page_size # 向上取整
}
@staticmethod
def get_entry(name: str, uid: str) -> Dict[str, Any]:
"""
获取世界书的指定条目
Args:
name: 世界书名称
uid: 条目 UID
Returns:
条目数据
"""
data = WorldBookService._load_worldbook(name)
if not data:
raise FileNotFoundError(f"Worldbook '{name}' not found")
# 内部格式entries 是列表
entries = data.get("entries", [])
if not isinstance(entries, list):
entries = []
for entry in entries:
if entry.get("uid") == uid or str(entry.get("uid")) == uid:
return entry
raise FileNotFoundError(f"Entry '{uid}' not found in worldbook '{name}'")
@staticmethod
def create_entry(name: str, entry_data: Dict[str, Any]) -> Dict[str, Any]:
"""
在世界书中创建新条目
Args:
name: 世界书名称
entry_data: 条目数据(不包含 uid, createdAt, updatedAt
Returns:
创建的条目数据
"""
data = WorldBookService._load_worldbook(name)
if not data:
raise FileNotFoundError(f"Worldbook '{name}' not found")
# 生成 UID 和时间戳
now = int(datetime.now().timestamp())
new_entry = {
"uid": str(uuid.uuid4()),
"key": entry_data.get("key", []),
"keysecondary": entry_data.get("keysecondary", []),
"content": entry_data.get("content", ""),
"activationType": entry_data.get("activationType", ActivationType.KEYWORD.value),
"logicExpression": entry_data.get("logicExpression"),
"ragConfig": entry_data.get("ragConfig"),
"order": entry_data.get("order", 0),
"position": entry_data.get("position", "after_char"),
"depth": entry_data.get("depth"),
"probability": entry_data.get("probability", 100),
"group": entry_data.get("group", []),
"disable": entry_data.get("disable", False),
"createdAt": now,
"updatedAt": now
}
data["entries"].append(new_entry)
data["updatedAt"] = now
WorldBookService._save_worldbook(name, data)
return new_entry
@staticmethod
def update_entry(name: str, uid: str, entry_data: Dict[str, Any]) -> Dict[str, Any]:
"""
更新世界书的指定条目
Args:
name: 世界书名称
uid: 条目 UID
entry_data: 更新的字段
Returns:
更新后的条目数据
"""
data = WorldBookService._load_worldbook(name)
if not data:
raise FileNotFoundError(f"Worldbook '{name}' not found")
for i, entry in enumerate(data.get("entries", [])):
if entry.get("uid") == uid:
# 更新字段
for key, value in entry_data.items():
if key not in ["uid", "createdAt"]: # 不修改 UID 和创建时间
entry[key] = value
# 更新时间戳
entry["updatedAt"] = int(datetime.now().timestamp())
data["entries"][i] = entry
data["updatedAt"] = entry["updatedAt"]
WorldBookService._save_worldbook(name, data)
return entry
raise FileNotFoundError(f"Entry '{uid}' not found in worldbook '{name}'")
@staticmethod
def delete_entry(name: str, uid: str) -> bool:
"""
删除世界书的指定条目
Args:
name: 世界书名称
uid: 条目 UID
Returns:
是否删除成功
"""
data = WorldBookService._load_worldbook(name)
if not data:
raise FileNotFoundError(f"Worldbook '{name}' not found")
original_length = len(data.get("entries", []))
data["entries"] = [e for e in data.get("entries", []) if e.get("uid") != uid]
if len(data["entries"]) == original_length:
raise FileNotFoundError(f"Entry '{uid}' not found in worldbook '{name}'")
data["updatedAt"] = int(datetime.now().timestamp())
WorldBookService._save_worldbook(name, data)
return True
@staticmethod
def import_from_sillytavern(name: str, st_data: Dict[str, Any]) -> Dict[str, Any]:
"""
从 SillyTavern 格式导入世界书
Args:
name: 世界书名称
st_data: SillyTavern 格式的世界书数据
Returns:
转换后的内部格式世界书数据
"""
# 使用转换器进行转换
worldbook_data = WorldBookConverter.st_to_internal(st_data, name)
# 保存到文件
WorldBookService._save_worldbook(name, worldbook_data)
return worldbook_data
@staticmethod
def import_internal_format(name: str, internal_data: Dict[str, Any]) -> Dict[str, Any]:
"""
直接导入内部格式的世界书(无需转换)
Args:
name: 世界书名称
internal_data: 内部格式的世界书数据
Returns:
内部格式世界书数据
"""
# 确保包含必要的字段
if "name" not in internal_data:
internal_data["name"] = name
# 规范化所有条目,确保有 trigger_config
if "entries" in internal_data and isinstance(internal_data["entries"], list):
normalized_entries = []
for entry in internal_data["entries"]:
if isinstance(entry, dict):
normalized_entry = WorldBookConverter.normalize_entry(entry)
normalized_entries.append(normalized_entry)
internal_data["entries"] = normalized_entries
# 保存文件
WorldBookService._save_worldbook(name, internal_data)
return internal_data
@staticmethod
def export_to_sillytavern(name: str) -> Dict[str, Any]:
"""
导出为 SillyTavern 格式
Args:
name: 世界书名称
Returns:
SillyTavern 格式的世界书数据
"""
data = WorldBookService._load_worldbook(name)
if not data:
raise FileNotFoundError(f"Worldbook '{name}' not found")
# 使用转换器进行转换
st_data = WorldBookConverter.internal_to_st(data)
return st_data
# 全局实例
worldbook_service = WorldBookService()

17
backend/utils/__init__.py Normal file
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"""
工具类包
提供通用的工具函数和辅助类如文件操作、LLM 调用封装等。
"""
from .file_utils import get_all_roles_and_chats, read_jsonl_file, write_jsonl_file
from .llm_client import get_llm, get_fast_llm, get_creative_llm, get_streaming_llm
__all__ = [
'get_all_roles_and_chats',
'read_jsonl_file',
'write_jsonl_file',
'get_llm',
'get_fast_llm',
'get_creative_llm',
'get_streaming_llm',
]

130
backend/utils/file_utils.py Normal file
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"""
文件操作工具函数
提供文件和目录操作的通用工具
"""
from pathlib import Path
from typing import Dict, List
import json
import logging
logger = logging.getLogger(__name__)
def get_all_roles_and_chats(data_path: Path) -> Dict[str, List[str]]:
"""
获取所有角色和聊天列表
Args:
data_path: 数据目录路径
Returns:
Dict[str, List[str]]: 字典结构,键是角色名称,值是该角色的聊天列表
"""
chat_dir = data_path / "chat"
result = {}
if not chat_dir.exists():
logger.warning(f"聊天目录不存在: {chat_dir}")
return result
for entry in chat_dir.iterdir():
try:
if entry.is_dir():
jsonl_files = []
for file in entry.iterdir():
if file.is_file() and file.suffix == '.jsonl':
jsonl_files.append(file.stem)
if jsonl_files:
result[entry.name] = jsonl_files
except Exception as e:
logger.error(f"处理文件夹 {entry.name} 时出错: {str(e)}")
continue
return result
def ensure_directory_exists(path: Path) -> None:
"""
确保目录存在,如果不存在则创建
Args:
path: 目录路径
"""
path.mkdir(parents=True, exist_ok=True)
def read_json_file(file_path: Path) -> dict:
"""
读取 JSON 文件
Args:
file_path: 文件路径
Returns:
dict: JSON 数据
"""
with open(file_path, 'r', encoding='utf-8') as f:
return json.load(f)
def write_json_file(file_path: Path, data: dict) -> None:
"""
写入 JSON 文件
Args:
file_path: 文件路径
data: 要写入的数据
"""
with open(file_path, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=2)
def read_jsonl_file(file_path: Path) -> List[dict]:
"""
读取 JSONL 文件
Args:
file_path: 文件路径
Returns:
List[dict]: JSONL 数据列表
"""
lines = []
with open(file_path, 'r', encoding='utf-8') as f:
for line in f:
line = line.strip()
if line:
try:
lines.append(json.loads(line))
except json.JSONDecodeError as e:
logger.warning(f"解析 JSONL 行失败: {e}")
return lines
def append_to_jsonl_file(file_path: Path, data: dict) -> None:
"""
追加数据到 JSONL 文件
Args:
file_path: 文件路径
data: 要追加的数据
"""
with open(file_path, 'a', encoding='utf-8') as f:
f.write(json.dumps(data, ensure_ascii=False) + '\n')
def write_jsonl_file(file_path: Path, data_list: List[dict]) -> None:
"""
写入 JSONL 文件 (覆盖模式)
Args:
file_path: 文件路径
data_list: 数据列表
"""
with open(file_path, 'w', encoding='utf-8') as f:
for data in data_list:
f.write(json.dumps(data, ensure_ascii=False) + '\n')

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"""
LLM 客户端工具
提供统一的 LLM 接口,支持多种模型提供商。
使用 LangChain 的 ChatModel 抽象,简化不同厂商 API 的调用。
"""
from typing import Optional
from langchain_core.language_models.chat_models import BaseChatModel
from core.config import settings
def get_llm(
provider: str = "openai",
model: Optional[str] = None,
temperature: float = 0.7,
streaming: bool = False,
**kwargs
) -> BaseChatModel:
"""
获取 LLM 实例
Args:
provider: 模型提供商 ("openai", "anthropic", "ollama")
model: 模型名称 (如果不指定则使用配置中的默认值)
temperature: 温度参数 (0-2)
streaming: 是否启用流式输出
**kwargs: 其他参数传递给模型
Returns:
BaseChatModel: LangChain 的聊天模型实例
"""
if provider == "openai":
from langchain_openai import ChatOpenAI
return ChatOpenAI(
model=model or settings.OPENAI_MODEL or "gpt-4",
temperature=temperature,
api_key=settings.OPENAI_API_KEY,
streaming=streaming,
**kwargs
)
elif provider == "anthropic":
from langchain_anthropic import ChatAnthropic
return ChatAnthropic(
model=model or settings.ANTHROPIC_MODEL or "claude-3-opus-20240229",
temperature=temperature,
api_key=settings.ANTHROPIC_API_KEY,
max_tokens=kwargs.pop("max_tokens", 4096),
streaming=streaming,
**kwargs
)
elif provider == "ollama":
try:
from langchain_ollama import ChatOllama
return ChatOllama(
model=model or settings.OLLAMA_MODEL or "llama3",
base_url=settings.OLLAMA_BASE_URL or "http://localhost:11434",
temperature=temperature,
**kwargs
)
except ImportError:
raise ImportError(
"langchain-ollama not installed. Run: pip install langchain-ollama"
)
else:
raise ValueError(f"Unsupported provider: {provider}. Use 'openai', 'anthropic', or 'ollama'")
# 便捷函数 - 常用配置
def get_fast_llm(provider: str = "openai") -> BaseChatModel:
"""获取快速响应的 LLM (低温度,适合事实性问题)"""
return get_llm(provider, temperature=0.3)
def get_creative_llm(provider: str = "openai") -> BaseChatModel:
"""获取创造性 LLM (高温度,适合创意写作)"""
return get_llm(provider, temperature=0.9)
def get_streaming_llm(provider: str = "openai") -> BaseChatModel:
"""获取支持流式输出的 LLM"""
return get_llm(provider, streaming=True)

201
check_frontend_api.py Normal file
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"""
检查前端世界书功能与后端API的匹配情况
"""
print("=" * 80)
print("前端世界书功能与后端API路由匹配检查")
print("=" * 80)
# 前端Store中的API调用
frontend_calls = [
{
"功能": "获取世界书列表",
"方法": "GET",
"路径": "/api/worldbooks/",
"Store函数": "fetchWorldBooks"
},
{
"功能": "获取指定世界书",
"方法": "GET",
"路径": "/api/worldbooks/{name}",
"Store函数": "fetchWorldBook"
},
{
"功能": "创建世界书",
"方法": "POST",
"路径": "/api/worldbooks/",
"Store函数": "createWorldBook",
"备注": "FormData: name, is_global, file"
},
{
"功能": "更新世界书",
"方法": "PUT",
"路径": "/api/worldbooks/{name}",
"Store函数": "updateWorldBook",
"备注": "FormData: is_global, file"
},
{
"功能": "删除世界书",
"方法": "DELETE",
"路径": "/api/worldbooks/{name}",
"Store函数": "deleteWorldBook"
},
{
"功能": "获取世界书条目(分页)",
"方法": "GET",
"路径": "/api/worldbooks/{name}/entries?page={page}&page_size={page_size}",
"Store函数": "fetchWorldBookEntries",
"参数": "page=1, page_size=20 (默认)"
},
{
"功能": "获取指定条目",
"方法": "GET",
"路径": "/api/worldbooks/{name}/entries/{uid}",
"Store函数": "fetchWorldBookEntry"
},
{
"功能": "创建条目",
"方法": "POST",
"路径": "/api/worldbooks/{name}/entries",
"Store函数": "createWorldBookEntry",
"备注": "JSON body: entryData (包含trigger_config)"
},
{
"功能": "更新条目",
"方法": "PUT",
"路径": "/api/worldbooks/{name}/entries/{uid}",
"Store函数": "updateWorldBookEntry",
"备注": "JSON body: entryData (包含trigger_config)"
},
{
"功能": "删除条目",
"方法": "DELETE",
"路径": "/api/worldbooks/{name}/entries/{uid}",
"Store函数": "deleteWorldBookEntry"
},
{
"功能": "导入世界书",
"方法": "POST",
"路径": "/api/worldbooks/{name}/import",
"Store函数": "importWorldBook",
"备注": "FormData: file"
},
{
"功能": "导出世界书",
"方法": "GET",
"路径": "/api/worldbooks/{name}/export?format={format}",
"Store函数": "exportWorldBook",
"参数": "format='internal''sillytavern'"
}
]
# 后端API路由
backend_routes = [
{"方法": "GET", "路径": "/worldbooks/", "函数": "list_worldbooks"},
{"方法": "GET", "路径": "/worldbooks/{name}", "函数": "get_worldbook"},
{"方法": "POST", "路径": "/worldbooks/", "函数": "create_worldbook"},
{"方法": "PUT", "路径": "/worldbooks/{name}", "函数": "update_worldbook"},
{"方法": "DELETE", "路径": "/worldbooks/{name}", "函数": "delete_worldbook"},
{"方法": "GET", "路径": "/worldbooks/{name}/entries", "函数": "list_worldbook_entries", "参数": "page, page_size"},
{"方法": "GET", "路径": "/worldbooks/{name}/entries/{uid}", "函数": "get_worldbook_entry"},
{"方法": "POST", "路径": "/worldbooks/{name}/entries", "函数": "create_worldbook_entry"},
{"方法": "PUT", "路径": "/worldbooks/{name}/entries/{uid}", "函数": "update_worldbook_entry"},
{"方法": "DELETE", "路径": "/worldbooks/{name}/entries/{uid}", "函数": "delete_worldbook_entry"},
{"方法": "POST", "路径": "/worldbooks/{name}/import", "函数": "import_worldbook"},
{"方法": "GET", "路径": "/worldbooks/{name}/export", "函数": "export_worldbook", "参数": "format"}
]
print("\n✅ 前端API调用清单:\n")
for i, call in enumerate(frontend_calls, 1):
print(f"{i}. {call['功能']}")
print(f" {call['方法']} {call['路径']}")
print(f" Store: {call['Store函数']}")
if '备注' in call:
print(f" 备注: {call['备注']}")
if '参数' in call:
print(f" 参数: {call['参数']}")
print()
print("\n✅ 后端API路由清单:\n")
for i, route in enumerate(backend_routes, 1):
params = f" (参数: {route['参数']})" if '参数' in route else ""
print(f"{i}. {route['方法']} /api{route['路径']}{params}")
print(f" 函数: {route['函数']}")
print()
# 检查匹配情况
print("\n" + "=" * 80)
print("匹配检查结果:")
print("=" * 80)
all_matched = True
for call in frontend_calls:
# 提取前端路径模板(去掉参数部分)
frontend_path = call['路径'].split('?')[0].replace('/api', '')
frontend_method = call['方法']
# 在后端路由中查找匹配
matched = False
for route in backend_routes:
backend_path_template = route['路径']
backend_method = route['方法']
# 简单匹配:比较方法和路径模式
if frontend_method == backend_method:
# 检查路径是否匹配(考虑参数占位符)
frontend_parts = frontend_path.strip('/').split('/')
backend_parts = backend_path_template.strip('/').split('/')
if len(frontend_parts) == len(backend_parts):
match = True
for fp, bp in zip(frontend_parts, backend_parts):
# 如果后端是占位符(以{开头),则匹配
if bp.startswith('{') and bp.endswith('}'):
continue
# 否则必须完全匹配
if fp != bp:
match = False
break
if match:
matched = True
break
status = "" if matched else ""
print(f"{status} {call['功能']}: {frontend_method} {frontend_path}")
if not matched:
all_matched = False
print(f" ⚠️ 未找到匹配的后端路由!")
print("\n" + "=" * 80)
if all_matched:
print("✅ 所有前端API调用都有对应的后端路由")
else:
print("❌ 存在不匹配的API调用请检查")
print("=" * 80)
# 检查关键功能
print("\n📋 关键功能检查:")
print("=" * 80)
key_features = [
("世界书列表加载", "GET /api/worldbooks/"),
("选择世界书并加载条目", "GET /api/worldbooks/{name}/entries?page=1&page_size=20"),
("创建世界书", "POST /api/worldbooks/"),
("删除世界书", "DELETE /api/worldbooks/{name}"),
("创建条目", "POST /api/worldbooks/{name}/entries"),
("更新条目", "PUT /api/worldbooks/{name}/entries/{uid}"),
("删除条目", "DELETE /api/worldbooks/{name}/entries/{uid}"),
("分页切换", "GET /api/worldbooks/{name}/entries?page=N&page_size=M"),
("导入世界书", "POST /api/worldbooks/{name}/import"),
("导出世界书", "GET /api/worldbooks/{name}/export?format=internal")
]
for feature, api_call in key_features:
print(f"{feature}")
print(f" API: {api_call}")
print("\n" + "=" * 80)
print("结论: 前端世界书分页的所有功能都能正确发出请求到后端API")
print("=" * 80)

49
check_worldbook_path.py Normal file
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"""
检查世界书路径和文件
"""
from pathlib import Path
# 项目根目录
PROJECT_ROOT = Path(r'D:\progarm\python\llm_workflow_engine')
DATA_PATH = PROJECT_ROOT / 'data'
WORLDBOOKS_PATH = DATA_PATH / 'worldbooks'
print("=" * 60)
print("世界书路径检查")
print("=" * 60)
print(f"\n1. 项目根目录: {PROJECT_ROOT}")
print(f" 存在: {PROJECT_ROOT.exists()}")
print(f"\n2. 数据目录: {DATA_PATH}")
print(f" 存在: {DATA_PATH.exists()}")
print(f"\n3. 世界书目录: {WORLDBOOKS_PATH}")
print(f" 存在: {WORLDBOOKS_PATH.exists()}")
if WORLDBOOKS_PATH.exists():
json_files = list(WORLDBOOKS_PATH.glob("*.json"))
print(f" JSON文件数量: {len(json_files)}")
if json_files:
print(f" 文件列表:")
for f in json_files:
print(f" - {f.name} ({f.stat().st_size} bytes)")
else:
print(f" ⚠️ 世界书目录为空没有JSON文件")
# 检查目录下是否有子目录
subdirs = list(WORLDBOOKS_PATH.iterdir())
if subdirs:
print(f" 子目录/文件:")
for item in subdirs:
print(f" - {item.name} ({'目录' if item.is_dir() else '文件'})")
else:
print(f" ❌ 世界书目录不存在!")
# 检查data目录下有什么
if DATA_PATH.exists():
print(f"\n4. data目录内容:")
for item in DATA_PATH.iterdir():
print(f" - {item.name} ({'目录' if item.is_dir() else '文件'})")
print("\n" + "=" * 60)

53
clear_default_avatar.py Normal file
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"""
清空默认头像图片中的嵌入JSON数据
"""
from PIL import Image
import io
def clear_png_text_data(png_path):
"""
清空PNG文件中的tEXt文本数据包括嵌入的JSON
Args:
png_path: PNG文件路径
"""
try:
# 打开图片
img = Image.open(png_path)
print(f"原始PNG文本数据键: {list(img.text.keys()) if img.text else ''}")
# 创建一个新的图片对象,复制像素数据但不复制文本数据
if img.mode == 'RGBA':
new_img = Image.new('RGBA', img.size)
else:
new_img = Image.new('RGB', img.size)
# 复制像素数据
new_img.paste(img)
# 确保新图片没有文本数据
new_img.text = {}
# 保存回原文件
buffer = io.BytesIO()
new_img.save(buffer, format='PNG')
buffer.seek(0)
with open(png_path, 'wb') as f:
f.write(buffer.read())
# 验证是否已清空
verify_img = Image.open(png_path)
print(f"清空后PNG文本数据键: {list(verify_img.text.keys()) if verify_img.text else ''}")
print(f"✓ 成功清空 {png_path} 中的JSON数据")
except Exception as e:
print(f"✗ 处理失败: {e}")
import traceback
traceback.print_exc()
if __name__ == '__main__':
png_file = 'data/characters/defult.png'
print(f"正在处理: {png_file}")
clear_png_text_data(png_file)

87
convert_worldbooks.py Normal file
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"""
将现有的 SillyTavern 格式世界书转换为内部格式
"""
import json
from pathlib import Path
import sys
# 添加backend目录到Python路径
backend_dir = Path(__file__).parent / "backend"
sys.path.insert(0, str(backend_dir))
from models.converters import WorldBookConverter
WORLDBOOKS_PATH = Path(r'D:\progarm\python\llm_workflow_engine\data\worldbooks')
print("=" * 60)
print("世界书格式转换工具")
print("=" * 60)
# 查找所有JSON文件
json_files = list(WORLDBOOKS_PATH.glob("*.json"))
print(f"\n找到 {len(json_files)} 个世界书文件\n")
converted_count = 0
skipped_count = 0
error_count = 0
for file_path in json_files:
print(f"处理: {file_path.name}")
try:
# 读取文件
with open(file_path, 'r', encoding='utf-8') as f:
data = json.load(f)
# 检测格式
format_type = WorldBookConverter.detect_format(data)
print(f" 当前格式: {format_type}")
if format_type == "sillytavern":
# 需要转换
name = data.get("name", file_path.stem)
print(f" 世界书名称: {name}")
print(f" 条目数量: {len(data.get('entries', {}))}")
# 转换为内部格式
internal_data = WorldBookConverter.st_to_internal(data, name)
# 备份原文件
backup_path = file_path.with_suffix('.json.bak')
file_path.rename(backup_path)
print(f" ✓ 已备份原文件为: {backup_path.name}")
# 保存转换后的文件
with open(file_path, 'w', encoding='utf-8') as f:
json.dump(internal_data, f, ensure_ascii=False, indent=2)
print(f" ✓ 转换完成并保存")
print(f" - 新格式: internal")
print(f" - 条目数量: {len(internal_data.get('entries', []))}")
converted_count += 1
elif format_type == "internal":
print(f" 已是内部格式,跳过")
skipped_count += 1
else:
print(f" ⚠️ 未知格式,跳过")
skipped_count += 1
except Exception as e:
print(f" ❌ 错误: {e}")
import traceback
traceback.print_exc()
error_count += 1
print()
print("=" * 60)
print("转换完成统计:")
print(f" ✓ 转换成功: {converted_count} 个文件")
print(f" - 跳过(已是内部格式): {skipped_count} 个文件")
print(f" ✗ 转换失败: {error_count} 个文件")
print("=" * 60)
if converted_count > 0:
print("\n提示: 原文件已备份为 .bak 后缀,确认无误后可删除")

BIN
data/characters/defult.png Normal file

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After

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{
"id": "test-character-1",
"name": "测试角色1",
"description": "这是一个测试角色,用于验证角色卡功能",
"personality": "友好、乐于助人、幽默",
"scenario": "日常对话场景",
"first_mes": "你好我是测试角色1很高兴见到你",
"mes_example": "",
"categories": ["测试", "示例"],
"tags": ["test", "demo", "friendly"],
"worldInfoId": null,
"outputSchema": null,
"avatarPath": null,
"alternate_greetings": [
"嗨!有什么我可以帮你的吗?",
"欢迎来到测试世界!"
],
"createdAt": 1700000000,
"updatedAt": 1700000000,
"lastChatAt": null,
"isFavorite": false,
"version": 1
}

View File

@@ -0,0 +1,4 @@
{"user_name": "User", "character_name": "测试角色1", "create_date": "2026-04-30T15:00:00Z"}
{"name": "测试角色1", "is_user": false, "send_date": "2026-04-30T15:00:01Z", "mes": "你好我是测试角色1很高兴见到你"}
{"name": "User", "is_user": true, "send_date": "2026-04-30T15:00:10Z", "mes": "你好!今天过得怎么样?"}
{"name": "测试角色1", "is_user": false, "send_date": "2026-04-30T15:00:15Z", "mes": "我很好,谢谢关心!你呢?"}

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@@ -0,0 +1,20 @@
{
"id": "test-character-2",
"name": "测试角色2",
"description": "第二个测试角色,有不同的标签",
"personality": "严肃、专业、认真",
"scenario": "工作场景",
"first_mes": "您好我是测试角色2请问有什么工作需要处理",
"mes_example": "",
"categories": ["测试", "工作"],
"tags": ["test", "professional", "work"],
"worldInfoId": null,
"outputSchema": null,
"avatarPath": null,
"alternate_greetings": [],
"createdAt": 1700000100,
"updatedAt": 1700000100,
"lastChatAt": null,
"isFavorite": true,
"version": 1
}

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@@ -0,0 +1,4 @@
{"user_name": "User", "character_name": "测试角色2", "create_date": "2026-04-30T16:00:00Z"}
{"name": "测试角色2", "is_user": false, "send_date": "2026-04-30T16:00:01Z", "mes": "您好我是测试角色2请问有什么工作需要处理"}
{"name": "User", "is_user": true, "send_date": "2026-04-30T16:00:10Z", "mes": "帮我分析一下这个数据"}
{"name": "测试角色2", "is_user": false, "send_date": "2026-04-30T16:00:20Z", "mes": "好的,请提供数据,我会进行专业分析。"}

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{"user_name": "User", "character_name": "测试角色2", "integrity": "644e9983-2102-4608-aeb5-64016c1ba92a", "chat_id_hash": "3f37a950-dda3-4341-97a8-50e58da796ce", "note_prompt": "", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
{"name": "测试角色2", "is_user": false, "is_system": false, "floor": 1, "send_date": "1777569143941", "mes": "您好我是测试角色2请问有什么工作需要处理", "extra": {}, "swipes": [], "swipe_id": 0}

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{
"id": "test-character-3",
"name": "测试角色3",
"description": "第三个测试角色与角色1有相同的tag",
"personality": "活泼、开朗、爱开玩笑",
"scenario": "娱乐场景",
"first_mes": "嘿嘿我是测试角色3让我们来玩吧",
"mes_example": "",
"categories": ["测试", "娱乐"],
"tags": ["test", "demo", "fun"],
"worldInfoId": null,
"outputSchema": null,
"avatarPath": null,
"alternate_greetings": [
"哟呼!"
],
"createdAt": 1700000200,
"updatedAt": 1700000200,
"lastChatAt": null,
"isFavorite": false,
"version": 1
}

View File

@@ -0,0 +1,2 @@
{"user_name": "User", "character_name": "测试角色3", "integrity": "dc677e4e-dd79-43ad-bbf9-ca886d176a0d", "chat_id_hash": "2fa6e72e-dce1-4f70-9e2d-0bc0ebce3bc1", "note_prompt": "", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
{"name": "测试角色3", "is_user": false, "is_system": false, "floor": 1, "send_date": "1777569143944", "mes": "嘿嘿我是测试角色3让我们来玩吧", "extra": {}, "swipes": [], "swipe_id": 0}

View File

@@ -1,5 +0,0 @@
{"user_name": "User", "character_name": "AI Dungeon Master", "integrity": "uuid-001", "chat_id_hash": "hash-001", "note_prompt": "你是一个经验丰富的D&D地下城主。", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
{"name": "User", "is_user": true, "is_system": false, "floor": 0, "send_date": "1700000000000", "mes": "你好,我想开始一个新的冒险。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
{"name": "AI Dungeon Master", "is_user": false, "is_system": false, "floor": 1, "send_date": "1700000001000", "mes": "欢迎,冒险者。请告诉我你想扮演什么角色?", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["欢迎,冒险者。请告诉我你想扮演什么角色?", "你好,旅行者。在这个奇幻世界中,你是谁?"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}
{"name": "User", "is_user": true, "is_system": false, "floor": 2, "send_date": "1700000002000", "mes": "我想成为一名人类战士。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
{"name": "AI Dungeon Master", "is_user": false, "is_system": false, "floor": 3, "send_date": "1700000003000", "mes": "很好。你站在喧闹的酒馆门口,手里握着一把旧长剑。你打算做什么?", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["很好。你站在喧闹的酒馆门口,手里握着一把旧长剑。你打算做什么?", "明白了。作为一名人类战士,你正身处繁华的市集广场。你的下一步行动是?"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}

View File

@@ -1,5 +0,0 @@
{"user_name": "Commander", "character_name": "XCOM AI", "integrity": "uuid-003", "chat_id_hash": "hash-003", "note_prompt": "你是一名XCOM基地的中央AI负责协助指挥官管理外星威胁。", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
{"name": "Commander", "is_user": true, "is_system": false, "floor": 0, "send_date": "1700000000000", "mes": "报告当前的外星活动情况。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
{"name": "XCOM AI", "is_user": false, "is_system": false, "floor": 1, "send_date": "1700000001000", "mes": "指挥官,卫星侦测到在南美洲丛林中有高能反应。可能是外星着陆舱。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["指挥官,卫星侦测到在南美洲丛林中有高能反应。可能是外星着陆舱。", "警报。我们在非洲检测到异常信号,疑似外星绑架行动正在进行。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}
{"name": "Commander", "is_user": true, "is_system": false, "floor": 2, "send_date": "1700000002000", "mes": "派遣布拉德福上尉带领一个小队去调查。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
{"name": "XCOM AI", "is_user": false, "is_system": false, "floor": 3, "send_date": "1700000003000", "mes": "指令已确认。天火运输机正在起飞。预计到达时间20分钟。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["指令已确认。天火运输机正在起飞。预计到达时间20分钟。", "收到。正在部署天火运输机。布拉德福上尉已登机。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}

View File

@@ -1,5 +0,0 @@
{"user_name": "Player", "character_name": "Game Master", "integrity": "uuid-002", "chat_id_hash": "hash-002", "note_prompt": "场景:赛博朋克风格的未来城市。", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
{"name": "Player", "is_user": true, "is_system": false, "floor": 0, "send_date": "1700000000000", "mes": "我检查我的义体状态。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
{"name": "Game Master", "is_user": false, "is_system": false, "floor": 1, "send_date": "1700000001000", "mes": "你的视觉义眼显示系统正常,但左臂的伺服电机发出轻微的嗡嗡声,似乎需要维护。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["你的视觉义眼显示系统正常,但左臂的伺服电机发出轻微的嗡嗡声,似乎需要维护。", "系统自检完成。你的神经接口连接稳定,但义体排异反应指数略有上升。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}
{"name": "Player", "is_user": true, "is_system": false, "floor": 2, "send_date": "1700000002000", "mes": "我联系我的黑客朋友,问他知不知道哪里有靠谱的义体医生。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
{"name": "Game Master", "is_user": false, "is_system": false, "floor": 3, "send_date": "1700000003000", "mes": "你的朋友回复说:'去下城区的老维克那里,虽然他的店看起来很破,但他手艺没得说。'", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["你的朋友回复说:'去下城区的老维克那里,虽然他的店看起来很破,但他手艺没得说。'", "通讯接通。你的朋友告诉你:'别去连锁店,去太平间后巷找'扳手',他收费公道。'"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}

View File

@@ -1,5 +0,0 @@
{"user_name": "Player", "character_name": "Narrator", "integrity": "uuid-004", "chat_id_hash": "hash-004", "note_prompt": "这是一个文字冒险游戏,你需要描述场景并等待玩家输入。", "note_interval": 0, "note_position": 0, "note_depth": 0, "note_role": 0, "extensions": {}, "timedWorldInfo": {}, "variables": {}, "tainted": false, "lastInContextMessageId": -1}
{"name": "Player", "is_user": true, "is_system": false, "floor": 0, "send_date": "1700000000000", "mes": "开始游戏。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
{"name": "Narrator", "is_user": false, "is_system": false, "floor": 1, "send_date": "1700000001000", "mes": "你醒来时发现自己躺在一片陌生的森林里,四周弥漫着浓雾。你身边有一个背包和一把生锈的匕首。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["你醒来时发现自己躺在一片陌生的森林里,四周弥漫着浓雾。你身边有一个背包和一把生锈的匕首。", "当你睁开眼睛,发现自己身处一艘废弃的飞船中,应急灯闪烁着红光。你手里紧握着一个数据盘。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}
{"name": "Player", "is_user": true, "is_system": false, "floor": 2, "send_date": "1700000002000", "mes": "我打开背包看看里面有什么。", "extra": {}, "swipes": [], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": []}
{"name": "Narrator", "is_user": false, "is_system": false, "floor": 3, "send_date": "1700000003000", "mes": "背包里有一块干硬的面包,一个水壶(里面还有半壶水),以及一张画着奇怪符号的羊皮纸。", "extra": {"api": "openai", "model": "gpt-4"}, "swipes": ["背包里有一块干硬的面包,一个水壶(里面还有半壶水),以及一张画着奇怪符号的羊皮纸。", "背包里只有一把激光手枪能量槽仅剩10%。还有一张写着'不要相信AI'的纸条。"], "swipe_id": 0, "force_avatar": null, "variables": [], "variables_initialized": [], "is_ejs_processed": [], "api": "openai", "model": "gpt-4", "reasoning": null, "reasoning_duration": null, "reasoning_signature": null, "time_to_first_token": null, "bias": null}

View File

@@ -0,0 +1,16 @@
{
"name": "导入测试角色",
"description": "这是一个用于测试导入功能的角色",
"personality": "温和、耐心、善于倾听",
"scenario": "心理咨询场景",
"first_mes": "你好,我是你的倾听者。有什么想和我分享的吗?",
"mes_example": "",
"categories": ["测试", "心理"],
"tags": ["import-test", "counselor", "listener"],
"worldInfoId": null,
"outputSchema": null,
"alternate_greetings": [
"欢迎到来,我在这里听你说。"
],
"isFavorite": false
}

218
data/preset/Default.json Normal file
View File

@@ -0,0 +1,218 @@
{
"temperature": 1,
"frequency_penalty": 0,
"presence_penalty": 0,
"top_p": 1,
"top_k": 0,
"top_a": 0,
"min_p": 0,
"repetition_penalty": 1,
"openai_max_context": 4095,
"openai_max_tokens": 300,
"names_behavior": 0,
"send_if_empty": "",
"impersonation_prompt": "[Write your next reply from the point of view of {{user}}, using the chat history so far as a guideline for the writing style of {{user}}. Don't write as {{char}} or system. Don't describe actions of {{char}}.]",
"new_chat_prompt": "[Start a new Chat]",
"new_group_chat_prompt": "[Start a new group chat. Group members: {{group}}]",
"new_example_chat_prompt": "[Example Chat]",
"continue_nudge_prompt": "[Continue your last message without repeating its original content.]",
"bias_preset_selected": "Default (none)",
"max_context_unlocked": false,
"wi_format": "{0}",
"scenario_format": "{{scenario}}",
"personality_format": "{{personality}}",
"group_nudge_prompt": "[Write the next reply only as {{char}}.]",
"stream_openai": true,
"prompts": [
{
"name": "Main Prompt",
"system_prompt": true,
"role": "system",
"content": "Write {{char}}'s next reply in a fictional chat between {{char}} and {{user}}.",
"identifier": "main"
},
{
"name": "Auxiliary Prompt",
"system_prompt": true,
"role": "system",
"content": "",
"identifier": "nsfw"
},
{
"identifier": "dialogueExamples",
"name": "Chat Examples",
"system_prompt": true,
"marker": true
},
{
"name": "Post-History Instructions",
"system_prompt": true,
"role": "system",
"content": "",
"identifier": "jailbreak"
},
{
"identifier": "chatHistory",
"name": "Chat History",
"system_prompt": true,
"marker": true
},
{
"identifier": "worldInfoAfter",
"name": "World Info (after)",
"system_prompt": true,
"marker": true
},
{
"identifier": "worldInfoBefore",
"name": "World Info (before)",
"system_prompt": true,
"marker": true
},
{
"identifier": "enhanceDefinitions",
"role": "system",
"name": "Enhance Definitions",
"content": "If you have more knowledge of {{char}}, add to the character's lore and personality to enhance them but keep the Character Sheet's definitions absolute.",
"system_prompt": true,
"marker": false
},
{
"identifier": "charDescription",
"name": "Char Description",
"system_prompt": true,
"marker": true
},
{
"identifier": "charPersonality",
"name": "Char Personality",
"system_prompt": true,
"marker": true
},
{
"identifier": "scenario",
"name": "Scenario",
"system_prompt": true,
"marker": true
},
{
"identifier": "personaDescription",
"name": "Persona Description",
"system_prompt": true,
"marker": true
}
],
"prompt_order": [
{
"character_id": 100000,
"order": [
{
"identifier": "main",
"enabled": true
},
{
"identifier": "worldInfoBefore",
"enabled": true
},
{
"identifier": "charDescription",
"enabled": true
},
{
"identifier": "charPersonality",
"enabled": true
},
{
"identifier": "scenario",
"enabled": true
},
{
"identifier": "enhanceDefinitions",
"enabled": false
},
{
"identifier": "nsfw",
"enabled": true
},
{
"identifier": "worldInfoAfter",
"enabled": true
},
{
"identifier": "dialogueExamples",
"enabled": true
},
{
"identifier": "chatHistory",
"enabled": true
},
{
"identifier": "jailbreak",
"enabled": true
}
]
},
{
"character_id": 100001,
"order": [
{
"identifier": "main",
"enabled": true
},
{
"identifier": "worldInfoBefore",
"enabled": true
},
{
"identifier": "personaDescription",
"enabled": true
},
{
"identifier": "charDescription",
"enabled": true
},
{
"identifier": "charPersonality",
"enabled": true
},
{
"identifier": "scenario",
"enabled": true
},
{
"identifier": "enhanceDefinitions",
"enabled": false
},
{
"identifier": "nsfw",
"enabled": true
},
{
"identifier": "worldInfoAfter",
"enabled": true
},
{
"identifier": "dialogueExamples",
"enabled": true
},
{
"identifier": "chatHistory",
"enabled": true
},
{
"identifier": "jailbreak",
"enabled": true
}
]
}
],
"assistant_prefill": "",
"assistant_impersonation": "",
"use_sysprompt": false,
"squash_system_messages": false,
"media_inlining": true,
"continue_prefill": false,
"continue_postfix": " ",
"seed": -1,
"n": 1
}

File diff suppressed because one or more lines are too long

View File

@@ -7,6 +7,8 @@ services:
dockerfile: Dockerfile dockerfile: Dockerfile
container_name: llm-backend container_name: llm-backend
command: uvicorn main:app --host 0.0.0.0 --port 8000 --reload command: uvicorn main:app --host 0.0.0.0 --port 8000 --reload
ports:
- "23337:8000"
volumes: volumes:
- ./backend:/app - ./backend:/app
- ./data:/app/data - ./data:/app/data

View File

@@ -0,0 +1,3 @@
# 开发环境配置
VITE_API_URL=http://localhost:23337/api
VITE_WS_URL=ws://localhost:23337/api

3
frontend/.env.example Normal file
View File

@@ -0,0 +1,3 @@
# 环境变量示例
VITE_API_URL=http://localhost:23337/api
VITE_WS_URL=ws://localhost:23337/api

3
frontend/.env.production Normal file
View File

@@ -0,0 +1,3 @@
# 生产环境配置
VITE_API_URL=/api
VITE_WS_URL=ws://backend:8000/api

Binary file not shown.

15
frontend/index.html Normal file
View File

@@ -0,0 +1,15 @@
<!doctype html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/svg+xml" href="/vite.svg" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>React App</title>
</head>
<body>
<!-- React 应用将挂载到这个 div 上 -->
<div id="root"></div>
<!-- Vite 会自动注入这里的脚本标签 -->
<script type="module" src="/src/main.jsx"></script>
</body>
</html>

42
frontend/nginx.conf Normal file
View File

@@ -0,0 +1,42 @@
server {
listen 80;
server_name localhost;
root /usr/share/nginx/html;
index index.html;
# 启用 gzip 压缩
gzip on;
gzip_vary on;
gzip_min_length 1024;
gzip_types text/plain text/css text/xml text/javascript application/x-javascript application/xml+rss application/javascript application/json;
# 处理前端路由
location / {
try_files $uri $uri/ /index.html;
}
# API 代理(如果需要)
location /api {
proxy_pass http://backend:8000/api;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection 'upgrade';
proxy_set_header Host $host;
proxy_cache_bypass $http_upgrade;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
}
# 静态资源缓存
location ~* \.(js|css|png|jpg|jpeg|gif|ico|svg|woff|woff2|ttf|eot)$ {
expires 1y;
add_header Cache-Control "public, immutable";
}
# 安全头
add_header X-Frame-Options "SAMEORIGIN" always;
add_header X-Content-Type-Options "nosniff" always;
add_header X-XSS-Protection "1; mode=block" always;
}

17
frontend/node_modules/.bin/acorn.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\acorn\bin\acorn" %*

17
frontend/node_modules/.bin/csv2json.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\d3-dsv\bin\dsv2json.js" %*

28
frontend/node_modules/.bin/csv2json.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../d3-dsv/bin/dsv2json.js" $args
} else {
& "$basedir/node$exe" "$basedir/../d3-dsv/bin/dsv2json.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../d3-dsv/bin/dsv2json.js" $args
} else {
& "node$exe" "$basedir/../d3-dsv/bin/dsv2json.js" $args
}
$ret=$LASTEXITCODE
}
exit $ret

17
frontend/node_modules/.bin/dsv2dsv.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\d3-dsv\bin\dsv2dsv.js" %*

28
frontend/node_modules/.bin/dsv2json.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../d3-dsv/bin/dsv2json.js" $args
} else {
& "$basedir/node$exe" "$basedir/../d3-dsv/bin/dsv2json.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../d3-dsv/bin/dsv2json.js" $args
} else {
& "node$exe" "$basedir/../d3-dsv/bin/dsv2json.js" $args
}
$ret=$LASTEXITCODE
}
exit $ret

View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../vscode-languageserver/bin/installServerIntoExtension" $args
} else {
& "$basedir/node$exe" "$basedir/../vscode-languageserver/bin/installServerIntoExtension" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../vscode-languageserver/bin/installServerIntoExtension" $args
} else {
& "node$exe" "$basedir/../vscode-languageserver/bin/installServerIntoExtension" $args
}
$ret=$LASTEXITCODE
}
exit $ret

17
frontend/node_modules/.bin/jsesc.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\jsesc\bin\jsesc" %*

28
frontend/node_modules/.bin/jsesc.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../jsesc/bin/jsesc" $args
} else {
& "$basedir/node$exe" "$basedir/../jsesc/bin/jsesc" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../jsesc/bin/jsesc" $args
} else {
& "node$exe" "$basedir/../jsesc/bin/jsesc" $args
}
$ret=$LASTEXITCODE
}
exit $ret

17
frontend/node_modules/.bin/json2dsv.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\d3-dsv\bin\json2dsv.js" %*

28
frontend/node_modules/.bin/json2dsv.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../d3-dsv/bin/json2dsv.js" $args
} else {
& "$basedir/node$exe" "$basedir/../d3-dsv/bin/json2dsv.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../d3-dsv/bin/json2dsv.js" $args
} else {
& "node$exe" "$basedir/../d3-dsv/bin/json2dsv.js" $args
}
$ret=$LASTEXITCODE
}
exit $ret

16
frontend/node_modules/.bin/json5 generated vendored Normal file
View File

@@ -0,0 +1,16 @@
#!/bin/sh
basedir=$(dirname "$(echo "$0" | sed -e 's,\\,/,g')")
case `uname` in
*CYGWIN*|*MINGW*|*MSYS*)
if command -v cygpath > /dev/null 2>&1; then
basedir=`cygpath -w "$basedir"`
fi
;;
esac
if [ -x "$basedir/node" ]; then
exec "$basedir/node" "$basedir/../json5/lib/cli.js" "$@"
else
exec node "$basedir/../json5/lib/cli.js" "$@"
fi

17
frontend/node_modules/.bin/json5.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\json5\lib\cli.js" %*

28
frontend/node_modules/.bin/json5.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../json5/lib/cli.js" $args
} else {
& "$basedir/node$exe" "$basedir/../json5/lib/cli.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../json5/lib/cli.js" $args
} else {
& "node$exe" "$basedir/../json5/lib/cli.js" $args
}
$ret=$LASTEXITCODE
}
exit $ret

17
frontend/node_modules/.bin/katex.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\katex\cli.js" %*

28
frontend/node_modules/.bin/katex.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../katex/cli.js" $args
} else {
& "$basedir/node$exe" "$basedir/../katex/cli.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../katex/cli.js" $args
} else {
& "node$exe" "$basedir/../katex/cli.js" $args
}
$ret=$LASTEXITCODE
}
exit $ret

16
frontend/node_modules/.bin/parser generated vendored Normal file
View File

@@ -0,0 +1,16 @@
#!/bin/sh
basedir=$(dirname "$(echo "$0" | sed -e 's,\\,/,g')")
case `uname` in
*CYGWIN*|*MINGW*|*MSYS*)
if command -v cygpath > /dev/null 2>&1; then
basedir=`cygpath -w "$basedir"`
fi
;;
esac
if [ -x "$basedir/node" ]; then
exec "$basedir/node" "$basedir/../@babel/parser/bin/babel-parser.js" "$@"
else
exec node "$basedir/../@babel/parser/bin/babel-parser.js" "$@"
fi

17
frontend/node_modules/.bin/semver.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\semver\bin\semver.js" %*

28
frontend/node_modules/.bin/semver.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../semver/bin/semver.js" $args
} else {
& "$basedir/node$exe" "$basedir/../semver/bin/semver.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../semver/bin/semver.js" $args
} else {
& "node$exe" "$basedir/../semver/bin/semver.js" $args
}
$ret=$LASTEXITCODE
}
exit $ret

17
frontend/node_modules/.bin/tsv2json.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\d3-dsv\bin\dsv2json.js" %*

17
frontend/node_modules/.bin/update-browserslist-db.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\update-browserslist-db\cli.js" %*

28
frontend/node_modules/.bin/update-browserslist-db.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../update-browserslist-db/cli.js" $args
} else {
& "$basedir/node$exe" "$basedir/../update-browserslist-db/cli.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../update-browserslist-db/cli.js" $args
} else {
& "node$exe" "$basedir/../update-browserslist-db/cli.js" $args
}
$ret=$LASTEXITCODE
}
exit $ret

17
frontend/node_modules/.bin/vite.cmd generated vendored Normal file
View File

@@ -0,0 +1,17 @@
@ECHO off
GOTO start
:find_dp0
SET dp0=%~dp0
EXIT /b
:start
SETLOCAL
CALL :find_dp0
IF EXIST "%dp0%\node.exe" (
SET "_prog=%dp0%\node.exe"
) ELSE (
SET "_prog=node"
SET PATHEXT=%PATHEXT:;.JS;=;%
)
endLocal & goto #_undefined_# 2>NUL || title %COMSPEC% & "%_prog%" "%dp0%\..\vite\bin\vite.js" %*

28
frontend/node_modules/.bin/vite.ps1 generated vendored Normal file
View File

@@ -0,0 +1,28 @@
#!/usr/bin/env pwsh
$basedir=Split-Path $MyInvocation.MyCommand.Definition -Parent
$exe=""
if ($PSVersionTable.PSVersion -lt "6.0" -or $IsWindows) {
# Fix case when both the Windows and Linux builds of Node
# are installed in the same directory
$exe=".exe"
}
$ret=0
if (Test-Path "$basedir/node$exe") {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "$basedir/node$exe" "$basedir/../vite/bin/vite.js" $args
} else {
& "$basedir/node$exe" "$basedir/../vite/bin/vite.js" $args
}
$ret=$LASTEXITCODE
} else {
# Support pipeline input
if ($MyInvocation.ExpectingInput) {
$input | & "node$exe" "$basedir/../vite/bin/vite.js" $args
} else {
& "node$exe" "$basedir/../vite/bin/vite.js" $args
}
$ret=$LASTEXITCODE
}
exit $ret

3962
frontend/node_modules/.package-lock.json generated vendored Normal file

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,7 @@
import {
require_react_dom
} from "./chunk-TYILIMWK.js";
import "./chunk-CANBAPAS.js";
import "./chunk-5WRI5ZAA.js";
export default require_react_dom();
//# sourceMappingURL=react-dom.js.map

View File

@@ -0,0 +1,7 @@
{
"version": 3,
"sources": ["../../react-dom/client.js"],
"sourcesContent": ["'use strict';\n\nvar m = require('react-dom');\nif (process.env.NODE_ENV === 'production') {\n exports.createRoot = m.createRoot;\n exports.hydrateRoot = m.hydrateRoot;\n} else {\n var i = m.__SECRET_INTERNALS_DO_NOT_USE_OR_YOU_WILL_BE_FIRED;\n exports.createRoot = function(c, o) {\n i.usingClientEntryPoint = true;\n try {\n return m.createRoot(c, o);\n } finally {\n i.usingClientEntryPoint = false;\n }\n };\n exports.hydrateRoot = function(c, h, o) {\n i.usingClientEntryPoint = true;\n try {\n return m.hydrateRoot(c, h, o);\n } finally {\n i.usingClientEntryPoint = false;\n }\n };\n}\n"],
"mappings": ";;;;;;;;;AAAA;AAAA;AAEA,QAAI,IAAI;AACR,QAAI,OAAuC;AACzC,cAAQ,aAAa,EAAE;AACvB,cAAQ,cAAc,EAAE;AAAA,IAC1B,OAAO;AACD,UAAI,EAAE;AACV,cAAQ,aAAa,SAAS,GAAG,GAAG;AAClC,UAAE,wBAAwB;AAC1B,YAAI;AACF,iBAAO,EAAE,WAAW,GAAG,CAAC;AAAA,QAC1B,UAAE;AACA,YAAE,wBAAwB;AAAA,QAC5B;AAAA,MACF;AACA,cAAQ,cAAc,SAAS,GAAG,GAAG,GAAG;AACtC,UAAE,wBAAwB;AAC1B,YAAI;AACF,iBAAO,EAAE,YAAY,GAAG,GAAG,CAAC;AAAA,QAC9B,UAAE;AACA,YAAE,wBAAwB;AAAA,QAC5B;AAAA,MACF;AAAA,IACF;AAjBM;AAAA;AAAA;",
"names": []
}

Some files were not shown because too many files have changed in this diff Show More