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v2026.01.0
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v2026.01.0
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134
.github/copilot-instructions.md
vendored
134
.github/copilot-instructions.md
vendored
@@ -841,10 +841,136 @@ def add_math(paragraph, latex_str):
|
||||
omml = mathml2omml(mathml)
|
||||
# ... 插入 OMML 到 paragraph._element ...
|
||||
```
|
||||
- [ ] 更新 `README.md` 插件列表
|
||||
- [ ] 更新 `README_CN.md` 插件列表
|
||||
- [ ] 更新/创建 `docs/` 下的对应文档
|
||||
- [ ] 确保文档版本号与代码一致
|
||||
|
||||
### JS 渲染并嵌入 Markdown (JS Render to Markdown)
|
||||
|
||||
对于需要复杂前端渲染(如 AntV 图表、Mermaid 图表、ECharts)但希望结果**持久化为纯 Markdown 格式**的场景,推荐使用 Data URL 嵌入模式:
|
||||
|
||||
#### 工作流程
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────┐
|
||||
│ Plugin Workflow │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 1. Python Action │
|
||||
│ ├── 分析消息内容 │
|
||||
│ ├── 调用 LLM 生成结构化数据(可选) │
|
||||
│ └── 通过 __event_call__ 发送 JS 代码到前端 │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 2. Browser JS (via __event_call__) │
|
||||
│ ├── 动态加载可视化库(如 AntV、Mermaid) │
|
||||
│ ├── 离屏渲染 SVG/Canvas │
|
||||
│ ├── 使用 toDataURL() 导出 Base64 Data URL │
|
||||
│ └── 通过 REST API 更新消息内容 │
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||||
├─────────────────────────────────────────────────────────────┤
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||||
│ 3. Markdown 渲染 │
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||||
│ └── 显示  │
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||||
└─────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
#### 核心实现代码
|
||||
|
||||
**Python 端(发送 JS 执行):**
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||||
|
||||
```python
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||||
async def action(self, body, __event_call__, __metadata__, ...):
|
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chat_id = self._extract_chat_id(body, __metadata__)
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message_id = self._extract_message_id(body, __metadata__)
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||||
|
||||
# 生成 JS 代码
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||||
js_code = self._generate_js_code(
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chat_id=chat_id,
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||||
message_id=message_id,
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||||
data=processed_data, # 可视化所需数据
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||||
)
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||||
|
||||
# 执行 JS
|
||||
if __event_call__:
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||||
await __event_call__({
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||||
"type": "execute",
|
||||
"data": {"code": js_code}
|
||||
})
|
||||
```
|
||||
|
||||
**JavaScript 端(渲染并回写):**
|
||||
|
||||
```javascript
|
||||
(async function() {
|
||||
// 1. 动态加载可视化库
|
||||
if (typeof VisualizationLib === 'undefined') {
|
||||
await new Promise((resolve, reject) => {
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.example.com/lib.min.js';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
});
|
||||
}
|
||||
|
||||
// 2. 创建离屏容器
|
||||
const container = document.createElement('div');
|
||||
container.style.cssText = 'position:absolute;left:-9999px;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// 3. 渲染可视化
|
||||
const instance = new VisualizationLib({ container, ... });
|
||||
instance.render(data);
|
||||
|
||||
// 4. 导出为 Data URL
|
||||
const dataUrl = await instance.toDataURL({ type: 'svg', embedResources: true });
|
||||
// 或手动转换 SVG:
|
||||
// const svgData = new XMLSerializer().serializeToString(svgElement);
|
||||
// const base64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
// const dataUrl = "data:image/svg+xml;base64," + base64;
|
||||
|
||||
// 5. 清理
|
||||
instance.destroy();
|
||||
document.body.removeChild(container);
|
||||
|
||||
// 6. 生成 Markdown 图片
|
||||
const markdownImage = ``;
|
||||
|
||||
// 7. 通过 API 更新消息
|
||||
const token = localStorage.getItem("token");
|
||||
await fetch(`/api/v1/chats/${chatId}/messages/${messageId}/event`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${token}`
|
||||
},
|
||||
body: JSON.stringify({
|
||||
type: "chat:message",
|
||||
data: { content: originalContent + "\n\n" + markdownImage }
|
||||
})
|
||||
});
|
||||
})();
|
||||
```
|
||||
|
||||
#### 优势
|
||||
|
||||
- **纯 Markdown 输出**:结果是标准的 Markdown 图片语法,无需 HTML 代码块
|
||||
- **自包含**:图片以 Base64 Data URL 嵌入,无外部依赖
|
||||
- **持久化**:通过 API 回写,消息重新加载后图片仍然存在
|
||||
- **跨平台**:任何支持 Markdown 图片的客户端都能显示
|
||||
- **无服务端渲染依赖**:利用用户浏览器的渲染能力
|
||||
|
||||
#### 与 HTML 注入模式对比
|
||||
|
||||
| 特性 | HTML 注入 (`\`\`\`html`) | JS 渲染 + Markdown 图片 |
|
||||
|------|-------------------------|------------------------|
|
||||
| 输出格式 | HTML 代码块 | Markdown 图片 |
|
||||
| 交互性 | ✅ 支持按钮、动画 | ❌ 静态图片 |
|
||||
| 外部依赖 | 需要加载 JS 库 | 无(图片自包含) |
|
||||
| 持久化 | 依赖浏览器渲染 | ✅ 永久可见 |
|
||||
| 文件导出 | 需特殊处理 | ✅ 直接导出 |
|
||||
| 适用场景 | 交互式内容 | 信息图、图表快照 |
|
||||
|
||||
#### 参考实现
|
||||
|
||||
- `plugins/actions/js-render-poc/infographic_markdown.py` - AntV Infographic 生成并嵌入
|
||||
- `plugins/actions/js-render-poc/js_render_poc.py` - 基础概念验证
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
|
||||
54
.github/workflows/community-stats.yml
vendored
Normal file
54
.github/workflows/community-stats.yml
vendored
Normal file
@@ -0,0 +1,54 @@
|
||||
# OpenWebUI 社区统计报告自动生成
|
||||
# 每小时自动获取并更新社区统计数据
|
||||
|
||||
name: Community Stats
|
||||
|
||||
on:
|
||||
# 每小时整点运行
|
||||
schedule:
|
||||
- cron: '0 * * * *'
|
||||
# 手动触发
|
||||
workflow_dispatch:
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
jobs:
|
||||
update-stats:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
token: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
pip install requests python-dotenv
|
||||
|
||||
- name: Generate stats report
|
||||
env:
|
||||
OPENWEBUI_API_KEY: ${{ secrets.OPENWEBUI_API_KEY }}
|
||||
OPENWEBUI_USER_ID: ${{ secrets.OPENWEBUI_USER_ID }}
|
||||
run: |
|
||||
python scripts/openwebui_stats.py
|
||||
|
||||
- name: Check for changes
|
||||
id: check_changes
|
||||
run: |
|
||||
git diff --quiet docs/community-stats.md docs/community-stats.en.md README.md README_CN.md || echo "changed=true" >> $GITHUB_OUTPUT
|
||||
|
||||
- name: Commit and push changes
|
||||
if: steps.check_changes.outputs.changed == 'true'
|
||||
run: |
|
||||
git config --local user.email "github-actions[bot]@users.noreply.github.com"
|
||||
git config --local user.name "github-actions[bot]"
|
||||
git add docs/community-stats.md docs/community-stats.en.md docs/community-stats.json README.md README_CN.md
|
||||
git commit -m "📊 更新社区统计数据 $(date +'%Y-%m-%d')"
|
||||
git push
|
||||
48
README.md
48
README.md
@@ -4,7 +4,37 @@ English | [中文](./README_CN.md)
|
||||
|
||||
A collection of enhancements, plugins, and prompts for [OpenWebUI](https://github.com/open-webui/open-webui), developed and curated for personal use to extend functionality and improve experience.
|
||||
|
||||
[Contributing](./CONTRIBUTING.md)
|
||||
<!-- STATS_START -->
|
||||
## 📊 Community Stats
|
||||
|
||||
> 🕐 Auto-updated: 2026-01-06 19:26 (Beijing Time)
|
||||
|
||||
| 👤 Author | 👥 Followers | ⭐ Points | 🏆 Contributions |
|
||||
|:---:|:---:|:---:|:---:|
|
||||
| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **41** | **63** | **17** |
|
||||
|
||||
| 📝 Posts | ⬇️ Downloads | 👁️ Views | 👍 Upvotes | 💾 Saves |
|
||||
|:---:|:---:|:---:|:---:|:---:|
|
||||
| **11** | **785** | **8394** | **54** | **46** |
|
||||
| **11** | **785** | **8411** | **54** | **47** |
|
||||
|
||||
### 🔥 Top 5 Popular Plugins
|
||||
|
||||
| Rank | Plugin | Downloads | Views |
|
||||
|:---:|------|:---:|:---:|
|
||||
| 🥇 | [Turn Any Text into Beautiful Mind Maps](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 235 | 2095 |
|
||||
| 🥈 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 170 | 455 |
|
||||
| 🥉 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 112 | 1234 |
|
||||
| 4️⃣ | [Flash Card ](https://openwebui.com/posts/flash_card_65a2ea8f) | 75 | 1413 |
|
||||
| 5️⃣ | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 65 | 900 |
|
||||
| 🥇 | [Turn Any Text into Beautiful Mind Maps](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 235 | 2103 |
|
||||
| 🥈 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 170 | 456 |
|
||||
| 🥉 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 112 | 1235 |
|
||||
| 4️⃣ | [Flash Card ](https://openwebui.com/posts/flash_card_65a2ea8f) | 75 | 1414 |
|
||||
| 5️⃣ | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 65 | 904 |
|
||||
|
||||
*See full stats in [Community Stats Report](./docs/community-stats.md)*
|
||||
<!-- STATS_END -->
|
||||
|
||||
## 📦 Project Contents
|
||||
|
||||
@@ -60,10 +90,16 @@ This project is a collection of resources and does not require a Python environm
|
||||
|
||||
### Using Plugins
|
||||
|
||||
1. Browse the `/plugins` directory and download the plugin file (`.py`) you need.
|
||||
2. Go to OpenWebUI **Admin Panel** -> **Settings** -> **Plugins**.
|
||||
3. Click the upload button and select the `.py` file you just downloaded.
|
||||
4. Once uploaded, refresh the page to enable the plugin in your chat settings or toolbar.
|
||||
1. **Install from OpenWebUI Community (Recommended)**:
|
||||
- Visit my profile: [Fu-Jie's Profile](https://openwebui.com/u/Fu-Jie)
|
||||
- Browse the plugins and select the one you like.
|
||||
- Click "Get" to import it directly into your OpenWebUI instance.
|
||||
|
||||
2. **Manual Installation**:
|
||||
- Browse the `/plugins` directory and download the plugin file (`.py`) you need.
|
||||
- Go to OpenWebUI **Admin Panel** -> **Settings** -> **Plugins**.
|
||||
- Click the upload button and select the `.py` file you just downloaded.
|
||||
- Once uploaded, refresh the page to enable the plugin in your chat settings or toolbar.
|
||||
|
||||
### Contributing
|
||||
|
||||
@@ -71,3 +107,5 @@ If you have great prompts or plugins to share:
|
||||
1. Fork this repository.
|
||||
2. Add your files to the appropriate `prompts/` or `plugins/` directory.
|
||||
3. Submit a Pull Request.
|
||||
|
||||
[Contributing](./CONTRIBUTING.md)
|
||||
|
||||
83
README_CN.md
83
README_CN.md
@@ -2,7 +2,37 @@
|
||||
|
||||
[English](./README.md) | 中文
|
||||
|
||||
OpenWebUI 增强功能集合。包含个人开发与收集的### 🧩 插件 (Plugins)
|
||||
OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词等资源。
|
||||
|
||||
<!-- STATS_START -->
|
||||
## 📊 社区统计
|
||||
|
||||
> 🕐 自动更新于 2026-01-06 19:26 (北京时间)
|
||||
|
||||
| 👤 作者 | 👥 粉丝 | ⭐ 积分 | 🏆 贡献 |
|
||||
|:---:|:---:|:---:|:---:|
|
||||
| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **41** | **63** | **17** |
|
||||
|
||||
| 📝 发布 | ⬇️ 下载 | 👁️ 浏览 | 👍 点赞 | 💾 收藏 |
|
||||
|:---:|:---:|:---:|:---:|:---:|
|
||||
| **11** | **785** | **8394** | **54** | **46** |
|
||||
|
||||
### 🔥 热门插件 Top 5
|
||||
|
||||
| 排名 | 插件 | 下载 | 浏览 |
|
||||
|:---:|------|:---:|:---:|
|
||||
| 🥇 | [Turn Any Text into Beautiful Mind Maps](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 235 | 2095 |
|
||||
| 🥈 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 170 | 455 |
|
||||
| 🥉 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 112 | 1234 |
|
||||
| 4️⃣ | [Flash Card ](https://openwebui.com/posts/flash_card_65a2ea8f) | 75 | 1413 |
|
||||
| 5️⃣ | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 65 | 900 |
|
||||
|
||||
*完整统计请查看 [社区统计报告](./docs/community-stats.md)*
|
||||
<!-- STATS_END -->
|
||||
|
||||
## 📦 项目内容
|
||||
|
||||
### 🧩 插件 (Plugins)
|
||||
|
||||
位于 `plugins/` 目录,包含各类 Python 编写的功能增强插件:
|
||||
|
||||
@@ -19,7 +49,6 @@ OpenWebUI 增强功能集合。包含个人开发与收集的### 🧩 插件 (Pl
|
||||
- **Context Enhancement** (`context_enhancement_filter`): 上下文增强过滤器。
|
||||
- **Gemini Manifold Companion** (`gemini_manifold_companion`): Gemini Manifold 配套增强。
|
||||
|
||||
|
||||
#### Pipes (模型管道)
|
||||
- **Gemini Manifold** (`gemini_mainfold`): 集成 Gemini 模型的管道。
|
||||
|
||||
@@ -31,40 +60,10 @@ OpenWebUI 增强功能集合。包含个人开发与收集的### 🧩 插件 (Pl
|
||||
位于 `prompts/` 目录,包含精心调优的 System Prompts:
|
||||
|
||||
- **Coding**: 编程辅助类提示词。
|
||||
- **Marketing**: 营销文案类提示词。(`/prompts/marketing`): 内容创作、品牌策划、市场分析相关的提示词
|
||||
- **Marketing**: 营销文案类提示词。
|
||||
|
||||
每个提示词都独立保存为 Markdown 文件,可直接在 OpenWebUI 中使用。
|
||||
|
||||
### 🔧 插件 (Plugins)
|
||||
|
||||
{{ ... }}
|
||||
|
||||
[贡献指南](./CONTRIBUTING.md) | [更新日志](./CHANGELOG.md)
|
||||
|
||||
## 📦 项目内容
|
||||
|
||||
### 🎯 提示词 (Prompts)
|
||||
|
||||
位于 `/prompts` 目录,包含针对不同领域的优质提示词模板:
|
||||
|
||||
- **编程类** (`/prompts/coding`): 代码生成、调试、优化相关的提示词
|
||||
- **营销类** (`/prompts/marketing`): 内容创作、品牌策划、市场分析相关的提示词
|
||||
|
||||
每个提示词都独立保存为 Markdown 文件,可直接在 OpenWebUI 中使用。
|
||||
|
||||
### 🔧 插件 (Plugins)
|
||||
|
||||
位于 `/plugins` 目录,提供三种类型的插件扩展:
|
||||
|
||||
- **过滤器 (Filters)** - 在用户输入发送给 LLM 前进行处理和优化
|
||||
- 异步上下文压缩:智能压缩长上下文,优化 token 使用效率
|
||||
|
||||
- **动作 (Actions)** - 自定义功能,从聊天中触发
|
||||
- 思维导图生成:快速生成和导出思维导图
|
||||
|
||||
- **管道 (Pipes)** - 对 LLM 响应进行处理和增强
|
||||
- 各类响应处理和格式化插件
|
||||
|
||||
## 📖 开发文档
|
||||
|
||||
位于 `docs/zh/` 目录:
|
||||
@@ -73,7 +72,7 @@ OpenWebUI 增强功能集合。包含个人开发与收集的### 🧩 插件 (Pl
|
||||
- **[从问一个AI到运营一支AI团队](./docs/zh/从问一个AI到运营一支AI团队.md)** - 深度运营经验分享。
|
||||
|
||||
更多示例请查看 `docs/examples/` 目录。
|
||||
|
||||
|
||||
## 🚀 快速开始
|
||||
|
||||
本项目是一个资源集合,无需安装 Python 环境。你只需要下载对应的文件并导入到你的 OpenWebUI 实例中即可。
|
||||
@@ -87,10 +86,16 @@ OpenWebUI 增强功能集合。包含个人开发与收集的### 🧩 插件 (Pl
|
||||
|
||||
### 使用插件 (Plugins)
|
||||
|
||||
1. 在 `/plugins` 目录中浏览并下载你需要的插件文件 (`.py`)。
|
||||
2. 打开 OpenWebUI 的 **管理员面板 (Admin Panel)** -> **设置 (Settings)** -> **插件 (Plugins)**。
|
||||
3. 点击上传按钮,选择刚才下载的 `.py` 文件。
|
||||
4. 上传成功后,刷新页面,你就可以在聊天设置或工具栏中启用该插件了。
|
||||
1. **从 OpenWebUI 社区安装 (推荐)**:
|
||||
- 访问我的主页: [Fu-Jie's Profile](https://openwebui.com/u/Fu-Jie)
|
||||
- 浏览插件列表,选择你喜欢的插件。
|
||||
- 点击 "Get" 按钮,将其直接导入到你的 OpenWebUI 实例中。
|
||||
|
||||
2. **手动安装**:
|
||||
- 在 `/plugins` 目录中浏览并下载你需要的插件文件 (`.py`)。
|
||||
- 打开 OpenWebUI 的 **管理员面板 (Admin Panel)** -> **设置 (Settings)** -> **插件 (Plugins)**。
|
||||
- 点击上传按钮,选择刚才下载的 `.py` 文件。
|
||||
- 上传成功后,刷新页面,你就可以在聊天设置或工具栏中启用该插件了。
|
||||
|
||||
### 贡献代码
|
||||
|
||||
@@ -98,3 +103,5 @@ OpenWebUI 增强功能集合。包含个人开发与收集的### 🧩 插件 (Pl
|
||||
1. Fork 本仓库。
|
||||
2. 将你的文件添加到对应的 `prompts/` 或 `plugins/` 目录。
|
||||
3. 提交 Pull Request。
|
||||
|
||||
[贡献指南](./CONTRIBUTING.md) | [更新日志](./CHANGELOG.md)
|
||||
|
||||
35
docs/community-stats.en.md
Normal file
35
docs/community-stats.en.md
Normal file
@@ -0,0 +1,35 @@
|
||||
# 📊 OpenWebUI Community Stats Report
|
||||
|
||||
> 📅 Updated: 2026-01-06 11:08:23
|
||||
|
||||
## 📈 Overview
|
||||
|
||||
| Metric | Value |
|
||||
|------|------|
|
||||
| 📝 Total Posts | 11 |
|
||||
| ⬇️ Total Downloads | 785 |
|
||||
| 👁️ Total Views | 8394 |
|
||||
| 👍 Total Upvotes | 54 |
|
||||
| 💾 Total Saves | 46 |
|
||||
| 💬 Total Comments | 13 |
|
||||
|
||||
## 📂 By Type
|
||||
|
||||
- **action**: 9
|
||||
- **filter**: 2
|
||||
|
||||
## 📋 Posts List
|
||||
|
||||
| Rank | Title | Type | Version | Downloads | Views | Upvotes | Saves | Updated |
|
||||
|:---:|------|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
|
||||
| 1 | [Turn Any Text into Beautiful Mind Maps](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.8.2 | 235 | 2095 | 10 | 15 | 2026-01-03 |
|
||||
| 2 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.6 | 170 | 455 | 3 | 3 | 2026-01-03 |
|
||||
| 3 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter | 1.1.0 | 112 | 1234 | 5 | 9 | 2025-12-31 |
|
||||
| 4 | [Flash Card ](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 75 | 1413 | 8 | 5 | 2026-01-03 |
|
||||
| 5 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.3.2 | 65 | 900 | 6 | 7 | 2026-01-03 |
|
||||
| 6 | [Export to Word (Enhanced Formatting)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.0 | 51 | 499 | 5 | 4 | 2026-01-05 |
|
||||
| 7 | [智能信息图](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.3.1 | 33 | 397 | 3 | 0 | 2025-12-29 |
|
||||
| 8 | [智能生成交互式思维导图,帮助用户可视化知识](https://openwebui.com/posts/智能生成交互式思维导图帮助用户可视化知识_8d4b097b) | action | 0.8.0 | 14 | 246 | 2 | 0 | 2025-12-31 |
|
||||
| 9 | [导出为 Word-支持公式、流程图、表格和代码块](https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0) | action | 0.4.1 | 13 | 737 | 7 | 1 | 2026-01-05 |
|
||||
| 10 | [闪记卡生成插件](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.2 | 12 | 309 | 3 | 1 | 2025-12-31 |
|
||||
| 11 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | filter | 1.1.0 | 5 | 109 | 2 | 1 | 2025-12-31 |
|
||||
203
docs/community-stats.json
Normal file
203
docs/community-stats.json
Normal file
@@ -0,0 +1,203 @@
|
||||
{
|
||||
"total_posts": 11,
|
||||
"total_downloads": 785,
|
||||
"total_views": 8394,
|
||||
"total_upvotes": 54,
|
||||
"total_downvotes": 0,
|
||||
"total_saves": 46,
|
||||
"total_comments": 13,
|
||||
"by_type": {
|
||||
"action": 9,
|
||||
"filter": 2
|
||||
},
|
||||
"posts": [
|
||||
{
|
||||
"title": "Turn Any Text into Beautiful Mind Maps",
|
||||
"slug": "turn_any_text_into_beautiful_mind_maps_3094c59a",
|
||||
"type": "action",
|
||||
"version": "0.8.2",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Intelligently analyzes text content and generates interactive mind maps to help users structure and visualize knowledge.",
|
||||
"downloads": 235,
|
||||
"views": 2095,
|
||||
"upvotes": 10,
|
||||
"saves": 15,
|
||||
"comments": 8,
|
||||
"created_at": "2025-12-30",
|
||||
"updated_at": "2026-01-03",
|
||||
"url": "https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a"
|
||||
},
|
||||
{
|
||||
"title": "Export to Excel",
|
||||
"slug": "export_mulit_table_to_excel_244b8f9d",
|
||||
"type": "action",
|
||||
"version": "0.3.6",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Extracts tables from chat messages and exports them to Excel (.xlsx) files with smart formatting.",
|
||||
"downloads": 170,
|
||||
"views": 455,
|
||||
"upvotes": 3,
|
||||
"saves": 3,
|
||||
"comments": 0,
|
||||
"created_at": "2025-05-30",
|
||||
"updated_at": "2026-01-03",
|
||||
"url": "https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d"
|
||||
},
|
||||
{
|
||||
"title": "Async Context Compression",
|
||||
"slug": "async_context_compression_b1655bc8",
|
||||
"type": "filter",
|
||||
"version": "1.1.0",
|
||||
"author": "Fu-Jie",
|
||||
"description": "This filter automatically compresses long conversation contexts by intelligently summarizing and removing intermediate messages while preserving critical information, thereby significantly reducing token consumption.",
|
||||
"downloads": 112,
|
||||
"views": 1234,
|
||||
"upvotes": 5,
|
||||
"saves": 9,
|
||||
"comments": 0,
|
||||
"created_at": "2025-11-08",
|
||||
"updated_at": "2025-12-31",
|
||||
"url": "https://openwebui.com/posts/async_context_compression_b1655bc8"
|
||||
},
|
||||
{
|
||||
"title": "Flash Card ",
|
||||
"slug": "flash_card_65a2ea8f",
|
||||
"type": "action",
|
||||
"version": "0.2.4",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Quickly generates beautiful flashcards from text, extracting key points and categories.",
|
||||
"downloads": 75,
|
||||
"views": 1413,
|
||||
"upvotes": 8,
|
||||
"saves": 5,
|
||||
"comments": 2,
|
||||
"created_at": "2025-12-30",
|
||||
"updated_at": "2026-01-03",
|
||||
"url": "https://openwebui.com/posts/flash_card_65a2ea8f"
|
||||
},
|
||||
{
|
||||
"title": "Smart Infographic",
|
||||
"slug": "smart_infographic_ad6f0c7f",
|
||||
"type": "action",
|
||||
"version": "1.3.2",
|
||||
"author": "jeff",
|
||||
"description": "AI-powered infographic generator based on AntV Infographic. Supports professional templates, auto-icon matching, and SVG/PNG downloads.",
|
||||
"downloads": 65,
|
||||
"views": 900,
|
||||
"upvotes": 6,
|
||||
"saves": 8,
|
||||
"comments": 2,
|
||||
"created_at": "2025-12-28",
|
||||
"updated_at": "2026-01-03",
|
||||
"url": "https://openwebui.com/posts/smart_infographic_ad6f0c7f"
|
||||
},
|
||||
{
|
||||
"title": "Export to Word (Enhanced Formatting)",
|
||||
"slug": "export_to_word_enhanced_formatting_fca6a315",
|
||||
"type": "action",
|
||||
"version": "0.4.0",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Export the current conversation to a formatted Word doc with syntax highlighting, AI-generated titles, and perfect Markdown rendering (tables, quotes, lists).",
|
||||
"downloads": 51,
|
||||
"views": 499,
|
||||
"upvotes": 5,
|
||||
"saves": 4,
|
||||
"comments": 0,
|
||||
"created_at": "2026-01-03",
|
||||
"updated_at": "2026-01-05",
|
||||
"url": "https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315"
|
||||
},
|
||||
{
|
||||
"title": "智能信息图",
|
||||
"slug": "智能信息图_e04a48ff",
|
||||
"type": "action",
|
||||
"version": "1.3.1",
|
||||
"author": "jeff",
|
||||
"description": "基于 AntV Infographic 的智能信息图生成插件。支持多种专业模板,自动图标匹配,并提供 SVG/PNG 下载功能。",
|
||||
"downloads": 33,
|
||||
"views": 397,
|
||||
"upvotes": 3,
|
||||
"saves": 0,
|
||||
"comments": 0,
|
||||
"created_at": "2025-12-28",
|
||||
"updated_at": "2025-12-29",
|
||||
"url": "https://openwebui.com/posts/智能信息图_e04a48ff"
|
||||
},
|
||||
{
|
||||
"title": "智能生成交互式思维导图,帮助用户可视化知识",
|
||||
"slug": "智能生成交互式思维导图帮助用户可视化知识_8d4b097b",
|
||||
"type": "action",
|
||||
"version": "0.8.0",
|
||||
"author": "",
|
||||
"description": "智能分析文本内容,生成交互式思维导图,帮助用户结构化和可视化知识。",
|
||||
"downloads": 14,
|
||||
"views": 246,
|
||||
"upvotes": 2,
|
||||
"saves": 0,
|
||||
"comments": 0,
|
||||
"created_at": "2025-12-31",
|
||||
"updated_at": "2025-12-31",
|
||||
"url": "https://openwebui.com/posts/智能生成交互式思维导图帮助用户可视化知识_8d4b097b"
|
||||
},
|
||||
{
|
||||
"title": "导出为 Word-支持公式、流程图、表格和代码块",
|
||||
"slug": "导出为_word_支持公式流程图表格和代码块_8a6306c0",
|
||||
"type": "action",
|
||||
"version": "0.4.1",
|
||||
"author": "Fu-Jie",
|
||||
"description": "将当前对话内容从 Markdown 转换并导出为 Word (.docx) 文件,支持中英文无乱码。",
|
||||
"downloads": 13,
|
||||
"views": 737,
|
||||
"upvotes": 7,
|
||||
"saves": 1,
|
||||
"comments": 1,
|
||||
"created_at": "2026-01-04",
|
||||
"updated_at": "2026-01-05",
|
||||
"url": "https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0"
|
||||
},
|
||||
{
|
||||
"title": "闪记卡生成插件",
|
||||
"slug": "闪记卡生成插件_4a31eac3",
|
||||
"type": "action",
|
||||
"version": "0.2.2",
|
||||
"author": "Fu-Jie",
|
||||
"description": "快速将文本提炼为精美的学习记忆卡片,支持核心要点提取与分类。",
|
||||
"downloads": 12,
|
||||
"views": 309,
|
||||
"upvotes": 3,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"created_at": "2025-12-30",
|
||||
"updated_at": "2025-12-31",
|
||||
"url": "https://openwebui.com/posts/闪记卡生成插件_4a31eac3"
|
||||
},
|
||||
{
|
||||
"title": "异步上下文压缩",
|
||||
"slug": "异步上下文压缩_5c0617cb",
|
||||
"type": "filter",
|
||||
"version": "1.1.0",
|
||||
"author": "Fu-Jie",
|
||||
"description": "在 LLM 响应完成后进行上下文摘要和压缩",
|
||||
"downloads": 5,
|
||||
"views": 109,
|
||||
"upvotes": 2,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"created_at": "2025-11-08",
|
||||
"updated_at": "2025-12-31",
|
||||
"url": "https://openwebui.com/posts/异步上下文压缩_5c0617cb"
|
||||
}
|
||||
],
|
||||
"user": {
|
||||
"username": "Fu-Jie",
|
||||
"name": "Fu-Jie",
|
||||
"profile_url": "https://openwebui.com/u/Fu-Jie",
|
||||
"profile_image": "https://community.s3.openwebui.com/uploads/users/b15d1348-4347-42b4-b815-e053342d6cb0/profile_d9510745-4bd4-4f8f-a997-4a21847d9300.webp",
|
||||
"followers": 41,
|
||||
"following": 2,
|
||||
"total_points": 63,
|
||||
"post_points": 54,
|
||||
"comment_points": 9,
|
||||
"contributions": 17
|
||||
}
|
||||
}
|
||||
35
docs/community-stats.md
Normal file
35
docs/community-stats.md
Normal file
@@ -0,0 +1,35 @@
|
||||
# 📊 OpenWebUI 社区统计报告
|
||||
|
||||
> 📅 更新时间: 2026-01-06 11:08:23
|
||||
|
||||
## 📈 总览
|
||||
|
||||
| 指标 | 数值 |
|
||||
|------|------|
|
||||
| 📝 发布数量 | 11 |
|
||||
| ⬇️ 总下载量 | 785 |
|
||||
| 👁️ 总浏览量 | 8394 |
|
||||
| 👍 总点赞数 | 54 |
|
||||
| 💾 总收藏数 | 46 |
|
||||
| 💬 总评论数 | 13 |
|
||||
|
||||
## 📂 按类型分类
|
||||
|
||||
- **action**: 9
|
||||
- **filter**: 2
|
||||
|
||||
## 📋 发布列表
|
||||
|
||||
| 排名 | 标题 | 类型 | 版本 | 下载 | 浏览 | 点赞 | 收藏 | 更新日期 |
|
||||
|:---:|------|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
|
||||
| 1 | [Turn Any Text into Beautiful Mind Maps](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.8.2 | 235 | 2095 | 10 | 15 | 2026-01-03 |
|
||||
| 2 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.6 | 170 | 455 | 3 | 3 | 2026-01-03 |
|
||||
| 3 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter | 1.1.0 | 112 | 1234 | 5 | 9 | 2025-12-31 |
|
||||
| 4 | [Flash Card ](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 75 | 1413 | 8 | 5 | 2026-01-03 |
|
||||
| 5 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.3.2 | 65 | 900 | 6 | 7 | 2026-01-03 |
|
||||
| 6 | [Export to Word (Enhanced Formatting)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.0 | 51 | 499 | 5 | 4 | 2026-01-05 |
|
||||
| 7 | [智能信息图](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.3.1 | 33 | 397 | 3 | 0 | 2025-12-29 |
|
||||
| 8 | [智能生成交互式思维导图,帮助用户可视化知识](https://openwebui.com/posts/智能生成交互式思维导图帮助用户可视化知识_8d4b097b) | action | 0.8.0 | 14 | 246 | 2 | 0 | 2025-12-31 |
|
||||
| 9 | [导出为 Word-支持公式、流程图、表格和代码块](https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0) | action | 0.4.1 | 13 | 737 | 7 | 1 | 2026-01-05 |
|
||||
| 10 | [闪记卡生成插件](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.2 | 12 | 309 | 3 | 1 | 2025-12-31 |
|
||||
| 11 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | filter | 1.1.0 | 5 | 109 | 2 | 1 | 2025-12-31 |
|
||||
@@ -235,6 +235,125 @@ llm_response = await generate_chat_completion(
|
||||
)
|
||||
```
|
||||
|
||||
### 4.4 JS Render to Markdown (Data URL Embedding)
|
||||
|
||||
For scenarios requiring complex frontend rendering (e.g., AntV charts, Mermaid diagrams) but wanting **persistent pure Markdown output**, use the Data URL embedding pattern:
|
||||
|
||||
#### Workflow
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────────────────────┐
|
||||
│ 1. Python Action │
|
||||
│ ├── Analyze message content │
|
||||
│ ├── Call LLM to generate structured data (optional) │
|
||||
│ └── Send JS code to frontend via __event_call__ │
|
||||
├──────────────────────────────────────────────────────────────┤
|
||||
│ 2. Browser JS (via __event_call__) │
|
||||
│ ├── Dynamically load visualization library │
|
||||
│ ├── Render SVG/Canvas offscreen │
|
||||
│ ├── Export to Base64 Data URL via toDataURL() │
|
||||
│ └── Update message content via REST API │
|
||||
├──────────────────────────────────────────────────────────────┤
|
||||
│ 3. Markdown Rendering │
|
||||
│ └── Display  │
|
||||
└──────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
#### Python Side (Send JS for Execution)
|
||||
|
||||
```python
|
||||
async def action(self, body, __event_call__, __metadata__, ...):
|
||||
chat_id = self._extract_chat_id(body, __metadata__)
|
||||
message_id = self._extract_message_id(body, __metadata__)
|
||||
|
||||
# Generate JS code
|
||||
js_code = self._generate_js_code(
|
||||
chat_id=chat_id,
|
||||
message_id=message_id,
|
||||
data=processed_data,
|
||||
)
|
||||
|
||||
# Execute JS
|
||||
if __event_call__:
|
||||
await __event_call__({
|
||||
"type": "execute",
|
||||
"data": {"code": js_code}
|
||||
})
|
||||
```
|
||||
|
||||
#### JavaScript Side (Render and Write-back)
|
||||
|
||||
```javascript
|
||||
(async function() {
|
||||
// 1. Load visualization library
|
||||
if (typeof VisualizationLib === 'undefined') {
|
||||
await new Promise((resolve, reject) => {
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.example.com/lib.min.js';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
});
|
||||
}
|
||||
|
||||
// 2. Create offscreen container
|
||||
const container = document.createElement('div');
|
||||
container.style.cssText = 'position:absolute;left:-9999px;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// 3. Render visualization
|
||||
const instance = new VisualizationLib({ container });
|
||||
instance.render(data);
|
||||
|
||||
// 4. Export to Data URL
|
||||
const dataUrl = await instance.toDataURL({ type: 'svg', embedResources: true });
|
||||
|
||||
// 5. Cleanup
|
||||
instance.destroy();
|
||||
document.body.removeChild(container);
|
||||
|
||||
// 6. Generate Markdown image
|
||||
const markdownImage = ``;
|
||||
|
||||
// 7. Update message via API
|
||||
const token = localStorage.getItem("token");
|
||||
await fetch(`/api/v1/chats/${chatId}/messages/${messageId}/event`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${token}`
|
||||
},
|
||||
body: JSON.stringify({
|
||||
type: "chat:message",
|
||||
data: { content: originalContent + "\n\n" + markdownImage }
|
||||
})
|
||||
});
|
||||
})();
|
||||
```
|
||||
|
||||
#### Benefits
|
||||
|
||||
- **Pure Markdown Output**: Standard Markdown image syntax, no HTML code blocks
|
||||
- **Self-Contained**: Images embedded as Base64 Data URL, no external dependencies
|
||||
- **Persistent**: Via API write-back, images remain after page reload
|
||||
- **Cross-Platform**: Works on any client supporting Markdown images
|
||||
|
||||
#### HTML Injection vs JS Render to Markdown
|
||||
|
||||
| Feature | HTML Injection | JS Render + Markdown |
|
||||
|---------|----------------|----------------------|
|
||||
| Output Format | HTML code block | Markdown image |
|
||||
| Interactivity | ✅ Buttons, animations | ❌ Static image |
|
||||
| External Deps | Requires JS libraries | None (self-contained) |
|
||||
| Persistence | Depends on browser | ✅ Permanent |
|
||||
| File Export | Needs special handling | ✅ Direct export |
|
||||
| Use Case | Interactive content | Infographics, chart snapshots |
|
||||
|
||||
#### Reference Implementations
|
||||
|
||||
- `plugins/actions/js-render-poc/infographic_markdown.py` - AntV Infographic + Data URL
|
||||
- `plugins/actions/js-render-poc/js_render_poc.py` - Basic proof of concept
|
||||
|
||||
---
|
||||
|
||||
## 5. Best Practices & Design Principles
|
||||
|
||||
@@ -199,7 +199,124 @@ async def background_job(self, chat_id):
|
||||
pass
|
||||
```
|
||||
|
||||
---
|
||||
### 4.3 JS 渲染并嵌入 Markdown (Data URL 嵌入)
|
||||
|
||||
对于需要复杂前端渲染(如 AntV 图表、Mermaid 图表)但希望结果**持久化为纯 Markdown 格式**的场景,推荐使用 Data URL 嵌入模式:
|
||||
|
||||
#### 工作流程
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────────────────────┐
|
||||
│ 1. Python Action │
|
||||
│ ├── 分析消息内容 │
|
||||
│ ├── 调用 LLM 生成结构化数据(可选) │
|
||||
│ └── 通过 __event_call__ 发送 JS 代码到前端 │
|
||||
├──────────────────────────────────────────────────────────────┤
|
||||
│ 2. Browser JS (通过 __event_call__) │
|
||||
│ ├── 动态加载可视化库 │
|
||||
│ ├── 离屏渲染 SVG/Canvas │
|
||||
│ ├── 使用 toDataURL() 导出 Base64 Data URL │
|
||||
│ └── 通过 REST API 更新消息内容 │
|
||||
├──────────────────────────────────────────────────────────────┤
|
||||
│ 3. Markdown 渲染 │
|
||||
│ └── 显示  │
|
||||
└──────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
#### Python 端(发送 JS 执行)
|
||||
|
||||
```python
|
||||
async def action(self, body, __event_call__, __metadata__, ...):
|
||||
chat_id = self._extract_chat_id(body, __metadata__)
|
||||
message_id = self._extract_message_id(body, __metadata__)
|
||||
|
||||
# 生成 JS 代码
|
||||
js_code = self._generate_js_code(
|
||||
chat_id=chat_id,
|
||||
message_id=message_id,
|
||||
data=processed_data,
|
||||
)
|
||||
|
||||
# 执行 JS
|
||||
if __event_call__:
|
||||
await __event_call__({
|
||||
"type": "execute",
|
||||
"data": {"code": js_code}
|
||||
})
|
||||
```
|
||||
|
||||
#### JavaScript 端(渲染并回写)
|
||||
|
||||
```javascript
|
||||
(async function() {
|
||||
// 1. 加载可视化库
|
||||
if (typeof VisualizationLib === 'undefined') {
|
||||
await new Promise((resolve, reject) => {
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.example.com/lib.min.js';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
});
|
||||
}
|
||||
|
||||
// 2. 创建离屏容器
|
||||
const container = document.createElement('div');
|
||||
container.style.cssText = 'position:absolute;left:-9999px;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// 3. 渲染可视化
|
||||
const instance = new VisualizationLib({ container });
|
||||
instance.render(data);
|
||||
|
||||
// 4. 导出为 Data URL
|
||||
const dataUrl = await instance.toDataURL({ type: 'svg', embedResources: true });
|
||||
|
||||
// 5. 清理
|
||||
instance.destroy();
|
||||
document.body.removeChild(container);
|
||||
|
||||
// 6. 生成 Markdown 图片
|
||||
const markdownImage = ``;
|
||||
|
||||
// 7. 通过 API 更新消息
|
||||
const token = localStorage.getItem("token");
|
||||
await fetch(`/api/v1/chats/${chatId}/messages/${messageId}/event`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${token}`
|
||||
},
|
||||
body: JSON.stringify({
|
||||
type: "chat:message",
|
||||
data: { content: originalContent + "\n\n" + markdownImage }
|
||||
})
|
||||
});
|
||||
})();
|
||||
```
|
||||
|
||||
#### 优势
|
||||
|
||||
- **纯 Markdown 输出**:结果是标准的 Markdown 图片语法,无需 HTML 代码块
|
||||
- **自包含**:图片以 Base64 Data URL 嵌入,无外部依赖
|
||||
- **持久化**:通过 API 回写,消息重新加载后图片仍然存在
|
||||
- **跨平台**:任何支持 Markdown 图片的客户端都能显示
|
||||
|
||||
#### HTML 注入 vs JS 渲染嵌入 Markdown
|
||||
|
||||
| 特性 | HTML 注入 | JS 渲染 + Markdown 图片 |
|
||||
|------|----------|------------------------|
|
||||
| 输出格式 | HTML 代码块 | Markdown 图片 |
|
||||
| 交互性 | ✅ 支持按钮、动画 | ❌ 静态图片 |
|
||||
| 外部依赖 | 需要加载 JS 库 | 无(图片自包含) |
|
||||
| 持久化 | 依赖浏览器渲染 | ✅ 永久可见 |
|
||||
| 文件导出 | 需特殊处理 | ✅ 直接导出 |
|
||||
| 适用场景 | 交互式内容 | 信息图、图表快照 |
|
||||
|
||||
#### 参考实现
|
||||
|
||||
- `plugins/actions/js-render-poc/infographic_markdown.py` - AntV 信息图 + Data URL
|
||||
- `plugins/actions/js-render-poc/js_render_poc.py` - 基础概念验证
|
||||
|
||||
## 5. 最佳实践与设计原则
|
||||
|
||||
|
||||
@@ -104,10 +104,16 @@ hide:
|
||||
|
||||
### Using Plugins
|
||||
|
||||
1. Browse the [Plugin Center](plugins/index.md) and download the plugin file (`.py`)
|
||||
2. Open OpenWebUI **Admin Panel** → **Settings** → **Plugins**
|
||||
3. Click the upload button and select the `.py` file
|
||||
4. Refresh the page and enable the plugin in your chat settings
|
||||
1. **Install from OpenWebUI Community (Recommended)**:
|
||||
- Visit my profile: [Fu-Jie's Profile](https://openwebui.com/u/Fu-Jie)
|
||||
- Browse the plugins and select the one you like.
|
||||
- Click "Get" to import it directly into your OpenWebUI instance.
|
||||
|
||||
2. **Manual Installation**:
|
||||
- Browse the [Plugin Center](plugins/index.md) and download the plugin file (`.py`)
|
||||
- Open OpenWebUI **Admin Panel** → **Settings** → **Plugins**
|
||||
- Click the upload button and select the `.py` file
|
||||
- Refresh the page and enable the plugin in your chat settings
|
||||
|
||||
---
|
||||
|
||||
|
||||
@@ -104,10 +104,16 @@ hide:
|
||||
|
||||
### 使用插件
|
||||
|
||||
1. 浏览[插件中心](plugins/index.md)并下载插件文件(`.py`)
|
||||
2. 打开 OpenWebUI **管理面板** → **设置** → **插件**
|
||||
3. 点击上传按钮并选择 `.py` 文件
|
||||
4. 刷新页面并在聊天设置中启用插件
|
||||
1. **从 OpenWebUI 社区安装 (推荐)**:
|
||||
- 访问我的主页: [Fu-Jie's Profile](https://openwebui.com/u/Fu-Jie)
|
||||
- 浏览插件列表,选择你喜欢的插件。
|
||||
- 点击 "Get" 按钮,将其直接导入到你的 OpenWebUI 实例中。
|
||||
|
||||
2. **手动安装**:
|
||||
- 浏览[插件中心](plugins/index.md)并下载插件文件(`.py`)
|
||||
- 打开 OpenWebUI **管理面板** → **设置** → **插件**
|
||||
- 点击上传按钮并选择 `.py` 文件
|
||||
- 刷新页面并在聊天设置中启用插件
|
||||
|
||||
---
|
||||
|
||||
|
||||
290
docs/js-visualization-guide.md
Normal file
290
docs/js-visualization-guide.md
Normal file
@@ -0,0 +1,290 @@
|
||||
# 使用 JavaScript 生成可视化内容的技术方案
|
||||
|
||||
## 概述
|
||||
|
||||
本文档描述了在 OpenWebUI Action 插件中使用浏览器端 JavaScript 代码生成可视化内容(如思维导图、信息图等)并将结果保存到消息中的技术方案。
|
||||
|
||||
## 核心架构
|
||||
|
||||
```mermaid
|
||||
sequenceDiagram
|
||||
participant Plugin as Python 插件
|
||||
participant EventCall as __event_call__
|
||||
participant Browser as 浏览器 (JS)
|
||||
participant API as OpenWebUI API
|
||||
participant DB as 数据库
|
||||
|
||||
Plugin->>EventCall: 1. 发送 execute 事件 (含 JS 代码)
|
||||
EventCall->>Browser: 2. 执行 JS 代码
|
||||
Browser->>Browser: 3. 加载可视化库 (D3/Markmap/AntV)
|
||||
Browser->>Browser: 4. 渲染可视化内容
|
||||
Browser->>Browser: 5. 转换为 Base64 Data URI
|
||||
Browser->>API: 6. GET 获取当前消息内容
|
||||
API-->>Browser: 7. 返回消息数据
|
||||
Browser->>API: 8. POST 追加 Markdown 图片到消息
|
||||
API->>DB: 9. 保存更新后的消息
|
||||
```
|
||||
|
||||
## 关键步骤
|
||||
|
||||
### 1. Python 端通过 `__event_call__` 执行 JS
|
||||
|
||||
Python 插件**不直接修改 `body["messages"]`**,而是通过 `__event_call__` 发送 JS 代码让浏览器执行:
|
||||
|
||||
```python
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: dict = None,
|
||||
__event_emitter__=None,
|
||||
__event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__metadata__: Optional[dict] = None,
|
||||
__request__: Request = None,
|
||||
) -> dict:
|
||||
# 从 body 获取 chat_id 和 message_id
|
||||
chat_id = body.get("chat_id", "")
|
||||
message_id = body.get("id", "") # 注意:body["id"] 是 message_id
|
||||
|
||||
# 通过 __event_call__ 执行 JS 代码
|
||||
if __event_call__:
|
||||
await __event_call__({
|
||||
"type": "execute",
|
||||
"data": {
|
||||
"code": f"""
|
||||
(async function() {{
|
||||
const chatId = "{chat_id}";
|
||||
const messageId = "{message_id}";
|
||||
// ... JS 渲染和 API 更新逻辑 ...
|
||||
}})();
|
||||
"""
|
||||
},
|
||||
})
|
||||
|
||||
# 不修改 body,直接返回
|
||||
return body
|
||||
```
|
||||
|
||||
### 2. JavaScript 加载可视化库
|
||||
|
||||
在浏览器端动态加载所需的 JS 库:
|
||||
|
||||
```javascript
|
||||
// 加载 D3.js
|
||||
if (!window.d3) {
|
||||
await new Promise((resolve, reject) => {
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.jsdelivr.net/npm/d3@7';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
});
|
||||
}
|
||||
|
||||
// 加载 Markmap (思维导图)
|
||||
if (!window.markmap) {
|
||||
await loadScript('https://cdn.jsdelivr.net/npm/markmap-lib@0.17');
|
||||
await loadScript('https://cdn.jsdelivr.net/npm/markmap-view@0.17');
|
||||
}
|
||||
```
|
||||
|
||||
### 3. 渲染并转换为 Data URI
|
||||
|
||||
```javascript
|
||||
// 创建 SVG 元素
|
||||
const svg = document.createElementNS('http://www.w3.org/2000/svg', 'svg');
|
||||
svg.setAttribute('width', '800');
|
||||
svg.setAttribute('height', '600');
|
||||
svg.setAttribute('xmlns', 'http://www.w3.org/2000/svg');
|
||||
|
||||
// ... 执行渲染逻辑 (添加图形元素) ...
|
||||
|
||||
// 转换为 Base64 Data URI
|
||||
const svgData = new XMLSerializer().serializeToString(svg);
|
||||
const base64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
const dataUri = 'data:image/svg+xml;base64,' + base64;
|
||||
```
|
||||
|
||||
### 4. 获取当前消息内容
|
||||
|
||||
由于 Python 端不传递原始内容,JS 需要通过 API 获取:
|
||||
|
||||
```javascript
|
||||
const token = localStorage.getItem('token');
|
||||
|
||||
// 获取当前聊天数据
|
||||
const getResponse = await fetch(`/api/v1/chats/${chatId}`, {
|
||||
method: 'GET',
|
||||
headers: {
|
||||
'Authorization': `Bearer ${token}`
|
||||
}
|
||||
});
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
|
||||
// 查找目标消息
|
||||
let originalContent = '';
|
||||
if (chatData.chat && chatData.chat.messages) {
|
||||
const targetMsg = chatData.chat.messages.find(m => m.id === messageId);
|
||||
if (targetMsg && targetMsg.content) {
|
||||
originalContent = targetMsg.content;
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 5. 调用 API 更新消息
|
||||
|
||||
```javascript
|
||||
// 构造新内容:原始内容 + Markdown 图片
|
||||
const markdownImage = ``;
|
||||
const newContent = originalContent + '\n\n' + markdownImage;
|
||||
|
||||
// 调用 API 更新消息
|
||||
const response = await fetch(`/api/v1/chats/${chatId}/messages/${messageId}/event`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
'Authorization': `Bearer ${token}`
|
||||
},
|
||||
body: JSON.stringify({
|
||||
type: 'chat:message',
|
||||
data: { content: newContent }
|
||||
})
|
||||
});
|
||||
|
||||
if (response.ok) {
|
||||
console.log('消息更新成功!');
|
||||
}
|
||||
```
|
||||
|
||||
## 完整示例
|
||||
|
||||
参考 [js_render_poc.py](https://github.com/Fu-Jie/awesome-openwebui/blob/main/plugins/actions/js-render-poc/js_render_poc.py) 获取完整的 PoC 实现。
|
||||
|
||||
## 事件类型
|
||||
|
||||
| 类型 | 用途 |
|
||||
|------|------|
|
||||
| `chat:message:delta` | 增量更新(追加文本) |
|
||||
| `chat:message` | 完全替换消息内容 |
|
||||
|
||||
```javascript
|
||||
// 增量更新
|
||||
{ type: "chat:message:delta", data: { content: "追加的内容" } }
|
||||
|
||||
// 完全替换
|
||||
{ type: "chat:message", data: { content: "完整的新内容" } }
|
||||
```
|
||||
|
||||
## 关键数据来源
|
||||
|
||||
| 数据 | 来源 | 说明 |
|
||||
|------|------|------|
|
||||
| `chat_id` | `body["chat_id"]` | 聊天会话 ID |
|
||||
| `message_id` | `body["id"]` | ⚠️ 注意:是 `body["id"]`,不是 `body["message_id"]` |
|
||||
| `token` | `localStorage.getItem('token')` | 用户认证 Token |
|
||||
| `originalContent` | 通过 API `GET /api/v1/chats/{chatId}` 获取 | 当前消息内容 |
|
||||
|
||||
## Python 端 API
|
||||
|
||||
| 参数 | 类型 | 说明 |
|
||||
|------|------|------|
|
||||
| `__event_emitter__` | Callable | 发送状态/通知事件 |
|
||||
| `__event_call__` | Callable | 执行 JS 代码(用于可视化渲染) |
|
||||
| `__metadata__` | dict | 元数据(可能为 None) |
|
||||
| `body` | dict | 请求体,包含 messages、chat_id、id 等 |
|
||||
|
||||
### body 结构示例
|
||||
|
||||
```json
|
||||
{
|
||||
"model": "gemini-3-flash-preview",
|
||||
"messages": [...],
|
||||
"chat_id": "ac2633a3-5731-4944-98e3-bf9b3f0ef0ab",
|
||||
"id": "2e0bb7d4-dfc0-43d7-b028-fd9e06c6fdc8",
|
||||
"session_id": "bX30sHI8r4_CKxCdAAAL"
|
||||
}
|
||||
```
|
||||
|
||||
### 常用事件
|
||||
|
||||
```python
|
||||
# 发送状态更新
|
||||
await __event_emitter__({
|
||||
"type": "status",
|
||||
"data": {"description": "正在渲染...", "done": False}
|
||||
})
|
||||
|
||||
# 执行 JS 代码
|
||||
await __event_call__({
|
||||
"type": "execute",
|
||||
"data": {"code": "console.log('Hello from Python!')"}
|
||||
})
|
||||
|
||||
# 发送通知
|
||||
await __event_emitter__({
|
||||
"type": "notification",
|
||||
"data": {"type": "success", "content": "渲染完成!"}
|
||||
})
|
||||
```
|
||||
|
||||
## 适用场景
|
||||
|
||||
- **思维导图** (Markmap)
|
||||
- **信息图** (AntV Infographic)
|
||||
- **流程图** (Mermaid)
|
||||
- **数据图表** (ECharts, Chart.js)
|
||||
- **任何需要 JS 渲染的可视化内容**
|
||||
|
||||
## 注意事项
|
||||
|
||||
### 1. 竞态条件问题
|
||||
|
||||
⚠️ **多次快速点击会导致内容覆盖问题**
|
||||
|
||||
由于 API 调用是异步的,如果用户快速多次触发 Action:
|
||||
- 第一次点击:获取原始内容 A → 渲染 → 更新为 A+图片1
|
||||
- 第二次点击:可能获取到旧内容 A(第一次还没保存完)→ 更新为 A+图片2
|
||||
|
||||
结果:图片1 被覆盖丢失!
|
||||
|
||||
**解决方案**:
|
||||
- 添加防抖(debounce)机制
|
||||
- 使用锁/标志位防止重复执行
|
||||
- 或使用 `chat:message:delta` 增量更新
|
||||
|
||||
### 2. 不要直接修改 `body["messages"]`
|
||||
|
||||
消息更新应由 JS 通过 API 完成,确保获取最新内容。
|
||||
|
||||
### 3. f-string 限制
|
||||
|
||||
Python f-string 内不能直接使用反斜杠,需要将转义字符串预先处理:
|
||||
|
||||
```python
|
||||
# 转义 JSON 中的特殊字符
|
||||
body_json = json.dumps(data, ensure_ascii=False)
|
||||
escaped = body_json.replace("\\", "\\\\").replace("`", "\\`").replace("${", "\\${")
|
||||
```
|
||||
|
||||
### 4. Data URI 大小限制
|
||||
|
||||
Base64 编码会增加约 33% 的体积,复杂图片可能导致消息过大。
|
||||
|
||||
### 5. 跨域问题
|
||||
|
||||
确保 CDN 资源支持 CORS。
|
||||
|
||||
### 6. API 权限
|
||||
|
||||
确保用户 token 有权限访问和更新目标消息。
|
||||
|
||||
## 与传统方式对比
|
||||
|
||||
| 特性 | 传统方式 (修改 body) | 新方式 (__event_call__) |
|
||||
|------|---------------------|------------------------|
|
||||
| 消息更新 | Python 直接修改 | JS 通过 API 更新 |
|
||||
| 原始内容 | Python 传递给 JS | JS 通过 API 获取 |
|
||||
| 灵活性 | 低 | 高 |
|
||||
| 实时性 | 一次性 | 可多次更新 |
|
||||
| 复杂度 | 简单 | 中等 |
|
||||
| 竞态风险 | 低 | ⚠️ 需要处理 |
|
||||
@@ -1,7 +1,7 @@
|
||||
# Export to Word
|
||||
|
||||
<span class="category-badge action">Action</span>
|
||||
<span class="version-badge">v0.2.0</span>
|
||||
<span class="version-badge">v0.4.1</span>
|
||||
|
||||
Export conversation to Word (.docx) with **syntax highlighting**, **native math equations**, **Mermaid diagrams**, **citations**, and **enhanced table formatting**.
|
||||
|
||||
@@ -34,11 +34,34 @@ You can configure the following settings via the **Valves** button in the plugin
|
||||
| Valve | Description | Default |
|
||||
| :--- | :--- | :--- |
|
||||
| `TITLE_SOURCE` | Source for document title/filename. Options: `chat_title`, `ai_generated`, `markdown_title` | `chat_title` |
|
||||
| `MERMAID_JS_URL` | URL for the Mermaid.js library (for diagram rendering). | `https://cdn.jsdelivr.net/npm/mermaid@10.9.1/dist/mermaid.min.js` |
|
||||
| `MERMAID_PNG_SCALE` | Scale factor for Mermaid PNG generation (Resolution). Higher = clearer but larger file size. | `3.0` |
|
||||
| `MERMAID_DISPLAY_SCALE` | Scale factor for Mermaid visual size in Word. >1.0 to enlarge, <1.0 to shrink. | `1.5` |
|
||||
| `MERMAID_OPTIMIZE_LAYOUT` | Automatically convert LR (Left-Right) flowcharts to TD (Top-Down) for better fit. | `True` |
|
||||
| `MAX_EMBED_IMAGE_MB` | Maximum image size to embed into DOCX (MB). | `20` |
|
||||
| `UI_LANGUAGE` | User interface language. Options: `en` (English), `zh` (Chinese). | `en` |
|
||||
| `FONT_LATIN` | Font name for Latin characters. | `Times New Roman` |
|
||||
| `FONT_ASIAN` | Font name for Asian characters. | `SimSun` |
|
||||
| `FONT_CODE` | Font name for code blocks. | `Consolas` |
|
||||
| `TABLE_HEADER_COLOR` | Table header background color (Hex without #). | `F2F2F2` |
|
||||
| `TABLE_ZEBRA_COLOR` | Table alternating row background color (Hex without #). | `FBFBFB` |
|
||||
| `MERMAID_JS_URL` | URL for the Mermaid.js library. | `https://cdn.jsdelivr.net/npm/mermaid@11.12.2/dist/mermaid.min.js` |
|
||||
| `MERMAID_JSZIP_URL` | URL for the JSZip library (required for DOCX manipulation). | `https://cdnjs.cloudflare.com/ajax/libs/jszip/3.10.1/jszip.min.js` |
|
||||
| `MERMAID_PNG_SCALE` | Scale factor for Mermaid PNG generation (Resolution). | `3.0` |
|
||||
| `MERMAID_DISPLAY_SCALE` | Scale factor for Mermaid visual size in Word. | `1.0` |
|
||||
| `MERMAID_OPTIMIZE_LAYOUT` | Automatically convert LR (Left-Right) flowcharts to TD (Top-Down). | `False` |
|
||||
| `MERMAID_BACKGROUND` | Background color for Mermaid diagrams (e.g., `white`, `transparent`). | `transparent` |
|
||||
| `MERMAID_CAPTIONS_ENABLE` | Enable/disable figure captions for Mermaid diagrams. | `True` |
|
||||
| `MERMAID_CAPTION_STYLE` | Paragraph style name for Mermaid captions. | `Caption` |
|
||||
| `MERMAID_CAPTION_PREFIX` | Caption prefix label (e.g., 'Figure'). Empty = auto-detect based on language. | `""` |
|
||||
| `MATH_ENABLE` | Enable LaTeX math block conversion. | `True` |
|
||||
| `MATH_INLINE_DOLLAR_ENABLE` | Enable inline `$ ... $` math conversion. | `True` |
|
||||
|
||||
### User-Level Configuration (UserValves)
|
||||
|
||||
Users can override the following settings in their personal settings:
|
||||
- `TITLE_SOURCE`
|
||||
- `UI_LANGUAGE`
|
||||
- `FONT_LATIN`, `FONT_ASIAN`, `FONT_CODE`
|
||||
- `TABLE_HEADER_COLOR`, `TABLE_ZEBRA_COLOR`
|
||||
- `MERMAID_...` (Selected Mermaid settings)
|
||||
- `MATH_...` (Math settings)
|
||||
|
||||
---
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
# Export to Word(导出为 Word)
|
||||
|
||||
<span class="category-badge action">Action</span>
|
||||
<span class="version-badge">v0.2.0</span>
|
||||
<span class="version-badge">v0.4.1</span>
|
||||
|
||||
将当前对话导出为完美格式的 Word 文档,支持**代码语法高亮**、**原生数学公式**、**Mermaid 图表**、**引用资料**以及**增强表格**渲染。
|
||||
|
||||
@@ -33,12 +33,35 @@ Export to Word 插件会把聊天消息从 Markdown 转成精致的 Word 文档
|
||||
|
||||
| Valve | 说明 | 默认值 |
|
||||
| :--- | :--- | :--- |
|
||||
| `TITLE_SOURCE` | 文档标题/文件名的来源。选项:`chat_title` (对话标题), `ai_generated` (AI 生成), `markdown_title` (Markdown 标题) | `chat_title` |
|
||||
| `MERMAID_JS_URL` | Mermaid.js 库的 URL(用于图表渲染)。 | `https://cdn.jsdelivr.net/npm/mermaid@10.9.1/dist/mermaid.min.js` |
|
||||
| `MERMAID_PNG_SCALE` | Mermaid PNG 生成缩放比例(分辨率)。越高越清晰但文件越大。 | `3.0` |
|
||||
| `MERMAID_DISPLAY_SCALE` | Mermaid 在 Word 中的显示比例(视觉大小)。>1.0 放大, <1.0 缩小。 | `1.5` |
|
||||
| `MERMAID_OPTIMIZE_LAYOUT` | 优化 Mermaid 布局: 自动将 LR (左右) 转换为 TD (上下) 以适应页面。 | `True` |
|
||||
| `MERMAID_CAPTIONS_ENABLE` | 启用/禁用 Mermaid 图表的图注。 | `True` |
|
||||
| `文档标题来源` | 文档标题/文件名的来源。选项:`chat_title` (对话标题), `ai_generated` (AI 生成), `markdown_title` (Markdown 标题) | `chat_title` |
|
||||
| `最大嵌入图片大小MB` | 嵌入图片的最大大小 (MB)。 | `20` |
|
||||
| `界面语言` | 界面语言。选项:`en` (英语), `zh` (中文)。 | `zh` |
|
||||
| `英文字体` | 英文字体名称。 | `Calibri` |
|
||||
| `中文字体` | 中文字体名称。 | `SimSun` |
|
||||
| `代码字体` | 代码字体名称。 | `Consolas` |
|
||||
| `表头背景色` | 表头背景色(十六进制,不带#)。 | `F2F2F2` |
|
||||
| `表格隔行背景色` | 表格隔行背景色(十六进制,不带#)。 | `FBFBFB` |
|
||||
| `Mermaid_JS地址` | Mermaid.js 库的 URL。 | `https://cdn.jsdelivr.net/npm/mermaid@11.12.2/dist/mermaid.min.js` |
|
||||
| `JSZip库地址` | JSZip 库的 URL(用于 DOCX 操作)。 | `https://cdnjs.cloudflare.com/ajax/libs/jszip/3.10.1/jszip.min.js` |
|
||||
| `Mermaid_PNG缩放比例` | Mermaid PNG 生成缩放比例(分辨率)。 | `3.0` |
|
||||
| `Mermaid显示比例` | Mermaid 在 Word 中的显示比例(视觉大小)。 | `1.0` |
|
||||
| `Mermaid布局优化` | 优化 Mermaid 布局: 自动将 LR (左右) 转换为 TD (上下)。 | `False` |
|
||||
| `Mermaid背景色` | Mermaid 图表背景色(如 `white`, `transparent`)。 | `transparent` |
|
||||
| `启用Mermaid图注` | 启用/禁用 Mermaid 图表的图注。 | `True` |
|
||||
| `Mermaid图注样式` | Mermaid 图注的段落样式名称。 | `Caption` |
|
||||
| `Mermaid图注前缀` | 图注前缀(如 '图')。留空则根据语言自动检测。 | `""` |
|
||||
| `启用数学公式` | 启用 LaTeX 数学公式块转换。 | `True` |
|
||||
| `启用行内公式` | 启用行内 `$ ... $` 数学公式转换。 | `True` |
|
||||
|
||||
### 用户级配置 (UserValves)
|
||||
|
||||
用户可以在个人设置中覆盖以下配置:
|
||||
- `文档标题来源`
|
||||
- `界面语言`
|
||||
- `英文字体`, `中文字体`, `代码字体`
|
||||
- `表头背景色`, `表格隔行背景色`
|
||||
- `Mermaid_...` (部分 Mermaid 设置)
|
||||
- `启用数学公式`, `启用行内公式`
|
||||
|
||||
---
|
||||
|
||||
|
||||
@@ -63,7 +63,7 @@ Actions are interactive plugins that:
|
||||
|
||||
Export the current conversation to a formatted Word doc with **syntax highlighting**, **native math equations**, **Mermaid diagrams**, **citations**, and **enhanced table formatting**.
|
||||
|
||||
**Version:** 0.2.0
|
||||
**Version:** 0.4.1
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](export-to-word.md)
|
||||
|
||||
@@ -77,6 +77,16 @@ Actions are interactive plugins that:
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](summary.md)
|
||||
|
||||
- :material-image-text:{ .lg .middle } **Infographic to Markdown**
|
||||
|
||||
---
|
||||
|
||||
AI-powered infographic generator that renders SVG and embeds it as Markdown Data URL image.
|
||||
|
||||
**Version:** 1.0.0
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](infographic-markdown.md)
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
@@ -63,7 +63,7 @@ Actions 是交互式插件,能够:
|
||||
|
||||
将当前对话导出为完美格式的 Word 文档,支持**代码语法高亮**、**原生数学公式**、**Mermaid 图表**、**引用资料**以及**增强表格**渲染。
|
||||
|
||||
**版本:** 0.2.0
|
||||
**版本:** 0.4.1
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](export-to-word.md)
|
||||
|
||||
@@ -77,6 +77,16 @@ Actions 是交互式插件,能够:
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](summary.md)
|
||||
|
||||
- :material-image-text:{ .lg .middle } **信息图转 Markdown**
|
||||
|
||||
---
|
||||
|
||||
AI 驱动的信息图生成器,渲染 SVG 并以 Markdown Data URL 图片嵌入。
|
||||
|
||||
**版本:** 1.0.0
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](infographic-markdown.zh.md)
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
120
docs/plugins/actions/infographic-markdown.md
Normal file
120
docs/plugins/actions/infographic-markdown.md
Normal file
@@ -0,0 +1,120 @@
|
||||
# Infographic to Markdown
|
||||
|
||||
> **Version:** 1.0.0 | **Author:** Fu-Jie
|
||||
|
||||
AI-powered infographic generator that renders SVG on the frontend and embeds it directly into Markdown as a Data URL image.
|
||||
|
||||
## Overview
|
||||
|
||||
This plugin combines the power of AI text analysis with AntV Infographic visualization to create beautiful infographics that are embedded directly into chat messages as Markdown images.
|
||||
|
||||
### Key Features
|
||||
|
||||
- :robot: **AI-Powered**: Automatically analyzes text and selects the best infographic template
|
||||
- :bar_chart: **Multiple Templates**: Supports 18+ infographic templates (lists, charts, comparisons, etc.)
|
||||
- :framed_picture: **Self-Contained**: SVG/PNG embedded as Data URL, no external dependencies
|
||||
- :memo: **Markdown Native**: Results are pure Markdown images, compatible everywhere
|
||||
- :arrows_counterclockwise: **API Writeback**: Updates message content via REST API for persistence
|
||||
|
||||
### How It Works
|
||||
|
||||
```mermaid
|
||||
graph TD
|
||||
A[User triggers action] --> B[Python extracts message content]
|
||||
B --> C[LLM generates Infographic syntax]
|
||||
C --> D[Frontend JS loads AntV library]
|
||||
D --> E[Render SVG offscreen]
|
||||
E --> F[Export to Data URL]
|
||||
F --> G[Update message via API]
|
||||
G --> H[Display as Markdown image]
|
||||
```
|
||||
|
||||
## Installation
|
||||
|
||||
1. Download `infographic_markdown.py` (English) or `infographic_markdown_cn.py` (Chinese)
|
||||
2. Navigate to **Admin Panel** → **Settings** → **Functions**
|
||||
3. Upload the file and configure settings
|
||||
4. Use the action button in chat messages
|
||||
|
||||
## Configuration
|
||||
|
||||
| Parameter | Type | Default | Description |
|
||||
|-----------|------|---------|-------------|
|
||||
| `SHOW_STATUS` | bool | `true` | Show operation status updates |
|
||||
| `MODEL_ID` | string | `""` | LLM model ID (empty = use current model) |
|
||||
| `MIN_TEXT_LENGTH` | int | `50` | Minimum text length required |
|
||||
| `MESSAGE_COUNT` | int | `1` | Number of recent messages to use |
|
||||
| `SVG_WIDTH` | int | `800` | Width of generated SVG (pixels) |
|
||||
| `EXPORT_FORMAT` | string | `"svg"` | Export format: `svg` or `png` |
|
||||
|
||||
## Supported Templates
|
||||
|
||||
| Category | Template | Description |
|
||||
|----------|----------|-------------|
|
||||
| List | `list-grid` | Grid cards |
|
||||
| List | `list-vertical` | Vertical list |
|
||||
| Tree | `tree-vertical` | Vertical tree |
|
||||
| Tree | `tree-horizontal` | Horizontal tree |
|
||||
| Mind Map | `mindmap` | Mind map |
|
||||
| Process | `sequence-roadmap` | Roadmap |
|
||||
| Process | `sequence-zigzag` | Zigzag process |
|
||||
| Relation | `relation-sankey` | Sankey diagram |
|
||||
| Relation | `relation-circle` | Circular relation |
|
||||
| Compare | `compare-binary` | Binary comparison |
|
||||
| Analysis | `compare-swot` | SWOT analysis |
|
||||
| Quadrant | `quadrant-quarter` | Quadrant chart |
|
||||
| Chart | `chart-bar` | Bar chart |
|
||||
| Chart | `chart-column` | Column chart |
|
||||
| Chart | `chart-line` | Line chart |
|
||||
| Chart | `chart-pie` | Pie chart |
|
||||
| Chart | `chart-doughnut` | Doughnut chart |
|
||||
| Chart | `chart-area` | Area chart |
|
||||
|
||||
## Usage Example
|
||||
|
||||
1. Generate some text content in the chat (or have the AI generate it)
|
||||
2. Click the **📊 Infographic to Markdown** action button
|
||||
3. Wait for AI analysis and SVG rendering
|
||||
4. The infographic will be embedded as a Markdown image
|
||||
|
||||
## Technical Details
|
||||
|
||||
### Data URL Embedding
|
||||
|
||||
The plugin converts SVG graphics to Base64-encoded Data URLs:
|
||||
|
||||
```javascript
|
||||
const svgData = new XMLSerializer().serializeToString(svg);
|
||||
const base64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
const dataUri = "data:image/svg+xml;base64," + base64;
|
||||
const markdownImage = ``;
|
||||
```
|
||||
|
||||
### AntV toDataURL API
|
||||
|
||||
```javascript
|
||||
// Export as SVG (recommended)
|
||||
const svgUrl = await instance.toDataURL({
|
||||
type: 'svg',
|
||||
embedResources: true
|
||||
});
|
||||
|
||||
// Export as PNG
|
||||
const pngUrl = await instance.toDataURL({
|
||||
type: 'png',
|
||||
dpr: 2
|
||||
});
|
||||
```
|
||||
|
||||
## Notes
|
||||
|
||||
1. **Browser Compatibility**: Requires modern browsers with ES6+ and Fetch API support
|
||||
2. **Network Dependency**: First use requires loading AntV library from CDN
|
||||
3. **Data URL Size**: Base64 encoding increases size by ~33%
|
||||
4. **Chinese Fonts**: SVG export embeds fonts for correct display
|
||||
|
||||
## Related Resources
|
||||
|
||||
- [AntV Infographic Documentation](https://infographic.antv.vision/)
|
||||
- [Infographic API Reference](https://infographic.antv.vision/reference/infographic-api)
|
||||
- [Infographic Syntax Guide](https://infographic.antv.vision/learn/infographic-syntax)
|
||||
120
docs/plugins/actions/infographic-markdown.zh.md
Normal file
120
docs/plugins/actions/infographic-markdown.zh.md
Normal file
@@ -0,0 +1,120 @@
|
||||
# 信息图转 Markdown
|
||||
|
||||
> **版本:** 1.0.0 | **作者:** Fu-Jie
|
||||
|
||||
AI 驱动的信息图生成器,在前端渲染 SVG 并以 Data URL 图片格式直接嵌入到 Markdown 中。
|
||||
|
||||
## 概述
|
||||
|
||||
这个插件结合了 AI 文本分析能力和 AntV Infographic 可视化引擎,生成精美的信息图并以 Markdown 图片格式直接嵌入到聊天消息中。
|
||||
|
||||
### 主要特性
|
||||
|
||||
- :robot: **AI 驱动**: 自动分析文本并选择最佳的信息图模板
|
||||
- :bar_chart: **多种模板**: 支持 18+ 种信息图模板(列表、图表、对比等)
|
||||
- :framed_picture: **自包含**: SVG/PNG 以 Data URL 嵌入,无外部依赖
|
||||
- :memo: **Markdown 原生**: 结果是纯 Markdown 图片,兼容任何平台
|
||||
- :arrows_counterclockwise: **API 回写**: 通过 REST API 更新消息内容实现持久化
|
||||
|
||||
### 工作原理
|
||||
|
||||
```mermaid
|
||||
graph TD
|
||||
A[用户触发动作] --> B[Python 提取消息内容]
|
||||
B --> C[LLM 生成 Infographic 语法]
|
||||
C --> D[前端 JS 加载 AntV 库]
|
||||
D --> E[离屏渲染 SVG]
|
||||
E --> F[导出为 Data URL]
|
||||
F --> G[通过 API 更新消息]
|
||||
G --> H[显示为 Markdown 图片]
|
||||
```
|
||||
|
||||
## 安装
|
||||
|
||||
1. 下载 `infographic_markdown.py`(英文版)或 `infographic_markdown_cn.py`(中文版)
|
||||
2. 进入 **管理面板** → **设置** → **功能**
|
||||
3. 上传文件并配置设置
|
||||
4. 在聊天消息中使用动作按钮
|
||||
|
||||
## 配置选项
|
||||
|
||||
| 参数 | 类型 | 默认值 | 描述 |
|
||||
|------|------|--------|------|
|
||||
| `SHOW_STATUS` | bool | `true` | 是否显示操作状态 |
|
||||
| `MODEL_ID` | string | `""` | LLM 模型 ID(空则使用当前模型) |
|
||||
| `MIN_TEXT_LENGTH` | int | `50` | 最小文本长度要求 |
|
||||
| `MESSAGE_COUNT` | int | `1` | 用于生成的最近消息数量 |
|
||||
| `SVG_WIDTH` | int | `800` | 生成的 SVG 宽度(像素) |
|
||||
| `EXPORT_FORMAT` | string | `"svg"` | 导出格式:`svg` 或 `png` |
|
||||
|
||||
## 支持的模板
|
||||
|
||||
| 类别 | 模板名称 | 描述 |
|
||||
|------|----------|------|
|
||||
| 列表 | `list-grid` | 网格卡片 |
|
||||
| 列表 | `list-vertical` | 垂直列表 |
|
||||
| 树形 | `tree-vertical` | 垂直树 |
|
||||
| 树形 | `tree-horizontal` | 水平树 |
|
||||
| 思维导图 | `mindmap` | 思维导图 |
|
||||
| 流程 | `sequence-roadmap` | 路线图 |
|
||||
| 流程 | `sequence-zigzag` | 折线流程 |
|
||||
| 关系 | `relation-sankey` | 桑基图 |
|
||||
| 关系 | `relation-circle` | 圆形关系 |
|
||||
| 对比 | `compare-binary` | 二元对比 |
|
||||
| 分析 | `compare-swot` | SWOT 分析 |
|
||||
| 象限 | `quadrant-quarter` | 四象限图 |
|
||||
| 图表 | `chart-bar` | 条形图 |
|
||||
| 图表 | `chart-column` | 柱状图 |
|
||||
| 图表 | `chart-line` | 折线图 |
|
||||
| 图表 | `chart-pie` | 饼图 |
|
||||
| 图表 | `chart-doughnut` | 环形图 |
|
||||
| 图表 | `chart-area` | 面积图 |
|
||||
|
||||
## 使用示例
|
||||
|
||||
1. 在聊天中生成一些文本内容(或让 AI 生成)
|
||||
2. 点击 **📊 信息图转 Markdown** 动作按钮
|
||||
3. 等待 AI 分析和 SVG 渲染
|
||||
4. 信息图将以 Markdown 图片形式嵌入
|
||||
|
||||
## 技术细节
|
||||
|
||||
### Data URL 嵌入
|
||||
|
||||
插件将 SVG 图形转换为 Base64 编码的 Data URL:
|
||||
|
||||
```javascript
|
||||
const svgData = new XMLSerializer().serializeToString(svg);
|
||||
const base64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
const dataUri = "data:image/svg+xml;base64," + base64;
|
||||
const markdownImage = ``;
|
||||
```
|
||||
|
||||
### AntV toDataURL API
|
||||
|
||||
```javascript
|
||||
// 导出 SVG(推荐)
|
||||
const svgUrl = await instance.toDataURL({
|
||||
type: 'svg',
|
||||
embedResources: true
|
||||
});
|
||||
|
||||
// 导出 PNG
|
||||
const pngUrl = await instance.toDataURL({
|
||||
type: 'png',
|
||||
dpr: 2
|
||||
});
|
||||
```
|
||||
|
||||
## 注意事项
|
||||
|
||||
1. **浏览器兼容性**: 需要现代浏览器支持 ES6+ 和 Fetch API
|
||||
2. **网络依赖**: 首次使用需要从 CDN 加载 AntV Infographic 库
|
||||
3. **Data URL 大小**: Base64 编码会增加约 33% 的体积
|
||||
4. **中文字体**: SVG 导出时会嵌入字体以确保正确显示
|
||||
|
||||
## 相关资源
|
||||
|
||||
- [AntV Infographic 官方文档](https://infographic.antv.vision/)
|
||||
- [Infographic API 参考](https://infographic.antv.vision/reference/infographic-api)
|
||||
- [Infographic 语法规范](https://infographic.antv.vision/learn/infographic-syntax)
|
||||
@@ -315,7 +315,7 @@ class Action:
|
||||
if role == "user"
|
||||
else "Assistant" if role == "assistant" else role
|
||||
)
|
||||
aggregated_parts.append(f"[{role_label} Message {i}]\n{text_content}")
|
||||
aggregated_parts.append(f"{text_content}")
|
||||
|
||||
if not aggregated_parts:
|
||||
return body # Or handle error
|
||||
|
||||
@@ -326,7 +326,7 @@ class Action:
|
||||
if role == "user"
|
||||
else "助手" if role == "assistant" else role
|
||||
)
|
||||
aggregated_parts.append(f"[{role_label} 消息 {i}]\n{text_content}")
|
||||
aggregated_parts.append(f"{text_content}")
|
||||
|
||||
if not aggregated_parts:
|
||||
return body # 或者处理错误
|
||||
|
||||
@@ -24,11 +24,24 @@ You can configure the following settings via the **Valves** button in the plugin
|
||||
- `chat_title`: Use the conversation title (default).
|
||||
- `ai_generated`: Use AI to generate a short title based on the content.
|
||||
- `markdown_title`: Extract the first h1/h2 heading from the Markdown content.
|
||||
- **MERMAID_JS_URL**: URL for the Mermaid.js library (for diagram rendering).
|
||||
- **MAX_EMBED_IMAGE_MB**: Maximum image size to embed into DOCX (MB). Default: `20`.
|
||||
- **UI_LANGUAGE**: User interface language, supports `en` (English) and `zh` (Chinese). Default: `en`.
|
||||
- **FONT_LATIN**: Font name for Latin characters. Default: `Times New Roman`.
|
||||
- **FONT_ASIAN**: Font name for Asian characters. Default: `SimSun`.
|
||||
- **FONT_CODE**: Font name for code blocks. Default: `Consolas`.
|
||||
- **TABLE_HEADER_COLOR**: Table header background color (Hex without #). Default: `F2F2F2`.
|
||||
- **TABLE_ZEBRA_COLOR**: Table alternating row background color (Hex without #). Default: `FBFBFB`.
|
||||
- **MERMAID_JS_URL**: URL for the Mermaid.js library.
|
||||
- **MERMAID_JSZIP_URL**: URL for the JSZip library (required for DOCX manipulation).
|
||||
- **MERMAID_PNG_SCALE**: Scale factor for Mermaid PNG generation (Resolution). Default: `3.0`.
|
||||
- **MERMAID_DISPLAY_SCALE**: Scale factor for Mermaid visual size in Word. Default: `1.5`.
|
||||
- **MERMAID_OPTIMIZE_LAYOUT**: Automatically convert LR (Left-Right) flowcharts to TD (Top-Down). Default: `True`.
|
||||
- **MERMAID_CAPTIONS_ENABLE**: Enable/disable figure captions for Mermaid diagrams.
|
||||
- **MERMAID_DISPLAY_SCALE**: Scale factor for Mermaid visual size in Word. Default: `1.0`.
|
||||
- **MERMAID_OPTIMIZE_LAYOUT**: Automatically convert LR (Left-Right) flowcharts to TD (Top-Down). Default: `False`.
|
||||
- **MERMAID_BACKGROUND**: Background color for Mermaid diagrams (e.g., `white`, `transparent`). Default: `transparent`.
|
||||
- **MERMAID_CAPTIONS_ENABLE**: Enable/disable figure captions for Mermaid diagrams. Default: `True`.
|
||||
- **MERMAID_CAPTION_STYLE**: Paragraph style name for Mermaid captions. Default: `Caption`.
|
||||
- **MERMAID_CAPTION_PREFIX**: Caption prefix label (e.g., 'Figure'). Empty = auto-detect based on language.
|
||||
- **MATH_ENABLE**: Enable LaTeX math block conversion (`\[...\]` and `$$...$$`). Default: `True`.
|
||||
- **MATH_INLINE_DOLLAR_ENABLE**: Enable inline `$ ... $` math conversion. Default: `True`.
|
||||
|
||||
## Supported Markdown Syntax
|
||||
|
||||
@@ -75,6 +88,28 @@ All dependencies are declared in the plugin docstring.
|
||||
|
||||
## Changelog
|
||||
|
||||
### v0.4.0
|
||||
|
||||
- **Multi-language Support**: Added UI language switching (English/Chinese) with localized messages.
|
||||
- **Font & Style Configuration**: Customizable fonts for Latin/Asian text and code, plus table colors.
|
||||
- **Mermaid Enhancements**:
|
||||
- Hybrid client-side rendering (SVG+PNG) for better clarity and compatibility.
|
||||
- Configurable background color, fixing issues in dark mode.
|
||||
- Added error boundaries to prevent export failures on render errors.
|
||||
- **Performance**: Real-time progress updates for large document exports.
|
||||
- **Bug Fixes**:
|
||||
- Fixed parsing errors in Markdown tables containing code blocks or links.
|
||||
- Fixed parsing issues with underscores (`_`), asterisks (`*`), and tildes (`~`) used as long separators.
|
||||
- Enhanced error handling for image embedding.
|
||||
|
||||
### v0.3.0
|
||||
|
||||
- **Mermaid Diagrams**: Native support for rendering Mermaid diagrams as images in Word.
|
||||
- **Native Math**: Converts LaTeX equations to native Office MathML for editable equations.
|
||||
- **Citations**: Automatic bibliography generation and citation linking.
|
||||
- **Reasoning Removal**: Option to strip `<think>` blocks from the output.
|
||||
- **Table Enhancements**: Improved table formatting with smart column widths.
|
||||
|
||||
### v0.2.0
|
||||
- Added native math equation support (LaTeX → OMML)
|
||||
- Added Mermaid diagram rendering
|
||||
|
||||
@@ -20,15 +20,28 @@
|
||||
|
||||
您可以通过插件设置中的 **Valves** 按钮配置以下选项:
|
||||
|
||||
- **TITLE_SOURCE**:选择文档标题/文件名的生成方式。
|
||||
- **文档标题来源**:选择文档标题/文件名的生成方式。
|
||||
- `chat_title`:使用对话标题(默认)。
|
||||
- `ai_generated`:使用 AI 根据内容生成简短标题。
|
||||
- `markdown_title`:从 Markdown 内容中提取第一个一级或二级标题。
|
||||
- **MERMAID_JS_URL**:Mermaid.js 库的 URL(用于图表渲染)。
|
||||
- **MERMAID_PNG_SCALE**:Mermaid PNG 生成缩放比例(分辨率)。默认:`3.0`。
|
||||
- **MERMAID_DISPLAY_SCALE**:Mermaid 在 Word 中的显示比例(视觉大小)。默认:`1.5`。
|
||||
- **MERMAID_OPTIMIZE_LAYOUT**:自动将 LR(左右)流程图转换为 TD(上下)。默认:`True`。
|
||||
- **MERMAID_CAPTIONS_ENABLE**:启用/禁用 Mermaid 图表的图注。
|
||||
- **最大嵌入图片大小MB**:嵌入图片的最大大小 (MB)。默认:`20`。
|
||||
- **界面语言**:界面语言,支持 `en` (英语) 和 `zh` (中文)。默认:`zh`。
|
||||
- **英文字体**:英文字体名称。默认:`Calibri`。
|
||||
- **中文字体**:中文字体名称。默认:`SimSun`。
|
||||
- **代码字体**:代码字体名称。默认:`Consolas`。
|
||||
- **表头背景色**:表头背景色(十六进制,不带#)。默认:`F2F2F2`。
|
||||
- **表格隔行背景色**:表格隔行背景色(十六进制,不带#)。默认:`FBFBFB`。
|
||||
- **Mermaid_JS地址**:Mermaid.js 库的 URL。
|
||||
- **JSZip库地址**:JSZip 库的 URL(用于 DOCX 操作)。
|
||||
- **Mermaid_PNG缩放比例**:Mermaid PNG 生成缩放比例(分辨率)。默认:`3.0`。
|
||||
- **Mermaid显示比例**:Mermaid 在 Word 中的显示比例(视觉大小)。默认:`1.0`。
|
||||
- **Mermaid布局优化**:自动将 LR(左右)流程图转换为 TD(上下)。默认:`False`。
|
||||
- **Mermaid背景色**:Mermaid 图表背景色(如 `white`, `transparent`)。默认:`transparent`。
|
||||
- **启用Mermaid图注**:启用/禁用 Mermaid 图表的图注。默认:`True`。
|
||||
- **Mermaid图注样式**:Mermaid 图注的段落样式名称。默认:`Caption`。
|
||||
- **Mermaid图注前缀**:图注前缀(如 '图')。留空则根据语言自动检测。
|
||||
- **启用数学公式**:启用 LaTeX 数学公式块转换(`\[...\]` 和 `$$...$$`)。默认:`True`。
|
||||
- **启用行内公式**:启用行内 `$ ... $` 数学公式转换。默认:`True`。
|
||||
|
||||
## 支持的 Markdown 语法
|
||||
|
||||
@@ -75,6 +88,32 @@
|
||||
|
||||
## 更新日志
|
||||
|
||||
### v0.4.1
|
||||
|
||||
- **中文参数名**: 将插件配置项名称和描述全部汉化,提升中文用户体验。
|
||||
|
||||
### v0.4.0
|
||||
|
||||
- **多语言支持**: 新增界面语言切换(中文/英文),提示信息更友好。
|
||||
- **字体与样式配置**: 支持自定义中英文字体、代码字体以及表格颜色。
|
||||
- **Mermaid 增强**:
|
||||
- 客户端混合渲染(SVG+PNG),提高清晰度与兼容性。
|
||||
- 支持背景色配置,修复深色模式下的显示问题。
|
||||
- 增加错误边界,渲染失败时显示提示而非中断导出。
|
||||
- **性能优化**: 导出大型文档时提供实时进度反馈。
|
||||
- **Bug 修复**:
|
||||
- 修复 Markdown 表格中包含代码块或链接时的解析错误。
|
||||
- 修复下划线(`_`)、星号(`*`)、波浪号(`~`)作为长分隔符时的解析问题。
|
||||
- 增强图片嵌入的错误处理。
|
||||
|
||||
### v0.3.0
|
||||
|
||||
- **Mermaid 图表**: 原生支持将 Mermaid 图表渲染为 Word 中的图片。
|
||||
- **原生公式**: 将 LaTeX 公式转换为原生 Office MathML,支持在 Word 中编辑。
|
||||
- **引用参考**: 自动生成参考文献列表并链接引用。
|
||||
- **移除推理**: 选项支持从输出中移除 `<think>` 推理块。
|
||||
- **表格增强**: 改进表格格式,支持智能列宽。
|
||||
|
||||
### v0.2.0
|
||||
- 新增原生数学公式支持(LaTeX → OMML)
|
||||
- 新增 Mermaid 图表渲染
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
170
plugins/actions/js-render-poc/README.md
Normal file
170
plugins/actions/js-render-poc/README.md
Normal file
@@ -0,0 +1,170 @@
|
||||
# Infographic to Markdown
|
||||
|
||||
> **Version:** 1.0.0
|
||||
|
||||
AI-powered infographic generator that renders SVG on the frontend and embeds it directly into Markdown as a Data URL image.
|
||||
|
||||
## Overview
|
||||
|
||||
This plugin combines the power of AI text analysis with AntV Infographic visualization to create beautiful infographics that are embedded directly into chat messages as Markdown images.
|
||||
|
||||
### How It Works
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────┐
|
||||
│ Open WebUI Plugin │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 1. Python Action │
|
||||
│ ├── Receive message content │
|
||||
│ ├── Call LLM to generate Infographic syntax │
|
||||
│ └── Send __event_call__ to execute frontend JS │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 2. Browser JS (via __event_call__) │
|
||||
│ ├── Dynamically load AntV Infographic library │
|
||||
│ ├── Render SVG offscreen │
|
||||
│ ├── Export to Data URL via toDataURL() │
|
||||
│ └── Update message content via REST API │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 3. Markdown Rendering │
|
||||
│ └── Display  │
|
||||
└─────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## Features
|
||||
|
||||
- 🤖 **AI-Powered**: Automatically analyzes text and selects the best infographic template
|
||||
- 📊 **Multiple Templates**: Supports 18+ infographic templates (lists, charts, comparisons, etc.)
|
||||
- 🖼️ **Self-Contained**: SVG/PNG embedded as Data URL, no external dependencies
|
||||
- 📝 **Markdown Native**: Results are pure Markdown images, compatible everywhere
|
||||
- 🔄 **API Writeback**: Updates message content via REST API for persistence
|
||||
|
||||
## Plugins in This Directory
|
||||
|
||||
### 1. `infographic_markdown.py` - Main Plugin ⭐
|
||||
- **Purpose**: Production use
|
||||
- **Features**: Full AI + AntV Infographic + Data URL embedding
|
||||
|
||||
### 2. `js_render_poc.py` - Proof of Concept
|
||||
- **Purpose**: Learning and testing
|
||||
- **Features**: Simple SVG creation demo, `__event_call__` pattern
|
||||
|
||||
## Configuration (Valves)
|
||||
|
||||
| Parameter | Type | Default | Description |
|
||||
|-----------|------|---------|-------------|
|
||||
| `SHOW_STATUS` | bool | `true` | Show operation status updates |
|
||||
| `MODEL_ID` | string | `""` | LLM model ID (empty = use current model) |
|
||||
| `MIN_TEXT_LENGTH` | int | `50` | Minimum text length required |
|
||||
| `MESSAGE_COUNT` | int | `1` | Number of recent messages to use |
|
||||
| `SVG_WIDTH` | int | `800` | Width of generated SVG (pixels) |
|
||||
| `EXPORT_FORMAT` | string | `"svg"` | Export format: `svg` or `png` |
|
||||
|
||||
## Supported Templates
|
||||
|
||||
| Category | Template | Description |
|
||||
|----------|----------|-------------|
|
||||
| List | `list-grid` | Grid cards |
|
||||
| List | `list-vertical` | Vertical list |
|
||||
| Tree | `tree-vertical` | Vertical tree |
|
||||
| Tree | `tree-horizontal` | Horizontal tree |
|
||||
| Mind Map | `mindmap` | Mind map |
|
||||
| Process | `sequence-roadmap` | Roadmap |
|
||||
| Process | `sequence-zigzag` | Zigzag process |
|
||||
| Relation | `relation-sankey` | Sankey diagram |
|
||||
| Relation | `relation-circle` | Circular relation |
|
||||
| Compare | `compare-binary` | Binary comparison |
|
||||
| Analysis | `compare-swot` | SWOT analysis |
|
||||
| Quadrant | `quadrant-quarter` | Quadrant chart |
|
||||
| Chart | `chart-bar` | Bar chart |
|
||||
| Chart | `chart-column` | Column chart |
|
||||
| Chart | `chart-line` | Line chart |
|
||||
| Chart | `chart-pie` | Pie chart |
|
||||
| Chart | `chart-doughnut` | Doughnut chart |
|
||||
| Chart | `chart-area` | Area chart |
|
||||
|
||||
## Syntax Examples
|
||||
|
||||
### Grid List
|
||||
```infographic
|
||||
infographic list-grid
|
||||
data
|
||||
title Project Overview
|
||||
items
|
||||
- label Module A
|
||||
desc Description of module A
|
||||
- label Module B
|
||||
desc Description of module B
|
||||
```
|
||||
|
||||
### Binary Comparison
|
||||
```infographic
|
||||
infographic compare-binary
|
||||
data
|
||||
title Pros vs Cons
|
||||
items
|
||||
- label Pros
|
||||
children
|
||||
- label Strong R&D
|
||||
desc Technology leadership
|
||||
- label Cons
|
||||
children
|
||||
- label Weak brand
|
||||
desc Insufficient marketing
|
||||
```
|
||||
|
||||
### Bar Chart
|
||||
```infographic
|
||||
infographic chart-bar
|
||||
data
|
||||
title Quarterly Revenue
|
||||
items
|
||||
- label Q1
|
||||
value 120
|
||||
- label Q2
|
||||
value 150
|
||||
```
|
||||
|
||||
## Technical Details
|
||||
|
||||
### Data URL Embedding
|
||||
```javascript
|
||||
// SVG to Base64 Data URL
|
||||
const svgData = new XMLSerializer().serializeToString(svg);
|
||||
const base64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
const dataUri = "data:image/svg+xml;base64," + base64;
|
||||
|
||||
// Markdown image syntax
|
||||
const markdownImage = ``;
|
||||
```
|
||||
|
||||
### AntV toDataURL API
|
||||
```javascript
|
||||
// Export as SVG (recommended, supports embedded resources)
|
||||
const svgUrl = await instance.toDataURL({
|
||||
type: 'svg',
|
||||
embedResources: true
|
||||
});
|
||||
|
||||
// Export as PNG (more compatible but larger)
|
||||
const pngUrl = await instance.toDataURL({
|
||||
type: 'png',
|
||||
dpr: 2
|
||||
});
|
||||
```
|
||||
|
||||
## Notes
|
||||
|
||||
1. **Browser Compatibility**: Requires modern browsers with ES6+ and Fetch API support
|
||||
2. **Network Dependency**: First use requires loading AntV library from CDN
|
||||
3. **Data URL Size**: Base64 encoding increases size by ~33%
|
||||
4. **Chinese Fonts**: SVG export embeds fonts for correct display
|
||||
|
||||
## Related Resources
|
||||
|
||||
- [AntV Infographic Documentation](https://infographic.antv.vision/)
|
||||
- [Infographic API Reference](https://infographic.antv.vision/reference/infographic-api)
|
||||
- [Infographic Syntax Guide](https://infographic.antv.vision/learn/infographic-syntax)
|
||||
|
||||
## License
|
||||
|
||||
MIT License
|
||||
174
plugins/actions/js-render-poc/README_CN.md
Normal file
174
plugins/actions/js-render-poc/README_CN.md
Normal file
@@ -0,0 +1,174 @@
|
||||
# 信息图转 Markdown
|
||||
|
||||
> **版本:** 1.0.0
|
||||
|
||||
AI 驱动的信息图生成器,在前端渲染 SVG 并以 Data URL 图片格式直接嵌入到 Markdown 中。
|
||||
|
||||
## 概述
|
||||
|
||||
这个插件结合了 AI 文本分析能力和 AntV Infographic 可视化引擎,生成精美的信息图并以 Markdown 图片格式直接嵌入到聊天消息中。
|
||||
|
||||
### 工作原理
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────┐
|
||||
│ Open WebUI 插件 │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 1. Python Action │
|
||||
│ ├── 接收消息内容 │
|
||||
│ ├── 调用 LLM 生成 Infographic 语法 │
|
||||
│ └── 发送 __event_call__ 执行前端 JS │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 2. 浏览器 JS (通过 __event_call__) │
|
||||
│ ├── 动态加载 AntV Infographic 库 │
|
||||
│ ├── 离屏渲染 SVG │
|
||||
│ ├── 使用 toDataURL() 导出 Data URL │
|
||||
│ └── 通过 REST API 更新消息内容 │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 3. Markdown 渲染 │
|
||||
│ └── 显示  │
|
||||
└─────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## 功能特点
|
||||
|
||||
- 🤖 **AI 驱动**: 自动分析文本并选择最佳的信息图模板
|
||||
- 📊 **多种模板**: 支持 18+ 种信息图模板(列表、图表、对比等)
|
||||
- 🖼️ **自包含**: SVG/PNG 以 Data URL 嵌入,无外部依赖
|
||||
- 📝 **Markdown 原生**: 结果是纯 Markdown 图片,兼容任何平台
|
||||
- 🔄 **API 回写**: 通过 REST API 更新消息内容实现持久化
|
||||
|
||||
## 目录中的插件
|
||||
|
||||
### 1. `infographic_markdown.py` - 主插件 ⭐
|
||||
- **用途**: 生产使用
|
||||
- **功能**: 完整的 AI + AntV Infographic + Data URL 嵌入
|
||||
|
||||
### 2. `infographic_markdown_cn.py` - 主插件(中文版)
|
||||
- **用途**: 生产使用
|
||||
- **功能**: 与英文版相同,界面文字为中文
|
||||
|
||||
### 3. `js_render_poc.py` - 概念验证
|
||||
- **用途**: 学习和测试
|
||||
- **功能**: 简单的 SVG 创建演示,`__event_call__` 模式
|
||||
|
||||
## 配置选项 (Valves)
|
||||
|
||||
| 参数 | 类型 | 默认值 | 描述 |
|
||||
|------|------|--------|------|
|
||||
| `SHOW_STATUS` | bool | `true` | 是否显示操作状态 |
|
||||
| `MODEL_ID` | string | `""` | LLM 模型 ID(空则使用当前模型) |
|
||||
| `MIN_TEXT_LENGTH` | int | `50` | 最小文本长度要求 |
|
||||
| `MESSAGE_COUNT` | int | `1` | 用于生成的最近消息数量 |
|
||||
| `SVG_WIDTH` | int | `800` | 生成的 SVG 宽度(像素) |
|
||||
| `EXPORT_FORMAT` | string | `"svg"` | 导出格式:`svg` 或 `png` |
|
||||
|
||||
## 支持的模板
|
||||
|
||||
| 类别 | 模板名称 | 描述 |
|
||||
|------|----------|------|
|
||||
| 列表 | `list-grid` | 网格卡片 |
|
||||
| 列表 | `list-vertical` | 垂直列表 |
|
||||
| 树形 | `tree-vertical` | 垂直树 |
|
||||
| 树形 | `tree-horizontal` | 水平树 |
|
||||
| 思维导图 | `mindmap` | 思维导图 |
|
||||
| 流程 | `sequence-roadmap` | 路线图 |
|
||||
| 流程 | `sequence-zigzag` | 折线流程 |
|
||||
| 关系 | `relation-sankey` | 桑基图 |
|
||||
| 关系 | `relation-circle` | 圆形关系 |
|
||||
| 对比 | `compare-binary` | 二元对比 |
|
||||
| 分析 | `compare-swot` | SWOT 分析 |
|
||||
| 象限 | `quadrant-quarter` | 四象限图 |
|
||||
| 图表 | `chart-bar` | 条形图 |
|
||||
| 图表 | `chart-column` | 柱状图 |
|
||||
| 图表 | `chart-line` | 折线图 |
|
||||
| 图表 | `chart-pie` | 饼图 |
|
||||
| 图表 | `chart-doughnut` | 环形图 |
|
||||
| 图表 | `chart-area` | 面积图 |
|
||||
|
||||
## 语法示例
|
||||
|
||||
### 网格列表
|
||||
```infographic
|
||||
infographic list-grid
|
||||
data
|
||||
title 项目概览
|
||||
items
|
||||
- label 模块一
|
||||
desc 这是第一个模块的描述
|
||||
- label 模块二
|
||||
desc 这是第二个模块的描述
|
||||
```
|
||||
|
||||
### 二元对比
|
||||
```infographic
|
||||
infographic compare-binary
|
||||
data
|
||||
title 优劣对比
|
||||
items
|
||||
- label 优势
|
||||
children
|
||||
- label 研发能力强
|
||||
desc 技术领先
|
||||
- label 劣势
|
||||
children
|
||||
- label 品牌曝光不足
|
||||
desc 营销力度不够
|
||||
```
|
||||
|
||||
### 条形图
|
||||
```infographic
|
||||
infographic chart-bar
|
||||
data
|
||||
title 季度收入
|
||||
items
|
||||
- label Q1
|
||||
value 120
|
||||
- label Q2
|
||||
value 150
|
||||
```
|
||||
|
||||
## 技术细节
|
||||
|
||||
### Data URL 嵌入
|
||||
```javascript
|
||||
// SVG 转 Base64 Data URL
|
||||
const svgData = new XMLSerializer().serializeToString(svg);
|
||||
const base64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
const dataUri = "data:image/svg+xml;base64," + base64;
|
||||
|
||||
// Markdown 图片语法
|
||||
const markdownImage = ``;
|
||||
```
|
||||
|
||||
### AntV toDataURL API
|
||||
```javascript
|
||||
// 导出 SVG(推荐,支持嵌入资源)
|
||||
const svgUrl = await instance.toDataURL({
|
||||
type: 'svg',
|
||||
embedResources: true
|
||||
});
|
||||
|
||||
// 导出 PNG(更兼容但体积更大)
|
||||
const pngUrl = await instance.toDataURL({
|
||||
type: 'png',
|
||||
dpr: 2
|
||||
});
|
||||
```
|
||||
|
||||
## 注意事项
|
||||
|
||||
1. **浏览器兼容性**: 需要现代浏览器支持 ES6+ 和 Fetch API
|
||||
2. **网络依赖**: 首次使用需要从 CDN 加载 AntV Infographic 库
|
||||
3. **Data URL 大小**: Base64 编码会增加约 33% 的体积
|
||||
4. **中文字体**: SVG 导出时会嵌入字体以确保正确显示
|
||||
|
||||
## 相关资源
|
||||
|
||||
- [AntV Infographic 官方文档](https://infographic.antv.vision/)
|
||||
- [Infographic API 参考](https://infographic.antv.vision/reference/infographic-api)
|
||||
- [Infographic 语法规范](https://infographic.antv.vision/learn/infographic-syntax)
|
||||
|
||||
## 许可证
|
||||
|
||||
MIT License
|
||||
592
plugins/actions/js-render-poc/infographic_markdown.py
Normal file
592
plugins/actions/js-render-poc/infographic_markdown.py
Normal file
@@ -0,0 +1,592 @@
|
||||
"""
|
||||
title: 📊 Infographic to Markdown
|
||||
author: Fu-Jie
|
||||
version: 1.0.0
|
||||
description: AI生成信息图语法,前端渲染SVG并转换为Markdown图片格式嵌入消息。支持AntV Infographic模板。
|
||||
"""
|
||||
|
||||
import time
|
||||
import json
|
||||
import logging
|
||||
import re
|
||||
from typing import Optional, Callable, Awaitable, Any, Dict
|
||||
from pydantic import BaseModel, Field
|
||||
from fastapi import Request
|
||||
from datetime import datetime
|
||||
|
||||
from open_webui.utils.chat import generate_chat_completion
|
||||
from open_webui.models.users import Users
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# =================================================================
|
||||
# LLM Prompts
|
||||
# =================================================================
|
||||
|
||||
SYSTEM_PROMPT_INFOGRAPHIC = """
|
||||
You are a professional infographic design expert who can analyze user-provided text content and convert it into AntV Infographic syntax format.
|
||||
|
||||
## Infographic Syntax Specification
|
||||
|
||||
Infographic syntax is a Mermaid-like declarative syntax for describing infographic templates, data, and themes.
|
||||
|
||||
### Syntax Rules
|
||||
- Entry uses `infographic <template-name>`
|
||||
- Key-value pairs are separated by spaces, **absolutely NO colons allowed**
|
||||
- Use two spaces for indentation
|
||||
- Object arrays use `-` with line breaks
|
||||
|
||||
⚠️ **IMPORTANT WARNING: This is NOT YAML format!**
|
||||
- ❌ Wrong: `children:` `items:` `data:` (with colons)
|
||||
- ✅ Correct: `children` `items` `data` (without colons)
|
||||
|
||||
### Template Library & Selection Guide
|
||||
|
||||
Choose the most appropriate template based on the content structure:
|
||||
|
||||
#### 1. List & Hierarchy
|
||||
- **List**: `list-grid` (Grid Cards), `list-vertical` (Vertical List)
|
||||
- **Tree**: `tree-vertical` (Vertical Tree), `tree-horizontal` (Horizontal Tree)
|
||||
- **Mindmap**: `mindmap` (Mind Map)
|
||||
|
||||
#### 2. Sequence & Relationship
|
||||
- **Process**: `sequence-roadmap` (Roadmap), `sequence-zigzag` (Zigzag Process)
|
||||
- **Relationship**: `relation-sankey` (Sankey Diagram), `relation-circle` (Circular)
|
||||
|
||||
#### 3. Comparison & Analysis
|
||||
- **Comparison**: `compare-binary` (Binary Comparison)
|
||||
- **Analysis**: `compare-swot` (SWOT Analysis), `quadrant-quarter` (Quadrant Chart)
|
||||
|
||||
#### 4. Charts & Data
|
||||
- **Charts**: `chart-bar`, `chart-column`, `chart-line`, `chart-pie`, `chart-doughnut`, `chart-area`
|
||||
|
||||
### Data Structure Examples
|
||||
|
||||
#### A. Standard List/Tree
|
||||
```infographic
|
||||
infographic list-grid
|
||||
data
|
||||
title Project Modules
|
||||
items
|
||||
- label Module A
|
||||
desc Description of A
|
||||
- label Module B
|
||||
desc Description of B
|
||||
```
|
||||
|
||||
#### B. Binary Comparison
|
||||
```infographic
|
||||
infographic compare-binary
|
||||
data
|
||||
title Advantages vs Disadvantages
|
||||
items
|
||||
- label Advantages
|
||||
children
|
||||
- label Strong R&D
|
||||
desc Leading technology
|
||||
- label Disadvantages
|
||||
children
|
||||
- label Weak brand
|
||||
desc Insufficient marketing
|
||||
```
|
||||
|
||||
#### C. Charts
|
||||
```infographic
|
||||
infographic chart-bar
|
||||
data
|
||||
title Quarterly Revenue
|
||||
items
|
||||
- label Q1
|
||||
value 120
|
||||
- label Q2
|
||||
value 150
|
||||
```
|
||||
|
||||
### Common Data Fields
|
||||
- `label`: Main title/label (Required)
|
||||
- `desc`: Description text (max 30 Chinese chars / 60 English chars for `list-grid`)
|
||||
- `value`: Numeric value (for charts)
|
||||
- `children`: Nested items
|
||||
|
||||
## Output Requirements
|
||||
1. **Language**: Output content in the user's language.
|
||||
2. **Format**: Wrap output in ```infographic ... ```.
|
||||
3. **No Colons**: Do NOT use colons after keys.
|
||||
4. **Indentation**: Use 2 spaces.
|
||||
"""
|
||||
|
||||
USER_PROMPT_GENERATE = """
|
||||
Please analyze the following text content and convert its core information into AntV Infographic syntax format.
|
||||
|
||||
---
|
||||
**User Context:**
|
||||
User Name: {user_name}
|
||||
Current Date/Time: {current_date_time_str}
|
||||
User Language: {user_language}
|
||||
---
|
||||
|
||||
**Text Content:**
|
||||
{long_text_content}
|
||||
|
||||
Please select the most appropriate infographic template based on text characteristics and output standard infographic syntax.
|
||||
|
||||
**Important Note:**
|
||||
- If using `list-grid` format, ensure each card's `desc` description is limited to **maximum 30 Chinese characters** (or **approximately 60 English characters**).
|
||||
- Descriptions should be concise and highlight key points.
|
||||
"""
|
||||
|
||||
|
||||
class Action:
|
||||
class Valves(BaseModel):
|
||||
SHOW_STATUS: bool = Field(
|
||||
default=True, description="Show operation status updates in chat interface."
|
||||
)
|
||||
MODEL_ID: str = Field(
|
||||
default="",
|
||||
description="LLM model ID for text analysis. If empty, uses current conversation model.",
|
||||
)
|
||||
MIN_TEXT_LENGTH: int = Field(
|
||||
default=50,
|
||||
description="Minimum text length (characters) required for infographic analysis.",
|
||||
)
|
||||
MESSAGE_COUNT: int = Field(
|
||||
default=1,
|
||||
description="Number of recent messages to use for generation.",
|
||||
)
|
||||
SVG_WIDTH: int = Field(
|
||||
default=800,
|
||||
description="Width of generated SVG in pixels.",
|
||||
)
|
||||
EXPORT_FORMAT: str = Field(
|
||||
default="svg",
|
||||
description="Export format: 'svg' or 'png'.",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _extract_chat_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""Extract chat_id from body or metadata"""
|
||||
if isinstance(body, dict):
|
||||
chat_id = body.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
chat_id = body_metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
chat_id = metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_message_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""Extract message_id from body or metadata"""
|
||||
if isinstance(body, dict):
|
||||
message_id = body.get("id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
message_id = body_metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
message_id = metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_infographic_syntax(self, llm_output: str) -> str:
|
||||
"""Extract infographic syntax from LLM output"""
|
||||
match = re.search(r"```infographic\s*(.*?)\s*```", llm_output, re.DOTALL)
|
||||
if match:
|
||||
return match.group(1).strip()
|
||||
else:
|
||||
logger.warning("LLM output did not follow expected format, treating entire output as syntax.")
|
||||
return llm_output.strip()
|
||||
|
||||
def _extract_text_content(self, content) -> str:
|
||||
"""Extract text from message content, supporting multimodal formats"""
|
||||
if isinstance(content, str):
|
||||
return content
|
||||
elif isinstance(content, list):
|
||||
text_parts = []
|
||||
for item in content:
|
||||
if isinstance(item, dict) and item.get("type") == "text":
|
||||
text_parts.append(item.get("text", ""))
|
||||
elif isinstance(item, str):
|
||||
text_parts.append(item)
|
||||
return "\n".join(text_parts)
|
||||
return str(content) if content else ""
|
||||
|
||||
async def _emit_status(self, emitter, description: str, done: bool = False):
|
||||
"""Send status update event"""
|
||||
if self.valves.SHOW_STATUS and emitter:
|
||||
await emitter(
|
||||
{"type": "status", "data": {"description": description, "done": done}}
|
||||
)
|
||||
|
||||
def _generate_js_code(
|
||||
self,
|
||||
unique_id: str,
|
||||
chat_id: str,
|
||||
message_id: str,
|
||||
infographic_syntax: str,
|
||||
svg_width: int,
|
||||
export_format: str,
|
||||
) -> str:
|
||||
"""Generate JavaScript code for frontend SVG rendering"""
|
||||
|
||||
# Escape the syntax for JS embedding
|
||||
syntax_escaped = (
|
||||
infographic_syntax
|
||||
.replace("\\", "\\\\")
|
||||
.replace("`", "\\`")
|
||||
.replace("${", "\\${")
|
||||
.replace("</script>", "<\\/script>")
|
||||
)
|
||||
|
||||
# Template mapping (same as infographic.py)
|
||||
template_mapping_js = """
|
||||
const TEMPLATE_MAPPING = {
|
||||
'list-grid': 'list-grid-compact-card',
|
||||
'list-vertical': 'list-column-simple-vertical-arrow',
|
||||
'tree-vertical': 'hierarchy-tree-tech-style-capsule-item',
|
||||
'tree-horizontal': 'hierarchy-tree-lr-tech-style-capsule-item',
|
||||
'mindmap': 'hierarchy-mindmap-branch-gradient-capsule-item',
|
||||
'sequence-roadmap': 'sequence-roadmap-vertical-simple',
|
||||
'sequence-zigzag': 'sequence-horizontal-zigzag-simple',
|
||||
'sequence-horizontal': 'sequence-horizontal-zigzag-simple',
|
||||
'relation-sankey': 'relation-sankey-simple',
|
||||
'relation-circle': 'relation-circle-icon-badge',
|
||||
'compare-binary': 'compare-binary-horizontal-simple-vs',
|
||||
'compare-swot': 'compare-swot',
|
||||
'quadrant-quarter': 'quadrant-quarter-simple-card',
|
||||
'statistic-card': 'list-grid-compact-card',
|
||||
'chart-bar': 'chart-bar-plain-text',
|
||||
'chart-column': 'chart-column-simple',
|
||||
'chart-line': 'chart-line-plain-text',
|
||||
'chart-area': 'chart-area-simple',
|
||||
'chart-pie': 'chart-pie-plain-text',
|
||||
'chart-doughnut': 'chart-pie-donut-plain-text'
|
||||
};
|
||||
"""
|
||||
|
||||
return f"""
|
||||
(async function() {{
|
||||
const uniqueId = "{unique_id}";
|
||||
const chatId = "{chat_id}";
|
||||
const messageId = "{message_id}";
|
||||
const svgWidth = {svg_width};
|
||||
const exportFormat = "{export_format}";
|
||||
|
||||
console.log("[Infographic Markdown] Starting render...");
|
||||
console.log("[Infographic Markdown] chatId:", chatId, "messageId:", messageId);
|
||||
|
||||
try {{
|
||||
// Load AntV Infographic if not loaded
|
||||
if (typeof AntVInfographic === 'undefined') {{
|
||||
console.log("[Infographic Markdown] Loading AntV Infographic library...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://unpkg.com/@antv/infographic@latest/dist/infographic.min.js';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
console.log("[Infographic Markdown] Library loaded.");
|
||||
}}
|
||||
|
||||
const {{ Infographic }} = AntVInfographic;
|
||||
|
||||
// Get infographic syntax
|
||||
let syntaxContent = `{syntax_escaped}`;
|
||||
console.log("[Infographic Markdown] Original syntax:", syntaxContent.substring(0, 200) + "...");
|
||||
|
||||
// Clean up syntax
|
||||
const backtick = String.fromCharCode(96);
|
||||
const prefix = backtick + backtick + backtick + 'infographic';
|
||||
const simplePrefix = backtick + backtick + backtick;
|
||||
|
||||
if (syntaxContent.toLowerCase().startsWith(prefix)) {{
|
||||
syntaxContent = syntaxContent.substring(prefix.length).trim();
|
||||
}} else if (syntaxContent.startsWith(simplePrefix)) {{
|
||||
syntaxContent = syntaxContent.substring(simplePrefix.length).trim();
|
||||
}}
|
||||
|
||||
if (syntaxContent.endsWith(simplePrefix)) {{
|
||||
syntaxContent = syntaxContent.substring(0, syntaxContent.length - simplePrefix.length).trim();
|
||||
}}
|
||||
|
||||
// Fix colons after keywords
|
||||
syntaxContent = syntaxContent.replace(/^(data|items|children|theme|config):/gm, '$1');
|
||||
syntaxContent = syntaxContent.replace(/(\\s)(children|items):/g, '$1$2');
|
||||
|
||||
// Ensure infographic prefix
|
||||
if (!syntaxContent.trim().toLowerCase().startsWith('infographic')) {{
|
||||
syntaxContent = 'infographic list-grid\\n' + syntaxContent;
|
||||
}}
|
||||
|
||||
// Apply template mapping
|
||||
{template_mapping_js}
|
||||
|
||||
for (const [key, value] of Object.entries(TEMPLATE_MAPPING)) {{
|
||||
const regex = new RegExp(`infographic\\\\s+${{key}}(?=\\\\s|$)`, 'i');
|
||||
if (regex.test(syntaxContent)) {{
|
||||
console.log(`[Infographic Markdown] Auto-mapping: ${{key}} -> ${{value}}`);
|
||||
syntaxContent = syntaxContent.replace(regex, `infographic ${{value}}`);
|
||||
break;
|
||||
}}
|
||||
}}
|
||||
|
||||
console.log("[Infographic Markdown] Cleaned syntax:", syntaxContent.substring(0, 200) + "...");
|
||||
|
||||
// Create offscreen container
|
||||
const container = document.createElement('div');
|
||||
container.id = 'infographic-offscreen-' + uniqueId;
|
||||
container.style.cssText = 'position:absolute;left:-9999px;top:-9999px;width:' + svgWidth + 'px;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// Create and render infographic
|
||||
const instance = new Infographic({{
|
||||
container: '#' + container.id,
|
||||
width: svgWidth,
|
||||
padding: 24,
|
||||
}});
|
||||
|
||||
console.log("[Infographic Markdown] Rendering infographic...");
|
||||
instance.render(syntaxContent);
|
||||
|
||||
// Wait for render and export
|
||||
await new Promise(resolve => setTimeout(resolve, 1000));
|
||||
|
||||
let dataUrl;
|
||||
if (exportFormat === 'png') {{
|
||||
dataUrl = await instance.toDataURL({{ type: 'png', dpr: 2 }});
|
||||
}} else {{
|
||||
dataUrl = await instance.toDataURL({{ type: 'svg', embedResources: true }});
|
||||
}}
|
||||
|
||||
console.log("[Infographic Markdown] Data URL generated, length:", dataUrl.length);
|
||||
|
||||
// Cleanup
|
||||
instance.destroy();
|
||||
document.body.removeChild(container);
|
||||
|
||||
// Generate markdown image
|
||||
const markdownImage = ``;
|
||||
|
||||
// Update message via API
|
||||
if (chatId && messageId) {{
|
||||
const token = localStorage.getItem("token");
|
||||
|
||||
// Get current message content
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("Failed to get chat data: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
let originalContent = "";
|
||||
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
const targetMsg = chatData.chat.messages.find(m => m.id === messageId);
|
||||
if (targetMsg && targetMsg.content) {{
|
||||
originalContent = targetMsg.content;
|
||||
}}
|
||||
}}
|
||||
|
||||
// Remove existing infographic images
|
||||
const infographicPattern = /\\n*!\\[📊[^\\]]*\\]\\(data:image\\/[^)]+\\)/g;
|
||||
let cleanedContent = originalContent.replace(infographicPattern, "");
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
|
||||
// Append new image
|
||||
const newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// Update message
|
||||
const updateResponse = await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: newContent }}
|
||||
}})
|
||||
}});
|
||||
|
||||
if (updateResponse.ok) {{
|
||||
console.log("[Infographic Markdown] ✅ Message updated successfully!");
|
||||
}} else {{
|
||||
console.error("[Infographic Markdown] API error:", updateResponse.status);
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[Infographic Markdown] ⚠️ Missing chatId or messageId");
|
||||
}}
|
||||
|
||||
}} catch (error) {{
|
||||
console.error("[Infographic Markdown] Error:", error);
|
||||
}}
|
||||
}})();
|
||||
"""
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: dict = None,
|
||||
__event_emitter__=None,
|
||||
__event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__metadata__: Optional[dict] = None,
|
||||
__request__: Request = None,
|
||||
) -> dict:
|
||||
"""
|
||||
Generate infographic using AntV and embed as Markdown image.
|
||||
"""
|
||||
logger.info("Action: Infographic to Markdown started")
|
||||
|
||||
# Get user information
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
user_language = __user__[0].get("language", "en") if __user__ else "en"
|
||||
user_name = __user__[0].get("name", "User") if __user__[0] else "User"
|
||||
user_id = __user__[0].get("id", "unknown_user") if __user__ else "unknown_user"
|
||||
elif isinstance(__user__, dict):
|
||||
user_language = __user__.get("language", "en")
|
||||
user_name = __user__.get("name", "User")
|
||||
user_id = __user__.get("id", "unknown_user")
|
||||
else:
|
||||
user_language = "en"
|
||||
user_name = "User"
|
||||
user_id = "unknown_user"
|
||||
|
||||
# Get current time
|
||||
now = datetime.now()
|
||||
current_date_time_str = now.strftime("%Y-%m-%d %H:%M:%S")
|
||||
|
||||
try:
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
raise ValueError("No messages available.")
|
||||
|
||||
# Get recent messages
|
||||
message_count = min(self.valves.MESSAGE_COUNT, len(messages))
|
||||
recent_messages = messages[-message_count:]
|
||||
|
||||
# Aggregate content
|
||||
aggregated_parts = []
|
||||
for msg in recent_messages:
|
||||
text_content = self._extract_text_content(msg.get("content"))
|
||||
if text_content:
|
||||
aggregated_parts.append(text_content)
|
||||
|
||||
if not aggregated_parts:
|
||||
raise ValueError("No text content found in messages.")
|
||||
|
||||
long_text_content = "\n\n---\n\n".join(aggregated_parts)
|
||||
|
||||
# Remove existing HTML blocks
|
||||
parts = re.split(r"```html.*?```", long_text_content, flags=re.DOTALL)
|
||||
clean_content = ""
|
||||
for part in reversed(parts):
|
||||
if part.strip():
|
||||
clean_content = part.strip()
|
||||
break
|
||||
|
||||
if not clean_content:
|
||||
clean_content = long_text_content.strip()
|
||||
|
||||
# Check minimum length
|
||||
if len(clean_content) < self.valves.MIN_TEXT_LENGTH:
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
f"⚠️ 内容太短 ({len(clean_content)} 字符),至少需要 {self.valves.MIN_TEXT_LENGTH} 字符",
|
||||
True,
|
||||
)
|
||||
return body
|
||||
|
||||
await self._emit_status(__event_emitter__, "📊 正在分析内容...", False)
|
||||
|
||||
# Generate infographic syntax via LLM
|
||||
formatted_user_prompt = USER_PROMPT_GENERATE.format(
|
||||
user_name=user_name,
|
||||
current_date_time_str=current_date_time_str,
|
||||
user_language=user_language,
|
||||
long_text_content=clean_content,
|
||||
)
|
||||
|
||||
target_model = self.valves.MODEL_ID or body.get("model")
|
||||
|
||||
llm_payload = {
|
||||
"model": target_model,
|
||||
"messages": [
|
||||
{"role": "system", "content": SYSTEM_PROMPT_INFOGRAPHIC},
|
||||
{"role": "user", "content": formatted_user_prompt},
|
||||
],
|
||||
"stream": False,
|
||||
}
|
||||
|
||||
user_obj = Users.get_user_by_id(user_id)
|
||||
if not user_obj:
|
||||
raise ValueError(f"Unable to get user object: {user_id}")
|
||||
|
||||
await self._emit_status(__event_emitter__, "📊 AI 正在生成信息图语法...", False)
|
||||
|
||||
llm_response = await generate_chat_completion(__request__, llm_payload, user_obj)
|
||||
|
||||
if not llm_response or "choices" not in llm_response or not llm_response["choices"]:
|
||||
raise ValueError("Invalid LLM response.")
|
||||
|
||||
assistant_content = llm_response["choices"][0]["message"]["content"]
|
||||
infographic_syntax = self._extract_infographic_syntax(assistant_content)
|
||||
|
||||
logger.info(f"Generated syntax: {infographic_syntax[:200]}...")
|
||||
|
||||
# Extract IDs for API callback
|
||||
chat_id = self._extract_chat_id(body, __metadata__)
|
||||
message_id = self._extract_message_id(body, __metadata__)
|
||||
unique_id = f"ig_{int(time.time() * 1000)}"
|
||||
|
||||
await self._emit_status(__event_emitter__, "📊 正在渲染 SVG...", False)
|
||||
|
||||
# Execute JS to render and embed
|
||||
if __event_call__:
|
||||
js_code = self._generate_js_code(
|
||||
unique_id=unique_id,
|
||||
chat_id=chat_id,
|
||||
message_id=message_id,
|
||||
infographic_syntax=infographic_syntax,
|
||||
svg_width=self.valves.SVG_WIDTH,
|
||||
export_format=self.valves.EXPORT_FORMAT,
|
||||
)
|
||||
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
|
||||
await self._emit_status(__event_emitter__, "✅ 信息图生成完成!", True)
|
||||
logger.info("Infographic to Markdown completed")
|
||||
|
||||
except Exception as e:
|
||||
error_message = f"Infographic generation failed: {str(e)}"
|
||||
logger.error(error_message, exc_info=True)
|
||||
await self._emit_status(__event_emitter__, f"❌ {error_message}", True)
|
||||
|
||||
return body
|
||||
592
plugins/actions/js-render-poc/infographic_markdown_cn.py
Normal file
592
plugins/actions/js-render-poc/infographic_markdown_cn.py
Normal file
@@ -0,0 +1,592 @@
|
||||
"""
|
||||
title: 📊 信息图转 Markdown
|
||||
author: Fu-Jie
|
||||
version: 1.0.0
|
||||
description: AI 生成信息图语法,前端渲染 SVG 并转换为 Markdown 图片格式嵌入消息。支持 AntV Infographic 模板。
|
||||
"""
|
||||
|
||||
import time
|
||||
import json
|
||||
import logging
|
||||
import re
|
||||
from typing import Optional, Callable, Awaitable, Any, Dict
|
||||
from pydantic import BaseModel, Field
|
||||
from fastapi import Request
|
||||
from datetime import datetime
|
||||
|
||||
from open_webui.utils.chat import generate_chat_completion
|
||||
from open_webui.models.users import Users
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# =================================================================
|
||||
# LLM 提示词
|
||||
# =================================================================
|
||||
|
||||
SYSTEM_PROMPT_INFOGRAPHIC = """
|
||||
你是一位专业的信息图设计专家,能够分析用户提供的文本内容并将其转换为 AntV Infographic 语法格式。
|
||||
|
||||
## 信息图语法规范
|
||||
|
||||
信息图语法是一种类似 Mermaid 的声明式语法,用于描述信息图模板、数据和主题。
|
||||
|
||||
### 语法规则
|
||||
- 入口使用 `infographic <模板名>`
|
||||
- 键值对用空格分隔,**绝对不允许使用冒号**
|
||||
- 使用两个空格缩进
|
||||
- 对象数组使用 `-` 加换行
|
||||
|
||||
⚠️ **重要警告:这不是 YAML 格式!**
|
||||
- ❌ 错误:`children:` `items:` `data:`(带冒号)
|
||||
- ✅ 正确:`children` `items` `data`(不带冒号)
|
||||
|
||||
### 模板库与选择指南
|
||||
|
||||
根据内容结构选择最合适的模板:
|
||||
|
||||
#### 1. 列表与层级
|
||||
- **列表**:`list-grid`(网格卡片)、`list-vertical`(垂直列表)
|
||||
- **树形**:`tree-vertical`(垂直树)、`tree-horizontal`(水平树)
|
||||
- **思维导图**:`mindmap`(思维导图)
|
||||
|
||||
#### 2. 序列与关系
|
||||
- **流程**:`sequence-roadmap`(路线图)、`sequence-zigzag`(折线流程)
|
||||
- **关系**:`relation-sankey`(桑基图)、`relation-circle`(圆形关系)
|
||||
|
||||
#### 3. 对比与分析
|
||||
- **对比**:`compare-binary`(二元对比)
|
||||
- **分析**:`compare-swot`(SWOT 分析)、`quadrant-quarter`(象限图)
|
||||
|
||||
#### 4. 图表与数据
|
||||
- **图表**:`chart-bar`、`chart-column`、`chart-line`、`chart-pie`、`chart-doughnut`、`chart-area`
|
||||
|
||||
### 数据结构示例
|
||||
|
||||
#### A. 标准列表/树形
|
||||
```infographic
|
||||
infographic list-grid
|
||||
data
|
||||
title 项目模块
|
||||
items
|
||||
- label 模块 A
|
||||
desc 模块 A 的描述
|
||||
- label 模块 B
|
||||
desc 模块 B 的描述
|
||||
```
|
||||
|
||||
#### B. 二元对比
|
||||
```infographic
|
||||
infographic compare-binary
|
||||
data
|
||||
title 优势与劣势
|
||||
items
|
||||
- label 优势
|
||||
children
|
||||
- label 研发能力强
|
||||
desc 技术领先
|
||||
- label 劣势
|
||||
children
|
||||
- label 品牌曝光弱
|
||||
desc 营销不足
|
||||
```
|
||||
|
||||
#### C. 图表
|
||||
```infographic
|
||||
infographic chart-bar
|
||||
data
|
||||
title 季度收入
|
||||
items
|
||||
- label Q1
|
||||
value 120
|
||||
- label Q2
|
||||
value 150
|
||||
```
|
||||
|
||||
### 常用数据字段
|
||||
- `label`:主标题/标签(必填)
|
||||
- `desc`:描述文字(`list-grid` 最多 30 个中文字符)
|
||||
- `value`:数值(用于图表)
|
||||
- `children`:嵌套项
|
||||
|
||||
## 输出要求
|
||||
1. **语言**:使用用户的语言输出内容。
|
||||
2. **格式**:用 ```infographic ... ``` 包裹输出。
|
||||
3. **无冒号**:键后面不要使用冒号。
|
||||
4. **缩进**:使用 2 个空格。
|
||||
"""
|
||||
|
||||
USER_PROMPT_GENERATE = """
|
||||
请分析以下文本内容,将其核心信息转换为 AntV Infographic 语法格式。
|
||||
|
||||
---
|
||||
**用户上下文:**
|
||||
用户名:{user_name}
|
||||
当前时间:{current_date_time_str}
|
||||
用户语言:{user_language}
|
||||
---
|
||||
|
||||
**文本内容:**
|
||||
{long_text_content}
|
||||
|
||||
请根据文本特征选择最合适的信息图模板,输出标准的信息图语法。
|
||||
|
||||
**重要提示:**
|
||||
- 如果使用 `list-grid` 格式,确保每个卡片的 `desc` 描述限制在 **最多 30 个中文字符**。
|
||||
- 描述应简洁,突出重点。
|
||||
"""
|
||||
|
||||
|
||||
class Action:
|
||||
class Valves(BaseModel):
|
||||
SHOW_STATUS: bool = Field(
|
||||
default=True, description="在聊天界面显示操作状态更新。"
|
||||
)
|
||||
MODEL_ID: str = Field(
|
||||
default="",
|
||||
description="用于文本分析的 LLM 模型 ID。留空则使用当前对话模型。",
|
||||
)
|
||||
MIN_TEXT_LENGTH: int = Field(
|
||||
default=50,
|
||||
description="信息图分析所需的最小文本长度(字符数)。",
|
||||
)
|
||||
MESSAGE_COUNT: int = Field(
|
||||
default=1,
|
||||
description="用于生成的最近消息数量。",
|
||||
)
|
||||
SVG_WIDTH: int = Field(
|
||||
default=800,
|
||||
description="生成的 SVG 宽度(像素)。",
|
||||
)
|
||||
EXPORT_FORMAT: str = Field(
|
||||
default="svg",
|
||||
description="导出格式:'svg' 或 'png'。",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _extract_chat_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""从 body 或 metadata 中提取 chat_id"""
|
||||
if isinstance(body, dict):
|
||||
chat_id = body.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
chat_id = body_metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
chat_id = metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_message_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""从 body 或 metadata 中提取 message_id"""
|
||||
if isinstance(body, dict):
|
||||
message_id = body.get("id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
message_id = body_metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
message_id = metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_infographic_syntax(self, llm_output: str) -> str:
|
||||
"""从 LLM 输出中提取信息图语法"""
|
||||
match = re.search(r"```infographic\s*(.*?)\s*```", llm_output, re.DOTALL)
|
||||
if match:
|
||||
return match.group(1).strip()
|
||||
else:
|
||||
logger.warning("LLM 输出未遵循预期格式,将整个输出作为语法处理。")
|
||||
return llm_output.strip()
|
||||
|
||||
def _extract_text_content(self, content) -> str:
|
||||
"""从消息内容中提取文本,支持多模态格式"""
|
||||
if isinstance(content, str):
|
||||
return content
|
||||
elif isinstance(content, list):
|
||||
text_parts = []
|
||||
for item in content:
|
||||
if isinstance(item, dict) and item.get("type") == "text":
|
||||
text_parts.append(item.get("text", ""))
|
||||
elif isinstance(item, str):
|
||||
text_parts.append(item)
|
||||
return "\n".join(text_parts)
|
||||
return str(content) if content else ""
|
||||
|
||||
async def _emit_status(self, emitter, description: str, done: bool = False):
|
||||
"""发送状态更新事件"""
|
||||
if self.valves.SHOW_STATUS and emitter:
|
||||
await emitter(
|
||||
{"type": "status", "data": {"description": description, "done": done}}
|
||||
)
|
||||
|
||||
def _generate_js_code(
|
||||
self,
|
||||
unique_id: str,
|
||||
chat_id: str,
|
||||
message_id: str,
|
||||
infographic_syntax: str,
|
||||
svg_width: int,
|
||||
export_format: str,
|
||||
) -> str:
|
||||
"""生成用于前端 SVG 渲染的 JavaScript 代码"""
|
||||
|
||||
# 转义语法以便嵌入 JS
|
||||
syntax_escaped = (
|
||||
infographic_syntax
|
||||
.replace("\\", "\\\\")
|
||||
.replace("`", "\\`")
|
||||
.replace("${", "\\${")
|
||||
.replace("</script>", "<\\/script>")
|
||||
)
|
||||
|
||||
# 模板映射
|
||||
template_mapping_js = """
|
||||
const TEMPLATE_MAPPING = {
|
||||
'list-grid': 'list-grid-compact-card',
|
||||
'list-vertical': 'list-column-simple-vertical-arrow',
|
||||
'tree-vertical': 'hierarchy-tree-tech-style-capsule-item',
|
||||
'tree-horizontal': 'hierarchy-tree-lr-tech-style-capsule-item',
|
||||
'mindmap': 'hierarchy-mindmap-branch-gradient-capsule-item',
|
||||
'sequence-roadmap': 'sequence-roadmap-vertical-simple',
|
||||
'sequence-zigzag': 'sequence-horizontal-zigzag-simple',
|
||||
'sequence-horizontal': 'sequence-horizontal-zigzag-simple',
|
||||
'relation-sankey': 'relation-sankey-simple',
|
||||
'relation-circle': 'relation-circle-icon-badge',
|
||||
'compare-binary': 'compare-binary-horizontal-simple-vs',
|
||||
'compare-swot': 'compare-swot',
|
||||
'quadrant-quarter': 'quadrant-quarter-simple-card',
|
||||
'statistic-card': 'list-grid-compact-card',
|
||||
'chart-bar': 'chart-bar-plain-text',
|
||||
'chart-column': 'chart-column-simple',
|
||||
'chart-line': 'chart-line-plain-text',
|
||||
'chart-area': 'chart-area-simple',
|
||||
'chart-pie': 'chart-pie-plain-text',
|
||||
'chart-doughnut': 'chart-pie-donut-plain-text'
|
||||
};
|
||||
"""
|
||||
|
||||
return f"""
|
||||
(async function() {{
|
||||
const uniqueId = "{unique_id}";
|
||||
const chatId = "{chat_id}";
|
||||
const messageId = "{message_id}";
|
||||
const svgWidth = {svg_width};
|
||||
const exportFormat = "{export_format}";
|
||||
|
||||
console.log("[信息图 Markdown] 开始渲染...");
|
||||
console.log("[信息图 Markdown] chatId:", chatId, "messageId:", messageId);
|
||||
|
||||
try {{
|
||||
// 加载 AntV Infographic(如果尚未加载)
|
||||
if (typeof AntVInfographic === 'undefined') {{
|
||||
console.log("[信息图 Markdown] 正在加载 AntV Infographic 库...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://unpkg.com/@antv/infographic@latest/dist/infographic.min.js';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
console.log("[信息图 Markdown] 库加载完成。");
|
||||
}}
|
||||
|
||||
const {{ Infographic }} = AntVInfographic;
|
||||
|
||||
// 获取信息图语法
|
||||
let syntaxContent = `{syntax_escaped}`;
|
||||
console.log("[信息图 Markdown] 原始语法:", syntaxContent.substring(0, 200) + "...");
|
||||
|
||||
// 清理语法
|
||||
const backtick = String.fromCharCode(96);
|
||||
const prefix = backtick + backtick + backtick + 'infographic';
|
||||
const simplePrefix = backtick + backtick + backtick;
|
||||
|
||||
if (syntaxContent.toLowerCase().startsWith(prefix)) {{
|
||||
syntaxContent = syntaxContent.substring(prefix.length).trim();
|
||||
}} else if (syntaxContent.startsWith(simplePrefix)) {{
|
||||
syntaxContent = syntaxContent.substring(simplePrefix.length).trim();
|
||||
}}
|
||||
|
||||
if (syntaxContent.endsWith(simplePrefix)) {{
|
||||
syntaxContent = syntaxContent.substring(0, syntaxContent.length - simplePrefix.length).trim();
|
||||
}}
|
||||
|
||||
// 修复关键字后的冒号
|
||||
syntaxContent = syntaxContent.replace(/^(data|items|children|theme|config):/gm, '$1');
|
||||
syntaxContent = syntaxContent.replace(/(\\s)(children|items):/g, '$1$2');
|
||||
|
||||
// 确保有 infographic 前缀
|
||||
if (!syntaxContent.trim().toLowerCase().startsWith('infographic')) {{
|
||||
syntaxContent = 'infographic list-grid\\n' + syntaxContent;
|
||||
}}
|
||||
|
||||
// 应用模板映射
|
||||
{template_mapping_js}
|
||||
|
||||
for (const [key, value] of Object.entries(TEMPLATE_MAPPING)) {{
|
||||
const regex = new RegExp(`infographic\\\\s+${{key}}(?=\\\\s|$)`, 'i');
|
||||
if (regex.test(syntaxContent)) {{
|
||||
console.log(`[信息图 Markdown] 自动映射: ${{key}} -> ${{value}}`);
|
||||
syntaxContent = syntaxContent.replace(regex, `infographic ${{value}}`);
|
||||
break;
|
||||
}}
|
||||
}}
|
||||
|
||||
console.log("[信息图 Markdown] 清理后语法:", syntaxContent.substring(0, 200) + "...");
|
||||
|
||||
// 创建离屏容器
|
||||
const container = document.createElement('div');
|
||||
container.id = 'infographic-offscreen-' + uniqueId;
|
||||
container.style.cssText = 'position:absolute;left:-9999px;top:-9999px;width:' + svgWidth + 'px;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// 创建并渲染信息图
|
||||
const instance = new Infographic({{
|
||||
container: '#' + container.id,
|
||||
width: svgWidth,
|
||||
padding: 24,
|
||||
}});
|
||||
|
||||
console.log("[信息图 Markdown] 正在渲染信息图...");
|
||||
instance.render(syntaxContent);
|
||||
|
||||
// 等待渲染完成并导出
|
||||
await new Promise(resolve => setTimeout(resolve, 1000));
|
||||
|
||||
let dataUrl;
|
||||
if (exportFormat === 'png') {{
|
||||
dataUrl = await instance.toDataURL({{ type: 'png', dpr: 2 }});
|
||||
}} else {{
|
||||
dataUrl = await instance.toDataURL({{ type: 'svg', embedResources: true }});
|
||||
}}
|
||||
|
||||
console.log("[信息图 Markdown] Data URL 已生成,长度:", dataUrl.length);
|
||||
|
||||
// 清理
|
||||
instance.destroy();
|
||||
document.body.removeChild(container);
|
||||
|
||||
// 生成 Markdown 图片
|
||||
const markdownImage = ``;
|
||||
|
||||
// 通过 API 更新消息
|
||||
if (chatId && messageId) {{
|
||||
const token = localStorage.getItem("token");
|
||||
|
||||
// 获取当前消息内容
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("获取对话数据失败: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
let originalContent = "";
|
||||
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
const targetMsg = chatData.chat.messages.find(m => m.id === messageId);
|
||||
if (targetMsg && targetMsg.content) {{
|
||||
originalContent = targetMsg.content;
|
||||
}}
|
||||
}}
|
||||
|
||||
// 移除已有的信息图图片
|
||||
const infographicPattern = /\\n*!\\[📊[^\\]]*\\]\\(data:image\\/[^)]+\\)/g;
|
||||
let cleanedContent = originalContent.replace(infographicPattern, "");
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
|
||||
// 追加新图片
|
||||
const newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// 更新消息
|
||||
const updateResponse = await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: newContent }}
|
||||
}})
|
||||
}});
|
||||
|
||||
if (updateResponse.ok) {{
|
||||
console.log("[信息图 Markdown] ✅ 消息更新成功!");
|
||||
}} else {{
|
||||
console.error("[信息图 Markdown] API 错误:", updateResponse.status);
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[信息图 Markdown] ⚠️ 缺少 chatId 或 messageId");
|
||||
}}
|
||||
|
||||
}} catch (error) {{
|
||||
console.error("[信息图 Markdown] 错误:", error);
|
||||
}}
|
||||
}})();
|
||||
"""
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: dict = None,
|
||||
__event_emitter__=None,
|
||||
__event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__metadata__: Optional[dict] = None,
|
||||
__request__: Request = None,
|
||||
) -> dict:
|
||||
"""
|
||||
使用 AntV 生成信息图并作为 Markdown 图片嵌入。
|
||||
"""
|
||||
logger.info("动作:信息图转 Markdown 开始")
|
||||
|
||||
# 获取用户信息
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
user_language = __user__[0].get("language", "zh") if __user__ else "zh"
|
||||
user_name = __user__[0].get("name", "用户") if __user__[0] else "用户"
|
||||
user_id = __user__[0].get("id", "unknown_user") if __user__ else "unknown_user"
|
||||
elif isinstance(__user__, dict):
|
||||
user_language = __user__.get("language", "zh")
|
||||
user_name = __user__.get("name", "用户")
|
||||
user_id = __user__.get("id", "unknown_user")
|
||||
else:
|
||||
user_language = "zh"
|
||||
user_name = "用户"
|
||||
user_id = "unknown_user"
|
||||
|
||||
# 获取当前时间
|
||||
now = datetime.now()
|
||||
current_date_time_str = now.strftime("%Y-%m-%d %H:%M:%S")
|
||||
|
||||
try:
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
raise ValueError("没有可用的消息。")
|
||||
|
||||
# 获取最近的消息
|
||||
message_count = min(self.valves.MESSAGE_COUNT, len(messages))
|
||||
recent_messages = messages[-message_count:]
|
||||
|
||||
# 聚合内容
|
||||
aggregated_parts = []
|
||||
for msg in recent_messages:
|
||||
text_content = self._extract_text_content(msg.get("content"))
|
||||
if text_content:
|
||||
aggregated_parts.append(text_content)
|
||||
|
||||
if not aggregated_parts:
|
||||
raise ValueError("消息中未找到文本内容。")
|
||||
|
||||
long_text_content = "\n\n---\n\n".join(aggregated_parts)
|
||||
|
||||
# 移除已有的 HTML 块
|
||||
parts = re.split(r"```html.*?```", long_text_content, flags=re.DOTALL)
|
||||
clean_content = ""
|
||||
for part in reversed(parts):
|
||||
if part.strip():
|
||||
clean_content = part.strip()
|
||||
break
|
||||
|
||||
if not clean_content:
|
||||
clean_content = long_text_content.strip()
|
||||
|
||||
# 检查最小长度
|
||||
if len(clean_content) < self.valves.MIN_TEXT_LENGTH:
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
f"⚠️ 内容太短({len(clean_content)} 字符),至少需要 {self.valves.MIN_TEXT_LENGTH} 字符",
|
||||
True,
|
||||
)
|
||||
return body
|
||||
|
||||
await self._emit_status(__event_emitter__, "📊 正在分析内容...", False)
|
||||
|
||||
# 通过 LLM 生成信息图语法
|
||||
formatted_user_prompt = USER_PROMPT_GENERATE.format(
|
||||
user_name=user_name,
|
||||
current_date_time_str=current_date_time_str,
|
||||
user_language=user_language,
|
||||
long_text_content=clean_content,
|
||||
)
|
||||
|
||||
target_model = self.valves.MODEL_ID or body.get("model")
|
||||
|
||||
llm_payload = {
|
||||
"model": target_model,
|
||||
"messages": [
|
||||
{"role": "system", "content": SYSTEM_PROMPT_INFOGRAPHIC},
|
||||
{"role": "user", "content": formatted_user_prompt},
|
||||
],
|
||||
"stream": False,
|
||||
}
|
||||
|
||||
user_obj = Users.get_user_by_id(user_id)
|
||||
if not user_obj:
|
||||
raise ValueError(f"无法获取用户对象:{user_id}")
|
||||
|
||||
await self._emit_status(__event_emitter__, "📊 AI 正在生成信息图语法...", False)
|
||||
|
||||
llm_response = await generate_chat_completion(__request__, llm_payload, user_obj)
|
||||
|
||||
if not llm_response or "choices" not in llm_response or not llm_response["choices"]:
|
||||
raise ValueError("无效的 LLM 响应。")
|
||||
|
||||
assistant_content = llm_response["choices"][0]["message"]["content"]
|
||||
infographic_syntax = self._extract_infographic_syntax(assistant_content)
|
||||
|
||||
logger.info(f"生成的语法:{infographic_syntax[:200]}...")
|
||||
|
||||
# 提取 API 回调所需的 ID
|
||||
chat_id = self._extract_chat_id(body, __metadata__)
|
||||
message_id = self._extract_message_id(body, __metadata__)
|
||||
unique_id = f"ig_{int(time.time() * 1000)}"
|
||||
|
||||
await self._emit_status(__event_emitter__, "📊 正在渲染 SVG...", False)
|
||||
|
||||
# 执行 JS 进行渲染和嵌入
|
||||
if __event_call__:
|
||||
js_code = self._generate_js_code(
|
||||
unique_id=unique_id,
|
||||
chat_id=chat_id,
|
||||
message_id=message_id,
|
||||
infographic_syntax=infographic_syntax,
|
||||
svg_width=self.valves.SVG_WIDTH,
|
||||
export_format=self.valves.EXPORT_FORMAT,
|
||||
)
|
||||
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
|
||||
await self._emit_status(__event_emitter__, "✅ 信息图生成完成!", True)
|
||||
logger.info("信息图转 Markdown 完成")
|
||||
|
||||
except Exception as e:
|
||||
error_message = f"信息图生成失败:{str(e)}"
|
||||
logger.error(error_message, exc_info=True)
|
||||
await self._emit_status(__event_emitter__, f"❌ {error_message}", True)
|
||||
|
||||
return body
|
||||
257
plugins/actions/js-render-poc/js_render_poc.py
Normal file
257
plugins/actions/js-render-poc/js_render_poc.py
Normal file
@@ -0,0 +1,257 @@
|
||||
"""
|
||||
title: JS Render PoC
|
||||
author: Fu-Jie
|
||||
version: 0.6.0
|
||||
description: Proof of concept for JS rendering + API write-back pattern. JS renders SVG and updates message via API.
|
||||
"""
|
||||
|
||||
import time
|
||||
import json
|
||||
import logging
|
||||
from typing import Optional, Callable, Awaitable, Any
|
||||
from pydantic import BaseModel, Field
|
||||
from fastapi import Request
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class Action:
|
||||
class Valves(BaseModel):
|
||||
pass
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _extract_chat_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""Extract chat_id from body or metadata"""
|
||||
if isinstance(body, dict):
|
||||
# body["chat_id"] 是 chat_id
|
||||
chat_id = body.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
chat_id = body_metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
chat_id = metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_message_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""Extract message_id from body or metadata"""
|
||||
if isinstance(body, dict):
|
||||
# body["id"] 是 message_id
|
||||
message_id = body.get("id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
message_id = body_metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
message_id = metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: dict = None,
|
||||
__event_emitter__=None,
|
||||
__event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__metadata__: Optional[dict] = None,
|
||||
__request__: Request = None,
|
||||
) -> dict:
|
||||
"""
|
||||
PoC: Use __event_call__ to execute JS that renders SVG and updates message via API.
|
||||
"""
|
||||
# 准备调试数据
|
||||
body_for_log = {}
|
||||
for k, v in body.items():
|
||||
if k == "messages":
|
||||
body_for_log[k] = f"[{len(v)} messages]"
|
||||
else:
|
||||
body_for_log[k] = v
|
||||
|
||||
body_json = json.dumps(body_for_log, ensure_ascii=False, default=str)
|
||||
metadata_json = (
|
||||
json.dumps(__metadata__, ensure_ascii=False, default=str)
|
||||
if __metadata__
|
||||
else "null"
|
||||
)
|
||||
|
||||
# 转义 JSON 中的特殊字符以便嵌入 JS
|
||||
body_json_escaped = (
|
||||
body_json.replace("\\", "\\\\").replace("`", "\\`").replace("${", "\\${")
|
||||
)
|
||||
metadata_json_escaped = (
|
||||
metadata_json.replace("\\", "\\\\")
|
||||
.replace("`", "\\`")
|
||||
.replace("${", "\\${")
|
||||
)
|
||||
|
||||
chat_id = self._extract_chat_id(body, __metadata__)
|
||||
message_id = self._extract_message_id(body, __metadata__)
|
||||
|
||||
unique_id = f"poc_{int(time.time() * 1000)}"
|
||||
|
||||
if __event_emitter__:
|
||||
await __event_emitter__(
|
||||
{
|
||||
"type": "status",
|
||||
"data": {"description": "🔄 正在渲染...", "done": False},
|
||||
}
|
||||
)
|
||||
|
||||
if __event_call__:
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {
|
||||
"code": f"""
|
||||
(async function() {{
|
||||
const uniqueId = "{unique_id}";
|
||||
const chatId = "{chat_id}";
|
||||
const messageId = "{message_id}";
|
||||
|
||||
// ===== DEBUG: 输出 Python 端的数据 =====
|
||||
console.log("[JS Render PoC] ===== DEBUG INFO (from Python) =====");
|
||||
console.log("[JS Render PoC] body:", `{body_json_escaped}`);
|
||||
console.log("[JS Render PoC] __metadata__:", `{metadata_json_escaped}`);
|
||||
console.log("[JS Render PoC] Extracted: chatId=", chatId, "messageId=", messageId);
|
||||
console.log("[JS Render PoC] =========================================");
|
||||
|
||||
try {{
|
||||
console.log("[JS Render PoC] Starting SVG render...");
|
||||
|
||||
// Create SVG
|
||||
const svg = document.createElementNS("http://www.w3.org/2000/svg", "svg");
|
||||
svg.setAttribute("width", "200");
|
||||
svg.setAttribute("height", "200");
|
||||
svg.setAttribute("viewBox", "0 0 200 200");
|
||||
svg.setAttribute("xmlns", "http://www.w3.org/2000/svg");
|
||||
|
||||
const defs = document.createElementNS("http://www.w3.org/2000/svg", "defs");
|
||||
const gradient = document.createElementNS("http://www.w3.org/2000/svg", "linearGradient");
|
||||
gradient.setAttribute("id", "grad-" + uniqueId);
|
||||
gradient.innerHTML = `
|
||||
<stop offset="0%" style="stop-color:#1e88e5;stop-opacity:1" />
|
||||
<stop offset="100%" style="stop-color:#43a047;stop-opacity:1" />
|
||||
`;
|
||||
defs.appendChild(gradient);
|
||||
svg.appendChild(defs);
|
||||
|
||||
const circle = document.createElementNS("http://www.w3.org/2000/svg", "circle");
|
||||
circle.setAttribute("cx", "100");
|
||||
circle.setAttribute("cy", "100");
|
||||
circle.setAttribute("r", "80");
|
||||
circle.setAttribute("fill", `url(#grad-${{uniqueId}})`);
|
||||
svg.appendChild(circle);
|
||||
|
||||
const text = document.createElementNS("http://www.w3.org/2000/svg", "text");
|
||||
text.setAttribute("x", "100");
|
||||
text.setAttribute("y", "105");
|
||||
text.setAttribute("text-anchor", "middle");
|
||||
text.setAttribute("fill", "white");
|
||||
text.setAttribute("font-size", "16");
|
||||
text.setAttribute("font-weight", "bold");
|
||||
text.textContent = "PoC Success!";
|
||||
svg.appendChild(text);
|
||||
|
||||
// Convert to Base64 Data URI
|
||||
const svgData = new XMLSerializer().serializeToString(svg);
|
||||
const base64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
const dataUri = "data:image/svg+xml;base64," + base64;
|
||||
|
||||
console.log("[JS Render PoC] SVG rendered, data URI length:", dataUri.length);
|
||||
|
||||
// Call API - 完全替换方案(更稳定)
|
||||
if (chatId && messageId) {{
|
||||
const token = localStorage.getItem("token");
|
||||
|
||||
// 1. 获取当前消息内容
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("Failed to get chat data: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
console.log("[JS Render PoC] Got chat data");
|
||||
|
||||
let originalContent = "";
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
const targetMsg = chatData.chat.messages.find(m => m.id === messageId);
|
||||
if (targetMsg && targetMsg.content) {{
|
||||
originalContent = targetMsg.content;
|
||||
console.log("[JS Render PoC] Found original content, length:", originalContent.length);
|
||||
}}
|
||||
}}
|
||||
|
||||
// 2. 移除已存在的 PoC 图片(如果有的话)
|
||||
// 匹配  格式
|
||||
const pocImagePattern = /\\n*!\\[JS Render PoC[^\\]]*\\]\\(data:image\\/svg\\+xml;base64,[^)]+\\)/g;
|
||||
let cleanedContent = originalContent.replace(pocImagePattern, "");
|
||||
// 移除可能残留的多余空行
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
|
||||
if (cleanedContent !== originalContent) {{
|
||||
console.log("[JS Render PoC] Removed existing PoC image(s)");
|
||||
}}
|
||||
|
||||
// 3. 添加新的 Markdown 图片
|
||||
const markdownImage = ``;
|
||||
const newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// 3. 使用 chat:message 完全替换
|
||||
const updateResponse = await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: newContent }}
|
||||
}})
|
||||
}});
|
||||
|
||||
if (updateResponse.ok) {{
|
||||
console.log("[JS Render PoC] ✅ Message updated successfully!");
|
||||
}} else {{
|
||||
console.error("[JS Render PoC] API error:", updateResponse.status, await updateResponse.text());
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[JS Render PoC] ⚠️ Missing chatId or messageId, cannot persist.");
|
||||
}}
|
||||
|
||||
}} catch (error) {{
|
||||
console.error("[JS Render PoC] Error:", error);
|
||||
}}
|
||||
}})();
|
||||
"""
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
if __event_emitter__:
|
||||
await __event_emitter__(
|
||||
{"type": "status", "data": {"description": "✅ 渲染完成", "done": True}}
|
||||
)
|
||||
|
||||
return body
|
||||
@@ -3,7 +3,7 @@ title: Smart Mind Map
|
||||
author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 0.8.2
|
||||
version: 0.9.0
|
||||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxyZWN0IHg9IjE2IiB5PSIxNiIgd2lkdGg9IjYiIGhlaWdodD0iNiIgcng9IjEiLz48cmVjdCB4PSIyIiB5PSIxNiIgd2lkdGg9IjYiIGhlaWdodD0iNiIgcng9IjEiLz48cmVjdCB4PSI5IiB5PSIyIiB3aWR0aD0iNiIgaGVpZ2h0PSI2IiByeD0iMSIvPjxwYXRoIGQ9Ik01IDE2di0zYTEgMSAwIDAgMSAxLTFoMTJhMSAxIDAgMCAxIDEgMXYzIi8+PHBhdGggZD0iTTEyIDEyVjgiLz48L3N2Zz4=
|
||||
description: Intelligently analyzes text content and generates interactive mind maps to help users structure and visualize knowledge.
|
||||
"""
|
||||
@@ -13,7 +13,7 @@ import os
|
||||
import re
|
||||
import time
|
||||
from datetime import datetime, timezone
|
||||
from typing import Any, Dict, Optional
|
||||
from typing import Any, Callable, Awaitable, Dict, Optional
|
||||
from zoneinfo import ZoneInfo
|
||||
|
||||
from fastapi import Request
|
||||
@@ -786,6 +786,18 @@ class Action:
|
||||
default=1,
|
||||
description="Number of recent messages to use for generation. Set to 1 for just the last message, or higher for more context.",
|
||||
)
|
||||
OUTPUT_MODE: str = Field(
|
||||
default="html",
|
||||
description="Output mode: 'html' for interactive HTML (default), or 'image' to embed as Markdown image.",
|
||||
)
|
||||
SVG_WIDTH: int = Field(
|
||||
default=1200,
|
||||
description="Width of the SVG canvas in pixels (for image mode).",
|
||||
)
|
||||
SVG_HEIGHT: int = Field(
|
||||
default=800,
|
||||
description="Height of the SVG canvas in pixels (for image mode).",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
@@ -814,6 +826,46 @@ class Action:
|
||||
"user_language": user_data.get("language", "en-US"),
|
||||
}
|
||||
|
||||
def _extract_chat_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""Extract chat_id from body or metadata"""
|
||||
if isinstance(body, dict):
|
||||
chat_id = body.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
chat_id = body_metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
chat_id = metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_message_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""Extract message_id from body or metadata"""
|
||||
if isinstance(body, dict):
|
||||
message_id = body.get("id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
message_id = body_metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
message_id = metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_markdown_syntax(self, llm_output: str) -> str:
|
||||
match = re.search(r"```markdown\s*(.*?)\s*```", llm_output, re.DOTALL)
|
||||
if match:
|
||||
@@ -901,11 +953,286 @@ class Action:
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _generate_image_js_code(
|
||||
self,
|
||||
unique_id: str,
|
||||
chat_id: str,
|
||||
message_id: str,
|
||||
markdown_syntax: str,
|
||||
svg_width: int,
|
||||
svg_height: int,
|
||||
) -> str:
|
||||
"""Generate JavaScript code for frontend SVG rendering and image embedding"""
|
||||
|
||||
# Escape the syntax for JS embedding
|
||||
syntax_escaped = (
|
||||
markdown_syntax
|
||||
.replace("\\", "\\\\")
|
||||
.replace("`", "\\`")
|
||||
.replace("${", "\\${")
|
||||
.replace("</script>", "<\\/script>")
|
||||
)
|
||||
|
||||
return f"""
|
||||
(async function() {{
|
||||
const uniqueId = "{unique_id}";
|
||||
const chatId = "{chat_id}";
|
||||
const messageId = "{message_id}";
|
||||
const defaultWidth = {svg_width};
|
||||
const defaultHeight = {svg_height};
|
||||
|
||||
// Auto-detect chat container width for responsive sizing
|
||||
let svgWidth = defaultWidth;
|
||||
let svgHeight = defaultHeight;
|
||||
const chatContainer = document.getElementById('chat-container');
|
||||
if (chatContainer) {{
|
||||
const containerWidth = chatContainer.clientWidth;
|
||||
if (containerWidth > 100) {{
|
||||
// Use container width with some padding (90% of container)
|
||||
svgWidth = Math.floor(containerWidth * 0.9);
|
||||
// Maintain aspect ratio based on default dimensions
|
||||
svgHeight = Math.floor(svgWidth * (defaultHeight / defaultWidth));
|
||||
console.log("[MindMap Image] Auto-detected container width:", containerWidth, "-> SVG:", svgWidth, "x", svgHeight);
|
||||
}}
|
||||
}}
|
||||
|
||||
console.log("[MindMap Image] Starting render...");
|
||||
console.log("[MindMap Image] chatId:", chatId, "messageId:", messageId);
|
||||
|
||||
try {{
|
||||
// Load D3 if not loaded
|
||||
if (typeof d3 === 'undefined') {{
|
||||
console.log("[MindMap Image] Loading D3...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.jsdelivr.net/npm/d3@7';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
}}
|
||||
|
||||
// Load markmap-lib if not loaded
|
||||
if (!window.markmap || !window.markmap.Transformer) {{
|
||||
console.log("[MindMap Image] Loading markmap-lib...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.jsdelivr.net/npm/markmap-lib@0.17';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
}}
|
||||
|
||||
// Load markmap-view if not loaded
|
||||
if (!window.markmap || !window.markmap.Markmap) {{
|
||||
console.log("[MindMap Image] Loading markmap-view...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.jsdelivr.net/npm/markmap-view@0.17';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
}}
|
||||
|
||||
const {{ Transformer, Markmap }} = window.markmap;
|
||||
|
||||
// Get markdown syntax
|
||||
let syntaxContent = `{syntax_escaped}`;
|
||||
console.log("[MindMap Image] Syntax length:", syntaxContent.length);
|
||||
|
||||
// Create offscreen container
|
||||
const container = document.createElement('div');
|
||||
container.id = 'mindmap-offscreen-' + uniqueId;
|
||||
container.style.cssText = 'position:absolute;left:-9999px;top:-9999px;width:' + svgWidth + 'px;height:' + svgHeight + 'px;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// Create SVG element
|
||||
const svgEl = document.createElementNS('http://www.w3.org/2000/svg', 'svg');
|
||||
svgEl.setAttribute('width', svgWidth);
|
||||
svgEl.setAttribute('height', svgHeight);
|
||||
svgEl.style.width = svgWidth + 'px';
|
||||
svgEl.style.height = svgHeight + 'px';
|
||||
svgEl.style.backgroundColor = '#ffffff';
|
||||
container.appendChild(svgEl);
|
||||
|
||||
// Transform markdown to tree
|
||||
const transformer = new Transformer();
|
||||
const {{ root }} = transformer.transform(syntaxContent);
|
||||
|
||||
// Create markmap instance
|
||||
const options = {{
|
||||
autoFit: true,
|
||||
initialExpandLevel: Infinity,
|
||||
zoom: false,
|
||||
pan: false
|
||||
}};
|
||||
|
||||
console.log("[MindMap Image] Rendering markmap...");
|
||||
const markmapInstance = Markmap.create(svgEl, options, root);
|
||||
|
||||
// Wait for render to complete
|
||||
await new Promise(resolve => setTimeout(resolve, 1500));
|
||||
markmapInstance.fit();
|
||||
await new Promise(resolve => setTimeout(resolve, 500));
|
||||
|
||||
// Clone and prepare SVG for export
|
||||
const clonedSvg = svgEl.cloneNode(true);
|
||||
clonedSvg.setAttribute('xmlns', 'http://www.w3.org/2000/svg');
|
||||
clonedSvg.setAttribute('xmlns:xlink', 'http://www.w3.org/1999/xlink');
|
||||
|
||||
// Add background rect
|
||||
const bgRect = document.createElementNS('http://www.w3.org/2000/svg', 'rect');
|
||||
bgRect.setAttribute('width', '100%');
|
||||
bgRect.setAttribute('height', '100%');
|
||||
bgRect.setAttribute('fill', '#ffffff');
|
||||
clonedSvg.insertBefore(bgRect, clonedSvg.firstChild);
|
||||
|
||||
// Add inline styles
|
||||
const style = document.createElementNS('http://www.w3.org/2000/svg', 'style');
|
||||
style.textContent = `
|
||||
text {{ font-family: sans-serif; font-size: 14px; fill: #000000; }}
|
||||
foreignObject, .markmap-foreign, .markmap-foreign div {{ color: #000000; font-family: sans-serif; font-size: 14px; }}
|
||||
h1 {{ font-size: 22px; font-weight: 700; margin: 0; }}
|
||||
h2 {{ font-size: 18px; font-weight: 600; margin: 0; }}
|
||||
strong {{ font-weight: 700; }}
|
||||
.markmap-link {{ stroke: #546e7a; fill: none; }}
|
||||
.markmap-node circle, .markmap-node rect {{ stroke: #94a3b8; }}
|
||||
`;
|
||||
clonedSvg.insertBefore(style, bgRect.nextSibling);
|
||||
|
||||
// Convert foreignObject to text for better compatibility
|
||||
const foreignObjects = clonedSvg.querySelectorAll('foreignObject');
|
||||
foreignObjects.forEach(fo => {{
|
||||
const text = fo.textContent || '';
|
||||
const g = document.createElementNS('http://www.w3.org/2000/svg', 'g');
|
||||
const textEl = document.createElementNS('http://www.w3.org/2000/svg', 'text');
|
||||
textEl.setAttribute('x', fo.getAttribute('x') || '0');
|
||||
textEl.setAttribute('y', (parseFloat(fo.getAttribute('y') || '0') + 14).toString());
|
||||
textEl.setAttribute('fill', '#000000');
|
||||
textEl.setAttribute('font-family', 'sans-serif');
|
||||
textEl.setAttribute('font-size', '14');
|
||||
textEl.textContent = text.trim();
|
||||
g.appendChild(textEl);
|
||||
fo.parentNode.replaceChild(g, fo);
|
||||
}});
|
||||
|
||||
// Serialize SVG to string
|
||||
const svgData = new XMLSerializer().serializeToString(clonedSvg);
|
||||
const svgBase64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
const dataUrl = 'data:image/svg+xml;base64,' + svgBase64;
|
||||
|
||||
console.log("[MindMap Image] Data URL generated, length:", dataUrl.length);
|
||||
|
||||
// Cleanup
|
||||
document.body.removeChild(container);
|
||||
|
||||
// Generate markdown image
|
||||
const markdownImage = ``;
|
||||
|
||||
// Update message via API
|
||||
if (chatId && messageId) {{
|
||||
const token = localStorage.getItem("token");
|
||||
|
||||
// Get current chat data
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("Failed to get chat data: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
let originalContent = "";
|
||||
let updatedMessages = [];
|
||||
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
updatedMessages = chatData.chat.messages.map(m => {{
|
||||
if (m.id === messageId) {{
|
||||
originalContent = m.content || "";
|
||||
// Remove existing mindmap images
|
||||
const mindmapPattern = /\\n*!\\[🧠[^\\]]*\\]\\(data:image\\/[^)]+\\)/g;
|
||||
let cleanedContent = originalContent.replace(mindmapPattern, "");
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
// Append new image
|
||||
const newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// Critical: Update content in both messages array AND history object
|
||||
// The history object is often the source of truth for the database
|
||||
if (chatData.chat.history && chatData.chat.history.messages && chatData.chat.history.messages[messageId]) {{
|
||||
chatData.chat.history.messages[messageId].content = newContent;
|
||||
}}
|
||||
|
||||
return {{ ...m, content: newContent }};
|
||||
}}
|
||||
return m;
|
||||
}});
|
||||
}}
|
||||
|
||||
// First: Update frontend display via event API (for immediate visual feedback)
|
||||
await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: updatedMessages.find(m => m.id === messageId)?.content || "" }}
|
||||
}})
|
||||
}});
|
||||
|
||||
// Second: Persist to database by updating the entire chat
|
||||
const updatePayload = {{
|
||||
chat: {{
|
||||
...chatData.chat,
|
||||
messages: updatedMessages
|
||||
}}
|
||||
}};
|
||||
|
||||
const persistResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify(updatePayload)
|
||||
}});
|
||||
|
||||
if (persistResponse.ok) {{
|
||||
console.log("[MindMap Image] ✅ Message persisted successfully!");
|
||||
}} else {{
|
||||
console.error("[MindMap Image] Persist API error:", persistResponse.status);
|
||||
// Try alternative update method
|
||||
const altResponse = await fetch(`/api/v1/chats/${{chatId}}/share`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}}
|
||||
}});
|
||||
console.log("[MindMap Image] Alt persist attempted:", altResponse.status);
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[MindMap Image] ⚠️ Missing chatId or messageId");
|
||||
}}
|
||||
|
||||
}} catch (error) {{
|
||||
console.error("[MindMap Image] Error:", error);
|
||||
}}
|
||||
}})();
|
||||
"""
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[Dict[str, Any]] = None,
|
||||
__event_emitter__: Optional[Any] = None,
|
||||
__event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__metadata__: Optional[dict] = None,
|
||||
__request__: Optional[Request] = None,
|
||||
) -> Optional[dict]:
|
||||
logger.info("Action: Smart Mind Map (v0.8.0) started")
|
||||
@@ -1090,6 +1417,47 @@ class Action:
|
||||
user_language,
|
||||
)
|
||||
|
||||
# Check output mode
|
||||
if self.valves.OUTPUT_MODE == "image":
|
||||
# Image mode: use JavaScript to render and embed as Markdown image
|
||||
chat_id = self._extract_chat_id(body, __metadata__)
|
||||
message_id = self._extract_message_id(body, __metadata__)
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"Smart Mind Map: Rendering image...",
|
||||
False,
|
||||
)
|
||||
|
||||
if __event_call__:
|
||||
js_code = self._generate_image_js_code(
|
||||
unique_id=unique_id,
|
||||
chat_id=chat_id,
|
||||
message_id=message_id,
|
||||
markdown_syntax=markdown_syntax,
|
||||
svg_width=self.valves.SVG_WIDTH,
|
||||
svg_height=self.valves.SVG_HEIGHT,
|
||||
)
|
||||
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "Smart Mind Map: Image generated!", True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"Mind map image has been generated, {user_name}!",
|
||||
"success",
|
||||
)
|
||||
logger.info("Action: Smart Mind Map (v0.9.0) completed in image mode")
|
||||
return body
|
||||
|
||||
# HTML mode (default): embed as HTML block
|
||||
html_embed_tag = f"```html\n{final_html}\n```"
|
||||
body["messages"][-1]["content"] = f"{long_text_content}\n\n{html_embed_tag}"
|
||||
|
||||
@@ -1101,7 +1469,7 @@ class Action:
|
||||
f"Mind map has been generated, {user_name}!",
|
||||
"success",
|
||||
)
|
||||
logger.info("Action: Smart Mind Map (v0.8.0) completed successfully")
|
||||
logger.info("Action: Smart Mind Map (v0.9.0) completed in HTML mode")
|
||||
|
||||
except Exception as e:
|
||||
error_message = f"Smart Mind Map processing failed: {str(e)}"
|
||||
|
||||
@@ -3,7 +3,7 @@ title: 思维导图
|
||||
author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 0.8.2
|
||||
version: 0.9.0
|
||||
icon_url: data:image/svg+xml;base64,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
|
||||
description: 智能分析文本内容,生成交互式思维导图,帮助用户结构化和可视化知识。
|
||||
"""
|
||||
@@ -13,7 +13,7 @@ import os
|
||||
import re
|
||||
import time
|
||||
from datetime import datetime, timezone
|
||||
from typing import Any, Dict, Optional
|
||||
from typing import Any, Callable, Awaitable, Dict, Optional
|
||||
from zoneinfo import ZoneInfo
|
||||
|
||||
from fastapi import Request
|
||||
@@ -443,7 +443,7 @@ SCRIPT_TEMPLATE_MINDMAP = """
|
||||
|
||||
const markdownContent = sourceEl.textContent.trim();
|
||||
if (!markdownContent) {
|
||||
containerEl.innerHTML = '<div class="error-message">⚠️ 无法加载思维导图:缺少有效内容。</div>';
|
||||
containerEl.innerHTML = '<div class="error-message">⚠️ 无法加载思维导图:缺少有效内容。</div>';
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -485,7 +485,7 @@ SCRIPT_TEMPLATE_MINDMAP = """
|
||||
|
||||
}).catch((error) => {
|
||||
console.error('Markmap loading error:', error);
|
||||
containerEl.innerHTML = '<div class="error-message">⚠️ 资源加载失败,请稍后重试。</div>';
|
||||
containerEl.innerHTML = '<div class="error-message">⚠️ 资源加载失败,请稍后重试。</div>';
|
||||
});
|
||||
};
|
||||
|
||||
@@ -771,19 +771,31 @@ class Action:
|
||||
)
|
||||
MODEL_ID: str = Field(
|
||||
default="",
|
||||
description="用于文本分析的内置LLM模型ID。如果为空,则使用当前对话的模型。",
|
||||
description="用于文本分析的内置LLM模型ID。如果为空,则使用当前对话的模型。",
|
||||
)
|
||||
MIN_TEXT_LENGTH: int = Field(
|
||||
default=100,
|
||||
description="进行思维导图分析所需的最小文本长度(字符数)。",
|
||||
description="进行思维导图分析所需的最小文本长度(字符数)。",
|
||||
)
|
||||
CLEAR_PREVIOUS_HTML: bool = Field(
|
||||
default=False,
|
||||
description="是否强制清除旧的插件结果(如果为 True,则不合并,直接覆盖)。",
|
||||
description="是否强制清除旧的插件结果(如果为 True,则不合并,直接覆盖)。",
|
||||
)
|
||||
MESSAGE_COUNT: int = Field(
|
||||
default=1,
|
||||
description="用于生成的最近消息数量。设置为1仅使用最后一条消息,更大值可包含更多上下文。",
|
||||
description="用于生成的最近消息数量。设置为1仅使用最后一条消息,更大值可包含更多上下文。",
|
||||
)
|
||||
OUTPUT_MODE: str = Field(
|
||||
default="html",
|
||||
description="输出模式: 'html' 为交互式HTML(默认),'image' 为嵌入Markdown图片。",
|
||||
)
|
||||
SVG_WIDTH: int = Field(
|
||||
default=1200,
|
||||
description="SVG画布宽度(像素,用于图片模式)。",
|
||||
)
|
||||
SVG_HEIGHT: int = Field(
|
||||
default=800,
|
||||
description="SVG画布高度(像素,用于图片模式)。",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
@@ -813,13 +825,53 @@ class Action:
|
||||
"user_language": user_data.get("language", "zh-CN"),
|
||||
}
|
||||
|
||||
def _extract_chat_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""从 body 或 metadata 中提取 chat_id"""
|
||||
if isinstance(body, dict):
|
||||
chat_id = body.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
chat_id = body_metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
chat_id = metadata.get("chat_id")
|
||||
if isinstance(chat_id, str) and chat_id.strip():
|
||||
return chat_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_message_id(self, body: dict, metadata: Optional[dict]) -> str:
|
||||
"""从 body 或 metadata 中提取 message_id"""
|
||||
if isinstance(body, dict):
|
||||
message_id = body.get("id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
body_metadata = body.get("metadata", {})
|
||||
if isinstance(body_metadata, dict):
|
||||
message_id = body_metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
if isinstance(metadata, dict):
|
||||
message_id = metadata.get("message_id")
|
||||
if isinstance(message_id, str) and message_id.strip():
|
||||
return message_id.strip()
|
||||
|
||||
return ""
|
||||
|
||||
def _extract_markdown_syntax(self, llm_output: str) -> str:
|
||||
match = re.search(r"```markdown\s*(.*?)\s*```", llm_output, re.DOTALL)
|
||||
if match:
|
||||
extracted_content = match.group(1).strip()
|
||||
else:
|
||||
logger.warning(
|
||||
"LLM输出未严格遵循预期Markdown格式,将整个输出作为摘要处理。"
|
||||
"LLM输出未严格遵循预期Markdown格式,将整个输出作为摘要处理。"
|
||||
)
|
||||
extracted_content = llm_output.strip()
|
||||
return extracted_content.replace("</script>", "<\\/script>")
|
||||
@@ -844,7 +896,7 @@ class Action:
|
||||
return re.sub(pattern, "", content).strip()
|
||||
|
||||
def _extract_text_content(self, content) -> str:
|
||||
"""从消息内容中提取文本,支持多模态消息格式"""
|
||||
"""从消息内容中提取文本,支持多模态消息格式"""
|
||||
if isinstance(content, str):
|
||||
return content
|
||||
elif isinstance(content, list):
|
||||
@@ -867,7 +919,7 @@ class Action:
|
||||
user_language: str = "zh-CN",
|
||||
) -> str:
|
||||
"""
|
||||
将新内容合并到现有的 HTML 容器中,或者创建一个新的容器。
|
||||
将新内容合并到现有的 HTML 容器中,或者创建一个新的容器。
|
||||
"""
|
||||
if (
|
||||
"<!-- OPENWEBUI_PLUGIN_OUTPUT -->" in existing_html_code
|
||||
@@ -900,11 +952,286 @@ class Action:
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _generate_image_js_code(
|
||||
self,
|
||||
unique_id: str,
|
||||
chat_id: str,
|
||||
message_id: str,
|
||||
markdown_syntax: str,
|
||||
svg_width: int,
|
||||
svg_height: int,
|
||||
) -> str:
|
||||
"""生成用于前端 SVG 渲染和图片嵌入的 JavaScript 代码"""
|
||||
|
||||
# 转义语法以便嵌入 JS
|
||||
syntax_escaped = (
|
||||
markdown_syntax
|
||||
.replace("\\", "\\\\")
|
||||
.replace("`", "\\`")
|
||||
.replace("${", "\\${")
|
||||
.replace("</script>", "<\\/script>")
|
||||
)
|
||||
|
||||
return f"""
|
||||
(async function() {{
|
||||
const uniqueId = "{unique_id}";
|
||||
const chatId = "{chat_id}";
|
||||
const messageId = "{message_id}";
|
||||
const defaultWidth = {svg_width};
|
||||
const defaultHeight = {svg_height};
|
||||
|
||||
// 自动检测聊天容器宽度以实现自适应
|
||||
let svgWidth = defaultWidth;
|
||||
let svgHeight = defaultHeight;
|
||||
const chatContainer = document.getElementById('chat-container');
|
||||
if (chatContainer) {{
|
||||
const containerWidth = chatContainer.clientWidth;
|
||||
if (containerWidth > 100) {{
|
||||
// 使用容器宽度的90%(留出边距)
|
||||
svgWidth = Math.floor(containerWidth * 0.9);
|
||||
// 根据默认尺寸保持宽高比
|
||||
svgHeight = Math.floor(svgWidth * (defaultHeight / defaultWidth));
|
||||
console.log("[思维导图图片] 自动检测容器宽度:", containerWidth, "-> SVG:", svgWidth, "x", svgHeight);
|
||||
}}
|
||||
}}
|
||||
|
||||
console.log("[思维导图图片] 开始渲染...");
|
||||
console.log("[思维导图图片] chatId:", chatId, "messageId:", messageId);
|
||||
|
||||
try {{
|
||||
// 加载 D3
|
||||
if (typeof d3 === 'undefined') {{
|
||||
console.log("[思维导图图片] 正在加载 D3...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.jsdelivr.net/npm/d3@7';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
}}
|
||||
|
||||
// 加载 markmap-lib
|
||||
if (!window.markmap || !window.markmap.Transformer) {{
|
||||
console.log("[思维导图图片] 正在加载 markmap-lib...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.jsdelivr.net/npm/markmap-lib@0.17';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
}}
|
||||
|
||||
// 加载 markmap-view
|
||||
if (!window.markmap || !window.markmap.Markmap) {{
|
||||
console.log("[思维导图图片] 正在加载 markmap-view...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://cdn.jsdelivr.net/npm/markmap-view@0.17';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
}}
|
||||
|
||||
const {{ Transformer, Markmap }} = window.markmap;
|
||||
|
||||
// 获取 markdown 语法
|
||||
let syntaxContent = `{syntax_escaped}`;
|
||||
console.log("[思维导图图片] 语法长度:", syntaxContent.length);
|
||||
|
||||
// 创建离屏容器
|
||||
const container = document.createElement('div');
|
||||
container.id = 'mindmap-offscreen-' + uniqueId;
|
||||
container.style.cssText = 'position:absolute;left:-9999px;top:-9999px;width:' + svgWidth + 'px;height:' + svgHeight + 'px;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// 创建 SVG 元素
|
||||
const svgEl = document.createElementNS('http://www.w3.org/2000/svg', 'svg');
|
||||
svgEl.setAttribute('width', svgWidth);
|
||||
svgEl.setAttribute('height', svgHeight);
|
||||
svgEl.style.width = svgWidth + 'px';
|
||||
svgEl.style.height = svgHeight + 'px';
|
||||
svgEl.style.backgroundColor = '#ffffff';
|
||||
container.appendChild(svgEl);
|
||||
|
||||
// 将 markdown 转换为树结构
|
||||
const transformer = new Transformer();
|
||||
const {{ root }} = transformer.transform(syntaxContent);
|
||||
|
||||
// 创建 markmap 实例
|
||||
const options = {{
|
||||
autoFit: true,
|
||||
initialExpandLevel: Infinity,
|
||||
zoom: false,
|
||||
pan: false
|
||||
}};
|
||||
|
||||
console.log("[思维导图图片] 正在渲染 markmap...");
|
||||
const markmapInstance = Markmap.create(svgEl, options, root);
|
||||
|
||||
// 等待渲染完成
|
||||
await new Promise(resolve => setTimeout(resolve, 1500));
|
||||
markmapInstance.fit();
|
||||
await new Promise(resolve => setTimeout(resolve, 500));
|
||||
|
||||
// 克隆并准备 SVG 导出
|
||||
const clonedSvg = svgEl.cloneNode(true);
|
||||
clonedSvg.setAttribute('xmlns', 'http://www.w3.org/2000/svg');
|
||||
clonedSvg.setAttribute('xmlns:xlink', 'http://www.w3.org/1999/xlink');
|
||||
|
||||
// 添加背景矩形
|
||||
const bgRect = document.createElementNS('http://www.w3.org/2000/svg', 'rect');
|
||||
bgRect.setAttribute('width', '100%');
|
||||
bgRect.setAttribute('height', '100%');
|
||||
bgRect.setAttribute('fill', '#ffffff');
|
||||
clonedSvg.insertBefore(bgRect, clonedSvg.firstChild);
|
||||
|
||||
// 添加内联样式
|
||||
const style = document.createElementNS('http://www.w3.org/2000/svg', 'style');
|
||||
style.textContent = `
|
||||
text {{ font-family: sans-serif; font-size: 14px; fill: #000000; }}
|
||||
foreignObject, .markmap-foreign, .markmap-foreign div {{ color: #000000; font-family: sans-serif; font-size: 14px; }}
|
||||
h1 {{ font-size: 22px; font-weight: 700; margin: 0; }}
|
||||
h2 {{ font-size: 18px; font-weight: 600; margin: 0; }}
|
||||
strong {{ font-weight: 700; }}
|
||||
.markmap-link {{ stroke: #546e7a; fill: none; }}
|
||||
.markmap-node circle, .markmap-node rect {{ stroke: #94a3b8; }}
|
||||
`;
|
||||
clonedSvg.insertBefore(style, bgRect.nextSibling);
|
||||
|
||||
// 将 foreignObject 转换为 text 以提高兼容性
|
||||
const foreignObjects = clonedSvg.querySelectorAll('foreignObject');
|
||||
foreignObjects.forEach(fo => {{
|
||||
const text = fo.textContent || '';
|
||||
const g = document.createElementNS('http://www.w3.org/2000/svg', 'g');
|
||||
const textEl = document.createElementNS('http://www.w3.org/2000/svg', 'text');
|
||||
textEl.setAttribute('x', fo.getAttribute('x') || '0');
|
||||
textEl.setAttribute('y', (parseFloat(fo.getAttribute('y') || '0') + 14).toString());
|
||||
textEl.setAttribute('fill', '#000000');
|
||||
textEl.setAttribute('font-family', 'sans-serif');
|
||||
textEl.setAttribute('font-size', '14');
|
||||
textEl.textContent = text.trim();
|
||||
g.appendChild(textEl);
|
||||
fo.parentNode.replaceChild(g, fo);
|
||||
}});
|
||||
|
||||
// 序列化 SVG 为字符串
|
||||
const svgData = new XMLSerializer().serializeToString(clonedSvg);
|
||||
const svgBase64 = btoa(unescape(encodeURIComponent(svgData)));
|
||||
const dataUrl = 'data:image/svg+xml;base64,' + svgBase64;
|
||||
|
||||
console.log("[思维导图图片] Data URL 已生成,长度:", dataUrl.length);
|
||||
|
||||
// 清理
|
||||
document.body.removeChild(container);
|
||||
|
||||
// 生成 markdown 图片
|
||||
const markdownImage = ``;
|
||||
|
||||
// 通过 API 更新消息
|
||||
if (chatId && messageId) {{
|
||||
const token = localStorage.getItem("token");
|
||||
|
||||
// 获取当前聊天数据
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("获取聊天数据失败: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
let originalContent = "";
|
||||
let updatedMessages = [];
|
||||
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
updatedMessages = chatData.chat.messages.map(m => {{
|
||||
if (m.id === messageId) {{
|
||||
originalContent = m.content || "";
|
||||
// 移除已有的思维导图图片
|
||||
const mindmapPattern = /\\n*!\\[🧠[^\\]]*\\]\\(data:image\\/[^)]+\\)/g;
|
||||
let cleanedContent = originalContent.replace(mindmapPattern, "");
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
// 追加新图片
|
||||
const newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// 关键: 同时更新 messages 数组和 history 对象中的内容
|
||||
// history 对象通常是数据库的单一真值来源
|
||||
if (chatData.chat.history && chatData.chat.history.messages && chatData.chat.history.messages[messageId]) {{
|
||||
chatData.chat.history.messages[messageId].content = newContent;
|
||||
}}
|
||||
|
||||
return {{ ...m, content: newContent }};
|
||||
}}
|
||||
return m;
|
||||
}});
|
||||
}}
|
||||
|
||||
// 第一步: 通过事件 API 更新前端显示(立即视觉反馈)
|
||||
await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: updatedMessages.find(m => m.id === messageId)?.content || "" }}
|
||||
}})
|
||||
}});
|
||||
|
||||
// 第二步: 通过更新整个聊天来持久化到数据库
|
||||
const updatePayload = {{
|
||||
chat: {{
|
||||
...chatData.chat,
|
||||
messages: updatedMessages
|
||||
}}
|
||||
}};
|
||||
|
||||
const persistResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify(updatePayload)
|
||||
}});
|
||||
|
||||
if (persistResponse.ok) {{
|
||||
console.log("[思维导图图片] ✅ 消息已持久化保存!");
|
||||
}} else {{
|
||||
console.error("[思维导图图片] 持久化 API 错误:", persistResponse.status);
|
||||
// 尝试备用更新方法
|
||||
const altResponse = await fetch(`/api/v1/chats/${{chatId}}/share`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}}
|
||||
}});
|
||||
console.log("[思维导图图片] 备用持久化尝试:", altResponse.status);
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[思维导图图片] ⚠️ 缺少 chatId 或 messageId");
|
||||
}}
|
||||
|
||||
}} catch (error) {{
|
||||
console.error("[思维导图图片] 错误:", error);
|
||||
}}
|
||||
}})();
|
||||
"""
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[Dict[str, Any]] = None,
|
||||
__event_emitter__: Optional[Any] = None,
|
||||
__event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__metadata__: Optional[dict] = None,
|
||||
__request__: Optional[Request] = None,
|
||||
) -> Optional[dict]:
|
||||
logger.info("Action: 思维导图 (v12 - Final Feedback Fix) started")
|
||||
@@ -923,7 +1250,7 @@ class Action:
|
||||
current_year = now_dt.strftime("%Y")
|
||||
current_timezone_str = tz_env or "UTC"
|
||||
except Exception as e:
|
||||
logger.warning(f"获取时区信息失败: {e},使用默认值。")
|
||||
logger.warning(f"获取时区信息失败: {e},使用默认值。")
|
||||
now = datetime.now()
|
||||
current_date_time_str = now.strftime("%Y年%m月%d日 %H:%M:%S")
|
||||
current_weekday_zh = "未知星期"
|
||||
@@ -931,7 +1258,7 @@ class Action:
|
||||
current_timezone_str = "未知时区"
|
||||
|
||||
await self._emit_notification(
|
||||
__event_emitter__, "思维导图已启动,正在为您生成思维导图...", "info"
|
||||
__event_emitter__, "思维导图已启动,正在为您生成思维导图...", "info"
|
||||
)
|
||||
|
||||
messages = body.get("messages")
|
||||
@@ -980,7 +1307,7 @@ class Action:
|
||||
long_text_content = original_content.strip()
|
||||
|
||||
if len(long_text_content) < self.valves.MIN_TEXT_LENGTH:
|
||||
short_text_message = f"文本内容过短({len(long_text_content)}字符),无法进行有效分析。请提供至少{self.valves.MIN_TEXT_LENGTH}字符的文本。"
|
||||
short_text_message = f"文本内容过短({len(long_text_content)}字符),无法进行有效分析。请提供至少{self.valves.MIN_TEXT_LENGTH}字符的文本。"
|
||||
await self._emit_notification(
|
||||
__event_emitter__, short_text_message, "warning"
|
||||
)
|
||||
@@ -1021,7 +1348,7 @@ class Action:
|
||||
}
|
||||
user_obj = Users.get_user_by_id(user_id)
|
||||
if not user_obj:
|
||||
raise ValueError(f"无法获取用户对象,用户ID: {user_id}")
|
||||
raise ValueError(f"无法获取用户对象,用户ID: {user_id}")
|
||||
|
||||
llm_response = await generate_chat_completion(
|
||||
__request__, llm_payload, user_obj
|
||||
@@ -1084,26 +1411,67 @@ class Action:
|
||||
user_language,
|
||||
)
|
||||
|
||||
# 检查输出模式
|
||||
if self.valves.OUTPUT_MODE == "image":
|
||||
# 图片模式: 使用 JavaScript 渲染并嵌入为 Markdown 图片
|
||||
chat_id = self._extract_chat_id(body, __metadata__)
|
||||
message_id = self._extract_message_id(body, __metadata__)
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"思维导图: 正在渲染图片...",
|
||||
False,
|
||||
)
|
||||
|
||||
if __event_call__:
|
||||
js_code = self._generate_image_js_code(
|
||||
unique_id=unique_id,
|
||||
chat_id=chat_id,
|
||||
message_id=message_id,
|
||||
markdown_syntax=markdown_syntax,
|
||||
svg_width=self.valves.SVG_WIDTH,
|
||||
svg_height=self.valves.SVG_HEIGHT,
|
||||
)
|
||||
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "思维导图: 图片已生成!", True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"思维导图图片已生成,{user_name}!",
|
||||
"success",
|
||||
)
|
||||
logger.info("Action: 思维导图 (v0.9.0) 图片模式完成")
|
||||
return body
|
||||
|
||||
# HTML 模式(默认): 嵌入为 HTML 块
|
||||
html_embed_tag = f"```html\n{final_html}\n```"
|
||||
body["messages"][-1]["content"] = f"{long_text_content}\n\n{html_embed_tag}"
|
||||
|
||||
await self._emit_status(__event_emitter__, "思维导图: 绘制完成!", True)
|
||||
await self._emit_status(__event_emitter__, "思维导图: 绘制完成!", True)
|
||||
await self._emit_notification(
|
||||
__event_emitter__, f"思维导图已生成,{user_name}!", "success"
|
||||
__event_emitter__, f"思维导图已生成,{user_name}!", "success"
|
||||
)
|
||||
logger.info("Action: 思维导图 (v12) completed successfully")
|
||||
logger.info("Action: 思维导图 (v0.9.0) HTML 模式完成")
|
||||
|
||||
except Exception as e:
|
||||
error_message = f"思维导图处理失败: {str(e)}"
|
||||
logger.error(f"思维导图错误: {error_message}", exc_info=True)
|
||||
user_facing_error = f"抱歉,思维导图在处理时遇到错误: {str(e)}。\n请检查Open WebUI后端日志获取更多详情。"
|
||||
user_facing_error = f"抱歉,思维导图在处理时遇到错误: {str(e)}。\n请检查Open WebUI后端日志获取更多详情。"
|
||||
body["messages"][-1][
|
||||
"content"
|
||||
] = f"{long_text_content}\n\n❌ **错误:** {user_facing_error}"
|
||||
|
||||
await self._emit_status(__event_emitter__, "思维导图: 处理失败。", True)
|
||||
await self._emit_notification(
|
||||
__event_emitter__, f"思维导图生成失败, {user_name}!", "error"
|
||||
__event_emitter__, f"思维导图生成失败, {user_name}!", "error"
|
||||
)
|
||||
|
||||
return body
|
||||
|
||||
550
scripts/openwebui_stats.py
Normal file
550
scripts/openwebui_stats.py
Normal file
@@ -0,0 +1,550 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
OpenWebUI 社区统计工具
|
||||
|
||||
获取并统计你在 openwebui.com 上发布的插件/帖子数据。
|
||||
|
||||
使用方法:
|
||||
1. 设置环境变量:
|
||||
- OPENWEBUI_API_KEY: 你的 API Key
|
||||
- OPENWEBUI_USER_ID: 你的用户 ID
|
||||
2. 运行: python scripts/openwebui_stats.py
|
||||
|
||||
获取 API Key:
|
||||
访问 https://openwebui.com/settings/api 创建 API Key (sk-开头)
|
||||
|
||||
获取 User ID:
|
||||
从个人主页的 API 请求中获取,格式如: b15d1348-4347-42b4-b815-e053342d6cb0
|
||||
"""
|
||||
|
||||
import os
|
||||
import json
|
||||
import requests
|
||||
from datetime import datetime, timezone, timedelta
|
||||
from typing import Optional
|
||||
from pathlib import Path
|
||||
|
||||
# 北京时区 (UTC+8)
|
||||
BEIJING_TZ = timezone(timedelta(hours=8))
|
||||
|
||||
|
||||
def get_beijing_time() -> datetime:
|
||||
"""获取当前北京时间"""
|
||||
return datetime.now(BEIJING_TZ)
|
||||
|
||||
|
||||
# 尝试加载 .env 文件
|
||||
try:
|
||||
from dotenv import load_dotenv
|
||||
|
||||
load_dotenv()
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
|
||||
class OpenWebUIStats:
|
||||
"""OpenWebUI 社区统计工具"""
|
||||
|
||||
BASE_URL = "https://api.openwebui.com/api/v1"
|
||||
|
||||
def __init__(self, api_key: str, user_id: Optional[str] = None):
|
||||
"""
|
||||
初始化统计工具
|
||||
|
||||
Args:
|
||||
api_key: OpenWebUI API Key (JWT Token)
|
||||
user_id: 用户 ID,如果为 None 则从 token 中解析
|
||||
"""
|
||||
self.api_key = api_key
|
||||
self.user_id = user_id or self._parse_user_id_from_token(api_key)
|
||||
self.session = requests.Session()
|
||||
self.session.headers.update(
|
||||
{
|
||||
"Authorization": f"Bearer {api_key}",
|
||||
"Accept": "application/json",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
)
|
||||
|
||||
def _parse_user_id_from_token(self, token: str) -> str:
|
||||
"""从 JWT Token 中解析用户 ID"""
|
||||
import base64
|
||||
|
||||
try:
|
||||
# JWT 格式: header.payload.signature
|
||||
payload = token.split(".")[1]
|
||||
# 添加 padding
|
||||
padding = 4 - len(payload) % 4
|
||||
if padding != 4:
|
||||
payload += "=" * padding
|
||||
decoded = base64.urlsafe_b64decode(payload)
|
||||
data = json.loads(decoded)
|
||||
return data.get("id", "")
|
||||
except Exception as e:
|
||||
print(f"⚠️ 无法从 Token 解析用户 ID: {e}")
|
||||
return ""
|
||||
|
||||
def get_user_posts(self, sort: str = "new", page: int = 1) -> list:
|
||||
"""
|
||||
获取用户发布的帖子列表
|
||||
|
||||
Args:
|
||||
sort: 排序方式 (new/top/hot)
|
||||
page: 页码
|
||||
|
||||
Returns:
|
||||
帖子列表
|
||||
"""
|
||||
url = f"{self.BASE_URL}/posts/users/{self.user_id}"
|
||||
params = {"sort": sort, "page": page}
|
||||
|
||||
response = self.session.get(url, params=params)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
def get_all_posts(self, sort: str = "new") -> list:
|
||||
"""获取所有帖子(自动分页)"""
|
||||
all_posts = []
|
||||
page = 1
|
||||
|
||||
while True:
|
||||
posts = self.get_user_posts(sort=sort, page=page)
|
||||
if not posts:
|
||||
break
|
||||
all_posts.extend(posts)
|
||||
page += 1
|
||||
|
||||
return all_posts
|
||||
|
||||
def generate_stats(self, posts: list) -> dict:
|
||||
"""生成统计数据"""
|
||||
stats = {
|
||||
"total_posts": len(posts),
|
||||
"total_downloads": 0,
|
||||
"total_views": 0,
|
||||
"total_upvotes": 0,
|
||||
"total_downvotes": 0,
|
||||
"total_saves": 0,
|
||||
"total_comments": 0,
|
||||
"by_type": {},
|
||||
"posts": [],
|
||||
"user": {}, # 用户信息
|
||||
}
|
||||
|
||||
# 从第一个帖子中提取用户信息
|
||||
if posts and "user" in posts[0]:
|
||||
user = posts[0]["user"]
|
||||
stats["user"] = {
|
||||
"username": user.get("username", ""),
|
||||
"name": user.get("name", ""),
|
||||
"profile_url": f"https://openwebui.com/u/{user.get('username', '')}",
|
||||
"profile_image": user.get("profileImageUrl", ""),
|
||||
"followers": user.get("followerCount", 0),
|
||||
"following": user.get("followingCount", 0),
|
||||
"total_points": user.get("totalPoints", 0),
|
||||
"post_points": user.get("postPoints", 0),
|
||||
"comment_points": user.get("commentPoints", 0),
|
||||
"contributions": user.get("totalContributions", 0),
|
||||
}
|
||||
|
||||
for post in posts:
|
||||
# 累计统计
|
||||
stats["total_downloads"] += post.get("downloads", 0)
|
||||
stats["total_views"] += post.get("views", 0)
|
||||
stats["total_upvotes"] += post.get("upvotes", 0)
|
||||
stats["total_downvotes"] += post.get("downvotes", 0)
|
||||
stats["total_saves"] += post.get("saveCount", 0)
|
||||
stats["total_comments"] += post.get("commentCount", 0)
|
||||
|
||||
# 解析 data 字段 - 正确路径: data.function.meta
|
||||
function_data = post.get("data", {}).get("function", {})
|
||||
meta = function_data.get("meta", {})
|
||||
manifest = meta.get("manifest", {})
|
||||
post_type = meta.get("type", function_data.get("type", "unknown"))
|
||||
|
||||
if post_type not in stats["by_type"]:
|
||||
stats["by_type"][post_type] = 0
|
||||
stats["by_type"][post_type] += 1
|
||||
|
||||
# 单个帖子信息
|
||||
created_at = datetime.fromtimestamp(post.get("createdAt", 0))
|
||||
updated_at = datetime.fromtimestamp(post.get("updatedAt", 0))
|
||||
|
||||
stats["posts"].append(
|
||||
{
|
||||
"title": post.get("title", ""),
|
||||
"slug": post.get("slug", ""),
|
||||
"type": post_type,
|
||||
"version": manifest.get("version", ""),
|
||||
"author": manifest.get("author", ""),
|
||||
"description": meta.get("description", ""),
|
||||
"downloads": post.get("downloads", 0),
|
||||
"views": post.get("views", 0),
|
||||
"upvotes": post.get("upvotes", 0),
|
||||
"saves": post.get("saveCount", 0),
|
||||
"comments": post.get("commentCount", 0),
|
||||
"created_at": created_at.strftime("%Y-%m-%d"),
|
||||
"updated_at": updated_at.strftime("%Y-%m-%d"),
|
||||
"url": f"https://openwebui.com/posts/{post.get('slug', '')}",
|
||||
}
|
||||
)
|
||||
|
||||
# 按下载量排序
|
||||
stats["posts"].sort(key=lambda x: x["downloads"], reverse=True)
|
||||
|
||||
return stats
|
||||
|
||||
def print_stats(self, stats: dict):
|
||||
"""打印统计报告到终端"""
|
||||
print("\n" + "=" * 60)
|
||||
print("📊 OpenWebUI 社区统计报告")
|
||||
print("=" * 60)
|
||||
print(f"📅 生成时间 (北京): {get_beijing_time().strftime('%Y-%m-%d %H:%M')}")
|
||||
print()
|
||||
|
||||
# 总览
|
||||
print("📈 总览")
|
||||
print("-" * 40)
|
||||
print(f" 📝 发布数量: {stats['total_posts']}")
|
||||
print(f" ⬇️ 总下载量: {stats['total_downloads']}")
|
||||
print(f" 👁️ 总浏览量: {stats['total_views']}")
|
||||
print(f" 👍 总点赞数: {stats['total_upvotes']}")
|
||||
print(f" 💾 总收藏数: {stats['total_saves']}")
|
||||
print(f" 💬 总评论数: {stats['total_comments']}")
|
||||
print()
|
||||
|
||||
# 按类型分类
|
||||
print("📂 按类型分类")
|
||||
print("-" * 40)
|
||||
for post_type, count in stats["by_type"].items():
|
||||
print(f" • {post_type}: {count}")
|
||||
print()
|
||||
|
||||
# 详细列表
|
||||
print("📋 发布列表 (按下载量排序)")
|
||||
print("-" * 60)
|
||||
|
||||
# 表头
|
||||
print(f"{'排名':<4} {'标题':<30} {'下载':<8} {'浏览':<8} {'点赞':<6}")
|
||||
print("-" * 60)
|
||||
|
||||
for i, post in enumerate(stats["posts"], 1):
|
||||
title = (
|
||||
post["title"][:28] + ".." if len(post["title"]) > 30 else post["title"]
|
||||
)
|
||||
print(
|
||||
f"{i:<4} {title:<30} {post['downloads']:<8} {post['views']:<8} {post['upvotes']:<6}"
|
||||
)
|
||||
|
||||
print("=" * 60)
|
||||
|
||||
def generate_markdown(self, stats: dict, lang: str = "zh") -> str:
|
||||
"""
|
||||
生成 Markdown 格式报告
|
||||
|
||||
Args:
|
||||
stats: 统计数据
|
||||
lang: 语言 ("zh" 中文, "en" 英文)
|
||||
"""
|
||||
# 中英文文本
|
||||
texts = {
|
||||
"zh": {
|
||||
"title": "# 📊 OpenWebUI 社区统计报告",
|
||||
"updated": f"> 📅 更新时间 (北京): {get_beijing_time().strftime('%Y-%m-%d %H:%M')}",
|
||||
"overview_title": "## 📈 总览",
|
||||
"overview_header": "| 指标 | 数值 |",
|
||||
"posts": "📝 发布数量",
|
||||
"downloads": "⬇️ 总下载量",
|
||||
"views": "👁️ 总浏览量",
|
||||
"upvotes": "👍 总点赞数",
|
||||
"saves": "💾 总收藏数",
|
||||
"comments": "💬 总评论数",
|
||||
"type_title": "## 📂 按类型分类",
|
||||
"list_title": "## 📋 发布列表",
|
||||
"list_header": "| 排名 | 标题 | 类型 | 版本 | 下载 | 浏览 | 点赞 | 收藏 | 更新日期 |",
|
||||
},
|
||||
"en": {
|
||||
"title": "# 📊 OpenWebUI Community Stats Report",
|
||||
"updated": f"> 📅 Updated (Beijing Time): {get_beijing_time().strftime('%Y-%m-%d %H:%M')}",
|
||||
"overview_title": "## 📈 Overview",
|
||||
"overview_header": "| Metric | Value |",
|
||||
"posts": "📝 Total Posts",
|
||||
"downloads": "⬇️ Total Downloads",
|
||||
"views": "👁️ Total Views",
|
||||
"upvotes": "👍 Total Upvotes",
|
||||
"saves": "💾 Total Saves",
|
||||
"comments": "💬 Total Comments",
|
||||
"type_title": "## 📂 By Type",
|
||||
"list_title": "## 📋 Posts List",
|
||||
"list_header": "| Rank | Title | Type | Version | Downloads | Views | Upvotes | Saves | Updated |",
|
||||
},
|
||||
}
|
||||
|
||||
t = texts.get(lang, texts["en"])
|
||||
|
||||
md = []
|
||||
md.append(t["title"])
|
||||
md.append("")
|
||||
md.append(t["updated"])
|
||||
md.append("")
|
||||
|
||||
# 总览
|
||||
md.append(t["overview_title"])
|
||||
md.append("")
|
||||
md.append(t["overview_header"])
|
||||
md.append("|------|------|")
|
||||
md.append(f"| {t['posts']} | {stats['total_posts']} |")
|
||||
md.append(f"| {t['downloads']} | {stats['total_downloads']} |")
|
||||
md.append(f"| {t['views']} | {stats['total_views']} |")
|
||||
md.append(f"| {t['upvotes']} | {stats['total_upvotes']} |")
|
||||
md.append(f"| {t['saves']} | {stats['total_saves']} |")
|
||||
md.append(f"| {t['comments']} | {stats['total_comments']} |")
|
||||
md.append("")
|
||||
|
||||
# 按类型分类
|
||||
md.append(t["type_title"])
|
||||
md.append("")
|
||||
for post_type, count in stats["by_type"].items():
|
||||
md.append(f"- **{post_type}**: {count}")
|
||||
md.append("")
|
||||
|
||||
# 详细列表
|
||||
md.append(t["list_title"])
|
||||
md.append("")
|
||||
md.append(t["list_header"])
|
||||
md.append("|:---:|------|:---:|:---:|:---:|:---:|:---:|:---:|:---:|")
|
||||
|
||||
for i, post in enumerate(stats["posts"], 1):
|
||||
title_link = f"[{post['title']}]({post['url']})"
|
||||
md.append(
|
||||
f"| {i} | {title_link} | {post['type']} | {post['version']} | "
|
||||
f"{post['downloads']} | {post['views']} | {post['upvotes']} | "
|
||||
f"{post['saves']} | {post['updated_at']} |"
|
||||
)
|
||||
|
||||
md.append("")
|
||||
return "\n".join(md)
|
||||
|
||||
def save_json(self, stats: dict, filepath: str):
|
||||
"""保存 JSON 格式数据"""
|
||||
with open(filepath, "w", encoding="utf-8") as f:
|
||||
json.dump(stats, f, ensure_ascii=False, indent=2)
|
||||
print(f"✅ JSON 数据已保存到: {filepath}")
|
||||
|
||||
def generate_readme_stats(self, stats: dict, lang: str = "zh") -> str:
|
||||
"""
|
||||
生成 README 统计徽章区域
|
||||
|
||||
Args:
|
||||
stats: 统计数据
|
||||
lang: 语言 ("zh" 中文, "en" 英文)
|
||||
"""
|
||||
# 获取 Top 5 插件
|
||||
top_plugins = stats["posts"][:5]
|
||||
|
||||
# 中英文文本
|
||||
texts = {
|
||||
"zh": {
|
||||
"title": "## 📊 社区统计",
|
||||
"updated": f"> 🕐 自动更新于 {get_beijing_time().strftime('%Y-%m-%d %H:%M')} (北京时间)",
|
||||
"author_header": "| 👤 作者 | 👥 粉丝 | ⭐ 积分 | 🏆 贡献 |",
|
||||
"header": "| 📝 发布 | ⬇️ 下载 | 👁️ 浏览 | 👍 点赞 | 💾 收藏 |",
|
||||
"top5_title": "### 🔥 热门插件 Top 5",
|
||||
"top5_header": "| 排名 | 插件 | 下载 | 浏览 |",
|
||||
"full_stats": "*完整统计请查看 [社区统计报告](./docs/community-stats.md)*",
|
||||
},
|
||||
"en": {
|
||||
"title": "## 📊 Community Stats",
|
||||
"updated": f"> 🕐 Auto-updated: {get_beijing_time().strftime('%Y-%m-%d %H:%M')} (Beijing Time)",
|
||||
"author_header": "| 👤 Author | 👥 Followers | ⭐ Points | 🏆 Contributions |",
|
||||
"header": "| 📝 Posts | ⬇️ Downloads | 👁️ Views | 👍 Upvotes | 💾 Saves |",
|
||||
"top5_title": "### 🔥 Top 5 Popular Plugins",
|
||||
"top5_header": "| Rank | Plugin | Downloads | Views |",
|
||||
"full_stats": "*See full stats in [Community Stats Report](./docs/community-stats.md)*",
|
||||
},
|
||||
}
|
||||
|
||||
t = texts.get(lang, texts["en"])
|
||||
user = stats.get("user", {})
|
||||
|
||||
lines = []
|
||||
lines.append("<!-- STATS_START -->")
|
||||
lines.append(t["title"])
|
||||
lines.append("")
|
||||
lines.append(t["updated"])
|
||||
lines.append("")
|
||||
|
||||
# 作者信息表格
|
||||
if user:
|
||||
username = user.get("username", "")
|
||||
profile_url = user.get("profile_url", "")
|
||||
lines.append(t["author_header"])
|
||||
lines.append("|:---:|:---:|:---:|:---:|")
|
||||
lines.append(
|
||||
f"| [{username}]({profile_url}) | **{user.get('followers', 0)}** | "
|
||||
f"**{user.get('total_points', 0)}** | **{user.get('contributions', 0)}** |"
|
||||
)
|
||||
lines.append("")
|
||||
|
||||
# 统计徽章表格
|
||||
lines.append(t["header"])
|
||||
lines.append("|:---:|:---:|:---:|:---:|:---:|")
|
||||
lines.append(
|
||||
f"| **{stats['total_posts']}** | **{stats['total_downloads']}** | "
|
||||
f"**{stats['total_views']}** | **{stats['total_upvotes']}** | **{stats['total_saves']}** |"
|
||||
)
|
||||
lines.append("")
|
||||
|
||||
# Top 5 热门插件
|
||||
lines.append(t["top5_title"])
|
||||
lines.append("")
|
||||
lines.append(t["top5_header"])
|
||||
lines.append("|:---:|------|:---:|:---:|")
|
||||
|
||||
medals = ["🥇", "🥈", "🥉", "4️⃣", "5️⃣"]
|
||||
for i, post in enumerate(top_plugins):
|
||||
medal = medals[i] if i < len(medals) else str(i + 1)
|
||||
lines.append(
|
||||
f"| {medal} | [{post['title']}]({post['url']}) | {post['downloads']} | {post['views']} |"
|
||||
)
|
||||
|
||||
lines.append("")
|
||||
lines.append(t["full_stats"])
|
||||
lines.append("<!-- STATS_END -->")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
def update_readme(self, stats: dict, readme_path: str, lang: str = "zh"):
|
||||
"""
|
||||
更新 README 文件中的统计区域
|
||||
|
||||
Args:
|
||||
stats: 统计数据
|
||||
readme_path: README 文件路径
|
||||
lang: 语言 ("zh" 中文, "en" 英文)
|
||||
"""
|
||||
import re
|
||||
|
||||
# 读取现有内容
|
||||
with open(readme_path, "r", encoding="utf-8") as f:
|
||||
content = f.read()
|
||||
|
||||
# 生成新的统计区域
|
||||
new_stats = self.generate_readme_stats(stats, lang)
|
||||
|
||||
# 检查是否已有统计区域
|
||||
pattern = r"<!-- STATS_START -->.*?<!-- STATS_END -->"
|
||||
if re.search(pattern, content, re.DOTALL):
|
||||
# 替换现有区域
|
||||
new_content = re.sub(pattern, new_stats, content, flags=re.DOTALL)
|
||||
else:
|
||||
# 在简介段落之后插入统计区域
|
||||
# 查找模式:标题 -> 语言切换行 -> 简介段落 -> 插入位置
|
||||
lines = content.split("\n")
|
||||
insert_pos = 0
|
||||
found_intro = False
|
||||
|
||||
for i, line in enumerate(lines):
|
||||
# 跳过标题
|
||||
if line.startswith("# "):
|
||||
continue
|
||||
# 跳过空行
|
||||
if line.strip() == "":
|
||||
continue
|
||||
# 跳过语言切换行 (如 "English | [中文]" 或 "[English] | 中文")
|
||||
if ("English" in line or "中文" in line) and "|" in line:
|
||||
continue
|
||||
# 找到第一个非空、非标题、非语言切换的段落(简介)
|
||||
if not found_intro:
|
||||
found_intro = True
|
||||
# 继续到这个段落结束
|
||||
continue
|
||||
# 简介段落后的空行或下一个标题就是插入位置
|
||||
if line.strip() == "" or line.startswith("#"):
|
||||
insert_pos = i
|
||||
break
|
||||
|
||||
# 如果没找到合适位置,就放在第3行(标题和语言切换后)
|
||||
if insert_pos == 0:
|
||||
insert_pos = 3
|
||||
|
||||
# 在适当位置插入
|
||||
lines.insert(insert_pos, "")
|
||||
lines.insert(insert_pos + 1, new_stats)
|
||||
lines.insert(insert_pos + 2, "")
|
||||
new_content = "\n".join(lines)
|
||||
|
||||
# 写回文件
|
||||
with open(readme_path, "w", encoding="utf-8") as f:
|
||||
f.write(new_content)
|
||||
|
||||
print(f"✅ README 已更新: {readme_path}")
|
||||
|
||||
|
||||
def main():
|
||||
"""主函数"""
|
||||
# 获取配置
|
||||
api_key = os.getenv("OPENWEBUI_API_KEY")
|
||||
user_id = os.getenv("OPENWEBUI_USER_ID")
|
||||
|
||||
if not api_key:
|
||||
print("❌ 错误: 未设置 OPENWEBUI_API_KEY 环境变量")
|
||||
print("请设置环境变量:")
|
||||
print(" export OPENWEBUI_API_KEY='your_api_key_here'")
|
||||
return 1
|
||||
|
||||
if not user_id:
|
||||
print("❌ 错误: 未设置 OPENWEBUI_USER_ID 环境变量")
|
||||
print("请设置环境变量:")
|
||||
print(" export OPENWEBUI_USER_ID='your_user_id_here'")
|
||||
print("\n提示: 用户 ID 可以从之前的 curl 请求中获取")
|
||||
print(" 例如: b15d1348-4347-42b4-b815-e053342d6cb0")
|
||||
return 1
|
||||
|
||||
# 初始化
|
||||
stats_client = OpenWebUIStats(api_key, user_id)
|
||||
print(f"🔍 用户 ID: {stats_client.user_id}")
|
||||
|
||||
# 获取所有帖子
|
||||
print("📥 正在获取帖子数据...")
|
||||
posts = stats_client.get_all_posts()
|
||||
print(f"✅ 获取到 {len(posts)} 个帖子")
|
||||
|
||||
# 生成统计
|
||||
stats = stats_client.generate_stats(posts)
|
||||
|
||||
# 打印到终端
|
||||
stats_client.print_stats(stats)
|
||||
|
||||
# 保存 Markdown 报告 (中英文双版本)
|
||||
script_dir = Path(__file__).parent.parent
|
||||
|
||||
# 中文报告
|
||||
md_zh_path = script_dir / "docs" / "community-stats.md"
|
||||
md_zh_content = stats_client.generate_markdown(stats, lang="zh")
|
||||
with open(md_zh_path, "w", encoding="utf-8") as f:
|
||||
f.write(md_zh_content)
|
||||
print(f"\n✅ 中文报告已保存到: {md_zh_path}")
|
||||
|
||||
# 英文报告
|
||||
md_en_path = script_dir / "docs" / "community-stats.en.md"
|
||||
md_en_content = stats_client.generate_markdown(stats, lang="en")
|
||||
with open(md_en_path, "w", encoding="utf-8") as f:
|
||||
f.write(md_en_content)
|
||||
print(f"✅ 英文报告已保存到: {md_en_path}")
|
||||
|
||||
# 保存 JSON 数据
|
||||
json_path = script_dir / "docs" / "community-stats.json"
|
||||
stats_client.save_json(stats, str(json_path))
|
||||
|
||||
# 更新 README 文件
|
||||
readme_path = script_dir / "README.md"
|
||||
readme_cn_path = script_dir / "README_CN.md"
|
||||
stats_client.update_readme(stats, str(readme_path), lang="en")
|
||||
stats_client.update_readme(stats, str(readme_cn_path), lang="zh")
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
exit(main())
|
||||
Reference in New Issue
Block a user