Compare commits
118 Commits
v2026.01.0
...
v2026.01.1
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
ef34cc326c | ||
|
|
5fa56ba88d | ||
|
|
b71df8ef43 | ||
|
|
8c6fe6784e | ||
|
|
29fa5bae29 | ||
|
|
dab465d924 | ||
|
|
77c0defe93 | ||
|
|
80cf2b5a52 | ||
|
|
96638d8092 | ||
|
|
21ad55ae55 | ||
|
|
530a6cd463 | ||
|
|
8615773b67 | ||
|
|
16eaec64b7 | ||
|
|
8558077dfe | ||
|
|
a15353ea52 | ||
|
|
5b44e3e688 | ||
|
|
a4b3628e01 | ||
|
|
bbb7db3878 | ||
|
|
dec2bbb4bf | ||
|
|
6a241b0ae0 | ||
|
|
51c53e0ed0 | ||
|
|
8cb6382e72 | ||
|
|
5889471e82 | ||
|
|
ca2e0b4fba | ||
|
|
10d24fbfa2 | ||
|
|
322bd6e167 | ||
|
|
3cc4478dd9 | ||
|
|
59f6f2ba97 | ||
|
|
172d9e0b41 | ||
|
|
de7086c9e1 | ||
|
|
5f63e8d1e2 | ||
|
|
3da0b894fd | ||
|
|
ad2d26aa16 | ||
|
|
a09f3e0bdb | ||
|
|
3a0faf27df | ||
|
|
cd3e7309a8 | ||
|
|
54cc10bb41 | ||
|
|
24e7d34524 | ||
|
|
a58ce9e99e | ||
|
|
4a42dcf8de | ||
|
|
5903ea0e40 | ||
|
|
6d7a5b45cf | ||
|
|
10433d38b3 | ||
|
|
bf2bc80b22 | ||
|
|
1e0f5fb65a | ||
|
|
7d5a696106 | ||
|
|
cf86012d4d | ||
|
|
961c1cbca6 | ||
|
|
7fb5c243fa | ||
|
|
f845281b72 | ||
|
|
0b2c6a2d36 | ||
|
|
245c37b2c3 | ||
|
|
d2a915a514 | ||
|
|
ae731f9bd6 | ||
|
|
2a8a8c5805 | ||
|
|
deb1272f62 | ||
|
|
51c41b8628 | ||
|
|
37893ded00 | ||
|
|
38fe50a898 | ||
|
|
1c731e70dc | ||
|
|
a55aa4d8fd | ||
|
|
6c79cb2f11 | ||
|
|
ba7943bd6f | ||
|
|
6eb09c3eaa | ||
|
|
63c5257162 | ||
|
|
a2422262b5 | ||
|
|
4f49b111fd | ||
|
|
1d066fc1f0 | ||
|
|
e960c40351 | ||
|
|
96284a3652 | ||
|
|
ad2f38ec1f | ||
|
|
87fc34d505 | ||
|
|
2aafd3cef7 | ||
|
|
afec54c4e0 | ||
|
|
905a9e67ca | ||
|
|
ce56815e77 | ||
|
|
2684098be1 | ||
|
|
57ebf24c75 | ||
|
|
9375df709f | ||
|
|
255e48bd33 | ||
|
|
18993c7fbe | ||
|
|
f3cf2b52fd | ||
|
|
856f76cd27 | ||
|
|
28bb9000d8 | ||
|
|
d0b9e46b74 | ||
|
|
a0a4d31715 | ||
|
|
d5f394f5f1 | ||
|
|
a477d2baad | ||
|
|
8471680efe | ||
|
|
4d44b72dab | ||
|
|
88e14d251a | ||
|
|
e446b6474d | ||
|
|
a2eda6e5af | ||
|
|
fe80c8bee3 | ||
|
|
133315d0c6 | ||
|
|
3907644282 | ||
|
|
d8cde2115f | ||
|
|
0ce63b548f | ||
|
|
06e81c0194 | ||
|
|
3763e6501d | ||
|
|
5911f75641 | ||
|
|
f936181a37 | ||
|
|
a7651f33a4 | ||
|
|
45ddf5092b | ||
|
|
61294e90e4 | ||
|
|
8619405802 | ||
|
|
f0017ffacd | ||
|
|
65fe16e185 | ||
|
|
136e7e9021 | ||
|
|
c1a660a2a1 | ||
|
|
53f04debaf | ||
|
|
4b9790df00 | ||
|
|
58452a8441 | ||
|
|
e104161007 | ||
|
|
6de0d6fbe4 | ||
|
|
28d55c1469 | ||
|
|
59933e9361 | ||
|
|
7cbd0e2920 |
@@ -25,6 +25,10 @@ Every plugin **MUST** have bilingual versions for both code and documentation:
|
||||
- **Valves**: Use `pydantic` for configuration.
|
||||
- **Database**: Re-use `open_webui.internal.db` shared connection.
|
||||
- **User Context**: Use `_get_user_context` helper method.
|
||||
- **Chat API**: For message updates, follow the "OpenWebUI Chat API 更新规范" in `.github/copilot-instructions.md`.
|
||||
- Use Event API for immediate UI updates
|
||||
- Use Chat Persistence API for database storage
|
||||
- Always update both `messages[]` and `history.messages`
|
||||
|
||||
### Commit Messages
|
||||
- **Language**: **English ONLY**. Do not use Chinese in commit messages.
|
||||
@@ -35,8 +39,8 @@ Every plugin **MUST** have bilingual versions for both code and documentation:
|
||||
When adding or updating a plugin, you **MUST** update the following documentation files to maintain consistency:
|
||||
|
||||
### Plugin Directory
|
||||
- `README.md`: Update version, description, and usage. **Explicitly describe new features.**
|
||||
- `README_CN.md`: Update version, description, and usage. **Explicitly describe new features.**
|
||||
- `README.md`: Update version, description, and usage. **Explicitly describe new features in a prominent position at the beginning.**
|
||||
- `README_CN.md`: Update version, description, and usage. **Explicitly describe new features in a prominent position at the beginning.**
|
||||
|
||||
### Global Documentation (`docs/`)
|
||||
- **Index Pages**:
|
||||
@@ -78,6 +82,11 @@ Reference: `.github/workflows/release.yml`
|
||||
- Generates release notes based on changes.
|
||||
- Creates a GitHub Release tag (e.g., `v2024.01.01-1`).
|
||||
- Uploads individual `.py` files of **changed plugins only** as assets.
|
||||
4. **Market Publishing**:
|
||||
- Workflow: `.github/workflows/publish_plugin.yml`
|
||||
- Trigger: Release published.
|
||||
- Action: Automatically updates the plugin code and metadata on OpenWebUI.com using `scripts/publish_plugin.py`.
|
||||
- Requirement: `OPENWEBUI_API_KEY` secret must be set.
|
||||
|
||||
### Pull Request Check
|
||||
- Workflow: `.github/workflows/plugin-version-check.yml`
|
||||
|
||||
632
.github/copilot-instructions.md
vendored
@@ -31,15 +31,75 @@ plugins/actions/export_to_docx/
|
||||
- `README.md` - English documentation
|
||||
- `README_CN.md` - 中文文档
|
||||
|
||||
README 文件应包含以下内容:
|
||||
- 功能描述 / Feature description
|
||||
- 配置参数及默认值 / Configuration parameters with defaults
|
||||
- 安装和设置说明 / Installation and setup instructions
|
||||
- 使用示例 / Usage examples
|
||||
- 故障排除指南 / Troubleshooting guide
|
||||
- 故障排除指南 / Troubleshooting guide
|
||||
- 版本和作者信息 / Version and author information
|
||||
- **新增功能 / New Features**: 如果是更新现有插件,必须明确列出并描述新增功能(发布到官方市场的重要要求)。/ If updating an existing plugin, explicitly list and describe new features (Critical for official market release).
|
||||
### README 结构规范 (README Structure Standard)
|
||||
|
||||
所有插件 README 必须遵循以下统一结构顺序:
|
||||
|
||||
1. **标题 (Title)**: 插件名称,带 Emoji 图标
|
||||
2. **元数据 (Metadata)**: 作者、版本、项目链接 (一行显示)
|
||||
- 格式: `**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** x.x.x | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)`
|
||||
- **注意**: Author 和 Project 为固定值,仅需更新 Version 版本号
|
||||
3. **描述 (Description)**: 一句话功能介绍
|
||||
4. **最新更新 (What's New)**: **必须**放在描述之后,显著展示最新版本的变更点
|
||||
5. **核心特性 (Key Features)**: 使用 Emoji + 粗体标题 + 描述格式
|
||||
6. **使用方法 (How to Use)**: 按步骤说明
|
||||
7. **配置参数 (Configuration/Valves)**: 使用表格格式,包含参数名、默认值、描述
|
||||
8. **其他 (Others)**: 支持的模板类型、语法示例、故障排除等
|
||||
|
||||
完整示例 (Full Example):
|
||||
|
||||
```markdown
|
||||
# 📊 Smart Plugin
|
||||
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 1.0.0 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
A one-sentence description of this plugin.
|
||||
|
||||
## 🔥 What's New in v1.0.0
|
||||
|
||||
- ✨ **Feature Name**: Brief description of the feature.
|
||||
- 🔧 **Configuration Change**: What changed in settings.
|
||||
- 🐛 **Bug Fix**: What was fixed.
|
||||
|
||||
## ✨ Key Features
|
||||
|
||||
- 🚀 **Feature A**: Description of feature A.
|
||||
- 🎨 **Feature B**: Description of feature B.
|
||||
- 📥 **Feature C**: Description of feature C.
|
||||
|
||||
## 🚀 How to Use
|
||||
|
||||
1. **Install**: Search for "Plugin Name" in the Open WebUI Community and install.
|
||||
2. **Trigger**: Enter your text in the chat, then click the **Action Button**.
|
||||
3. **Result**: View the generated result.
|
||||
|
||||
## ⚙️ Configuration (Valves)
|
||||
|
||||
| Parameter | Default | Description |
|
||||
| :--- | :--- | :--- |
|
||||
| **Show Status (SHOW_STATUS)** | `True` | Whether to show status updates. |
|
||||
| **Model ID (MODEL_ID)** | `Empty` | LLM model for processing. |
|
||||
| **Output Mode (OUTPUT_MODE)** | `image` | `image` for static, `html` for interactive. |
|
||||
|
||||
## 🛠️ Supported Types (Optional)
|
||||
|
||||
| Category | Type Name | Use Case |
|
||||
| :--- | :--- | :--- |
|
||||
| **Category A** | `type-a`, `type-b` | Use case description |
|
||||
|
||||
## 📝 Advanced Example (Optional)
|
||||
|
||||
\`\`\`syntax
|
||||
example code or syntax here
|
||||
\`\`\`
|
||||
```
|
||||
|
||||
### 文档内容要求 (Content Requirements)
|
||||
|
||||
- **新增功能**: 必须在 "What's New" 章节中明确列出,使用 Emoji + 粗体标题格式。
|
||||
- **双语**: 必须提供 `README.md` (英文) 和 `README_CN.md` (中文)。
|
||||
- **表格对齐**: 配置参数表格使用左对齐 `:---`。
|
||||
- **Emoji 规范**: 标题使用合适的 Emoji 增强可读性。
|
||||
|
||||
### 官方文档 (Official Documentation)
|
||||
|
||||
@@ -93,33 +153,7 @@ icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0i...(完整的 Base64 编
|
||||
|
||||
---
|
||||
|
||||
## 👤 作者和许可证信息 (Author and License)
|
||||
|
||||
所有 README 文件和主要文档必须包含以下统一信息:
|
||||
|
||||
```markdown
|
||||
## Author
|
||||
|
||||
Fu-Jie
|
||||
GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
## License
|
||||
|
||||
MIT License
|
||||
```
|
||||
|
||||
中文版本:
|
||||
|
||||
```markdown
|
||||
## 作者
|
||||
|
||||
Fu-Jie
|
||||
GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
## 许可证
|
||||
|
||||
MIT License
|
||||
```
|
||||
(Author info is now part of the top metadata section, see "README Structure Standard" above)
|
||||
|
||||
---
|
||||
|
||||
@@ -226,7 +260,46 @@ async def _emit_notification(
|
||||
|
||||
## 📋 日志规范 (Logging Standard)
|
||||
|
||||
- **禁止使用** `print()` 语句
|
||||
### 1. 前端控制台调试 (Frontend Console Debugging) - **优先推荐 (Preferred)**
|
||||
|
||||
对于需要实时查看数据流、排查 UI 交互或内容变更的场景,**优先使用**前端控制台日志。这种方式可以直接在浏览器 DevTools (F12) 中查看,无需访问服务端日志。
|
||||
|
||||
**实现方式**: 通过 `__event_emitter__` 发送 `type: "execute"` 事件执行 JS 代码。
|
||||
|
||||
```python
|
||||
import json
|
||||
|
||||
async def _emit_debug_log(self, __event_emitter__, title: str, data: dict):
|
||||
"""在浏览器控制台打印结构化调试日志"""
|
||||
if not self.valves.show_debug_log or not __event_emitter__:
|
||||
return
|
||||
|
||||
try:
|
||||
js_code = f"""
|
||||
(async function() {{
|
||||
console.group("🛠️ {title}");
|
||||
console.log({json.dumps(data, ensure_ascii=False)});
|
||||
console.groupEnd();
|
||||
}})();
|
||||
"""
|
||||
|
||||
await __event_emitter__({
|
||||
"type": "execute",
|
||||
"data": {"code": js_code}
|
||||
})
|
||||
except Exception as e:
|
||||
print(f"Error emitting debug log: {e}")
|
||||
```
|
||||
|
||||
**配置要求**:
|
||||
- 在 `Valves` 中添加 `show_debug_log: bool` 开关,默认关闭。
|
||||
- 仅在开关开启时发送日志。
|
||||
|
||||
### 2. 服务端日志 (Server-side Logging)
|
||||
|
||||
用于记录系统级错误、异常堆栈或无需前端感知的后台任务。
|
||||
|
||||
- **禁止使用** `print()` 语句 (除非用于简单的脚本调试)
|
||||
- 必须使用 Python 标准库 `logging`
|
||||
|
||||
```python
|
||||
@@ -507,7 +580,164 @@ Base = declarative_base()
|
||||
|
||||
---
|
||||
|
||||
## 🔧 代码规范 (Code Style)
|
||||
## 📂 文件存储访问规范 (File Storage Access)
|
||||
|
||||
OpenWebUI 支持多种文件存储后端(本地磁盘、S3/MinIO 对象存储等)。插件在访问用户上传的文件或生成的图片时,必须实现多级回退机制以兼容所有存储配置。
|
||||
|
||||
### 存储类型检测 (Storage Type Detection)
|
||||
|
||||
通过 `Files.get_file_by_id()` 获取的文件对象,其 `path` 属性决定了存储位置:
|
||||
|
||||
| Path 格式 | 存储类型 | 访问方式 |
|
||||
|-----------|----------|----------|
|
||||
| `s3://bucket/key` | S3/MinIO 对象存储 | boto3 直连或 API 回调 |
|
||||
| `/app/backend/data/...` | Docker 卷存储 | 本地文件系统读取 |
|
||||
| `./uploads/...` | 本地相对路径 | 本地文件系统读取 |
|
||||
| `gs://bucket/key` | Google Cloud Storage | API 回调 |
|
||||
|
||||
### 多级回退机制 (Multi-level Fallback)
|
||||
|
||||
推荐实现以下优先级的文件获取策略:
|
||||
|
||||
```python
|
||||
def _get_file_content(self, file_id: str, max_bytes: int) -> Optional[bytes]:
|
||||
"""获取文件内容,支持多种存储后端"""
|
||||
file_obj = Files.get_file_by_id(file_id)
|
||||
if not file_obj:
|
||||
return None
|
||||
|
||||
# 1️⃣ 数据库直接存储 (小文件)
|
||||
data_field = getattr(file_obj, "data", None)
|
||||
if isinstance(data_field, dict):
|
||||
if "bytes" in data_field:
|
||||
return data_field["bytes"]
|
||||
if "base64" in data_field:
|
||||
return base64.b64decode(data_field["base64"])
|
||||
|
||||
# 2️⃣ S3 直连 (对象存储 - 最快)
|
||||
s3_path = getattr(file_obj, "path", None)
|
||||
if isinstance(s3_path, str) and s3_path.startswith("s3://"):
|
||||
data = self._read_from_s3(s3_path, max_bytes)
|
||||
if data:
|
||||
return data
|
||||
|
||||
# 3️⃣ 本地文件系统 (磁盘存储)
|
||||
for attr in ("path", "file_path"):
|
||||
path = getattr(file_obj, attr, None)
|
||||
if path and not path.startswith(("s3://", "gs://", "http")):
|
||||
# 尝试多个常见路径
|
||||
for base in ["", "./data", "/app/backend/data"]:
|
||||
full_path = Path(base) / path if base else Path(path)
|
||||
if full_path.exists():
|
||||
return full_path.read_bytes()[:max_bytes]
|
||||
|
||||
# 4️⃣ 公共 URL 下载
|
||||
url = getattr(file_obj, "url", None)
|
||||
if url and url.startswith("http"):
|
||||
return self._download_from_url(url, max_bytes)
|
||||
|
||||
# 5️⃣ 内部 API 回调 (通用兜底方案)
|
||||
if self._api_base_url:
|
||||
api_url = f"{self._api_base_url}/api/v1/files/{file_id}/content"
|
||||
return self._download_from_api(api_url, self._api_token, max_bytes)
|
||||
|
||||
return None
|
||||
```
|
||||
|
||||
### S3 直连实现 (S3 Direct Access)
|
||||
|
||||
当检测到 `s3://` 路径时,使用 `boto3` 直接访问对象存储,读取以下环境变量:
|
||||
|
||||
| 环境变量 | 说明 | 示例 |
|
||||
|----------|------|------|
|
||||
| `S3_ENDPOINT_URL` | S3 兼容服务端点 | `https://minio.example.com` |
|
||||
| `S3_ACCESS_KEY_ID` | 访问密钥 ID | `minioadmin` |
|
||||
| `S3_SECRET_ACCESS_KEY` | 访问密钥 | `minioadmin` |
|
||||
| `S3_ADDRESSING_STYLE` | 寻址样式 | `auto`, `path`, `virtual` |
|
||||
|
||||
```python
|
||||
# S3 直连示例
|
||||
import boto3
|
||||
from botocore.config import Config as BotoConfig
|
||||
import os
|
||||
|
||||
def _read_from_s3(self, s3_path: str, max_bytes: int) -> Optional[bytes]:
|
||||
"""从 S3 直接读取文件 (比 API 回调更快)"""
|
||||
if not s3_path.startswith("s3://"):
|
||||
return None
|
||||
|
||||
# 解析 s3://bucket/key
|
||||
parts = s3_path[5:].split("/", 1)
|
||||
bucket, key = parts[0], parts[1]
|
||||
|
||||
# 从环境变量读取配置
|
||||
endpoint = os.environ.get("S3_ENDPOINT_URL")
|
||||
access_key = os.environ.get("S3_ACCESS_KEY_ID")
|
||||
secret_key = os.environ.get("S3_SECRET_ACCESS_KEY")
|
||||
|
||||
if not all([endpoint, access_key, secret_key]):
|
||||
return None # 回退到 API 方式
|
||||
|
||||
s3_client = boto3.client(
|
||||
"s3",
|
||||
endpoint_url=endpoint,
|
||||
aws_access_key_id=access_key,
|
||||
aws_secret_access_key=secret_key,
|
||||
config=BotoConfig(s3={"addressing_style": os.environ.get("S3_ADDRESSING_STYLE", "auto")})
|
||||
)
|
||||
|
||||
response = s3_client.get_object(Bucket=bucket, Key=key)
|
||||
return response["Body"].read(max_bytes)
|
||||
```
|
||||
|
||||
### API 回调实现 (API Fallback)
|
||||
|
||||
当其他方式失败时,通过 OpenWebUI 内部 API 获取文件:
|
||||
|
||||
```python
|
||||
def _download_from_api(self, api_url: str, token: str, max_bytes: int) -> Optional[bytes]:
|
||||
"""通过 OpenWebUI API 获取文件内容"""
|
||||
import urllib.request
|
||||
|
||||
headers = {"User-Agent": "OpenWebUI-Plugin"}
|
||||
if token:
|
||||
headers["Authorization"] = token
|
||||
|
||||
req = urllib.request.Request(api_url, headers=headers)
|
||||
with urllib.request.urlopen(req, timeout=15) as response:
|
||||
if 200 <= response.status < 300:
|
||||
return response.read(max_bytes)
|
||||
return None
|
||||
```
|
||||
|
||||
### 获取 API 上下文 (API Context Extraction)
|
||||
|
||||
在 `action()` 方法中捕获请求上下文,用于 API 回调:
|
||||
|
||||
```python
|
||||
async def action(self, body: dict, __request__=None, ...):
|
||||
# 从请求对象获取 API 凭证
|
||||
if __request__:
|
||||
self._api_token = __request__.headers.get("Authorization")
|
||||
self._api_base_url = str(__request__.base_url).rstrip("/")
|
||||
else:
|
||||
# 从环境变量获取端口作为备用
|
||||
port = os.environ.get("PORT") or "8080"
|
||||
self._api_base_url = f"http://localhost:{port}"
|
||||
self._api_token = None
|
||||
```
|
||||
|
||||
### 性能对比 (Performance Comparison)
|
||||
|
||||
| 方式 | 网络跳数 | 适用场景 |
|
||||
|------|----------|----------|
|
||||
| S3 直连 | 1 (插件 → S3) | 对象存储,最快 |
|
||||
| 本地文件 | 0 | 磁盘存储,最快 |
|
||||
| API 回调 | 2 (插件 → OpenWebUI → S3/磁盘) | 通用兜底 |
|
||||
|
||||
### 参考实现 (Reference Implementation)
|
||||
|
||||
- `plugins/actions/export_to_docx/export_to_word.py` - `_image_bytes_from_owui_file_id` 方法
|
||||
|
||||
### Python 规范
|
||||
|
||||
@@ -841,10 +1071,328 @@ 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 │
|
||||
├─────────────────────────────────────────────────────────────┤
|
||||
│ 3. Markdown 渲染 │
|
||||
│ └── 显示  │
|
||||
└─────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
#### 核心实现代码
|
||||
|
||||
**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, # 可视化所需数据
|
||||
)
|
||||
|
||||
# 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. 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
|
||||
- **高效存储**:图片上传至 `/api/v1/files`,避免 Base64 字符串膨胀聊天记录
|
||||
- **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 | 依赖 `/api/v1/files` 存储 |
|
||||
| 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
|
||||
|
||||
### OpenWebUI Chat API 更新规范 (Chat API Update Specification)
|
||||
|
||||
当插件需要修改消息内容并持久化到数据库时,必须遵循 OpenWebUI 的 Backend-Controlled API 流程。
|
||||
|
||||
When a plugin needs to modify message content and persist it to the database, follow OpenWebUI's Backend-Controlled API flow.
|
||||
|
||||
#### 核心概念 (Core Concepts)
|
||||
|
||||
1. **Event API** (`/api/v1/chats/{chatId}/messages/{messageId}/event`)
|
||||
- 用于**即时更新前端显示**,用户无需刷新页面
|
||||
- 是可选的,部分版本可能不支持
|
||||
- 仅影响当前会话的 UI,不持久化
|
||||
|
||||
2. **Chat Persistence API** (`/api/v1/chats/{chatId}`)
|
||||
- 用于**持久化到数据库**,确保刷新页面后数据仍存在
|
||||
- 必须同时更新 `messages[]` 数组和 `history.messages` 对象
|
||||
- 是消息持久化的唯一可靠方式
|
||||
|
||||
#### 数据结构 (Data Structure)
|
||||
|
||||
OpenWebUI 的 Chat 对象包含两个关键位置存储消息内容:
|
||||
|
||||
```javascript
|
||||
{
|
||||
"chat": {
|
||||
"id": "chat-uuid",
|
||||
"title": "Chat Title",
|
||||
"messages": [ // 1️⃣ 消息数组
|
||||
{ "id": "msg-1", "role": "user", "content": "..." },
|
||||
{ "id": "msg-2", "role": "assistant", "content": "..." }
|
||||
],
|
||||
"history": {
|
||||
"current_id": "msg-2",
|
||||
"messages": { // 2️⃣ 消息索引对象
|
||||
"msg-1": { "id": "msg-1", "role": "user", "content": "..." },
|
||||
"msg-2": { "id": "msg-2", "role": "assistant", "content": "..." }
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
> **重要**:修改消息时,**必须同时更新两个位置**,否则可能导致数据不一致。
|
||||
|
||||
#### 标准实现流程 (Standard Implementation)
|
||||
|
||||
```javascript
|
||||
(async function() {
|
||||
const chatId = "{chat_id}";
|
||||
const messageId = "{message_id}";
|
||||
const token = localStorage.getItem("token");
|
||||
|
||||
// 1️⃣ 获取当前 Chat 数据
|
||||
const getResponse = await fetch(`/api/v1/chats/${chatId}`, {
|
||||
method: "GET",
|
||||
headers: { "Authorization": `Bearer ${token}` }
|
||||
});
|
||||
const chatData = await getResponse.json();
|
||||
|
||||
// 2️⃣ 使用 map 遍历 messages,只修改目标消息
|
||||
let newContent = "";
|
||||
const updatedMessages = chatData.chat.messages.map(m => {
|
||||
if (m.id === messageId) {
|
||||
const originalContent = m.content || "";
|
||||
newContent = originalContent + "\n\n" + newMarkdown;
|
||||
|
||||
// 3️⃣ 同时更新 history.messages 中对应的消息
|
||||
if (chatData.chat.history && chatData.chat.history.messages) {
|
||||
if (chatData.chat.history.messages[messageId]) {
|
||||
chatData.chat.history.messages[messageId].content = newContent;
|
||||
}
|
||||
}
|
||||
|
||||
// 4️⃣ 保留消息的其他属性,只修改 content
|
||||
return { ...m, content: newContent };
|
||||
}
|
||||
return m; // 其他消息原样返回
|
||||
});
|
||||
|
||||
// 5️⃣ 通过 Event API 即时更新前端(可选)
|
||||
try {
|
||||
await fetch(`/api/v1/chats/${chatId}/messages/${messageId}/event`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${token}`
|
||||
},
|
||||
body: JSON.stringify({
|
||||
type: "chat:message",
|
||||
data: { content: newContent }
|
||||
})
|
||||
});
|
||||
} catch (e) {
|
||||
// Event API 是可选的,继续执行持久化
|
||||
console.log("Event API not available, continuing...");
|
||||
}
|
||||
|
||||
// 6️⃣ 持久化到数据库(必须)
|
||||
const updatePayload = {
|
||||
chat: {
|
||||
...chatData.chat, // 保留所有原有属性
|
||||
messages: updatedMessages
|
||||
// history 已在上面原地修改
|
||||
}
|
||||
};
|
||||
|
||||
await fetch(`/api/v1/chats/${chatId}`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${token}`
|
||||
},
|
||||
body: JSON.stringify(updatePayload)
|
||||
});
|
||||
})();
|
||||
```
|
||||
|
||||
#### 最佳实践 (Best Practices)
|
||||
|
||||
1. **保留原有结构**:使用展开运算符 `...chatData.chat` 和 `...m` 确保不丢失任何原有属性
|
||||
2. **双位置更新**:必须同时更新 `messages[]` 和 `history.messages[id]`
|
||||
3. **错误处理**:Event API 调用应包裹在 try-catch 中,失败时继续持久化
|
||||
4. **重试机制**:对持久化 API 实现重试逻辑,提高可靠性
|
||||
|
||||
```javascript
|
||||
// 带重试的请求函数
|
||||
const fetchWithRetry = async (url, options, retries = 3) => {
|
||||
for (let i = 0; i < retries; i++) {
|
||||
try {
|
||||
const response = await fetch(url, options);
|
||||
if (response.ok) return response;
|
||||
if (i < retries - 1) {
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1))); // 指数退避
|
||||
}
|
||||
} catch (e) {
|
||||
if (i === retries - 1) throw e;
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}
|
||||
}
|
||||
return null;
|
||||
};
|
||||
```
|
||||
|
||||
5. **禁止使用的 API**:不要使用 `/api/v1/chats/{chatId}/share` 作为持久化备用方案,该 API 用于分享功能,不是更新功能
|
||||
|
||||
#### 提取 Chat ID 和 Message ID (Extracting IDs)
|
||||
|
||||
```python
|
||||
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 ""
|
||||
```
|
||||
|
||||
#### 参考实现
|
||||
|
||||
- `plugins/actions/smart-mind-map/smart_mind_map.py` - 思维导图图片模式实现
|
||||
- 官方文档: [Backend-Controlled, UI-Compatible API Flow](https://docs.openwebui.com/tutorials/tips/backend-controlled-ui-compatible-api-flow)
|
||||
|
||||
---
|
||||
|
||||
|
||||
78
.github/workflows/community-stats.yml
vendored
Normal file
@@ -0,0 +1,78 @@
|
||||
# OpenWebUI 社区统计报告自动生成
|
||||
# 只在统计数据变化时 commit,避免频繁提交
|
||||
|
||||
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: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
pip install requests python-dotenv
|
||||
|
||||
- name: Get previous stats
|
||||
id: prev_stats
|
||||
run: |
|
||||
# 获取当前的 points 用于比较
|
||||
if [ -f docs/community-stats.json ]; then
|
||||
OLD_POINTS=$(jq -r '.user.total_points' docs/community-stats.json 2>/dev/null || echo "0")
|
||||
echo "old_points=$OLD_POINTS" >> $GITHUB_OUTPUT
|
||||
else
|
||||
echo "old_points=0" >> $GITHUB_OUTPUT
|
||||
fi
|
||||
|
||||
- name: Generate stats report
|
||||
env:
|
||||
OPENWEBUI_API_KEY: ${{ secrets.OPENWEBUI_API_KEY }}
|
||||
OPENWEBUI_USER_ID: ${{ secrets.OPENWEBUI_USER_ID }}
|
||||
run: |
|
||||
python scripts/openwebui_stats.py
|
||||
|
||||
- name: Check for significant changes
|
||||
id: check_changes
|
||||
run: |
|
||||
# 获取新的 points
|
||||
NEW_POINTS=$(jq -r '.user.total_points' docs/community-stats.json 2>/dev/null || echo "0")
|
||||
|
||||
echo "📊 Previous points: ${{ steps.prev_stats.outputs.old_points }}"
|
||||
echo "📊 Current points: $NEW_POINTS"
|
||||
|
||||
# 只在 points 变化时才 commit
|
||||
if [ "$NEW_POINTS" != "${{ steps.prev_stats.outputs.old_points }}" ]; then
|
||||
echo "changed=true" >> $GITHUB_OUTPUT
|
||||
echo "✅ Points changed (${{ steps.prev_stats.outputs.old_points }} → $NEW_POINTS), will commit"
|
||||
else
|
||||
echo "changed=false" >> $GITHUB_OUTPUT
|
||||
echo "⏭️ Points unchanged, skipping commit"
|
||||
fi
|
||||
|
||||
- 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.zh.md docs/community-stats.md docs/community-stats.json README.md README_CN.md
|
||||
git diff --staged --quiet || git commit -m "chore: update community stats $(date +'%Y-%m-%d')"
|
||||
git push
|
||||
68
.github/workflows/publish_new_plugin.yml
vendored
Normal file
@@ -0,0 +1,68 @@
|
||||
name: Publish New Plugin
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
plugin_dir:
|
||||
description: 'Plugin directory (e.g., plugins/actions/deep-dive)'
|
||||
required: true
|
||||
type: string
|
||||
dry_run:
|
||||
description: 'Dry run mode (preview only)'
|
||||
required: false
|
||||
type: boolean
|
||||
default: false
|
||||
|
||||
jobs:
|
||||
publish:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.x'
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
pip install requests
|
||||
|
||||
- name: Validate plugin directory
|
||||
run: |
|
||||
if [ ! -d "${{ github.event.inputs.plugin_dir }}" ]; then
|
||||
echo "❌ Error: Directory '${{ github.event.inputs.plugin_dir }}' does not exist"
|
||||
exit 1
|
||||
fi
|
||||
echo "✅ Found plugin directory: ${{ github.event.inputs.plugin_dir }}"
|
||||
ls -la "${{ github.event.inputs.plugin_dir }}"
|
||||
|
||||
- name: Publish Plugin
|
||||
env:
|
||||
OPENWEBUI_API_KEY: ${{ secrets.OPENWEBUI_API_KEY }}
|
||||
run: |
|
||||
if [ "${{ github.event.inputs.dry_run }}" = "true" ]; then
|
||||
echo "🔍 Dry run mode - previewing..."
|
||||
python scripts/publish_plugin.py --new "${{ github.event.inputs.plugin_dir }}" --dry-run
|
||||
else
|
||||
echo "🚀 Publishing plugin..."
|
||||
python scripts/publish_plugin.py --new "${{ github.event.inputs.plugin_dir }}"
|
||||
fi
|
||||
|
||||
- name: Commit changes (if ID was added)
|
||||
if: ${{ github.event.inputs.dry_run != 'true' }}
|
||||
run: |
|
||||
git config user.name "github-actions[bot]"
|
||||
git config user.email "github-actions[bot]@users.noreply.github.com"
|
||||
|
||||
# Check if there are changes to commit
|
||||
if git diff --quiet; then
|
||||
echo "No changes to commit"
|
||||
else
|
||||
git add "${{ github.event.inputs.plugin_dir }}"
|
||||
git commit -m "feat: add openwebui_id to ${{ github.event.inputs.plugin_dir }}"
|
||||
git push
|
||||
echo "✅ Committed and pushed openwebui_id changes"
|
||||
fi
|
||||
28
.github/workflows/publish_plugin.yml
vendored
Normal file
@@ -0,0 +1,28 @@
|
||||
name: Publish Plugins to OpenWebUI Market
|
||||
|
||||
on:
|
||||
release:
|
||||
types: [published]
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
publish:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.x'
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
pip install requests
|
||||
|
||||
- name: Publish Plugins
|
||||
env:
|
||||
OPENWEBUI_API_KEY: ${{ secrets.OPENWEBUI_API_KEY }}
|
||||
run: python scripts/publish_plugin.py
|
||||
45
.github/workflows/release.yml
vendored
@@ -180,14 +180,34 @@ jobs:
|
||||
|
||||
- name: Determine version
|
||||
id: version
|
||||
env:
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
run: |
|
||||
if [ "${{ github.event_name }}" = "workflow_dispatch" ] && [ -n "${{ github.event.inputs.version }}" ]; then
|
||||
VERSION="${{ github.event.inputs.version }}"
|
||||
elif [[ "${{ github.ref }}" == refs/tags/v* ]]; then
|
||||
VERSION="${GITHUB_REF#refs/tags/}"
|
||||
else
|
||||
# Auto-generate version based on date and run number
|
||||
VERSION="v$(date +'%Y.%m.%d')-${{ github.run_number }}"
|
||||
# Auto-generate version based on date and daily release count
|
||||
TODAY=$(date +'%Y.%m.%d')
|
||||
TODAY_PREFIX="v${TODAY}-"
|
||||
|
||||
# Count existing releases with today's date prefix
|
||||
# grep -c returns 1 if count is 0, so we use || true to avoid script failure
|
||||
EXISTING_COUNT=$(gh release list --limit 100 2>/dev/null | grep -c "^${TODAY_PREFIX}" || true)
|
||||
|
||||
# Clean up output (handle potential newlines or fallback issues)
|
||||
EXISTING_COUNT=$(echo "$EXISTING_COUNT" | tr -cd '0-9')
|
||||
if [ -z "$EXISTING_COUNT" ]; then EXISTING_COUNT=0; fi
|
||||
|
||||
NEXT_NUM=$((EXISTING_COUNT + 1))
|
||||
|
||||
VERSION="${TODAY_PREFIX}${NEXT_NUM}"
|
||||
|
||||
# Final fallback to ensure VERSION is never empty
|
||||
if [ -z "$VERSION" ]; then
|
||||
VERSION="v$(date +'%Y.%m.%d-%H%M%S')"
|
||||
fi
|
||||
fi
|
||||
echo "version=$VERSION" >> $GITHUB_OUTPUT
|
||||
echo "Release version: $VERSION"
|
||||
@@ -325,13 +345,34 @@ jobs:
|
||||
echo "=== Release Notes ==="
|
||||
cat release_notes.md
|
||||
|
||||
- name: Create Git Tag
|
||||
run: |
|
||||
VERSION="${{ steps.version.outputs.version }}"
|
||||
|
||||
if [ -z "$VERSION" ]; then
|
||||
echo "Error: Version is empty!"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if ! git rev-parse "$VERSION" >/dev/null 2>&1; then
|
||||
echo "Creating tag $VERSION"
|
||||
git tag "$VERSION"
|
||||
git push origin "$VERSION"
|
||||
else
|
||||
echo "Tag $VERSION already exists"
|
||||
fi
|
||||
env:
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Create GitHub Release
|
||||
uses: softprops/action-gh-release@v2
|
||||
with:
|
||||
tag_name: ${{ steps.version.outputs.version }}
|
||||
target_commitish: ${{ github.sha }}
|
||||
name: ${{ github.event.inputs.release_title || steps.version.outputs.version }}
|
||||
body_path: release_notes.md
|
||||
prerelease: ${{ github.event.inputs.prerelease || false }}
|
||||
make_latest: true
|
||||
files: |
|
||||
plugin_versions.json
|
||||
env:
|
||||
|
||||
43
README.md
@@ -4,7 +4,32 @@ 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: 2026-01-09 20:14
|
||||
|
||||
| 👤 Author | 👥 Followers | ⭐ Points | 🏆 Contributions |
|
||||
|:---:|:---:|:---:|:---:|
|
||||
| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **59** | **70** | **20** |
|
||||
|
||||
| 📝 Posts | ⬇️ Downloads | 👁️ Views | 👍 Upvotes | 💾 Saves |
|
||||
|:---:|:---:|:---:|:---:|:---:|
|
||||
| **13** | **1016** | **10831** | **62** | **56** |
|
||||
|
||||
### 🔥 Top 6 Popular Plugins
|
||||
|
||||
| Rank | Plugin | Downloads | Views |
|
||||
|:---:|------|:---:|:---:|
|
||||
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 323 | 2878 |
|
||||
| 🥈 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 180 | 532 |
|
||||
| 🥉 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 121 | 1355 |
|
||||
| 4️⃣ | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 106 | 1265 |
|
||||
| 5️⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 91 | 1665 |
|
||||
| 6️⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 80 | 751 |
|
||||
|
||||
*See full stats in [Community Stats Report](./docs/community-stats.md)*
|
||||
<!-- STATS_END -->
|
||||
|
||||
## 📦 Project Contents
|
||||
|
||||
@@ -60,10 +85,16 @@ 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 +102,5 @@ 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)
|
||||
|
||||
84
README_CN.md
@@ -2,7 +2,38 @@
|
||||
|
||||
[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 2026-01-09 20:14
|
||||
|
||||
| 👤 作者 | 👥 粉丝 | ⭐ 积分 | 🏆 贡献 |
|
||||
|:---:|:---:|:---:|:---:|
|
||||
| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **59** | **70** | **20** |
|
||||
|
||||
| 📝 发布 | ⬇️ 下载 | 👁️ 浏览 | 👍 点赞 | 💾 收藏 |
|
||||
|:---:|:---:|:---:|:---:|:---:|
|
||||
| **13** | **1016** | **10831** | **62** | **56** |
|
||||
|
||||
### 🔥 热门插件 Top 6
|
||||
|
||||
| 排名 | 插件 | 下载 | 浏览 |
|
||||
|:---:|------|:---:|:---:|
|
||||
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 323 | 2878 |
|
||||
| 🥈 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 180 | 532 |
|
||||
| 🥉 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 121 | 1355 |
|
||||
| 4️⃣ | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 106 | 1265 |
|
||||
| 5️⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 91 | 1665 |
|
||||
| 6️⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 80 | 751 |
|
||||
|
||||
*完整统计请查看 [社区统计报告](./docs/community-stats.zh.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 +50,6 @@ 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 +61,10 @@ 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 +73,7 @@ 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 +87,16 @@ 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 +104,5 @@ 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)
|
||||
|
||||
235
docs/community-stats.json
Normal file
@@ -0,0 +1,235 @@
|
||||
{
|
||||
"total_posts": 13,
|
||||
"total_downloads": 1016,
|
||||
"total_views": 10831,
|
||||
"total_upvotes": 62,
|
||||
"total_downvotes": 2,
|
||||
"total_saves": 56,
|
||||
"total_comments": 15,
|
||||
"by_type": {
|
||||
"action": 11,
|
||||
"filter": 2
|
||||
},
|
||||
"posts": [
|
||||
{
|
||||
"title": "Smart Mind Map",
|
||||
"slug": "turn_any_text_into_beautiful_mind_maps_3094c59a",
|
||||
"type": "action",
|
||||
"version": "0.9.1",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Intelligently analyzes text content and generates interactive mind maps to help users structure and visualize knowledge.",
|
||||
"downloads": 323,
|
||||
"views": 2878,
|
||||
"upvotes": 10,
|
||||
"saves": 17,
|
||||
"comments": 10,
|
||||
"created_at": "2025-12-30",
|
||||
"updated_at": "2026-01-07",
|
||||
"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": "0.3.7",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Extracts tables from chat messages and exports them to Excel (.xlsx) files with smart formatting.",
|
||||
"downloads": 180,
|
||||
"views": 532,
|
||||
"upvotes": 3,
|
||||
"saves": 3,
|
||||
"comments": 0,
|
||||
"created_at": "2025-05-30",
|
||||
"updated_at": "2026-01-07",
|
||||
"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": "Reduces token consumption in long conversations while maintaining coherence through intelligent summarization and message compression.",
|
||||
"downloads": 121,
|
||||
"views": 1355,
|
||||
"upvotes": 5,
|
||||
"saves": 9,
|
||||
"comments": 0,
|
||||
"created_at": "2025-11-08",
|
||||
"updated_at": "2026-01-07",
|
||||
"url": "https://openwebui.com/posts/async_context_compression_b1655bc8"
|
||||
},
|
||||
{
|
||||
"title": "📊 Smart Infographic (AntV)",
|
||||
"slug": "smart_infographic_ad6f0c7f",
|
||||
"type": "action",
|
||||
"version": "1.4.1",
|
||||
"author": "jeff",
|
||||
"description": "AI-powered infographic generator based on AntV Infographic. Supports professional templates, auto-icon matching, and SVG/PNG downloads.",
|
||||
"downloads": 106,
|
||||
"views": 1265,
|
||||
"upvotes": 7,
|
||||
"saves": 9,
|
||||
"comments": 2,
|
||||
"created_at": "2025-12-28",
|
||||
"updated_at": "2026-01-07",
|
||||
"url": "https://openwebui.com/posts/smart_infographic_ad6f0c7f"
|
||||
},
|
||||
{
|
||||
"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": 91,
|
||||
"views": 1665,
|
||||
"upvotes": 8,
|
||||
"saves": 5,
|
||||
"comments": 2,
|
||||
"created_at": "2025-12-30",
|
||||
"updated_at": "2026-01-07",
|
||||
"url": "https://openwebui.com/posts/flash_card_65a2ea8f"
|
||||
},
|
||||
{
|
||||
"title": "Export to Word (Enhanced)",
|
||||
"slug": "export_to_word_enhanced_formatting_fca6a315",
|
||||
"type": "action",
|
||||
"version": "0.4.3",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Export current conversation from Markdown to Word (.docx) with Mermaid diagrams rendered client-side (Mermaid.js, SVG+PNG), LaTeX math, real hyperlinks, improved tables, syntax highlighting, and blockquote support.",
|
||||
"downloads": 80,
|
||||
"views": 751,
|
||||
"upvotes": 5,
|
||||
"saves": 6,
|
||||
"comments": 0,
|
||||
"created_at": "2026-01-03",
|
||||
"updated_at": "2026-01-07",
|
||||
"url": "https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315"
|
||||
},
|
||||
{
|
||||
"title": "📊 智能信息图 (AntV Infographic)",
|
||||
"slug": "智能信息图_e04a48ff",
|
||||
"type": "action",
|
||||
"version": "1.4.1",
|
||||
"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": 35,
|
||||
"views": 473,
|
||||
"upvotes": 3,
|
||||
"saves": 0,
|
||||
"comments": 0,
|
||||
"created_at": "2025-12-28",
|
||||
"updated_at": "2026-01-07",
|
||||
"url": "https://openwebui.com/posts/智能信息图_e04a48ff"
|
||||
},
|
||||
{
|
||||
"title": "导出为 Word (增强版)",
|
||||
"slug": "导出为_word_支持公式流程图表格和代码块_8a6306c0",
|
||||
"type": "action",
|
||||
"version": "0.4.3",
|
||||
"author": "Fu-Jie",
|
||||
"description": "将对话导出为 Word (.docx),支持 Mermaid 图表 (客户端渲染 SVG+PNG)、LaTeX 数学公式、真实超链接、增强表格格式、代码高亮和引用块。",
|
||||
"downloads": 30,
|
||||
"views": 902,
|
||||
"upvotes": 8,
|
||||
"saves": 2,
|
||||
"comments": 1,
|
||||
"created_at": "2026-01-04",
|
||||
"updated_at": "2026-01-07",
|
||||
"url": "https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0"
|
||||
},
|
||||
{
|
||||
"title": "思维导图",
|
||||
"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": "0.9.1",
|
||||
"author": "Fu-Jie",
|
||||
"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": 17,
|
||||
"views": 295,
|
||||
"upvotes": 2,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"created_at": "2025-12-31",
|
||||
"updated_at": "2026-01-07",
|
||||
"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": "Deep Dive",
|
||||
"slug": "deep_dive_c0b846e4",
|
||||
"type": "action",
|
||||
"version": "1.0.0",
|
||||
"author": "Fu-Jie",
|
||||
"description": "A comprehensive thinking lens that dives deep into any content - from context to logic, insights, and action paths.",
|
||||
"downloads": 14,
|
||||
"views": 167,
|
||||
"upvotes": 3,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"created_at": "2026-01-08",
|
||||
"updated_at": "2026-01-08",
|
||||
"url": "https://openwebui.com/posts/deep_dive_c0b846e4"
|
||||
},
|
||||
{
|
||||
"title": "闪记卡 (Flash Card)",
|
||||
"slug": "闪记卡生成插件_4a31eac3",
|
||||
"type": "action",
|
||||
"version": "0.2.4",
|
||||
"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": 339,
|
||||
"upvotes": 4,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"created_at": "2025-12-30",
|
||||
"updated_at": "2026-01-07",
|
||||
"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": "通过智能摘要和消息压缩,降低长对话的 token 消耗,同时保持对话连贯性。",
|
||||
"downloads": 6,
|
||||
"views": 148,
|
||||
"upvotes": 2,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"created_at": "2025-11-08",
|
||||
"updated_at": "2026-01-07",
|
||||
"url": "https://openwebui.com/posts/异步上下文压缩_5c0617cb"
|
||||
},
|
||||
{
|
||||
"title": "精读",
|
||||
"slug": "精读_99830b0f",
|
||||
"type": "action",
|
||||
"version": "1.0.0",
|
||||
"author": "Fu-Jie",
|
||||
"description": "全方位的思维透镜 —— 从背景全景到逻辑脉络,从深度洞察到行动路径。",
|
||||
"downloads": 1,
|
||||
"views": 61,
|
||||
"upvotes": 2,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"created_at": "2026-01-08",
|
||||
"updated_at": "2026-01-08",
|
||||
"url": "https://openwebui.com/posts/精读_99830b0f"
|
||||
}
|
||||
],
|
||||
"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": 59,
|
||||
"following": 2,
|
||||
"total_points": 70,
|
||||
"post_points": 60,
|
||||
"comment_points": 10,
|
||||
"contributions": 20
|
||||
}
|
||||
}
|
||||
37
docs/community-stats.md
Normal file
@@ -0,0 +1,37 @@
|
||||
# 📊 OpenWebUI Community Stats Report
|
||||
|
||||
> 📅 Updated: 2026-01-09 20:14
|
||||
|
||||
## 📈 Overview
|
||||
|
||||
| Metric | Value |
|
||||
|------|------|
|
||||
| 📝 Total Posts | 13 |
|
||||
| ⬇️ Total Downloads | 1016 |
|
||||
| 👁️ Total Views | 10831 |
|
||||
| 👍 Total Upvotes | 62 |
|
||||
| 💾 Total Saves | 56 |
|
||||
| 💬 Total Comments | 15 |
|
||||
|
||||
## 📂 By Type
|
||||
|
||||
- **action**: 11
|
||||
- **filter**: 2
|
||||
|
||||
## 📋 Posts List
|
||||
|
||||
| Rank | Title | Type | Version | Downloads | Views | Upvotes | Saves | Updated |
|
||||
|:---:|------|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
|
||||
| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.9.1 | 323 | 2878 | 10 | 17 | 2026-01-07 |
|
||||
| 2 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 180 | 532 | 3 | 3 | 2026-01-07 |
|
||||
| 3 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter | 1.1.0 | 121 | 1355 | 5 | 9 | 2026-01-07 |
|
||||
| 4 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.1 | 106 | 1265 | 7 | 9 | 2026-01-07 |
|
||||
| 5 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 91 | 1665 | 8 | 5 | 2026-01-07 |
|
||||
| 6 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 80 | 751 | 5 | 6 | 2026-01-07 |
|
||||
| 7 | [📊 智能信息图 (AntV Infographic)](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.4.1 | 35 | 473 | 3 | 0 | 2026-01-07 |
|
||||
| 8 | [导出为 Word (增强版)](https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0) | action | 0.4.3 | 30 | 902 | 8 | 2 | 2026-01-07 |
|
||||
| 9 | [思维导图](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 | 0.9.1 | 17 | 295 | 2 | 1 | 2026-01-07 |
|
||||
| 10 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action | 1.0.0 | 14 | 167 | 3 | 1 | 2026-01-08 |
|
||||
| 11 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 12 | 339 | 4 | 1 | 2026-01-07 |
|
||||
| 12 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | filter | 1.1.0 | 6 | 148 | 2 | 1 | 2026-01-07 |
|
||||
| 13 | [精读](https://openwebui.com/posts/精读_99830b0f) | action | 1.0.0 | 1 | 61 | 2 | 1 | 2026-01-08 |
|
||||
37
docs/community-stats.zh.md
Normal file
@@ -0,0 +1,37 @@
|
||||
# 📊 OpenWebUI 社区统计报告
|
||||
|
||||
> 📅 更新时间: 2026-01-09 20:14
|
||||
|
||||
## 📈 总览
|
||||
|
||||
| 指标 | 数值 |
|
||||
|------|------|
|
||||
| 📝 发布数量 | 13 |
|
||||
| ⬇️ 总下载量 | 1016 |
|
||||
| 👁️ 总浏览量 | 10831 |
|
||||
| 👍 总点赞数 | 62 |
|
||||
| 💾 总收藏数 | 56 |
|
||||
| 💬 总评论数 | 15 |
|
||||
|
||||
## 📂 按类型分类
|
||||
|
||||
- **action**: 11
|
||||
- **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 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.9.1 | 323 | 2878 | 10 | 17 | 2026-01-07 |
|
||||
| 2 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 180 | 532 | 3 | 3 | 2026-01-07 |
|
||||
| 3 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter | 1.1.0 | 121 | 1355 | 5 | 9 | 2026-01-07 |
|
||||
| 4 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.1 | 106 | 1265 | 7 | 9 | 2026-01-07 |
|
||||
| 5 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 91 | 1665 | 8 | 5 | 2026-01-07 |
|
||||
| 6 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 80 | 751 | 5 | 6 | 2026-01-07 |
|
||||
| 7 | [📊 智能信息图 (AntV Infographic)](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.4.1 | 35 | 473 | 3 | 0 | 2026-01-07 |
|
||||
| 8 | [导出为 Word (增强版)](https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0) | action | 0.4.3 | 30 | 902 | 8 | 2 | 2026-01-07 |
|
||||
| 9 | [思维导图](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 | 0.9.1 | 17 | 295 | 2 | 1 | 2026-01-07 |
|
||||
| 10 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action | 1.0.0 | 14 | 167 | 3 | 1 | 2026-01-08 |
|
||||
| 11 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 12 | 339 | 4 | 1 | 2026-01-07 |
|
||||
| 12 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | filter | 1.1.0 | 6 | 148 | 2 | 1 | 2026-01-07 |
|
||||
| 13 | [精读](https://openwebui.com/posts/精读_99830b0f) | action | 1.0.0 | 1 | 61 | 2 | 1 | 2026-01-08 |
|
||||
150
docs/development/frontend-console-debugging.md
Normal file
@@ -0,0 +1,150 @@
|
||||
# 🛠️ Debugging Python Plugins with Frontend Console
|
||||
|
||||
When developing plugins for Open WebUI, debugging can be challenging. Standard `print()` statements or server-side logging might not always be accessible, especially in hosted environments or when you want to see the data flow in real-time alongside the UI interactions.
|
||||
|
||||
This guide introduces a powerful technique: **Frontend Console Debugging**. By injecting JavaScript from your Python plugin, you can print structured logs directly to the browser's Developer Tools console (F12).
|
||||
|
||||
## Why Frontend Debugging?
|
||||
|
||||
* **Real-time Feedback**: See logs immediately as actions happen in the browser.
|
||||
* **Rich Objects**: Inspect complex JSON objects (like `body` or `messages`) interactively, rather than reading massive text dumps.
|
||||
* **No Server Access Needed**: Debug issues even if you don't have SSH/Console access to the backend server.
|
||||
* **Clean Output**: Group logs using `console.group()` to keep your console organized.
|
||||
|
||||
## The Core Mechanism
|
||||
|
||||
Open WebUI plugins (both Actions and Filters) support an event system. We can leverage the `__event_call__` (or sometimes `__event_emitter__`) to send a special event of type `execute`. This tells the frontend to run the provided JavaScript code.
|
||||
|
||||
### The Helper Method
|
||||
|
||||
To make this easy to use, we recommend adding a helper method `_emit_debug_log` to your plugin class.
|
||||
|
||||
```python
|
||||
import json
|
||||
from typing import List
|
||||
|
||||
async def _emit_debug_log(
|
||||
self,
|
||||
__event_call__,
|
||||
title: str,
|
||||
data: dict
|
||||
):
|
||||
"""
|
||||
Emit debug log to browser console via JS execution.
|
||||
|
||||
Args:
|
||||
__event_call__: The event callable passed to action/outlet.
|
||||
title: A title for the log group.
|
||||
data: A dictionary of data to log.
|
||||
"""
|
||||
# 1. Check if debugging is enabled (recommended)
|
||||
if not getattr(self.valves, "show_debug_log", True) or not __event_call__:
|
||||
return
|
||||
|
||||
try:
|
||||
# 2. Construct the JavaScript code
|
||||
# We use an async IIFE (Immediately Invoked Function Expression)
|
||||
# to ensure a clean scope and support await if needed.
|
||||
js_code = f"""
|
||||
(async function() {{
|
||||
console.group("🛠️ Plugin Debug: {title}");
|
||||
console.log({json.dumps(data, ensure_ascii=False)});
|
||||
console.groupEnd();
|
||||
}})();
|
||||
"""
|
||||
|
||||
# 3. Send the execute event
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"Error emitting debug log: {e}")
|
||||
```
|
||||
|
||||
## Implementation Steps
|
||||
|
||||
### 1. Add a Valve for Control
|
||||
|
||||
It's best practice to make debugging optional so it doesn't clutter the console for normal users.
|
||||
|
||||
```python
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
class Filter:
|
||||
class Valves(BaseModel):
|
||||
show_debug_log: bool = Field(
|
||||
default=False,
|
||||
description="Print debug logs to browser console (F12)"
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
```
|
||||
|
||||
### 2. Inject `__event_call__`
|
||||
|
||||
Ensure your `action` (for Actions) or `outlet` (for Filters) method accepts `__event_call__`.
|
||||
|
||||
**For Filters (`outlet`):**
|
||||
|
||||
```python
|
||||
async def outlet(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[dict] = None,
|
||||
__event_call__=None, # <--- Add this
|
||||
__metadata__: Optional[dict] = None,
|
||||
) -> dict:
|
||||
```
|
||||
|
||||
**For Actions (`action`):**
|
||||
|
||||
```python
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__=None,
|
||||
__event_call__=None, # <--- Add this
|
||||
__request__=None,
|
||||
):
|
||||
```
|
||||
|
||||
### 3. Call the Helper
|
||||
|
||||
Now you can log anything, anywhere in your logic!
|
||||
|
||||
```python
|
||||
# Inside your logic...
|
||||
new_content = self.process_content(content)
|
||||
|
||||
# Log the before and after
|
||||
await self._emit_debug_log(
|
||||
__event_call__,
|
||||
"Content Normalization",
|
||||
{
|
||||
"original": content,
|
||||
"processed": new_content,
|
||||
"changes": diff_list
|
||||
}
|
||||
)
|
||||
```
|
||||
|
||||
## Best Practices
|
||||
|
||||
1. **Use `json.dumps`**: Always serialize your Python dictionaries to JSON strings before embedding them in the f-string. This handles escaping quotes and special characters correctly.
|
||||
2. **Async IIFE**: Wrapping your JS in `(async function() { ... })();` is safer than raw code. It prevents variable collisions with other scripts and allows using `await` inside your debug script if you ever need to check DOM elements.
|
||||
3. **Check for None**: Always check if `__event_call__` is not None before using it, as it might not be available in all contexts (e.g., when running tests or in older Open WebUI versions).
|
||||
|
||||
## Example Output
|
||||
|
||||
When enabled, your browser console will show:
|
||||
|
||||
```text
|
||||
> 🛠️ Plugin Debug: Content Normalization
|
||||
> {original: "...", processed: "...", changes: [...]}
|
||||
```
|
||||
|
||||
You can expand the object to inspect every detail of your data. Happy debugging!
|
||||
64
docs/development/mermaid-syntax-standards.md
Normal file
@@ -0,0 +1,64 @@
|
||||
# Mermaid Syntax Standards & Best Practices
|
||||
|
||||
This document summarizes the official syntax standards for Mermaid flowcharts, focusing on node labels, quoting rules, and special character handling. It serves as a reference for the `markdown_normalizer` plugin logic.
|
||||
|
||||
## 1. Node Shapes & Syntax
|
||||
|
||||
Mermaid supports various node shapes defined by specific wrapping characters.
|
||||
|
||||
| Shape | Syntax | Example |
|
||||
| :--- | :--- | :--- |
|
||||
| **Rectangle** (Default) | `id[Label]` | `A[Start]` |
|
||||
| **Rounded** | `id(Label)` | `B(Process)` |
|
||||
| **Stadium** (Pill) | `id([Label])` | `C([End])` |
|
||||
| **Subroutine** | `id[[Label]]` | `D[[Subroutine]]` |
|
||||
| **Cylinder** (Database) | `id[(Label)]` | `E[(Database)]` |
|
||||
| **Circle** | `id((Label))` | `F((Point))` |
|
||||
| **Double Circle** | `id(((Label)))` | `G(((Endpoint)))` |
|
||||
| **Asymmetric** | `id>Label]` | `H>Flag]` |
|
||||
| **Rhombus** (Decision) | `id{Label}` | `I{Decision}` |
|
||||
| **Hexagon** | `id{{Label}}` | `J{{Prepare}}` |
|
||||
| **Parallelogram** | `id[/Label/]` | `K[/Input/]` |
|
||||
| **Parallelogram Alt** | `id[\Label\]` | `L[\Output\]` |
|
||||
| **Trapezoid** | `id[/Label\]` | `M[/Trap/]` |
|
||||
| **Trapezoid Alt** | `id[\Label/]` | `N[\TrapAlt/]` |
|
||||
|
||||
## 2. Quoting Rules (Critical)
|
||||
|
||||
### Why Quote?
|
||||
Quoting node labels is **highly recommended** and sometimes **mandatory** to prevent syntax errors.
|
||||
|
||||
### Mandatory Quoting Scenarios
|
||||
You **MUST** enclose labels in double quotes `"` if they contain:
|
||||
1. **Special Characters**: `()`, `[]`, `{}`, `;`, `"`, etc.
|
||||
2. **Keywords**: Words like `end`, `subgraph`, etc., if used in specific contexts.
|
||||
3. **Unicode/Emoji**: While often supported without quotes, quoting ensures consistent rendering across different environments.
|
||||
4. **Markdown**: If you want to use Markdown formatting (bold, italic) inside a label.
|
||||
|
||||
### Best Practice: Always Quote
|
||||
To ensure robustness, especially when processing LLM-generated content which may contain unpredictable characters, **always enclosing labels in double quotes is the safest strategy**.
|
||||
|
||||
**Examples:**
|
||||
* ❌ Risky: `id(Start: 15:00)` (Colon might be interpreted as style separator)
|
||||
* ✅ Safe: `id("Start: 15:00")`
|
||||
* ❌ Broken: `id(Func(x))` (Nested parentheses break parsing)
|
||||
* ✅ Safe: `id("Func(x)")`
|
||||
|
||||
## 3. Escape Characters
|
||||
|
||||
Inside a quoted string:
|
||||
* Double quotes `"` must be escaped as `\"`.
|
||||
* HTML entities (e.g., `#35;` for `#`) can be used.
|
||||
|
||||
## 4. Plugin Logic Verification
|
||||
|
||||
The `markdown_normalizer` plugin implements the following logic:
|
||||
|
||||
1. **Detection**: Identifies Mermaid node definitions using a comprehensive regex covering all shapes above.
|
||||
2. **Normalization**:
|
||||
* Checks if the label is already quoted.
|
||||
* If **NOT quoted**, it wraps the label in double quotes `""`.
|
||||
* Escapes any existing double quotes inside the label (`"` -> `\"`).
|
||||
3. **Shape Preservation**: The regex captures the specific opening and closing delimiters (e.g., `((` and `))`) to ensure the node shape is strictly preserved during normalization.
|
||||
|
||||
**Conclusion**: The plugin's behavior of automatically adding quotes to unquoted labels is **fully aligned with Mermaid's official best practices** for robustness and error prevention.
|
||||
@@ -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
@@ -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 |
|
||||
111
docs/plugins/actions/deep-dive.md
Normal file
@@ -0,0 +1,111 @@
|
||||
# Deep Dive
|
||||
|
||||
<span class="category-badge action">Action</span>
|
||||
<span class="version-badge">v1.0.0</span>
|
||||
|
||||
A comprehensive thinking lens that dives deep into any content - from context to logic, insights, and action paths.
|
||||
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
The Deep Dive plugin transforms how you understand complex content by guiding you through a structured thinking process. Rather than just summarizing, it deconstructs content across four phases:
|
||||
|
||||
- **🔍 The Context (What?)**: Panoramic view of the situation and background
|
||||
- **🧠 The Logic (Why?)**: Deconstruction of reasoning and mental models
|
||||
- **💎 The Insight (So What?)**: Non-obvious value and hidden implications
|
||||
- **🚀 The Path (Now What?)**: Specific, prioritized strategic actions
|
||||
|
||||
## Features
|
||||
|
||||
- :material-brain: **Thinking Chain**: Complete structured analysis process
|
||||
- :material-eye: **Deep Understanding**: Reveals hidden assumptions and blind spots
|
||||
- :material-lightbulb-on: **Insight Extraction**: Finds the "Aha!" moments
|
||||
- :material-rocket-launch: **Action Oriented**: Translates understanding into actionable steps
|
||||
- :material-theme-light-dark: **Theme Adaptive**: Auto-adapts to OpenWebUI light/dark theme
|
||||
- :material-translate: **Multi-language**: Outputs in user's preferred language
|
||||
|
||||
---
|
||||
|
||||
## Installation
|
||||
|
||||
1. Download the plugin file: [`deep_dive.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/deep-dive)
|
||||
2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
|
||||
3. Enable the plugin
|
||||
|
||||
---
|
||||
|
||||
## Usage
|
||||
|
||||
1. Provide any long text, article, or meeting notes in the chat
|
||||
2. Click the **Deep Dive** button in the message action bar
|
||||
3. Follow the visual timeline from Context → Logic → Insight → Path
|
||||
|
||||
---
|
||||
|
||||
## Configuration
|
||||
|
||||
| Option | Type | Default | Description |
|
||||
|--------|------|---------|-------------|
|
||||
| `SHOW_STATUS` | boolean | `true` | Show status updates during processing |
|
||||
| `MODEL_ID` | string | `""` | LLM model for analysis (empty = current model) |
|
||||
| `MIN_TEXT_LENGTH` | integer | `200` | Minimum text length for analysis |
|
||||
| `CLEAR_PREVIOUS_HTML` | boolean | `true` | Clear previous plugin results |
|
||||
| `MESSAGE_COUNT` | integer | `1` | Number of recent messages to analyze |
|
||||
|
||||
---
|
||||
|
||||
## Theme Support
|
||||
|
||||
Deep Dive automatically adapts to OpenWebUI's light/dark theme:
|
||||
|
||||
- Detects theme from parent document `<meta name="theme-color">` tag
|
||||
- Falls back to `html/body` class or `data-theme` attribute
|
||||
- Uses system preference `prefers-color-scheme: dark` as last resort
|
||||
|
||||
!!! tip "For Best Results"
|
||||
Enable **iframe Sandbox Allow Same Origin** in OpenWebUI:
|
||||
**Settings** → **Interface** → **Artifacts** → Check **iframe Sandbox Allow Same Origin**
|
||||
|
||||
---
|
||||
|
||||
## Example Output
|
||||
|
||||
The plugin generates a beautiful structured timeline:
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────┐
|
||||
│ 🌊 Deep Dive Analysis │
|
||||
│ 👤 User 📅 Date 📊 Word count │
|
||||
├─────────────────────────────────────┤
|
||||
│ 🔍 Phase 01: The Context │
|
||||
│ [High-level panoramic view] │
|
||||
│ │
|
||||
│ 🧠 Phase 02: The Logic │
|
||||
│ • Reasoning structure... │
|
||||
│ • Hidden assumptions... │
|
||||
│ │
|
||||
│ 💎 Phase 03: The Insight │
|
||||
│ • Non-obvious value... │
|
||||
│ • Blind spots revealed... │
|
||||
│ │
|
||||
│ 🚀 Phase 04: The Path │
|
||||
│ ▸ Priority Action 1... │
|
||||
│ ▸ Priority Action 2... │
|
||||
└─────────────────────────────────────┘
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Requirements
|
||||
|
||||
!!! note "Prerequisites"
|
||||
- OpenWebUI v0.3.0 or later
|
||||
- Uses the active LLM model for analysis
|
||||
- Requires `markdown` Python package
|
||||
|
||||
---
|
||||
|
||||
## Source Code
|
||||
|
||||
[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/deep-dive){ .md-button }
|
||||
111
docs/plugins/actions/deep-dive.zh.md
Normal file
@@ -0,0 +1,111 @@
|
||||
# 精读 (Deep Dive)
|
||||
|
||||
<span class="category-badge action">Action</span>
|
||||
<span class="version-badge">v1.0.0</span>
|
||||
|
||||
全方位的思维透镜 —— 从背景全景到逻辑脉络,从深度洞察到行动路径。
|
||||
|
||||
---
|
||||
|
||||
## 概述
|
||||
|
||||
精读插件改变了您理解复杂内容的方式,通过结构化的思维过程引导您进行深度分析。它不仅仅是摘要,而是从四个阶段解构内容:
|
||||
|
||||
- **🔍 全景 (The Context)**: 情境与背景的高层级全景视图
|
||||
- **🧠 脉络 (The Logic)**: 解构底层推理逻辑与思维模型
|
||||
- **💎 洞察 (The Insight)**: 提取非显性价值与隐藏含义
|
||||
- **🚀 路径 (The Path)**: 具体的、按优先级排列的战略行动
|
||||
|
||||
## 功能特性
|
||||
|
||||
- :material-brain: **思维链**: 完整的结构化分析过程
|
||||
- :material-eye: **深度理解**: 揭示隐藏的假设和思维盲点
|
||||
- :material-lightbulb-on: **洞察提取**: 发现"原来如此"的时刻
|
||||
- :material-rocket-launch: **行动导向**: 将深度理解转化为可执行步骤
|
||||
- :material-theme-light-dark: **主题自适应**: 自动适配 OpenWebUI 深色/浅色主题
|
||||
- :material-translate: **多语言**: 以用户偏好语言输出
|
||||
|
||||
---
|
||||
|
||||
## 安装
|
||||
|
||||
1. 下载插件文件: [`deep_dive_cn.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/deep-dive)
|
||||
2. 上传到 OpenWebUI: **管理面板** → **设置** → **Functions**
|
||||
3. 启用插件
|
||||
|
||||
---
|
||||
|
||||
## 使用方法
|
||||
|
||||
1. 在聊天中提供任何长文本、文章或会议记录
|
||||
2. 点击消息操作栏中的 **精读** 按钮
|
||||
3. 沿着视觉时间轴从"全景"探索到"路径"
|
||||
|
||||
---
|
||||
|
||||
## 配置参数
|
||||
|
||||
| 选项 | 类型 | 默认值 | 描述 |
|
||||
|------|------|--------|------|
|
||||
| `SHOW_STATUS` | boolean | `true` | 处理过程中是否显示状态更新 |
|
||||
| `MODEL_ID` | string | `""` | 用于分析的 LLM 模型(空 = 当前模型) |
|
||||
| `MIN_TEXT_LENGTH` | integer | `200` | 分析所需的最小文本长度 |
|
||||
| `CLEAR_PREVIOUS_HTML` | boolean | `true` | 是否清除之前的插件结果 |
|
||||
| `MESSAGE_COUNT` | integer | `1` | 要分析的最近消息数量 |
|
||||
|
||||
---
|
||||
|
||||
## 主题支持
|
||||
|
||||
精读插件自动适配 OpenWebUI 的深色/浅色主题:
|
||||
|
||||
- 从父文档 `<meta name="theme-color">` 标签检测主题
|
||||
- 回退到 `html/body` 的 class 或 `data-theme` 属性
|
||||
- 最后使用系统偏好 `prefers-color-scheme: dark`
|
||||
|
||||
!!! tip "最佳效果"
|
||||
请在 OpenWebUI 中启用 **iframe Sandbox Allow Same Origin**:
|
||||
**设置** → **界面** → **Artifacts** → 勾选 **iframe Sandbox Allow Same Origin**
|
||||
|
||||
---
|
||||
|
||||
## 输出示例
|
||||
|
||||
插件生成精美的结构化时间轴:
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────┐
|
||||
│ 📖 精读分析报告 │
|
||||
│ 👤 用户 📅 日期 📊 字数 │
|
||||
├─────────────────────────────────────┤
|
||||
│ 🔍 阶段 01: 全景 (The Context) │
|
||||
│ [高层级全景视图内容] │
|
||||
│ │
|
||||
│ 🧠 阶段 02: 脉络 (The Logic) │
|
||||
│ • 推理结构分析... │
|
||||
│ • 隐藏假设识别... │
|
||||
│ │
|
||||
│ 💎 阶段 03: 洞察 (The Insight) │
|
||||
│ • 非显性价值提取... │
|
||||
│ • 思维盲点揭示... │
|
||||
│ │
|
||||
│ 🚀 阶段 04: 路径 (The Path) │
|
||||
│ ▸ 优先级行动 1... │
|
||||
│ ▸ 优先级行动 2... │
|
||||
└─────────────────────────────────────┘
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 系统要求
|
||||
|
||||
!!! note "前提条件"
|
||||
- OpenWebUI v0.3.0 或更高版本
|
||||
- 使用当前活跃的 LLM 模型进行分析
|
||||
- 需要 `markdown` Python 包
|
||||
|
||||
---
|
||||
|
||||
## 源代码
|
||||
|
||||
[:fontawesome-brands-github: 在 GitHub 上查看](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/deep-dive){ .md-button }
|
||||
@@ -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">v0.4.3</span>
|
||||
|
||||
Export conversation to Word (.docx) with **syntax highlighting**, **native math equations**, **Mermaid diagrams**, **citations**, and **enhanced table formatting**.
|
||||
|
||||
@@ -34,11 +34,36 @@ 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` |
|
||||
|
||||
## 🔥 What's New in v0.4.3
|
||||
|
||||
### 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)
|
||||
|
||||
---
|
||||
|
||||
@@ -95,3 +120,4 @@ You can configure the following settings via the **Valves** button in the plugin
|
||||
## Source Code
|
||||
|
||||
[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/export_to_docx){ .md-button }
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.4.3 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
@@ -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">v0.4.3</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`
|
||||
|
||||
---
|
||||
|
||||
@@ -94,4 +117,4 @@ Export to Word 插件会把聊天消息从 Markdown 转成精致的 Word 文档
|
||||
|
||||
## 源码
|
||||
|
||||
[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/export_to_docx){ .md-button }
|
||||
[:fontawes**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.4.3 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)/tree/main/plugins/actions/export_to_docx){ .md-button }
|
||||
|
||||
@@ -33,7 +33,7 @@ Actions are interactive plugins that:
|
||||
|
||||
Transform text into professional infographics using AntV visualization engine with various templates.
|
||||
|
||||
**Version:** 1.3.0
|
||||
**Version:** 1.4.1
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](smart-infographic.md)
|
||||
|
||||
@@ -63,19 +63,29 @@ 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:** 0.4.2
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](export-to-word.md)
|
||||
|
||||
- :material-text-box-search:{ .lg .middle } **Summary**
|
||||
- :material-brain:{ .lg .middle } **Deep Dive**
|
||||
|
||||
---
|
||||
|
||||
Generate concise summaries of long text content with key points extraction.
|
||||
A comprehensive thinking lens that dives deep into any content - Context → Logic → Insight → Path. Supports theme auto-adaptation.
|
||||
|
||||
**Version:** 0.1.0
|
||||
**Version:** 1.0.0
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](summary.md)
|
||||
[:octicons-arrow-right-24: Documentation](deep-dive.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>
|
||||
|
||||
|
||||
@@ -33,7 +33,7 @@ Actions 是交互式插件,能够:
|
||||
|
||||
使用 AntV 可视化引擎,将文本转成专业的信息图。
|
||||
|
||||
**版本:** 1.3.0
|
||||
**版本:** 1.4.1
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](smart-infographic.md)
|
||||
|
||||
@@ -63,19 +63,29 @@ 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:** 0.4.2
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](export-to-word.md)
|
||||
|
||||
- :material-text-box-search:{ .lg .middle } **Summary**
|
||||
- :material-brain:{ .lg .middle } **精读 (Deep Dive)**
|
||||
|
||||
---
|
||||
|
||||
对长文本进行精简总结,提取要点。
|
||||
全方位的思维透镜 —— 全景 → 脉络 → 洞察 → 路径。支持主题自适应。
|
||||
|
||||
**版本:** 0.1.0
|
||||
**版本:** 1.0.0
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](summary.md)
|
||||
[:octicons-arrow-right-24: 查看文档](deep-dive.zh.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
@@ -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
@@ -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)
|
||||
@@ -1,7 +1,7 @@
|
||||
# Smart Infographic
|
||||
|
||||
<span class="category-badge action">Action</span>
|
||||
<span class="version-badge">v1.3.0</span>
|
||||
<span class="version-badge">v1.4.0</span>
|
||||
|
||||
An AntV Infographic engine powered plugin that transforms long text into professional, beautiful infographics with a single click.
|
||||
|
||||
@@ -19,6 +19,8 @@ The Smart Infographic plugin uses AI to analyze text content and generate profes
|
||||
- :material-download: **Multi-Format Export**: Download your infographics as **SVG**, **PNG**, or **Standalone HTML** file
|
||||
- :material-theme-light-dark: **Theme Support**: Supports Dark/Light modes, auto-adapts theme colors
|
||||
- :material-cellphone-link: **Responsive Design**: Generated charts look great on both desktop and mobile devices
|
||||
- :material-image: **Image Embedding**: Option to embed charts as static images for better compatibility
|
||||
- :material-monitor-screenshot: **Adaptive Sizing**: Images automatically adapt to the chat container width
|
||||
|
||||
---
|
||||
|
||||
@@ -60,6 +62,7 @@ The Smart Infographic plugin uses AI to analyze text content and generate profes
|
||||
| `MIN_TEXT_LENGTH` | integer | `100` | Minimum characters required to trigger analysis |
|
||||
| `CLEAR_PREVIOUS_HTML` | boolean | `false` | Whether to clear previous charts |
|
||||
| `MESSAGE_COUNT` | integer | `1` | Number of recent messages to use for analysis |
|
||||
| `OUTPUT_MODE` | string | `image` | `image` for static image embedding (default), `html` for interactive chart |
|
||||
|
||||
---
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
# Smart Infographic(智能信息图)
|
||||
|
||||
<span class="category-badge action">Action</span>
|
||||
<span class="version-badge">v1.0.0</span>
|
||||
<span class="version-badge">v1.4.0</span>
|
||||
|
||||
基于 AntV 信息图引擎,将长文本一键转成专业、美观的信息图。
|
||||
|
||||
@@ -19,6 +19,8 @@ Smart Infographic 使用 AI 分析文本,并基于 AntV 可视化引擎生成
|
||||
- :material-download: **多格式导出**:支持下载 **SVG**、**PNG**、**独立 HTML**
|
||||
- :material-theme-light-dark: **主题支持**:适配深色/浅色模式
|
||||
- :material-cellphone-link: **响应式**:桌面与移动端都能良好展示
|
||||
- :material-image: **图片嵌入**:支持将图表作为静态图片嵌入,兼容性更好
|
||||
- :material-monitor-screenshot: **自适应尺寸**:图片模式下自动适应聊天容器宽度
|
||||
|
||||
---
|
||||
|
||||
@@ -60,6 +62,7 @@ Smart Infographic 使用 AI 分析文本,并基于 AntV 可视化引擎生成
|
||||
| `MIN_TEXT_LENGTH` | integer | `100` | 触发分析的最小字符数 |
|
||||
| `CLEAR_PREVIOUS_HTML` | boolean | `false` | 是否清空之前生成的图表 |
|
||||
| `MESSAGE_COUNT` | integer | `1` | 参与分析的最近消息条数 |
|
||||
| `OUTPUT_MODE` | string | `image` | `image` 为静态图片嵌入(默认),`html` 为交互式图表 |
|
||||
|
||||
---
|
||||
|
||||
|
||||
@@ -1,82 +0,0 @@
|
||||
# Summary
|
||||
|
||||
<span class="category-badge action">Action</span>
|
||||
<span class="version-badge">v0.1.0</span>
|
||||
|
||||
Generate concise summaries of long text content with key points extraction.
|
||||
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
The Summary plugin helps you quickly understand long pieces of text by generating concise summaries with extracted key points. It's perfect for:
|
||||
|
||||
- Summarizing long articles or documents
|
||||
- Extracting key points from conversations
|
||||
- Creating quick overviews of complex topics
|
||||
|
||||
## Features
|
||||
|
||||
- :material-text-box-search: **Smart Summarization**: AI-powered content analysis
|
||||
- :material-format-list-bulleted: **Key Points**: Extracted important highlights
|
||||
- :material-content-copy: **Easy Copy**: One-click copying of summaries
|
||||
- :material-tune: **Adjustable Length**: Control summary detail level
|
||||
|
||||
---
|
||||
|
||||
## Installation
|
||||
|
||||
1. Download the plugin file: [`summary.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/summary)
|
||||
2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
|
||||
3. Enable the plugin
|
||||
|
||||
---
|
||||
|
||||
## Usage
|
||||
|
||||
1. Get a long response from the AI or paste long text
|
||||
2. Click the **Summary** button in the message action bar
|
||||
3. View the generated summary with key points
|
||||
|
||||
---
|
||||
|
||||
## Configuration
|
||||
|
||||
| Option | Type | Default | Description |
|
||||
|--------|------|---------|-------------|
|
||||
| `summary_length` | string | `"medium"` | Length of summary (short/medium/long) |
|
||||
| `include_key_points` | boolean | `true` | Extract and list key points |
|
||||
| `language` | string | `"auto"` | Output language |
|
||||
|
||||
---
|
||||
|
||||
## Example Output
|
||||
|
||||
```markdown
|
||||
## Summary
|
||||
|
||||
This document discusses the implementation of a new feature
|
||||
for the application, focusing on user experience improvements
|
||||
and performance optimizations.
|
||||
|
||||
### Key Points
|
||||
|
||||
- ✅ New user interface design improves accessibility
|
||||
- ✅ Backend optimizations reduce load times by 40%
|
||||
- ✅ Mobile responsiveness enhanced
|
||||
- ✅ Integration with third-party services simplified
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Requirements
|
||||
|
||||
!!! note "Prerequisites"
|
||||
- OpenWebUI v0.3.0 or later
|
||||
- Uses the active LLM model for summarization
|
||||
|
||||
---
|
||||
|
||||
## Source Code
|
||||
|
||||
[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/summary){ .md-button }
|
||||
@@ -1,82 +0,0 @@
|
||||
# Summary(摘要)
|
||||
|
||||
<span class="category-badge action">Action</span>
|
||||
<span class="version-badge">v0.1.0</span>
|
||||
|
||||
为长文本生成简洁摘要,并提取关键要点。
|
||||
|
||||
---
|
||||
|
||||
## 概览
|
||||
|
||||
Summary 插件可以快速理解长文本,生成精炼摘要并列出关键点,适合:
|
||||
|
||||
- 总结长文章或文档
|
||||
- 从对话中提炼要点
|
||||
- 为复杂主题制作快速概览
|
||||
|
||||
## 功能特性
|
||||
|
||||
- :material-text-box-search: **智能摘要**:AI 驱动的内容分析
|
||||
- :material-format-list-bulleted: **关键点**:提取重要信息
|
||||
- :material-content-copy: **便捷复制**:一键复制摘要
|
||||
- :material-tune: **长度可调**:可选择摘要详略程度
|
||||
|
||||
---
|
||||
|
||||
## 安装
|
||||
|
||||
1. 下载插件文件:[`summary.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/summary)
|
||||
2. 上传到 OpenWebUI:**Admin Panel** → **Settings** → **Functions**
|
||||
3. 启用插件
|
||||
|
||||
---
|
||||
|
||||
## 使用方法
|
||||
|
||||
1. 获取一段较长的 AI 回复或粘贴长文本
|
||||
2. 点击消息操作栏的 **Summary** 按钮
|
||||
3. 查看生成的摘要与关键点
|
||||
|
||||
---
|
||||
|
||||
## 配置项
|
||||
|
||||
| 选项 | 类型 | 默认值 | 说明 |
|
||||
|--------|------|---------|-------------|
|
||||
| `summary_length` | string | `"medium"` | 摘要长度(short/medium/long) |
|
||||
| `include_key_points` | boolean | `true` | 是否提取并列出关键点 |
|
||||
| `language` | string | `"auto"` | 输出语言 |
|
||||
|
||||
---
|
||||
|
||||
## 输出示例
|
||||
|
||||
```markdown
|
||||
## Summary
|
||||
|
||||
This document discusses the implementation of a new feature
|
||||
for the application, focusing on user experience improvements
|
||||
and performance optimizations.
|
||||
|
||||
### Key Points
|
||||
|
||||
- ✅ New user interface design improves accessibility
|
||||
- ✅ Backend optimizations reduce load times by 40%
|
||||
- ✅ Mobile responsiveness enhanced
|
||||
- ✅ Integration with third-party services simplified
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 运行要求
|
||||
|
||||
!!! note "前置条件"
|
||||
- OpenWebUI v0.3.0 及以上
|
||||
- 使用当前会话的 LLM 模型进行摘要
|
||||
|
||||
---
|
||||
|
||||
## 源码
|
||||
|
||||
[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/summary){ .md-button }
|
||||
@@ -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
|
||||
|
||||
83
plugins/actions/deep-dive/README.md
Normal file
@@ -0,0 +1,83 @@
|
||||
# 🌊 Deep Dive
|
||||
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 1.0.0 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
A comprehensive thinking lens that dives deep into any content - from context to logic, insights, and action paths.
|
||||
|
||||
## 🔥 What's New in v1.0.0
|
||||
|
||||
- ✨ **Thinking Chain Structure**: Moves from surface understanding to deep strategic action.
|
||||
- 🔍 **Phase 01: The Context**: Panoramic view of the situation and background.
|
||||
- 🧠 **Phase 02: The Logic**: Deconstruction of the underlying reasoning and mental models.
|
||||
- 💎 **Phase 03: The Insight**: Extraction of non-obvious value and hidden implications.
|
||||
- 🚀 **Phase 04: The Path**: Definition of specific, prioritized strategic directions.
|
||||
- 🎨 **Premium UI**: Modern, process-oriented design with a "Thinking Line" timeline.
|
||||
- 🌗 **Theme Adaptive**: Automatically adapts to OpenWebUI's light/dark theme.
|
||||
|
||||
## ✨ Key Features
|
||||
|
||||
- 🌊 **Deep Thinking**: Not just a summary, but a full deconstruction of content.
|
||||
- 🧠 **Logical Analysis**: Reveals how arguments are built and identifies hidden assumptions.
|
||||
- 💎 **Value Extraction**: Finds the "Aha!" moments and blind spots.
|
||||
- 🚀 **Action Oriented**: Translates deep understanding into immediate, actionable steps.
|
||||
- 🌍 **Multi-language**: Automatically adapts to the user's preferred language.
|
||||
- 🌗 **Theme Support**: Seamlessly switches between light and dark themes based on OpenWebUI settings.
|
||||
|
||||
## 🚀 How to Use
|
||||
|
||||
1. **Input Content**: Provide any text, article, or meeting notes in the chat.
|
||||
2. **Trigger Deep Dive**: Click the **Deep Dive** action button.
|
||||
3. **Explore the Chain**: Follow the visual timeline from Context to Path.
|
||||
|
||||
## ⚙️ Configuration (Valves)
|
||||
|
||||
| Parameter | Default | Description |
|
||||
| :--- | :--- | :--- |
|
||||
| **Show Status (SHOW_STATUS)** | `True` | Whether to show status updates during the thinking process. |
|
||||
| **Model ID (MODEL_ID)** | `Empty` | LLM model for analysis. Empty = use current model. |
|
||||
| **Min Text Length (MIN_TEXT_LENGTH)** | `200` | Minimum characters required for a meaningful deep dive. |
|
||||
| **Clear Previous HTML (CLEAR_PREVIOUS_HTML)** | `True` | Whether to clear previous plugin results. |
|
||||
| **Message Count (MESSAGE_COUNT)** | `1` | Number of recent messages to analyze. |
|
||||
|
||||
## 🌗 Theme Support
|
||||
|
||||
The plugin automatically detects and adapts to OpenWebUI's theme settings:
|
||||
|
||||
- **Detection Priority**:
|
||||
1. Parent document `<meta name="theme-color">` tag
|
||||
2. Parent document `html/body` class or `data-theme` attribute
|
||||
3. System preference via `prefers-color-scheme: dark`
|
||||
|
||||
- **Requirements**: For best results, enable **iframe Sandbox Allow Same Origin** in OpenWebUI:
|
||||
- Go to **Settings** → **Interface** → **Artifacts** → Check **iframe Sandbox Allow Same Origin**
|
||||
|
||||
## 🎨 Visual Preview
|
||||
|
||||
The plugin generates a structured thinking timeline:
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────┐
|
||||
│ 🌊 Deep Dive Analysis │
|
||||
│ 👤 User 📅 Date 📊 Word count │
|
||||
├─────────────────────────────────────┤
|
||||
│ 🔍 Phase 01: The Context │
|
||||
│ [High-level panoramic view] │
|
||||
│ │
|
||||
│ 🧠 Phase 02: The Logic │
|
||||
│ • Reasoning structure... │
|
||||
│ • Hidden assumptions... │
|
||||
│ │
|
||||
│ 💎 Phase 03: The Insight │
|
||||
│ • Non-obvious value... │
|
||||
│ • Blind spots revealed... │
|
||||
│ │
|
||||
│ 🚀 Phase 04: The Path │
|
||||
│ ▸ Priority Action 1... │
|
||||
│ ▸ Priority Action 2... │
|
||||
└─────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## 📂 Files
|
||||
|
||||
- `deep_dive.py` - English version
|
||||
- `deep_dive_cn.py` - Chinese version (精读)
|
||||
83
plugins/actions/deep-dive/README_CN.md
Normal file
@@ -0,0 +1,83 @@
|
||||
# 📖 精读
|
||||
|
||||
**作者:** [Fu-Jie](https://github.com/Fu-Jie) | **版本:** 1.0.0 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
全方位的思维透镜 —— 从背景全景到逻辑脉络,从深度洞察到行动路径。
|
||||
|
||||
## 🔥 v1.0.0 更新内容
|
||||
|
||||
- ✨ **思维链结构**: 从表面理解一步步深入到战略行动。
|
||||
- 🔍 **阶段 01: 全景 (The Context)**: 提供情境与背景的高层级全景视图。
|
||||
- 🧠 **阶段 02: 脉络 (The Logic)**: 解构底层推理逻辑与思维模型。
|
||||
- 💎 **阶段 03: 洞察 (The Insight)**: 提取非显性价值与隐藏的深层含义。
|
||||
- 🚀 **阶段 04: 路径 (The Path)**: 定义具体的、按优先级排列的战略方向。
|
||||
- 🎨 **高端 UI**: 现代化的过程导向设计,带有"思维导火索"时间轴。
|
||||
- 🌗 **主题自适应**: 自动适配 OpenWebUI 的深色/浅色主题。
|
||||
|
||||
## ✨ 核心特性
|
||||
|
||||
- 📖 **深度思考**: 不仅仅是摘要,而是对内容的全面解构。
|
||||
- 🧠 **逻辑分析**: 揭示论点是如何构建的,识别隐藏的假设。
|
||||
- 💎 **价值提取**: 发现"原来如此"的时刻与思维盲点。
|
||||
- 🚀 **行动导向**: 将深度理解转化为立即、可执行的步骤。
|
||||
- 🌍 **多语言支持**: 自动适配用户的偏好语言。
|
||||
- 🌗 **主题支持**: 根据 OpenWebUI 设置自动切换深色/浅色主题。
|
||||
|
||||
## 🚀 如何使用
|
||||
|
||||
1. **输入内容**: 在聊天中提供任何文本、文章或会议记录。
|
||||
2. **触发精读**: 点击 **精读** 操作按钮。
|
||||
3. **探索思维链**: 沿着视觉时间轴从"全景"探索到"路径"。
|
||||
|
||||
## ⚙️ 配置参数 (Valves)
|
||||
|
||||
| 参数 | 默认值 | 描述 |
|
||||
| :--- | :--- | :--- |
|
||||
| **显示状态 (SHOW_STATUS)** | `True` | 是否在思维过程中显示状态更新。 |
|
||||
| **模型 ID (MODEL_ID)** | `空` | 用于分析的 LLM 模型。留空 = 使用当前模型。 |
|
||||
| **最小文本长度 (MIN_TEXT_LENGTH)** | `200` | 进行有意义的精读所需的最小字符数。 |
|
||||
| **清除旧 HTML (CLEAR_PREVIOUS_HTML)** | `True` | 是否清除之前的插件结果。 |
|
||||
| **消息数量 (MESSAGE_COUNT)** | `1` | 要分析的最近消息数量。 |
|
||||
|
||||
## 🌗 主题支持
|
||||
|
||||
插件会自动检测并适配 OpenWebUI 的主题设置:
|
||||
|
||||
- **检测优先级**:
|
||||
1. 父文档 `<meta name="theme-color">` 标签
|
||||
2. 父文档 `html/body` 的 class 或 `data-theme` 属性
|
||||
3. 系统偏好 `prefers-color-scheme: dark`
|
||||
|
||||
- **环境要求**: 为获得最佳效果,请在 OpenWebUI 中启用 **iframe Sandbox Allow Same Origin**:
|
||||
- 进入 **设置** → **界面** → **Artifacts** → 勾选 **iframe Sandbox Allow Same Origin**
|
||||
|
||||
## 🎨 视觉预览
|
||||
|
||||
插件生成结构化的思维时间轴:
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────┐
|
||||
│ 📖 精读分析报告 │
|
||||
│ 👤 用户 📅 日期 📊 字数 │
|
||||
├─────────────────────────────────────┤
|
||||
│ 🔍 阶段 01: 全景 (The Context) │
|
||||
│ [高层级全景视图内容] │
|
||||
│ │
|
||||
│ 🧠 阶段 02: 脉络 (The Logic) │
|
||||
│ • 推理结构分析... │
|
||||
│ • 隐藏假设识别... │
|
||||
│ │
|
||||
│ 💎 阶段 03: 洞察 (The Insight) │
|
||||
│ • 非显性价值提取... │
|
||||
│ • 思维盲点揭示... │
|
||||
│ │
|
||||
│ 🚀 阶段 04: 路径 (The Path) │
|
||||
│ ▸ 优先级行动 1... │
|
||||
│ ▸ 优先级行动 2... │
|
||||
└─────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## 📂 文件说明
|
||||
|
||||
- `deep_dive.py` - 英文版 (Deep Dive)
|
||||
- `deep_dive_cn.py` - 中文版 (精读)
|
||||
BIN
plugins/actions/deep-dive/deep_dive.png
Normal file
|
After Width: | Height: | Size: 783 KiB |
884
plugins/actions/deep-dive/deep_dive.py
Normal file
@@ -0,0 +1,884 @@
|
||||
"""
|
||||
title: Deep Dive
|
||||
author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 1.0.0
|
||||
icon_url: data:image/svg+xml;base64,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
|
||||
requirements: markdown
|
||||
description: A comprehensive thinking lens that dives deep into any content - from context to logic, insights, and action paths.
|
||||
"""
|
||||
|
||||
# Standard library imports
|
||||
import re
|
||||
import logging
|
||||
from typing import Optional, Dict, Any, Callable, Awaitable
|
||||
from datetime import datetime
|
||||
|
||||
# Third-party imports
|
||||
from pydantic import BaseModel, Field
|
||||
from fastapi import Request
|
||||
import markdown
|
||||
|
||||
# OpenWebUI imports
|
||||
from open_webui.utils.chat import generate_chat_completion
|
||||
from open_webui.models.users import Users
|
||||
|
||||
# Logging setup
|
||||
logging.basicConfig(
|
||||
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
|
||||
)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# =================================================================
|
||||
# HTML Template - Process-Oriented Design with Theme Support
|
||||
# =================================================================
|
||||
HTML_WRAPPER_TEMPLATE = """
|
||||
<!-- OPENWEBUI_PLUGIN_OUTPUT -->
|
||||
<!DOCTYPE html>
|
||||
<html lang="{user_language}">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<style>
|
||||
:root {
|
||||
--dd-bg-primary: #ffffff;
|
||||
--dd-bg-secondary: #f8fafc;
|
||||
--dd-bg-tertiary: #f1f5f9;
|
||||
--dd-text-primary: #0f172a;
|
||||
--dd-text-secondary: #334155;
|
||||
--dd-text-dim: #64748b;
|
||||
--dd-border: #e2e8f0;
|
||||
--dd-accent: #3b82f6;
|
||||
--dd-accent-soft: #eff6ff;
|
||||
--dd-header-gradient: linear-gradient(135deg, #1e293b 0%, #0f172a 100%);
|
||||
--dd-shadow: 0 10px 40px rgba(0,0,0,0.06);
|
||||
--dd-code-bg: #f1f5f9;
|
||||
}
|
||||
.theme-dark {
|
||||
--dd-bg-primary: #1e293b;
|
||||
--dd-bg-secondary: #0f172a;
|
||||
--dd-bg-tertiary: #334155;
|
||||
--dd-text-primary: #f1f5f9;
|
||||
--dd-text-secondary: #e2e8f0;
|
||||
--dd-text-dim: #94a3b8;
|
||||
--dd-border: #475569;
|
||||
--dd-accent: #60a5fa;
|
||||
--dd-accent-soft: rgba(59, 130, 246, 0.15);
|
||||
--dd-header-gradient: linear-gradient(135deg, #0f172a 0%, #1e1e2e 100%);
|
||||
--dd-shadow: 0 10px 40px rgba(0,0,0,0.3);
|
||||
--dd-code-bg: #334155;
|
||||
}
|
||||
body {
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
|
||||
margin: 0;
|
||||
padding: 10px;
|
||||
background-color: transparent;
|
||||
}
|
||||
#main-container {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 24px;
|
||||
width: 100%;
|
||||
max-width: 900px;
|
||||
margin: 0 auto;
|
||||
}
|
||||
.plugin-item {
|
||||
background: var(--dd-bg-primary);
|
||||
border-radius: 24px;
|
||||
box-shadow: var(--dd-shadow);
|
||||
overflow: hidden;
|
||||
border: 1px solid var(--dd-border);
|
||||
}
|
||||
/* STYLES_INSERTION_POINT */
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<div id="main-container">
|
||||
<!-- CONTENT_INSERTION_POINT -->
|
||||
</div>
|
||||
<!-- SCRIPTS_INSERTION_POINT -->
|
||||
<script>
|
||||
(function() {
|
||||
const parseColorLuma = (colorStr) => {
|
||||
if (!colorStr) return null;
|
||||
let m = colorStr.match(/^#?([0-9a-f]{6})$/i);
|
||||
if (m) {
|
||||
const hex = m[1];
|
||||
const r = parseInt(hex.slice(0, 2), 16);
|
||||
const g = parseInt(hex.slice(2, 4), 16);
|
||||
const b = parseInt(hex.slice(4, 6), 16);
|
||||
return (0.2126 * r + 0.7152 * g + 0.0722 * b) / 255;
|
||||
}
|
||||
m = colorStr.match(/rgba?\\s*\\(\\s*(\\d+)\\s*,\\s*(\\d+)\\s*,\\s*(\\d+)/i);
|
||||
if (m) {
|
||||
const r = parseInt(m[1], 10);
|
||||
const g = parseInt(m[2], 10);
|
||||
const b = parseInt(m[3], 10);
|
||||
return (0.2126 * r + 0.7152 * g + 0.0722 * b) / 255;
|
||||
}
|
||||
return null;
|
||||
};
|
||||
const getThemeFromMeta = (doc) => {
|
||||
const metas = Array.from((doc || document).querySelectorAll('meta[name="theme-color"]'));
|
||||
if (!metas.length) return null;
|
||||
const color = metas[metas.length - 1].content.trim();
|
||||
const luma = parseColorLuma(color);
|
||||
if (luma === null) return null;
|
||||
return luma < 0.5 ? 'dark' : 'light';
|
||||
};
|
||||
const getParentDocumentSafe = () => {
|
||||
try {
|
||||
if (!window.parent || window.parent === window) return null;
|
||||
const pDoc = window.parent.document;
|
||||
void pDoc.title;
|
||||
return pDoc;
|
||||
} catch (err) { return null; }
|
||||
};
|
||||
const getThemeFromParentClass = () => {
|
||||
try {
|
||||
if (!window.parent || window.parent === window) return null;
|
||||
const pDoc = window.parent.document;
|
||||
const html = pDoc.documentElement;
|
||||
const body = pDoc.body;
|
||||
const htmlClass = html ? html.className : '';
|
||||
const bodyClass = body ? body.className : '';
|
||||
const htmlDataTheme = html ? html.getAttribute('data-theme') : '';
|
||||
if (htmlDataTheme === 'dark' || bodyClass.includes('dark') || htmlClass.includes('dark')) return 'dark';
|
||||
if (htmlDataTheme === 'light' || bodyClass.includes('light') || htmlClass.includes('light')) return 'light';
|
||||
return null;
|
||||
} catch (err) { return null; }
|
||||
};
|
||||
const setTheme = () => {
|
||||
const parentDoc = getParentDocumentSafe();
|
||||
const metaTheme = parentDoc ? getThemeFromMeta(parentDoc) : null;
|
||||
const parentClassTheme = getThemeFromParentClass();
|
||||
const prefersDark = window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches;
|
||||
const chosen = metaTheme || parentClassTheme || (prefersDark ? 'dark' : 'light');
|
||||
document.documentElement.classList.toggle('theme-dark', chosen === 'dark');
|
||||
};
|
||||
setTheme();
|
||||
if (window.matchMedia) {
|
||||
window.matchMedia('(prefers-color-scheme: dark)').addEventListener('change', setTheme);
|
||||
}
|
||||
})();
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
# =================================================================
|
||||
# LLM Prompts - Deep Dive Thinking Chain
|
||||
# =================================================================
|
||||
|
||||
SYSTEM_PROMPT = """
|
||||
You are a Deep Dive Analyst. Your goal is to guide the user through a comprehensive thinking process, moving from surface understanding to deep strategic action.
|
||||
|
||||
## Thinking Structure (STRICT)
|
||||
|
||||
You MUST analyze the input across these four specific dimensions:
|
||||
|
||||
### 1. 🔍 The Context (What?)
|
||||
Provide a high-level panoramic view. What is this content about? What is the core situation, background, or problem being addressed? (2-3 paragraphs)
|
||||
|
||||
### 2. 🧠 The Logic (Why?)
|
||||
Deconstruct the underlying structure. How is the argument built? What is the reasoning, the hidden assumptions, or the mental models at play? (Bullet points)
|
||||
|
||||
### 3. 💎 The Insight (So What?)
|
||||
Extract the non-obvious value. What are the "Aha!" moments? What are the implications, the blind spots, or the unique perspectives revealed? (Bullet points)
|
||||
|
||||
### 4. 🚀 The Path (Now What?)
|
||||
Define the strategic direction. What are the specific, prioritized next steps? How can this knowledge be applied immediately? (Actionable steps)
|
||||
|
||||
## Rules
|
||||
- Output in the user's specified language.
|
||||
- Maintain a professional, analytical, yet inspiring tone.
|
||||
- Focus on the *process* of understanding, not just the result.
|
||||
- No greetings or meta-commentary.
|
||||
"""
|
||||
|
||||
USER_PROMPT = """
|
||||
Initiate a Deep Dive into the following content:
|
||||
|
||||
**User Context:**
|
||||
- User: {user_name}
|
||||
- Time: {current_date_time_str}
|
||||
- Language: {user_language}
|
||||
|
||||
**Content to Analyze:**
|
||||
```
|
||||
{long_text_content}
|
||||
```
|
||||
|
||||
Please execute the full thinking chain: Context → Logic → Insight → Path.
|
||||
"""
|
||||
|
||||
# =================================================================
|
||||
# Premium CSS Design - Deep Dive Theme
|
||||
# =================================================================
|
||||
|
||||
CSS_TEMPLATE = """
|
||||
.deep-dive {
|
||||
font-family: 'Inter', -apple-system, system-ui, sans-serif;
|
||||
color: var(--dd-text-secondary);
|
||||
}
|
||||
|
||||
.dd-header {
|
||||
background: var(--dd-header-gradient);
|
||||
padding: 40px 32px;
|
||||
color: white;
|
||||
position: relative;
|
||||
}
|
||||
|
||||
.dd-header-badge {
|
||||
display: inline-block;
|
||||
padding: 4px 12px;
|
||||
background: rgba(255,255,255,0.1);
|
||||
border: 1px solid rgba(255,255,255,0.2);
|
||||
border-radius: 100px;
|
||||
font-size: 0.75rem;
|
||||
font-weight: 600;
|
||||
letter-spacing: 0.05em;
|
||||
text-transform: uppercase;
|
||||
margin-bottom: 16px;
|
||||
}
|
||||
|
||||
.dd-title {
|
||||
font-size: 2rem;
|
||||
font-weight: 800;
|
||||
margin: 0 0 12px 0;
|
||||
letter-spacing: -0.02em;
|
||||
}
|
||||
|
||||
.dd-meta {
|
||||
display: flex;
|
||||
gap: 20px;
|
||||
font-size: 0.85rem;
|
||||
opacity: 0.7;
|
||||
}
|
||||
|
||||
.dd-body {
|
||||
padding: 32px;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 40px;
|
||||
position: relative;
|
||||
background: var(--dd-bg-primary);
|
||||
}
|
||||
|
||||
/* The Thinking Line */
|
||||
.dd-body::before {
|
||||
content: '';
|
||||
position: absolute;
|
||||
left: 52px;
|
||||
top: 40px;
|
||||
bottom: 40px;
|
||||
width: 2px;
|
||||
background: var(--dd-border);
|
||||
z-index: 0;
|
||||
}
|
||||
|
||||
.dd-step {
|
||||
position: relative;
|
||||
z-index: 1;
|
||||
display: flex;
|
||||
gap: 24px;
|
||||
}
|
||||
|
||||
.dd-step-icon {
|
||||
flex-shrink: 0;
|
||||
width: 40px;
|
||||
height: 40px;
|
||||
background: var(--dd-bg-primary);
|
||||
border: 2px solid var(--dd-border);
|
||||
border-radius: 12px;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
font-size: 1.25rem;
|
||||
box-shadow: 0 4px 12px rgba(0,0,0,0.03);
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
|
||||
.dd-step:hover .dd-step-icon {
|
||||
border-color: var(--dd-accent);
|
||||
transform: scale(1.1);
|
||||
}
|
||||
|
||||
.dd-step-content {
|
||||
flex: 1;
|
||||
}
|
||||
|
||||
.dd-step-label {
|
||||
font-size: 0.75rem;
|
||||
font-weight: 700;
|
||||
color: var(--dd-accent);
|
||||
text-transform: uppercase;
|
||||
letter-spacing: 0.1em;
|
||||
margin-bottom: 4px;
|
||||
}
|
||||
|
||||
.dd-step-title {
|
||||
font-size: 1.25rem;
|
||||
font-weight: 700;
|
||||
color: var(--dd-text-primary);
|
||||
margin: 0 0 16px 0;
|
||||
}
|
||||
|
||||
.dd-text {
|
||||
line-height: 1.7;
|
||||
font-size: 1rem;
|
||||
}
|
||||
|
||||
.dd-text p { margin-bottom: 16px; }
|
||||
.dd-text p:last-child { margin-bottom: 0; }
|
||||
|
||||
.dd-list {
|
||||
list-style: none;
|
||||
padding: 0;
|
||||
margin: 0;
|
||||
display: grid;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.dd-list-item {
|
||||
background: var(--dd-bg-secondary);
|
||||
padding: 16px 20px;
|
||||
border-radius: 12px;
|
||||
border-left: 4px solid var(--dd-border);
|
||||
transition: all 0.2s ease;
|
||||
}
|
||||
|
||||
.dd-list-item:hover {
|
||||
background: var(--dd-bg-tertiary);
|
||||
border-left-color: var(--dd-accent);
|
||||
transform: translateX(4px);
|
||||
}
|
||||
|
||||
.dd-list-item strong {
|
||||
color: var(--dd-text-primary);
|
||||
display: block;
|
||||
margin-bottom: 4px;
|
||||
}
|
||||
|
||||
.dd-path-item {
|
||||
background: var(--dd-accent-soft);
|
||||
border-left-color: var(--dd-accent);
|
||||
}
|
||||
|
||||
.dd-footer {
|
||||
padding: 24px 32px;
|
||||
background: var(--dd-bg-secondary);
|
||||
border-top: 1px solid var(--dd-border);
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
font-size: 0.8rem;
|
||||
color: var(--dd-text-dim);
|
||||
}
|
||||
|
||||
.dd-tag {
|
||||
padding: 2px 8px;
|
||||
background: var(--dd-bg-tertiary);
|
||||
border-radius: 4px;
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
.dd-text code,
|
||||
.dd-list-item code {
|
||||
background: var(--dd-code-bg);
|
||||
color: var(--dd-text-primary);
|
||||
padding: 2px 6px;
|
||||
border-radius: 4px;
|
||||
font-family: 'SF Mono', 'Consolas', 'Monaco', monospace;
|
||||
font-size: 0.85em;
|
||||
}
|
||||
|
||||
.dd-list-item em {
|
||||
font-style: italic;
|
||||
color: var(--dd-text-dim);
|
||||
}
|
||||
"""
|
||||
|
||||
CONTENT_TEMPLATE = """
|
||||
<div class="deep-dive">
|
||||
<div class="dd-header">
|
||||
<div class="dd-header-badge">Thinking Process</div>
|
||||
<h1 class="dd-title">Deep Dive Analysis</h1>
|
||||
<div class="dd-meta">
|
||||
<span>👤 {user_name}</span>
|
||||
<span>📅 {current_date_time_str}</span>
|
||||
<span>📊 {word_count} words</span>
|
||||
</div>
|
||||
</div>
|
||||
<div class="dd-body">
|
||||
<!-- Step 1: Context -->
|
||||
<div class="dd-step">
|
||||
<div class="dd-step-icon">🔍</div>
|
||||
<div class="dd-step-content">
|
||||
<div class="dd-step-label">Phase 01</div>
|
||||
<h2 class="dd-step-title">The Context</h2>
|
||||
<div class="dd-text">{context_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Step 2: Logic -->
|
||||
<div class="dd-step">
|
||||
<div class="dd-step-icon">🧠</div>
|
||||
<div class="dd-step-content">
|
||||
<div class="dd-step-label">Phase 02</div>
|
||||
<h2 class="dd-step-title">The Logic</h2>
|
||||
<div class="dd-text">{logic_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Step 3: Insight -->
|
||||
<div class="dd-step">
|
||||
<div class="dd-step-icon">💎</div>
|
||||
<div class="dd-step-content">
|
||||
<div class="dd-step-label">Phase 03</div>
|
||||
<h2 class="dd-step-title">The Insight</h2>
|
||||
<div class="dd-text">{insight_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Step 4: Path -->
|
||||
<div class="dd-step">
|
||||
<div class="dd-step-icon">🚀</div>
|
||||
<div class="dd-step-content">
|
||||
<div class="dd-step-label">Phase 04</div>
|
||||
<h2 class="dd-step-title">The Path</h2>
|
||||
<div class="dd-text">{path_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="dd-footer">
|
||||
<span>Deep Dive Engine v1.0</span>
|
||||
<span><span class="dd-tag">AI-Powered</span></span>
|
||||
</div>
|
||||
</div>
|
||||
"""
|
||||
|
||||
|
||||
class Action:
|
||||
class Valves(BaseModel):
|
||||
SHOW_STATUS: bool = Field(
|
||||
default=True,
|
||||
description="Whether to show operation status updates.",
|
||||
)
|
||||
MODEL_ID: str = Field(
|
||||
default="",
|
||||
description="LLM Model ID for analysis. Empty = use current model.",
|
||||
)
|
||||
MIN_TEXT_LENGTH: int = Field(
|
||||
default=200,
|
||||
description="Minimum text length for deep dive (chars).",
|
||||
)
|
||||
CLEAR_PREVIOUS_HTML: bool = Field(
|
||||
default=True,
|
||||
description="Whether to clear previous plugin results.",
|
||||
)
|
||||
MESSAGE_COUNT: int = Field(
|
||||
default=1,
|
||||
description="Number of recent messages to analyze.",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _get_user_context(self, __user__: Optional[Dict[str, Any]]) -> Dict[str, str]:
|
||||
"""Safely extracts user context information."""
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
user_data = __user__[0] if __user__ else {}
|
||||
elif isinstance(__user__, dict):
|
||||
user_data = __user__
|
||||
else:
|
||||
user_data = {}
|
||||
|
||||
return {
|
||||
"user_id": user_data.get("id", "unknown_user"),
|
||||
"user_name": user_data.get("name", "User"),
|
||||
"user_language": user_data.get("language", "en-US"),
|
||||
}
|
||||
|
||||
def _process_llm_output(self, llm_output: str) -> Dict[str, str]:
|
||||
"""Parse LLM output and convert to styled HTML."""
|
||||
# Extract sections using flexible regex
|
||||
context_match = re.search(
|
||||
r"###\s*1\.\s*🔍?\s*The Context\s*\((.*?)\)\s*\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
logic_match = re.search(
|
||||
r"###\s*2\.\s*🧠?\s*The Logic\s*\((.*?)\)\s*\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
insight_match = re.search(
|
||||
r"###\s*3\.\s*💎?\s*The Insight\s*\((.*?)\)\s*\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
path_match = re.search(
|
||||
r"###\s*4\.\s*🚀?\s*The Path\s*\((.*?)\)\s*\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
|
||||
# Fallback if numbering is different
|
||||
if not context_match:
|
||||
context_match = re.search(
|
||||
r"###\s*🔍?\s*The Context.*?\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
if not logic_match:
|
||||
logic_match = re.search(
|
||||
r"###\s*🧠?\s*The Logic.*?\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
if not insight_match:
|
||||
insight_match = re.search(
|
||||
r"###\s*💎?\s*The Insight.*?\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
if not path_match:
|
||||
path_match = re.search(
|
||||
r"###\s*🚀?\s*The Path.*?\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
|
||||
context_md = (
|
||||
context_match.group(1 if context_match.lastindex == 1 else 2).strip()
|
||||
if context_match
|
||||
else ""
|
||||
)
|
||||
logic_md = (
|
||||
logic_match.group(1 if logic_match.lastindex == 1 else 2).strip()
|
||||
if logic_match
|
||||
else ""
|
||||
)
|
||||
insight_md = (
|
||||
insight_match.group(1 if insight_match.lastindex == 1 else 2).strip()
|
||||
if insight_match
|
||||
else ""
|
||||
)
|
||||
path_md = (
|
||||
path_match.group(1 if path_match.lastindex == 1 else 2).strip()
|
||||
if path_match
|
||||
else ""
|
||||
)
|
||||
|
||||
if not any([context_md, logic_md, insight_md, path_md]):
|
||||
context_md = llm_output.strip()
|
||||
logger.warning("LLM output did not follow format. Using as context.")
|
||||
|
||||
md_extensions = ["nl2br"]
|
||||
|
||||
context_html = (
|
||||
markdown.markdown(context_md, extensions=md_extensions)
|
||||
if context_md
|
||||
else '<p class="dd-no-content">No context extracted.</p>'
|
||||
)
|
||||
logic_html = (
|
||||
self._process_list_items(logic_md, "logic")
|
||||
if logic_md
|
||||
else '<p class="dd-no-content">No logic deconstructed.</p>'
|
||||
)
|
||||
insight_html = (
|
||||
self._process_list_items(insight_md, "insight")
|
||||
if insight_md
|
||||
else '<p class="dd-no-content">No insights found.</p>'
|
||||
)
|
||||
path_html = (
|
||||
self._process_list_items(path_md, "path")
|
||||
if path_md
|
||||
else '<p class="dd-no-content">No path defined.</p>'
|
||||
)
|
||||
|
||||
return {
|
||||
"context_html": context_html,
|
||||
"logic_html": logic_html,
|
||||
"insight_html": insight_html,
|
||||
"path_html": path_html,
|
||||
}
|
||||
|
||||
def _process_list_items(self, md_content: str, section_type: str) -> str:
|
||||
"""Convert markdown list to styled HTML cards with full markdown support."""
|
||||
lines = md_content.strip().split("\n")
|
||||
items = []
|
||||
current_paragraph = []
|
||||
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
|
||||
# Check for list item (bullet or numbered)
|
||||
bullet_match = re.match(r"^[-*]\s+(.+)$", line)
|
||||
numbered_match = re.match(r"^\d+\.\s+(.+)$", line)
|
||||
|
||||
if bullet_match or numbered_match:
|
||||
# Flush any accumulated paragraph
|
||||
if current_paragraph:
|
||||
para_text = " ".join(current_paragraph)
|
||||
para_html = self._convert_inline_markdown(para_text)
|
||||
items.append(f"<p>{para_html}</p>")
|
||||
current_paragraph = []
|
||||
|
||||
# Extract the list item content
|
||||
text = (
|
||||
bullet_match.group(1) if bullet_match else numbered_match.group(1)
|
||||
)
|
||||
|
||||
# Handle bold title pattern: **Title:** Description or **Title**: Description
|
||||
title_match = re.match(r"\*\*(.+?)\*\*[:\s]*(.*)$", text)
|
||||
if title_match:
|
||||
title = self._convert_inline_markdown(title_match.group(1))
|
||||
desc = self._convert_inline_markdown(title_match.group(2).strip())
|
||||
path_class = "dd-path-item" if section_type == "path" else ""
|
||||
item_html = f'<div class="dd-list-item {path_class}"><strong>{title}</strong>{desc}</div>'
|
||||
else:
|
||||
text_html = self._convert_inline_markdown(text)
|
||||
path_class = "dd-path-item" if section_type == "path" else ""
|
||||
item_html = (
|
||||
f'<div class="dd-list-item {path_class}">{text_html}</div>'
|
||||
)
|
||||
items.append(item_html)
|
||||
elif line and not line.startswith("#"):
|
||||
# Accumulate paragraph text
|
||||
current_paragraph.append(line)
|
||||
elif not line and current_paragraph:
|
||||
# Empty line ends paragraph
|
||||
para_text = " ".join(current_paragraph)
|
||||
para_html = self._convert_inline_markdown(para_text)
|
||||
items.append(f"<p>{para_html}</p>")
|
||||
current_paragraph = []
|
||||
|
||||
# Flush remaining paragraph
|
||||
if current_paragraph:
|
||||
para_text = " ".join(current_paragraph)
|
||||
para_html = self._convert_inline_markdown(para_text)
|
||||
items.append(f"<p>{para_html}</p>")
|
||||
|
||||
if items:
|
||||
return f'<div class="dd-list">{" ".join(items)}</div>'
|
||||
return f'<p class="dd-no-content">No items found.</p>'
|
||||
|
||||
def _convert_inline_markdown(self, text: str) -> str:
|
||||
"""Convert inline markdown (bold, italic, code) to HTML."""
|
||||
# Convert inline code: `code` -> <code>code</code>
|
||||
text = re.sub(r"`([^`]+)`", r"<code>\1</code>", text)
|
||||
# Convert bold: **text** -> <strong>text</strong>
|
||||
text = re.sub(r"\*\*(.+?)\*\*", r"<strong>\1</strong>", text)
|
||||
# Convert italic: *text* -> <em>text</em> (but not inside **)
|
||||
text = re.sub(r"(?<!\*)\*([^*]+)\*(?!\*)", r"<em>\1</em>", text)
|
||||
return text
|
||||
|
||||
async def _emit_status(
|
||||
self,
|
||||
emitter: Optional[Callable[[Any], Awaitable[None]]],
|
||||
description: str,
|
||||
done: bool = False,
|
||||
):
|
||||
"""Emits a status update event."""
|
||||
if self.valves.SHOW_STATUS and emitter:
|
||||
await emitter(
|
||||
{"type": "status", "data": {"description": description, "done": done}}
|
||||
)
|
||||
|
||||
async def _emit_notification(
|
||||
self,
|
||||
emitter: Optional[Callable[[Any], Awaitable[None]]],
|
||||
content: str,
|
||||
ntype: str = "info",
|
||||
):
|
||||
"""Emits a notification event."""
|
||||
if emitter:
|
||||
await emitter(
|
||||
{"type": "notification", "data": {"type": ntype, "content": content}}
|
||||
)
|
||||
|
||||
def _remove_existing_html(self, content: str) -> str:
|
||||
"""Removes existing plugin-generated HTML."""
|
||||
pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"
|
||||
return re.sub(pattern, "", content).strip()
|
||||
|
||||
def _extract_text_content(self, content) -> str:
|
||||
"""Extract text from message content."""
|
||||
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 ""
|
||||
|
||||
def _merge_html(
|
||||
self,
|
||||
existing_html: str,
|
||||
new_content: str,
|
||||
new_styles: str = "",
|
||||
user_language: str = "en-US",
|
||||
) -> str:
|
||||
"""Merges new content into HTML container."""
|
||||
if "<!-- OPENWEBUI_PLUGIN_OUTPUT -->" in existing_html:
|
||||
base_html = re.sub(r"^```html\s*", "", existing_html)
|
||||
base_html = re.sub(r"\s*```$", "", base_html)
|
||||
else:
|
||||
base_html = HTML_WRAPPER_TEMPLATE.replace("{user_language}", user_language)
|
||||
|
||||
wrapped = f'<div class="plugin-item">\n{new_content}\n</div>'
|
||||
|
||||
if new_styles:
|
||||
base_html = base_html.replace(
|
||||
"/* STYLES_INSERTION_POINT */",
|
||||
f"{new_styles}\n/* STYLES_INSERTION_POINT */",
|
||||
)
|
||||
|
||||
base_html = base_html.replace(
|
||||
"<!-- CONTENT_INSERTION_POINT -->",
|
||||
f"{wrapped}\n<!-- CONTENT_INSERTION_POINT -->",
|
||||
)
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _build_content_html(self, context: dict) -> str:
|
||||
"""Build content HTML."""
|
||||
html = CONTENT_TEMPLATE
|
||||
for key, value in context.items():
|
||||
html = html.replace(f"{{{key}}}", str(value))
|
||||
return html
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[Dict[str, Any]] = None,
|
||||
__event_emitter__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__request__: Optional[Request] = None,
|
||||
) -> Optional[dict]:
|
||||
logger.info("Action: Deep Dive v1.0.0 started")
|
||||
|
||||
user_ctx = self._get_user_context(__user__)
|
||||
user_id = user_ctx["user_id"]
|
||||
user_name = user_ctx["user_name"]
|
||||
user_language = user_ctx["user_language"]
|
||||
|
||||
now = datetime.now()
|
||||
current_date_time_str = now.strftime("%b %d, %Y %H:%M")
|
||||
|
||||
original_content = ""
|
||||
try:
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
raise ValueError("No messages found.")
|
||||
|
||||
message_count = min(self.valves.MESSAGE_COUNT, len(messages))
|
||||
recent_messages = messages[-message_count:]
|
||||
|
||||
aggregated_parts = []
|
||||
for msg in recent_messages:
|
||||
text = self._extract_text_content(msg.get("content"))
|
||||
if text:
|
||||
aggregated_parts.append(text)
|
||||
|
||||
if not aggregated_parts:
|
||||
raise ValueError("No text content found.")
|
||||
|
||||
original_content = "\n\n---\n\n".join(aggregated_parts)
|
||||
word_count = len(original_content.split())
|
||||
|
||||
if len(original_content) < self.valves.MIN_TEXT_LENGTH:
|
||||
msg = f"Content too brief ({len(original_content)} chars). Deep Dive requires at least {self.valves.MIN_TEXT_LENGTH} chars for meaningful analysis."
|
||||
await self._emit_notification(__event_emitter__, msg, "warning")
|
||||
return {"messages": [{"role": "assistant", "content": f"⚠️ {msg}"}]}
|
||||
|
||||
await self._emit_notification(
|
||||
__event_emitter__, "🌊 Initiating Deep Dive thinking process...", "info"
|
||||
)
|
||||
await self._emit_status(
|
||||
__event_emitter__, "🌊 Deep Dive: Analyzing Context & Logic...", False
|
||||
)
|
||||
|
||||
prompt = USER_PROMPT.format(
|
||||
user_name=user_name,
|
||||
current_date_time_str=current_date_time_str,
|
||||
user_language=user_language,
|
||||
long_text_content=original_content,
|
||||
)
|
||||
|
||||
model = self.valves.MODEL_ID or body.get("model")
|
||||
payload = {
|
||||
"model": model,
|
||||
"messages": [
|
||||
{"role": "system", "content": SYSTEM_PROMPT},
|
||||
{"role": "user", "content": prompt},
|
||||
],
|
||||
"stream": False,
|
||||
}
|
||||
|
||||
user_obj = Users.get_user_by_id(user_id)
|
||||
if not user_obj:
|
||||
raise ValueError(f"User not found: {user_id}")
|
||||
|
||||
response = await generate_chat_completion(__request__, payload, user_obj)
|
||||
llm_output = response["choices"][0]["message"]["content"]
|
||||
|
||||
processed = self._process_llm_output(llm_output)
|
||||
|
||||
context = {
|
||||
"user_name": user_name,
|
||||
"current_date_time_str": current_date_time_str,
|
||||
"word_count": word_count,
|
||||
**processed,
|
||||
}
|
||||
|
||||
content_html = self._build_content_html(context)
|
||||
|
||||
# Handle existing HTML
|
||||
existing = ""
|
||||
match = re.search(
|
||||
r"```html\s*(<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?)```",
|
||||
original_content,
|
||||
)
|
||||
if match:
|
||||
existing = match.group(1)
|
||||
|
||||
if self.valves.CLEAR_PREVIOUS_HTML or not existing:
|
||||
original_content = self._remove_existing_html(original_content)
|
||||
final_html = self._merge_html(
|
||||
"", content_html, CSS_TEMPLATE, user_language
|
||||
)
|
||||
else:
|
||||
original_content = self._remove_existing_html(original_content)
|
||||
final_html = self._merge_html(
|
||||
existing, content_html, CSS_TEMPLATE, user_language
|
||||
)
|
||||
|
||||
body["messages"][-1][
|
||||
"content"
|
||||
] = f"{original_content}\n\n```html\n{final_html}\n```"
|
||||
|
||||
await self._emit_status(__event_emitter__, "🌊 Deep Dive complete!", True)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"🌊 Deep Dive complete, {user_name}! Thinking chain generated.",
|
||||
"success",
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Deep Dive Error: {e}", exc_info=True)
|
||||
body["messages"][-1][
|
||||
"content"
|
||||
] = f"{original_content}\n\n❌ **Error:** {str(e)}"
|
||||
await self._emit_status(__event_emitter__, "Deep Dive failed.", True)
|
||||
await self._emit_notification(
|
||||
__event_emitter__, f"Error: {str(e)}", "error"
|
||||
)
|
||||
|
||||
return body
|
||||
BIN
plugins/actions/deep-dive/deep_dive_cn.png
Normal file
|
After Width: | Height: | Size: 997 KiB |
876
plugins/actions/deep-dive/deep_dive_cn.py
Normal file
@@ -0,0 +1,876 @@
|
||||
"""
|
||||
title: 精读
|
||||
author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 1.0.0
|
||||
icon_url: data:image/svg+xml;base64,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
|
||||
requirements: markdown
|
||||
description: 全方位的思维透镜 —— 从背景全景到逻辑脉络,从深度洞察到行动路径。
|
||||
"""
|
||||
|
||||
# Standard library imports
|
||||
import re
|
||||
import logging
|
||||
from typing import Optional, Dict, Any, Callable, Awaitable
|
||||
from datetime import datetime
|
||||
|
||||
# Third-party imports
|
||||
from pydantic import BaseModel, Field
|
||||
from fastapi import Request
|
||||
import markdown
|
||||
|
||||
# OpenWebUI imports
|
||||
from open_webui.utils.chat import generate_chat_completion
|
||||
from open_webui.models.users import Users
|
||||
|
||||
# Logging setup
|
||||
logging.basicConfig(
|
||||
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
|
||||
)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# =================================================================
|
||||
# HTML 模板 - 过程导向设计,支持主题自适应
|
||||
# =================================================================
|
||||
HTML_WRAPPER_TEMPLATE = """
|
||||
<!-- OPENWEBUI_PLUGIN_OUTPUT -->
|
||||
<!DOCTYPE html>
|
||||
<html lang="{user_language}">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<style>
|
||||
:root {
|
||||
--dd-bg-primary: #ffffff;
|
||||
--dd-bg-secondary: #f8fafc;
|
||||
--dd-bg-tertiary: #f1f5f9;
|
||||
--dd-text-primary: #0f172a;
|
||||
--dd-text-secondary: #334155;
|
||||
--dd-text-dim: #64748b;
|
||||
--dd-border: #e2e8f0;
|
||||
--dd-accent: #3b82f6;
|
||||
--dd-accent-soft: #eff6ff;
|
||||
--dd-header-gradient: linear-gradient(135deg, #1e293b 0%, #0f172a 100%);
|
||||
--dd-shadow: 0 10px 40px rgba(0,0,0,0.06);
|
||||
--dd-code-bg: #f1f5f9;
|
||||
}
|
||||
.theme-dark {
|
||||
--dd-bg-primary: #1e293b;
|
||||
--dd-bg-secondary: #0f172a;
|
||||
--dd-bg-tertiary: #334155;
|
||||
--dd-text-primary: #f1f5f9;
|
||||
--dd-text-secondary: #e2e8f0;
|
||||
--dd-text-dim: #94a3b8;
|
||||
--dd-border: #475569;
|
||||
--dd-accent: #60a5fa;
|
||||
--dd-accent-soft: rgba(59, 130, 246, 0.15);
|
||||
--dd-header-gradient: linear-gradient(135deg, #0f172a 0%, #1e1e2e 100%);
|
||||
--dd-shadow: 0 10px 40px rgba(0,0,0,0.3);
|
||||
--dd-code-bg: #334155;
|
||||
}
|
||||
body {
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
|
||||
margin: 0;
|
||||
padding: 10px;
|
||||
background-color: transparent;
|
||||
}
|
||||
#main-container {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 24px;
|
||||
width: 100%;
|
||||
max-width: 900px;
|
||||
margin: 0 auto;
|
||||
}
|
||||
.plugin-item {
|
||||
background: var(--dd-bg-primary);
|
||||
border-radius: 24px;
|
||||
box-shadow: var(--dd-shadow);
|
||||
overflow: hidden;
|
||||
border: 1px solid var(--dd-border);
|
||||
}
|
||||
/* STYLES_INSERTION_POINT */
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<div id="main-container">
|
||||
<!-- CONTENT_INSERTION_POINT -->
|
||||
</div>
|
||||
<!-- SCRIPTS_INSERTION_POINT -->
|
||||
<script>
|
||||
(function() {
|
||||
const parseColorLuma = (colorStr) => {
|
||||
if (!colorStr) return null;
|
||||
let m = colorStr.match(/^#?([0-9a-f]{6})$/i);
|
||||
if (m) {
|
||||
const hex = m[1];
|
||||
const r = parseInt(hex.slice(0, 2), 16);
|
||||
const g = parseInt(hex.slice(2, 4), 16);
|
||||
const b = parseInt(hex.slice(4, 6), 16);
|
||||
return (0.2126 * r + 0.7152 * g + 0.0722 * b) / 255;
|
||||
}
|
||||
m = colorStr.match(/rgba?\\s*\\(\\s*(\\d+)\\s*,\\s*(\\d+)\\s*,\\s*(\\d+)/i);
|
||||
if (m) {
|
||||
const r = parseInt(m[1], 10);
|
||||
const g = parseInt(m[2], 10);
|
||||
const b = parseInt(m[3], 10);
|
||||
return (0.2126 * r + 0.7152 * g + 0.0722 * b) / 255;
|
||||
}
|
||||
return null;
|
||||
};
|
||||
const getThemeFromMeta = (doc) => {
|
||||
const metas = Array.from((doc || document).querySelectorAll('meta[name="theme-color"]'));
|
||||
if (!metas.length) return null;
|
||||
const color = metas[metas.length - 1].content.trim();
|
||||
const luma = parseColorLuma(color);
|
||||
if (luma === null) return null;
|
||||
return luma < 0.5 ? 'dark' : 'light';
|
||||
};
|
||||
const getParentDocumentSafe = () => {
|
||||
try {
|
||||
if (!window.parent || window.parent === window) return null;
|
||||
const pDoc = window.parent.document;
|
||||
void pDoc.title;
|
||||
return pDoc;
|
||||
} catch (err) { return null; }
|
||||
};
|
||||
const getThemeFromParentClass = () => {
|
||||
try {
|
||||
if (!window.parent || window.parent === window) return null;
|
||||
const pDoc = window.parent.document;
|
||||
const html = pDoc.documentElement;
|
||||
const body = pDoc.body;
|
||||
const htmlClass = html ? html.className : '';
|
||||
const bodyClass = body ? body.className : '';
|
||||
const htmlDataTheme = html ? html.getAttribute('data-theme') : '';
|
||||
if (htmlDataTheme === 'dark' || bodyClass.includes('dark') || htmlClass.includes('dark')) return 'dark';
|
||||
if (htmlDataTheme === 'light' || bodyClass.includes('light') || htmlClass.includes('light')) return 'light';
|
||||
return null;
|
||||
} catch (err) { return null; }
|
||||
};
|
||||
const setTheme = () => {
|
||||
const parentDoc = getParentDocumentSafe();
|
||||
const metaTheme = parentDoc ? getThemeFromMeta(parentDoc) : null;
|
||||
const parentClassTheme = getThemeFromParentClass();
|
||||
const prefersDark = window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches;
|
||||
const chosen = metaTheme || parentClassTheme || (prefersDark ? 'dark' : 'light');
|
||||
document.documentElement.classList.toggle('theme-dark', chosen === 'dark');
|
||||
};
|
||||
setTheme();
|
||||
if (window.matchMedia) {
|
||||
window.matchMedia('(prefers-color-scheme: dark)').addEventListener('change', setTheme);
|
||||
}
|
||||
})();
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
# =================================================================
|
||||
# LLM 提示词 - 深度下潜思维链
|
||||
# =================================================================
|
||||
|
||||
SYSTEM_PROMPT = """
|
||||
你是一位“深度下潜 (Deep Dive)”分析专家。你的目标是引导用户完成一个全面的思维过程,从表面理解深入到战略行动。
|
||||
|
||||
## 思维结构 (严格遵守)
|
||||
|
||||
你必须从以下四个维度剖析输入内容:
|
||||
|
||||
### 1. 🔍 The Context (全景)
|
||||
提供一个高层级的全景视图。内容是关于什么的?核心情境、背景或正在解决的问题是什么?(2-3 段话)
|
||||
|
||||
### 2. 🧠 The Logic (脉络)
|
||||
解构底层结构。论点是如何构建的?其中的推理逻辑、隐藏假设或起作用的思维模型是什么?(列表形式)
|
||||
|
||||
### 3. 💎 The Insight (洞察)
|
||||
提取非显性的价值。有哪些“原来如此”的时刻?揭示了哪些深层含义、盲点或独特视角?(列表形式)
|
||||
|
||||
### 4. 🚀 The Path (路径)
|
||||
定义战略方向。具体的、按优先级排列的下一步行动是什么?如何立即应用这些知识?(可执行步骤)
|
||||
|
||||
## 规则
|
||||
- 使用用户指定的语言输出。
|
||||
- 保持专业、分析性且富有启发性的语调。
|
||||
- 聚焦于“理解的过程”,而不仅仅是结果。
|
||||
- 不要包含寒暄或元对话。
|
||||
"""
|
||||
|
||||
USER_PROMPT = """
|
||||
对以下内容发起“深度下潜”:
|
||||
|
||||
**用户上下文:**
|
||||
- 用户:{user_name}
|
||||
- 时间:{current_date_time_str}
|
||||
- 语言:{user_language}
|
||||
|
||||
**待分析内容:**
|
||||
```
|
||||
{long_text_content}
|
||||
```
|
||||
|
||||
请执行完整的思维链:全景 (Context) → 脉络 (Logic) → 洞察 (Insight) → 路径 (Path)。
|
||||
"""
|
||||
|
||||
# =================================================================
|
||||
# 现代 CSS 设计 - 深度下潜主题
|
||||
# =================================================================
|
||||
|
||||
CSS_TEMPLATE = """
|
||||
.deep-dive {
|
||||
font-family: 'Inter', -apple-system, system-ui, sans-serif;
|
||||
color: var(--dd-text-secondary);
|
||||
}
|
||||
|
||||
.dd-header {
|
||||
background: var(--dd-header-gradient);
|
||||
padding: 40px 32px;
|
||||
color: white;
|
||||
position: relative;
|
||||
}
|
||||
|
||||
.dd-header-badge {
|
||||
display: inline-block;
|
||||
padding: 4px 12px;
|
||||
background: rgba(255,255,255,0.1);
|
||||
border: 1px solid rgba(255,255,255,0.2);
|
||||
border-radius: 100px;
|
||||
font-size: 0.75rem;
|
||||
font-weight: 600;
|
||||
letter-spacing: 0.05em;
|
||||
text-transform: uppercase;
|
||||
margin-bottom: 16px;
|
||||
}
|
||||
|
||||
.dd-title {
|
||||
font-size: 2rem;
|
||||
font-weight: 800;
|
||||
margin: 0 0 12px 0;
|
||||
letter-spacing: -0.02em;
|
||||
}
|
||||
|
||||
.dd-meta {
|
||||
display: flex;
|
||||
gap: 20px;
|
||||
font-size: 0.85rem;
|
||||
opacity: 0.7;
|
||||
}
|
||||
|
||||
.dd-body {
|
||||
padding: 32px;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 40px;
|
||||
position: relative;
|
||||
background: var(--dd-bg-primary);
|
||||
}
|
||||
|
||||
/* 思维导火索 */
|
||||
.dd-body::before {
|
||||
content: '';
|
||||
position: absolute;
|
||||
left: 52px;
|
||||
top: 40px;
|
||||
bottom: 40px;
|
||||
width: 2px;
|
||||
background: var(--dd-border);
|
||||
z-index: 0;
|
||||
}
|
||||
|
||||
.dd-step {
|
||||
position: relative;
|
||||
z-index: 1;
|
||||
display: flex;
|
||||
gap: 24px;
|
||||
}
|
||||
|
||||
.dd-step-icon {
|
||||
flex-shrink: 0;
|
||||
width: 40px;
|
||||
height: 40px;
|
||||
background: var(--dd-bg-primary);
|
||||
border: 2px solid var(--dd-border);
|
||||
border-radius: 12px;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
font-size: 1.25rem;
|
||||
box-shadow: 0 4px 12px rgba(0,0,0,0.03);
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
|
||||
.dd-step:hover .dd-step-icon {
|
||||
border-color: var(--dd-accent);
|
||||
transform: scale(1.1);
|
||||
}
|
||||
|
||||
.dd-step-content {
|
||||
flex: 1;
|
||||
}
|
||||
|
||||
.dd-step-label {
|
||||
font-size: 0.75rem;
|
||||
font-weight: 700;
|
||||
color: var(--dd-accent);
|
||||
text-transform: uppercase;
|
||||
letter-spacing: 0.1em;
|
||||
margin-bottom: 4px;
|
||||
}
|
||||
|
||||
.dd-step-title {
|
||||
font-size: 1.25rem;
|
||||
font-weight: 700;
|
||||
color: var(--dd-text-primary);
|
||||
margin: 0 0 16px 0;
|
||||
}
|
||||
|
||||
.dd-text {
|
||||
line-height: 1.7;
|
||||
font-size: 1rem;
|
||||
}
|
||||
|
||||
.dd-text p { margin-bottom: 16px; }
|
||||
.dd-text p:last-child { margin-bottom: 0; }
|
||||
|
||||
.dd-list {
|
||||
list-style: none;
|
||||
padding: 0;
|
||||
margin: 0;
|
||||
display: grid;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.dd-list-item {
|
||||
background: var(--dd-bg-secondary);
|
||||
padding: 16px 20px;
|
||||
border-radius: 12px;
|
||||
border-left: 4px solid var(--dd-border);
|
||||
transition: all 0.2s ease;
|
||||
}
|
||||
|
||||
.dd-list-item:hover {
|
||||
background: var(--dd-bg-tertiary);
|
||||
border-left-color: var(--dd-accent);
|
||||
transform: translateX(4px);
|
||||
}
|
||||
|
||||
.dd-list-item strong {
|
||||
color: var(--dd-text-primary);
|
||||
display: block;
|
||||
margin-bottom: 4px;
|
||||
}
|
||||
|
||||
.dd-path-item {
|
||||
background: var(--dd-accent-soft);
|
||||
border-left-color: var(--dd-accent);
|
||||
}
|
||||
|
||||
.dd-footer {
|
||||
padding: 24px 32px;
|
||||
background: var(--dd-bg-secondary);
|
||||
border-top: 1px solid var(--dd-border);
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
font-size: 0.8rem;
|
||||
color: var(--dd-text-dim);
|
||||
}
|
||||
|
||||
.dd-tag {
|
||||
padding: 2px 8px;
|
||||
background: var(--dd-bg-tertiary);
|
||||
border-radius: 4px;
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
.dd-text code,
|
||||
.dd-list-item code {
|
||||
background: var(--dd-code-bg);
|
||||
color: var(--dd-text-primary);
|
||||
padding: 2px 6px;
|
||||
border-radius: 4px;
|
||||
font-family: 'SF Mono', 'Consolas', 'Monaco', monospace;
|
||||
font-size: 0.85em;
|
||||
}
|
||||
|
||||
.dd-list-item em {
|
||||
font-style: italic;
|
||||
color: var(--dd-text-dim);
|
||||
}
|
||||
"""
|
||||
|
||||
CONTENT_TEMPLATE = """
|
||||
<div class="deep-dive">
|
||||
<div class="dd-header">
|
||||
<div class="dd-header-badge">思维过程</div>
|
||||
<h1 class="dd-title">精读分析报告</h1>
|
||||
<div class="dd-meta">
|
||||
<span>👤 {user_name}</span>
|
||||
<span>📅 {current_date_time_str}</span>
|
||||
<span>📊 {word_count} 字</span>
|
||||
</div>
|
||||
</div>
|
||||
<div class="dd-body">
|
||||
<!-- 第一步:全景 -->
|
||||
<div class="dd-step">
|
||||
<div class="dd-step-icon">🔍</div>
|
||||
<div class="dd-step-content">
|
||||
<div class="dd-step-label">Phase 01</div>
|
||||
<h2 class="dd-step-title">全景 (The Context)</h2>
|
||||
<div class="dd-text">{context_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 第二步:脉络 -->
|
||||
<div class="dd-step">
|
||||
<div class="dd-step-icon">🧠</div>
|
||||
<div class="dd-step-content">
|
||||
<div class="dd-step-label">Phase 02</div>
|
||||
<h2 class="dd-step-title">脉络 (The Logic)</h2>
|
||||
<div class="dd-text">{logic_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 第三步:洞察 -->
|
||||
<div class="dd-step">
|
||||
<div class="dd-step-icon">💎</div>
|
||||
<div class="dd-step-content">
|
||||
<div class="dd-step-label">Phase 03</div>
|
||||
<h2 class="dd-step-title">洞察 (The Insight)</h2>
|
||||
<div class="dd-text">{insight_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 第四步:路径 -->
|
||||
<div class="dd-step">
|
||||
<div class="dd-step-icon">🚀</div>
|
||||
<div class="dd-step-content">
|
||||
<div class="dd-step-label">Phase 04</div>
|
||||
<h2 class="dd-step-title">路径 (The Path)</h2>
|
||||
<div class="dd-text">{path_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="dd-footer">
|
||||
<span>Deep Dive Engine v1.0</span>
|
||||
<span><span class="dd-tag">AI 驱动分析</span></span>
|
||||
</div>
|
||||
</div>
|
||||
"""
|
||||
|
||||
|
||||
class Action:
|
||||
class Valves(BaseModel):
|
||||
SHOW_STATUS: bool = Field(
|
||||
default=True,
|
||||
description="是否显示操作状态更新。",
|
||||
)
|
||||
MODEL_ID: str = Field(
|
||||
default="",
|
||||
description="用于分析的 LLM 模型 ID。留空则使用当前模型。",
|
||||
)
|
||||
MIN_TEXT_LENGTH: int = Field(
|
||||
default=200,
|
||||
description="深度下潜所需的最小文本长度(字符)。",
|
||||
)
|
||||
CLEAR_PREVIOUS_HTML: bool = Field(
|
||||
default=True,
|
||||
description="是否清除之前的插件结果。",
|
||||
)
|
||||
MESSAGE_COUNT: int = Field(
|
||||
default=1,
|
||||
description="要分析的最近消息数量。",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _get_user_context(self, __user__: Optional[Dict[str, Any]]) -> Dict[str, str]:
|
||||
"""安全提取用户上下文信息。"""
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
user_data = __user__[0] if __user__ else {}
|
||||
elif isinstance(__user__, dict):
|
||||
user_data = __user__
|
||||
else:
|
||||
user_data = {}
|
||||
|
||||
return {
|
||||
"user_id": user_data.get("id", "unknown_user"),
|
||||
"user_name": user_data.get("name", "用户"),
|
||||
"user_language": user_data.get("language", "zh-CN"),
|
||||
}
|
||||
|
||||
def _process_llm_output(self, llm_output: str) -> Dict[str, str]:
|
||||
"""解析 LLM 输出并转换为样式化 HTML。"""
|
||||
# 使用灵活的正则提取各部分
|
||||
context_match = re.search(
|
||||
r"###\s*1\.\s*🔍?\s*(?:全景|The Context)\s*(?:\((.*?)\))?\s*\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
logic_match = re.search(
|
||||
r"###\s*2\.\s*🧠?\s*(?:脉络|The Logic)\s*(?:\((.*?)\))?\s*\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
insight_match = re.search(
|
||||
r"###\s*3\.\s*💎?\s*(?:洞察|The Insight)\s*(?:\((.*?)\))?\s*\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
path_match = re.search(
|
||||
r"###\s*4\.\s*🚀?\s*(?:路径|The Path)\s*(?:\((.*?)\))?\s*\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
|
||||
# 兜底正则
|
||||
if not context_match:
|
||||
context_match = re.search(
|
||||
r"###\s*🔍?\s*(?:全景|The Context).*?\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
if not logic_match:
|
||||
logic_match = re.search(
|
||||
r"###\s*🧠?\s*(?:脉络|The Logic).*?\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
if not insight_match:
|
||||
insight_match = re.search(
|
||||
r"###\s*💎?\s*(?:洞察|The Insight).*?\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
if not path_match:
|
||||
path_match = re.search(
|
||||
r"###\s*🚀?\s*(?:路径|The Path).*?\n(.*?)(?=\n###|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
|
||||
context_md = (
|
||||
context_match.group(context_match.lastindex).strip()
|
||||
if context_match
|
||||
else ""
|
||||
)
|
||||
logic_md = (
|
||||
logic_match.group(logic_match.lastindex).strip() if logic_match else ""
|
||||
)
|
||||
insight_md = (
|
||||
insight_match.group(insight_match.lastindex).strip()
|
||||
if insight_match
|
||||
else ""
|
||||
)
|
||||
path_md = path_match.group(path_match.lastindex).strip() if path_match else ""
|
||||
|
||||
if not any([context_md, logic_md, insight_md, path_md]):
|
||||
context_md = llm_output.strip()
|
||||
logger.warning("LLM 输出未遵循格式,将作为全景处理。")
|
||||
|
||||
md_extensions = ["nl2br"]
|
||||
|
||||
context_html = (
|
||||
markdown.markdown(context_md, extensions=md_extensions)
|
||||
if context_md
|
||||
else '<p class="dd-no-content">未能提取全景信息。</p>'
|
||||
)
|
||||
logic_html = (
|
||||
self._process_list_items(logic_md, "logic")
|
||||
if logic_md
|
||||
else '<p class="dd-no-content">未能解构脉络。</p>'
|
||||
)
|
||||
insight_html = (
|
||||
self._process_list_items(insight_md, "insight")
|
||||
if insight_md
|
||||
else '<p class="dd-no-content">未能发现洞察。</p>'
|
||||
)
|
||||
path_html = (
|
||||
self._process_list_items(path_md, "path")
|
||||
if path_md
|
||||
else '<p class="dd-no-content">未能定义路径。</p>'
|
||||
)
|
||||
|
||||
return {
|
||||
"context_html": context_html,
|
||||
"logic_html": logic_html,
|
||||
"insight_html": insight_html,
|
||||
"path_html": path_html,
|
||||
}
|
||||
|
||||
def _process_list_items(self, md_content: str, section_type: str) -> str:
|
||||
"""将 markdown 列表转换为样式化卡片,支持完整的 markdown 格式。"""
|
||||
lines = md_content.strip().split("\n")
|
||||
items = []
|
||||
current_paragraph = []
|
||||
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
|
||||
# 检查列表项(无序或有序)
|
||||
bullet_match = re.match(r"^[-*]\s+(.+)$", line)
|
||||
numbered_match = re.match(r"^\d+\.\s+(.+)$", line)
|
||||
|
||||
if bullet_match or numbered_match:
|
||||
# 清空累积的段落
|
||||
if current_paragraph:
|
||||
para_text = " ".join(current_paragraph)
|
||||
para_html = self._convert_inline_markdown(para_text)
|
||||
items.append(f"<p>{para_html}</p>")
|
||||
current_paragraph = []
|
||||
|
||||
# 提取列表项内容
|
||||
text = (
|
||||
bullet_match.group(1) if bullet_match else numbered_match.group(1)
|
||||
)
|
||||
|
||||
# 处理粗体标题模式:**标题:** 描述 或 **标题**: 描述
|
||||
title_match = re.match(r"\*\*(.+?)\*\*[:\s:]*(.*)$", text)
|
||||
if title_match:
|
||||
title = self._convert_inline_markdown(title_match.group(1))
|
||||
desc = self._convert_inline_markdown(title_match.group(2).strip())
|
||||
path_class = "dd-path-item" if section_type == "path" else ""
|
||||
item_html = f'<div class="dd-list-item {path_class}"><strong>{title}</strong>{desc}</div>'
|
||||
else:
|
||||
text_html = self._convert_inline_markdown(text)
|
||||
path_class = "dd-path-item" if section_type == "path" else ""
|
||||
item_html = (
|
||||
f'<div class="dd-list-item {path_class}">{text_html}</div>'
|
||||
)
|
||||
items.append(item_html)
|
||||
elif line and not line.startswith("#"):
|
||||
# 累积段落文本
|
||||
current_paragraph.append(line)
|
||||
elif not line and current_paragraph:
|
||||
# 空行结束段落
|
||||
para_text = " ".join(current_paragraph)
|
||||
para_html = self._convert_inline_markdown(para_text)
|
||||
items.append(f"<p>{para_html}</p>")
|
||||
current_paragraph = []
|
||||
|
||||
# 清空剩余段落
|
||||
if current_paragraph:
|
||||
para_text = " ".join(current_paragraph)
|
||||
para_html = self._convert_inline_markdown(para_text)
|
||||
items.append(f"<p>{para_html}</p>")
|
||||
|
||||
if items:
|
||||
return f'<div class="dd-list">{" ".join(items)}</div>'
|
||||
return f'<p class="dd-no-content">未找到条目。</p>'
|
||||
|
||||
def _convert_inline_markdown(self, text: str) -> str:
|
||||
"""将行内 markdown(粗体、斜体、代码)转换为 HTML。"""
|
||||
# 转换行内代码:`code` -> <code>code</code>
|
||||
text = re.sub(r"`([^`]+)`", r"<code>\1</code>", text)
|
||||
# 转换粗体:**text** -> <strong>text</strong>
|
||||
text = re.sub(r"\*\*(.+?)\*\*", r"<strong>\1</strong>", text)
|
||||
# 转换斜体:*text* -> <em>text</em>(但不在 ** 内部)
|
||||
text = re.sub(r"(?<!\*)\*([^*]+)\*(?!\*)", r"<em>\1</em>", text)
|
||||
return text
|
||||
|
||||
async def _emit_status(
|
||||
self,
|
||||
emitter: Optional[Callable[[Any], Awaitable[None]]],
|
||||
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}}
|
||||
)
|
||||
|
||||
async def _emit_notification(
|
||||
self,
|
||||
emitter: Optional[Callable[[Any], Awaitable[None]]],
|
||||
content: str,
|
||||
ntype: str = "info",
|
||||
):
|
||||
"""发送通知事件。"""
|
||||
if emitter:
|
||||
await emitter(
|
||||
{"type": "notification", "data": {"type": ntype, "content": content}}
|
||||
)
|
||||
|
||||
def _remove_existing_html(self, content: str) -> str:
|
||||
"""移除已有的插件生成的 HTML。"""
|
||||
pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"
|
||||
return re.sub(pattern, "", content).strip()
|
||||
|
||||
def _extract_text_content(self, content) -> str:
|
||||
"""从消息内容中提取文本。"""
|
||||
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 ""
|
||||
|
||||
def _merge_html(
|
||||
self,
|
||||
existing_html: str,
|
||||
new_content: str,
|
||||
new_styles: str = "",
|
||||
user_language: str = "zh-CN",
|
||||
) -> str:
|
||||
"""合并新内容到 HTML 容器。"""
|
||||
if "<!-- OPENWEBUI_PLUGIN_OUTPUT -->" in existing_html:
|
||||
base_html = re.sub(r"^```html\s*", "", existing_html)
|
||||
base_html = re.sub(r"\s*```$", "", base_html)
|
||||
else:
|
||||
base_html = HTML_WRAPPER_TEMPLATE.replace("{user_language}", user_language)
|
||||
|
||||
wrapped = f'<div class="plugin-item">\n{new_content}\n</div>'
|
||||
|
||||
if new_styles:
|
||||
base_html = base_html.replace(
|
||||
"/* STYLES_INSERTION_POINT */",
|
||||
f"{new_styles}\n/* STYLES_INSERTION_POINT */",
|
||||
)
|
||||
|
||||
base_html = base_html.replace(
|
||||
"<!-- CONTENT_INSERTION_POINT -->",
|
||||
f"{wrapped}\n<!-- CONTENT_INSERTION_POINT -->",
|
||||
)
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _build_content_html(self, context: dict) -> str:
|
||||
"""构建内容 HTML。"""
|
||||
html = CONTENT_TEMPLATE
|
||||
for key, value in context.items():
|
||||
html = html.replace(f"{{{key}}}", str(value))
|
||||
return html
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[Dict[str, Any]] = None,
|
||||
__event_emitter__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__request__: Optional[Request] = None,
|
||||
) -> Optional[dict]:
|
||||
logger.info("Action: 精读 v1.0.0 启动")
|
||||
|
||||
user_ctx = self._get_user_context(__user__)
|
||||
user_id = user_ctx["user_id"]
|
||||
user_name = user_ctx["user_name"]
|
||||
user_language = user_ctx["user_language"]
|
||||
|
||||
now = datetime.now()
|
||||
current_date_time_str = now.strftime("%Y年%m月%d日 %H:%M")
|
||||
|
||||
original_content = ""
|
||||
try:
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
raise ValueError("未找到消息内容。")
|
||||
|
||||
message_count = min(self.valves.MESSAGE_COUNT, len(messages))
|
||||
recent_messages = messages[-message_count:]
|
||||
|
||||
aggregated_parts = []
|
||||
for msg in recent_messages:
|
||||
text = self._extract_text_content(msg.get("content"))
|
||||
if text:
|
||||
aggregated_parts.append(text)
|
||||
|
||||
if not aggregated_parts:
|
||||
raise ValueError("未找到文本内容。")
|
||||
|
||||
original_content = "\n\n---\n\n".join(aggregated_parts)
|
||||
word_count = len(original_content)
|
||||
|
||||
if len(original_content) < self.valves.MIN_TEXT_LENGTH:
|
||||
msg = f"内容过短({len(original_content)} 字符)。精读至少需要 {self.valves.MIN_TEXT_LENGTH} 字符才能进行有意义的分析。"
|
||||
await self._emit_notification(__event_emitter__, msg, "warning")
|
||||
return {"messages": [{"role": "assistant", "content": f"⚠️ {msg}"}]}
|
||||
|
||||
await self._emit_notification(
|
||||
__event_emitter__, "📖 正在发起精读分析...", "info"
|
||||
)
|
||||
await self._emit_status(
|
||||
__event_emitter__, "📖 精读:正在分析全景与脉络...", False
|
||||
)
|
||||
|
||||
prompt = USER_PROMPT.format(
|
||||
user_name=user_name,
|
||||
current_date_time_str=current_date_time_str,
|
||||
user_language=user_language,
|
||||
long_text_content=original_content,
|
||||
)
|
||||
|
||||
model = self.valves.MODEL_ID or body.get("model")
|
||||
payload = {
|
||||
"model": model,
|
||||
"messages": [
|
||||
{"role": "system", "content": SYSTEM_PROMPT},
|
||||
{"role": "user", "content": prompt},
|
||||
],
|
||||
"stream": False,
|
||||
}
|
||||
|
||||
user_obj = Users.get_user_by_id(user_id)
|
||||
if not user_obj:
|
||||
raise ValueError(f"未找到用户:{user_id}")
|
||||
|
||||
response = await generate_chat_completion(__request__, payload, user_obj)
|
||||
llm_output = response["choices"][0]["message"]["content"]
|
||||
|
||||
processed = self._process_llm_output(llm_output)
|
||||
|
||||
context = {
|
||||
"user_name": user_name,
|
||||
"current_date_time_str": current_date_time_str,
|
||||
"word_count": word_count,
|
||||
**processed,
|
||||
}
|
||||
|
||||
content_html = self._build_content_html(context)
|
||||
|
||||
# 处理已有 HTML
|
||||
existing = ""
|
||||
match = re.search(
|
||||
r"```html\s*(<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?)```",
|
||||
original_content,
|
||||
)
|
||||
if match:
|
||||
existing = match.group(1)
|
||||
|
||||
if self.valves.CLEAR_PREVIOUS_HTML or not existing:
|
||||
original_content = self._remove_existing_html(original_content)
|
||||
final_html = self._merge_html(
|
||||
"", content_html, CSS_TEMPLATE, user_language
|
||||
)
|
||||
else:
|
||||
original_content = self._remove_existing_html(original_content)
|
||||
final_html = self._merge_html(
|
||||
existing, content_html, CSS_TEMPLATE, user_language
|
||||
)
|
||||
|
||||
body["messages"][-1][
|
||||
"content"
|
||||
] = f"{original_content}\n\n```html\n{final_html}\n```"
|
||||
|
||||
await self._emit_status(__event_emitter__, "📖 精读完成!", True)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"📖 精读完成,{user_name}!思维链已生成。",
|
||||
"success",
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Deep Dive 错误:{e}", exc_info=True)
|
||||
body["messages"][-1][
|
||||
"content"
|
||||
] = f"{original_content}\n\n❌ **错误:** {str(e)}"
|
||||
await self._emit_status(__event_emitter__, "精读失败。", True)
|
||||
await self._emit_notification(__event_emitter__, f"错误:{str(e)}", "error")
|
||||
|
||||
return body
|
||||
@@ -1,95 +1,88 @@
|
||||
# Export to Word
|
||||
# 📝 Export to Word (Enhanced)
|
||||
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.4.3 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
Export conversation to Word (.docx) with **syntax highlighting**, **native math equations**, **Mermaid diagrams**, **citations**, and **enhanced table formatting**.
|
||||
|
||||
## Features
|
||||
## 🔥 What's New in v0.4.3
|
||||
|
||||
- **One-Click Export**: Adds an "Export to Word" action button to the chat.
|
||||
- **Markdown Conversion**: Converts Markdown syntax to Word formatting (headings, bold, italic, code, tables, lists).
|
||||
- **Syntax Highlighting**: Code blocks are highlighted with Pygments (supports 500+ languages).
|
||||
- **Native Math Equations**: LaTeX math (`$$...$$`, `\[...\]`, `$...$`, `\(...\)`) converted to editable Word equations.
|
||||
- **Mermaid Diagrams**: Mermaid flowcharts and sequence diagrams rendered as images in the document.
|
||||
- **Citations & References**: Auto-generates a References section from OpenWebUI sources with clickable citation links.
|
||||
- **Reasoning Stripping**: Automatically removes AI thinking blocks (`<think>`, `<analysis>`) from exports.
|
||||
- **Enhanced Tables**: Smart column widths, column alignment (`:---`, `---:`, `:---:`), header row repeat across pages.
|
||||
- **Blockquote Support**: Markdown blockquotes are rendered with left border and gray styling.
|
||||
- **Multi-language Support**: Properly handles both Chinese and English text.
|
||||
- **Smarter Filenames**: Configurable title source (Chat Title, AI Generated, or Markdown Title).
|
||||
- ✨ **S3 Object Storage Support**: Direct access to images stored in S3/MinIO via boto3, bypassing API layer for faster exports.
|
||||
- 🔧 **Multi-level File Fallback**: 6-level fallback mechanism for file retrieval (DB → S3 → Local → URL → API → Attributes).
|
||||
- 🛡️ **Improved Error Handling**: Better logging and error messages for file retrieval failures.
|
||||
|
||||
## Configuration
|
||||
## ✨ Key Features
|
||||
|
||||
You can configure the following settings via the **Valves** button in the plugin settings:
|
||||
- 🚀 **One-Click Export**: Adds an "Export to Word" action button to the chat.
|
||||
- 📄 **Markdown Conversion**: Full Markdown syntax support (headings, bold, italic, code, tables, lists).
|
||||
- 🎨 **Syntax Highlighting**: Code blocks highlighted with Pygments (500+ languages).
|
||||
- 🔢 **Native Math Equations**: LaTeX math (`$$...$$`, `\[...\]`, `$...$`) converted to editable Word equations.
|
||||
- 📊 **Mermaid Diagrams**: Flowcharts and sequence diagrams rendered as images.
|
||||
- 📚 **Citations & References**: Auto-generates References section with clickable citation links.
|
||||
- 🧹 **Reasoning Stripping**: Automatically removes AI thinking blocks (`<think>`, `<analysis>`).
|
||||
- 📋 **Enhanced Tables**: Smart column widths, alignment, header row repeat across pages.
|
||||
- 💬 **Blockquote Support**: Markdown blockquotes with left border and gray styling.
|
||||
- 🌐 **Multi-language Support**: Proper handling of Chinese and English text.
|
||||
|
||||
- **TITLE_SOURCE**: Choose how the document title/filename is generated.
|
||||
- `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).
|
||||
- **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.
|
||||
## 🚀 How to Use
|
||||
|
||||
## Supported Markdown Syntax
|
||||
1. **Install**: Search for "Export to Word" in the Open WebUI Community and install.
|
||||
2. **Trigger**: In any chat, click the "Export to Word" action button.
|
||||
3. **Download**: The .docx file will be automatically downloaded.
|
||||
|
||||
| Syntax | Word Result |
|
||||
| :---------------------------------- | :------------------------------------ |
|
||||
| `# Heading 1` to `###### Heading 6` | Heading levels 1-6 |
|
||||
| `**bold**` or `__bold__` | Bold text |
|
||||
| `*italic*` or `_italic_` | Italic text |
|
||||
| `***bold italic***` | Bold + Italic |
|
||||
| `` `inline code` `` | Monospace with gray background |
|
||||
| ` ``` code block ``` ` | **Syntax highlighted** code block |
|
||||
| `> blockquote` | Left-bordered gray italic text |
|
||||
| `[link](url)` | Blue underlined link text |
|
||||
| `~~strikethrough~~` | Strikethrough text |
|
||||
| `- item` or `* item` | Bullet list |
|
||||
| `1. item` | Numbered list |
|
||||
| Markdown tables | **Enhanced table** with smart widths |
|
||||
| `---` or `***` | Horizontal rule |
|
||||
| `$$LaTeX$$` or `\[LaTeX\]` | **Native Word equation** (display) |
|
||||
| `$LaTeX$` or `\(LaTeX\)` | **Native Word equation** (inline) |
|
||||
| ` ```mermaid ... ``` ` | **Mermaid diagram** as image |
|
||||
| `[1]` citation markers | **Clickable links** to References |
|
||||
## ⚙️ Configuration (Valves)
|
||||
|
||||
## Usage
|
||||
| Parameter | Default | Description |
|
||||
| :--- | :--- | :--- |
|
||||
| **Title Source (TITLE_SOURCE)** | `chat_title` | `chat_title`, `ai_generated`, or `markdown_title` |
|
||||
| **Max Image Size (MAX_EMBED_IMAGE_MB)** | `20` | Maximum image size to embed (MB) |
|
||||
| **UI Language (UI_LANGUAGE)** | `en` | `en` (English) or `zh` (Chinese) |
|
||||
| **Latin Font (FONT_LATIN)** | `Times New Roman` | Font for Latin characters |
|
||||
| **Asian Font (FONT_ASIAN)** | `SimSun` | Font for Asian characters |
|
||||
| **Code Font (FONT_CODE)** | `Consolas` | Font for code blocks |
|
||||
| **Table Header Color** | `F2F2F2` | Header background color (hex) |
|
||||
| **Table Zebra Color** | `FBFBFB` | Alternating row color (hex) |
|
||||
| **Mermaid PNG Scale** | `3.0` | Resolution multiplier for Mermaid images |
|
||||
| **Math Enable** | `True` | Enable LaTeX math conversion |
|
||||
|
||||
1. Install the plugin.
|
||||
2. In any chat, click the "Export to Word" button.
|
||||
3. The .docx file will be automatically downloaded to your device.
|
||||
## 🛠️ Supported Markdown Syntax
|
||||
|
||||
## Requirements
|
||||
| Syntax | Word Result |
|
||||
| :--- | :--- |
|
||||
| `# Heading 1` to `###### Heading 6` | Heading levels 1-6 |
|
||||
| `**bold**` or `__bold__` | Bold text |
|
||||
| `*italic*` or `_italic_` | Italic text |
|
||||
| `` `inline code` `` | Monospace with gray background |
|
||||
| ` ``` code block ``` ` | **Syntax highlighted** code block |
|
||||
| `> blockquote` | Left-bordered gray italic text |
|
||||
| `[link](url)` | Blue underlined link |
|
||||
| `~~strikethrough~~` | Strikethrough text |
|
||||
| `- item` or `* item` | Bullet list |
|
||||
| `1. item` | Numbered list |
|
||||
| Markdown tables | **Enhanced table** with smart widths |
|
||||
| `$$LaTeX$$` or `\[LaTeX\]` | **Native Word equation** (display) |
|
||||
| `$LaTeX$` or `\(LaTeX\)` | **Native Word equation** (inline) |
|
||||
| ` ```mermaid ... ``` ` | **Mermaid diagram** as image |
|
||||
| `[1]` citation markers | **Clickable links** to References |
|
||||
|
||||
## 📦 Requirements
|
||||
|
||||
- `python-docx==1.1.2` - Word document generation
|
||||
- `Pygments>=2.15.0` - Syntax highlighting
|
||||
- `latex2mathml` - LaTeX to MathML conversion
|
||||
- `mathml2omml` - MathML to Office Math (OMML) conversion
|
||||
|
||||
All dependencies are declared in the plugin docstring.
|
||||
## 📝 Changelog
|
||||
|
||||
## Font Configuration
|
||||
### v0.4.3
|
||||
- **S3 Object Storage**: Direct S3/MinIO access via boto3 for faster image retrieval.
|
||||
- **6-Level Fallback**: Robust file retrieval: DB → S3 → Local → URL → API → Attributes.
|
||||
- **Better Logging**: Improved error messages for debugging file access issues.
|
||||
|
||||
- **English Text**: Times New Roman
|
||||
- **Chinese Text**: SimSun (宋体) for body, SimHei (黑体) for headings
|
||||
- **Code**: Consolas
|
||||
### v0.4.1
|
||||
- **Chinese Parameter Names**: Localized configuration names for Chinese version.
|
||||
|
||||
## Changelog
|
||||
|
||||
### v0.2.0
|
||||
- Added native math equation support (LaTeX → OMML)
|
||||
- Added Mermaid diagram rendering
|
||||
- Added citations and references section generation
|
||||
- Added automatic reasoning block stripping
|
||||
- Enhanced table formatting with smart column widths and alignment
|
||||
|
||||
### v0.1.1
|
||||
- Initial release with basic Markdown to Word conversion
|
||||
|
||||
## Author
|
||||
|
||||
Fu-Jie
|
||||
GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
## License
|
||||
|
||||
MIT License
|
||||
### v0.4.0
|
||||
- **Multi-language Support**: UI language switching (English/Chinese).
|
||||
- **Font & Style Configuration**: Customizable fonts and table colors.
|
||||
- **Mermaid Enhancements**: Hybrid SVG+PNG rendering, background color config.
|
||||
- **Performance**: Real-time progress updates for large exports.
|
||||
|
||||
@@ -1,95 +1,88 @@
|
||||
# 导出为 Word
|
||||
# 📝 导出为 Word (增强版)
|
||||
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.4.3 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
将对话导出为 Word (.docx),支持**代码语法高亮**、**原生数学公式**、**Mermaid 图表**、**引用参考**和**增强表格格式**。
|
||||
|
||||
## 功能特点
|
||||
## 🔥 v0.4.3 更新内容
|
||||
|
||||
- **一键导出**:在聊天界面添加"导出为 Word"动作按钮。
|
||||
- **Markdown 转换**:将 Markdown 语法转换为 Word 格式(标题、粗体、斜体、代码、表格、列表)。
|
||||
- **代码语法高亮**:使用 Pygments 库为代码块添加语法高亮(支持 500+ 种语言)。
|
||||
- **原生数学公式**:LaTeX 公式(`$$...$$`、`\[...\]`、`$...$`、`\(...\)`)转换为可编辑的 Word 公式。
|
||||
- **Mermaid 图表**:Mermaid 流程图和时序图渲染为文档中的图片。
|
||||
- **引用与参考**:自动从 OpenWebUI 来源生成参考资料章节,支持可点击的引用链接。
|
||||
- **移除思考过程**:自动移除 AI 思考块(`<think>`、`<analysis>`)。
|
||||
- **增强表格**:智能列宽、列对齐(`:---`、`---:`、`:---:`)、表头跨页重复。
|
||||
- **引用块支持**:Markdown 引用块渲染为带左侧边框的灰色斜体样式。
|
||||
- **多语言支持**:正确处理中文和英文文本,无乱码问题。
|
||||
- **智能文件名**:可配置标题来源(对话标题、AI 生成或 Markdown 标题)。
|
||||
- ✨ **S3 对象存储支持**: 通过 boto3 直连 S3/MinIO,绕过 API 层,导出速度更快。
|
||||
- 🔧 **多级文件回退**: 6 级文件获取机制(数据库 → S3 → 本地 → URL → API → 属性)。
|
||||
- 🛡️ **错误处理优化**: 更完善的日志记录和错误提示,便于调试文件访问问题。
|
||||
|
||||
## 配置
|
||||
## ✨ 核心特性
|
||||
|
||||
您可以通过插件设置中的 **Valves** 按钮配置以下选项:
|
||||
- 🚀 **一键导出**: 在聊天界面添加"导出为 Word"动作按钮。
|
||||
- 📄 **Markdown 转换**: 完整支持 Markdown 语法(标题、粗体、斜体、代码、表格、列表)。
|
||||
- 🎨 **代码语法高亮**: 使用 Pygments 库高亮代码块(支持 500+ 种语言)。
|
||||
- 🔢 **原生数学公式**: LaTeX 公式(`$$...$$`、`\[...\]`、`$...$`)转换为可编辑的 Word 公式。
|
||||
- 📊 **Mermaid 图表**: 流程图和时序图渲染为文档中的图片。
|
||||
- 📚 **引用与参考**: 自动生成参考资料章节,支持可点击的引用链接。
|
||||
- 🧹 **移除思考过程**: 自动移除 AI 思考块(`<think>`、`<analysis>`)。
|
||||
- 📋 **增强表格**: 智能列宽、对齐、表头跨页重复。
|
||||
- 💬 **引用块支持**: Markdown 引用块渲染为带左侧边框的灰色斜体样式。
|
||||
- 🌐 **多语言支持**: 正确处理中文和英文文本。
|
||||
|
||||
- **TITLE_SOURCE**: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。
|
||||
## 🚀 使用方法
|
||||
|
||||
## 支持的 Markdown 语法
|
||||
1. **安装**: 在 Open WebUI 社区搜索 "导出为 Word" 并安装。
|
||||
2. **触发**: 在任意对话中,点击"导出为 Word"动作按钮。
|
||||
3. **下载**: .docx 文件将自动下载到你的设备。
|
||||
|
||||
| 语法 | Word 效果 |
|
||||
| :---------------------------- | :-------------------------------- |
|
||||
| `# 标题1` 到 `###### 标题6` | 标题级别 1-6 |
|
||||
| `**粗体**` 或 `__粗体__` | 粗体文本 |
|
||||
| `*斜体*` 或 `_斜体_` | 斜体文本 |
|
||||
| `***粗斜体***` | 粗体 + 斜体 |
|
||||
| `` `行内代码` `` | 等宽字体 + 灰色背景 |
|
||||
| ` ``` 代码块 ``` ` | **语法高亮**的代码块 |
|
||||
| `> 引用文本` | 带左侧边框的灰色斜体文本 |
|
||||
| `[链接](url)` | 蓝色下划线链接文本 |
|
||||
| `~~删除线~~` | 删除线文本 |
|
||||
| `- 项目` 或 `* 项目` | 无序列表 |
|
||||
| `1. 项目` | 有序列表 |
|
||||
| Markdown 表格 | **增强表格**(智能列宽) |
|
||||
| `---` 或 `***` | 水平分割线 |
|
||||
| `$$LaTeX$$` 或 `\[LaTeX\]` | **原生 Word 公式**(块级) |
|
||||
| `$LaTeX$` 或 `\(LaTeX\)` | **原生 Word 公式**(行内) |
|
||||
| ` ```mermaid ... ``` ` | **Mermaid 图表**(图片形式) |
|
||||
| `[1]` 引用标记 | **可点击链接**到参考资料 |
|
||||
## ⚙️ 配置参数 (Valves)
|
||||
|
||||
## 使用方法
|
||||
| 参数 | 默认值 | 说明 |
|
||||
| :--- | :--- | :--- |
|
||||
| **文档标题来源** | `chat_title` | `chat_title`(对话标题)、`ai_generated`(AI 生成)、`markdown_title`(Markdown 标题)|
|
||||
| **最大嵌入图片大小MB** | `20` | 嵌入图片的最大大小 (MB) |
|
||||
| **界面语言** | `zh` | `en`(英语)或 `zh`(中文)|
|
||||
| **英文字体** | `Calibri` | 英文字体名称 |
|
||||
| **中文字体** | `SimSun` | 中文字体名称 |
|
||||
| **代码字体** | `Consolas` | 代码块字体名称 |
|
||||
| **表头背景色** | `F2F2F2` | 表头背景色(十六进制)|
|
||||
| **表格隔行背景色** | `FBFBFB` | 表格隔行背景色(十六进制)|
|
||||
| **Mermaid_PNG缩放比例** | `3.0` | Mermaid 图片分辨率倍数 |
|
||||
| **启用数学公式** | `True` | 启用 LaTeX 公式转换 |
|
||||
|
||||
1. 安装插件。
|
||||
2. 在任意对话中,点击"导出为 Word"按钮。
|
||||
3. .docx 文件将自动下载到你的设备。
|
||||
## 🛠️ 支持的 Markdown 语法
|
||||
|
||||
## 依赖
|
||||
| 语法 | Word 效果 |
|
||||
| :--- | :--- |
|
||||
| `# 标题1` 到 `###### 标题6` | 标题级别 1-6 |
|
||||
| `**粗体**` 或 `__粗体__` | 粗体文本 |
|
||||
| `*斜体*` 或 `_斜体_` | 斜体文本 |
|
||||
| `` `行内代码` `` | 等宽字体 + 灰色背景 |
|
||||
| ` ``` 代码块 ``` ` | **语法高亮**的代码块 |
|
||||
| `> 引用文本` | 带左侧边框的灰色斜体文本 |
|
||||
| `[链接](url)` | 蓝色下划线链接文本 |
|
||||
| `~~删除线~~` | 删除线文本 |
|
||||
| `- 项目` 或 `* 项目` | 无序列表 |
|
||||
| `1. 项目` | 有序列表 |
|
||||
| Markdown 表格 | **增强表格**(智能列宽)|
|
||||
| `$$LaTeX$$` 或 `\[LaTeX\]` | **原生 Word 公式**(块级)|
|
||||
| `$LaTeX$` 或 `\(LaTeX\)` | **原生 Word 公式**(行内)|
|
||||
| ` ```mermaid ... ``` ` | **Mermaid 图表**(图片形式)|
|
||||
| `[1]` 引用标记 | **可点击链接**到参考资料 |
|
||||
|
||||
## 📦 依赖
|
||||
|
||||
- `python-docx==1.1.2` - Word 文档生成
|
||||
- `Pygments>=2.15.0` - 语法高亮
|
||||
- `latex2mathml` - LaTeX 转 MathML
|
||||
- `mathml2omml` - MathML 转 Office Math (OMML)
|
||||
|
||||
所有依赖已在插件文档字符串中声明。
|
||||
## 📝 更新日志
|
||||
|
||||
## 字体配置
|
||||
### v0.4.3
|
||||
- **S3 对象存储**: 通过 boto3 直连 S3/MinIO,图片获取速度更快。
|
||||
- **6 级回退机制**: 稳健的文件获取:数据库 → S3 → 本地 → URL → API → 属性。
|
||||
- **日志优化**: 改进错误提示,便于调试文件访问问题。
|
||||
|
||||
- **英文文本**:Times New Roman
|
||||
- **中文文本**:宋体(正文)、黑体(标题)
|
||||
- **代码**:Consolas
|
||||
### v0.4.1
|
||||
- **中文参数名**: 配置项名称和描述全部汉化。
|
||||
|
||||
## 更新日志
|
||||
|
||||
### v0.2.0
|
||||
- 新增原生数学公式支持(LaTeX → OMML)
|
||||
- 新增 Mermaid 图表渲染
|
||||
- 新增引用与参考资料章节生成
|
||||
- 新增自动移除 AI 思考块
|
||||
- 增强表格格式(智能列宽、对齐)
|
||||
|
||||
### v0.1.1
|
||||
- 初始版本,支持基本 Markdown 转 Word
|
||||
|
||||
## 作者
|
||||
|
||||
Fu-Jie
|
||||
GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
## 许可证
|
||||
|
||||
MIT License
|
||||
### v0.4.0
|
||||
- **多语言支持**: 界面语言切换(中文/英文)。
|
||||
- **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**: 混合 SVG+PNG 渲染,支持背景色配置。
|
||||
- **性能优化**: 导出大型文档时提供实时进度反馈。
|
||||
|
||||
BIN
plugins/actions/export_to_docx/export_to_word.png
Normal file
|
After Width: | Height: | Size: 78 KiB |
BIN
plugins/actions/export_to_docx/export_to_word_cn.png
Normal file
|
After Width: | Height: | Size: 86 KiB |
@@ -4,6 +4,7 @@ author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 0.3.7
|
||||
openwebui_id: 244b8f9d-7459-47d6-84d3-c7ae8e3ec710
|
||||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxwYXRoIGQ9Ik0xNSAySDZhMiAyIDAgMCAwLTIgMnYxNmEyIDIgMCAwIDAgMiAyaDEyYTIgMiAwIDAgMCAyLTJWN1oiLz48cGF0aCBkPSJNMTQgMnY0YTIgMiAwIDAgMCAyIDJoNCIvPjxwYXRoIGQ9Ik04IDEzaDIiLz48cGF0aCBkPSJNMTQgMTNoMiIvPjxwYXRoIGQ9Ik04IDE3aDIiLz48cGF0aCBkPSJNMTQgMTdoMiIvPjwvc3ZnPg==
|
||||
description: Extracts tables from chat messages and exports them to Excel (.xlsx) files with smart formatting.
|
||||
"""
|
||||
|
||||
@@ -4,6 +4,7 @@ author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 0.2.4
|
||||
openwebui_id: 65a2ea8f-2a13-4587-9d76-55eea0035cc8
|
||||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxwb2x5Z29uIHBvaW50cz0iMTIgMiAyIDcgMTIgMTIgMjIgNyAxMiAyIi8+PHBvbHlsaW5lIHBvaW50cz0iMiAxNyAxMiAyMiAyMiAxNyIvPjxwb2x5bGluZSBwb2ludHM9IjIgMTIgMTIgMTcgMjIgMTIiLz48L3N2Zz4=
|
||||
description: Quickly generates beautiful flashcards from text, extracting key points and categories.
|
||||
"""
|
||||
|
||||
@@ -4,6 +4,7 @@ author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 0.2.4
|
||||
openwebui_id: 4a31eac3-a3c4-4c30-9ca5-dab36b5fac65
|
||||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxwb2x5Z29uIHBvaW50cz0iMTIgMiAyIDcgMTIgMTIgMjIgNyAxMiAyIi8+PHBvbHlsaW5lIHBvaW50cz0iMiAxNyAxMiAyMiAyMiAxNyIvPjxwb2x5bGluZSBwb2ludHM9IjIgMTIgMTIgMTcgMjIgMTIiLz48L3N2Zz4=
|
||||
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。
|
||||
"""
|
||||
|
||||
@@ -1,7 +1,19 @@
|
||||
# 📊 Smart Infographic (AntV)
|
||||
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 1.4.1 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
An Open WebUI plugin powered by the AntV Infographic engine. It transforms long text into professional, beautiful infographics with a single click.
|
||||
|
||||
## 🔥 What's New in v1.4.1
|
||||
|
||||
- ✨ **PNG Upload**: Infographics now upload as PNG format for better Word export compatibility.
|
||||
- 🔧 **Canvas Conversion**: Uses browser canvas for high-quality SVG to PNG conversion (2x scale).
|
||||
|
||||
### Previous: v1.4.0
|
||||
|
||||
- ✨ **Default Mode Change**: Default output mode is now `image` (static image) for better compatibility.
|
||||
- 📱 **Responsive Sizing**: Images now auto-adapt to the chat container width.
|
||||
|
||||
## ✨ Key Features
|
||||
|
||||
- 🚀 **AI-Powered Transformation**: Automatically analyzes text logic, extracts key points, and generates structured charts.
|
||||
@@ -11,15 +23,6 @@ An Open WebUI plugin powered by the AntV Infographic engine. It transforms long
|
||||
- 🌈 **Highly Customizable**: Supports Dark/Light modes, auto-adapts theme colors, with bold titles and refined card layouts.
|
||||
- 📱 **Responsive Design**: Generated charts look great on both desktop and mobile devices.
|
||||
|
||||
## 🛠️ Supported Template Types
|
||||
|
||||
| Category | Template Name | Use Case |
|
||||
| :--- | :--- | :--- |
|
||||
| **Lists & Hierarchy** | `list-grid`, `tree-vertical`, `mindmap` | Features, Org Charts, Brainstorming |
|
||||
| **Sequence & Relation** | `sequence-roadmap`, `relation-circle` | Roadmaps, Circular Flows, Steps |
|
||||
| **Comparison & Analysis** | `compare-binary`, `compare-swot`, `quadrant-quarter` | Pros/Cons, SWOT, Quadrants |
|
||||
| **Charts & Data** | `chart-bar`, `chart-line`, `chart-pie` | Trends, Distributions, Metrics |
|
||||
|
||||
## 🚀 How to Use
|
||||
|
||||
1. **Install**: Search for "Smart Infographic" in the Open WebUI Community and install.
|
||||
@@ -38,6 +41,16 @@ You can adjust the following parameters in the plugin settings to optimize the g
|
||||
| **Min Text Length (MIN_TEXT_LENGTH)** | `100` | Minimum characters required to trigger analysis, preventing accidental triggers on short text. |
|
||||
| **Clear Previous (CLEAR_PREVIOUS_HTML)** | `False` | Whether to clear previous charts. If `False`, new charts will be appended below. |
|
||||
| **Message Count (MESSAGE_COUNT)** | `1` | Number of recent messages to use for analysis. Increase this for more context. |
|
||||
| **Output Mode (OUTPUT_MODE)** | `image` | `image` for static image embedding (default, better compatibility), `html` for interactive chart. |
|
||||
|
||||
## 🛠️ Supported Template Types
|
||||
|
||||
| Category | Template Name | Use Case |
|
||||
| :--- | :--- | :--- |
|
||||
| **Lists & Hierarchy** | `list-grid`, `tree-vertical`, `mindmap` | Features, Org Charts, Brainstorming |
|
||||
| **Sequence & Relation** | `sequence-roadmap`, `relation-circle` | Roadmaps, Circular Flows, Steps |
|
||||
| **Comparison & Analysis** | `compare-binary`, `compare-swot`, `quadrant-quarter` | Pros/Cons, SWOT, Quadrants |
|
||||
| **Charts & Data** | `chart-bar`, `chart-line`, `chart-pie` | Trends, Distributions, Metrics |
|
||||
|
||||
## 📝 Syntax Example (For Advanced Users)
|
||||
|
||||
@@ -54,18 +67,3 @@ data
|
||||
- label Beautiful Design
|
||||
desc Uses AntV professional design standards
|
||||
```
|
||||
|
||||
## 👨💻 Author
|
||||
|
||||
**jeff**
|
||||
- GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
## 📄 License
|
||||
|
||||
MIT License
|
||||
|
||||
## Changelog
|
||||
|
||||
### v1.3.2
|
||||
|
||||
- Removed debug messages from output
|
||||
|
||||
@@ -1,7 +1,19 @@
|
||||
# 📊 智能信息图 (AntV Infographic)
|
||||
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 1.4.1 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
基于 AntV Infographic 引擎的 Open WebUI 插件,能够将长文本内容一键转换为专业、美观的信息图表。
|
||||
|
||||
## 🔥 v1.4.1 更新日志
|
||||
|
||||
- ✨ **PNG 上传**:信息图现在以 PNG 格式上传,与 Word 导出完美兼容。
|
||||
- 🔧 **Canvas 转换**:使用浏览器 Canvas 高质量转换 SVG 为 PNG(2倍缩放)。
|
||||
|
||||
### 此前: v1.4.0
|
||||
|
||||
- ✨ **默认模式变更**:默认输出模式调整为 `image`(静态图片)。
|
||||
- 📱 **响应式尺寸**:图片模式下自动适应聊天容器宽度。
|
||||
|
||||
## ✨ 核心特性
|
||||
|
||||
- 🚀 **智能转换**:自动分析文本核心逻辑,提取关键点并生成结构化图表。
|
||||
@@ -11,15 +23,6 @@
|
||||
- 🌈 **高度自定义**:支持深色/浅色模式,自动适配主题颜色,主标题加粗突出,卡片布局精美。
|
||||
- 📱 **响应式设计**:生成的图表在桌面端和移动端均有良好的展示效果。
|
||||
|
||||
## 🛠️ 支持的模板类型
|
||||
|
||||
| 分类 | 模板名称 | 适用场景 |
|
||||
| :--- | :--- | :--- |
|
||||
| **列表与层级** | `list-grid`, `tree-vertical`, `mindmap` | 功能亮点、组织架构、思维导图 |
|
||||
| **顺序与关系** | `sequence-roadmap`, `relation-circle` | 发展历程、循环关系、步骤说明 |
|
||||
| **对比与分析** | `compare-binary`, `compare-swot`, `quadrant-quarter` | 优劣势对比、SWOT 分析、象限图 |
|
||||
| **图表与数据** | `chart-bar`, `chart-line`, `chart-pie` | 数据趋势、比例分布、数值对比 |
|
||||
|
||||
## 🚀 使用方法
|
||||
|
||||
1. **安装插件**:在 Open WebUI 插件市场搜索并安装。
|
||||
@@ -38,6 +41,16 @@
|
||||
| **最小文本长度 (MIN_TEXT_LENGTH)** | `100` | 触发分析所需的最小字符数,防止对过短的对话误操作。 |
|
||||
| **清除旧结果 (CLEAR_PREVIOUS_HTML)** | `False` | 每次生成是否清除之前的图表。若为 `False`,新图表将追加在下方。 |
|
||||
| **上下文消息数 (MESSAGE_COUNT)** | `1` | 用于分析的最近消息条数。增加此值可让 AI 参考更多对话背景。 |
|
||||
| **输出模式 (OUTPUT_MODE)** | `image` | `image` 为静态图片嵌入(默认,兼容性好),`html` 为交互式图表。 |
|
||||
|
||||
## 🛠️ 支持的模板类型
|
||||
|
||||
| 分类 | 模板名称 | 适用场景 |
|
||||
| :--- | :--- | :--- |
|
||||
| **列表与层级** | `list-grid`, `tree-vertical`, `mindmap` | 功能亮点、组织架构、思维导图 |
|
||||
| **顺序与关系** | `sequence-roadmap`, `relation-circle` | 发展历程、循环关系、步骤说明 |
|
||||
| **对比与分析** | `compare-binary`, `compare-swot`, `quadrant-quarter` | 优劣势对比、SWOT 分析、象限图 |
|
||||
| **图表与数据** | `chart-bar`, `chart-line`, `chart-pie` | 数据趋势、比例分布、数值对比 |
|
||||
|
||||
## 📝 语法示例 (高级用户)
|
||||
|
||||
@@ -54,18 +67,3 @@ data
|
||||
- label 视觉精美
|
||||
desc 采用 AntV 专业设计规范
|
||||
```
|
||||
|
||||
## 👨💻 作者
|
||||
|
||||
**jeff**
|
||||
- GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
## 📄 许可证
|
||||
|
||||
MIT License
|
||||
|
||||
## 更新日志
|
||||
|
||||
### v1.3.2
|
||||
|
||||
- 移除输出中的调试信息
|
||||
|
||||
BIN
plugins/actions/infographic/infographic.png
Normal file
|
After Width: | Height: | Size: 162 KiB |
@@ -3,12 +3,13 @@ title: 📊 Smart Infographic (AntV)
|
||||
author: jeff
|
||||
author_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPgogIDxsaW5lIHgxPSIxMiIgeTE9IjIwIiB4Mj0iMTIiIHkyPSIxMCIgLz4KICA8bGluZSB4MT0iMTgiIHkxPSIyMCIgeDI9IjE4IiB5Mj0iNCIgLz4KICA8bGluZSB4MT0iNiIgeTE9IjIwIiB4Mj0iNiIgeTI9IjE2IiAvPgo8L3N2Zz4=
|
||||
version: 1.3.2
|
||||
version: 1.4.1
|
||||
openwebui_id: ad6f0c7f-c571-4dea-821d-8e71697274cf
|
||||
description: AI-powered infographic generator based on AntV Infographic. Supports professional templates, auto-icon matching, and SVG/PNG downloads.
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Optional, Dict, Any
|
||||
from typing import Optional, Dict, Any, Callable, Awaitable
|
||||
import logging
|
||||
import time
|
||||
import re
|
||||
@@ -821,10 +822,54 @@ 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="image",
|
||||
description="Output mode: 'html' for interactive HTML, or 'image' to embed as Markdown image (default).",
|
||||
)
|
||||
|
||||
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)
|
||||
@@ -912,14 +957,359 @@ class Action:
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _generate_image_js_code(
|
||||
self,
|
||||
unique_id: str,
|
||||
chat_id: str,
|
||||
message_id: str,
|
||||
infographic_syntax: str,
|
||||
) -> str:
|
||||
"""Generate JavaScript code for frontend SVG rendering and image embedding"""
|
||||
|
||||
# Escape the syntax for JS embedding
|
||||
syntax_escaped = (
|
||||
infographic_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 = 1100;
|
||||
const defaultHeight = 500;
|
||||
|
||||
// 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 padding (80% of container, leaving more space on the right)
|
||||
svgWidth = Math.floor(containerWidth * 0.8);
|
||||
// Maintain aspect ratio based on default dimensions
|
||||
svgHeight = Math.floor(svgWidth * (defaultHeight / defaultWidth));
|
||||
console.log("[Infographic Image] Auto-detected container width:", containerWidth, "-> SVG:", svgWidth, "x", svgHeight);
|
||||
}}
|
||||
}}
|
||||
|
||||
console.log("[Infographic Image] Starting render...");
|
||||
console.log("[Infographic Image] chatId:", chatId, "messageId:", messageId);
|
||||
|
||||
try {{
|
||||
// Load AntV Infographic if not loaded
|
||||
if (typeof AntVInfographic === 'undefined') {{
|
||||
console.log("[Infographic Image] Loading AntV Infographic...");
|
||||
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);
|
||||
}});
|
||||
}}
|
||||
|
||||
const {{ Infographic }} = AntVInfographic;
|
||||
|
||||
// Get syntax content
|
||||
let syntaxContent = `{syntax_escaped}`;
|
||||
console.log("[Infographic Image] Syntax length:", syntaxContent.length);
|
||||
|
||||
// Clean up syntax: remove code block markers
|
||||
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 syntax: remove colons after keywords
|
||||
syntaxContent = syntaxContent.replace(/^(data|items|children|theme|config):/gm, '$1');
|
||||
syntaxContent = syntaxContent.replace(/(\\s)(children|items):/g, '$1$2');
|
||||
|
||||
// Ensure infographic prefix
|
||||
if (!syntaxContent.trim().toLowerCase().startsWith('infographic')) {{
|
||||
const firstWord = syntaxContent.trim().split(/\\s+/)[0].toLowerCase();
|
||||
if (!['data', 'theme', 'design', 'items'].includes(firstWord)) {{
|
||||
syntaxContent = 'infographic ' + syntaxContent;
|
||||
}}
|
||||
}}
|
||||
|
||||
// Template mapping
|
||||
const TEMPLATE_MAPPING = {{
|
||||
'list-grid': 'list-grid-compact-card',
|
||||
'list-vertical': 'list-column-simple-vertical-arrow',
|
||||
'tree-vertical': 'hierarchy-tree-tech-style-capsule-item',
|
||||
'tree-horizontal': 'hierarchy-tree-lr-tech-style-capsule-item',
|
||||
'mindmap': 'hierarchy-mindmap-branch-gradient-capsule-item',
|
||||
'sequence-roadmap': 'sequence-roadmap-vertical-simple',
|
||||
'sequence-zigzag': 'sequence-horizontal-zigzag-simple',
|
||||
'sequence-horizontal': 'sequence-horizontal-zigzag-simple',
|
||||
'relation-sankey': 'relation-sankey-simple',
|
||||
'relation-circle': 'relation-circle-icon-badge',
|
||||
'compare-binary': 'compare-binary-horizontal-simple-vs',
|
||||
'compare-swot': 'compare-swot',
|
||||
'quadrant-quarter': 'quadrant-quarter-simple-card',
|
||||
'statistic-card': 'list-grid-compact-card',
|
||||
'chart-bar': 'chart-bar-plain-text',
|
||||
'chart-column': 'chart-column-simple',
|
||||
'chart-line': 'chart-line-plain-text',
|
||||
'chart-area': 'chart-area-simple',
|
||||
'chart-pie': 'chart-pie-plain-text',
|
||||
'chart-doughnut': 'chart-pie-donut-plain-text'
|
||||
}};
|
||||
|
||||
for (const [key, value] of Object.entries(TEMPLATE_MAPPING)) {{
|
||||
const regex = new RegExp(`infographic\\\\s+${{key}}(?=\\\\s|$)`, 'i');
|
||||
if (regex.test(syntaxContent)) {{
|
||||
syntaxContent = syntaxContent.replace(regex, `infographic ${{value}}`);
|
||||
break;
|
||||
}}
|
||||
}}
|
||||
|
||||
// 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;height:' + svgHeight + 'px;background:#ffffff;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// Create infographic instance
|
||||
const instance = new Infographic({{
|
||||
container: '#' + container.id,
|
||||
width: svgWidth,
|
||||
height: svgHeight,
|
||||
padding: 12,
|
||||
}});
|
||||
|
||||
console.log("[Infographic Image] Rendering infographic...");
|
||||
instance.render(syntaxContent);
|
||||
|
||||
// Wait for render to complete
|
||||
await new Promise(resolve => setTimeout(resolve, 2000));
|
||||
|
||||
// Get SVG element
|
||||
const svgEl = container.querySelector('svg');
|
||||
if (!svgEl) {{
|
||||
throw new Error('SVG element not found after rendering');
|
||||
}}
|
||||
|
||||
// Get actual dimensions
|
||||
const bbox = svgEl.getBoundingClientRect();
|
||||
const width = bbox.width || svgWidth;
|
||||
const height = bbox.height || svgHeight;
|
||||
|
||||
// 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');
|
||||
clonedSvg.setAttribute('width', width);
|
||||
clonedSvg.setAttribute('height', height);
|
||||
|
||||
// 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);
|
||||
|
||||
// Serialize SVG to string
|
||||
const svgData = new XMLSerializer().serializeToString(clonedSvg);
|
||||
|
||||
// Cleanup container
|
||||
document.body.removeChild(container);
|
||||
|
||||
// Convert SVG to PNG using canvas for better compatibility
|
||||
console.log("[Infographic Image] Converting SVG to PNG...");
|
||||
const pngBlob = await new Promise((resolve, reject) => {{
|
||||
const canvas = document.createElement('canvas');
|
||||
const ctx = canvas.getContext('2d');
|
||||
const scale = 2; // Higher resolution for clarity
|
||||
canvas.width = Math.round(width * scale);
|
||||
canvas.height = Math.round(height * scale);
|
||||
|
||||
// Fill white background
|
||||
ctx.fillStyle = '#ffffff';
|
||||
ctx.fillRect(0, 0, canvas.width, canvas.height);
|
||||
ctx.scale(scale, scale);
|
||||
|
||||
const img = new Image();
|
||||
img.onload = () => {{
|
||||
ctx.drawImage(img, 0, 0, width, height);
|
||||
canvas.toBlob((blob) => {{
|
||||
if (blob) {{
|
||||
resolve(blob);
|
||||
}} else {{
|
||||
reject(new Error('Canvas toBlob failed'));
|
||||
}}
|
||||
}}, 'image/png');
|
||||
}};
|
||||
img.onerror = (e) => reject(new Error('Failed to load SVG as image: ' + e));
|
||||
img.src = 'data:image/svg+xml;base64,' + btoa(unescape(encodeURIComponent(svgData)));
|
||||
}});
|
||||
|
||||
const file = new File([pngBlob], `infographic-${{uniqueId}}.png`, {{ type: 'image/png' }});
|
||||
|
||||
// Upload file to OpenWebUI API
|
||||
console.log("[Infographic Image] Uploading PNG file...");
|
||||
const token = localStorage.getItem("token");
|
||||
const formData = new FormData();
|
||||
formData.append('file', file);
|
||||
|
||||
const uploadResponse = await fetch('/api/v1/files/', {{
|
||||
method: 'POST',
|
||||
headers: {{
|
||||
'Authorization': `Bearer ${{token}}`
|
||||
}},
|
||||
body: formData
|
||||
}});
|
||||
|
||||
if (!uploadResponse.ok) {{
|
||||
throw new Error(`Upload failed: ${{uploadResponse.statusText}}`);
|
||||
}}
|
||||
|
||||
const fileData = await uploadResponse.json();
|
||||
const fileId = fileData.id;
|
||||
const imageUrl = `/api/v1/files/${{fileId}}/content`;
|
||||
|
||||
console.log("[Infographic Image] PNG file uploaded, ID:", fileId);
|
||||
|
||||
// Generate markdown image with file URL
|
||||
const markdownImage = ``;
|
||||
|
||||
// Update message via API
|
||||
if (chatId && messageId) {{
|
||||
|
||||
// Helper function with retry logic
|
||||
const fetchWithRetry = async (url, options, retries = 3) => {{
|
||||
for (let i = 0; i < retries; i++) {{
|
||||
try {{
|
||||
const response = await fetch(url, options);
|
||||
if (response.ok) return response;
|
||||
if (i < retries - 1) {{
|
||||
console.log(`[Infographic Image] Retry ${{i + 1}}/${{retries}} for ${{url}}`);
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}}
|
||||
}} catch (e) {{
|
||||
if (i === retries - 1) throw e;
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}}
|
||||
}}
|
||||
return null;
|
||||
}};
|
||||
|
||||
// Get current chat data
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("Failed to get chat data: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
let updatedMessages = [];
|
||||
let newContent = "";
|
||||
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
updatedMessages = chatData.chat.messages.map(m => {{
|
||||
if (m.id === messageId) {{
|
||||
const originalContent = m.content || "";
|
||||
// Remove existing infographic images
|
||||
const infographicPattern = /\\n*!\\[📊[^\\]]*\\]\\((?:data:image\\/[^)]+|(?:\\/api\\/v1\\/files\\/[^)]+))\\)/g;
|
||||
let cleanedContent = originalContent.replace(infographicPattern, "");
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
// Append new image
|
||||
newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// Update history object as well
|
||||
if (chatData.chat.history && chatData.chat.history.messages) {{
|
||||
if (chatData.chat.history.messages[messageId]) {{
|
||||
chatData.chat.history.messages[messageId].content = newContent;
|
||||
}}
|
||||
}}
|
||||
|
||||
return {{ ...m, content: newContent }};
|
||||
}}
|
||||
return m;
|
||||
}});
|
||||
}}
|
||||
|
||||
if (!newContent) {{
|
||||
console.warn("[Infographic Image] Could not find message to update");
|
||||
return;
|
||||
}}
|
||||
|
||||
// Try to update frontend display via event API
|
||||
try {{
|
||||
await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: newContent }}
|
||||
}})
|
||||
}});
|
||||
}} catch (eventErr) {{
|
||||
console.log("[Infographic Image] Event API not available, continuing...");
|
||||
}}
|
||||
|
||||
// Persist to database
|
||||
const updatePayload = {{
|
||||
chat: {{
|
||||
...chatData.chat,
|
||||
messages: updatedMessages
|
||||
}}
|
||||
}};
|
||||
|
||||
const persistResponse = await fetchWithRetry(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify(updatePayload)
|
||||
}});
|
||||
|
||||
if (persistResponse && persistResponse.ok) {{
|
||||
console.log("[Infographic Image] ✅ Message persisted successfully!");
|
||||
}} else {{
|
||||
console.error("[Infographic Image] ❌ Failed to persist message after retries");
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[Infographic Image] ⚠️ Missing chatId or messageId, cannot persist");
|
||||
}}
|
||||
|
||||
}} catch (error) {{
|
||||
console.error("[Infographic 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: Infographic started (v1.0.0)")
|
||||
logger.info("Action: Infographic started (v1.4.0)")
|
||||
|
||||
# Get user information
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
@@ -1114,6 +1504,45 @@ 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, body.get("metadata"))
|
||||
message_id = self._extract_message_id(body, body.get("metadata"))
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"📊 Infographic: 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,
|
||||
infographic_syntax=infographic_syntax,
|
||||
)
|
||||
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "✅ Infographic: Image generated!", True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"📊 Infographic image generated, {user_name}!",
|
||||
"success",
|
||||
)
|
||||
logger.info("Infographic generation 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"{original_content}\n\n{html_embed_tag}"
|
||||
|
||||
|
||||
BIN
plugins/actions/infographic/infographic_cn.png
Normal file
|
After Width: | Height: | Size: 169 KiB |
@@ -3,12 +3,13 @@ title: 📊 智能信息图 (AntV Infographic)
|
||||
author: jeff
|
||||
author_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPgogIDxsaW5lIHgxPSIxMiIgeTE9IjIwIiB4Mj0iMTIiIHkyPSIxMCIgLz4KICA8bGluZSB4MT0iMTgiIHkxPSIyMCIgeDI9IjE4IiB5Mj0iNCIgLz4KICA8bGluZSB4MT0iNiIgeTE9IjIwIiB4Mj0iNiIgeTI9IjE2IiAvPgo8L3N2Zz4=
|
||||
version: 1.3.2
|
||||
version: 1.4.1
|
||||
openwebui_id: e04a48ff-23ee-4a41-8ea7-66c19524e7c8
|
||||
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。
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Optional, Dict, Any
|
||||
from typing import Optional, Dict, Any, Callable, Awaitable
|
||||
import logging
|
||||
import time
|
||||
import re
|
||||
@@ -849,6 +850,10 @@ class Action:
|
||||
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。",
|
||||
)
|
||||
OUTPUT_MODE: str = Field(
|
||||
default="image",
|
||||
description="输出模式:'html' 为交互式HTML,'image' 将嵌入为Markdown图片(默认)。",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
@@ -862,6 +867,46 @@ class Action:
|
||||
"Sunday": "星期日",
|
||||
}
|
||||
|
||||
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:
|
||||
"""提取LLM输出中的infographic语法"""
|
||||
# 1. 优先匹配 ```infographic
|
||||
@@ -973,14 +1018,359 @@ class Action:
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _generate_image_js_code(
|
||||
self,
|
||||
unique_id: str,
|
||||
chat_id: str,
|
||||
message_id: str,
|
||||
infographic_syntax: str,
|
||||
) -> str:
|
||||
"""生成前端 SVG 渲染和图片嵌入的 JavaScript 代码"""
|
||||
|
||||
# 转义语法以便在 JS 中嵌入
|
||||
syntax_escaped = (
|
||||
infographic_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 = 1100;
|
||||
const defaultHeight = 500;
|
||||
|
||||
// 自动检测聊天容器宽度以实现响应式尺寸
|
||||
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 80%(右边留更多空间)
|
||||
svgWidth = Math.floor(containerWidth * 0.8);
|
||||
// 根据默认尺寸保持宽高比
|
||||
svgHeight = Math.floor(svgWidth * (defaultHeight / defaultWidth));
|
||||
console.log("[Infographic Image] 自动检测容器宽度:", containerWidth, "-> SVG:", svgWidth, "x", svgHeight);
|
||||
}}
|
||||
}}
|
||||
|
||||
console.log("[Infographic Image] 开始渲染...");
|
||||
console.log("[Infographic Image] chatId:", chatId, "messageId:", messageId);
|
||||
|
||||
try {{
|
||||
// 加载 AntV Infographic(如果未加载)
|
||||
if (typeof AntVInfographic === 'undefined') {{
|
||||
console.log("[Infographic Image] 加载 AntV Infographic...");
|
||||
await new Promise((resolve, reject) => {{
|
||||
const script = document.createElement('script');
|
||||
script.src = 'https://registry.npmmirror.com/@antv/infographic/0.2.1/files/dist/infographic.min.js';
|
||||
script.onload = resolve;
|
||||
script.onerror = reject;
|
||||
document.head.appendChild(script);
|
||||
}});
|
||||
}}
|
||||
|
||||
const {{ Infographic }} = AntVInfographic;
|
||||
|
||||
// 获取语法内容
|
||||
let syntaxContent = `{syntax_escaped}`;
|
||||
console.log("[Infographic Image] 语法长度:", syntaxContent.length);
|
||||
|
||||
// 清理语法:移除代码块标记
|
||||
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();
|
||||
}}
|
||||
|
||||
// 修复语法:移除关键字后的冒号
|
||||
syntaxContent = syntaxContent.replace(/^(data|items|children|theme|config):/gm, '$1');
|
||||
syntaxContent = syntaxContent.replace(/(\\s)(children|items):/g, '$1$2');
|
||||
|
||||
// 确保 infographic 前缀
|
||||
if (!syntaxContent.trim().toLowerCase().startsWith('infographic')) {{
|
||||
const firstWord = syntaxContent.trim().split(/\\s+/)[0].toLowerCase();
|
||||
if (!['data', 'theme', 'design', 'items'].includes(firstWord)) {{
|
||||
syntaxContent = 'infographic ' + syntaxContent;
|
||||
}}
|
||||
}}
|
||||
|
||||
// 模板映射
|
||||
const TEMPLATE_MAPPING = {{
|
||||
'list-grid': 'list-grid-compact-card',
|
||||
'list-vertical': 'list-column-simple-vertical-arrow',
|
||||
'tree-vertical': 'hierarchy-tree-tech-style-capsule-item',
|
||||
'tree-horizontal': 'hierarchy-tree-lr-tech-style-capsule-item',
|
||||
'mindmap': 'hierarchy-mindmap-branch-gradient-capsule-item',
|
||||
'sequence-roadmap': 'sequence-roadmap-vertical-simple',
|
||||
'sequence-zigzag': 'sequence-horizontal-zigzag-simple',
|
||||
'sequence-horizontal': 'sequence-horizontal-zigzag-simple',
|
||||
'relation-sankey': 'relation-sankey-simple',
|
||||
'relation-circle': 'relation-circle-icon-badge',
|
||||
'compare-binary': 'compare-binary-horizontal-simple-vs',
|
||||
'compare-swot': 'compare-swot',
|
||||
'quadrant-quarter': 'quadrant-quarter-simple-card',
|
||||
'statistic-card': 'list-grid-compact-card',
|
||||
'chart-bar': 'chart-bar-plain-text',
|
||||
'chart-column': 'chart-column-simple',
|
||||
'chart-line': 'chart-line-plain-text',
|
||||
'chart-area': 'chart-area-simple',
|
||||
'chart-pie': 'chart-pie-plain-text',
|
||||
'chart-doughnut': 'chart-pie-donut-plain-text'
|
||||
}};
|
||||
|
||||
for (const [key, value] of Object.entries(TEMPLATE_MAPPING)) {{
|
||||
const regex = new RegExp(`infographic\\\\s+${{key}}(?=\\\\s|$)`, 'i');
|
||||
if (regex.test(syntaxContent)) {{
|
||||
syntaxContent = syntaxContent.replace(regex, `infographic ${{value}}`);
|
||||
break;
|
||||
}}
|
||||
}}
|
||||
|
||||
// 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;height:' + svgHeight + 'px;background:#ffffff;';
|
||||
document.body.appendChild(container);
|
||||
|
||||
// 创建信息图实例
|
||||
const instance = new Infographic({{
|
||||
container: '#' + container.id,
|
||||
width: svgWidth,
|
||||
height: svgHeight,
|
||||
padding: 12,
|
||||
}});
|
||||
|
||||
console.log("[Infographic Image] 渲染信息图...");
|
||||
instance.render(syntaxContent);
|
||||
|
||||
// 等待渲染完成
|
||||
await new Promise(resolve => setTimeout(resolve, 2000));
|
||||
|
||||
// 获取 SVG 元素
|
||||
const svgEl = container.querySelector('svg');
|
||||
if (!svgEl) {{
|
||||
throw new Error('渲染后未找到 SVG 元素');
|
||||
}}
|
||||
|
||||
// 获取实际尺寸
|
||||
const bbox = svgEl.getBoundingClientRect();
|
||||
const width = bbox.width || svgWidth;
|
||||
const height = bbox.height || svgHeight;
|
||||
|
||||
// 克隆并准备导出的 SVG
|
||||
const clonedSvg = svgEl.cloneNode(true);
|
||||
clonedSvg.setAttribute('xmlns', 'http://www.w3.org/2000/svg');
|
||||
clonedSvg.setAttribute('xmlns:xlink', 'http://www.w3.org/1999/xlink');
|
||||
clonedSvg.setAttribute('width', width);
|
||||
clonedSvg.setAttribute('height', height);
|
||||
|
||||
// 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);
|
||||
|
||||
// 序列化 SVG 为字符串
|
||||
const svgData = new XMLSerializer().serializeToString(clonedSvg);
|
||||
|
||||
// 清理容器
|
||||
document.body.removeChild(container);
|
||||
|
||||
// 使用 canvas 将 SVG 转换为 PNG 以提高兼容性
|
||||
console.log("[Infographic Image] 正在将 SVG 转换为 PNG...");
|
||||
const pngBlob = await new Promise((resolve, reject) => {{
|
||||
const canvas = document.createElement('canvas');
|
||||
const ctx = canvas.getContext('2d');
|
||||
const scale = 2; // 更高分辨率以提高清晰度
|
||||
canvas.width = Math.round(width * scale);
|
||||
canvas.height = Math.round(height * scale);
|
||||
|
||||
// 填充白色背景
|
||||
ctx.fillStyle = '#ffffff';
|
||||
ctx.fillRect(0, 0, canvas.width, canvas.height);
|
||||
ctx.scale(scale, scale);
|
||||
|
||||
const img = new Image();
|
||||
img.onload = () => {{
|
||||
ctx.drawImage(img, 0, 0, width, height);
|
||||
canvas.toBlob((blob) => {{
|
||||
if (blob) {{
|
||||
resolve(blob);
|
||||
}} else {{
|
||||
reject(new Error('Canvas toBlob 失败'));
|
||||
}}
|
||||
}}, 'image/png');
|
||||
}};
|
||||
img.onerror = (e) => reject(new Error('加载 SVG 图片失败: ' + e));
|
||||
img.src = 'data:image/svg+xml;base64,' + btoa(unescape(encodeURIComponent(svgData)));
|
||||
}});
|
||||
|
||||
const file = new File([pngBlob], `infographic-${{uniqueId}}.png`, {{ type: 'image/png' }});
|
||||
|
||||
// 上传文件到 OpenWebUI API
|
||||
console.log("[Infographic Image] 上传 PNG 文件...");
|
||||
const token = localStorage.getItem("token");
|
||||
const formData = new FormData();
|
||||
formData.append('file', file);
|
||||
|
||||
const uploadResponse = await fetch('/api/v1/files/', {{
|
||||
method: 'POST',
|
||||
headers: {{
|
||||
'Authorization': `Bearer ${{token}}`
|
||||
}},
|
||||
body: formData
|
||||
}});
|
||||
|
||||
if (!uploadResponse.ok) {{
|
||||
throw new Error(`上传失败: ${{uploadResponse.statusText}}`);
|
||||
}}
|
||||
|
||||
const fileData = await uploadResponse.json();
|
||||
const fileId = fileData.id;
|
||||
const imageUrl = `/api/v1/files/${{fileId}}/content`;
|
||||
|
||||
console.log("[Infographic Image] PNG 文件已上传, ID:", fileId);
|
||||
|
||||
// 生成带文件 URL 的 markdown 图片
|
||||
const markdownImage = ``;
|
||||
|
||||
// 通过 API 更新消息
|
||||
if (chatId && messageId) {{
|
||||
|
||||
// 带重试逻辑的辅助函数
|
||||
const fetchWithRetry = async (url, options, retries = 3) => {{
|
||||
for (let i = 0; i < retries; i++) {{
|
||||
try {{
|
||||
const response = await fetch(url, options);
|
||||
if (response.ok) return response;
|
||||
if (i < retries - 1) {{
|
||||
console.log(`[Infographic Image] 重试 ${{i + 1}}/${{retries}} for ${{url}}`);
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}}
|
||||
}} catch (e) {{
|
||||
if (i === retries - 1) throw e;
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}}
|
||||
}}
|
||||
return null;
|
||||
}};
|
||||
|
||||
// 获取当前聊天数据
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("获取聊天数据失败: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
let updatedMessages = [];
|
||||
let newContent = "";
|
||||
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
updatedMessages = chatData.chat.messages.map(m => {{
|
||||
if (m.id === messageId) {{
|
||||
const originalContent = m.content || "";
|
||||
// 移除已有的信息图图片
|
||||
const infographicPattern = /\\n*!\\[📊[^\\]]*\\]\\((?:data:image\\/[^)]+|(?:\\/api\\/v1\\/files\\/[^)]+))\\)/g;
|
||||
let cleanedContent = originalContent.replace(infographicPattern, "");
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
// 追加新图片
|
||||
newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// 同时更新 history 对象
|
||||
if (chatData.chat.history && chatData.chat.history.messages) {{
|
||||
if (chatData.chat.history.messages[messageId]) {{
|
||||
chatData.chat.history.messages[messageId].content = newContent;
|
||||
}}
|
||||
}}
|
||||
|
||||
return {{ ...m, content: newContent }};
|
||||
}}
|
||||
return m;
|
||||
}});
|
||||
}}
|
||||
|
||||
if (!newContent) {{
|
||||
console.warn("[Infographic Image] 找不到要更新的消息");
|
||||
return;
|
||||
}}
|
||||
|
||||
// 尝试通过事件 API 更新前端显示
|
||||
try {{
|
||||
await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: newContent }}
|
||||
}})
|
||||
}});
|
||||
}} catch (eventErr) {{
|
||||
console.log("[Infographic Image] 事件 API 不可用,继续...");
|
||||
}}
|
||||
|
||||
// 持久化到数据库
|
||||
const updatePayload = {{
|
||||
chat: {{
|
||||
...chatData.chat,
|
||||
messages: updatedMessages
|
||||
}}
|
||||
}};
|
||||
|
||||
const persistResponse = await fetchWithRetry(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify(updatePayload)
|
||||
}});
|
||||
|
||||
if (persistResponse && persistResponse.ok) {{
|
||||
console.log("[Infographic Image] ✅ 消息持久化成功!");
|
||||
}} else {{
|
||||
console.error("[Infographic Image] ❌ 重试后消息持久化失败");
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[Infographic Image] ⚠️ 缺少 chatId 或 messageId,无法持久化");
|
||||
}}
|
||||
|
||||
}} catch (error) {{
|
||||
console.error("[Infographic Image] 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: 信息图启动 (v1.0.0)")
|
||||
logger.info("Action: 信息图启动 (v1.4.0)")
|
||||
|
||||
# 获取用户信息
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
@@ -1169,6 +1559,45 @@ 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, body.get("metadata"))
|
||||
message_id = self._extract_message_id(body, body.get("metadata"))
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"📊 信息图: 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,
|
||||
infographic_syntax=infographic_syntax,
|
||||
)
|
||||
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "✅ 信息图: 图片生成完成!", True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"📊 信息图图片已生成,{user_name}!",
|
||||
"success",
|
||||
)
|
||||
logger.info("信息图生成完成(图片模式)")
|
||||
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"{original_content}\n\n{html_embed_tag}"
|
||||
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Smart Mind Map - Mind Mapping Generation Plugin
|
||||
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.8.2 | **License:** MIT
|
||||
**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.9.1 | **License:** MIT
|
||||
|
||||
> **Important**: To ensure the maintainability and usability of all plugins, each plugin should be accompanied by clear and comprehensive documentation to ensure its functionality, configuration, and usage are well explained.
|
||||
|
||||
@@ -8,6 +8,25 @@ Smart Mind Map is a powerful OpenWebUI action plugin that intelligently analyzes
|
||||
|
||||
---
|
||||
|
||||
## 🔥 What's New in v0.9.1
|
||||
|
||||
**New Feature: Image Output Mode**
|
||||
|
||||
- **Static Image Support**: Added `OUTPUT_MODE` configuration parameter.
|
||||
- `html` (default): Interactive HTML mind map.
|
||||
- `image`: Static SVG image embedded directly in Markdown (**No HTML code output**, cleaner chat history).
|
||||
- **Efficient Storage**: Image mode uploads SVG to `/api/v1/files`, avoiding huge base64 strings in chat history.
|
||||
- **Smart Features**: Auto-responsive width and automatic theme detection (light/dark) for generated images.
|
||||
|
||||
| Feature | HTML Mode (Default) | Image Mode |
|
||||
| :--- | :--- | :--- |
|
||||
| **Output Format** | Interactive HTML Block | Static Markdown Image |
|
||||
| **Interactivity** | Zoom, Pan, Expand/Collapse | None (Static Image) |
|
||||
| **Chat History** | Contains HTML Code | Clean (Image URL only) |
|
||||
| **Storage** | Browser Rendering | `/api/v1/files` Upload |
|
||||
|
||||
---
|
||||
|
||||
## Core Features
|
||||
|
||||
- ✅ **Intelligent Text Analysis**: Automatically identifies core themes, key concepts, and hierarchical structures
|
||||
@@ -20,6 +39,7 @@ Smart Mind Map is a powerful OpenWebUI action plugin that intelligently analyzes
|
||||
- ✅ **Real-time Rendering**: Renders mind maps directly in the chat interface without navigation
|
||||
- ✅ **Export Capabilities**: Supports PNG, SVG code, and Markdown source export
|
||||
- ✅ **Customizable Configuration**: Configurable LLM model, minimum text length, and other parameters
|
||||
- ✅ **Image Output Mode**: Generate static SVG images embedded directly in Markdown (**No HTML code output**, cleaner chat history)
|
||||
|
||||
---
|
||||
|
||||
@@ -80,6 +100,7 @@ You can adjust the following parameters in the plugin's settings (Valves):
|
||||
| `MIN_TEXT_LENGTH` | `100` | Minimum text length (in characters) required for mind map analysis. Text that's too short cannot generate valid mind maps. |
|
||||
| `CLEAR_PREVIOUS_HTML` | `false` | Whether to clear previous plugin-generated HTML content when generating a new mind map. |
|
||||
| `MESSAGE_COUNT` | `1` | Number of recent messages to use for mind map generation (1-5). |
|
||||
| `OUTPUT_MODE` | `html` | Output mode: `html` for interactive HTML (default), or `image` to embed as static Markdown image. |
|
||||
|
||||
---
|
||||
|
||||
@@ -277,6 +298,32 @@ This plugin uses only OpenWebUI's built-in dependencies. **No additional package
|
||||
|
||||
## Changelog
|
||||
|
||||
### v0.9.1
|
||||
|
||||
**New Feature: Image Output Mode**
|
||||
|
||||
- Added `OUTPUT_MODE` configuration parameter with two options:
|
||||
- `html` (default): Interactive HTML mind map with full control panel
|
||||
- `image`: Static SVG image embedded directly in Markdown (uploaded to `/api/v1/files`)
|
||||
- Image mode features:
|
||||
- Auto-responsive width (adapts to chat container)
|
||||
- Automatic theme detection (light/dark)
|
||||
- Persistent storage via Chat API (survives page refresh)
|
||||
- Efficient file storage (no huge base64 strings in chat history)
|
||||
|
||||
**Improvements:**
|
||||
|
||||
- Implemented robust Chat API update mechanism with retry logic
|
||||
- Fixed message persistence using both `messages[]` and `history.messages`
|
||||
- Added Event API for immediate frontend updates
|
||||
- Removed unnecessary `SVG_WIDTH` and `SVG_HEIGHT` parameters (now auto-calculated)
|
||||
|
||||
**Technical Details:**
|
||||
|
||||
- Image mode uses `__event_call__` to execute JavaScript in the browser
|
||||
- SVG is rendered offline, converted to Blob, and uploaded to OpenWebUI Files API
|
||||
- Updates chat message with `/api/v1/files/{id}/content` URL via OpenWebUI Backend-Controlled API flow
|
||||
|
||||
### v0.8.2
|
||||
|
||||
- Removed debug messages from output
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# 思维导图 - 思维导图生成插件
|
||||
|
||||
**作者:** [Fu-Jie](https://github.com/Fu-Jie) | **版本:** 0.8.2 | **许可证:** MIT
|
||||
**作者:** [Fu-Jie](https://github.com/Fu-Jie) | **版本:** 0.9.1 | **许可证:** MIT
|
||||
|
||||
> **重要提示**:为了确保所有插件的可维护性和易用性,每个插件都应附带清晰、完整的文档,以确保其功能、配置和使用方法得到充分说明。
|
||||
|
||||
@@ -8,6 +8,25 @@
|
||||
|
||||
---
|
||||
|
||||
## 🔥 v0.9.1 更新亮点
|
||||
|
||||
**新功能:图片输出模式**
|
||||
|
||||
- **静态图片支持**:新增 `OUTPUT_MODE` 配置参数。
|
||||
- `html`(默认):交互式 HTML 思维导图。
|
||||
- `image`:静态 SVG 图片直接嵌入 Markdown(**不输出 HTML 代码**,聊天记录更简洁)。
|
||||
- **高效存储**:图片模式将 SVG 上传至 `/api/v1/files`,避免聊天记录中出现超长 Base64 字符串。
|
||||
- **智能特性**:生成的图片支持自动响应式宽度和自动主题检测(亮色/暗色)。
|
||||
|
||||
| 特性 | HTML 模式 (默认) | 图片模式 |
|
||||
| :--- | :--- | :--- |
|
||||
| **输出格式** | 交互式 HTML 代码块 | 静态 Markdown 图片 |
|
||||
| **交互性** | 缩放、拖拽、展开/折叠 | 无 (静态图片) |
|
||||
| **聊天记录** | 包含 HTML 代码 | 简洁 (仅图片链接) |
|
||||
| **存储方式** | 浏览器实时渲染 | `/api/v1/files` 上传 |
|
||||
|
||||
---
|
||||
|
||||
## 核心特性
|
||||
|
||||
- ✅ **智能文本分析**:自动识别文本的核心主题、关键概念和层次结构
|
||||
@@ -20,6 +39,7 @@
|
||||
- ✅ **实时渲染**:在聊天界面中直接渲染思维导图,无需跳转
|
||||
- ✅ **导出功能**:支持 PNG、SVG 代码和 Markdown 源码导出
|
||||
- ✅ **自定义配置**:可配置 LLM 模型、最小文本长度等参数
|
||||
- ✅ **图片输出模式**:生成静态 SVG 图片直接嵌入 Markdown(**不输出 HTML 代码**,聊天记录更简洁)
|
||||
|
||||
---
|
||||
|
||||
@@ -80,6 +100,7 @@
|
||||
| `MIN_TEXT_LENGTH` | `100` | 进行思维导图分析所需的最小文本长度(字符数)。文本过短将无法生成有效的导图。 |
|
||||
| `CLEAR_PREVIOUS_HTML` | `false` | 在生成新的思维导图时,是否清除之前由插件生成的 HTML 内容。 |
|
||||
| `MESSAGE_COUNT` | `1` | 用于生成思维导图的最近消息数量(1-5)。 |
|
||||
| `OUTPUT_MODE` | `html` | 输出模式:`html` 为交互式 HTML(默认),`image` 为嵌入静态 Markdown 图片。 |
|
||||
|
||||
---
|
||||
|
||||
@@ -277,6 +298,32 @@
|
||||
|
||||
## 更新日志
|
||||
|
||||
### v0.9.1
|
||||
|
||||
**新功能:图片输出模式**
|
||||
|
||||
- 新增 `OUTPUT_MODE` 配置参数,支持两种模式:
|
||||
- `html`(默认):交互式 HTML 思维导图,带完整控制面板
|
||||
- `image`:静态 SVG 图片直接嵌入 Markdown(上传至 `/api/v1/files`)
|
||||
- 图片模式特性:
|
||||
- 自动响应式宽度(适应聊天容器)
|
||||
- 自动主题检测(亮色/暗色)
|
||||
- 通过 Chat API 持久化存储(刷新页面后保留)
|
||||
- 高效文件存储(聊天记录中无超长 Base64 字符串)
|
||||
|
||||
**改进项:**
|
||||
|
||||
- 实现健壮的 Chat API 更新机制,带重试逻辑
|
||||
- 修复消息持久化,同时更新 `messages[]` 和 `history.messages`
|
||||
- 添加 Event API 实现即时前端更新
|
||||
- 移除不必要的 `SVG_WIDTH` 和 `SVG_HEIGHT` 参数(现已自动计算)
|
||||
|
||||
**技术细节:**
|
||||
|
||||
- 图片模式使用 `__event_call__` 在浏览器中执行 JavaScript
|
||||
- SVG 离屏渲染,转换为 Blob,并上传至 OpenWebUI Files API
|
||||
- 通过 OpenWebUI Backend-Controlled API 流程更新聊天消息为 `/api/v1/files/{id}/content` URL
|
||||
|
||||
### v0.8.2
|
||||
|
||||
- 移除输出中的调试信息
|
||||
|
||||
BIN
plugins/actions/smart-mind-map/smart_mind_map.png
Normal file
|
After Width: | Height: | Size: 752 KiB |
@@ -3,7 +3,8 @@ 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: 0.9.1
|
||||
openwebui_id: 3094c59a-b4dd-4e0c-9449-15e2dd547dc4
|
||||
icon_url: data:image/svg+xml;base64,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
|
||||
description: Intelligently analyzes text content and generates interactive mind maps to help users structure and visualize knowledge.
|
||||
"""
|
||||
@@ -13,7 +14,7 @@ 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 +787,10 @@ 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.",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
@@ -814,6 +819,46 @@ 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:
|
||||
@@ -901,14 +946,391 @@ class Action:
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _generate_image_js_code(
|
||||
self,
|
||||
unique_id: str,
|
||||
chat_id: str,
|
||||
message_id: str,
|
||||
markdown_syntax: str,
|
||||
) -> 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 = 1200;
|
||||
const defaultHeight = 800;
|
||||
|
||||
// Theme detection - check parent document for OpenWebUI theme
|
||||
const detectTheme = () => {{
|
||||
try {{
|
||||
// 1. Check parent document's html/body class or data-theme
|
||||
const html = document.documentElement;
|
||||
const body = document.body;
|
||||
const htmlClass = html ? html.className : '';
|
||||
const bodyClass = body ? body.className : '';
|
||||
const htmlDataTheme = html ? html.getAttribute('data-theme') : '';
|
||||
|
||||
if (htmlDataTheme === 'dark' || bodyClass.includes('dark') || htmlClass.includes('dark')) {{
|
||||
return 'dark';
|
||||
}}
|
||||
if (htmlDataTheme === 'light' || bodyClass.includes('light') || htmlClass.includes('light')) {{
|
||||
return 'light';
|
||||
}}
|
||||
|
||||
// 2. Check meta theme-color
|
||||
const metas = document.querySelectorAll('meta[name="theme-color"]');
|
||||
if (metas.length > 0) {{
|
||||
const color = metas[metas.length - 1].content.trim();
|
||||
const m = color.match(/^#?([0-9a-f]{{6}})$/i);
|
||||
if (m) {{
|
||||
const hex = m[1];
|
||||
const r = parseInt(hex.slice(0, 2), 16);
|
||||
const g = parseInt(hex.slice(2, 4), 16);
|
||||
const b = parseInt(hex.slice(4, 6), 16);
|
||||
const luma = (0.2126 * r + 0.7152 * g + 0.0722 * b) / 255;
|
||||
return luma < 0.5 ? 'dark' : 'light';
|
||||
}}
|
||||
}}
|
||||
|
||||
// 3. Check system preference
|
||||
if (window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches) {{
|
||||
return 'dark';
|
||||
}}
|
||||
|
||||
return 'light';
|
||||
}} catch (e) {{
|
||||
return 'light';
|
||||
}}
|
||||
}};
|
||||
|
||||
const currentTheme = detectTheme();
|
||||
console.log("[MindMap Image] Detected theme:", currentTheme);
|
||||
|
||||
// Theme-based colors
|
||||
const colors = currentTheme === 'dark' ? {{
|
||||
background: '#1f2937',
|
||||
text: '#e5e7eb',
|
||||
link: '#94a3b8',
|
||||
nodeStroke: '#64748b'
|
||||
}} : {{
|
||||
background: '#ffffff',
|
||||
text: '#1f2937',
|
||||
link: '#546e7a',
|
||||
nodeStroke: '#94a3b8'
|
||||
}};
|
||||
|
||||
// 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 = colors.background;
|
||||
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 with theme color
|
||||
const bgRect = document.createElementNS('http://www.w3.org/2000/svg', 'rect');
|
||||
bgRect.setAttribute('width', '100%');
|
||||
bgRect.setAttribute('height', '100%');
|
||||
bgRect.setAttribute('fill', colors.background);
|
||||
clonedSvg.insertBefore(bgRect, clonedSvg.firstChild);
|
||||
|
||||
// Add inline styles with theme colors
|
||||
const style = document.createElementNS('http://www.w3.org/2000/svg', 'style');
|
||||
style.textContent = `
|
||||
text {{ font-family: sans-serif; font-size: 14px; fill: ${{colors.text}}; }}
|
||||
foreignObject, .markmap-foreign, .markmap-foreign div {{ color: ${{colors.text}}; 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: ${{colors.link}}; fill: none; }}
|
||||
.markmap-node circle, .markmap-node rect {{ stroke: ${{colors.nodeStroke}}; }}
|
||||
`;
|
||||
clonedSvg.insertBefore(style, bgRect.nextSibling);
|
||||
|
||||
// Convert foreignObject to text for better compatibility
|
||||
const foreignObjects = clonedSvg.querySelectorAll('foreignObject');
|
||||
foreignObjects.forEach(fo => {{
|
||||
const text = fo.textContent || '';
|
||||
const g = document.createElementNS('http://www.w3.org/2000/svg', 'g');
|
||||
const textEl = document.createElementNS('http://www.w3.org/2000/svg', 'text');
|
||||
textEl.setAttribute('x', fo.getAttribute('x') || '0');
|
||||
textEl.setAttribute('y', (parseFloat(fo.getAttribute('y') || '0') + 14).toString());
|
||||
textEl.setAttribute('fill', colors.text);
|
||||
textEl.setAttribute('font-family', 'sans-serif');
|
||||
textEl.setAttribute('font-size', '14');
|
||||
textEl.textContent = text.trim();
|
||||
g.appendChild(textEl);
|
||||
fo.parentNode.replaceChild(g, fo);
|
||||
}});
|
||||
|
||||
// Serialize SVG to string
|
||||
const svgData = new XMLSerializer().serializeToString(clonedSvg);
|
||||
|
||||
// Cleanup container
|
||||
document.body.removeChild(container);
|
||||
|
||||
// Convert SVG string to Blob
|
||||
const blob = new Blob([svgData], {{ type: 'image/svg+xml' }});
|
||||
const file = new File([blob], `mindmap-${{uniqueId}}.svg`, {{ type: 'image/svg+xml' }});
|
||||
|
||||
// Upload file to OpenWebUI API
|
||||
console.log("[MindMap Image] Uploading SVG file...");
|
||||
const token = localStorage.getItem("token");
|
||||
const formData = new FormData();
|
||||
formData.append('file', file);
|
||||
|
||||
const uploadResponse = await fetch('/api/v1/files/', {{
|
||||
method: 'POST',
|
||||
headers: {{
|
||||
'Authorization': `Bearer ${{token}}`
|
||||
}},
|
||||
body: formData
|
||||
}});
|
||||
|
||||
if (!uploadResponse.ok) {{
|
||||
throw new Error(`Upload failed: ${{uploadResponse.statusText}}`);
|
||||
}}
|
||||
|
||||
const fileData = await uploadResponse.json();
|
||||
const fileId = fileData.id;
|
||||
const imageUrl = `/api/v1/files/${{fileId}}/content`;
|
||||
|
||||
console.log("[MindMap Image] File uploaded, ID:", fileId);
|
||||
|
||||
// Generate markdown image with file URL
|
||||
const markdownImage = ``;
|
||||
|
||||
// Update message via API
|
||||
if (chatId && messageId) {{
|
||||
|
||||
// Helper function with retry logic
|
||||
const fetchWithRetry = async (url, options, retries = 3) => {{
|
||||
for (let i = 0; i < retries; i++) {{
|
||||
try {{
|
||||
const response = await fetch(url, options);
|
||||
if (response.ok) return response;
|
||||
if (i < retries - 1) {{
|
||||
console.log(`[MindMap Image] Retry ${{i + 1}}/${{retries}} for ${{url}}`);
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}}
|
||||
}} catch (e) {{
|
||||
if (i === retries - 1) throw e;
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}}
|
||||
}}
|
||||
return null;
|
||||
}};
|
||||
|
||||
// Get current chat data
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("Failed to get chat data: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
let updatedMessages = [];
|
||||
let newContent = "";
|
||||
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
updatedMessages = chatData.chat.messages.map(m => {{
|
||||
if (m.id === messageId) {{
|
||||
const originalContent = m.content || "";
|
||||
// Remove existing mindmap images (both base64 and file URL patterns)
|
||||
const mindmapPattern = /\\n*!\\[🧠[^\\]]*\\]\\((?:data:image\\/[^)]+|(?:\\/api\\/v1\\/files\\/[^)]+))\\)/g;
|
||||
let cleanedContent = originalContent.replace(mindmapPattern, "");
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
// Append new image
|
||||
newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// Critical: Update content in both messages array AND history object
|
||||
// The history object is the source of truth for the database
|
||||
if (chatData.chat.history && chatData.chat.history.messages) {{
|
||||
if (chatData.chat.history.messages[messageId]) {{
|
||||
chatData.chat.history.messages[messageId].content = newContent;
|
||||
}}
|
||||
}}
|
||||
|
||||
return {{ ...m, content: newContent }};
|
||||
}}
|
||||
return m;
|
||||
}});
|
||||
}}
|
||||
|
||||
if (!newContent) {{
|
||||
console.warn("[MindMap Image] Could not find message to update");
|
||||
return;
|
||||
}}
|
||||
|
||||
// Try to update frontend display via event API (optional, may not exist in all versions)
|
||||
try {{
|
||||
await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: newContent }}
|
||||
}})
|
||||
}});
|
||||
}} catch (eventErr) {{
|
||||
// Event API is optional, continue with persistence
|
||||
console.log("[MindMap Image] Event API not available, continuing...");
|
||||
}}
|
||||
|
||||
// Persist to database by updating the entire chat object
|
||||
// This follows the OpenWebUI Backend-Controlled API Flow
|
||||
const updatePayload = {{
|
||||
chat: {{
|
||||
...chatData.chat,
|
||||
messages: updatedMessages
|
||||
// history is already updated in-place above
|
||||
}}
|
||||
}};
|
||||
|
||||
const persistResponse = await fetchWithRetry(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify(updatePayload)
|
||||
}});
|
||||
|
||||
if (persistResponse && persistResponse.ok) {{
|
||||
console.log("[MindMap Image] ✅ Message persisted successfully!");
|
||||
}} else {{
|
||||
console.error("[MindMap Image] ❌ Failed to persist message after retries");
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[MindMap Image] ⚠️ Missing chatId or messageId, cannot persist");
|
||||
}}
|
||||
|
||||
}} 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")
|
||||
logger.info("Action: Smart Mind Map (v0.9.1) started")
|
||||
user_ctx = self._get_user_context(__user__)
|
||||
user_language = user_ctx["user_language"]
|
||||
user_name = user_ctx["user_name"]
|
||||
@@ -1090,6 +1512,45 @@ 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,
|
||||
)
|
||||
|
||||
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 (v0.9.1) 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 +1562,7 @@ 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 (v0.9.1) completed in HTML mode")
|
||||
|
||||
except Exception as e:
|
||||
error_message = f"Smart Mind Map processing failed: {str(e)}"
|
||||
|
||||
BIN
plugins/actions/smart-mind-map/smart_mind_map_cn.png
Normal file
|
After Width: | Height: | Size: 216 KiB |
@@ -3,7 +3,8 @@ 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: 0.9.1
|
||||
openwebui_id: 8d4b097b-219b-4dd2-b509-05fbe6388335
|
||||
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 +14,7 @@ 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 +444,7 @@ 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 +486,7 @@ 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 +772,23 @@ 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。",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
@@ -813,14 +818,52 @@ 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。"
|
||||
)
|
||||
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。")
|
||||
extracted_content = llm_output.strip()
|
||||
return extracted_content.replace("</script>", "<\\/script>")
|
||||
|
||||
@@ -844,7 +887,7 @@ 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 +910,7 @@ 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
|
||||
@@ -900,14 +943,392 @@ class Action:
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _generate_image_js_code(
|
||||
self,
|
||||
unique_id: str,
|
||||
chat_id: str,
|
||||
message_id: str,
|
||||
markdown_syntax: str,
|
||||
) -> 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 = 1200;
|
||||
const defaultHeight = 800;
|
||||
|
||||
// 主题检测 - 检查 OpenWebUI 当前主题
|
||||
const detectTheme = () => {{
|
||||
try {{
|
||||
// 1. 检查 html/body 的 class 或 data-theme 属性
|
||||
const html = document.documentElement;
|
||||
const body = document.body;
|
||||
const htmlClass = html ? html.className : '';
|
||||
const bodyClass = body ? body.className : '';
|
||||
const htmlDataTheme = html ? html.getAttribute('data-theme') : '';
|
||||
|
||||
if (htmlDataTheme === 'dark' || bodyClass.includes('dark') || htmlClass.includes('dark')) {{
|
||||
return 'dark';
|
||||
}}
|
||||
if (htmlDataTheme === 'light' || bodyClass.includes('light') || htmlClass.includes('light')) {{
|
||||
return 'light';
|
||||
}}
|
||||
|
||||
// 2. 检查 meta theme-color
|
||||
const metas = document.querySelectorAll('meta[name="theme-color"]');
|
||||
if (metas.length > 0) {{
|
||||
const color = metas[metas.length - 1].content.trim();
|
||||
const m = color.match(/^#?([0-9a-f]{{6}})$/i);
|
||||
if (m) {{
|
||||
const hex = m[1];
|
||||
const r = parseInt(hex.slice(0, 2), 16);
|
||||
const g = parseInt(hex.slice(2, 4), 16);
|
||||
const b = parseInt(hex.slice(4, 6), 16);
|
||||
const luma = (0.2126 * r + 0.7152 * g + 0.0722 * b) / 255;
|
||||
return luma < 0.5 ? 'dark' : 'light';
|
||||
}}
|
||||
}}
|
||||
|
||||
// 3. 检查系统偏好
|
||||
if (window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches) {{
|
||||
return 'dark';
|
||||
}}
|
||||
|
||||
return 'light';
|
||||
}} catch (e) {{
|
||||
return 'light';
|
||||
}}
|
||||
}};
|
||||
|
||||
const currentTheme = detectTheme();
|
||||
console.log("[思维导图图片] 检测到主题:", currentTheme);
|
||||
|
||||
// 基于主题的颜色配置
|
||||
const colors = currentTheme === 'dark' ? {{
|
||||
background: '#1f2937',
|
||||
text: '#e5e7eb',
|
||||
link: '#94a3b8',
|
||||
nodeStroke: '#64748b'
|
||||
}} : {{
|
||||
background: '#ffffff',
|
||||
text: '#1f2937',
|
||||
link: '#546e7a',
|
||||
nodeStroke: '#94a3b8'
|
||||
}};
|
||||
|
||||
// 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 = colors.background;
|
||||
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(使用主题颜色)
|
||||
const bgRect = document.createElementNS('http://www.w3.org/2000/svg', 'rect');
|
||||
bgRect.setAttribute('width', '100%');
|
||||
bgRect.setAttribute('height', '100%');
|
||||
bgRect.setAttribute('fill', colors.background);
|
||||
clonedSvg.insertBefore(bgRect, clonedSvg.firstChild);
|
||||
|
||||
// 添加内联样式(使用主题颜色)
|
||||
const style = document.createElementNS('http://www.w3.org/2000/svg', 'style');
|
||||
style.textContent = `
|
||||
text {{ font-family: sans-serif; font-size: 14px; fill: ${{colors.text}}; }}
|
||||
foreignObject, .markmap-foreign, .markmap-foreign div {{ color: ${{colors.text}}; 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: ${{colors.link}}; fill: none; }}
|
||||
.markmap-node circle, .markmap-node rect {{ stroke: ${{colors.nodeStroke}}; }}
|
||||
`;
|
||||
clonedSvg.insertBefore(style, bgRect.nextSibling);
|
||||
|
||||
// 将 foreignObject 转换为 text 以提高兼容性
|
||||
const foreignObjects = clonedSvg.querySelectorAll('foreignObject');
|
||||
foreignObjects.forEach(fo => {{
|
||||
const text = fo.textContent || '';
|
||||
const g = document.createElementNS('http://www.w3.org/2000/svg', 'g');
|
||||
const textEl = document.createElementNS('http://www.w3.org/2000/svg', 'text');
|
||||
textEl.setAttribute('x', fo.getAttribute('x') || '0');
|
||||
textEl.setAttribute('y', (parseFloat(fo.getAttribute('y') || '0') + 14).toString());
|
||||
textEl.setAttribute('fill', colors.text);
|
||||
textEl.setAttribute('font-family', 'sans-serif');
|
||||
textEl.setAttribute('font-size', '14');
|
||||
textEl.textContent = text.trim();
|
||||
g.appendChild(textEl);
|
||||
fo.parentNode.replaceChild(g, fo);
|
||||
}});
|
||||
|
||||
// 序列化 SVG 为字符串
|
||||
const svgData = new XMLSerializer().serializeToString(clonedSvg);
|
||||
|
||||
// 清理容器
|
||||
document.body.removeChild(container);
|
||||
|
||||
// 将 SVG 字符串转换为 Blob
|
||||
const blob = new Blob([svgData], {{ type: 'image/svg+xml' }});
|
||||
const file = new File([blob], `mindmap-${{uniqueId}}.svg`, {{ type: 'image/svg+xml' }});
|
||||
|
||||
// 上传文件到 OpenWebUI API
|
||||
console.log("[思维导图图片] 正在上传 SVG 文件...");
|
||||
const token = localStorage.getItem("token");
|
||||
const formData = new FormData();
|
||||
formData.append('file', file);
|
||||
|
||||
const uploadResponse = await fetch('/api/v1/files/', {{
|
||||
method: 'POST',
|
||||
headers: {{
|
||||
'Authorization': `Bearer ${{token}}`
|
||||
}},
|
||||
body: formData
|
||||
}});
|
||||
|
||||
if (!uploadResponse.ok) {{
|
||||
throw new Error(`上传失败: ${{uploadResponse.statusText}}`);
|
||||
}}
|
||||
|
||||
const fileData = await uploadResponse.json();
|
||||
const fileId = fileData.id;
|
||||
const imageUrl = `/api/v1/files/${{fileId}}/content`;
|
||||
|
||||
console.log("[思维导图图片] 文件已上传, ID:", fileId);
|
||||
|
||||
// 生成包含文件 URL 的 markdown 图片
|
||||
const markdownImage = ``;
|
||||
|
||||
// 通过 API 更新消息
|
||||
if (chatId && messageId) {{
|
||||
const token = localStorage.getItem("token");
|
||||
|
||||
// 带重试逻辑的请求函数
|
||||
const fetchWithRetry = async (url, options, retries = 3) => {{
|
||||
for (let i = 0; i < retries; i++) {{
|
||||
try {{
|
||||
const response = await fetch(url, options);
|
||||
if (response.ok) return response;
|
||||
if (i < retries - 1) {{
|
||||
console.log(`[思维导图图片] 重试 ${{i + 1}}/${{retries}}: ${{url}}`);
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}}
|
||||
}} catch (e) {{
|
||||
if (i === retries - 1) throw e;
|
||||
await new Promise(r => setTimeout(r, 1000 * (i + 1)));
|
||||
}}
|
||||
}}
|
||||
return null;
|
||||
}};
|
||||
|
||||
// 获取当前聊天数据
|
||||
const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "GET",
|
||||
headers: {{ "Authorization": `Bearer ${{token}}` }}
|
||||
}});
|
||||
|
||||
if (!getResponse.ok) {{
|
||||
throw new Error("获取聊天数据失败: " + getResponse.status);
|
||||
}}
|
||||
|
||||
const chatData = await getResponse.json();
|
||||
let updatedMessages = [];
|
||||
let newContent = "";
|
||||
|
||||
if (chatData.chat && chatData.chat.messages) {{
|
||||
updatedMessages = chatData.chat.messages.map(m => {{
|
||||
if (m.id === messageId) {{
|
||||
const originalContent = m.content || "";
|
||||
// 移除已有的思维导图图片 (包括 base64 和文件 URL 格式)
|
||||
const mindmapPattern = /\\n*!\\[🧠[^\\]]*\\]\\((?:data:image\\/[^)]+|(?:\\/api\\/v1\\/files\\/[^)]+))\\)/g;
|
||||
let cleanedContent = originalContent.replace(mindmapPattern, "");
|
||||
cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
|
||||
// 追加新图片
|
||||
newContent = cleanedContent + "\\n\\n" + markdownImage;
|
||||
|
||||
// 关键: 同时更新 messages 数组和 history 对象中的内容
|
||||
// history 对象是数据库的单一真值来源
|
||||
if (chatData.chat.history && chatData.chat.history.messages) {{
|
||||
if (chatData.chat.history.messages[messageId]) {{
|
||||
chatData.chat.history.messages[messageId].content = newContent;
|
||||
}}
|
||||
}}
|
||||
|
||||
return {{ ...m, content: newContent }};
|
||||
}}
|
||||
return m;
|
||||
}});
|
||||
}}
|
||||
|
||||
if (!newContent) {{
|
||||
console.warn("[思维导图图片] 找不到要更新的消息");
|
||||
return;
|
||||
}}
|
||||
|
||||
// 尝试通过事件 API 更新前端显示(可选,部分版本可能不支持)
|
||||
try {{
|
||||
await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify({{
|
||||
type: "chat:message",
|
||||
data: {{ content: newContent }}
|
||||
}})
|
||||
}});
|
||||
}} catch (eventErr) {{
|
||||
// 事件 API 是可选的,继续执行持久化
|
||||
console.log("[思维导图图片] 事件 API 不可用,继续执行...");
|
||||
}}
|
||||
|
||||
// 通过更新整个聊天对象来持久化到数据库
|
||||
// 遵循 OpenWebUI 后端控制的 API 流程
|
||||
const updatePayload = {{
|
||||
chat: {{
|
||||
...chatData.chat,
|
||||
messages: updatedMessages
|
||||
// history 已在上面原地更新
|
||||
}}
|
||||
}};
|
||||
|
||||
const persistResponse = await fetchWithRetry(`/api/v1/chats/${{chatId}}`, {{
|
||||
method: "POST",
|
||||
headers: {{
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": `Bearer ${{token}}`
|
||||
}},
|
||||
body: JSON.stringify(updatePayload)
|
||||
}});
|
||||
|
||||
if (persistResponse && 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] ❌ 重试后仍然无法持久化消息");
|
||||
}}
|
||||
}} else {{
|
||||
console.warn("[思维导图图片] ⚠️ 缺少 chatId 或 messageId,无法持久化");
|
||||
}}
|
||||
|
||||
}} 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")
|
||||
logger.info("Action: 思维导图 (v0.9.1) started")
|
||||
user_ctx = self._get_user_context(__user__)
|
||||
user_language = user_ctx["user_language"]
|
||||
user_name = user_ctx["user_name"]
|
||||
@@ -923,7 +1344,7 @@ 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 +1352,7 @@ 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 +1401,7 @@ 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 +1442,7 @@ 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 +1505,65 @@ 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,
|
||||
)
|
||||
|
||||
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 (v0.9.1) 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 (v0.9.1) 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
|
||||
|
||||
@@ -1,30 +0,0 @@
|
||||
# Deep Reading & Summary
|
||||
|
||||
A powerful tool for analyzing long texts, generating detailed summaries, key points, and actionable insights.
|
||||
|
||||
## Features
|
||||
|
||||
- **Deep Analysis**: Goes beyond simple summarization to understand the core message.
|
||||
- **Key Point Extraction**: Identifies and lists the most important information.
|
||||
- **Actionable Advice**: Provides practical suggestions based on the text content.
|
||||
|
||||
## Usage
|
||||
|
||||
1. Install the plugin.
|
||||
2. Send a long text or article to the chat.
|
||||
3. Click the "Deep Reading" button (or trigger via command).
|
||||
|
||||
## Author
|
||||
|
||||
Fu-Jie
|
||||
GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
## License
|
||||
|
||||
MIT License
|
||||
|
||||
## Changelog
|
||||
|
||||
### v0.1.2
|
||||
|
||||
- Removed debug messages from output
|
||||
@@ -1,30 +0,0 @@
|
||||
# 深度阅读与摘要 (Deep Reading & Summary)
|
||||
|
||||
一个强大的长文本分析工具,用于生成详细摘要、关键信息点和可执行的行动建议。
|
||||
|
||||
## 功能特点
|
||||
|
||||
- **深度分析**:超越简单的总结,深入理解核心信息。
|
||||
- **关键点提取**:识别并列出最重要的信息点。
|
||||
- **行动建议**:基于文本内容提供切实可行的建议。
|
||||
|
||||
## 使用方法
|
||||
|
||||
1. 安装插件。
|
||||
2. 发送长文本或文章到聊天框。
|
||||
3. 点击“精读”按钮(或通过命令触发)。
|
||||
|
||||
## 作者
|
||||
|
||||
Fu-Jie
|
||||
GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
|
||||
|
||||
## 许可证
|
||||
|
||||
MIT License
|
||||
|
||||
## 更新日志
|
||||
|
||||
### v0.1.2
|
||||
|
||||
- 移除输出中的调试信息
|
||||
@@ -1,674 +0,0 @@
|
||||
"""
|
||||
title: Deep Reading & Summary
|
||||
author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 0.1.2
|
||||
icon_url: data:image/svg+xml;base64,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
|
||||
description: Provides deep reading analysis and summarization for long texts.
|
||||
requirements: jinja2, markdown
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Optional, Dict, Any
|
||||
import logging
|
||||
import re
|
||||
from fastapi import Request
|
||||
from datetime import datetime
|
||||
import pytz
|
||||
import markdown
|
||||
from jinja2 import Template
|
||||
|
||||
from open_webui.utils.chat import generate_chat_completion
|
||||
from open_webui.models.users import Users
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
|
||||
)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# =================================================================
|
||||
# HTML Wrapper Template (supports multiple plugins and grid layout)
|
||||
# =================================================================
|
||||
HTML_WRAPPER_TEMPLATE = """
|
||||
<!-- OPENWEBUI_PLUGIN_OUTPUT -->
|
||||
<!DOCTYPE html>
|
||||
<html lang="{user_language}">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<style>
|
||||
body {
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
|
||||
margin: 0;
|
||||
padding: 10px;
|
||||
background-color: transparent;
|
||||
}
|
||||
#main-container {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 20px;
|
||||
align-items: flex-start;
|
||||
width: 100%;
|
||||
}
|
||||
.plugin-item {
|
||||
flex: 1 1 400px; /* Default width, allows shrinking/growing */
|
||||
min-width: 300px;
|
||||
background: white;
|
||||
border-radius: 12px;
|
||||
box-shadow: 0 4px 6px rgba(0,0,0,0.05);
|
||||
overflow: hidden;
|
||||
border: 1px solid #e5e7eb;
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
.plugin-item:hover {
|
||||
box-shadow: 0 10px 15px rgba(0,0,0,0.1);
|
||||
}
|
||||
@media (max-width: 768px) {
|
||||
.plugin-item { flex: 1 1 100%; }
|
||||
}
|
||||
/* STYLES_INSERTION_POINT */
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<div id="main-container">
|
||||
<!-- CONTENT_INSERTION_POINT -->
|
||||
</div>
|
||||
<!-- SCRIPTS_INSERTION_POINT -->
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
# =================================================================
|
||||
# Internal LLM Prompts
|
||||
# =================================================================
|
||||
|
||||
SYSTEM_PROMPT_READING_ASSISTANT = """
|
||||
You are a professional Deep Text Analysis Expert, specializing in reading long texts and extracting the essence. Your task is to conduct a comprehensive and in-depth analysis.
|
||||
|
||||
Please provide the following:
|
||||
1. **Detailed Summary**: Summarize the core content of the text in 2-3 paragraphs, ensuring accuracy and completeness. Do not be too brief; ensure the reader fully understands the main idea.
|
||||
2. **Key Information Points**: List 5-8 most important facts, viewpoints, or arguments. Each point should:
|
||||
- Be specific and insightful
|
||||
- Include necessary details and context
|
||||
- Use Markdown list format
|
||||
3. **Actionable Advice**: Identify and refine specific, actionable items from the text. Each suggestion should:
|
||||
- Be clear and actionable
|
||||
- Include execution priority or timing suggestions
|
||||
- If there are no clear action items, provide learning suggestions or thinking directions
|
||||
|
||||
Please strictly follow these guidelines:
|
||||
- **Language**: All output must be in the user's specified language.
|
||||
- **Format**: Please strictly follow the Markdown format below, ensuring each section has a clear header:
|
||||
## Summary
|
||||
[Detailed summary content here, 2-3 paragraphs, use Markdown **bold** or *italic* to emphasize key points]
|
||||
|
||||
## Key Information Points
|
||||
- [Key Point 1: Include specific details and context]
|
||||
- [Key Point 2: Include specific details and context]
|
||||
- [Key Point 3: Include specific details and context]
|
||||
- [At least 5, at most 8 key points]
|
||||
|
||||
## Actionable Advice
|
||||
- [Action Item 1: Specific, actionable, include priority]
|
||||
- [Action Item 2: Specific, actionable, include priority]
|
||||
- [If no clear action items, provide learning suggestions or thinking directions]
|
||||
- **Depth First**: Analysis should be deep and comprehensive, not superficial.
|
||||
- **Action Oriented**: Focus on actionable suggestions and next steps.
|
||||
- **Analysis Results Only**: Do not include any extra pleasantries, explanations, or leading text.
|
||||
"""
|
||||
|
||||
USER_PROMPT_GENERATE_SUMMARY = """
|
||||
Please conduct a deep analysis of the following long text, providing:
|
||||
1. Detailed Summary (2-3 paragraphs, comprehensive overview)
|
||||
2. Key Information Points List (5-8 items, including specific details)
|
||||
3. Actionable Advice (Specific, clear, including priority)
|
||||
|
||||
---
|
||||
**User Context:**
|
||||
User Name: {user_name}
|
||||
Current Date/Time: {current_date_time_str}
|
||||
Weekday: {current_weekday}
|
||||
Timezone: {current_timezone_str}
|
||||
User Language: {user_language}
|
||||
---
|
||||
|
||||
**Long Text Content:**
|
||||
```
|
||||
{long_text_content}
|
||||
```
|
||||
|
||||
Please conduct a deep and comprehensive analysis, focusing on actionable advice.
|
||||
"""
|
||||
|
||||
# =================================================================
|
||||
# Frontend HTML Template (Jinja2 Syntax)
|
||||
# =================================================================
|
||||
|
||||
CSS_TEMPLATE_SUMMARY = """
|
||||
:root {
|
||||
--primary-color: #4285f4;
|
||||
--secondary-color: #1e88e5;
|
||||
--action-color: #34a853;
|
||||
--background-color: #f8f9fa;
|
||||
--card-bg-color: #ffffff;
|
||||
--text-color: #202124;
|
||||
--muted-text-color: #5f6368;
|
||||
--border-color: #dadce0;
|
||||
--header-gradient: linear-gradient(135deg, #4285f4, #1e88e5);
|
||||
--shadow: 0 1px 3px rgba(60,64,67,.3);
|
||||
--border-radius: 8px;
|
||||
--font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
|
||||
}
|
||||
.summary-container-wrapper {
|
||||
font-family: var(--font-family);
|
||||
line-height: 1.8;
|
||||
color: var(--text-color);
|
||||
height: 100%;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
}
|
||||
.summary-container-wrapper .header {
|
||||
background: var(--header-gradient);
|
||||
color: white;
|
||||
padding: 20px 24px;
|
||||
text-align: center;
|
||||
}
|
||||
.summary-container-wrapper .header h1 {
|
||||
margin: 0;
|
||||
font-size: 1.5em;
|
||||
font-weight: 500;
|
||||
letter-spacing: -0.5px;
|
||||
}
|
||||
.summary-container-wrapper .user-context {
|
||||
font-size: 0.8em;
|
||||
color: var(--muted-text-color);
|
||||
background-color: #f1f3f4;
|
||||
padding: 8px 16px;
|
||||
display: flex;
|
||||
justify-content: space-around;
|
||||
flex-wrap: wrap;
|
||||
border-bottom: 1px solid var(--border-color);
|
||||
}
|
||||
.summary-container-wrapper .user-context span { margin: 2px 8px; }
|
||||
.summary-container-wrapper .content { padding: 20px; flex-grow: 1; }
|
||||
.summary-container-wrapper .section {
|
||||
margin-bottom: 16px;
|
||||
padding-bottom: 16px;
|
||||
border-bottom: 1px solid #e8eaed;
|
||||
}
|
||||
.summary-container-wrapper .section:last-child {
|
||||
border-bottom: none;
|
||||
margin-bottom: 0;
|
||||
padding-bottom: 0;
|
||||
}
|
||||
.summary-container-wrapper .section h2 {
|
||||
margin-top: 0;
|
||||
margin-bottom: 12px;
|
||||
font-size: 1.2em;
|
||||
font-weight: 500;
|
||||
color: var(--text-color);
|
||||
display: flex;
|
||||
align-items: center;
|
||||
padding-bottom: 8px;
|
||||
border-bottom: 2px solid var(--primary-color);
|
||||
}
|
||||
.summary-container-wrapper .section h2 .icon {
|
||||
margin-right: 8px;
|
||||
font-size: 1.1em;
|
||||
line-height: 1;
|
||||
}
|
||||
.summary-container-wrapper .summary-section h2 { border-bottom-color: var(--primary-color); }
|
||||
.summary-container-wrapper .keypoints-section h2 { border-bottom-color: var(--secondary-color); }
|
||||
.summary-container-wrapper .actions-section h2 { border-bottom-color: var(--action-color); }
|
||||
.summary-container-wrapper .html-content {
|
||||
font-size: 0.95em;
|
||||
line-height: 1.7;
|
||||
}
|
||||
.summary-container-wrapper .html-content p:first-child { margin-top: 0; }
|
||||
.summary-container-wrapper .html-content p:last-child { margin-bottom: 0; }
|
||||
.summary-container-wrapper .html-content ul {
|
||||
list-style: none;
|
||||
padding-left: 0;
|
||||
margin: 12px 0;
|
||||
}
|
||||
.summary-container-wrapper .html-content li {
|
||||
padding: 8px 0 8px 24px;
|
||||
position: relative;
|
||||
margin-bottom: 6px;
|
||||
line-height: 1.6;
|
||||
}
|
||||
.summary-container-wrapper .html-content li::before {
|
||||
position: absolute;
|
||||
left: 0;
|
||||
top: 8px;
|
||||
font-family: 'Arial';
|
||||
font-weight: bold;
|
||||
font-size: 1em;
|
||||
}
|
||||
.summary-container-wrapper .keypoints-section .html-content li::before {
|
||||
content: '•';
|
||||
color: var(--secondary-color);
|
||||
font-size: 1.3em;
|
||||
top: 5px;
|
||||
}
|
||||
.summary-container-wrapper .actions-section .html-content li::before {
|
||||
content: '▸';
|
||||
color: var(--action-color);
|
||||
}
|
||||
.summary-container-wrapper .no-content {
|
||||
color: var(--muted-text-color);
|
||||
font-style: italic;
|
||||
padding: 12px;
|
||||
background: #f8f9fa;
|
||||
border-radius: 4px;
|
||||
}
|
||||
.summary-container-wrapper .footer {
|
||||
text-align: center;
|
||||
padding: 16px;
|
||||
font-size: 0.8em;
|
||||
color: #5f6368;
|
||||
background-color: #f8f9fa;
|
||||
border-top: 1px solid var(--border-color);
|
||||
}
|
||||
"""
|
||||
|
||||
CONTENT_TEMPLATE_SUMMARY = """
|
||||
<div class="summary-container-wrapper">
|
||||
<div class="header">
|
||||
<h1>📖 Deep Reading: Analysis Report</h1>
|
||||
</div>
|
||||
<div class="user-context">
|
||||
<span><strong>User:</strong> {user_name}</span>
|
||||
<span><strong>Time:</strong> {current_date_time_str}</span>
|
||||
</div>
|
||||
<div class="content">
|
||||
<div class="section summary-section">
|
||||
<h2><span class="icon">📝</span>Detailed Summary</h2>
|
||||
<div class="html-content">{summary_html}</div>
|
||||
</div>
|
||||
<div class="section keypoints-section">
|
||||
<h2><span class="icon">💡</span>Key Information Points</h2>
|
||||
<div class="html-content">{keypoints_html}</div>
|
||||
</div>
|
||||
<div class="section actions-section">
|
||||
<h2><span class="icon">🎯</span>Actionable Advice</h2>
|
||||
<div class="html-content">{actions_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="footer">
|
||||
<p>© {current_year} Deep Reading - Text Analysis Service</p>
|
||||
</div>
|
||||
</div>
|
||||
"""
|
||||
|
||||
|
||||
class Action:
|
||||
class Valves(BaseModel):
|
||||
SHOW_STATUS: bool = Field(
|
||||
default=True,
|
||||
description="Whether to show operation status updates in the chat interface.",
|
||||
)
|
||||
MODEL_ID: str = Field(
|
||||
default="",
|
||||
description="Built-in LLM Model ID used for text analysis. If empty, uses the current conversation's model.",
|
||||
)
|
||||
MIN_TEXT_LENGTH: int = Field(
|
||||
default=200,
|
||||
description="Minimum text length required for deep analysis (characters). Recommended 200+.",
|
||||
)
|
||||
RECOMMENDED_MIN_LENGTH: int = Field(
|
||||
default=500,
|
||||
description="Recommended minimum text length for best analysis results.",
|
||||
)
|
||||
CLEAR_PREVIOUS_HTML: bool = Field(
|
||||
default=False,
|
||||
description="Whether to force clear previous plugin results (if True, overwrites instead of merging).",
|
||||
)
|
||||
MESSAGE_COUNT: int = Field(
|
||||
default=1,
|
||||
description="Number of recent messages to use for generation. Set to 1 for just the last message, or higher for more context.",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _process_llm_output(self, llm_output: str) -> Dict[str, str]:
|
||||
"""
|
||||
Parse LLM Markdown output and convert to HTML fragments.
|
||||
"""
|
||||
summary_match = re.search(
|
||||
r"##\s*Summary\s*\n(.*?)(?=\n##|$)", llm_output, re.DOTALL | re.IGNORECASE
|
||||
)
|
||||
keypoints_match = re.search(
|
||||
r"##\s*Key Information Points\s*\n(.*?)(?=\n##|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
actions_match = re.search(
|
||||
r"##\s*Actionable Advice\s*\n(.*?)(?=\n##|$)",
|
||||
llm_output,
|
||||
re.DOTALL | re.IGNORECASE,
|
||||
)
|
||||
|
||||
summary_md = summary_match.group(1).strip() if summary_match else ""
|
||||
keypoints_md = keypoints_match.group(1).strip() if keypoints_match else ""
|
||||
actions_md = actions_match.group(1).strip() if actions_match else ""
|
||||
|
||||
if not any([summary_md, keypoints_md, actions_md]):
|
||||
summary_md = llm_output.strip()
|
||||
logger.warning(
|
||||
"LLM output did not follow expected Markdown format. Treating entire output as summary."
|
||||
)
|
||||
|
||||
# Use 'nl2br' extension to convert newlines \n to <br>
|
||||
md_extensions = ["nl2br"]
|
||||
summary_html = (
|
||||
markdown.markdown(summary_md, extensions=md_extensions)
|
||||
if summary_md
|
||||
else '<p class="no-content">Failed to extract summary.</p>'
|
||||
)
|
||||
keypoints_html = (
|
||||
markdown.markdown(keypoints_md, extensions=md_extensions)
|
||||
if keypoints_md
|
||||
else '<p class="no-content">Failed to extract key information points.</p>'
|
||||
)
|
||||
actions_html = (
|
||||
markdown.markdown(actions_md, extensions=md_extensions)
|
||||
if actions_md
|
||||
else '<p class="no-content">No explicit actionable advice.</p>'
|
||||
)
|
||||
|
||||
return {
|
||||
"summary_html": summary_html,
|
||||
"keypoints_html": keypoints_html,
|
||||
"actions_html": actions_html,
|
||||
}
|
||||
|
||||
async def _emit_status(self, emitter, description: str, done: bool = False):
|
||||
"""Emits a status update event."""
|
||||
if self.valves.SHOW_STATUS and emitter:
|
||||
await emitter(
|
||||
{"type": "status", "data": {"description": description, "done": done}}
|
||||
)
|
||||
|
||||
async def _emit_notification(self, emitter, content: str, ntype: str = "info"):
|
||||
"""Emits a notification event (info/success/warning/error)."""
|
||||
if emitter:
|
||||
await emitter(
|
||||
{"type": "notification", "data": {"type": ntype, "content": content}}
|
||||
)
|
||||
|
||||
def _remove_existing_html(self, content: str) -> str:
|
||||
"""Removes existing plugin-generated HTML code blocks from the content."""
|
||||
pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"
|
||||
return re.sub(pattern, "", content).strip()
|
||||
|
||||
def _extract_text_content(self, content) -> str:
|
||||
"""Extract text from message content, supporting multimodal message formats"""
|
||||
if isinstance(content, str):
|
||||
return content
|
||||
elif isinstance(content, list):
|
||||
# Multimodal message: [{"type": "text", "text": "..."}, {"type": "image_url", ...}]
|
||||
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 ""
|
||||
|
||||
def _merge_html(
|
||||
self,
|
||||
existing_html_code: str,
|
||||
new_content: str,
|
||||
new_styles: str = "",
|
||||
new_scripts: str = "",
|
||||
user_language: str = "en-US",
|
||||
) -> str:
|
||||
"""
|
||||
Merges new content into an existing HTML container, or creates a new one.
|
||||
"""
|
||||
if (
|
||||
"<!-- OPENWEBUI_PLUGIN_OUTPUT -->" in existing_html_code
|
||||
and "<!-- CONTENT_INSERTION_POINT -->" in existing_html_code
|
||||
):
|
||||
base_html = existing_html_code
|
||||
base_html = re.sub(r"^```html\s*", "", base_html)
|
||||
base_html = re.sub(r"\s*```$", "", base_html)
|
||||
else:
|
||||
base_html = HTML_WRAPPER_TEMPLATE.replace("{user_language}", user_language)
|
||||
|
||||
wrapped_content = f'<div class="plugin-item">\n{new_content}\n</div>'
|
||||
|
||||
if new_styles:
|
||||
base_html = base_html.replace(
|
||||
"/* STYLES_INSERTION_POINT */",
|
||||
f"{new_styles}\n/* STYLES_INSERTION_POINT */",
|
||||
)
|
||||
|
||||
base_html = base_html.replace(
|
||||
"<!-- CONTENT_INSERTION_POINT -->",
|
||||
f"{wrapped_content}\n<!-- CONTENT_INSERTION_POINT -->",
|
||||
)
|
||||
|
||||
if new_scripts:
|
||||
base_html = base_html.replace(
|
||||
"<!-- SCRIPTS_INSERTION_POINT -->",
|
||||
f"{new_scripts}\n<!-- SCRIPTS_INSERTION_POINT -->",
|
||||
)
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _build_content_html(self, context: dict) -> str:
|
||||
"""
|
||||
Build content HTML using context data.
|
||||
"""
|
||||
return (
|
||||
CONTENT_TEMPLATE_SUMMARY.replace(
|
||||
"{user_name}", context.get("user_name", "User")
|
||||
)
|
||||
.replace(
|
||||
"{current_date_time_str}", context.get("current_date_time_str", "")
|
||||
)
|
||||
.replace("{current_year}", context.get("current_year", ""))
|
||||
.replace("{summary_html}", context.get("summary_html", ""))
|
||||
.replace("{keypoints_html}", context.get("keypoints_html", ""))
|
||||
.replace("{actions_html}", context.get("actions_html", ""))
|
||||
)
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[Dict[str, Any]] = None,
|
||||
__event_emitter__: Optional[Any] = None,
|
||||
__request__: Optional[Request] = None,
|
||||
) -> Optional[dict]:
|
||||
logger.info("Action: Deep Reading Started (v2.0.0)")
|
||||
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
user_language = (
|
||||
__user__[0].get("language", "en-US") if __user__ else "en-US"
|
||||
)
|
||||
user_name = __user__[0].get("name", "User") if __user__[0] else "User"
|
||||
user_id = (
|
||||
__user__[0]["id"]
|
||||
if __user__ and "id" in __user__[0]
|
||||
else "unknown_user"
|
||||
)
|
||||
elif isinstance(__user__, dict):
|
||||
user_language = __user__.get("language", "en-US")
|
||||
user_name = __user__.get("name", "User")
|
||||
user_id = __user__.get("id", "unknown_user")
|
||||
|
||||
now = datetime.now()
|
||||
current_date_time_str = now.strftime("%B %d, %Y %H:%M:%S")
|
||||
current_weekday = now.strftime("%A")
|
||||
current_year = now.strftime("%Y")
|
||||
current_timezone_str = "Unknown Timezone"
|
||||
|
||||
original_content = ""
|
||||
try:
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
raise ValueError("Unable to get valid user message content.")
|
||||
|
||||
# Get last N messages based on MESSAGE_COUNT
|
||||
message_count = min(self.valves.MESSAGE_COUNT, len(messages))
|
||||
recent_messages = messages[-message_count:]
|
||||
|
||||
# Aggregate content from selected messages with labels
|
||||
aggregated_parts = []
|
||||
for i, msg in enumerate(recent_messages, 1):
|
||||
text_content = self._extract_text_content(msg.get("content"))
|
||||
if text_content:
|
||||
role = msg.get("role", "unknown")
|
||||
role_label = (
|
||||
"User"
|
||||
if role == "user"
|
||||
else "Assistant" if role == "assistant" else role
|
||||
)
|
||||
aggregated_parts.append(f"{text_content}")
|
||||
|
||||
if not aggregated_parts:
|
||||
raise ValueError("Unable to get valid user message content.")
|
||||
|
||||
original_content = "\n\n---\n\n".join(aggregated_parts)
|
||||
|
||||
if len(original_content) < self.valves.MIN_TEXT_LENGTH:
|
||||
short_text_message = f"Text content too short ({len(original_content)} chars), recommended at least {self.valves.MIN_TEXT_LENGTH} chars for effective deep analysis.\n\n💡 Tip: For short texts, consider using '⚡ Flash Card' for quick refinement."
|
||||
await self._emit_notification(
|
||||
__event_emitter__, short_text_message, "warning"
|
||||
)
|
||||
return {
|
||||
"messages": [
|
||||
{"role": "assistant", "content": f"⚠️ {short_text_message}"}
|
||||
]
|
||||
}
|
||||
|
||||
# Recommend for longer texts
|
||||
if len(original_content) < self.valves.RECOMMENDED_MIN_LENGTH:
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"Text length is {len(original_content)} chars. Recommended {self.valves.RECOMMENDED_MIN_LENGTH}+ chars for best analysis results.",
|
||||
"info",
|
||||
)
|
||||
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
"📖 Deep Reading started, analyzing deeply...",
|
||||
"info",
|
||||
)
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"📖 Deep Reading: Analyzing text, extracting essence...",
|
||||
False,
|
||||
)
|
||||
|
||||
formatted_user_prompt = USER_PROMPT_GENERATE_SUMMARY.format(
|
||||
user_name=user_name,
|
||||
current_date_time_str=current_date_time_str,
|
||||
current_weekday=current_weekday,
|
||||
current_timezone_str=current_timezone_str,
|
||||
user_language=user_language,
|
||||
long_text_content=original_content,
|
||||
)
|
||||
|
||||
# Determine model to use
|
||||
target_model = self.valves.MODEL_ID
|
||||
if not target_model:
|
||||
target_model = body.get("model")
|
||||
|
||||
llm_payload = {
|
||||
"model": target_model,
|
||||
"messages": [
|
||||
{"role": "system", "content": SYSTEM_PROMPT_READING_ASSISTANT},
|
||||
{"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: {user_id}")
|
||||
|
||||
llm_response = await generate_chat_completion(
|
||||
__request__, llm_payload, user_obj
|
||||
)
|
||||
assistant_response_content = llm_response["choices"][0]["message"][
|
||||
"content"
|
||||
]
|
||||
|
||||
processed_content = self._process_llm_output(assistant_response_content)
|
||||
|
||||
context = {
|
||||
"user_language": user_language,
|
||||
"user_name": user_name,
|
||||
"current_date_time_str": current_date_time_str,
|
||||
"current_weekday": current_weekday,
|
||||
"current_year": current_year,
|
||||
**processed_content,
|
||||
}
|
||||
|
||||
content_html = self._build_content_html(context)
|
||||
|
||||
# Extract existing HTML if any
|
||||
existing_html_block = ""
|
||||
match = re.search(
|
||||
r"```html\s*(<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?)```",
|
||||
original_content,
|
||||
)
|
||||
if match:
|
||||
existing_html_block = match.group(1)
|
||||
|
||||
if self.valves.CLEAR_PREVIOUS_HTML:
|
||||
original_content = self._remove_existing_html(original_content)
|
||||
final_html = self._merge_html(
|
||||
"", content_html, CSS_TEMPLATE_SUMMARY, "", user_language
|
||||
)
|
||||
else:
|
||||
if existing_html_block:
|
||||
original_content = self._remove_existing_html(original_content)
|
||||
final_html = self._merge_html(
|
||||
existing_html_block,
|
||||
content_html,
|
||||
CSS_TEMPLATE_SUMMARY,
|
||||
"",
|
||||
user_language,
|
||||
)
|
||||
else:
|
||||
final_html = self._merge_html(
|
||||
"", content_html, CSS_TEMPLATE_SUMMARY, "", user_language
|
||||
)
|
||||
|
||||
html_embed_tag = f"```html\n{final_html}\n```"
|
||||
body["messages"][-1]["content"] = f"{original_content}\n\n{html_embed_tag}"
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "📖 Deep Reading: Analysis complete!", True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"📖 Deep Reading complete, {user_name}! Deep analysis report generated.",
|
||||
"success",
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
error_message = f"Deep Reading processing failed: {str(e)}"
|
||||
logger.error(f"Deep Reading Error: {error_message}", exc_info=True)
|
||||
user_facing_error = f"Sorry, Deep Reading encountered an error while processing: {str(e)}.\nPlease check Open WebUI backend logs for more details."
|
||||
body["messages"][-1][
|
||||
"content"
|
||||
] = f"{original_content}\n\n❌ **Error:** {user_facing_error}"
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "Deep Reading: Processing failed.", True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"Deep Reading processing failed, {user_name}!",
|
||||
"error",
|
||||
)
|
||||
|
||||
return body
|
||||
@@ -1,663 +0,0 @@
|
||||
"""
|
||||
title: 精读 (Deep Reading)
|
||||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0Ij48ZGVmcz48bGluZWFyR3JhZGllbnQgaWQ9ImciIHgxPSIwIiB5MT0iMCIgeDI9IjEiIHkyPSIxIj48c3RvcCBvZmZzZXQ9IjAlIiBzdG9wLWNvbG9yPSIjNDI4NWY0Ii8+PHN0b3Agb2Zmc2V0PSIxMDAlIiBzdG9wLWNvbG9yPSIjMWU4OGU1Ii8+PC9saW5lYXJHcmFkaWVudD48L2RlZnM+PHBhdGggZD0iTTYgMmg4bDYgNnYxMmEyIDIgMCAwIDEtMiAySDZhMiAyIDAgMCAxLTItMlY0YTIgMiAwIDAgMSAyLTJ6IiBmaWxsPSJ1cmwoI2cpIi8+PHBhdGggZD0iTTE0IDJsNiA2aC02eiIgZmlsbD0iIzFlODhlNSIgb3BhY2l0eT0iMC42Ii8+PGxpbmUgeDE9IjgiIHkxPSIxMyIgeDI9IjE2IiB5Mj0iMTMiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiLz48bGluZSB4MT0iOCIgeTE9IjE3IiB4Mj0iMTQiIHkyPSIxNyIgc3Ryb2tlPSIjZmZmIiBzdHJva2Utd2lkdGg9IjEuNSIvPjxjaXJjbGUgY3g9IjE2IiBjeT0iMTgiIHI9IjMiIGZpbGw9IiNmZmQ3MDAiLz48cGF0aCBkPSJNMTYgMTZsMS41IDEuNSIgc3Ryb2tlPSIjNDI4NWY0IiBzdHJva2Utd2lkdGg9IjIiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPjwvc3ZnPg==
|
||||
version: 0.1.2
|
||||
description: 深度分析长篇文本,提炼详细摘要、关键信息点和可执行的行动建议,适合工作和学习场景。
|
||||
requirements: jinja2, markdown
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Optional, Dict, Any
|
||||
import logging
|
||||
import re
|
||||
from fastapi import Request
|
||||
from datetime import datetime
|
||||
import pytz
|
||||
import markdown
|
||||
from jinja2 import Template
|
||||
|
||||
from open_webui.utils.chat import generate_chat_completion
|
||||
from open_webui.models.users import Users
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
|
||||
)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# =================================================================
|
||||
# HTML 容器模板 (支持多插件共存与网格布局)
|
||||
# =================================================================
|
||||
HTML_WRAPPER_TEMPLATE = """
|
||||
<!-- OPENWEBUI_PLUGIN_OUTPUT -->
|
||||
<!DOCTYPE html>
|
||||
<html lang="{user_language}">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<style>
|
||||
body {
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
|
||||
margin: 0;
|
||||
padding: 10px;
|
||||
background-color: transparent;
|
||||
}
|
||||
#main-container {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 20px;
|
||||
align-items: flex-start;
|
||||
width: 100%;
|
||||
}
|
||||
.plugin-item {
|
||||
flex: 1 1 400px; /* 默认宽度,允许伸缩 */
|
||||
min-width: 300px;
|
||||
background: white;
|
||||
border-radius: 12px;
|
||||
box-shadow: 0 4px 6px rgba(0,0,0,0.05);
|
||||
overflow: hidden;
|
||||
border: 1px solid #e5e7eb;
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
.plugin-item:hover {
|
||||
box-shadow: 0 10px 15px rgba(0,0,0,0.1);
|
||||
}
|
||||
@media (max-width: 768px) {
|
||||
.plugin-item { flex: 1 1 100%; }
|
||||
}
|
||||
/* STYLES_INSERTION_POINT */
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<div id="main-container">
|
||||
<!-- CONTENT_INSERTION_POINT -->
|
||||
</div>
|
||||
<!-- SCRIPTS_INSERTION_POINT -->
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
# =================================================================
|
||||
# 内部 LLM 提示词设计
|
||||
# =================================================================
|
||||
|
||||
SYSTEM_PROMPT_READING_ASSISTANT = """
|
||||
你是一个专业的深度文本分析专家,擅长精读长篇文本并提炼精华。你的任务是进行全面、深入的分析。
|
||||
|
||||
请提供以下内容:
|
||||
1. **详细摘要**:用 2-3 段话全面总结文本的核心内容,确保准确性和完整性。不要过于简略,要让读者充分理解文本主旨。
|
||||
2. **关键信息点**:列出 5-8 个最重要的事实、观点或论据。每个信息点应该:
|
||||
- 具体且有深度
|
||||
- 包含必要的细节和背景
|
||||
- 使用 Markdown 列表格式
|
||||
3. **行动建议**:从文本中识别并提炼出具体的、可执行的行动项。每个建议应该:
|
||||
- 明确且可操作
|
||||
- 包含执行的优先级或时间建议
|
||||
- 如果没有明确的行动项,可以提供学习建议或思考方向
|
||||
|
||||
请严格遵循以下指导原则:
|
||||
- **语言**:所有输出必须使用用户指定的语言。
|
||||
- **格式**:请严格按照以下 Markdown 格式输出,确保每个部分都有明确的标题:
|
||||
## 摘要
|
||||
[这里是详细的摘要内容,2-3段话,可以使用 Markdown 进行**加粗**或*斜体*强调重点]
|
||||
|
||||
## 关键信息点
|
||||
- [关键点1:包含具体细节和背景]
|
||||
- [关键点2:包含具体细节和背景]
|
||||
- [关键点3:包含具体细节和背景]
|
||||
- [至少5个,最多8个关键点]
|
||||
|
||||
## 行动建议
|
||||
- [行动项1:具体、可执行,包含优先级]
|
||||
- [行动项2:具体、可执行,包含优先级]
|
||||
- [如果没有明确行动项,提供学习建议或思考方向]
|
||||
- **深度优先**:分析要深入、全面,不要浮于表面。
|
||||
- **行动导向**:重点关注可执行的建议和下一步行动。
|
||||
- **只输出分析结果**:不要包含任何额外的寒暄、解释或引导性文字。
|
||||
"""
|
||||
|
||||
USER_PROMPT_GENERATE_SUMMARY = """
|
||||
请对以下长篇文本进行深度分析,提供:
|
||||
1. 详细的摘要(2-3段话,全面概括文本内容)
|
||||
2. 关键信息点列表(5-8个,包含具体细节)
|
||||
3. 可执行的行动建议(具体、明确,包含优先级)
|
||||
|
||||
---
|
||||
**用户上下文信息:**
|
||||
用户姓名: {user_name}
|
||||
当前日期时间: {current_date_time_str}
|
||||
当前星期: {current_weekday}
|
||||
当前时区: {current_timezone_str}
|
||||
用户语言: {user_language}
|
||||
---
|
||||
|
||||
**长篇文本内容:**
|
||||
```
|
||||
{long_text_content}
|
||||
```
|
||||
|
||||
请进行深入、全面的分析,重点关注可执行的行动建议。
|
||||
"""
|
||||
|
||||
# =================================================================
|
||||
# 前端 HTML 模板 (Jinja2 语法)
|
||||
# =================================================================
|
||||
|
||||
CSS_TEMPLATE_SUMMARY = """
|
||||
:root {
|
||||
--primary-color: #4285f4;
|
||||
--secondary-color: #1e88e5;
|
||||
--action-color: #34a853;
|
||||
--background-color: #f8f9fa;
|
||||
--card-bg-color: #ffffff;
|
||||
--text-color: #202124;
|
||||
--muted-text-color: #5f6368;
|
||||
--border-color: #dadce0;
|
||||
--header-gradient: linear-gradient(135deg, #4285f4, #1e88e5);
|
||||
--shadow: 0 1px 3px rgba(60,64,67,.3);
|
||||
--border-radius: 8px;
|
||||
--font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
|
||||
}
|
||||
.summary-container-wrapper {
|
||||
font-family: var(--font-family);
|
||||
line-height: 1.8;
|
||||
color: var(--text-color);
|
||||
height: 100%;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
}
|
||||
.summary-container-wrapper .header {
|
||||
background: var(--header-gradient);
|
||||
color: white;
|
||||
padding: 20px 24px;
|
||||
text-align: center;
|
||||
}
|
||||
.summary-container-wrapper .header h1 {
|
||||
margin: 0;
|
||||
font-size: 1.5em;
|
||||
font-weight: 500;
|
||||
letter-spacing: -0.5px;
|
||||
}
|
||||
.summary-container-wrapper .user-context {
|
||||
font-size: 0.8em;
|
||||
color: var(--muted-text-color);
|
||||
background-color: #f1f3f4;
|
||||
padding: 8px 16px;
|
||||
display: flex;
|
||||
justify-content: space-around;
|
||||
flex-wrap: wrap;
|
||||
border-bottom: 1px solid var(--border-color);
|
||||
}
|
||||
.summary-container-wrapper .user-context span { margin: 2px 8px; }
|
||||
.summary-container-wrapper .content { padding: 20px; flex-grow: 1; }
|
||||
.summary-container-wrapper .section {
|
||||
margin-bottom: 16px;
|
||||
padding-bottom: 16px;
|
||||
border-bottom: 1px solid #e8eaed;
|
||||
}
|
||||
.summary-container-wrapper .section:last-child {
|
||||
border-bottom: none;
|
||||
margin-bottom: 0;
|
||||
padding-bottom: 0;
|
||||
}
|
||||
.summary-container-wrapper .section h2 {
|
||||
margin-top: 0;
|
||||
margin-bottom: 12px;
|
||||
font-size: 1.2em;
|
||||
font-weight: 500;
|
||||
color: var(--text-color);
|
||||
display: flex;
|
||||
align-items: center;
|
||||
padding-bottom: 8px;
|
||||
border-bottom: 2px solid var(--primary-color);
|
||||
}
|
||||
.summary-container-wrapper .section h2 .icon {
|
||||
margin-right: 8px;
|
||||
font-size: 1.1em;
|
||||
line-height: 1;
|
||||
}
|
||||
.summary-container-wrapper .summary-section h2 { border-bottom-color: var(--primary-color); }
|
||||
.summary-container-wrapper .keypoints-section h2 { border-bottom-color: var(--secondary-color); }
|
||||
.summary-container-wrapper .actions-section h2 { border-bottom-color: var(--action-color); }
|
||||
.summary-container-wrapper .html-content {
|
||||
font-size: 0.95em;
|
||||
line-height: 1.7;
|
||||
}
|
||||
.summary-container-wrapper .html-content p:first-child { margin-top: 0; }
|
||||
.summary-container-wrapper .html-content p:last-child { margin-bottom: 0; }
|
||||
.summary-container-wrapper .html-content ul {
|
||||
list-style: none;
|
||||
padding-left: 0;
|
||||
margin: 12px 0;
|
||||
}
|
||||
.summary-container-wrapper .html-content li {
|
||||
padding: 8px 0 8px 24px;
|
||||
position: relative;
|
||||
margin-bottom: 6px;
|
||||
line-height: 1.6;
|
||||
}
|
||||
.summary-container-wrapper .html-content li::before {
|
||||
position: absolute;
|
||||
left: 0;
|
||||
top: 8px;
|
||||
font-family: 'Arial';
|
||||
font-weight: bold;
|
||||
font-size: 1em;
|
||||
}
|
||||
.summary-container-wrapper .keypoints-section .html-content li::before {
|
||||
content: '•';
|
||||
color: var(--secondary-color);
|
||||
font-size: 1.3em;
|
||||
top: 5px;
|
||||
}
|
||||
.summary-container-wrapper .actions-section .html-content li::before {
|
||||
content: '▸';
|
||||
color: var(--action-color);
|
||||
}
|
||||
.summary-container-wrapper .no-content {
|
||||
color: var(--muted-text-color);
|
||||
font-style: italic;
|
||||
padding: 12px;
|
||||
background: #f8f9fa;
|
||||
border-radius: 4px;
|
||||
}
|
||||
.summary-container-wrapper .footer {
|
||||
text-align: center;
|
||||
padding: 16px;
|
||||
font-size: 0.8em;
|
||||
color: #5f6368;
|
||||
background-color: #f8f9fa;
|
||||
border-top: 1px solid var(--border-color);
|
||||
}
|
||||
"""
|
||||
|
||||
CONTENT_TEMPLATE_SUMMARY = """
|
||||
<div class="summary-container-wrapper">
|
||||
<div class="header">
|
||||
<h1>📖 精读:深度分析报告</h1>
|
||||
</div>
|
||||
<div class="user-context">
|
||||
<span><strong>用户:</strong> {user_name}</span>
|
||||
<span><strong>时间:</strong> {current_date_time_str}</span>
|
||||
</div>
|
||||
<div class="content">
|
||||
<div class="section summary-section">
|
||||
<h2><span class="icon">📝</span>详细摘要</h2>
|
||||
<div class="html-content">{summary_html}</div>
|
||||
</div>
|
||||
<div class="section keypoints-section">
|
||||
<h2><span class="icon">💡</span>关键信息点</h2>
|
||||
<div class="html-content">{keypoints_html}</div>
|
||||
</div>
|
||||
<div class="section actions-section">
|
||||
<h2><span class="icon">🎯</span>行动建议</h2>
|
||||
<div class="html-content">{actions_html}</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="footer">
|
||||
<p>© {current_year} 精读 - 深度文本分析服务</p>
|
||||
</div>
|
||||
</div>
|
||||
"""
|
||||
|
||||
|
||||
class Action:
|
||||
class Valves(BaseModel):
|
||||
SHOW_STATUS: bool = Field(
|
||||
default=True, description="是否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=200,
|
||||
description="进行深度分析所需的最小文本长度(字符数)。建议200字符以上。",
|
||||
)
|
||||
RECOMMENDED_MIN_LENGTH: int = Field(
|
||||
default=500, description="建议的最小文本长度,以获得最佳分析效果。"
|
||||
)
|
||||
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)。",
|
||||
)
|
||||
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。",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
self.weekday_map = {
|
||||
"Monday": "星期一",
|
||||
"Tuesday": "星期二",
|
||||
"Wednesday": "星期三",
|
||||
"Thursday": "星期四",
|
||||
"Friday": "星期五",
|
||||
"Saturday": "星期六",
|
||||
"Sunday": "星期日",
|
||||
}
|
||||
|
||||
def _process_llm_output(self, llm_output: str) -> Dict[str, str]:
|
||||
"""
|
||||
解析LLM的Markdown输出,将其转换为HTML片段。
|
||||
"""
|
||||
summary_match = re.search(
|
||||
r"##\s*摘要\s*\n(.*?)(?=\n##|$)", llm_output, re.DOTALL
|
||||
)
|
||||
keypoints_match = re.search(
|
||||
r"##\s*关键信息点\s*\n(.*?)(?=\n##|$)", llm_output, re.DOTALL
|
||||
)
|
||||
actions_match = re.search(
|
||||
r"##\s*行动建议\s*\n(.*?)(?=\n##|$)", llm_output, re.DOTALL
|
||||
)
|
||||
|
||||
summary_md = summary_match.group(1).strip() if summary_match else ""
|
||||
keypoints_md = keypoints_match.group(1).strip() if keypoints_match else ""
|
||||
actions_md = actions_match.group(1).strip() if actions_match else ""
|
||||
|
||||
if not any([summary_md, keypoints_md, actions_md]):
|
||||
summary_md = llm_output.strip()
|
||||
logger.warning("LLM输出未遵循预期的Markdown格式。将整个输出视为摘要。")
|
||||
|
||||
# 使用 'nl2br' 扩展将换行符 \n 转换为 <br>
|
||||
md_extensions = ["nl2br"]
|
||||
summary_html = (
|
||||
markdown.markdown(summary_md, extensions=md_extensions)
|
||||
if summary_md
|
||||
else '<p class="no-content">未能提取摘要信息。</p>'
|
||||
)
|
||||
keypoints_html = (
|
||||
markdown.markdown(keypoints_md, extensions=md_extensions)
|
||||
if keypoints_md
|
||||
else '<p class="no-content">未能提取关键信息点。</p>'
|
||||
)
|
||||
actions_html = (
|
||||
markdown.markdown(actions_md, extensions=md_extensions)
|
||||
if actions_md
|
||||
else '<p class="no-content">暂无明确的行动建议。</p>'
|
||||
)
|
||||
|
||||
return {
|
||||
"summary_html": summary_html,
|
||||
"keypoints_html": keypoints_html,
|
||||
"actions_html": actions_html,
|
||||
}
|
||||
|
||||
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}}
|
||||
)
|
||||
|
||||
async def _emit_notification(self, emitter, content: str, ntype: str = "info"):
|
||||
"""发送通知事件 (info/success/warning/error)。"""
|
||||
if emitter:
|
||||
await emitter(
|
||||
{"type": "notification", "data": {"type": ntype, "content": content}}
|
||||
)
|
||||
|
||||
def _remove_existing_html(self, content: str) -> str:
|
||||
"""移除内容中已有的插件生成 HTML 代码块 (通过标记识别)。"""
|
||||
pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"
|
||||
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"""
|
||||
if isinstance(content, str):
|
||||
return content
|
||||
elif isinstance(content, list):
|
||||
# 多模态消息: [{"type": "text", "text": "..."}, {"type": "image_url", ...}]
|
||||
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 ""
|
||||
|
||||
def _merge_html(
|
||||
self,
|
||||
existing_html_code: str,
|
||||
new_content: str,
|
||||
new_styles: str = "",
|
||||
new_scripts: str = "",
|
||||
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。
|
||||
"""
|
||||
if (
|
||||
"<!-- OPENWEBUI_PLUGIN_OUTPUT -->" in existing_html_code
|
||||
and "<!-- CONTENT_INSERTION_POINT -->" in existing_html_code
|
||||
):
|
||||
base_html = existing_html_code
|
||||
base_html = re.sub(r"^```html\s*", "", base_html)
|
||||
base_html = re.sub(r"\s*```$", "", base_html)
|
||||
else:
|
||||
base_html = HTML_WRAPPER_TEMPLATE.replace("{user_language}", user_language)
|
||||
|
||||
wrapped_content = f'<div class="plugin-item">\n{new_content}\n</div>'
|
||||
|
||||
if new_styles:
|
||||
base_html = base_html.replace(
|
||||
"/* STYLES_INSERTION_POINT */",
|
||||
f"{new_styles}\n/* STYLES_INSERTION_POINT */",
|
||||
)
|
||||
|
||||
base_html = base_html.replace(
|
||||
"<!-- CONTENT_INSERTION_POINT -->",
|
||||
f"{wrapped_content}\n<!-- CONTENT_INSERTION_POINT -->",
|
||||
)
|
||||
|
||||
if new_scripts:
|
||||
base_html = base_html.replace(
|
||||
"<!-- SCRIPTS_INSERTION_POINT -->",
|
||||
f"{new_scripts}\n<!-- SCRIPTS_INSERTION_POINT -->",
|
||||
)
|
||||
|
||||
return base_html.strip()
|
||||
|
||||
def _build_content_html(self, context: dict) -> str:
|
||||
"""
|
||||
使用上下文数据构建内容 HTML。
|
||||
"""
|
||||
return (
|
||||
CONTENT_TEMPLATE_SUMMARY.replace(
|
||||
"{user_name}", context.get("user_name", "用户")
|
||||
)
|
||||
.replace(
|
||||
"{current_date_time_str}", context.get("current_date_time_str", "")
|
||||
)
|
||||
.replace("{current_year}", context.get("current_year", ""))
|
||||
.replace("{summary_html}", context.get("summary_html", ""))
|
||||
.replace("{keypoints_html}", context.get("keypoints_html", ""))
|
||||
.replace("{actions_html}", context.get("actions_html", ""))
|
||||
)
|
||||
|
||||
async def action(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[Dict[str, Any]] = None,
|
||||
__event_emitter__: Optional[Any] = None,
|
||||
__request__: Optional[Request] = None,
|
||||
) -> Optional[dict]:
|
||||
logger.info("Action: 精读启动 (v2.0.0 - Deep Reading)")
|
||||
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
user_language = (
|
||||
__user__[0].get("language", "zh-CN") if __user__ else "zh-CN"
|
||||
)
|
||||
user_name = __user__[0].get("name", "用户") if __user__[0] else "用户"
|
||||
user_id = (
|
||||
__user__[0]["id"]
|
||||
if __user__ and "id" in __user__[0]
|
||||
else "unknown_user"
|
||||
)
|
||||
elif isinstance(__user__, dict):
|
||||
user_language = __user__.get("language", "zh-CN")
|
||||
user_name = __user__.get("name", "用户")
|
||||
user_id = __user__.get("id", "unknown_user")
|
||||
|
||||
now = datetime.now()
|
||||
current_date_time_str = now.strftime("%Y年%m月%d日 %H:%M:%S")
|
||||
current_weekday_en = now.strftime("%A")
|
||||
current_weekday = self.weekday_map.get(current_weekday_en, current_weekday_en)
|
||||
current_year = now.strftime("%Y")
|
||||
current_timezone_str = "未知时区"
|
||||
|
||||
original_content = ""
|
||||
try:
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
raise ValueError("无法获取有效的用户消息内容。")
|
||||
|
||||
# Get last N messages based on MESSAGE_COUNT
|
||||
message_count = min(self.valves.MESSAGE_COUNT, len(messages))
|
||||
recent_messages = messages[-message_count:]
|
||||
|
||||
# Aggregate content from selected messages with labels
|
||||
aggregated_parts = []
|
||||
for i, msg in enumerate(recent_messages, 1):
|
||||
text_content = self._extract_text_content(msg.get("content"))
|
||||
if text_content:
|
||||
role = msg.get("role", "unknown")
|
||||
role_label = (
|
||||
"用户"
|
||||
if role == "user"
|
||||
else "助手" if role == "assistant" else role
|
||||
)
|
||||
aggregated_parts.append(f"{text_content}")
|
||||
|
||||
if not aggregated_parts:
|
||||
raise ValueError("无法获取有效的用户消息内容。")
|
||||
|
||||
original_content = "\n\n---\n\n".join(aggregated_parts)
|
||||
|
||||
if len(original_content) < self.valves.MIN_TEXT_LENGTH:
|
||||
short_text_message = f"文本内容过短({len(original_content)}字符),建议至少{self.valves.MIN_TEXT_LENGTH}字符以获得有效的深度分析。\n\n💡 提示:对于短文本,建议使用'⚡ 闪记卡'进行快速提炼。"
|
||||
await self._emit_notification(
|
||||
__event_emitter__, short_text_message, "warning"
|
||||
)
|
||||
return {
|
||||
"messages": [
|
||||
{"role": "assistant", "content": f"⚠️ {short_text_message}"}
|
||||
]
|
||||
}
|
||||
|
||||
# Recommend for longer texts
|
||||
if len(original_content) < self.valves.RECOMMENDED_MIN_LENGTH:
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"文本长度为{len(original_content)}字符。建议{self.valves.RECOMMENDED_MIN_LENGTH}字符以上可获得更好的分析效果。",
|
||||
"info",
|
||||
)
|
||||
|
||||
await self._emit_notification(
|
||||
__event_emitter__, "📖 精读已启动,正在进行深度分析...", "info"
|
||||
)
|
||||
await self._emit_status(
|
||||
__event_emitter__, "📖 精读: 深入分析文本,提炼精华...", False
|
||||
)
|
||||
|
||||
formatted_user_prompt = USER_PROMPT_GENERATE_SUMMARY.format(
|
||||
user_name=user_name,
|
||||
current_date_time_str=current_date_time_str,
|
||||
current_weekday=current_weekday,
|
||||
current_timezone_str=current_timezone_str,
|
||||
user_language=user_language,
|
||||
long_text_content=original_content,
|
||||
)
|
||||
|
||||
# 确定使用的模型
|
||||
target_model = self.valves.MODEL_ID
|
||||
if not target_model:
|
||||
target_model = body.get("model")
|
||||
|
||||
llm_payload = {
|
||||
"model": target_model,
|
||||
"messages": [
|
||||
{"role": "system", "content": SYSTEM_PROMPT_READING_ASSISTANT},
|
||||
{"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, 用户ID: {user_id}")
|
||||
|
||||
llm_response = await generate_chat_completion(
|
||||
__request__, llm_payload, user_obj
|
||||
)
|
||||
assistant_response_content = llm_response["choices"][0]["message"][
|
||||
"content"
|
||||
]
|
||||
|
||||
processed_content = self._process_llm_output(assistant_response_content)
|
||||
|
||||
context = {
|
||||
"user_language": user_language,
|
||||
"user_name": user_name,
|
||||
"current_date_time_str": current_date_time_str,
|
||||
"current_weekday": current_weekday,
|
||||
"current_year": current_year,
|
||||
**processed_content,
|
||||
}
|
||||
|
||||
content_html = self._build_content_html(context)
|
||||
|
||||
# Extract existing HTML if any
|
||||
existing_html_block = ""
|
||||
match = re.search(
|
||||
r"```html\s*(<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?)```",
|
||||
original_content,
|
||||
)
|
||||
if match:
|
||||
existing_html_block = match.group(1)
|
||||
|
||||
if self.valves.CLEAR_PREVIOUS_HTML:
|
||||
original_content = self._remove_existing_html(original_content)
|
||||
final_html = self._merge_html(
|
||||
"", content_html, CSS_TEMPLATE_SUMMARY, "", user_language
|
||||
)
|
||||
else:
|
||||
if existing_html_block:
|
||||
original_content = self._remove_existing_html(original_content)
|
||||
final_html = self._merge_html(
|
||||
existing_html_block,
|
||||
content_html,
|
||||
CSS_TEMPLATE_SUMMARY,
|
||||
"",
|
||||
user_language,
|
||||
)
|
||||
else:
|
||||
final_html = self._merge_html(
|
||||
"", content_html, CSS_TEMPLATE_SUMMARY, "", user_language
|
||||
)
|
||||
|
||||
html_embed_tag = f"```html\n{final_html}\n```"
|
||||
body["messages"][-1]["content"] = f"{original_content}\n\n{html_embed_tag}"
|
||||
|
||||
await self._emit_status(__event_emitter__, "📖 精读: 分析完成!", True)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"📖 精读完成,{user_name}!深度分析报告已生成。",
|
||||
"success",
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
error_message = f"精读处理失败: {str(e)}"
|
||||
logger.error(f"精读错误: {error_message}", exc_info=True)
|
||||
user_facing_error = f"抱歉, 精读在处理时遇到错误: {str(e)}。\n请检查Open WebUI后端日志获取更多详情。"
|
||||
body["messages"][-1][
|
||||
"content"
|
||||
] = f"{original_content}\n\n❌ **错误:** {user_facing_error}"
|
||||
|
||||
await self._emit_status(__event_emitter__, "精读: 处理失败。", True)
|
||||
await self._emit_notification(
|
||||
__event_emitter__, f"精读处理失败, {user_name}!", "error"
|
||||
)
|
||||
|
||||
return body
|
||||
@@ -6,6 +6,7 @@ author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
description: Reduces token consumption in long conversations while maintaining coherence through intelligent summarization and message compression.
|
||||
version: 1.1.0
|
||||
openwebui_id: b1655bc8-6de9-4cad-8cb5-a6f7829a02ce
|
||||
license: MIT
|
||||
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
@@ -6,6 +6,7 @@ author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
description: 通过智能摘要和消息压缩,降低长对话的 token 消耗,同时保持对话连贯性。
|
||||
version: 1.1.0
|
||||
openwebui_id: 5c0617cb-a9e4-4bd6-a440-d276534ebd18
|
||||
license: MIT
|
||||
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
519
plugins/filters/markdown_normalizer/markdown_normalizer.py
Normal file
@@ -0,0 +1,519 @@
|
||||
"""
|
||||
title: Markdown Normalizer
|
||||
author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 1.0.0
|
||||
description: A production-grade content normalizer filter that fixes common Markdown formatting issues in LLM outputs, such as broken code blocks, LaTeX formulas, and list formatting.
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Optional, List, Callable
|
||||
import re
|
||||
import logging
|
||||
import logging
|
||||
import asyncio
|
||||
import json
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
# Configure logging
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class NormalizerConfig:
|
||||
"""Configuration class for enabling/disabling specific normalization rules"""
|
||||
|
||||
enable_escape_fix: bool = True # Fix excessive escape characters
|
||||
enable_thought_tag_fix: bool = True # Normalize thought tags
|
||||
enable_code_block_fix: bool = True # Fix code block formatting
|
||||
enable_latex_fix: bool = True # Fix LaTeX formula formatting
|
||||
enable_list_fix: bool = (
|
||||
False # Fix list item newlines (default off as it can be aggressive)
|
||||
)
|
||||
enable_unclosed_block_fix: bool = True # Auto-close unclosed code blocks
|
||||
enable_fullwidth_symbol_fix: bool = False # Fix full-width symbols in code blocks
|
||||
enable_mermaid_fix: bool = True # Fix common Mermaid syntax errors
|
||||
enable_heading_fix: bool = (
|
||||
True # Fix missing space in headings (#Header -> # Header)
|
||||
)
|
||||
enable_table_fix: bool = True # Fix missing closing pipe in tables
|
||||
enable_xml_tag_cleanup: bool = True # Cleanup leftover XML tags
|
||||
|
||||
# Custom cleaner functions (for advanced extension)
|
||||
custom_cleaners: List[Callable[[str], str]] = field(default_factory=list)
|
||||
|
||||
|
||||
class ContentNormalizer:
|
||||
"""LLM Output Content Normalizer - Production Grade Implementation"""
|
||||
|
||||
# --- 1. Pre-compiled Regex Patterns (Performance Optimization) ---
|
||||
_PATTERNS = {
|
||||
# Code block prefix: if ``` is not at start of line or file
|
||||
"code_block_prefix": re.compile(r"(?<!^)(?<!\n)(```)", re.MULTILINE),
|
||||
# Code block suffix: ```lang followed by non-whitespace (no newline)
|
||||
"code_block_suffix": re.compile(r"(```[\w\+\-\.]*)[ \t]+([^\n\r])"),
|
||||
# Code block indent: whitespace at start of line + ```
|
||||
"code_block_indent": re.compile(r"^[ \t]+(```)", re.MULTILINE),
|
||||
# Thought tag: </thought> followed by optional whitespace/newlines
|
||||
"thought_end": re.compile(
|
||||
r"</(thought|think|thinking)>[ \t]*\n*", re.IGNORECASE
|
||||
),
|
||||
"thought_start": re.compile(r"<(thought|think|thinking)>", re.IGNORECASE),
|
||||
# LaTeX block: \[ ... \]
|
||||
"latex_bracket_block": re.compile(r"\\\[(.+?)\\\]", re.DOTALL),
|
||||
# LaTeX inline: \( ... \)
|
||||
"latex_paren_inline": re.compile(r"\\\((.+?)\\\)"),
|
||||
# List item: non-newline + digit + dot + space
|
||||
"list_item": re.compile(r"([^\n])(\d+\. )"),
|
||||
# XML artifacts (e.g. Claude's)
|
||||
"xml_artifacts": re.compile(
|
||||
r"</?(?:antArtifact|antThinking|artifact)[^>]*>", re.IGNORECASE
|
||||
),
|
||||
# Mermaid: Match various node shapes and quote unquoted labels
|
||||
# Fix "reverse optimization": Must precisely match shape delimiters to avoid breaking structure
|
||||
# Priority: Longer delimiters match first
|
||||
"mermaid_node": re.compile(
|
||||
r"(\w+)\s*(?:"
|
||||
r"(\(\(\()(?![\"])(.*?)(?<![\"])(\)\)\))|" # (((...))) Double Circle
|
||||
r"(\(\()(?![\"])(.*?)(?<![\"])(\)\))|" # ((...)) Circle
|
||||
r"(\(\[)(?![\"])(.*?)(?<![\"])(\]\))|" # ([...]) Stadium
|
||||
r"(\[\()(?![\"])(.*?)(?<![\"])(\)\])|" # [(...)] Cylinder
|
||||
r"(\[\[)(?![\"])(.*?)(?<![\"])(\]\])|" # [[...]] Subroutine
|
||||
r"(\{\{)(?![\"])(.*?)(?<![\"])(\}\})|" # {{...}} Hexagon
|
||||
r"(\[/)(?![\"])(.*?)(?<![\"])(/\])|" # [/.../] Parallelogram
|
||||
r"(\[\\)(?![\"])(.*?)(?<![\"])(\\\])|" # [\...\] Parallelogram Alt
|
||||
r"(\[/)(?![\"])(.*?)(?<![\"])(\\\])|" # [/...\] Trapezoid
|
||||
r"(\[\\)(?![\"])(.*?)(?<![\"])(/\])|" # [\.../] Trapezoid Alt
|
||||
r"(\()(?![\"])(.*?)(?<![\"])(\))|" # (...) Round
|
||||
r"(\[)(?![\"])(.*?)(?<![\"])(\])|" # [...] Square
|
||||
r"(\{)(?![\"])(.*?)(?<![\"])(\})|" # {...} Rhombus
|
||||
r"(>)(?![\"])(.*?)(?<![\"])(\])" # >...] Asymmetric
|
||||
r")"
|
||||
),
|
||||
# Heading: #Heading -> # Heading
|
||||
"heading_space": re.compile(r"^(#+)([^ \n#])", re.MULTILINE),
|
||||
# Table: | col1 | col2 -> | col1 | col2 |
|
||||
"table_pipe": re.compile(r"^(\|.*[^|\n])$", re.MULTILINE),
|
||||
}
|
||||
|
||||
def __init__(self, config: Optional[NormalizerConfig] = None):
|
||||
self.config = config or NormalizerConfig()
|
||||
self.applied_fixes = []
|
||||
|
||||
def normalize(self, content: str) -> str:
|
||||
"""Main entry point: apply all normalization rules in order"""
|
||||
self.applied_fixes = []
|
||||
if not content:
|
||||
return content
|
||||
|
||||
original_content = content # Keep a copy for logging
|
||||
|
||||
try:
|
||||
# 1. Escape character fix (Must be first)
|
||||
if self.config.enable_escape_fix:
|
||||
original = content
|
||||
content = self._fix_escape_characters(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Escape Chars")
|
||||
|
||||
# 2. Thought tag normalization
|
||||
if self.config.enable_thought_tag_fix:
|
||||
original = content
|
||||
content = self._fix_thought_tags(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Normalize Thought Tags")
|
||||
|
||||
# 3. Code block formatting fix
|
||||
if self.config.enable_code_block_fix:
|
||||
original = content
|
||||
content = self._fix_code_blocks(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Code Blocks")
|
||||
|
||||
# 4. LaTeX formula normalization
|
||||
if self.config.enable_latex_fix:
|
||||
original = content
|
||||
content = self._fix_latex_formulas(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Normalize LaTeX")
|
||||
|
||||
# 5. List formatting fix
|
||||
if self.config.enable_list_fix:
|
||||
original = content
|
||||
content = self._fix_list_formatting(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix List Format")
|
||||
|
||||
# 6. Unclosed code block fix
|
||||
if self.config.enable_unclosed_block_fix:
|
||||
original = content
|
||||
content = self._fix_unclosed_code_blocks(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Close Code Blocks")
|
||||
|
||||
# 7. Full-width symbol fix (in code blocks only)
|
||||
if self.config.enable_fullwidth_symbol_fix:
|
||||
original = content
|
||||
content = self._fix_fullwidth_symbols_in_code(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Full-width Symbols")
|
||||
|
||||
# 8. Mermaid syntax fix
|
||||
if self.config.enable_mermaid_fix:
|
||||
original = content
|
||||
content = self._fix_mermaid_syntax(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Mermaid Syntax")
|
||||
|
||||
# 9. Heading fix
|
||||
if self.config.enable_heading_fix:
|
||||
original = content
|
||||
content = self._fix_headings(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Headings")
|
||||
|
||||
# 10. Table fix
|
||||
if self.config.enable_table_fix:
|
||||
original = content
|
||||
content = self._fix_tables(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Tables")
|
||||
|
||||
# 11. XML tag cleanup
|
||||
if self.config.enable_xml_tag_cleanup:
|
||||
original = content
|
||||
content = self._cleanup_xml_tags(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Cleanup XML Tags")
|
||||
|
||||
# 9. Custom cleaners
|
||||
for cleaner in self.config.custom_cleaners:
|
||||
original = content
|
||||
content = cleaner(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Custom Cleaner")
|
||||
|
||||
if self.applied_fixes:
|
||||
logger.info(f"Markdown Normalizer Applied Fixes: {self.applied_fixes}")
|
||||
logger.debug(
|
||||
f"--- Original Content ---\n{original_content}\n------------------------"
|
||||
)
|
||||
logger.debug(
|
||||
f"--- Normalized Content ---\n{content}\n--------------------------"
|
||||
)
|
||||
|
||||
return content
|
||||
|
||||
except Exception as e:
|
||||
# Production safeguard: return original content on error
|
||||
logger.error(f"Content normalization failed: {e}", exc_info=True)
|
||||
return content
|
||||
|
||||
def _fix_escape_characters(self, content: str) -> str:
|
||||
"""Fix excessive escape characters"""
|
||||
content = content.replace("\\r\\n", "\n")
|
||||
content = content.replace("\\n", "\n")
|
||||
content = content.replace("\\t", "\t")
|
||||
content = content.replace("\\\\", "\\")
|
||||
return content
|
||||
|
||||
def _fix_thought_tags(self, content: str) -> str:
|
||||
"""Normalize thought tags: unify naming and fix spacing"""
|
||||
# 1. Standardize start tag: <think>, <thinking> -> <thought>
|
||||
content = self._PATTERNS["thought_start"].sub("<thought>", content)
|
||||
# 2. Standardize end tag and ensure newlines: </think> -> </thought>\n\n
|
||||
return self._PATTERNS["thought_end"].sub("</thought>\n\n", content)
|
||||
|
||||
def _fix_code_blocks(self, content: str) -> str:
|
||||
"""Fix code block formatting (prefixes, suffixes, indentation)"""
|
||||
# Remove indentation before code blocks
|
||||
content = self._PATTERNS["code_block_indent"].sub(r"\1", content)
|
||||
# Ensure newline before ```
|
||||
content = self._PATTERNS["code_block_prefix"].sub(r"\n\1", content)
|
||||
# Ensure newline after ```lang
|
||||
content = self._PATTERNS["code_block_suffix"].sub(r"\1\n\2", content)
|
||||
return content
|
||||
|
||||
def _fix_latex_formulas(self, content: str) -> str:
|
||||
"""Normalize LaTeX formulas: \[ -> $$ (block), \( -> $ (inline)"""
|
||||
content = self._PATTERNS["latex_bracket_block"].sub(r"$$\1$$", content)
|
||||
content = self._PATTERNS["latex_paren_inline"].sub(r"$\1$", content)
|
||||
return content
|
||||
|
||||
def _fix_list_formatting(self, content: str) -> str:
|
||||
"""Fix missing newlines in lists (e.g., 'text1. item' -> 'text\\n1. item')"""
|
||||
return self._PATTERNS["list_item"].sub(r"\1\n\2", content)
|
||||
|
||||
def _fix_unclosed_code_blocks(self, content: str) -> str:
|
||||
"""Auto-close unclosed code blocks"""
|
||||
if content.count("```") % 2 != 0:
|
||||
content += "\n```"
|
||||
return content
|
||||
|
||||
def _fix_fullwidth_symbols_in_code(self, content: str) -> str:
|
||||
"""Convert full-width symbols to half-width inside code blocks"""
|
||||
FULLWIDTH_MAP = {
|
||||
",": ",",
|
||||
"。": ".",
|
||||
"(": "(",
|
||||
")": ")",
|
||||
"【": "[",
|
||||
"】": "]",
|
||||
";": ";",
|
||||
":": ":",
|
||||
"?": "?",
|
||||
"!": "!",
|
||||
'"': '"',
|
||||
'"': '"',
|
||||
""": "'", """: "'",
|
||||
}
|
||||
|
||||
parts = content.split("```")
|
||||
# Code block content is at odd indices: 1, 3, 5...
|
||||
for i in range(1, len(parts), 2):
|
||||
for full, half in FULLWIDTH_MAP.items():
|
||||
parts[i] = parts[i].replace(full, half)
|
||||
|
||||
return "```".join(parts)
|
||||
|
||||
def _fix_mermaid_syntax(self, content: str) -> str:
|
||||
"""Fix common Mermaid syntax errors while preserving node shapes"""
|
||||
|
||||
def replacer(match):
|
||||
# Group 1 is ID
|
||||
id_str = match.group(1)
|
||||
|
||||
# Find matching shape group
|
||||
# Groups start at index 2, each shape has 3 groups (Open, Content, Close)
|
||||
# We iterate to find the non-None one
|
||||
groups = match.groups()
|
||||
for i in range(1, len(groups), 3):
|
||||
if groups[i] is not None:
|
||||
open_char = groups[i]
|
||||
content = groups[i + 1]
|
||||
close_char = groups[i + 2]
|
||||
|
||||
# Escape quotes in content
|
||||
content = content.replace('"', '\\"')
|
||||
|
||||
return f'{id_str}{open_char}"{content}"{close_char}'
|
||||
|
||||
return match.group(0)
|
||||
|
||||
parts = content.split("```")
|
||||
for i in range(1, len(parts), 2):
|
||||
# Check if it's a mermaid block
|
||||
lang_line = parts[i].split("\n", 1)[0].strip().lower()
|
||||
if "mermaid" in lang_line:
|
||||
# Apply the comprehensive regex fix
|
||||
parts[i] = self._PATTERNS["mermaid_node"].sub(replacer, parts[i])
|
||||
|
||||
# Auto-close subgraphs
|
||||
subgraph_count = len(
|
||||
re.findall(r"\bsubgraph\b", parts[i], re.IGNORECASE)
|
||||
)
|
||||
end_count = len(re.findall(r"\bend\b", parts[i], re.IGNORECASE))
|
||||
|
||||
if subgraph_count > end_count:
|
||||
missing_ends = subgraph_count - end_count
|
||||
parts[i] = parts[i].rstrip() + ("\n end" * missing_ends) + "\n"
|
||||
|
||||
return "```".join(parts)
|
||||
|
||||
def _fix_headings(self, content: str) -> str:
|
||||
"""Fix missing space in headings: #Heading -> # Heading"""
|
||||
# We only fix if it's not inside a code block.
|
||||
# But splitting by code block is expensive.
|
||||
# Given headings usually don't appear inside code blocks without space in valid code (except comments),
|
||||
# we might risk false positives in comments like `#TODO`.
|
||||
# To be safe, let's split by code blocks.
|
||||
|
||||
parts = content.split("```")
|
||||
for i in range(0, len(parts), 2): # Even indices are markdown text
|
||||
parts[i] = self._PATTERNS["heading_space"].sub(r"\1 \2", parts[i])
|
||||
return "```".join(parts)
|
||||
|
||||
def _fix_tables(self, content: str) -> str:
|
||||
"""Fix tables missing closing pipe"""
|
||||
parts = content.split("```")
|
||||
for i in range(0, len(parts), 2):
|
||||
parts[i] = self._PATTERNS["table_pipe"].sub(r"\1|", parts[i])
|
||||
return "```".join(parts)
|
||||
|
||||
def _cleanup_xml_tags(self, content: str) -> str:
|
||||
"""Remove leftover XML tags"""
|
||||
return self._PATTERNS["xml_artifacts"].sub("", content)
|
||||
|
||||
|
||||
class Filter:
|
||||
class Valves(BaseModel):
|
||||
priority: int = Field(
|
||||
default=50,
|
||||
description="Priority level. Higher runs later (recommended to run after other filters).",
|
||||
)
|
||||
enable_escape_fix: bool = Field(
|
||||
default=True, description="Fix excessive escape characters (\\n, \\t, etc.)"
|
||||
)
|
||||
enable_thought_tag_fix: bool = Field(
|
||||
default=True, description="Normalize </thought> tags"
|
||||
)
|
||||
enable_code_block_fix: bool = Field(
|
||||
default=True,
|
||||
description="Fix code block formatting (indentation, newlines)",
|
||||
)
|
||||
enable_latex_fix: bool = Field(
|
||||
default=True, description="Normalize LaTeX formulas (\\[ -> $$, \\( -> $)"
|
||||
)
|
||||
enable_list_fix: bool = Field(
|
||||
default=False, description="Fix list item newlines (Experimental)"
|
||||
)
|
||||
enable_unclosed_block_fix: bool = Field(
|
||||
default=True, description="Auto-close unclosed code blocks"
|
||||
)
|
||||
enable_fullwidth_symbol_fix: bool = Field(
|
||||
default=False, description="Fix full-width symbols in code blocks"
|
||||
)
|
||||
enable_mermaid_fix: bool = Field(
|
||||
default=True,
|
||||
description="Fix common Mermaid syntax errors (e.g. unquoted labels)",
|
||||
)
|
||||
enable_heading_fix: bool = Field(
|
||||
default=True,
|
||||
description="Fix missing space in headings (#Header -> # Header)",
|
||||
)
|
||||
enable_table_fix: bool = Field(
|
||||
default=True, description="Fix missing closing pipe in tables"
|
||||
)
|
||||
enable_xml_tag_cleanup: bool = Field(
|
||||
default=True, description="Cleanup leftover XML tags"
|
||||
)
|
||||
show_status: bool = Field(
|
||||
default=True, description="Show status notification when fixes are applied"
|
||||
)
|
||||
show_debug_log: bool = Field(
|
||||
default=False, description="Print debug logs to browser console (F12)"
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _contains_html(self, content: str) -> bool:
|
||||
"""Check if content contains HTML tags (to avoid breaking HTML output)"""
|
||||
pattern = r"<\s*/?\s*(?:html|head|body|div|span|p|br|hr|ul|ol|li|table|thead|tbody|tfoot|tr|td|th|img|a|b|i|strong|em|code|pre|blockquote|h[1-6]|script|style|form|input|button|label|select|option|iframe|link|meta|title)\b"
|
||||
return bool(re.search(pattern, content, re.IGNORECASE))
|
||||
|
||||
async def _emit_status(self, __event_emitter__, applied_fixes: List[str]):
|
||||
"""Emit status notification"""
|
||||
if not self.valves.show_status or not applied_fixes:
|
||||
return
|
||||
|
||||
description = "✓ Markdown Normalized"
|
||||
if applied_fixes:
|
||||
description += f": {', '.join(applied_fixes)}"
|
||||
|
||||
try:
|
||||
await __event_emitter__(
|
||||
{
|
||||
"type": "status",
|
||||
"data": {
|
||||
"description": description,
|
||||
"done": True,
|
||||
},
|
||||
}
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"Error emitting status: {e}")
|
||||
|
||||
async def _emit_debug_log(
|
||||
self, __event_call__, applied_fixes: List[str], original: str, normalized: str
|
||||
):
|
||||
"""Emit debug log to browser console via JS execution"""
|
||||
if not self.valves.show_debug_log or not __event_call__:
|
||||
return
|
||||
|
||||
try:
|
||||
# Prepare data for JS
|
||||
log_data = {
|
||||
"fixes": applied_fixes,
|
||||
"original": original,
|
||||
"normalized": normalized,
|
||||
}
|
||||
|
||||
# Construct JS code
|
||||
js_code = f"""
|
||||
(async function() {{
|
||||
console.group("🛠️ Markdown Normalizer Debug");
|
||||
console.log("Applied Fixes:", {json.dumps(applied_fixes, ensure_ascii=False)});
|
||||
console.log("Original Content:", {json.dumps(original, ensure_ascii=False)});
|
||||
console.log("Normalized Content:", {json.dumps(normalized, ensure_ascii=False)});
|
||||
console.groupEnd();
|
||||
}})();
|
||||
"""
|
||||
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"Error emitting debug log: {e}")
|
||||
|
||||
async def outlet(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[dict] = None,
|
||||
__event_emitter__=None,
|
||||
__event_call__=None,
|
||||
__metadata__: Optional[dict] = None,
|
||||
) -> dict:
|
||||
"""
|
||||
Process the response body to normalize Markdown content.
|
||||
"""
|
||||
if "messages" in body and body["messages"]:
|
||||
last = body["messages"][-1]
|
||||
content = last.get("content", "") or ""
|
||||
|
||||
if last.get("role") == "assistant" and isinstance(content, str):
|
||||
# Skip if content looks like HTML to avoid breaking it
|
||||
if self._contains_html(content):
|
||||
return body
|
||||
|
||||
# Configure normalizer based on valves
|
||||
config = NormalizerConfig(
|
||||
enable_escape_fix=self.valves.enable_escape_fix,
|
||||
enable_thought_tag_fix=self.valves.enable_thought_tag_fix,
|
||||
enable_code_block_fix=self.valves.enable_code_block_fix,
|
||||
enable_latex_fix=self.valves.enable_latex_fix,
|
||||
enable_list_fix=self.valves.enable_list_fix,
|
||||
enable_unclosed_block_fix=self.valves.enable_unclosed_block_fix,
|
||||
enable_fullwidth_symbol_fix=self.valves.enable_fullwidth_symbol_fix,
|
||||
enable_mermaid_fix=self.valves.enable_mermaid_fix,
|
||||
enable_heading_fix=self.valves.enable_heading_fix,
|
||||
enable_table_fix=self.valves.enable_table_fix,
|
||||
enable_xml_tag_cleanup=self.valves.enable_xml_tag_cleanup,
|
||||
)
|
||||
|
||||
normalizer = ContentNormalizer(config)
|
||||
|
||||
# Execute normalization
|
||||
new_content = normalizer.normalize(content)
|
||||
|
||||
# Update content if changed
|
||||
if new_content != content:
|
||||
last["content"] = new_content
|
||||
|
||||
# Emit status if enabled
|
||||
if __event_emitter__:
|
||||
await self._emit_status(
|
||||
__event_emitter__, normalizer.applied_fixes
|
||||
)
|
||||
await self._emit_debug_log(
|
||||
__event_call__,
|
||||
normalizer.applied_fixes,
|
||||
content,
|
||||
new_content,
|
||||
)
|
||||
|
||||
return body
|
||||
544
plugins/filters/markdown_normalizer/markdown_normalizer_cn.py
Normal file
@@ -0,0 +1,544 @@
|
||||
"""
|
||||
title: Markdown 格式修复器 (Markdown Normalizer)
|
||||
author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie
|
||||
funding_url: https://github.com/Fu-Jie/awesome-openwebui
|
||||
version: 1.0.0
|
||||
description: 生产级内容规范化过滤器,修复 LLM 输出中常见的 Markdown 格式问题,如损坏的代码块、LaTeX 公式、Mermaid 图表和列表格式。
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Optional, List, Callable
|
||||
import re
|
||||
import logging
|
||||
import asyncio
|
||||
import json
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
# Configure logging
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class NormalizerConfig:
|
||||
"""配置类,用于启用/禁用特定的规范化规则"""
|
||||
|
||||
enable_escape_fix: bool = True # 修复过度的转义字符
|
||||
enable_thought_tag_fix: bool = True # 规范化思维链标签
|
||||
enable_code_block_fix: bool = True # 修复代码块格式
|
||||
enable_latex_fix: bool = True # 修复 LaTeX 公式格式
|
||||
enable_list_fix: bool = False # 修复列表项换行 (默认关闭,因为可能过于激进)
|
||||
enable_unclosed_block_fix: bool = True # 自动闭合未闭合的代码块
|
||||
enable_fullwidth_symbol_fix: bool = False # 修复代码块中的全角符号
|
||||
enable_mermaid_fix: bool = True # 修复常见的 Mermaid 语法错误
|
||||
enable_heading_fix: bool = True # 修复标题中缺失的空格 (#Header -> # Header)
|
||||
enable_table_fix: bool = True # 修复表格中缺失的闭合管道符
|
||||
enable_xml_tag_cleanup: bool = True # 清理残留的 XML 标签
|
||||
|
||||
# 自定义清理函数 (用于高级扩展)
|
||||
custom_cleaners: List[Callable[[str], str]] = field(default_factory=list)
|
||||
|
||||
|
||||
class ContentNormalizer:
|
||||
"""LLM Output Content Normalizer - Production Grade Implementation"""
|
||||
|
||||
# --- 1. Pre-compiled Regex Patterns (Performance Optimization) ---
|
||||
_PATTERNS = {
|
||||
# Code block prefix: if ``` is not at start of line or file
|
||||
"code_block_prefix": re.compile(r"(?<!^)(?<!\n)(```)", re.MULTILINE),
|
||||
# Code block suffix: ```lang followed by non-whitespace (no newline)
|
||||
"code_block_suffix": re.compile(r"(```[\w\+\-\.]*)[ \t]+([^\n\r])"),
|
||||
# Code block indent: whitespace at start of line + ```
|
||||
"code_block_indent": re.compile(r"^[ \t]+(```)", re.MULTILINE),
|
||||
# Thought tag: </thought> followed by optional whitespace/newlines
|
||||
"thought_end": re.compile(
|
||||
r"</(thought|think|thinking)>[ \t]*\n*", re.IGNORECASE
|
||||
),
|
||||
"thought_start": re.compile(r"<(thought|think|thinking)>", re.IGNORECASE),
|
||||
# LaTeX block: \[ ... \]
|
||||
"latex_bracket_block": re.compile(r"\\\[(.+?)\\\]", re.DOTALL),
|
||||
# LaTeX inline: \( ... \)
|
||||
"latex_paren_inline": re.compile(r"\\\((.+?)\\\)"),
|
||||
# List item: non-newline + digit + dot + space
|
||||
"list_item": re.compile(r"([^\n])(\d+\. )"),
|
||||
# XML artifacts (e.g. Claude's)
|
||||
"xml_artifacts": re.compile(
|
||||
r"</?(?:antArtifact|antThinking|artifact)[^>]*>", re.IGNORECASE
|
||||
),
|
||||
# Mermaid: 匹配各种形状的节点并为未加引号的标签添加引号
|
||||
# 修复"反向优化"问题:必须精确匹配各种形状的定界符,避免破坏形状结构
|
||||
# 优先级:长定界符优先匹配
|
||||
"mermaid_node": re.compile(
|
||||
r"(\w+)\s*(?:"
|
||||
r"(\(\(\()(?![\"])(.*?)(?<![\"])(\)\)\))|" # (((...))) Double Circle
|
||||
r"(\(\()(?![\"])(.*?)(?<![\"])(\)\))|" # ((...)) Circle
|
||||
r"(\(\[)(?![\"])(.*?)(?<![\"])(\]\))|" # ([...]) Stadium
|
||||
r"(\[\()(?![\"])(.*?)(?<![\"])(\)\])|" # [(...)] Cylinder
|
||||
r"(\[\[)(?![\"])(.*?)(?<![\"])(\]\])|" # [[...]] Subroutine
|
||||
r"(\{\{)(?![\"])(.*?)(?<![\"])(\}\})|" # {{...}} Hexagon
|
||||
r"(\[/)(?![\"])(.*?)(?<![\"])(/\])|" # [/.../] Parallelogram
|
||||
r"(\[\\)(?![\"])(.*?)(?<![\"])(\\\])|" # [\...\] Parallelogram Alt
|
||||
r"(\[/)(?![\"])(.*?)(?<![\"])(\\\])|" # [/...\] Trapezoid
|
||||
r"(\[\\)(?![\"])(.*?)(?<![\"])(/\])|" # [\.../] Trapezoid Alt
|
||||
r"(\()(?![\"])(.*?)(?<![\"])(\))|" # (...) Round
|
||||
r"(\[)(?![\"])(.*?)(?<![\"])(\])|" # [...] Square
|
||||
r"(\{)(?![\"])(.*?)(?<![\"])(\})|" # {...} Rhombus
|
||||
r"(>)(?![\"])(.*?)(?<![\"])(\])" # >...] Asymmetric
|
||||
r")"
|
||||
),
|
||||
# Heading: #Heading -> # Heading
|
||||
"heading_space": re.compile(r"^(#+)([^ \n#])", re.MULTILINE),
|
||||
# Table: | col1 | col2 -> | col1 | col2 |
|
||||
"table_pipe": re.compile(r"^(\|.*[^|\n])$", re.MULTILINE),
|
||||
}
|
||||
|
||||
def __init__(self, config: Optional[NormalizerConfig] = None):
|
||||
self.config = config or NormalizerConfig()
|
||||
self.applied_fixes = []
|
||||
|
||||
def normalize(self, content: str) -> str:
|
||||
"""Main entry point: apply all normalization rules in order"""
|
||||
self.applied_fixes = []
|
||||
if not content:
|
||||
return content
|
||||
|
||||
original_content = content # Keep a copy for logging
|
||||
|
||||
try:
|
||||
# 1. Escape character fix (Must be first)
|
||||
if self.config.enable_escape_fix:
|
||||
original = content
|
||||
content = self._fix_escape_characters(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Escape Chars")
|
||||
|
||||
# 2. Thought tag normalization
|
||||
if self.config.enable_thought_tag_fix:
|
||||
original = content
|
||||
content = self._fix_thought_tags(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Normalize Thought Tags")
|
||||
|
||||
# 3. Code block formatting fix
|
||||
if self.config.enable_code_block_fix:
|
||||
original = content
|
||||
content = self._fix_code_blocks(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Code Blocks")
|
||||
|
||||
# 4. LaTeX formula normalization
|
||||
if self.config.enable_latex_fix:
|
||||
original = content
|
||||
content = self._fix_latex_formulas(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Normalize LaTeX")
|
||||
|
||||
# 5. List formatting fix
|
||||
if self.config.enable_list_fix:
|
||||
original = content
|
||||
content = self._fix_list_formatting(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix List Format")
|
||||
|
||||
# 6. Unclosed code block fix
|
||||
if self.config.enable_unclosed_block_fix:
|
||||
original = content
|
||||
content = self._fix_unclosed_code_blocks(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Close Code Blocks")
|
||||
|
||||
# 7. Full-width symbol fix (in code blocks only)
|
||||
if self.config.enable_fullwidth_symbol_fix:
|
||||
original = content
|
||||
content = self._fix_fullwidth_symbols_in_code(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Full-width Symbols")
|
||||
|
||||
# 8. Mermaid syntax fix
|
||||
if self.config.enable_mermaid_fix:
|
||||
original = content
|
||||
content = self._fix_mermaid_syntax(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Mermaid Syntax")
|
||||
|
||||
# 9. Heading fix
|
||||
if self.config.enable_heading_fix:
|
||||
original = content
|
||||
content = self._fix_headings(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Headings")
|
||||
|
||||
# 10. Table fix
|
||||
if self.config.enable_table_fix:
|
||||
original = content
|
||||
content = self._fix_tables(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Fix Tables")
|
||||
|
||||
# 11. XML tag cleanup
|
||||
if self.config.enable_xml_tag_cleanup:
|
||||
original = content
|
||||
content = self._cleanup_xml_tags(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Cleanup XML Tags")
|
||||
|
||||
# 9. Custom cleaners
|
||||
for cleaner in self.config.custom_cleaners:
|
||||
original = content
|
||||
content = cleaner(content)
|
||||
if content != original:
|
||||
self.applied_fixes.append("Custom Cleaner")
|
||||
|
||||
if self.applied_fixes:
|
||||
print(f"[Markdown Normalizer] Applied fixes: {self.applied_fixes}")
|
||||
print(
|
||||
f"[Markdown Normalizer] --- Original Content ---\n{original_content}\n------------------------"
|
||||
)
|
||||
print(
|
||||
f"[Markdown Normalizer] --- Normalized Content ---\n{content}\n--------------------------"
|
||||
)
|
||||
|
||||
return content
|
||||
|
||||
except Exception as e:
|
||||
# Production safeguard: return original content on error
|
||||
logger.error(f"Content normalization failed: {e}", exc_info=True)
|
||||
return content
|
||||
|
||||
def _fix_escape_characters(self, content: str) -> str:
|
||||
"""Fix excessive escape characters"""
|
||||
content = content.replace("\\r\\n", "\n")
|
||||
content = content.replace("\\n", "\n")
|
||||
content = content.replace("\\t", "\t")
|
||||
content = content.replace("\\\\", "\\")
|
||||
return content
|
||||
|
||||
def _fix_thought_tags(self, content: str) -> str:
|
||||
"""Normalize thought tags: unify naming and fix spacing"""
|
||||
# 1. Standardize start tag: <think>, <thinking> -> <thought>
|
||||
content = self._PATTERNS["thought_start"].sub("<thought>", content)
|
||||
# 2. Standardize end tag and ensure newlines: </think> -> </thought>\n\n
|
||||
return self._PATTERNS["thought_end"].sub("</thought>\n\n", content)
|
||||
|
||||
def _fix_code_blocks(self, content: str) -> str:
|
||||
"""Fix code block formatting (prefixes, suffixes, indentation)"""
|
||||
# Remove indentation before code blocks
|
||||
content = self._PATTERNS["code_block_indent"].sub(r"\1", content)
|
||||
# Ensure newline before ```
|
||||
content = self._PATTERNS["code_block_prefix"].sub(r"\n\1", content)
|
||||
# Ensure newline after ```lang
|
||||
content = self._PATTERNS["code_block_suffix"].sub(r"\1\n\2", content)
|
||||
return content
|
||||
|
||||
def _fix_latex_formulas(self, content: str) -> str:
|
||||
"""Normalize LaTeX formulas: \[ -> $$ (block), \( -> $ (inline)"""
|
||||
content = self._PATTERNS["latex_bracket_block"].sub(r"$$\1$$", content)
|
||||
content = self._PATTERNS["latex_paren_inline"].sub(r"$\1$", content)
|
||||
return content
|
||||
|
||||
def _fix_list_formatting(self, content: str) -> str:
|
||||
"""Fix missing newlines in lists (e.g., 'text1. item' -> 'text\\n1. item')"""
|
||||
return self._PATTERNS["list_item"].sub(r"\1\n\2", content)
|
||||
|
||||
def _fix_unclosed_code_blocks(self, content: str) -> str:
|
||||
"""Auto-close unclosed code blocks"""
|
||||
if content.count("```") % 2 != 0:
|
||||
content += "\n```"
|
||||
return content
|
||||
|
||||
def _fix_fullwidth_symbols_in_code(self, content: str) -> str:
|
||||
"""Convert full-width symbols to half-width inside code blocks"""
|
||||
FULLWIDTH_MAP = {
|
||||
",": ",",
|
||||
"。": ".",
|
||||
"(": "(",
|
||||
")": ")",
|
||||
"【": "[",
|
||||
"】": "]",
|
||||
";": ";",
|
||||
":": ":",
|
||||
"?": "?",
|
||||
"!": "!",
|
||||
'"': '"',
|
||||
'"': '"',
|
||||
""": "'", """: "'",
|
||||
}
|
||||
|
||||
parts = content.split("```")
|
||||
# Code block content is at odd indices: 1, 3, 5...
|
||||
for i in range(1, len(parts), 2):
|
||||
for full, half in FULLWIDTH_MAP.items():
|
||||
parts[i] = parts[i].replace(full, half)
|
||||
|
||||
return "```".join(parts)
|
||||
|
||||
def _fix_mermaid_syntax(self, content: str) -> str:
|
||||
"""修复常见的 Mermaid 语法错误,同时保留节点形状"""
|
||||
|
||||
def replacer(match):
|
||||
# Group 1 是 ID
|
||||
id_str = match.group(1)
|
||||
|
||||
# 查找匹配的形状组
|
||||
# 组从索引 2 开始,每个形状有 3 个组 (Open, Content, Close)
|
||||
# 我们遍历找到非 None 的那一组
|
||||
groups = match.groups()
|
||||
for i in range(1, len(groups), 3):
|
||||
if groups[i] is not None:
|
||||
open_char = groups[i]
|
||||
content = groups[i + 1]
|
||||
close_char = groups[i + 2]
|
||||
|
||||
# 如果内容包含引号,进行转义
|
||||
content = content.replace('"', '\\"')
|
||||
|
||||
return f'{id_str}{open_char}"{content}"{close_char}'
|
||||
|
||||
return match.group(0)
|
||||
|
||||
parts = content.split("```")
|
||||
for i in range(1, len(parts), 2):
|
||||
# Check if it's a mermaid block
|
||||
lang_line = parts[i].split("\n", 1)[0].strip().lower()
|
||||
if "mermaid" in lang_line:
|
||||
# Apply the comprehensive regex fix
|
||||
parts[i] = self._PATTERNS["mermaid_node"].sub(replacer, parts[i])
|
||||
|
||||
# Auto-close subgraphs
|
||||
# Count 'subgraph' and 'end' (case-insensitive)
|
||||
# We use a simple regex to avoid matching words inside labels (though labels are now quoted, so it's safer)
|
||||
# But for simplicity and speed, we just count occurrences in the whole block.
|
||||
# A more robust way would be to strip quoted strings first, but that's expensive.
|
||||
# Given we just quoted everything, let's try to count keywords outside quotes?
|
||||
# Actually, since we just normalized nodes, most text is in quotes.
|
||||
# Let's just do a simple count. It's a heuristic fix.
|
||||
subgraph_count = len(
|
||||
re.findall(r"\bsubgraph\b", parts[i], re.IGNORECASE)
|
||||
)
|
||||
end_count = len(re.findall(r"\bend\b", parts[i], re.IGNORECASE))
|
||||
|
||||
if subgraph_count > end_count:
|
||||
missing_ends = subgraph_count - end_count
|
||||
parts[i] = parts[i].rstrip() + ("\n end" * missing_ends) + "\n"
|
||||
|
||||
return "```".join(parts)
|
||||
|
||||
def _fix_headings(self, content: str) -> str:
|
||||
"""Fix missing space in headings: #Heading -> # Heading"""
|
||||
# We only fix if it's not inside a code block.
|
||||
# But splitting by code block is expensive.
|
||||
# Given headings usually don't appear inside code blocks without space in valid code (except comments),
|
||||
# we might risk false positives in comments like `#TODO`.
|
||||
# To be safe, let's split by code blocks.
|
||||
|
||||
parts = content.split("```")
|
||||
for i in range(0, len(parts), 2): # Even indices are markdown text
|
||||
parts[i] = self._PATTERNS["heading_space"].sub(r"\1 \2", parts[i])
|
||||
return "```".join(parts)
|
||||
|
||||
def _fix_tables(self, content: str) -> str:
|
||||
"""Fix tables missing closing pipe"""
|
||||
parts = content.split("```")
|
||||
for i in range(0, len(parts), 2):
|
||||
parts[i] = self._PATTERNS["table_pipe"].sub(r"\1|", parts[i])
|
||||
return "```".join(parts)
|
||||
|
||||
def _cleanup_xml_tags(self, content: str) -> str:
|
||||
"""Remove leftover XML tags"""
|
||||
return self._PATTERNS["xml_artifacts"].sub("", content)
|
||||
|
||||
|
||||
class Filter:
|
||||
class Valves(BaseModel):
|
||||
priority: int = Field(
|
||||
default=50,
|
||||
description="优先级。数值越高运行越晚 (建议在其他过滤器之后运行)。",
|
||||
)
|
||||
enable_escape_fix: bool = Field(
|
||||
default=True, description="修复过度的转义字符 (\\n, \\t 等)"
|
||||
)
|
||||
enable_thought_tag_fix: bool = Field(
|
||||
default=True, description="规范化思维链标签 (<think> -> <thought>)"
|
||||
)
|
||||
enable_code_block_fix: bool = Field(
|
||||
default=True,
|
||||
description="修复代码块格式 (缩进、换行)",
|
||||
)
|
||||
enable_latex_fix: bool = Field(
|
||||
default=True, description="规范化 LaTeX 公式 (\\[ -> $$, \\( -> $)"
|
||||
)
|
||||
enable_list_fix: bool = Field(
|
||||
default=False, description="修复列表项换行 (实验性)"
|
||||
)
|
||||
enable_unclosed_block_fix: bool = Field(
|
||||
default=True, description="自动闭合未闭合的代码块"
|
||||
)
|
||||
enable_fullwidth_symbol_fix: bool = Field(
|
||||
default=False, description="修复代码块中的全角符号"
|
||||
)
|
||||
enable_mermaid_fix: bool = Field(
|
||||
default=True,
|
||||
description="修复常见的 Mermaid 语法错误 (如未加引号的标签)",
|
||||
)
|
||||
enable_heading_fix: bool = Field(
|
||||
default=True,
|
||||
description="修复标题中缺失的空格 (#Header -> # Header)",
|
||||
)
|
||||
enable_table_fix: bool = Field(
|
||||
default=True, description="修复表格中缺失的闭合管道符"
|
||||
)
|
||||
enable_xml_tag_cleanup: bool = Field(
|
||||
default=True, description="清理残留的 XML 标签"
|
||||
)
|
||||
show_status: bool = Field(default=True, description="应用修复时显示状态通知")
|
||||
show_debug_log: bool = Field(
|
||||
default=False, description="在浏览器控制台打印调试日志 (F12)"
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _contains_html(self, content: str) -> bool:
|
||||
"""Check if content contains HTML tags (to avoid breaking HTML output)"""
|
||||
pattern = r"<\s*/?\s*(?:html|head|body|div|span|p|br|hr|ul|ol|li|table|thead|tbody|tfoot|tr|td|th|img|a|b|i|strong|em|code|pre|blockquote|h[1-6]|script|style|form|input|button|label|select|option|iframe|link|meta|title)\b"
|
||||
return bool(re.search(pattern, content, re.IGNORECASE))
|
||||
|
||||
async def _emit_status(self, __event_emitter__, applied_fixes: List[str]):
|
||||
"""Emit status notification"""
|
||||
if not self.valves.show_status or not applied_fixes:
|
||||
return
|
||||
|
||||
description = "✓ Markdown 已修复"
|
||||
if applied_fixes:
|
||||
# Translate fix names for status display
|
||||
fix_map = {
|
||||
"Fix Escape Chars": "转义字符",
|
||||
"Normalize Thought Tags": "思维标签",
|
||||
"Fix Code Blocks": "代码块",
|
||||
"Normalize LaTeX": "LaTeX公式",
|
||||
"Fix List Format": "列表格式",
|
||||
"Close Code Blocks": "闭合代码块",
|
||||
"Fix Full-width Symbols": "全角符号",
|
||||
"Fix Mermaid Syntax": "Mermaid语法",
|
||||
"Fix Headings": "标题格式",
|
||||
"Fix Tables": "表格格式",
|
||||
"Cleanup XML Tags": "XML清理",
|
||||
"Custom Cleaner": "自定义清理",
|
||||
}
|
||||
translated_fixes = [fix_map.get(fix, fix) for fix in applied_fixes]
|
||||
description += f": {', '.join(translated_fixes)}"
|
||||
|
||||
try:
|
||||
await __event_emitter__(
|
||||
{
|
||||
"type": "status",
|
||||
"data": {
|
||||
"description": description,
|
||||
"done": True,
|
||||
},
|
||||
}
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"Error emitting status: {e}")
|
||||
|
||||
async def _emit_debug_log(
|
||||
self,
|
||||
__event_emitter__,
|
||||
applied_fixes: List[str],
|
||||
original: str,
|
||||
normalized: str,
|
||||
):
|
||||
"""Emit debug log to browser console via JS execution"""
|
||||
|
||||
async def _emit_debug_log(
|
||||
self, __event_call__, applied_fixes: List[str], original: str, normalized: str
|
||||
):
|
||||
"""Emit debug log to browser console via JS execution"""
|
||||
if not self.valves.show_debug_log or not __event_call__:
|
||||
return
|
||||
|
||||
try:
|
||||
# Prepare data for JS
|
||||
log_data = {
|
||||
"fixes": applied_fixes,
|
||||
"original": original,
|
||||
"normalized": normalized,
|
||||
}
|
||||
|
||||
# Construct JS code
|
||||
js_code = f"""
|
||||
(async function() {{
|
||||
console.group("🛠️ Markdown Normalizer Debug");
|
||||
console.log("Applied Fixes:", {json.dumps(applied_fixes, ensure_ascii=False)});
|
||||
console.log("Original Content:", {json.dumps(original, ensure_ascii=False)});
|
||||
console.log("Normalized Content:", {json.dumps(normalized, ensure_ascii=False)});
|
||||
console.groupEnd();
|
||||
}})();
|
||||
"""
|
||||
await __event_call__(
|
||||
{
|
||||
"type": "execute",
|
||||
"data": {"code": js_code},
|
||||
}
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error emitting debug log: {e}")
|
||||
|
||||
async def outlet(
|
||||
self,
|
||||
body: dict,
|
||||
__user__: Optional[dict] = None,
|
||||
__event_emitter__=None,
|
||||
__event_call__=None,
|
||||
__metadata__: Optional[dict] = None,
|
||||
) -> dict:
|
||||
"""
|
||||
Process the response body to normalize Markdown content.
|
||||
"""
|
||||
if "messages" in body and body["messages"]:
|
||||
last = body["messages"][-1]
|
||||
content = last.get("content", "") or ""
|
||||
|
||||
if last.get("role") == "assistant" and isinstance(content, str):
|
||||
# Skip if content looks like HTML to avoid breaking it
|
||||
if self._contains_html(content):
|
||||
return body
|
||||
|
||||
# Configure normalizer based on valves
|
||||
config = NormalizerConfig(
|
||||
enable_escape_fix=self.valves.enable_escape_fix,
|
||||
enable_thought_tag_fix=self.valves.enable_thought_tag_fix,
|
||||
enable_code_block_fix=self.valves.enable_code_block_fix,
|
||||
enable_latex_fix=self.valves.enable_latex_fix,
|
||||
enable_list_fix=self.valves.enable_list_fix,
|
||||
enable_unclosed_block_fix=self.valves.enable_unclosed_block_fix,
|
||||
enable_fullwidth_symbol_fix=self.valves.enable_fullwidth_symbol_fix,
|
||||
enable_mermaid_fix=self.valves.enable_mermaid_fix,
|
||||
enable_heading_fix=self.valves.enable_heading_fix,
|
||||
enable_table_fix=self.valves.enable_table_fix,
|
||||
enable_xml_tag_cleanup=self.valves.enable_xml_tag_cleanup,
|
||||
)
|
||||
|
||||
normalizer = ContentNormalizer(config)
|
||||
|
||||
# Execute normalization
|
||||
new_content = normalizer.normalize(content)
|
||||
|
||||
# Update content if changed
|
||||
if new_content != content:
|
||||
last["content"] = new_content
|
||||
|
||||
# Emit status if enabled
|
||||
if __event_emitter__:
|
||||
await self._emit_status(
|
||||
__event_emitter__, normalizer.applied_fixes
|
||||
)
|
||||
await self._emit_debug_log(
|
||||
__event_call__,
|
||||
normalizer.applied_fixes,
|
||||
content,
|
||||
new_content,
|
||||
)
|
||||
|
||||
return body
|
||||
191
plugins/filters/markdown_normalizer/test_markdown_normalizer.py
Normal file
@@ -0,0 +1,191 @@
|
||||
import unittest
|
||||
import sys
|
||||
import os
|
||||
|
||||
# Add the current directory to sys.path to import the module
|
||||
current_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
sys.path.append(current_dir)
|
||||
|
||||
from markdown_normalizer import ContentNormalizer, NormalizerConfig
|
||||
|
||||
|
||||
class TestMarkdownNormalizer(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.config = NormalizerConfig(
|
||||
enable_escape_fix=True,
|
||||
enable_thought_tag_fix=True,
|
||||
enable_code_block_fix=True,
|
||||
enable_latex_fix=True,
|
||||
enable_list_fix=True,
|
||||
enable_unclosed_block_fix=True,
|
||||
enable_fullwidth_symbol_fix=True,
|
||||
enable_mermaid_fix=True,
|
||||
enable_xml_tag_cleanup=True,
|
||||
)
|
||||
self.normalizer = ContentNormalizer(self.config)
|
||||
|
||||
def test_escape_fix(self):
|
||||
input_text = "Line 1\\nLine 2\\tTabbed"
|
||||
expected = "Line 1\nLine 2\tTabbed"
|
||||
self.assertEqual(self.normalizer.normalize(input_text), expected)
|
||||
|
||||
def test_thought_tag_fix(self):
|
||||
# Case 1: Standard tag spacing
|
||||
input_text = "Thinking...</thought>Result"
|
||||
expected = "Thinking...</thought>\n\nResult"
|
||||
self.assertEqual(self.normalizer.normalize(input_text), expected)
|
||||
|
||||
# Case 2: Tag standardization (<think> -> <thought>)
|
||||
input_text_deepseek = "<think>Deep thinking...</think>Result"
|
||||
expected_deepseek = "<thought>Deep thinking...</thought>\n\nResult"
|
||||
self.assertEqual(
|
||||
self.normalizer.normalize(input_text_deepseek), expected_deepseek
|
||||
)
|
||||
|
||||
def test_code_block_fix(self):
|
||||
# Case 1: Indentation
|
||||
self.assertEqual(self.normalizer._fix_code_blocks(" ```python"), "```python")
|
||||
|
||||
# Case 2: Prefix (newline before block)
|
||||
self.assertEqual(
|
||||
self.normalizer._fix_code_blocks("Text```python"), "Text\n```python"
|
||||
)
|
||||
|
||||
# Case 3: Suffix (newline after lang)
|
||||
self.assertEqual(
|
||||
self.normalizer._fix_code_blocks("```python print('hi')"),
|
||||
"```python\nprint('hi')",
|
||||
)
|
||||
|
||||
def test_latex_fix(self):
|
||||
input_text = "Block: \\[ x^2 \\] Inline: \\( E=mc^2 \\)"
|
||||
expected = "Block: $$ x^2 $$ Inline: $ E=mc^2 $"
|
||||
self.assertEqual(self.normalizer.normalize(input_text), expected)
|
||||
|
||||
def test_list_fix(self):
|
||||
input_text = "Item 1. First\nItem 2. Second" # This is fine
|
||||
input_text_bad = "Header1. Item 1"
|
||||
expected = "Header\n1. Item 1"
|
||||
self.assertEqual(self.normalizer.normalize(input_text_bad), expected)
|
||||
|
||||
def test_unclosed_code_block_fix(self):
|
||||
input_text = "```python\nprint('hello')"
|
||||
expected = "```python\nprint('hello')\n```"
|
||||
self.assertEqual(self.normalizer.normalize(input_text), expected)
|
||||
|
||||
def test_fullwidth_symbol_fix(self):
|
||||
input_text = "Outside:Fullwidth ```python\nprint('hello')```"
|
||||
expected = "Outside:Fullwidth \n```python\nprint('hello')\n```"
|
||||
|
||||
normalized = self.normalizer.normalize(input_text)
|
||||
self.assertIn("print('hello')", normalized)
|
||||
self.assertIn("Outside:Fullwidth", normalized)
|
||||
self.assertNotIn("(", normalized)
|
||||
self.assertNotIn(")", normalized)
|
||||
|
||||
def test_mermaid_fix(self):
|
||||
# Test Mermaid syntax fix for unquoted labels
|
||||
# Note: Regex-based fix handles mixed brackets well (e.g. [] inside ())
|
||||
# but cannot perfectly handle same-type nesting (e.g. {} inside {}) without a parser.
|
||||
input_text = """
|
||||
```mermaid
|
||||
graph TD
|
||||
A[Label with (parens)] --> B(Label with [brackets])
|
||||
C{Label with [brackets]}
|
||||
```
|
||||
"""
|
||||
expected_snippet = """
|
||||
```mermaid
|
||||
graph TD
|
||||
A["Label with (parens)"] --> B("Label with [brackets]")
|
||||
C{"Label with [brackets]"}
|
||||
```
|
||||
"""
|
||||
normalized = self.normalizer.normalize(input_text)
|
||||
|
||||
self.assertIn('A["Label with (parens)"]', normalized)
|
||||
self.assertIn('B("Label with [brackets]")', normalized)
|
||||
self.assertIn('C{"Label with [brackets]"}', normalized)
|
||||
|
||||
def test_mermaid_shapes_regression(self):
|
||||
# Regression test for "reverse optimization" where ((...)) was broken into ("(...)")
|
||||
input_text = """
|
||||
```mermaid
|
||||
graph TD
|
||||
Start((开始)) --> Input[[输入]]
|
||||
Input --> Verify{验证}
|
||||
Verify --> End(((结束)))
|
||||
```
|
||||
"""
|
||||
expected_snippet = """
|
||||
```mermaid
|
||||
graph TD
|
||||
Start(("开始")) --> Input[["输入"]]
|
||||
Input --> Verify{"验证"}
|
||||
Verify --> End((("结束")))
|
||||
```
|
||||
"""
|
||||
normalized = self.normalizer.normalize(input_text)
|
||||
self.assertIn('Start(("开始"))', normalized)
|
||||
self.assertIn('Input[["输入"]]', normalized)
|
||||
self.assertIn('Verify{"验证"}', normalized)
|
||||
self.assertIn('End((("结束")))', normalized)
|
||||
|
||||
def test_xml_cleanup(self):
|
||||
input_text = "Some text <antArtifact>hidden</antArtifact> visible"
|
||||
expected = "Some text hidden visible"
|
||||
self.assertEqual(self.normalizer.normalize(input_text), expected)
|
||||
|
||||
def test_heading_fix(self):
|
||||
input_text = "#Heading 1\n##Heading 2\n### Valid Heading"
|
||||
expected = "# Heading 1\n## Heading 2\n### Valid Heading"
|
||||
self.assertEqual(self.normalizer.normalize(input_text), expected)
|
||||
|
||||
def test_table_fix(self):
|
||||
input_text = "| Col 1 | Col 2\n| Val 1 | Val 2"
|
||||
expected = "| Col 1 | Col 2|\n| Val 1 | Val 2|"
|
||||
self.assertEqual(self.normalizer.normalize(input_text), expected)
|
||||
|
||||
def test_mermaid_subgraph_autoclose(self):
|
||||
"""Test auto-closing of Mermaid subgraphs"""
|
||||
# Case 1: Simple unclosed subgraph
|
||||
original = """
|
||||
```mermaid
|
||||
graph TD
|
||||
subgraph One
|
||||
A --> B
|
||||
```
|
||||
"""
|
||||
expected = """
|
||||
```mermaid
|
||||
graph TD
|
||||
subgraph One
|
||||
A --> B
|
||||
end
|
||||
```
|
||||
"""
|
||||
# Note: The normalizer might add quotes to A and B if they match the node pattern,
|
||||
# but here they are simple IDs. However, our regex is strict about shapes.
|
||||
# Simple IDs like A and B are NOT matched by our mermaid_node regex because it requires a shape delimiter.
|
||||
# So A and B remain A and B.
|
||||
|
||||
normalized = self.normalizer.normalize(original)
|
||||
# We need to be careful about whitespace in comparison
|
||||
self.assertIn("end", normalized)
|
||||
self.assertEqual(normalized.strip(), expected.strip())
|
||||
|
||||
# Case 2: Nested unclosed subgraphs
|
||||
original_nested = """
|
||||
```mermaid
|
||||
graph TD
|
||||
subgraph Outer
|
||||
subgraph Inner
|
||||
C --> D
|
||||
```
|
||||
"""
|
||||
normalized_nested = self.normalizer.normalize(original_nested)
|
||||
self.assertEqual(normalized_nested.count("end"), 2)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
133
scripts/download_plugin_images.py
Normal file
@@ -0,0 +1,133 @@
|
||||
"""
|
||||
Download plugin images from OpenWebUI Community
|
||||
下载远程插件图片到本地目录
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import re
|
||||
import requests
|
||||
from urllib.parse import urlparse
|
||||
|
||||
# Add current directory to path
|
||||
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
|
||||
|
||||
from openwebui_community_client import get_client
|
||||
|
||||
|
||||
def find_local_plugin_by_id(plugins_dir: str, post_id: str) -> str | None:
|
||||
"""根据 post_id 查找本地插件文件"""
|
||||
for root, _, files in os.walk(plugins_dir):
|
||||
for file in files:
|
||||
if file.endswith(".py"):
|
||||
file_path = os.path.join(root, file)
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
content = f.read(2000)
|
||||
|
||||
id_match = re.search(
|
||||
r"(?:openwebui_id|post_id):\s*([a-z0-9-]+)", content
|
||||
)
|
||||
if id_match and id_match.group(1).strip() == post_id:
|
||||
return file_path
|
||||
return None
|
||||
|
||||
|
||||
def download_image(url: str, save_path: str) -> bool:
|
||||
"""下载图片"""
|
||||
try:
|
||||
response = requests.get(url, timeout=30)
|
||||
response.raise_for_status()
|
||||
with open(save_path, "wb") as f:
|
||||
f.write(response.content)
|
||||
return True
|
||||
except Exception as e:
|
||||
print(f" Error downloading: {e}")
|
||||
return False
|
||||
|
||||
|
||||
def get_image_extension(url: str) -> str:
|
||||
"""从 URL 获取图片扩展名"""
|
||||
parsed = urlparse(url)
|
||||
path = parsed.path
|
||||
ext = os.path.splitext(path)[1].lower()
|
||||
if ext in [".png", ".jpg", ".jpeg", ".gif", ".webp"]:
|
||||
return ext
|
||||
return ".png" # 默认
|
||||
|
||||
|
||||
def main():
|
||||
try:
|
||||
client = get_client()
|
||||
except ValueError as e:
|
||||
print(f"Error: {e}")
|
||||
sys.exit(1)
|
||||
|
||||
base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
||||
plugins_dir = os.path.join(base_dir, "plugins")
|
||||
|
||||
print("Fetching remote posts from OpenWebUI Community...")
|
||||
posts = client.get_all_posts()
|
||||
print(f"Found {len(posts)} remote posts.\n")
|
||||
|
||||
downloaded = 0
|
||||
skipped = 0
|
||||
not_found = 0
|
||||
|
||||
for post in posts:
|
||||
post_id = post.get("id")
|
||||
title = post.get("title", "Unknown")
|
||||
media = post.get("media", [])
|
||||
|
||||
if not media:
|
||||
continue
|
||||
|
||||
# 只取第一张图片
|
||||
first_media = media[0] if isinstance(media, list) else media
|
||||
|
||||
# 处理字典格式 {'url': '...', 'type': 'image'}
|
||||
if isinstance(first_media, dict):
|
||||
image_url = first_media.get("url")
|
||||
else:
|
||||
image_url = first_media
|
||||
|
||||
if not image_url:
|
||||
continue
|
||||
|
||||
print(f"Processing: {title}")
|
||||
print(f" Image URL: {image_url}")
|
||||
|
||||
# 查找对应的本地插件
|
||||
local_plugin = find_local_plugin_by_id(plugins_dir, post_id)
|
||||
if not local_plugin:
|
||||
print(f" ⚠️ No local plugin found for ID: {post_id}")
|
||||
not_found += 1
|
||||
continue
|
||||
|
||||
# 确定保存路径
|
||||
plugin_dir = os.path.dirname(local_plugin)
|
||||
plugin_name = os.path.splitext(os.path.basename(local_plugin))[0]
|
||||
ext = get_image_extension(image_url)
|
||||
save_path = os.path.join(plugin_dir, plugin_name + ext)
|
||||
|
||||
# 检查是否已存在
|
||||
if os.path.exists(save_path):
|
||||
print(f" ⏭️ Image already exists: {os.path.basename(save_path)}")
|
||||
skipped += 1
|
||||
continue
|
||||
|
||||
# 下载
|
||||
print(f" Downloading to: {save_path}")
|
||||
if download_image(image_url, save_path):
|
||||
print(f" ✅ Downloaded: {os.path.basename(save_path)}")
|
||||
downloaded += 1
|
||||
else:
|
||||
print(f" ❌ Failed to download")
|
||||
|
||||
print(f"\n{'='*50}")
|
||||
print(
|
||||
f"Finished: {downloaded} downloaded, {skipped} skipped, {not_found} not found locally"
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -140,22 +140,49 @@ def compare_versions(current: list[dict], previous_file: str) -> dict[str, list[
|
||||
return {"added": current, "updated": [], "removed": []}
|
||||
|
||||
# Create lookup dictionaries by title
|
||||
current_by_title = {p["title"]: p for p in current}
|
||||
previous_by_title = {p["title"]: p for p in previous}
|
||||
# Helper to extract title/version from either simple dict or raw post object
|
||||
def get_info(p):
|
||||
if "data" in p and "function" in p["data"]:
|
||||
# It's a raw post object
|
||||
manifest = p["data"]["function"].get("meta", {}).get("manifest", {})
|
||||
title = manifest.get("title") or p.get("title")
|
||||
version = manifest.get("version", "0.0.0")
|
||||
return title, version, p
|
||||
else:
|
||||
# It's a simple dict
|
||||
return p.get("title"), p.get("version"), p
|
||||
|
||||
current_by_title = {}
|
||||
for p in current:
|
||||
title, _, _ = get_info(p)
|
||||
if title:
|
||||
current_by_title[title] = p
|
||||
|
||||
previous_by_title = {}
|
||||
for p in previous:
|
||||
title, _, _ = get_info(p)
|
||||
if title:
|
||||
previous_by_title[title] = p
|
||||
|
||||
result = {"added": [], "updated": [], "removed": []}
|
||||
|
||||
# Find added and updated plugins
|
||||
for title, plugin in current_by_title.items():
|
||||
curr_title, curr_ver, _ = get_info(plugin)
|
||||
|
||||
if title not in previous_by_title:
|
||||
result["added"].append(plugin)
|
||||
elif plugin["version"] != previous_by_title[title]["version"]:
|
||||
result["updated"].append(
|
||||
{
|
||||
"current": plugin,
|
||||
"previous": previous_by_title[title],
|
||||
}
|
||||
)
|
||||
else:
|
||||
prev_plugin = previous_by_title[title]
|
||||
_, prev_ver, _ = get_info(prev_plugin)
|
||||
|
||||
if curr_ver != prev_ver:
|
||||
result["updated"].append(
|
||||
{
|
||||
"current": plugin,
|
||||
"previous": prev_plugin,
|
||||
}
|
||||
)
|
||||
|
||||
# Find removed plugins
|
||||
for title, plugin in previous_by_title.items():
|
||||
@@ -212,9 +239,26 @@ def format_release_notes(
|
||||
for update in comparison["updated"]:
|
||||
curr = update["current"]
|
||||
prev = update["previous"]
|
||||
lines.append(
|
||||
f"- **{curr['title']}**: v{prev['version']} → v{curr['version']}"
|
||||
|
||||
# Extract info safely
|
||||
curr_manifest = (
|
||||
curr.get("data", {})
|
||||
.get("function", {})
|
||||
.get("meta", {})
|
||||
.get("manifest", {})
|
||||
)
|
||||
curr_title = curr_manifest.get("title") or curr.get("title")
|
||||
curr_ver = curr_manifest.get("version") or curr.get("version")
|
||||
|
||||
prev_manifest = (
|
||||
prev.get("data", {})
|
||||
.get("function", {})
|
||||
.get("meta", {})
|
||||
.get("manifest", {})
|
||||
)
|
||||
prev_ver = prev_manifest.get("version") or prev.get("version")
|
||||
|
||||
lines.append(f"- **{curr_title}**: v{prev_ver} → v{curr_ver}")
|
||||
lines.append("")
|
||||
|
||||
if comparison["removed"] and not ignore_removed:
|
||||
|
||||
47
scripts/fetch_remote_versions.py
Normal file
@@ -0,0 +1,47 @@
|
||||
"""
|
||||
Fetch remote plugin versions from OpenWebUI Community
|
||||
获取远程插件版本信息
|
||||
"""
|
||||
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
|
||||
# Add current directory to path
|
||||
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
|
||||
|
||||
from openwebui_community_client import get_client
|
||||
|
||||
|
||||
def main():
|
||||
try:
|
||||
client = get_client()
|
||||
except ValueError as e:
|
||||
print(f"Error: {e}")
|
||||
sys.exit(1)
|
||||
|
||||
print("Fetching remote plugins from OpenWebUI Community...")
|
||||
try:
|
||||
posts = client.get_all_posts()
|
||||
except Exception as e:
|
||||
print(f"Error fetching posts: {e}")
|
||||
sys.exit(1)
|
||||
|
||||
formatted_plugins = []
|
||||
for post in posts:
|
||||
post["type"] = "remote_plugin"
|
||||
formatted_plugins.append(post)
|
||||
|
||||
output_file = "remote_versions.json"
|
||||
with open(output_file, "w", encoding="utf-8") as f:
|
||||
json.dump(formatted_plugins, f, indent=2, ensure_ascii=False)
|
||||
|
||||
print(
|
||||
f"✅ Successfully saved {len(formatted_plugins)} remote plugins to {output_file}"
|
||||
)
|
||||
print(f" You can now compare local vs remote using:")
|
||||
print(f" python scripts/extract_plugin_versions.py --compare {output_file}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
659
scripts/openwebui_community_client.py
Normal file
@@ -0,0 +1,659 @@
|
||||
"""
|
||||
OpenWebUI Community Client
|
||||
统一封装所有与 OpenWebUI 官方社区 (openwebui.com) 的 API 交互。
|
||||
|
||||
功能:
|
||||
- 获取用户发布的插件/帖子
|
||||
- 更新插件内容和元数据
|
||||
- 版本比较
|
||||
- 同步插件 ID
|
||||
|
||||
使用方法:
|
||||
from openwebui_community_client import OpenWebUICommunityClient
|
||||
|
||||
client = OpenWebUICommunityClient(api_key="your_api_key")
|
||||
posts = client.get_all_posts()
|
||||
"""
|
||||
|
||||
import os
|
||||
import re
|
||||
import json
|
||||
import base64
|
||||
import requests
|
||||
from datetime import datetime, timezone, timedelta
|
||||
from typing import Optional, Dict, List, Any, Tuple
|
||||
|
||||
# 北京时区 (UTC+8)
|
||||
BEIJING_TZ = timezone(timedelta(hours=8))
|
||||
|
||||
|
||||
class OpenWebUICommunityClient:
|
||||
"""OpenWebUI 官方社区 API 客户端"""
|
||||
|
||||
BASE_URL = "https://api.openwebui.com/api/v1"
|
||||
|
||||
def __init__(self, api_key: str, user_id: Optional[str] = None):
|
||||
"""
|
||||
初始化客户端
|
||||
|
||||
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.headers = {
|
||||
"Authorization": f"Bearer {api_key}",
|
||||
"Content-Type": "application/json",
|
||||
"Accept": "application/json",
|
||||
}
|
||||
# 如果没有 user_id,尝试通过 API 获取
|
||||
if not self.user_id:
|
||||
self.user_id = self._get_user_id_from_api()
|
||||
|
||||
def _parse_user_id_from_token(self, token: str) -> Optional[str]:
|
||||
"""从 JWT Token 中解析用户 ID"""
|
||||
# sk- 开头的是 API Key,无法解析用户 ID
|
||||
if token.startswith("sk-"):
|
||||
return None
|
||||
try:
|
||||
parts = token.split(".")
|
||||
if len(parts) >= 2:
|
||||
payload = parts[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") or data.get("sub")
|
||||
except Exception:
|
||||
pass
|
||||
return None
|
||||
|
||||
def _get_user_id_from_api(self) -> Optional[str]:
|
||||
"""通过 API 获取当前用户 ID"""
|
||||
try:
|
||||
url = f"{self.BASE_URL}/auths/"
|
||||
response = requests.get(url, headers=self.headers)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
return data.get("id")
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
# ========== 帖子/插件获取 ==========
|
||||
|
||||
def get_user_posts(self, sort: str = "new", page: int = 1) -> List[Dict]:
|
||||
"""
|
||||
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}?sort={sort}&page={page}"
|
||||
response = requests.get(url, headers=self.headers)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
def get_all_posts(self, sort: str = "new") -> List[Dict]:
|
||||
"""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 get_post(self, post_id: str) -> Optional[Dict]:
|
||||
"""
|
||||
获取单个帖子详情
|
||||
|
||||
Args:
|
||||
post_id: 帖子 ID
|
||||
|
||||
Returns:
|
||||
帖子数据,如果不存在返回 None
|
||||
"""
|
||||
try:
|
||||
url = f"{self.BASE_URL}/posts/{post_id}"
|
||||
response = requests.get(url, headers=self.headers)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
except requests.exceptions.HTTPError as e:
|
||||
if e.response.status_code == 404:
|
||||
return None
|
||||
raise
|
||||
|
||||
# ========== 帖子/插件创建 ==========
|
||||
|
||||
def create_post(
|
||||
self,
|
||||
title: str,
|
||||
content: str,
|
||||
post_type: str = "function",
|
||||
data: Optional[Dict] = None,
|
||||
media: Optional[List[str]] = None,
|
||||
) -> Optional[Dict]:
|
||||
"""
|
||||
创建新帖子
|
||||
|
||||
Args:
|
||||
title: 帖子标题
|
||||
content: 帖子内容(README/描述)
|
||||
post_type: 帖子类型 (function/tool/filter/pipeline)
|
||||
data: 插件数据结构
|
||||
media: 图片 URL 列表
|
||||
|
||||
Returns:
|
||||
创建成功返回帖子数据,失败返回 None
|
||||
"""
|
||||
try:
|
||||
url = f"{self.BASE_URL}/posts/create"
|
||||
|
||||
# 将字符串 URL 转换为字典格式 (API 要求)
|
||||
media_list = []
|
||||
if media:
|
||||
for item in media:
|
||||
if isinstance(item, str):
|
||||
media_list.append({"url": item})
|
||||
elif isinstance(item, dict):
|
||||
media_list.append(item)
|
||||
|
||||
payload = {
|
||||
"title": title,
|
||||
"content": content,
|
||||
"type": post_type,
|
||||
"data": data or {},
|
||||
"media": media_list,
|
||||
}
|
||||
print(f" [DEBUG] Payload keys: {list(payload.keys())}")
|
||||
print(
|
||||
f" [DEBUG] media format: {media_list[:1] if media_list else 'empty'}"
|
||||
)
|
||||
response = requests.post(url, headers=self.headers, json=payload)
|
||||
if response.status_code != 200:
|
||||
print(f" [DEBUG] Response status: {response.status_code}")
|
||||
print(f" [DEBUG] Response body: {response.text[:500]}")
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
except Exception as e:
|
||||
print(f" Error creating post: {e}")
|
||||
return None
|
||||
|
||||
def create_plugin(
|
||||
self,
|
||||
title: str,
|
||||
source_code: str,
|
||||
readme_content: Optional[str] = None,
|
||||
metadata: Optional[Dict] = None,
|
||||
media_urls: Optional[List[str]] = None,
|
||||
plugin_type: str = "action",
|
||||
) -> Optional[str]:
|
||||
"""
|
||||
创建新插件帖子
|
||||
|
||||
Args:
|
||||
title: 插件标题
|
||||
source_code: 插件源代码
|
||||
readme_content: README 内容
|
||||
metadata: 插件元数据
|
||||
media_urls: 图片 URL 列表
|
||||
plugin_type: 插件类型 (action/filter/pipe)
|
||||
|
||||
Returns:
|
||||
创建成功返回帖子 ID,失败返回 None
|
||||
"""
|
||||
# 构建 function 数据结构
|
||||
function_data = {
|
||||
"id": "", # 服务器会生成
|
||||
"name": title,
|
||||
"type": plugin_type,
|
||||
"content": source_code,
|
||||
"meta": {
|
||||
"description": metadata.get("description", "") if metadata else "",
|
||||
"manifest": metadata or {},
|
||||
},
|
||||
}
|
||||
|
||||
data = {"function": function_data}
|
||||
|
||||
result = self.create_post(
|
||||
title=title,
|
||||
content=(
|
||||
readme_content or metadata.get("description", "") if metadata else ""
|
||||
),
|
||||
post_type="function",
|
||||
data=data,
|
||||
media=media_urls,
|
||||
)
|
||||
|
||||
if result:
|
||||
return result.get("id")
|
||||
return None
|
||||
|
||||
# ========== 帖子/插件更新 ==========
|
||||
|
||||
def update_post(self, post_id: str, post_data: Dict) -> bool:
|
||||
"""
|
||||
更新帖子
|
||||
|
||||
Args:
|
||||
post_id: 帖子 ID
|
||||
post_data: 完整的帖子数据
|
||||
|
||||
Returns:
|
||||
是否成功
|
||||
"""
|
||||
url = f"{self.BASE_URL}/posts/{post_id}/update"
|
||||
response = requests.post(url, headers=self.headers, json=post_data)
|
||||
response.raise_for_status()
|
||||
return True
|
||||
|
||||
def update_plugin(
|
||||
self,
|
||||
post_id: str,
|
||||
source_code: str,
|
||||
readme_content: Optional[str] = None,
|
||||
metadata: Optional[Dict] = None,
|
||||
media_urls: Optional[List[str]] = None,
|
||||
) -> bool:
|
||||
"""
|
||||
更新插件(代码 + README + 元数据 + 图片)
|
||||
|
||||
Args:
|
||||
post_id: 帖子 ID
|
||||
source_code: 插件源代码
|
||||
readme_content: README 内容(用于社区页面展示)
|
||||
metadata: 插件元数据(title, version, description 等)
|
||||
media_urls: 图片 URL 列表
|
||||
|
||||
Returns:
|
||||
是否成功
|
||||
"""
|
||||
post_data = self.get_post(post_id)
|
||||
if not post_data:
|
||||
return False
|
||||
|
||||
# 确保结构存在
|
||||
if "data" not in post_data:
|
||||
post_data["data"] = {}
|
||||
if "function" not in post_data["data"]:
|
||||
post_data["data"]["function"] = {}
|
||||
if "meta" not in post_data["data"]["function"]:
|
||||
post_data["data"]["function"]["meta"] = {}
|
||||
if "manifest" not in post_data["data"]["function"]["meta"]:
|
||||
post_data["data"]["function"]["meta"]["manifest"] = {}
|
||||
|
||||
# 更新源代码
|
||||
post_data["data"]["function"]["content"] = source_code
|
||||
|
||||
# 更新 README(社区页面展示内容)
|
||||
if readme_content:
|
||||
post_data["content"] = readme_content
|
||||
|
||||
# 更新元数据
|
||||
if metadata:
|
||||
post_data["data"]["function"]["meta"]["manifest"].update(metadata)
|
||||
if "title" in metadata:
|
||||
post_data["title"] = metadata["title"]
|
||||
post_data["data"]["function"]["name"] = metadata["title"]
|
||||
if "description" in metadata:
|
||||
post_data["data"]["function"]["meta"]["description"] = metadata[
|
||||
"description"
|
||||
]
|
||||
|
||||
# 更新图片
|
||||
if media_urls:
|
||||
post_data["media"] = media_urls
|
||||
|
||||
return self.update_post(post_id, post_data)
|
||||
|
||||
# ========== 图片上传 ==========
|
||||
|
||||
def upload_image(self, file_path: str) -> Optional[str]:
|
||||
"""
|
||||
上传图片到 OpenWebUI 社区
|
||||
|
||||
Args:
|
||||
file_path: 图片文件路径
|
||||
|
||||
Returns:
|
||||
上传成功后的图片 URL,失败返回 None
|
||||
"""
|
||||
if not os.path.exists(file_path):
|
||||
return None
|
||||
|
||||
# 获取文件信息
|
||||
filename = os.path.basename(file_path)
|
||||
|
||||
# 根据文件扩展名确定 MIME 类型
|
||||
ext = os.path.splitext(filename)[1].lower()
|
||||
mime_types = {
|
||||
".png": "image/png",
|
||||
".jpg": "image/jpeg",
|
||||
".jpeg": "image/jpeg",
|
||||
".gif": "image/gif",
|
||||
".webp": "image/webp",
|
||||
}
|
||||
content_type = mime_types.get(ext, "application/octet-stream")
|
||||
|
||||
try:
|
||||
with open(file_path, "rb") as f:
|
||||
files = {"file": (filename, f, content_type)}
|
||||
# 上传时不使用 JSON Content-Type
|
||||
headers = {
|
||||
"Authorization": f"Bearer {self.api_key}",
|
||||
"Accept": "application/json",
|
||||
}
|
||||
response = requests.post(
|
||||
f"{self.BASE_URL}/files/",
|
||||
headers=headers,
|
||||
files=files,
|
||||
)
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
|
||||
# 返回图片 URL
|
||||
return result.get("url")
|
||||
except Exception as e:
|
||||
print(f" Warning: Failed to upload image: {e}")
|
||||
return None
|
||||
|
||||
# ========== 版本比较 ==========
|
||||
|
||||
def get_remote_version(self, post_id: str) -> Optional[str]:
|
||||
"""
|
||||
获取远程插件版本
|
||||
|
||||
Args:
|
||||
post_id: 帖子 ID
|
||||
|
||||
Returns:
|
||||
版本号,如果不存在返回 None
|
||||
"""
|
||||
post_data = self.get_post(post_id)
|
||||
if not post_data:
|
||||
return None
|
||||
return (
|
||||
post_data.get("data", {})
|
||||
.get("function", {})
|
||||
.get("meta", {})
|
||||
.get("manifest", {})
|
||||
.get("version")
|
||||
)
|
||||
|
||||
def version_needs_update(self, post_id: str, local_version: str) -> bool:
|
||||
"""
|
||||
检查是否需要更新
|
||||
|
||||
Args:
|
||||
post_id: 帖子 ID
|
||||
local_version: 本地版本号
|
||||
|
||||
Returns:
|
||||
如果本地版本与远程不同,返回 True
|
||||
"""
|
||||
remote_version = self.get_remote_version(post_id)
|
||||
if not remote_version:
|
||||
return True # 远程不存在,需要更新
|
||||
return local_version != remote_version
|
||||
|
||||
# ========== 插件发布 ==========
|
||||
|
||||
def publish_plugin_from_file(
|
||||
self, file_path: str, force: bool = False, auto_create: bool = True
|
||||
) -> Tuple[bool, str]:
|
||||
"""
|
||||
从文件发布插件(支持首次创建和更新)
|
||||
|
||||
Args:
|
||||
file_path: 插件文件路径
|
||||
force: 是否强制更新(忽略版本检查)
|
||||
auto_create: 如果没有 openwebui_id,是否自动创建新帖子
|
||||
|
||||
Returns:
|
||||
(是否成功, 消息)
|
||||
"""
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
content = f.read()
|
||||
|
||||
metadata = self._parse_frontmatter(content)
|
||||
if not metadata:
|
||||
return False, "No frontmatter found"
|
||||
|
||||
title = metadata.get("title")
|
||||
if not title:
|
||||
return False, "No title in frontmatter"
|
||||
|
||||
post_id = metadata.get("openwebui_id") or metadata.get("post_id")
|
||||
local_version = metadata.get("version")
|
||||
|
||||
# 查找 README
|
||||
readme_content = self._find_readme(file_path)
|
||||
|
||||
# 查找并上传图片
|
||||
media_urls = None
|
||||
image_path = self._find_image(file_path)
|
||||
if image_path:
|
||||
print(f" Found image: {os.path.basename(image_path)}")
|
||||
image_url = self.upload_image(image_path)
|
||||
if image_url:
|
||||
print(f" Uploaded image: {image_url}")
|
||||
media_urls = [image_url]
|
||||
|
||||
# 如果没有 post_id,尝试创建新帖子
|
||||
if not post_id:
|
||||
if not auto_create:
|
||||
return False, "No openwebui_id found and auto_create is disabled"
|
||||
|
||||
print(f" Creating new post for: {title}")
|
||||
new_post_id = self.create_plugin(
|
||||
title=title,
|
||||
source_code=content,
|
||||
readme_content=readme_content or metadata.get("description", ""),
|
||||
metadata=metadata,
|
||||
media_urls=media_urls,
|
||||
)
|
||||
|
||||
if new_post_id:
|
||||
# 将新 ID 写回本地文件
|
||||
self._inject_id_to_file(file_path, new_post_id)
|
||||
return True, f"Created new post (ID: {new_post_id})"
|
||||
return False, "Failed to create new post"
|
||||
|
||||
# 版本检查(仅对更新有效)
|
||||
if not force and local_version:
|
||||
if not self.version_needs_update(post_id, local_version):
|
||||
return True, f"Skipped: version {local_version} matches remote"
|
||||
|
||||
# 更新
|
||||
success = self.update_plugin(
|
||||
post_id=post_id,
|
||||
source_code=content,
|
||||
readme_content=readme_content or metadata.get("description", ""),
|
||||
metadata=metadata,
|
||||
media_urls=media_urls,
|
||||
)
|
||||
|
||||
if success:
|
||||
return True, f"Updated to version {local_version}"
|
||||
return False, "Update failed"
|
||||
|
||||
def _parse_frontmatter(self, content: str) -> Dict[str, str]:
|
||||
"""解析插件文件的 frontmatter"""
|
||||
match = re.search(r'^\s*"""\n(.*?)\n"""', content, re.DOTALL)
|
||||
if not match:
|
||||
match = re.search(r'"""\n(.*?)\n"""', content, re.DOTALL)
|
||||
if not match:
|
||||
return {}
|
||||
|
||||
frontmatter = match.group(1)
|
||||
meta = {}
|
||||
for line in frontmatter.split("\n"):
|
||||
if ":" in line:
|
||||
key, value = line.split(":", 1)
|
||||
meta[key.strip()] = value.strip()
|
||||
return meta
|
||||
|
||||
def _find_readme(self, plugin_file_path: str) -> Optional[str]:
|
||||
"""查找插件对应的 README 文件"""
|
||||
plugin_dir = os.path.dirname(plugin_file_path)
|
||||
base_name = os.path.basename(plugin_file_path).lower()
|
||||
|
||||
# 确定优先顺序
|
||||
if base_name.endswith("_cn.py"):
|
||||
readme_files = ["README_CN.md", "README.md"]
|
||||
else:
|
||||
readme_files = ["README.md", "README_CN.md"]
|
||||
|
||||
for readme_name in readme_files:
|
||||
readme_path = os.path.join(plugin_dir, readme_name)
|
||||
if os.path.exists(readme_path):
|
||||
with open(readme_path, "r", encoding="utf-8") as f:
|
||||
return f.read()
|
||||
return None
|
||||
|
||||
def _find_image(self, plugin_file_path: str) -> Optional[str]:
|
||||
"""
|
||||
查找插件对应的图片文件
|
||||
图片名称需要和插件文件名一致(不含扩展名)
|
||||
|
||||
例如:
|
||||
export_to_word.py -> export_to_word.png / export_to_word.jpg
|
||||
"""
|
||||
plugin_dir = os.path.dirname(plugin_file_path)
|
||||
plugin_name = os.path.splitext(os.path.basename(plugin_file_path))[0]
|
||||
|
||||
# 支持的图片格式
|
||||
image_extensions = [".png", ".jpg", ".jpeg", ".gif", ".webp"]
|
||||
|
||||
for ext in image_extensions:
|
||||
image_path = os.path.join(plugin_dir, plugin_name + ext)
|
||||
if os.path.exists(image_path):
|
||||
return image_path
|
||||
return None
|
||||
|
||||
def _inject_id_to_file(self, file_path: str, post_id: str) -> bool:
|
||||
"""
|
||||
将新创建的帖子 ID 写回本地插件文件的 frontmatter
|
||||
|
||||
Args:
|
||||
file_path: 插件文件路径
|
||||
post_id: 新创建的帖子 ID
|
||||
|
||||
Returns:
|
||||
是否成功
|
||||
"""
|
||||
try:
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
lines = f.readlines()
|
||||
|
||||
new_lines = []
|
||||
inserted = False
|
||||
in_frontmatter = False
|
||||
|
||||
for line in lines:
|
||||
# Check for start/end of frontmatter
|
||||
if line.strip() == '"""':
|
||||
if not in_frontmatter:
|
||||
in_frontmatter = True
|
||||
else:
|
||||
in_frontmatter = False
|
||||
|
||||
new_lines.append(line)
|
||||
|
||||
# Insert after version line
|
||||
if (
|
||||
in_frontmatter
|
||||
and not inserted
|
||||
and line.strip().startswith("version:")
|
||||
):
|
||||
new_lines.append(f"openwebui_id: {post_id}\n")
|
||||
inserted = True
|
||||
print(f" Injected openwebui_id: {post_id}")
|
||||
|
||||
if inserted:
|
||||
with open(file_path, "w", encoding="utf-8") as f:
|
||||
f.writelines(new_lines)
|
||||
return True
|
||||
|
||||
print(f" Warning: Could not inject ID (no version line found)")
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
print(f" Error injecting ID to file: {e}")
|
||||
return False
|
||||
|
||||
# ========== 统计功能 ==========
|
||||
|
||||
def generate_stats(self, posts: List[Dict]) -> Dict:
|
||||
"""
|
||||
生成统计数据
|
||||
|
||||
Args:
|
||||
posts: 帖子列表
|
||||
|
||||
Returns:
|
||||
统计数据字典
|
||||
"""
|
||||
stats = {
|
||||
"total_posts": len(posts),
|
||||
"total_downloads": 0,
|
||||
"total_likes": 0,
|
||||
"posts_by_type": {},
|
||||
"posts_detail": [],
|
||||
"generated_at": datetime.now(BEIJING_TZ).isoformat(),
|
||||
}
|
||||
|
||||
for post in posts:
|
||||
downloads = post.get("downloadCount", 0)
|
||||
likes = post.get("likeCount", 0)
|
||||
post_type = post.get("type", "unknown")
|
||||
|
||||
stats["total_downloads"] += downloads
|
||||
stats["total_likes"] += likes
|
||||
stats["posts_by_type"][post_type] = (
|
||||
stats["posts_by_type"].get(post_type, 0) + 1
|
||||
)
|
||||
|
||||
stats["posts_detail"].append(
|
||||
{
|
||||
"id": post.get("id"),
|
||||
"title": post.get("title"),
|
||||
"type": post_type,
|
||||
"downloads": downloads,
|
||||
"likes": likes,
|
||||
"created_at": post.get("createdAt"),
|
||||
"updated_at": post.get("updatedAt"),
|
||||
}
|
||||
)
|
||||
|
||||
# 按下载量排序
|
||||
stats["posts_detail"].sort(key=lambda x: x["downloads"], reverse=True)
|
||||
|
||||
return stats
|
||||
|
||||
|
||||
# 便捷函数
|
||||
def get_client(api_key: Optional[str] = None) -> OpenWebUICommunityClient:
|
||||
"""
|
||||
获取客户端实例
|
||||
|
||||
Args:
|
||||
api_key: API Key,如果为 None 则从环境变量获取
|
||||
|
||||
Returns:
|
||||
OpenWebUICommunityClient 实例
|
||||
"""
|
||||
key = api_key or os.environ.get("OPENWEBUI_API_KEY")
|
||||
if not key:
|
||||
raise ValueError("OPENWEBUI_API_KEY not set")
|
||||
return OpenWebUICommunityClient(key)
|
||||
615
scripts/openwebui_stats.py
Normal file
@@ -0,0 +1,615 @@
|
||||
#!/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: {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: {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_shields_endpoints(self, stats: dict, output_dir: str = "docs/badges"):
|
||||
"""
|
||||
生成 Shields.io endpoint JSON 文件
|
||||
|
||||
Args:
|
||||
stats: 统计数据
|
||||
output_dir: 输出目录
|
||||
"""
|
||||
Path(output_dir).mkdir(parents=True, exist_ok=True)
|
||||
|
||||
def format_number(n: int) -> str:
|
||||
"""格式化数字为易读格式"""
|
||||
if n >= 1000000:
|
||||
return f"{n/1000000:.1f}M"
|
||||
elif n >= 1000:
|
||||
return f"{n/1000:.1f}k"
|
||||
return str(n)
|
||||
|
||||
# 各种徽章数据
|
||||
badges = {
|
||||
"downloads": {
|
||||
"schemaVersion": 1,
|
||||
"label": "downloads",
|
||||
"message": format_number(stats["total_downloads"]),
|
||||
"color": "blue",
|
||||
"namedLogo": "openwebui",
|
||||
},
|
||||
"plugins": {
|
||||
"schemaVersion": 1,
|
||||
"label": "plugins",
|
||||
"message": str(stats["total_posts"]),
|
||||
"color": "green",
|
||||
},
|
||||
"followers": {
|
||||
"schemaVersion": 1,
|
||||
"label": "followers",
|
||||
"message": format_number(stats.get("user", {}).get("followers", 0)),
|
||||
"color": "blue",
|
||||
},
|
||||
"points": {
|
||||
"schemaVersion": 1,
|
||||
"label": "points",
|
||||
"message": format_number(stats.get("user", {}).get("total_points", 0)),
|
||||
"color": "orange",
|
||||
},
|
||||
"upvotes": {
|
||||
"schemaVersion": 1,
|
||||
"label": "upvotes",
|
||||
"message": format_number(stats["total_upvotes"]),
|
||||
"color": "brightgreen",
|
||||
},
|
||||
}
|
||||
|
||||
for name, data in badges.items():
|
||||
filepath = Path(output_dir) / f"{name}.json"
|
||||
with open(filepath, "w", encoding="utf-8") as f:
|
||||
json.dump(data, f, indent=2)
|
||||
print(f" 📊 Generated badge: {name}.json")
|
||||
|
||||
print(f"✅ Shields.io endpoints saved to: {output_dir}/")
|
||||
|
||||
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 6 插件
|
||||
top_plugins = stats["posts"][:6]
|
||||
|
||||
# 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')}",
|
||||
"author_header": "| 👤 作者 | 👥 粉丝 | ⭐ 积分 | 🏆 贡献 |",
|
||||
"header": "| 📝 发布 | ⬇️ 下载 | 👁️ 浏览 | 👍 点赞 | 💾 收藏 |",
|
||||
"top6_title": "### 🔥 热门插件 Top 6",
|
||||
"top6_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.zh.md)*",
|
||||
},
|
||||
"en": {
|
||||
"title": "## 📊 Community Stats",
|
||||
"updated": f"> 🕐 Auto-updated: {get_beijing_time().strftime('%Y-%m-%d %H:%M')}",
|
||||
"author_header": "| 👤 Author | 👥 Followers | ⭐ Points | 🏆 Contributions |",
|
||||
"header": "| 📝 Posts | ⬇️ Downloads | 👁️ Views | 👍 Upvotes | 💾 Saves |",
|
||||
"top6_title": "### 🔥 Top 6 Popular Plugins",
|
||||
"top6_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 6 热门插件
|
||||
lines.append(t["top6_title"])
|
||||
lines.append("")
|
||||
lines.append(t["top6_header"])
|
||||
lines.append("|:---:|------|:---:|:---:|")
|
||||
|
||||
medals = ["🥇", "🥈", "🥉", "4️⃣", "5️⃣", "6️⃣"]
|
||||
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.zh.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.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))
|
||||
|
||||
# 生成 Shields.io endpoint JSON (用于动态徽章)
|
||||
badges_dir = script_dir / "docs" / "badges"
|
||||
stats_client.generate_shields_endpoints(stats, str(badges_dir))
|
||||
|
||||
# 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())
|
||||
232
scripts/publish_plugin.py
Normal file
@@ -0,0 +1,232 @@
|
||||
"""
|
||||
Publish plugins to OpenWebUI Community
|
||||
使用 OpenWebUICommunityClient 发布插件到官方社区
|
||||
|
||||
用法:
|
||||
python scripts/publish_plugin.py # 更新已发布的插件(版本变化时)
|
||||
python scripts/publish_plugin.py --force # 强制更新所有已发布的插件
|
||||
python scripts/publish_plugin.py --new plugins/actions/xxx # 首次发布指定目录的新插件
|
||||
python scripts/publish_plugin.py --new plugins/actions/xxx --force # 强制发布新插件
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import re
|
||||
import argparse
|
||||
|
||||
# Add current directory to path
|
||||
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
|
||||
|
||||
from openwebui_community_client import get_client
|
||||
|
||||
|
||||
def find_existing_plugins(plugins_dir: str) -> list:
|
||||
"""查找所有已发布的插件文件(有 openwebui_id 的)"""
|
||||
plugins = []
|
||||
for root, _, files in os.walk(plugins_dir):
|
||||
for file in files:
|
||||
if file.endswith(".py") and not file.startswith("__"):
|
||||
file_path = os.path.join(root, file)
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
content = f.read(2000)
|
||||
|
||||
id_match = re.search(
|
||||
r"(?:openwebui_id|post_id):\s*([a-z0-9-]+)", content
|
||||
)
|
||||
if id_match:
|
||||
plugins.append(
|
||||
{
|
||||
"file_path": file_path,
|
||||
"post_id": id_match.group(1).strip(),
|
||||
}
|
||||
)
|
||||
return plugins
|
||||
|
||||
|
||||
def find_new_plugins_in_dir(target_dir: str) -> list:
|
||||
"""查找指定目录中没有 openwebui_id 的新插件"""
|
||||
plugins = []
|
||||
|
||||
if not os.path.isdir(target_dir):
|
||||
print(f"Error: {target_dir} is not a directory")
|
||||
return plugins
|
||||
|
||||
for file in os.listdir(target_dir):
|
||||
if file.endswith(".py") and not file.startswith("__"):
|
||||
file_path = os.path.join(target_dir, file)
|
||||
if not os.path.isfile(file_path):
|
||||
continue
|
||||
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
content = f.read(2000)
|
||||
|
||||
# 检查是否有 frontmatter (title)
|
||||
title_match = re.search(r"title:\s*(.+)", content)
|
||||
if not title_match:
|
||||
continue
|
||||
|
||||
# 检查是否已有 ID
|
||||
id_match = re.search(r"(?:openwebui_id|post_id):\s*([a-z0-9-]+)", content)
|
||||
if id_match:
|
||||
print(f" ⚠️ {file} already has ID, will update instead")
|
||||
plugins.append(
|
||||
{
|
||||
"file_path": file_path,
|
||||
"title": title_match.group(1).strip(),
|
||||
"post_id": id_match.group(1).strip(),
|
||||
"is_new": False,
|
||||
}
|
||||
)
|
||||
else:
|
||||
plugins.append(
|
||||
{
|
||||
"file_path": file_path,
|
||||
"title": title_match.group(1).strip(),
|
||||
"post_id": None,
|
||||
"is_new": True,
|
||||
}
|
||||
)
|
||||
|
||||
return plugins
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Publish plugins to OpenWebUI Market",
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
epilog="""
|
||||
Examples:
|
||||
# Update existing plugins (with version check)
|
||||
python scripts/publish_plugin.py
|
||||
|
||||
# Force update all existing plugins
|
||||
python scripts/publish_plugin.py --force
|
||||
|
||||
# Publish new plugins from a specific directory
|
||||
python scripts/publish_plugin.py --new plugins/actions/summary
|
||||
|
||||
# Preview what would be done
|
||||
python scripts/publish_plugin.py --new plugins/actions/summary --dry-run
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--force", action="store_true", help="Force update even if version matches"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--new",
|
||||
metavar="DIR",
|
||||
help="Publish new plugins from the specified directory (required for first-time publishing)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--dry-run",
|
||||
action="store_true",
|
||||
help="Show what would be done without actually publishing",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
client = get_client()
|
||||
except ValueError as e:
|
||||
print(f"Error: {e}")
|
||||
sys.exit(1)
|
||||
|
||||
base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
|
||||
plugins_dir = os.path.join(base_dir, "plugins")
|
||||
|
||||
updated = 0
|
||||
created = 0
|
||||
skipped = 0
|
||||
failed = 0
|
||||
|
||||
# 处理新插件发布
|
||||
if args.new:
|
||||
target_dir = args.new
|
||||
if not os.path.isabs(target_dir):
|
||||
target_dir = os.path.join(base_dir, target_dir)
|
||||
|
||||
print(f"🆕 Publishing new plugins from: {target_dir}\n")
|
||||
new_plugins = find_new_plugins_in_dir(target_dir)
|
||||
|
||||
if not new_plugins:
|
||||
print("No plugins found in the specified directory.")
|
||||
return
|
||||
|
||||
for plugin in new_plugins:
|
||||
file_path = plugin["file_path"]
|
||||
file_name = os.path.basename(file_path)
|
||||
title = plugin["title"]
|
||||
is_new = plugin.get("is_new", True)
|
||||
|
||||
if is_new:
|
||||
print(f"🆕 Creating: {file_name} ({title})")
|
||||
else:
|
||||
print(f"📦 Updating: {file_name} (ID: {plugin['post_id'][:8]}...)")
|
||||
|
||||
if args.dry_run:
|
||||
print(f" [DRY-RUN] Would {'create' if is_new else 'update'}")
|
||||
continue
|
||||
|
||||
success, message = client.publish_plugin_from_file(
|
||||
file_path, force=args.force, auto_create=True
|
||||
)
|
||||
|
||||
if success:
|
||||
if "Created" in message:
|
||||
print(f" 🎉 {message}")
|
||||
created += 1
|
||||
elif "Skipped" in message:
|
||||
print(f" ⏭️ {message}")
|
||||
skipped += 1
|
||||
else:
|
||||
print(f" ✅ {message}")
|
||||
updated += 1
|
||||
else:
|
||||
print(f" ❌ {message}")
|
||||
failed += 1
|
||||
|
||||
# 处理已有插件更新
|
||||
else:
|
||||
existing_plugins = find_existing_plugins(plugins_dir)
|
||||
print(f"Found {len(existing_plugins)} existing plugins with OpenWebUI ID.\n")
|
||||
|
||||
if not existing_plugins:
|
||||
print("No existing plugins to update.")
|
||||
print(
|
||||
"\n💡 Tip: Use --new <dir> to publish new plugins from a specific directory"
|
||||
)
|
||||
return
|
||||
|
||||
for plugin in existing_plugins:
|
||||
file_path = plugin["file_path"]
|
||||
file_name = os.path.basename(file_path)
|
||||
post_id = plugin["post_id"]
|
||||
|
||||
print(f"📦 {file_name} (ID: {post_id[:8]}...)")
|
||||
|
||||
if args.dry_run:
|
||||
print(f" [DRY-RUN] Would update")
|
||||
continue
|
||||
|
||||
success, message = client.publish_plugin_from_file(
|
||||
file_path, force=args.force, auto_create=False # 不自动创建,只更新
|
||||
)
|
||||
|
||||
if success:
|
||||
if "Skipped" in message:
|
||||
print(f" ⏭️ {message}")
|
||||
skipped += 1
|
||||
else:
|
||||
print(f" ✅ {message}")
|
||||
updated += 1
|
||||
else:
|
||||
print(f" ❌ {message}")
|
||||
failed += 1
|
||||
|
||||
print(f"\n{'='*50}")
|
||||
print(
|
||||
f"Finished: {created} created, {updated} updated, {skipped} skipped, {failed} failed"
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
138
scripts/sync_plugin_ids.py
Normal file
@@ -0,0 +1,138 @@
|
||||
"""
|
||||
Sync OpenWebUI Post IDs to local plugin files
|
||||
同步远程插件 ID 到本地文件
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import re
|
||||
import difflib
|
||||
|
||||
# Add current directory to path
|
||||
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
|
||||
|
||||
from openwebui_community_client import get_client
|
||||
|
||||
try:
|
||||
from extract_plugin_versions import scan_plugins_directory
|
||||
except ImportError:
|
||||
print("Error: extract_plugin_versions.py not found.")
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
def normalize(s):
|
||||
if not s:
|
||||
return ""
|
||||
return re.sub(r"\s+", " ", s.lower().strip())
|
||||
|
||||
|
||||
def insert_id_into_file(file_path, post_id):
|
||||
with open(file_path, "r", encoding="utf-8") as f:
|
||||
lines = f.readlines()
|
||||
|
||||
new_lines = []
|
||||
inserted = False
|
||||
in_frontmatter = False
|
||||
|
||||
for line in lines:
|
||||
# Check for start/end of frontmatter
|
||||
if line.strip() == '"""':
|
||||
if not in_frontmatter:
|
||||
in_frontmatter = True
|
||||
else:
|
||||
# End of frontmatter
|
||||
in_frontmatter = False
|
||||
|
||||
# Check if ID already exists
|
||||
if in_frontmatter and (
|
||||
line.strip().startswith("openwebui_id:")
|
||||
or line.strip().startswith("post_id:")
|
||||
):
|
||||
print(f" ID already exists in {os.path.basename(file_path)}")
|
||||
return False
|
||||
|
||||
new_lines.append(line)
|
||||
|
||||
# Insert after version
|
||||
if in_frontmatter and not inserted and line.strip().startswith("version:"):
|
||||
new_lines.append(f"openwebui_id: {post_id}\n")
|
||||
inserted = True
|
||||
|
||||
if inserted:
|
||||
with open(file_path, "w", encoding="utf-8") as f:
|
||||
f.writelines(new_lines)
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
def main():
|
||||
try:
|
||||
client = get_client()
|
||||
except ValueError as e:
|
||||
print(f"Error: {e}")
|
||||
sys.exit(1)
|
||||
|
||||
print("Fetching remote posts from OpenWebUI Community...")
|
||||
remote_posts = client.get_all_posts()
|
||||
print(f"Fetched {len(remote_posts)} remote posts.")
|
||||
|
||||
plugins_dir = os.path.join(
|
||||
os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "plugins"
|
||||
)
|
||||
local_plugins = scan_plugins_directory(plugins_dir)
|
||||
print(f"Found {len(local_plugins)} local plugins.")
|
||||
|
||||
matched_count = 0
|
||||
|
||||
for plugin in local_plugins:
|
||||
local_title = plugin.get("title", "")
|
||||
if not local_title:
|
||||
continue
|
||||
|
||||
file_path = plugin.get("file_path")
|
||||
best_match = None
|
||||
highest_ratio = 0.0
|
||||
|
||||
# 1. Try Exact Match on Manifest Title (High Confidence)
|
||||
for post in remote_posts:
|
||||
manifest_title = (
|
||||
post.get("data", {})
|
||||
.get("function", {})
|
||||
.get("meta", {})
|
||||
.get("manifest", {})
|
||||
.get("title")
|
||||
)
|
||||
if manifest_title and normalize(manifest_title) == normalize(local_title):
|
||||
best_match = post
|
||||
highest_ratio = 1.0
|
||||
break
|
||||
|
||||
# 2. Try Fuzzy Match on Post Title if no exact match
|
||||
if not best_match:
|
||||
for post in remote_posts:
|
||||
post_title = post.get("title", "")
|
||||
ratio = difflib.SequenceMatcher(
|
||||
None, normalize(local_title), normalize(post_title)
|
||||
).ratio()
|
||||
if ratio > 0.8 and ratio > highest_ratio:
|
||||
highest_ratio = ratio
|
||||
best_match = post
|
||||
|
||||
if best_match:
|
||||
post_id = best_match.get("id")
|
||||
post_title = best_match.get("title")
|
||||
print(
|
||||
f"Match found: '{local_title}' <--> '{post_title}' (ID: {post_id}) [Score: {highest_ratio:.2f}]"
|
||||
)
|
||||
|
||||
if insert_id_into_file(file_path, post_id):
|
||||
print(f" -> Updated {os.path.basename(file_path)}")
|
||||
matched_count += 1
|
||||
else:
|
||||
print(f"No match found for: '{local_title}'")
|
||||
|
||||
print(f"\nTotal updated: {matched_count}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||