docs: sync markdown_normalizer 1.2.2

docs: add nahoj as a contributor for ideas

.agent/rules/plugin_standards.md

@@ -0,0 +1,30 @@
+---
+description: Standards for OpenWebUI Plugin Development, specifically README formatting.
+globs: plugins/**
+always_on: true
+---
+# Plugin Development Standards
+
+## README Documentation
+
+All plugins MUST follow the standard README template.
+
+**Reference Template**: @docs/PLUGIN_README_TEMPLATE.md
+
+### Language Requirements
+- **English Version (`README.md`)**: The primary documentation source. Must follow the template strictly.
+- **Chinese Version (`README_CN.md`)**: MUST be translated based on the English version (`README.md`) to ensure consistency in structure and content.
+
+### Metadata Requirements
+The metadata line must follow this format:
+`**Author:** [Name](Link) | **Version:** [X.Y.Z] | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT`
+
+### Structure Checklist
+1.  **Title & Description**
+2.  **Metadata Line** (Author, Version, Project, License)
+3.  **Preview** (Screenshots/GIFs)
+4.  **What's New** (Keep last 3 versions)
+5.  **Key Features**
+6.  **How to Use**
+7.  **Configuration (Valves)**
+8.  **Troubleshooting** (Must include link to GitHub Issues)

.agent/workflows/plugin-development.md

@@ -25,6 +25,8 @@ 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 Context**: Use `_get_chat_context` helper method for `chat_id` and `message_id`.
+- **Debugging**: Use `_emit_debug_log` for frontend console logging (requires `SHOW_DEBUG_LOG` valve).
 - **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
@@ -86,6 +88,7 @@ Reference: `.github/workflows/release.yml`
     - 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`.
+    - **Auto-Sync**: If a local plugin has no ID but matches an existing published plugin by **Title**, the script will automatically fetch the ID, update the local file, and proceed with the update.
     - Requirement: `OPENWEBUI_API_KEY` secret must be set.
 
 ### Pull Request Check

.all-contributorsrc

@@ -0,0 +1,56 @@
+{
+  "files": [
+    "README.md"
+  ],
+  "imageSize": 100,
+  "commit": false,
+  "commitType": "docs",
+  "commitConvention": "angular",
+  "contributors": [
+    {
+      "login": "rbb-dev",
+      "name": "rbb-dev",
+      "avatar_url": "https://avatars.githubusercontent.com/u/37469229?v=4",
+      "profile": "https://github.com/rbb-dev",
+      "contributions": [
+        "ideas",
+        "code"
+      ]
+    },
+    {
+      "login": "dhaern",
+      "name": "Raxxoor",
+      "avatar_url": "https://avatars.githubusercontent.com/u/7317522?v=4",
+      "profile": "https://trade.xyz/?ref=BZ1RJRXWO",
+      "contributions": [
+        "bug",
+        "ideas"
+      ]
+    },
+    {
+      "login": "i-iooi-i",
+      "name": "ZOLO",
+      "avatar_url": "https://avatars.githubusercontent.com/u/1827701?v=4",
+      "profile": "https://github.com/i-iooi-i",
+      "contributions": [
+        "bug",
+        "ideas"
+      ]
+    },
+    {
+      "login": "nahoj",
+      "name": "Johan Grande",
+      "avatar_url": "https://avatars.githubusercontent.com/u/469017?v=4",
+      "profile": "https://perso.crans.org/grande/",
+      "contributions": [
+        "ideas"
+      ]
+    }
+  ],
+  "contributorsPerLine": 7,
+  "skipCi": true,
+  "repoType": "github",
+  "repoHost": "https://github.com",
+  "projectName": "awesome-openwebui",
+  "projectOwner": "Fu-Jie"
+}

.github/workflows/community-stats.yml

@@ -1,5 +1,9 @@
 # OpenWebUI 社区统计报告自动生成
-# 每小时自动获取并更新社区统计数据
+# 智能检测：只在有意义的变更时才 commit
+# - 新增插件 (total_posts)
+# - 插件版本变更 (version)
+# - 积分增加 (total_points)
+# - 粉丝增加 (followers)
 
 name: Community Stats
 
@@ -31,24 +35,95 @@ jobs:
       - name: Install dependencies
         run: |
           pip install requests python-dotenv
-      
+
+      - name: Capture existing stats (before update)
+        id: old_stats
+        run: |
+          if [ -f docs/community-stats.json ]; then
+            echo "total_posts=$(jq -r '.total_posts // 0' docs/community-stats.json)" >> $GITHUB_OUTPUT
+            echo "total_points=$(jq -r '.user.total_points // 0' docs/community-stats.json)" >> $GITHUB_OUTPUT
+            echo "followers=$(jq -r '.user.followers // 0' docs/community-stats.json)" >> $GITHUB_OUTPUT
+            # 提取所有插件的版本号，生成一个排序后的字符串用于比较
+            echo "versions=$(jq -r '[.posts[].version] | sort | join(",")' docs/community-stats.json)" >> $GITHUB_OUTPUT
+          else
+            echo "total_posts=0" >> $GITHUB_OUTPUT
+            echo "total_points=0" >> $GITHUB_OUTPUT
+            echo "followers=0" >> $GITHUB_OUTPUT
+            echo "versions=" >> $GITHUB_OUTPUT
+          fi
+
       - name: Generate stats report
         env:
           OPENWEBUI_API_KEY: ${{ secrets.OPENWEBUI_API_KEY }}
           OPENWEBUI_USER_ID: ${{ secrets.OPENWEBUI_USER_ID }}
         run: |
           python scripts/openwebui_stats.py
-      
-      - name: Check for changes
+
+      - name: Capture new stats (after update)
+        id: new_stats
+        run: |
+          echo "total_posts=$(jq -r '.total_posts // 0' docs/community-stats.json)" >> $GITHUB_OUTPUT
+          echo "total_points=$(jq -r '.user.total_points // 0' docs/community-stats.json)" >> $GITHUB_OUTPUT
+          echo "followers=$(jq -r '.user.followers // 0' docs/community-stats.json)" >> $GITHUB_OUTPUT
+          echo "versions=$(jq -r '[.posts[].version] | sort | join(",")' docs/community-stats.json)" >> $GITHUB_OUTPUT
+
+      - name: Check for significant changes
         id: check_changes
         run: |
-          git diff --quiet docs/community-stats.zh.md docs/community-stats.md README.md README_CN.md || echo "changed=true" >> $GITHUB_OUTPUT
-      
+          OLD_POSTS="${{ steps.old_stats.outputs.total_posts }}"
+          NEW_POSTS="${{ steps.new_stats.outputs.total_posts }}"
+          OLD_POINTS="${{ steps.old_stats.outputs.total_points }}"
+          NEW_POINTS="${{ steps.new_stats.outputs.total_points }}"
+          OLD_FOLLOWERS="${{ steps.old_stats.outputs.followers }}"
+          NEW_FOLLOWERS="${{ steps.new_stats.outputs.followers }}"
+          OLD_VERSIONS="${{ steps.old_stats.outputs.versions }}"
+          NEW_VERSIONS="${{ steps.new_stats.outputs.versions }}"
+          
+          SHOULD_COMMIT="false"
+          CHANGE_REASON=""
+          
+          # 检查新增插件
+          if [ "$NEW_POSTS" -gt "$OLD_POSTS" ]; then
+            SHOULD_COMMIT="true"
+            CHANGE_REASON="new plugin added ($OLD_POSTS -> $NEW_POSTS)"
+            echo "📦 New plugin detected: $OLD_POSTS -> $NEW_POSTS"
+          fi
+          
+          # 检查版本变更
+          if [ "$OLD_VERSIONS" != "$NEW_VERSIONS" ]; then
+            SHOULD_COMMIT="true"
+            CHANGE_REASON="${CHANGE_REASON:+$CHANGE_REASON, }plugin version updated"
+            echo "🔄 Plugin version changed"
+          fi
+          
+          # 检查积分增加
+          if [ "$NEW_POINTS" -gt "$OLD_POINTS" ]; then
+            SHOULD_COMMIT="true"
+            CHANGE_REASON="${CHANGE_REASON:+$CHANGE_REASON, }points increased ($OLD_POINTS -> $NEW_POINTS)"
+            echo "⭐ Points increased: $OLD_POINTS -> $NEW_POINTS"
+          fi
+          
+          # 检查粉丝增加
+          if [ "$NEW_FOLLOWERS" -gt "$OLD_FOLLOWERS" ]; then
+            SHOULD_COMMIT="true"
+            CHANGE_REASON="${CHANGE_REASON:+$CHANGE_REASON, }followers increased ($OLD_FOLLOWERS -> $NEW_FOLLOWERS)"
+            echo "👥 Followers increased: $OLD_FOLLOWERS -> $NEW_FOLLOWERS"
+          fi
+          
+          echo "should_commit=$SHOULD_COMMIT" >> $GITHUB_OUTPUT
+          echo "change_reason=$CHANGE_REASON" >> $GITHUB_OUTPUT
+          
+          if [ "$SHOULD_COMMIT" = "false" ]; then
+            echo "ℹ️ No significant changes detected, skipping commit"
+          else
+            echo "✅ Significant changes detected: $CHANGE_REASON"
+          fi
+
       - name: Commit and push changes
-        if: steps.check_changes.outputs.changed == 'true'
+        if: steps.check_changes.outputs.should_commit == '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 commit -m "chore: update community stats $(date +'%Y-%m-%d')"
+          git add docs/community-stats.zh.md docs/community-stats.md docs/community-stats.json docs/badges README.md README_CN.md
+          git diff --staged --quiet || git commit -m "chore: update community stats - ${{ steps.check_changes.outputs.change_reason }}"
           git push

.github/workflows/publish_plugin.yml

@@ -1,6 +1,11 @@
 name: Publish Plugins to OpenWebUI Market
 
 on:
+  push:
+    branches:
+      - main
+    paths:
+      - 'plugins/**/*.py'
   release:
     types: [published]
   workflow_dispatch:

CONTRIBUTING.md

@@ -1,87 +1,16 @@
-# 贡献指南 (Contributing Guide)
+# Contributing Guide
 
-感谢你对 **OpenWebUI Extras** 感兴趣！我们非常欢迎社区贡献更多的插件、提示词和创意。
+Thank you for your interest in **OpenWebUI Extras**!
 
-## 🤝 如何贡献
+## 🚀 How to Contribute
 
-### 1. 分享提示词 (Prompts)
+1. **Fork** this repository.
+2. **Add/Modify** the plugin file in the `plugins/` directory.
+3. **Submit PR**: We will review and merge it.
 
-如果你有一个好用的提示词：
-1. 在 `prompts/` 目录下找到合适的分类（如 `coding/`, `writing/`）。如果没有合适的，可以新建一个文件夹。
-2. 创建一个新的 `.md` 或 `.json` 文件。
-3. 提交 Pull Request (PR)。
+## 💡 Important
 
-### 2. 开发插件 (Plugins)
+- Ensure your plugin includes complete metadata (title, author, version, description).
+- If updating an existing plugin, please **increment the version number** (e.g., `0.1.0` -> `0.1.1`) to trigger the auto-update.
 
-如果你开发了一个新的 OpenWebUI 插件 (Function/Tool)：
-1. 确保你的插件代码包含完整的元数据（Frontmatter）：
-   ```python
-   """
-   title: 插件名称
-   author: 你的名字
-   version: 0.1.0
-   description: 简短描述插件的功能
-   """
-   ```
-2. 将插件文件放入 `plugins/` 目录下的合适位置：
-   - `plugins/actions/`: 用于添加按钮或修改消息的 Action 插件。
-   - `plugins/filters/`: 用于拦截请求或响应的 Filter 插件。
-   - `plugins/pipes/`: 用于自定义模型或 API 的 Pipe 插件。
-   - `plugins/tools/`: 用于 LLM 调用的 Tool 插件。
-3. 建议在 `docs/` 下添加一个简单的使用说明。
-
-### 3. 改进文档
-
-如果你发现文档有错误或可以改进的地方，直接提交 PR 即可。
-
-## 🛠️ 开发规范
-
-- **代码风格**：Python 代码请遵循 PEP 8 规范。
-- **注释**：关键逻辑请添加注释，方便他人理解。
-- **测试**：提交前请在本地 OpenWebUI 环境中测试通过。
-
-## 📝 提交 PR
-
-1. Fork 本仓库。
-2. 创建一个新的分支 (`git checkout -b feature/AmazingFeature`)。
-3. 提交你的修改 (`git commit -m 'Add some AmazingFeature'`)。
-4. 推送到分支 (`git push origin feature/AmazingFeature`)。
-5. 开启一个 Pull Request。
-
-## 📦 版本更新与发布
-
-当你更新插件时，请遵循以下流程：
-
-### 1. 更新版本号
-
-在插件文件的 docstring 中更新版本号（遵循[语义化版本](https://semver.org/lang/zh-CN/)）：
-
-```python
-"""
-title: 我的插件
-version: 0.2.0  # 更新此处
-...
-"""
-```
-
-### 2. 更新更新日志
-
-在 `CHANGELOG.md` 的 `[Unreleased]` 部分添加你的更改：
-
-```markdown
-### Added / 新增
-- 新功能描述
-
-### Fixed / 修复
-- Bug 修复描述
-```
-
-### 3. 发布流程
-
-维护者会通过以下方式发布新版本：
-- 手动触发 GitHub Actions 中的 "Plugin Release" 工作流
-- 或创建版本标签 (`v*`)
-
-详细说明请参阅 [发布工作流文档](docs/release-workflow.zh.md)。
-
-再次感谢你的贡献！🚀
+Thank you! 🚀

CONTRIBUTING_CN.md

@@ -0,0 +1,16 @@
+# 贡献指南
+
+感谢你对 **OpenWebUI Extras** 感兴趣！
+
+## 🚀 贡献流程
+
+1. **Fork** 本仓库。
+2. **修改/添加** `plugins/` 目录下的插件文件。
+3. **提交 PR**: 我们会尽快审核并合并。
+
+## 💡 注意事项
+
+- 请确保插件包含完整的元数据（title, author, version, description）。
+- 如果是更新已有插件，请记得**增加版本号**（如 `0.1.0` -> `0.1.1`），这样系统会自动同步更新。
+
+再次感谢你的贡献！🚀

README.md

@@ -1,4 +1,7 @@
 # OpenWebUI Extras
+<!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section -->
+[![All Contributors](https://img.shields.io/badge/all_contributors-4-orange.svg?style=flat-square)](#contributors-)
+<!-- ALL-CONTRIBUTORS-BADGE:END -->
 
 English | [中文](./README_CN.md)
 
@@ -7,26 +10,28 @@ A collection of enhancements, plugins, and prompts for [OpenWebUI](https://githu
 <!-- STATS_START -->
 ## 📊 Community Stats
 
-> 🕐 Auto-updated: 2026-01-08 08:35
+> 🕐 Auto-updated: 2026-01-17 17:07
 
 | 👤 Author | 👥 Followers | ⭐ Points | 🏆 Contributions |
 |:---:|:---:|:---:|:---:|
-| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **50** | **64** | **18** |
+| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **118** | **108** | **25** |
 
 | 📝 Posts | ⬇️ Downloads | 👁️ Views | 👍 Upvotes | 💾 Saves |
 |:---:|:---:|:---:|:---:|:---:|
-| **11** | **916** | **9670** | **55** | **50** |
+| **16** | **1622** | **19716** | **94** | **123** |
 
 ### 🔥 Top 6 Popular Plugins
 
-| Rank | Plugin | Downloads | Views |
-|:---:|------|:---:|:---:|
-| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 294 | 2550 |
-| 🥈 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 178 | 507 |
-| 🥉 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 119 | 1308 |
-| 4️⃣ | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 87 | 1123 |
-| 5️⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 84 | 1561 |
-| 6️⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 69 | 644 |
+> 🕐 Auto-updated: 2026-01-17 17:07
+
+| Rank | Plugin | Version | Downloads | Views | Updated |
+|:---:|------|:---:|:---:|:---:|:---:|
+| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 0.9.1 | 503 | 4601 | 2026-01-17 |
+| 🥈 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 1.4.9 | 217 | 2232 | 2026-01-17 |
+| 🥉 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 0.3.7 | 202 | 747 | 2026-01-07 |
+| 4️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 1.1.3 | 171 | 1889 | 2026-01-17 |
+| 5️⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 0.2.4 | 131 | 2254 | 2026-01-17 |
+| 6️⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 0.4.3 | 130 | 1234 | 2026-01-17 |
 
 *See full stats in [Community Stats Report](./docs/community-stats.md)*
 <!-- STATS_END -->
@@ -40,19 +45,15 @@ Located in the `plugins/` directory, containing Python-based enhancements:
 #### Actions
 - **Smart Mind Map** (`smart-mind-map`): Generates interactive mind maps from text.
 - **Smart Infographic** (`infographic`): Transforms text into professional infographics using AntV.
-- **Knowledge Card** (`knowledge-card`): Creates beautiful flashcards for learning.
+- **Flash Card** (`flash-card`): Quickly generates beautiful flashcards for learning.
+- **Deep Dive** (`deep-dive`): A comprehensive thinking lens that dives deep into any content.
 - **Export to Excel** (`export_to_excel`): Exports chat history to Excel files.
 - **Export to Word** (`export_to_docx`): Exports chat history to Word documents.
-- **Summary** (`summary`): Text summarization tool.
 
 #### Filters
 - **Async Context Compression** (`async-context-compression`): Optimizes token usage via context compression.
 - **Context Enhancement** (`context_enhancement_filter`): Enhances chat context.
-- **Gemini Manifold Companion** (`gemini_manifold_companion`): Companion filter for Gemini Manifold.
-
-
-#### Pipes
-- **Gemini Manifold** (`gemini_mainfold`): Pipeline for Gemini model integration.
+- **Markdown Normalizer** (`markdown_normalizer`): Fixes common Markdown formatting issues in LLM outputs.
 
 #### Pipelines
 - **MoE Prompt Refiner** (`moe_prompt_refiner`): Refines prompts for Mixture of Experts (MoE) summary requests to generate high-quality comprehensive reports.
@@ -104,3 +105,28 @@ If you have great prompts or plugins to share:
 3. Submit a Pull Request.
 
 [Contributing](./CONTRIBUTING.md)
+
+## Contributors ✨
+
+Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):
+
+<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
+<!-- prettier-ignore-start -->
+<!-- markdownlint-disable -->
+<table>
+  <tbody>
+    <tr>
+      <td align="center" valign="top" width="14.28%"><a href="https://github.com/rbb-dev"><img src="https://avatars.githubusercontent.com/u/37469229?v=4?s=100" width="100px;" alt="rbb-dev"/><br /><sub><b>rbb-dev</b></sub></a><br /><a href="#ideas-rbb-dev" title="Ideas, Planning, & Feedback">🤔</a> <a href="https://github.com/Fu-Jie/awesome-openwebui/commits?author=rbb-dev" title="Code">💻</a></td>
+      <td align="center" valign="top" width="14.28%"><a href="https://trade.xyz/?ref=BZ1RJRXWO"><img src="https://avatars.githubusercontent.com/u/7317522?v=4?s=100" width="100px;" alt="Raxxoor"/><br /><sub><b>Raxxoor</b></sub></a><br /><a href="https://github.com/Fu-Jie/awesome-openwebui/issues?q=author%3Adhaern" title="Bug reports">🐛</a> <a href="#ideas-dhaern" title="Ideas, Planning, & Feedback">🤔</a></td>
+      <td align="center" valign="top" width="14.28%"><a href="https://github.com/i-iooi-i"><img src="https://avatars.githubusercontent.com/u/1827701?v=4?s=100" width="100px;" alt="ZOLO"/><br /><sub><b>ZOLO</b></sub></a><br /><a href="https://github.com/Fu-Jie/awesome-openwebui/issues?q=author%3Ai-iooi-i" title="Bug reports">🐛</a> <a href="#ideas-i-iooi-i" title="Ideas, Planning, & Feedback">🤔</a></td>
+      <td align="center" valign="top" width="14.28%"><a href="https://perso.crans.org/grande/"><img src="https://avatars.githubusercontent.com/u/469017?v=4?s=100" width="100px;" alt="Johan Grande"/><br /><sub><b>Johan Grande</b></sub></a><br /><a href="#ideas-nahoj" title="Ideas, Planning, & Feedback">🤔</a></td>
+    </tr>
+  </tbody>
+</table>
+
+<!-- markdownlint-restore -->
+<!-- prettier-ignore-end -->
+
+<!-- ALL-CONTRIBUTORS-LIST:END -->
+
+This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!

README_CN.md

@@ -7,26 +7,28 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
 <!-- STATS_START -->
 ## 📊 社区统计
 
-> 🕐 自动更新于 2026-01-08 08:35
+> 🕐 自动更新于 2026-01-17 17:07
 
 | 👤 作者 | 👥 粉丝 | ⭐ 积分 | 🏆 贡献 |
 |:---:|:---:|:---:|:---:|
-| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **50** | **64** | **18** |
+| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **118** | **108** | **25** |
 
 | 📝 发布 | ⬇️ 下载 | 👁️ 浏览 | 👍 点赞 | 💾 收藏 |
 |:---:|:---:|:---:|:---:|:---:|
-| **11** | **916** | **9670** | **55** | **50** |
+| **16** | **1622** | **19716** | **94** | **123** |
 
 ### 🔥 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) | 294 | 2550 |
-| 🥈 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 178 | 507 |
-| 🥉 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 119 | 1308 |
-| 4️⃣ | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 87 | 1123 |
-| 5️⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 84 | 1561 |
-| 6️⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 69 | 644 |
+> 🕐 自动更新于 2026-01-17 17:07
+
+| 排名 | 插件 | 版本 | 下载 | 浏览 | 更新日期 |
+|:---:|------|:---:|:---:|:---:|:---:|
+| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 0.9.1 | 503 | 4601 | 2026-01-17 |
+| 🥈 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 1.4.9 | 217 | 2232 | 2026-01-17 |
+| 🥉 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 0.3.7 | 202 | 747 | 2026-01-07 |
+| 4️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 1.1.3 | 171 | 1889 | 2026-01-17 |
+| 5️⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 0.2.4 | 131 | 2254 | 2026-01-17 |
+| 6️⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 0.4.3 | 130 | 1234 | 2026-01-17 |
 
 *完整统计请查看 [社区统计报告](./docs/community-stats.zh.md)*
 <!-- STATS_END -->
@@ -40,15 +42,18 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
 #### Actions (交互增强)
 - **Smart Mind Map** (`smart-mind-map`): 智能分析文本并生成交互式思维导图。
 - **Smart Infographic** (`infographic`): 基于 AntV 的智能信息图生成工具。
-- **Knowledge Card** (`knowledge-card`): 快速生成精美的学习记忆卡片。
+- **Flash Card** (`flash-card`): 快速生成精美的学习记忆卡片。
+- **Deep Dive** (`deep-dive`): 深度思考透镜，从背景、逻辑、洞察到行动路径的全方位分析。
 - **Export to Excel** (`export_to_excel`): 将对话内容导出为 Excel 文件。
 - **Export to Word** (`export_to_docx`): 将对话内容导出为 Word 文档。
-- **Summary** (`summary`): 文本摘要生成工具。
 
 #### Filters (消息处理)
 - **Async Context Compression** (`async-context-compression`): 异步上下文压缩，优化 Token 使用。
 - **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。
+- **Gemini Multimodal Filter** (`web_gemini_multimodel_filter`): 为任意模型提供多模态能力（PDF、Office、视频等），支持智能路由和字幕精修。
+- **Markdown Normalizer** (`markdown_normalizer`): 修复 LLM 输出中常见的 Markdown 格式问题。
+- **Multi-Model Context Merger** (`multi_model_context_merger`): 自动合并并注入多模型回答的上下文。
 
 #### Pipes (模型管道)
 - **Gemini Manifold** (`gemini_mainfold`): 集成 Gemini 模型的管道。
@@ -105,4 +110,4 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
 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)
+[贡献指南](./CONTRIBUTING_CN.md) | [更新日志](./CHANGELOG.md)

docs/PLUGIN_README_TEMPLATE.md

@@ -0,0 +1,44 @@
+<!--
+NOTE: This template is for the English version (README.md).
+The Chinese version (README_CN.md) MUST be translated based on this English version to ensure consistency in structure and content.
+-->
+# [Plugin Name] [Optional Emoji]
+
+[Brief description of what the plugin does. Keep it concise and engaging.]
+
+**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 1.0.0 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
+
+## What's New
+
+<!-- Keep the changelog for the last 3 versions here. Remove this section for the initial release. -->
+
+### v1.0.0
+- **Initial Release**: Released the first version of the plugin.
+- **[Feature Name]**: [Brief description of the feature].
+
+## Key Features 🔑
+
+- **[Feature 1]**: [Description of feature 1].
+- **[Feature 2]**: [Description of feature 2].
+- **[Feature 3]**: [Description of feature 3].
+
+## How to Use 🛠️
+
+1. **Install**: Add the plugin to your OpenWebUI instance.
+2. **Configure**: Adjust settings in the Valves menu (optional).
+3. **[Action Step]**: Describe how to trigger or use the plugin.
+4. **[Result Step]**: Describe the expected outcome.
+
+## Configuration (Valves) ⚙️
+
+| Valve | Default | Description |
+|-------|---------|-------------|
+| `VALVE_NAME` | `Default Value` | Description of what this setting does. |
+| `ANOTHER_VALVE` | `True` | Another setting description. |
+
+## Troubleshooting ❓
+
+- **Plugin not working?**: Check if the filter/action is enabled in the model settings.
+- **Debug Logs**: Enable `SHOW_DEBUG_LOG` in Valves and check the browser console (F12) for detailed logs.
+- **Error Messages**: If you see an error, please copy the full error message and report it.
+- **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)

docs/badges/downloads.json

@@ -0,0 +1,7 @@
+{
+  "schemaVersion": 1,
+  "label": "downloads",
+  "message": "1.6k",
+  "color": "blue",
+  "namedLogo": "openwebui"
+}

docs/badges/followers.json

@@ -0,0 +1,6 @@
+{
+  "schemaVersion": 1,
+  "label": "followers",
+  "message": "118",
+  "color": "blue"
+}

docs/badges/plugins.json

@@ -0,0 +1,6 @@
+{
+  "schemaVersion": 1,
+  "label": "plugins",
+  "message": "16",
+  "color": "green"
+}

docs/badges/points.json

@@ -0,0 +1,6 @@
+{
+  "schemaVersion": 1,
+  "label": "points",
+  "message": "108",
+  "color": "orange"
+}

docs/badges/upvotes.json

@@ -0,0 +1,6 @@
+{
+  "schemaVersion": 1,
+  "label": "upvotes",
+  "message": "94",
+  "color": "brightgreen"
+}

docs/community-stats.json

@@ -1,14 +1,14 @@
 {
-  "total_posts": 11,
-  "total_downloads": 916,
-  "total_views": 9670,
-  "total_upvotes": 55,
-  "total_downvotes": 1,
-  "total_saves": 50,
-  "total_comments": 15,
+  "total_posts": 16,
+  "total_downloads": 1622,
+  "total_views": 19716,
+  "total_upvotes": 94,
+  "total_downvotes": 2,
+  "total_saves": 123,
+  "total_comments": 23,
   "by_type": {
-    "action": 9,
-    "filter": 2
+    "action": 14,
+    "unknown": 2
   },
   "posts": [
     {
@@ -18,15 +18,31 @@
       "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": 294,
-      "views": 2550,
-      "upvotes": 10,
-      "saves": 16,
-      "comments": 10,
+      "downloads": 503,
+      "views": 4601,
+      "upvotes": 13,
+      "saves": 28,
+      "comments": 11,
       "created_at": "2025-12-30",
-      "updated_at": "2026-01-07",
+      "updated_at": "2026-01-17",
       "url": "https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a"
     },
+    {
+      "title": "📊 Smart Infographic (AntV)",
+      "slug": "smart_infographic_ad6f0c7f",
+      "type": "action",
+      "version": "1.4.9",
+      "author": "Fu-Jie",
+      "description": "AI-powered infographic generator based on AntV Infographic. Supports professional templates, auto-icon matching, and SVG/PNG downloads.",
+      "downloads": 217,
+      "views": 2232,
+      "upvotes": 10,
+      "saves": 15,
+      "comments": 2,
+      "created_at": "2025-12-28",
+      "updated_at": "2026-01-17",
+      "url": "https://openwebui.com/posts/smart_infographic_ad6f0c7f"
+    },
     {
       "title": "Export to Excel",
       "slug": "export_mulit_table_to_excel_244b8f9d",
@@ -34,10 +50,10 @@
       "version": "0.3.7",
       "author": "Fu-Jie",
       "description": "Extracts tables from chat messages and exports them to Excel (.xlsx) files with smart formatting.",
-      "downloads": 178,
-      "views": 507,
+      "downloads": 202,
+      "views": 747,
       "upvotes": 3,
-      "saves": 3,
+      "saves": 5,
       "comments": 0,
       "created_at": "2025-05-30",
       "updated_at": "2026-01-07",
@@ -46,35 +62,19 @@
     {
       "title": "Async Context Compression",
       "slug": "async_context_compression_b1655bc8",
-      "type": "filter",
-      "version": "1.1.0",
+      "type": "action",
+      "version": "1.1.3",
       "author": "Fu-Jie",
       "description": "Reduces token consumption in long conversations while maintaining coherence through intelligent summarization and message compression.",
-      "downloads": 119,
-      "views": 1308,
-      "upvotes": 5,
-      "saves": 9,
+      "downloads": 171,
+      "views": 1889,
+      "upvotes": 7,
+      "saves": 18,
       "comments": 0,
       "created_at": "2025-11-08",
-      "updated_at": "2026-01-07",
+      "updated_at": "2026-01-17",
       "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": 87,
-      "views": 1123,
-      "upvotes": 7,
-      "saves": 8,
-      "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",
@@ -82,13 +82,13 @@
       "version": "0.2.4",
       "author": "Fu-Jie",
       "description": "Quickly generates beautiful flashcards from text, extracting key points and categories.",
-      "downloads": 84,
-      "views": 1561,
+      "downloads": 131,
+      "views": 2254,
       "upvotes": 8,
-      "saves": 5,
+      "saves": 10,
       "comments": 2,
       "created_at": "2025-12-30",
-      "updated_at": "2026-01-07",
+      "updated_at": "2026-01-17",
       "url": "https://openwebui.com/posts/flash_card_65a2ea8f"
     },
     {
@@ -98,31 +98,15 @@
       "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": 69,
-      "views": 644,
-      "upvotes": 5,
-      "saves": 5,
+      "downloads": 130,
+      "views": 1234,
+      "upvotes": 6,
+      "saves": 14,
       "comments": 0,
       "created_at": "2026-01-03",
-      "updated_at": "2026-01-07",
+      "updated_at": "2026-01-17",
       "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": 33,
-      "views": 434,
-      "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",
@@ -130,15 +114,63 @@
       "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": 20,
-      "views": 815,
-      "upvotes": 7,
-      "saves": 1,
+      "downloads": 58,
+      "views": 1246,
+      "upvotes": 9,
+      "saves": 3,
       "comments": 1,
       "created_at": "2026-01-04",
-      "updated_at": "2026-01-07",
+      "updated_at": "2026-01-17",
       "url": "https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0"
     },
+    {
+      "title": "Markdown Normalizer",
+      "slug": "markdown_normalizer_baaa8732",
+      "type": "action",
+      "version": "1.2.0",
+      "author": "Fu-Jie",
+      "description": "A content normalizer filter that fixes common Markdown formatting issues in LLM outputs, such as broken code blocks, LaTeX formulas, and list formatting.",
+      "downloads": 57,
+      "views": 1681,
+      "upvotes": 8,
+      "saves": 14,
+      "comments": 5,
+      "created_at": "2026-01-12",
+      "updated_at": "2026-01-17",
+      "url": "https://openwebui.com/posts/markdown_normalizer_baaa8732"
+    },
+    {
+      "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": 57,
+      "views": 597,
+      "upvotes": 3,
+      "saves": 5,
+      "comments": 0,
+      "created_at": "2026-01-08",
+      "updated_at": "2026-01-08",
+      "url": "https://openwebui.com/posts/deep_dive_c0b846e4"
+    },
+    {
+      "title": "📊 智能信息图 (AntV Infographic)",
+      "slug": "智能信息图_e04a48ff",
+      "type": "action",
+      "version": "1.4.9",
+      "author": "Fu-Jie",
+      "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": 41,
+      "views": 650,
+      "upvotes": 4,
+      "saves": 0,
+      "comments": 0,
+      "created_at": "2025-12-28",
+      "updated_at": "2026-01-17",
+      "url": "https://openwebui.com/posts/智能信息图_e04a48ff"
+    },
     {
       "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",
@@ -146,15 +178,31 @@
       "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": 15,
-      "views": 273,
+      "downloads": 22,
+      "views": 389,
       "upvotes": 2,
       "saves": 1,
       "comments": 0,
       "created_at": "2025-12-31",
-      "updated_at": "2026-01-07",
+      "updated_at": "2026-01-17",
       "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": "异步上下文压缩",
+      "slug": "异步上下文压缩_5c0617cb",
+      "type": "action",
+      "version": "1.1.3",
+      "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": 14,
+      "views": 337,
+      "upvotes": 4,
+      "saves": 1,
+      "comments": 0,
+      "created_at": "2025-11-08",
+      "updated_at": "2026-01-17",
+      "url": "https://openwebui.com/posts/异步上下文压缩_5c0617cb"
+    },
     {
       "title": "闪记卡 (Flash Card)",
       "slug": "闪记卡生成插件_4a31eac3",
@@ -162,30 +210,62 @@
       "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": 329,
-      "upvotes": 3,
+      "downloads": 13,
+      "views": 423,
+      "upvotes": 4,
       "saves": 1,
       "comments": 0,
       "created_at": "2025-12-30",
-      "updated_at": "2026-01-07",
+      "updated_at": "2026-01-17",
       "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",
+      "title": "精读",
+      "slug": "精读_99830b0f",
+      "type": "action",
+      "version": "1.0.0",
       "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": 5,
-      "views": 126,
+      "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": 6,
+      "views": 254,
       "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"
+      "created_at": "2026-01-08",
+      "updated_at": "2026-01-08",
+      "url": "https://openwebui.com/posts/精读_99830b0f"
+    },
+    {
+      "title": "Review of Claude Haiku 4.5",
+      "slug": "review_of_claude_haiku_45_41b0db39",
+      "type": "unknown",
+      "version": "",
+      "author": "",
+      "description": "",
+      "downloads": 0,
+      "views": 43,
+      "upvotes": 0,
+      "saves": 0,
+      "comments": 0,
+      "created_at": "2026-01-14",
+      "updated_at": "2026-01-14",
+      "url": "https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39"
+    },
+    {
+      "title": " 🛠️ Debug Open WebUI Plugins in Your Browser",
+      "slug": "debug_open_webui_plugins_in_your_browser_81bf7960",
+      "type": "unknown",
+      "version": "",
+      "author": "",
+      "description": "",
+      "downloads": 0,
+      "views": 1139,
+      "upvotes": 11,
+      "saves": 7,
+      "comments": 2,
+      "created_at": "2026-01-10",
+      "updated_at": "2026-01-10",
+      "url": "https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960"
     }
   ],
   "user": {
@@ -193,11 +273,11 @@
     "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": 50,
+    "followers": 118,
     "following": 2,
-    "total_points": 64,
-    "post_points": 54,
-    "comment_points": 10,
-    "contributions": 18
+    "total_points": 108,
+    "post_points": 92,
+    "comment_points": 16,
+    "contributions": 25
   }
 }

docs/community-stats.md

@@ -1,35 +1,40 @@
 # 📊 OpenWebUI Community Stats Report
 
-> 📅 Updated: 2026-01-08 08:35
+> 📅 Updated: 2026-01-17 17:07
 
 ## 📈 Overview
 
 | Metric | Value |
 |------|------|
-| 📝 Total Posts | 11 |
-| ⬇️ Total Downloads | 916 |
-| 👁️ Total Views | 9670 |
-| 👍 Total Upvotes | 55 |
-| 💾 Total Saves | 50 |
-| 💬 Total Comments | 15 |
+| 📝 Total Posts | 16 |
+| ⬇️ Total Downloads | 1622 |
+| 👁️ Total Views | 19716 |
+| 👍 Total Upvotes | 94 |
+| 💾 Total Saves | 123 |
+| 💬 Total Comments | 23 |
 
 ## 📂 By Type
 
-- **action**: 9
-- **filter**: 2
+- **action**: 14
+- **unknown**: 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 | 294 | 2550 | 10 | 16 | 2026-01-07 |
-| 2 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 178 | 507 | 3 | 3 | 2026-01-07 |
-| 3 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter | 1.1.0 | 119 | 1308 | 5 | 9 | 2026-01-07 |
-| 4 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.1 | 87 | 1123 | 7 | 8 | 2026-01-07 |
-| 5 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 84 | 1561 | 8 | 5 | 2026-01-07 |
-| 6 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 69 | 644 | 5 | 5 | 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 | 33 | 434 | 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 | 20 | 815 | 7 | 1 | 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 | 15 | 273 | 2 | 1 | 2026-01-07 |
-| 10 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 12 | 329 | 3 | 1 | 2026-01-07 |
-| 11 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | filter | 1.1.0 | 5 | 126 | 2 | 1 | 2026-01-07 |
+| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.9.1 | 503 | 4601 | 13 | 28 | 2026-01-17 |
+| 2 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.9 | 217 | 2232 | 10 | 15 | 2026-01-17 |
+| 3 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 202 | 747 | 3 | 5 | 2026-01-07 |
+| 4 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | action | 1.1.3 | 171 | 1889 | 7 | 18 | 2026-01-17 |
+| 5 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 131 | 2254 | 8 | 10 | 2026-01-17 |
+| 6 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 130 | 1234 | 6 | 14 | 2026-01-17 |
+| 7 | [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 | 58 | 1246 | 9 | 3 | 2026-01-17 |
+| 8 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | action | 1.2.0 | 57 | 1681 | 8 | 14 | 2026-01-17 |
+| 9 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action | 1.0.0 | 57 | 597 | 3 | 5 | 2026-01-08 |
+| 10 | [📊 智能信息图 (AntV Infographic)](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.4.9 | 41 | 650 | 4 | 0 | 2026-01-17 |
+| 11 | [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 | 22 | 389 | 2 | 1 | 2026-01-17 |
+| 12 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | action | 1.1.3 | 14 | 337 | 4 | 1 | 2026-01-17 |
+| 13 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 13 | 423 | 4 | 1 | 2026-01-17 |
+| 14 | [精读](https://openwebui.com/posts/精读_99830b0f) | action | 1.0.0 | 6 | 254 | 2 | 1 | 2026-01-08 |
+| 15 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | unknown |  | 0 | 43 | 0 | 0 | 2026-01-14 |
+| 16 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | unknown |  | 0 | 1139 | 11 | 7 | 2026-01-10 |

docs/community-stats.zh.md

@@ -1,35 +1,40 @@
 # 📊 OpenWebUI 社区统计报告
 
-> 📅 更新时间: 2026-01-08 08:35
+> 📅 更新时间: 2026-01-17 17:07
 
 ## 📈 总览
 
 | 指标 | 数值 |
 |------|------|
-| 📝 发布数量 | 11 |
-| ⬇️ 总下载量 | 916 |
-| 👁️ 总浏览量 | 9670 |
-| 👍 总点赞数 | 55 |
-| 💾 总收藏数 | 50 |
-| 💬 总评论数 | 15 |
+| 📝 发布数量 | 16 |
+| ⬇️ 总下载量 | 1622 |
+| 👁️ 总浏览量 | 19716 |
+| 👍 总点赞数 | 94 |
+| 💾 总收藏数 | 123 |
+| 💬 总评论数 | 23 |
 
 ## 📂 按类型分类
 
-- **action**: 9
-- **filter**: 2
+- **action**: 14
+- **unknown**: 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 | 294 | 2550 | 10 | 16 | 2026-01-07 |
-| 2 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 178 | 507 | 3 | 3 | 2026-01-07 |
-| 3 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter | 1.1.0 | 119 | 1308 | 5 | 9 | 2026-01-07 |
-| 4 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.1 | 87 | 1123 | 7 | 8 | 2026-01-07 |
-| 5 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 84 | 1561 | 8 | 5 | 2026-01-07 |
-| 6 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 69 | 644 | 5 | 5 | 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 | 33 | 434 | 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 | 20 | 815 | 7 | 1 | 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 | 15 | 273 | 2 | 1 | 2026-01-07 |
-| 10 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 12 | 329 | 3 | 1 | 2026-01-07 |
-| 11 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | filter | 1.1.0 | 5 | 126 | 2 | 1 | 2026-01-07 |
+| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.9.1 | 503 | 4601 | 13 | 28 | 2026-01-17 |
+| 2 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.9 | 217 | 2232 | 10 | 15 | 2026-01-17 |
+| 3 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 202 | 747 | 3 | 5 | 2026-01-07 |
+| 4 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | action | 1.1.3 | 171 | 1889 | 7 | 18 | 2026-01-17 |
+| 5 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 131 | 2254 | 8 | 10 | 2026-01-17 |
+| 6 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 130 | 1234 | 6 | 14 | 2026-01-17 |
+| 7 | [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 | 58 | 1246 | 9 | 3 | 2026-01-17 |
+| 8 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | action | 1.2.0 | 57 | 1681 | 8 | 14 | 2026-01-17 |
+| 9 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action | 1.0.0 | 57 | 597 | 3 | 5 | 2026-01-08 |
+| 10 | [📊 智能信息图 (AntV Infographic)](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.4.9 | 41 | 650 | 4 | 0 | 2026-01-17 |
+| 11 | [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 | 22 | 389 | 2 | 1 | 2026-01-17 |
+| 12 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | action | 1.1.3 | 14 | 337 | 4 | 1 | 2026-01-17 |
+| 13 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 13 | 423 | 4 | 1 | 2026-01-17 |
+| 14 | [精读](https://openwebui.com/posts/精读_99830b0f) | action | 1.0.0 | 6 | 254 | 2 | 1 | 2026-01-08 |
+| 15 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | unknown |  | 0 | 43 | 0 | 0 | 2026-01-14 |
+| 16 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | unknown |  | 0 | 1139 | 11 | 7 | 2026-01-10 |

docs/development/frontend-console-debugging.md

@@ -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!

docs/development/mermaid-syntax-standards.md

@@ -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.

docs/development/plugin-guide.md

@@ -7,10 +7,10 @@
 ## 📚 Table of Contents
 
 1. [Quick Start](#1-quick-start)
-2. [Core Concepts & SDK Details](#2-core-concepts--sdk-details)
+2. [Core Concepts & SDK Details](#2-core-concepts-sdk-details)
 3. [Deep Dive into Plugin Types](#3-deep-dive-into-plugin-types)
 4. [Advanced Development Patterns](#4-advanced-development-patterns)
-5. [Best Practices & Design Principles](#5-best-practices--design-principles)
+5. [Best Practices & Design Principles](#5-best-practices-design-principles)
 6. [Troubleshooting](#6-troubleshooting)
 
 ---
@@ -351,8 +351,7 @@ async def action(self, body, __event_call__, __metadata__, ...):
 
 #### 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
+- `plugins/actions/infographic/infographic.py` - Production-ready implementation using AntV + Data URL
 
 ---
 

docs/development/plugin-guide.zh.md

@@ -4,19 +4,19 @@
 
 ## 📚 目录
 
-1.  [插件开发快速入门](#1-插件开发快速入门)
-2.  [核心概念与 SDK 详解](#2-核心概念与-sdk-详解)
-3.  [插件类型深度解析](#3-插件类型深度解析)
-    *   [Action (动作)](#31-action-动作)
-    *   [Filter (过滤器)](#32-filter-过滤器)
-    *   [Pipe (管道)](#33-pipe-管道)
-4.  [高级开发模式](#4-高级开发模式)
-5.  [最佳实践与设计原则](#5-最佳实践与设计原则)
-6.  [故障排查](#6-故障排查)
+1.  [插件开发快速入门](#1-quick-start)
+2.  [核心概念与 SDK 详解](#2-core-concepts-sdk-details)
+3.  [插件类型深度解析](#3-plugin-types)
+    *   [Action (动作)](#31-action)
+    *   [Filter (过滤器)](#32-filter)
+    *   [Pipe (管道)](#33-pipe)
+4.  [高级开发模式](#4-advanced-patterns)
+5.  [最佳实践与设计原则](#5-best-practices)
+6.  [故障排查](#6-troubleshooting)
 
 ---
 
-## 1. 插件开发快速入门
+## 1. 插件开发快速入门 {: #1-quick-start }
 
 ### 1.1 什么是 OpenWebUI 插件？
 
@@ -64,7 +64,7 @@ class Action:
 
 ---
 
-## 2. 核心概念与 SDK 详解
+## 2. 核心概念与 SDK 详解 {: #2-core-concepts-sdk-details }
 
 ### 2.1 ⚠️ 重要：同步与异步
 
@@ -107,9 +107,9 @@ class Filter:
 
 ---
 
-## 3. 插件类型深度解析
+## 3. 插件类型深度解析 {: #3-plugin-types }
 
-### 3.1 Action (动作)
+### 3.1 Action (动作) {: #31-action }
 
 **定位**：在消息下方添加按钮，用户点击触发。
 
@@ -134,7 +134,7 @@ async def action(self, body, __event_call__):
     await __event_call__({"type": "execute", "data": {"code": js}})
 ```
 
-### 3.2 Filter (过滤器)
+### 3.2 Filter (过滤器) {: #32-filter }
 
 **定位**：中间件，拦截并修改请求/响应。
 
@@ -155,7 +155,7 @@ async def inlet(self, body, __metadata__):
     return body
 ```
 
-### 3.3 Pipe (管道)
+### 3.3 Pipe (管道) {: #33-pipe }
 
 **定位**：自定义模型/代理。
 
@@ -177,7 +177,7 @@ class Pipe:
 
 ---
 
-## 4. 高级开发模式
+## 4. 高级开发模式 {: #4-advanced-patterns }
 
 ### 4.1 Pipe 与 Filter 协同
 利用 `__request__.app.state` 在不同插件间共享数据。
@@ -315,10 +315,9 @@ async def action(self, body, __event_call__, __metadata__, ...):
 
 #### 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
+- `plugins/actions/infographic/infographic.py` - 基于 AntV + Data URL 的生产级实现
 
-## 5. 最佳实践与设计原则
+## 5. 最佳实践与设计原则 {: #5-best-practices }
 
 ### 5.1 命名与定位
 *   **简短有力**：如 "闪记卡", "精读"。避免 "文本分析助手" 这种泛词。
@@ -344,7 +343,7 @@ except Exception as e:
 
 ---
 
-## 6. 故障排查
+## 6. 故障排查 {: #6-troubleshooting }
 
 *   **HTML 不显示？** 确保包裹在 ` ```html ... ``` ` 代码块中。
 *   **数据库报错？** 检查是否在 `async` 函数中直接调用了同步的 DB 方法，请使用 `asyncio.to_thread`。

docs/index.md

@@ -73,13 +73,13 @@ hide:
 
     [:octicons-arrow-right-24: Learn More](plugins/actions/smart-mind-map.md)
 
--   :material-card-text:{ .lg .middle } **Knowledge Card**
+-   :material-card-text:{ .lg .middle } **Flash Card**
 
     ---
 
-    Quickly generates beautiful learning memory cards, perfect for studying and quick memorization.
+    Quickly generates beautiful flashcards from text, extracting key points and categories.
 
-    [:octicons-arrow-right-24: Learn More](plugins/actions/knowledge-card.md)
+    [:octicons-arrow-right-24: Learn More](plugins/actions/flash-card.md)
 
 -   :material-arrow-collapse-vertical:{ .lg .middle } **Async Context Compression**
 

docs/index.zh.md

@@ -73,13 +73,13 @@ hide:
 
     [:octicons-arrow-right-24: 了解更多](plugins/actions/smart-mind-map.md)
 
--   :material-card-text:{ .lg .middle } **知识卡片**
+-   :material-card-text:{ .lg .middle } **Flash Card（闪记卡）**
 
     ---
 
     快速生成精美的学习记忆卡片，非常适合学习和快速记忆。
 
-    [:octicons-arrow-right-24: 了解更多](plugins/actions/knowledge-card.md)
+    [:octicons-arrow-right-24: 了解更多](plugins/actions/flash-card.md)
 
 -   :material-arrow-collapse-vertical:{ .lg .middle } **异步上下文压缩**
 

docs/plugins/actions/flash-card.md

@@ -1,9 +1,9 @@
-# Knowledge Card
+# Flash Card
 
 <span class="category-badge action">Action</span>
-<span class="version-badge">v0.2.2</span>
+<span class="version-badge">v0.2.4</span>
 
-Quickly generates beautiful learning memory cards, perfect for studying and quick memorization.
+Quickly generates beautiful flashcards from text, extracting key points and categories.
 
 ---
 
@@ -23,7 +23,7 @@ The Knowledge Card plugin (also known as Flash Card / 闪记卡) transforms cont
 
 ## Installation
 
-1. Download the plugin file: [`knowledge_card.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/knowledge-card)
+1. Download the plugin file: [`flash_card.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/flash-card)
 2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
 3. Enable the plugin
 
@@ -85,4 +85,4 @@ The Knowledge Card plugin (also known as Flash Card / 闪记卡) transforms cont
 
 ## Source Code
 
-[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/knowledge-card){ .md-button }
+[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/flash-card){ .md-button }

docs/plugins/actions/flash-card.zh.md

@@ -1,7 +1,7 @@
-# Knowledge Card（知识卡片）
+# Flash Card（闪记卡）
 
 <span class="category-badge action">Action</span>
-<span class="version-badge">v0.2.0</span>
+<span class="version-badge">v0.2.4</span>
 
 快速生成精美的学习记忆卡片，适合学习和速记。
 
@@ -23,7 +23,7 @@ Knowledge Card 插件（又名 Flash Card / 闪记卡）会把内容转成视觉
 
 ## 安装
 
-1. 下载插件文件：[`knowledge_card.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/knowledge-card)
+1. 下载插件文件：[`flash_card.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/flash-card)
 2. 上传到 OpenWebUI：**Admin Panel** → **Settings** → **Functions**
 3. 启用插件
 
@@ -85,4 +85,4 @@ Knowledge Card 插件（又名 Flash Card / 闪记卡）会把内容转成视觉
 
 ## 源码
 
-[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/knowledge-card){ .md-button }
+[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/flash-card){ .md-button }

docs/plugins/actions/index.md

@@ -23,7 +23,7 @@ Actions are interactive plugins that:
 
     Intelligently analyzes text content and generates interactive mind maps with beautiful visualizations.
 
-    **Version:** 0.8.0
+    **Version:** 0.9.1
 
     [:octicons-arrow-right-24: Documentation](smart-mind-map.md)
 
@@ -33,19 +33,19 @@ Actions are interactive plugins that:
 
     Transform text into professional infographics using AntV visualization engine with various templates.
 
-    **Version:** 1.4.1
+    **Version:** 1.4.9
 
     [:octicons-arrow-right-24: Documentation](smart-infographic.md)
 
--   :material-card-text:{ .lg .middle } **Knowledge Card**
+-   :material-card-text:{ .lg .middle } **Flash Card**
 
     ---
 
-    Quickly generates beautiful learning memory cards, perfect for studying and memorization.
+    Quickly generates beautiful flashcards from text, extracting key points and categories.
 
-    **Version:** 0.2.2
+    **Version:** 0.2.4
 
-    [:octicons-arrow-right-24: Documentation](knowledge-card.md)
+    [:octicons-arrow-right-24: Documentation](flash-card.md)
 
 -   :material-file-excel:{ .lg .middle } **Export to Excel**
 
@@ -77,15 +77,7 @@ Actions are interactive plugins that:
 
     [: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>
 

docs/plugins/actions/index.zh.md

@@ -33,19 +33,19 @@ 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：** 1.4.1
+    **版本：** 1.4.9
 
     [:octicons-arrow-right-24: 查看文档](smart-infographic.md)
 
--   :material-card-text:{ .lg .middle } **Knowledge Card**
+-   :material-card-text:{ .lg .middle } **Flash Card（闪记卡）**
 
     ---
 
-    快速生成精美的学习记忆卡片，适合学习与记忆。
+    快速生成精美的学习记忆卡片，非常适合学习和快速记忆。
 
-    **版本：** 0.2.2
+    **版本：** 0.2.4
 
-    [:octicons-arrow-right-24: 查看文档](knowledge-card.md)
+    [:octicons-arrow-right-24: 查看文档](flash-card.md)
 
 -   :material-file-excel:{ .lg .middle } **Export to Excel**
 
@@ -77,15 +77,7 @@ Actions 是交互式插件，能够：
 
     [: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>
 

docs/plugins/actions/smart-infographic.md

@@ -1,7 +1,7 @@
 # Smart Infographic
 
 <span class="category-badge action">Action</span>
-<span class="version-badge">v1.4.0</span>
+<span class="version-badge">v1.4.9</span>
 
 An AntV Infographic engine powered plugin that transforms long text into professional, beautiful infographics with a single click.
 
@@ -14,8 +14,8 @@ The Smart Infographic plugin uses AI to analyze text content and generate profes
 ## Features
 
 - :material-robot: **AI-Powered Transformation**: Automatically analyzes text logic, extracts key points, and generates structured charts
-- :material-palette: **Professional Templates**: Includes various AntV official templates: Lists, Trees, Mindmaps, Comparison Tables, Flowcharts, and Statistical Charts
-- :material-magnify: **Auto-Icon Matching**: Built-in logic to search and match the most relevant Material Design Icons based on content
+- :material-palette: **70+ Professional Templates**: Includes various AntV official templates: Lists, Trees, Roadmaps, Timelines, Comparison Tables, SWOT, Quadrants, and Statistical Charts
+- :material-magnify: **Auto-Icon Matching**: Built-in logic to search and match the most relevant icons (Iconify) and illustrations (unDraw)
 - :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
@@ -37,10 +37,11 @@ The Smart Infographic plugin uses AI to analyze text content and generate profes
 
 | 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 |
+| **Sequence** | `sequence-timeline-simple`, `sequence-roadmap-vertical-simple`, `sequence-snake-steps-compact-card` | Timelines, Roadmaps, Processes |
+| **Lists** | `list-grid-candy-card-lite`, `list-row-horizontal-icon-arrow`, `list-column-simple-vertical-arrow` | Features, Bullet Points, Lists |
+| **Comparison** | `compare-binary-horizontal-underline-text-vs`, `compare-swot`, `quadrant-quarter-simple-card` | Pros/Cons, SWOT, Quadrants |
+| **Hierarchy** | `hierarchy-tree-tech-style-capsule-item`, `hierarchy-structure` | Org Charts, Structures |
+| **Charts** | `chart-column-simple`, `chart-bar-plain-text`, `chart-line-plain-text`, `chart-wordcloud` | Trends, Distributions, Metrics |
 
 ---
 

docs/plugins/actions/smart-infographic.zh.md

@@ -1,7 +1,7 @@
 # Smart Infographic（智能信息图）
 
 <span class="category-badge action">Action</span>
-<span class="version-badge">v1.4.0</span>
+<span class="version-badge">v1.4.9</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。
 
@@ -14,8 +14,8 @@ Smart Infographic 使用 AI 分析文本，并基于 AntV 可视化引擎生成
 ## 功能特性
 
 - :material-robot: **AI 转换**：自动分析文本逻辑，提取要点并生成结构化图表
-- :material-palette: **专业模板**：内置 AntV 官方模板：列表、树、思维导图、对比表、流程图、统计图等
-- :material-magnify: **自动匹配图标**：根据内容自动选择最合适的 Material Design Icons
+- :material-palette: **70+ 专业模板**：内置多种 AntV 官方模板，包括列表、树图、路线图、时间线、对比图、SWOT、象限图及统计图表等
+- :material-magnify: **自动匹配图标**：内置图标搜索逻辑，支持 Iconify 图标和 unDraw 插图自动匹配
 - :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
@@ -37,10 +37,11 @@ Smart Infographic 使用 AI 分析文本，并基于 AntV 可视化引擎生成
 
 | 分类 | 模板名称 | 典型场景 |
 |:---------|:--------------|:---------|
-| **列表与层级** | `list-grid`, `tree-vertical`, `mindmap` | 特性列表、组织结构、头脑风暴 |
-| **序列与关系** | `sequence-roadmap`, `relation-circle` | 路线图、循环流程、步骤拆解 |
-| **对比与分析** | `compare-binary`, `compare-swot`, `quadrant-quarter` | 优劣势、SWOT、象限分析 |
-| **图表与数据** | `chart-bar`, `chart-line`, `chart-pie` | 趋势、分布、指标对比 |
+| **时序与流程** | `sequence-timeline-simple`, `sequence-roadmap-vertical-simple`, `sequence-snake-steps-compact-card` | 时间线、路线图、步骤说明 |
+| **列表与网格** | `list-grid-candy-card-lite`, `list-row-horizontal-icon-arrow`, `list-column-simple-vertical-arrow` | 功能亮点、要点列举、清单 |
+| **对比与分析** | `compare-binary-horizontal-underline-text-vs`, `compare-swot`, `quadrant-quarter-simple-card` | 优劣势对比、SWOT 分析、象限图 |
+| **层级与结构** | `hierarchy-tree-tech-style-capsule-item`, `hierarchy-structure` | 组织架构、层级关系 |
+| **图表与数据** | `chart-column-simple`, `chart-bar-plain-text`, `chart-line-plain-text`, `chart-wordcloud` | 数据趋势、比例分布、数值对比 |
 
 ---
 

docs/plugins/actions/smart-mind-map.md

@@ -1,7 +1,7 @@
 # Smart Mind Map
 
 <span class="category-badge action">Action</span>
-<span class="version-badge">v0.8.0</span>
+<span class="version-badge">v0.9.1</span>
 
 Intelligently analyzes text content and generates interactive mind maps for better visualization and understanding.
 
@@ -23,7 +23,7 @@ The Smart Mind Map plugin transforms text content into beautiful, interactive mi
 
 ## Installation
 
-1. Download the plugin file: [`思维导图.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/smart-mind-map)
+1. Download the plugin file: [`smart_mind_map.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/smart-mind-map)
 2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions** (Actions)
 3. Enable the plugin, and optionally allow iframe same-origin access so theme auto-detection works
 

docs/plugins/actions/smart-mind-map.zh.md

@@ -1,7 +1,7 @@
 # Smart Mind Map（智能思维导图）
 
 <span class="category-badge action">Action</span>
-<span class="version-badge">v0.8.0</span>
+<span class="version-badge">v0.9.1</span>
 
 智能分析文本内容，生成交互式思维导图，帮助你更直观地理解信息结构。
 
@@ -23,7 +23,7 @@ Smart Mind Map 会将文本转换成漂亮的交互式思维导图。插件会
 
 ## 安装
 
-1. 下载插件文件：[`思维导图.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/smart-mind-map)
+1. 下载插件文件：[`smart_mind_map.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/actions/smart-mind-map)
 2. 上传到 OpenWebUI：**Admin Panel** → **Settings** → **Functions**（Actions）
 3. 启用插件，并可在设置中允许 iframe same-origin 以启用主题自动检测
 

docs/plugins/actions/summary.md

@@ -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 }

docs/plugins/actions/summary.zh.md

@@ -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 }

docs/plugins/filters/async-context-compression.md

@@ -1,7 +1,7 @@
 # Async Context Compression
 
 <span class="category-badge filter">Filter</span>
-<span class="version-badge">v1.1.0</span>
+<span class="version-badge">v1.1.3</span>
 
 Reduces token consumption in long conversations through intelligent summarization while maintaining conversational coherence.
 
@@ -29,6 +29,11 @@ This is especially useful for:
 - :material-clock-fast: **Async Processing**: Non-blocking background compression
 - :material-memory: **Context Preservation**: Keeps important information
 - :material-currency-usd-off: **Cost Reduction**: Minimize token usage
+- :material-console: **Frontend Debugging**: Debug logs in browser console
+- :material-alert-circle-check: **Enhanced Error Reporting**: Clear error status notifications
+- :material-check-all: **Open WebUI v0.7.x Compatibility**: Dynamic DB session handling
+- :material-account-convert: **Improved Compatibility**: Summary role changed to `assistant`
+- :material-shield-check: **Enhanced Stability**: Resolved race conditions in state management
 
 ---
 

docs/plugins/filters/async-context-compression.zh.md

@@ -1,7 +1,7 @@
 # Async Context Compression（异步上下文压缩）
 
 <span class="category-badge filter">Filter</span>
-<span class="version-badge">v1.1.0</span>
+<span class="version-badge">v1.1.3</span>
 
 通过智能摘要减少长对话的 token 消耗，同时保持对话连贯。
 
@@ -29,6 +29,11 @@ Async Context Compression 过滤器通过以下方式帮助管理长对话的 to
 - :material-clock-fast: **异步处理**：后台非阻塞压缩
 - :material-memory: **保留上下文**：尽量保留重要信息
 - :material-currency-usd-off: **降低成本**：减少 token 使用
+- :material-console: **前端调试**：支持浏览器控制台日志
+- :material-alert-circle-check: **增强错误报告**：清晰的错误状态通知
+- :material-check-all: **Open WebUI v0.7.x 兼容性**：动态数据库会话处理
+- :material-account-convert: **兼容性提升**：摘要角色改为 `assistant`
+- :material-shield-check: **稳定性增强**：解决状态管理竞态条件
 
 ---
 

docs/plugins/filters/gemini-manifold-companion.md

@@ -1,54 +0,0 @@
-# Gemini Manifold Companion
-
-<span class="category-badge filter">Filter</span>
-<span class="version-badge">v0.3.2</span>
-
-Companion filter for the Gemini Manifold pipe plugin, providing enhanced functionality.
-
----
-
-## Overview
-
-The Gemini Manifold Companion works alongside the [Gemini Manifold Pipe](../pipes/gemini-manifold.md) to provide additional processing and enhancement for Gemini model integrations.
-
-## Features
-
-- :material-handshake: **Seamless Integration**: Works with Gemini Manifold pipe
-- :material-format-text: **Message Formatting**: Optimizes messages for Gemini
-- :material-shield: **Error Handling**: Graceful handling of API issues
-- :material-tune: **Fine-tuning**: Additional configuration options
-
----
-
-## Installation
-
-1. First, install the [Gemini Manifold Pipe](../pipes/gemini-manifold.md)
-2. Download the companion filter: [`gemini_manifold_companion.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/filters/gemini_manifold_companion)
-3. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
-4. Enable the filter
-
----
-
-## Configuration
-
-| Option | Type | Default | Description |
-|--------|------|---------|-------------|
-| `auto_format` | boolean | `true` | Auto-format messages for Gemini |
-| `handle_errors` | boolean | `true` | Enable error handling |
-
----
-
-## Requirements
-
-!!! warning "Dependency"
-    This filter requires the **Gemini Manifold Pipe** to be installed and configured.
-
-!!! note "Prerequisites"
-    - OpenWebUI v0.3.0 or later
-    - Gemini Manifold Pipe installed
-
----
-
-## Source Code
-
-[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/filters/gemini_manifold_companion){ .md-button }

docs/plugins/filters/gemini-manifold-companion.zh.md

@@ -1,54 +0,0 @@
-# Gemini Manifold Companion
-
-<span class="category-badge filter">Filter</span>
-<span class="version-badge">v0.3.2</span>
-
-Gemini Manifold Pipe 的伴随过滤器，用于增强 Gemini 集成的处理效果。
-
----
-
-## 概览
-
-Gemini Manifold Companion 与 [Gemini Manifold Pipe](../pipes/gemini-manifold.md) 搭配使用，为 Gemini 模型集成提供额外的处理与优化。
-
-## 功能特性
-
-- :material-handshake: **无缝协同**：与 Gemini Manifold Pipe 配合工作
-- :material-format-text: **消息格式化**：针对 Gemini 优化消息
-- :material-shield: **错误处理**：更友好的 API 异常处理
-- :material-tune: **精细配置**：提供额外调优选项
-
----
-
-## 安装
-
-1. 先安装 [Gemini Manifold Pipe](../pipes/gemini-manifold.md)
-2. 下载伴随过滤器：[`gemini_manifold_companion.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/filters/gemini_manifold_companion)
-3. 上传到 OpenWebUI：**Admin Panel** → **Settings** → **Functions**
-4. 启用过滤器
-
----
-
-## 配置项
-
-| 选项 | 类型 | 默认值 | 说明 |
-|--------|------|---------|-------------|
-| `auto_format` | boolean | `true` | 为 Gemini 自动格式化消息 |
-| `handle_errors` | boolean | `true` | 开启错误处理 |
-
----
-
-## 运行要求
-
-!!! warning "依赖"
-    本过滤器需要先安装并配置 **Gemini Manifold Pipe**。
-
-!!! note "前置条件"
-    - OpenWebUI v0.3.0 及以上
-    - 已安装 Gemini Manifold Pipe
-
----
-
-## 源码
-
-[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/filters/gemini_manifold_companion){ .md-button }

docs/plugins/filters/index.md

@@ -22,7 +22,7 @@ Filters act as middleware in the message pipeline:
 
     Reduces token consumption in long conversations through intelligent summarization while maintaining coherence.
 
-    **Version:** 1.1.0
+    **Version:** 1.1.3
 
     [:octicons-arrow-right-24: Documentation](async-context-compression.md)
 
@@ -36,15 +36,37 @@ Filters act as middleware in the message pipeline:
 
     [:octicons-arrow-right-24: Documentation](context-enhancement.md)
 
--   :material-google:{ .lg .middle } **Gemini Manifold Companion**
+
+
+-   :material-format-paint:{ .lg .middle } **Markdown Normalizer**
 
     ---
 
-    Companion filter for the Gemini Manifold pipe plugin.
+    Fixes common Markdown formatting issues in LLM outputs, including Mermaid syntax, code blocks, and LaTeX formulas.
 
-    **Version:** 1.7.0
+    **Version:** 1.1.2
 
-    [:octicons-arrow-right-24: Documentation](gemini-manifold-companion.md)
+    [:octicons-arrow-right-24: Documentation](markdown_normalizer.md)
+
+-   :material-merge:{ .lg .middle } **Multi-Model Context Merger**
+
+    ---
+
+    Automatically merges context from multiple model responses in the previous turn, enabling collaborative answers.
+
+    **Version:** 0.1.0
+
+    [:octicons-arrow-right-24: Documentation](multi-model-context-merger.md)
+
+-   :material-file-document-multiple:{ .lg .middle } **Web Gemini Multimodal Filter**
+
+    ---
+
+    A powerful filter that provides multimodal capabilities (PDF, Office, Images, Audio, Video) to any model in OpenWebUI.
+
+    **Version:** 0.3.2
+
+    [:octicons-arrow-right-24: Documentation](web-gemini-multimodel.md)
 
 </div>
 

docs/plugins/filters/index.zh.md

@@ -22,7 +22,7 @@ Filter 充当消息管线中的中间件：
 
     通过智能总结减少长对话的 token 消耗，同时保持连贯性。
 
-    **版本：** 1.1.0
+    **版本：** 1.1.3
 
     [:octicons-arrow-right-24: 查看文档](async-context-compression.md)
 
@@ -36,15 +36,17 @@ Filter 充当消息管线中的中间件：
 
     [:octicons-arrow-right-24: 查看文档](context-enhancement.md)
 
--   :material-google:{ .lg .middle } **Gemini Manifold Companion**
+
+
+-   :material-format-paint:{ .lg .middle } **Markdown Normalizer**
 
     ---
 
-    Gemini Manifold Pipe 插件的伴随过滤器。
+    修复 LLM 输出中常见的 Markdown 格式问题，包括 Mermaid 语法、代码块和 LaTeX 公式。
 
-    **版本：** 1.7.0
+    **版本：** 1.0.1
 
-    [:octicons-arrow-right-24: 查看文档](gemini-manifold-companion.md)
+    [:octicons-arrow-right-24: 查看文档](markdown_normalizer.zh.md)
 
 </div>
 

docs/plugins/filters/markdown_normalizer.md

@@ -0,0 +1,86 @@
+# Markdown Normalizer Filter
+
+A content normalizer filter for Open WebUI that fixes common Markdown formatting issues in LLM outputs. It ensures that code blocks, LaTeX formulas, Mermaid diagrams, and other Markdown elements are rendered correctly.
+
+## Features
+
+* **Details Tag Normalization**: Ensures proper spacing for `<details>` tags (used for thought chains). Adds a blank line after `</details>` and ensures a newline after self-closing `<details />` tags to prevent rendering issues.
+* **Emphasis Spacing Fix**: Fixes extra spaces inside emphasis markers (e.g., `** text **` -> `**text**`) which can cause rendering failures. Includes safeguards to protect math expressions (e.g., `2 * 3 * 4`) and list variables.
+* **Mermaid Syntax Fix**: Automatically fixes common Mermaid syntax errors, such as unquoted node labels (including multi-line labels and citations) and unclosed subgraphs. **New in v1.1.2**: Comprehensive protection for edge labels (text on connecting lines) across all link types (solid, dotted, thick).
+* **Frontend Console Debugging**: Supports printing structured debug logs directly to the browser console (F12) for easier troubleshooting.
+* **Code Block Formatting**: Fixes broken code block prefixes, suffixes, and indentation.
+* **LaTeX Normalization**: Standardizes LaTeX formula delimiters (`\[` -> `$$`, `\(` -> `$`).
+* **Thought Tag Normalization**: Unifies thought tags (`<think>`, `<thinking>` -> `<thought>`).
+* **Escape Character Fix**: Cleans up excessive escape characters (`\\n`, `\\t`).
+* **List Formatting**: Ensures proper newlines in list items.
+* **Heading Fix**: Adds missing spaces in headings (`#Heading` -> `# Heading`).
+* **Table Fix**: Adds missing closing pipes in tables.
+* **XML Cleanup**: Removes leftover XML artifacts.
+
+## Usage
+
+1. Install the plugin in Open WebUI.
+2. Enable the filter globally or for specific models.
+3. Configure the enabled fixes in the **Valves** settings.
+4. (Optional) **Show Debug Log** is enabled by default in Valves. This prints structured logs to the browser console (F12).
+    > [!WARNING]
+    > As this is an initial version, some "negative fixes" might occur (e.g., breaking valid Markdown). If you encounter issues, please check the console logs, copy the "Original" vs "Normalized" content, and submit an issue.
+
+## Configuration (Valves)
+
+* `priority`: Filter priority (default: 50).
+* `enable_escape_fix`: Fix excessive escape characters.
+* `enable_thought_tag_fix`: Normalize thought tags.
+* `enable_details_tag_fix`: Normalize details tags (default: True).
+* `enable_code_block_fix`: Fix code block formatting.
+* `enable_latex_fix`: Normalize LaTeX formulas.
+* `enable_list_fix`: Fix list item newlines (Experimental).
+* `enable_unclosed_block_fix`: Auto-close unclosed code blocks.
+* `enable_fullwidth_symbol_fix`: Fix full-width symbols in code blocks.
+* `enable_mermaid_fix`: Fix Mermaid syntax errors.
+* `enable_heading_fix`: Fix missing space in headings.
+* `enable_table_fix`: Fix missing closing pipe in tables.
+* `enable_xml_tag_cleanup`: Cleanup leftover XML tags.
+* `enable_emphasis_spacing_fix`: Fix extra spaces in emphasis (default: True).
+* `show_status`: Show status notification when fixes are applied.
+* `show_debug_log`: Print debug logs to browser console.
+
+## Troubleshooting ❓
+
+* **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)
+
+## Changelog
+
+### v1.2.2
+
+* **Version Bump**: Documentation and metadata updated for the latest release.
+
+### v1.2.1
+
+* **Emphasis Spacing Fix**: Added a new fix for extra spaces inside emphasis markers (e.g., `** text **` -> `**text**`).
+  * Uses a recursive approach to handle nested emphasis (e.g., `**bold _italic _**`).
+  * Includes safeguards to prevent modifying math expressions (e.g., `2 * 3 * 4`) or list variables.
+  * Controlled by the `enable_emphasis_spacing_fix` valve (default: True).
+
+### v1.2.0
+
+* **Details Tag Support**: Added normalization for `<details>` tags.
+  * Ensures a blank line is added after `</details>` closing tags to separate thought content from the main response.
+  * Ensures a newline is added after self-closing `<details ... />` tags to prevent them from interfering with subsequent Markdown headings (e.g., fixing `<details/>#Heading`).
+  * Includes safeguard to prevent modification of `<details>` tags inside code blocks.
+
+### v1.1.2
+
+* **Mermaid Edge Label Protection**: Implemented comprehensive protection for edge labels (text on connecting lines) to prevent them from being incorrectly modified. Now supports all Mermaid link types including solid (`--`), dotted (`-.`), and thick (`==`) lines with or without arrows.
+* **Bug Fixes**: Fixed an issue where lines without arrows (e.g., `A -- text --- B`) were not correctly protected.
+
+### v1.1.0
+
+* **Mermaid Fix Refinement**: Improved regex to handle nested parentheses in node labels (e.g., `ID("Label (text)")`) and avoided matching connection labels.
+* **HTML Safeguard Optimization**: Refined `_contains_html` to allow common tags like `<br/>`, `<b>`, `<i>`, etc., ensuring Mermaid diagrams with these tags are still normalized.
+* **Full-width Symbol Cleanup**: Fixed duplicate keys and incorrect quote mapping in `FULLWIDTH_MAP`.
+* **Bug Fixes**: Fixed missing `Dict` import in Python files.
+
+## License
+
+MIT

docs/plugins/filters/markdown_normalizer.zh.md

@@ -0,0 +1,86 @@
+# Markdown 格式化过滤器 (Markdown Normalizer)
+
+这是一个用于 Open WebUI 的内容格式化过滤器，旨在修复 LLM 输出中常见的 Markdown 格式问题。它能确保代码块、LaTeX 公式、Mermaid 图表和其他 Markdown 元素被正确渲染。
+
+## 功能特性
+
+* **Details 标签规范化**: 确保 `<details>` 标签（常用于思维链）有正确的间距。在 `</details>` 后添加空行，并在自闭合 `<details />` 标签后添加换行，防止渲染问题。
+* **强调空格修复**: 修复强调标记内部的多余空格（例如 `** 文本 **` -> `**文本**`），这会导致 Markdown 渲染失败。包含保护机制，防止误修改数学表达式（如 `2 * 3 * 4`）或列表变量。
+* **Mermaid 语法修复**: 自动修复常见的 Mermaid 语法错误，如未加引号的节点标签（支持多行标签和引用标记）和未闭合的子图 (Subgraph)。**v1.1.2 新增**: 全面保护各种类型的连线标签（实线、虚线、粗线），防止被误修改。
+* **前端控制台调试**: 支持将结构化的调试日志直接打印到浏览器控制台 (F12)，方便排查问题。
+* **代码块格式化**: 修复破损的代码块前缀、后缀和缩进问题。
+* **LaTeX 规范化**: 标准化 LaTeX 公式定界符 (`\[` -> `$$`, `\(` -> `$`)。
+* **思维标签规范化**: 统一思维链标签 (`<think>`, `<thinking>` -> `<thought>`)。
+* **转义字符修复**: 清理过度的转义字符 (`\\n`, `\\t`)。
+* **列表格式化**: 确保列表项有正确的换行。
+* **标题修复**: 修复标题中缺失的空格 (`#标题` -> `# 标题`)。
+* **表格修复**: 修复表格中缺失的闭合管道符。
+* **XML 清理**: 移除残留的 XML 标签。
+
+## 使用方法
+
+1. 在 Open WebUI 中安装此插件。
+2. 全局启用或为特定模型启用此过滤器。
+3. 在 **Valves** 设置中配置需要启用的修复项。
+4. (可选) **显示调试日志 (Show Debug Log)** 在 Valves 中默认开启。这会将结构化的日志打印到浏览器控制台 (F12)。
+    > [!WARNING]
+    > 由于这是初版，可能会出现“负向修复”的情况（例如破坏了原本正确的格式）。如果您遇到问题，请务必查看控制台日志，复制“原始 (Original)”与“规范化 (Normalized)”的内容对比，并提交 Issue 反馈。
+
+## 配置项 (Valves)
+
+* `priority`: 过滤器优先级 (默认: 50)。
+* `enable_escape_fix`: 修复过度的转义字符。
+* `enable_thought_tag_fix`: 规范化思维标签。
+* `enable_details_tag_fix`: 规范化 Details 标签 (默认: True)。
+* `enable_code_block_fix`: 修复代码块格式。
+* `enable_latex_fix`: 规范化 LaTeX 公式。
+* `enable_list_fix`: 修复列表项换行 (实验性)。
+* `enable_unclosed_block_fix`: 自动闭合未闭合的代码块。
+* `enable_fullwidth_symbol_fix`: 修复代码块中的全角符号。
+* `enable_mermaid_fix`: 修复 Mermaid 语法错误。
+* `enable_heading_fix`: 修复标题中缺失的空格。
+* `enable_table_fix`: 修复表格中缺失的闭合管道符。
+* `enable_xml_tag_cleanup`: 清理残留的 XML 标签。
+* `enable_emphasis_spacing_fix`: 修复强调语法中的多余空格 (默认: True)。
+* `show_status`: 应用修复时显示状态通知。
+* `show_debug_log`: 在浏览器控制台打印调试日志。
+
+## 故障排除 (Troubleshooting) ❓
+
+* **提交 Issue**: 如果遇到任何问题，请在 GitHub 上提交 Issue：[Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)
+
+## 更新日志
+
+### v1.2.2
+
+* **版本更新**: 文档与元数据已同步到最新版本。
+
+### v1.2.1
+
+* **强调空格修复**: 新增了对强调标记内部多余空格的修复（例如 `** 文本 **` -> `**文本**`）。
+  * 采用递归方法处理嵌套强调（例如 `**加粗 _斜体 _**`）。
+  * 包含保护机制，防止误修改数学表达式（如 `2 * 3 * 4`）或列表变量。
+  * 通过 `enable_emphasis_spacing_fix` 开关控制（默认：开启）。
+
+### v1.2.0
+
+* **Details 标签支持**: 新增了对 `<details>` 标签的规范化支持。
+  * 确保在 `</details>` 闭合标签后添加空行，将思维内容与正文分隔开。
+  * 确保在自闭合 `<details ... />` 标签后添加换行，防止其干扰后续的 Markdown 标题（例如修复 `<details/>#标题`）。
+  * 包含保护机制，防止修改代码块内部的 `<details>` 标签。
+
+### v1.1.2
+
+* **Mermaid 连线标签保护**: 实现了全面的连线标签保护机制，防止连接线上的文字被误修改。现在支持所有 Mermaid 连线类型，包括实线 (`--`)、虚线 (`-.`) 和粗线 (`==`)，无论是否带有箭头。
+* **Bug 修复**: 修复了无箭头连线（如 `A -- text --- B`）未被正确保护的问题。
+
+### v1.1.0
+
+* **Mermaid 修复优化**: 改进了正则表达式以处理节点标签中的嵌套括号（如 `ID("标签 (文本)")`），并避免误匹配连接线上的文字。
+* **HTML 保护机制优化**: 优化了 `_contains_html` 检测，允许 `<br/>`, `<b>`, `<i>` 等常见标签，确保包含这些标签的 Mermaid 图表能被正常规范化。
+* **全角符号清理**: 修复了 `FULLWIDTH_MAP` 中的重复键名和错误的引号映射。
+* **Bug 修复**: 修复了 Python 文件中缺失的 `Dict` 类型导入。
+
+## 许可证
+
+MIT

docs/plugins/filters/multi-model-context-merger.md

@@ -0,0 +1,35 @@
+# Multi-Model Context Merger
+
+<span class="category-badge filter">Filter</span>
+<span class="version-badge">v0.1.0</span>
+
+Automatically merges context from multiple model responses in the previous turn, enabling collaborative answers.
+
+---
+
+## Overview
+
+This filter detects when multiple models have responded in the previous turn (e.g., using "Arena" mode or multiple models selected). It consolidates these responses and injects them as context for the current turn, allowing the next model to see what others have said.
+
+## Features
+
+- :material-merge: **Auto-Merge**: Consolidates responses from multiple models into a single context block.
+- :material-format-list-group: **Structured Injection**: Uses XML-like tags (`<response>`) to separate different model outputs.
+- :material-robot-confused: **Collaboration**: Enables models to build upon or critique each other's answers.
+
+---
+
+## Installation
+
+1. Download the plugin file: [`multi_model_context_merger.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/filters)
+2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
+3. Enable the filter.
+
+---
+
+## Usage
+
+1. Select **multiple models** in the chat (or use Arena mode).
+2. Ask a question. All models will respond.
+3. Ask a follow-up question.
+4. The filter will inject the previous responses from ALL models into the context of the current model(s).

docs/plugins/filters/multi-model-context-merger.zh.md

@@ -0,0 +1,35 @@
+# 多模型上下文合并 (Multi-Model Context Merger)
+
+<span class="category-badge filter">Filter</span>
+<span class="version-badge">v0.1.0</span>
+
+自动合并上一轮中多个模型的回答上下文，实现协作问答。
+
+---
+
+## 概述
+
+此过滤器检测上一轮是否由多个模型回复（例如使用“竞技场”模式或选择了多个模型）。它将这些回复合并并作为上下文注入到当前轮次，使下一个模型能够看到其他模型之前所说的内容。
+
+## 功能特性
+
+- :material-merge: **自动合并**: 将多个模型的回复合并为单个上下文块。
+- :material-format-list-group: **结构化注入**: 使用类似 XML 的标签 (`<response>`) 分隔不同模型的输出。
+- :material-robot-confused: **协作**: 允许模型基于彼此的回答进行构建或评论。
+
+---
+
+## 安装
+
+1. 下载插件文件: [`multi_model_context_merger.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/filters)
+2. 上传到 OpenWebUI: **管理员面板** → **设置** → **函数**
+3. 启用过滤器。
+
+---
+
+## 使用方法
+
+1. 在聊天中选择 **多个模型** (或使用竞技场模式)。
+2. 提问。所有模型都会回答。
+3. 提出后续问题。
+4. 过滤器会将所有模型之前的回答注入到当前模型的上下文中。

docs/plugins/filters/web-gemini-multimodel.md

@@ -0,0 +1,51 @@
+# Web Gemini Multimodal Filter
+
+<span class="category-badge filter">Filter</span>
+<span class="version-badge">v0.3.2</span>
+
+A powerful filter that provides multimodal capabilities (PDF, Office, Images, Audio, Video) to any model in OpenWebUI.
+
+---
+
+## Overview
+
+This plugin enables multimodal processing for any model by leveraging Gemini as an analyzer. It supports direct file processing for Gemini models and "Analyzer Mode" for other models (like DeepSeek, Llama), where Gemini analyzes the file and injects the result as context.
+
+## Features
+
+- :material-file-document-multiple: **Multimodal Support**: Process PDF, Word, Excel, PowerPoint, EPUB, MP3, MP4, and Images.
+- :material-router-network: **Smart Routing**:
+    - **Direct Mode**: Files are passed directly to Gemini models.
+    - **Analyzer Mode**: Files are analyzed by Gemini, and results are injected into the context for other models.
+- :material-history: **Persistent Context**: Maintains session history across multiple turns using OpenWebUI Chat ID.
+- :material-database-check: **Deduplication**: Automatically tracks analyzed file hashes to prevent redundant processing.
+- :material-subtitles: **Subtitle Enhancement**: Specialized mode for generating high-quality SRT subtitles from video/audio.
+
+---
+
+## Installation
+
+1. Download the plugin file: [`web_gemini_multimodel.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/filters/web_gemini_multimodel_filter)
+2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
+3. Configure the Gemini Adapter URL and other settings.
+4. Enable the filter globally or per chat.
+
+---
+
+## Configuration
+
+| Option | Type | Default | Description |
+|--------|------|---------|-------------|
+| `gemini_adapter_url` | string | `http://...` | URL of the Gemini Adapter service |
+| `target_model_keyword` | string | `"webgemini"` | Keyword to identify Gemini models |
+| `mode` | string | `"auto"` | `auto`, `direct`, or `analyzer` |
+| `analyzer_base_model_id` | string | `"gemini-3.0-pro"` | Model used for document analysis |
+| `subtitle_keywords` | string | `"字幕,srt"` | Keywords to trigger subtitle flow |
+
+---
+
+## Usage
+
+1. **Upload a file** (PDF, Image, Video, etc.) in the chat.
+2. **Ask a question** about the file.
+3. The plugin will automatically process the file and provide context to your selected model.

docs/plugins/filters/web-gemini-multimodel.zh.md

@@ -0,0 +1,51 @@
+# Web Gemini 多模态过滤器
+
+<span class="category-badge filter">Filter</span>
+<span class="version-badge">v0.3.2</span>
+
+一个强大的过滤器，为 OpenWebUI 中的任何模型提供多模态能力：PDF、Office、图片、音频、视频等。
+
+---
+
+## 概述
+
+此插件利用 Gemini 作为分析器，为任何模型提供多模态处理能力。它支持 Gemini 模型的直接文件处理，以及其他模型（如 DeepSeek, Llama）的“分析器模式”，即由 Gemini 分析文件并将结果注入上下文。
+
+## 功能特性
+
+- :material-file-document-multiple: **多模态支持**: 处理 PDF, Word, Excel, PowerPoint, EPUB, MP3, MP4 和图片。
+- :material-router-network: **智能路由**:
+    - **直连模式 (Direct Mode)**: 对于 Gemini 模型，文件直接传递（原生多模态）。
+    - **分析器模式 (Analyzer Mode)**: 对于非 Gemini 模型，文件由 Gemini 分析，结果注入为上下文。
+- :material-history: **持久上下文**: 利用 OpenWebUI 的 Chat ID 跨多轮对话维护会话历史。
+- :material-database-check: **数据库去重**: 自动记录已分析文件的哈希值，防止重复上传和分析。
+- :material-subtitles: **字幕增强**: 针对视频/音频上传的专用模式，生成高质量 SRT 字幕。
+
+---
+
+## 安装
+
+1. 下载插件文件: [`web_gemini_multimodel.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/filters/web_gemini_multimodel_filter)
+2. 上传到 OpenWebUI: **管理员面板** → **设置** → **函数**
+3. 配置 Gemini Adapter URL 和其他设置。
+4. 启用过滤器。
+
+---
+
+## 配置
+
+| 选项 | 类型 | 默认值 | 描述 |
+|------|------|--------|------|
+| `gemini_adapter_url` | string | `http://...` | Gemini Adapter 服务的 URL |
+| `target_model_keyword` | string | `"webgemini"` | 识别 Gemini 模型的关键字 |
+| `mode` | string | `"auto"` | `auto` (自动), `direct` (直连), 或 `analyzer` (分析器) |
+| `analyzer_base_model_id` | string | `"gemini-3.0-pro"` | 用于文档分析的模型 |
+| `subtitle_keywords` | string | `"字幕,srt"` | 触发字幕流程的关键字 |
+
+---
+
+## 使用方法
+
+1. 在聊天中 **上传文件** (PDF, 图片, 视频等)。
+2. 关于文件 **提问**。
+3. 插件会自动处理文件并为所选模型提供上下文。

docs/plugins/index.md

@@ -48,16 +48,15 @@ OpenWebUI supports four types of plugins, each serving a different purpose:
 
 | Plugin | Type | Description | Version |
 |--------|------|-------------|---------|
-| [Smart Mind Map](actions/smart-mind-map.md) | Action | Generate interactive mind maps from text | 0.8.0 |
-| [Smart Infographic](actions/smart-infographic.md) | Action | Transform text into professional infographics | 1.0.0 |
-| [Knowledge Card](actions/knowledge-card.md) | Action | Create beautiful learning flashcards | 0.2.0 |
-| [Export to Excel](actions/export-to-excel.md) | Action | Export chat history to Excel files | 1.0.0 |
-| [Export to Word](actions/export-to-word.md) | Action | Export chat content to Word (.docx) with formatting | 0.1.0 |
-| [Summary](actions/summary.md) | Action | Text summarization tool | 1.0.0 |
-| [Async Context Compression](filters/async-context-compression.md) | Filter | Intelligent context compression | 1.0.0 |
-| [Context Enhancement](filters/context-enhancement.md) | Filter | Enhance chat context | 1.0.0 |
-| [Gemini Manifold Companion](filters/gemini-manifold-companion.md) | Filter | Companion for Gemini Manifold | 1.0.0 |
-| [Gemini Manifold](pipes/gemini-manifold.md) | Pipe | Gemini model integration | 1.0.0 |
+| [Smart Mind Map](actions/smart-mind-map.md) | Action | Generate interactive mind maps from text | 0.9.1 |
+| [Smart Infographic](actions/smart-infographic.md) | Action | Transform text into professional infographics | 1.4.9 |
+| [Flash Card](actions/flash-card.md) | Action | Create beautiful learning flashcards | 0.2.4 |
+| [Export to Excel](actions/export-to-excel.md) | Action | Export chat history to Excel files | 0.3.7 |
+| [Export to Word](actions/export-to-word.md) | Action | Export chat content to Word (.docx) with formatting | 0.4.3 |
+| [Async Context Compression](filters/async-context-compression.md) | Filter | Intelligent context compression | 1.1.3 |
+| [Context Enhancement](filters/context-enhancement.md) | Filter | Enhance chat context | 0.3.0 |
+| [Multi-Model Context Merger](filters/multi-model-context-merger.md) | Filter | Merge context from multiple models | 0.1.0 |
+| [Web Gemini Multimodal Filter](filters/web-gemini-multimodel.md) | Filter | Multimodal capabilities for any model | 0.3.2 |
 | [MoE Prompt Refiner](pipelines/moe-prompt-refiner.md) | Pipeline | Multi-model prompt refinement | 1.0.0 |
 
 ---

docs/plugins/index.zh.md

@@ -48,16 +48,15 @@ OpenWebUI 支持四种类型的插件，每种都有不同的用途：
 
 | 插件 | 类型 | 描述 | 版本 |
 |--------|------|-------------|---------|
-| [Smart Mind Map（智能思维导图）](actions/smart-mind-map.md) | Action | 从文本生成交互式思维导图 | 0.8.0 |
-| [Smart Infographic（智能信息图）](actions/smart-infographic.md) | Action | 将文本转成专业信息图 | 1.0.0 |
-| [Knowledge Card（知识卡片）](actions/knowledge-card.md) | Action | 生成精美学习卡片 | 0.2.0 |
-| [Export to Excel（导出到 Excel）](actions/export-to-excel.md) | Action | 导出聊天记录为 Excel | 1.0.0 |
-| [Export to Word（导出为 Word）](actions/export-to-word.md) | Action | 将聊天内容导出为 Word (.docx) 并保留格式 | 0.1.0 |
-| [Summary（摘要）](actions/summary.md) | Action | 文本摘要工具 | 1.0.0 |
-| [Async Context Compression（异步上下文压缩）](filters/async-context-compression.md) | Filter | 智能上下文压缩 | 1.0.0 |
-| [Context Enhancement（上下文增强）](filters/context-enhancement.md) | Filter | 提升对话上下文 | 1.0.0 |
-| [Gemini Manifold Companion](filters/gemini-manifold-companion.md) | Filter | Gemini Manifold 伴侣 | 1.0.0 |
-| [Gemini Manifold](pipes/gemini-manifold.md) | Pipe | Gemini 模型集成 | 1.0.0 |
+| [Smart Mind Map（智能思维导图）](actions/smart-mind-map.md) | Action | 从文本生成交互式思维导图 | 0.9.1 |
+| [Smart Infographic（智能信息图）](actions/smart-infographic.md) | Action | 将文本转成专业信息图 | 1.4.9 |
+| [Flash Card（闪记卡）](actions/flash-card.md) | Action | 生成精美学习卡片 | 0.2.4 |
+| [Export to Excel（导出到 Excel）](actions/export-to-excel.md) | Action | 导出聊天记录为 Excel | 0.3.7 |
+| [Export to Word（导出为 Word）](actions/export-to-word.md) | Action | 将聊天内容导出为 Word (.docx) 并保留格式 | 0.4.3 |
+| [Async Context Compression（异步上下文压缩）](filters/async-context-compression.md) | Filter | 智能上下文压缩 | 1.1.3 |
+| [Context Enhancement（上下文增强）](filters/context-enhancement.md) | Filter | 提升对话上下文 | 0.3.0 |
+| [Multi-Model Context Merger（多模型上下文合并）](filters/multi-model-context-merger.md) | Filter | 合并多个模型的上下文 | 0.1.0 |
+| [Web Gemini Multimodal Filter（Web Gemini 多模态过滤器）](filters/web-gemini-multimodel.md) | Filter | 为任何模型提供多模态能力 | 0.3.2 |
 | [MoE Prompt Refiner](pipelines/moe-prompt-refiner.md) | Pipeline | 多模型提示词优化 | 1.0.0 |
 
 ---

docs/plugins/pipes/gemini-manifold.md

@@ -1,106 +0,0 @@
-# Gemini Manifold
-
-<span class="category-badge pipe">Pipe</span>
-<span class="version-badge">v1.0.0</span>
-
-Integration pipeline for Google's Gemini models with full streaming support.
-
----
-
-## Overview
-
-The Gemini Manifold pipe provides seamless integration with Google's Gemini AI models. It exposes Gemini models as selectable options in OpenWebUI, allowing you to use them just like any other model.
-
-## Features
-
-- :material-google: **Full Gemini Support**: Access all Gemini model variants
-- :material-stream: **Streaming**: Real-time response streaming
-- :material-image: **Multimodal**: Support for images and text
-- :material-shield: **Error Handling**: Robust error management
-- :material-tune: **Configurable**: Customize model parameters
-
----
-
-## Installation
-
-1. Download the plugin file: [`gemini_manifold.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/pipes/gemini_mainfold)
-2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
-3. Configure your Gemini API key
-4. Select Gemini models from the model dropdown
-
----
-
-## Configuration
-
-| Option | Type | Required | Description |
-|--------|------|----------|-------------|
-| `GEMINI_API_KEY` | string | Yes | Your Google AI Studio API key |
-| `DEFAULT_MODEL` | string | No | Default Gemini model to use |
-| `TEMPERATURE` | float | No | Response temperature (0-1) |
-| `MAX_TOKENS` | integer | No | Maximum response tokens |
-
----
-
-## Available Models
-
-When configured, the following models become available:
-
-- `gemini-pro` - Text-only model
-- `gemini-pro-vision` - Multimodal model
-- `gemini-1.5-pro` - Latest Pro model
-- `gemini-1.5-flash` - Fast response model
-
----
-
-## Usage
-
-1. After installation, go to any chat
-2. Open the model selector dropdown
-3. Look for models prefixed with your pipe name
-4. Select a Gemini model
-5. Start chatting!
-
----
-
-## Getting an API Key
-
-1. Visit [Google AI Studio](https://makersuite.google.com/app/apikey)
-2. Create a new API key
-3. Copy the key and paste it in the plugin configuration
-
-!!! warning "API Key Security"
-    Keep your API key secure. Never share it publicly or commit it to version control.
-
----
-
-## Companion Filter
-
-For enhanced functionality, consider installing the [Gemini Manifold Companion](../filters/gemini-manifold-companion.md) filter.
-
----
-
-## Requirements
-
-!!! note "Prerequisites"
-    - OpenWebUI v0.3.0 or later
-    - Valid Gemini API key
-    - Internet access to Google AI APIs
-
----
-
-## Troubleshooting
-
-??? question "Models not appearing?"
-    Ensure your API key is correctly configured and the plugin is enabled.
-
-??? question "API errors?"
-    Check your API key validity and quota limits in Google AI Studio.
-
-??? question "Slow responses?"
-    Consider using `gemini-1.5-flash` for faster response times.
-
----
-
-## Source Code
-
-[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/pipes/gemini_mainfold){ .md-button }

docs/plugins/pipes/gemini-manifold.zh.md

@@ -1,106 +0,0 @@
-# Gemini Manifold
-
-<span class="category-badge pipe">Pipe</span>
-<span class="version-badge">v1.0.0</span>
-
-面向 Google Gemini 模型的集成流水线，支持完整流式返回。
-
----
-
-## 概览
-
-Gemini Manifold Pipe 提供与 Google Gemini AI 模型的无缝集成。它会将 Gemini 模型作为可选项暴露在 OpenWebUI 中，你可以像使用其他模型一样使用它们。
-
-## 功能特性
-
-- :material-google: **完整 Gemini 支持**：可使用所有 Gemini 模型变体
-- :material-stream: **流式输出**：实时流式响应
-- :material-image: **多模态**：支持图像与文本
-- :material-shield: **错误处理**：健壮的错误管理
-- :material-tune: **可配置**：可自定义模型参数
-
----
-
-## 安装
-
-1. 下载插件文件：[`gemini_manifold.py`](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/pipes/gemini_mainfold)
-2. 上传到 OpenWebUI：**Admin Panel** → **Settings** → **Functions**
-3. 配置你的 Gemini API Key
-4. 在模型下拉中选择 Gemini 模型
-
----
-
-## 配置
-
-| 选项 | 类型 | 是否必填 | 说明 |
-|--------|------|----------|-------------|
-| `GEMINI_API_KEY` | string | 是 | 你的 Google AI Studio API Key |
-| `DEFAULT_MODEL` | string | 否 | 默认使用的 Gemini 模型 |
-| `TEMPERATURE` | float | 否 | 输出温度（0-1） |
-| `MAX_TOKENS` | integer | 否 | 最大回复 token 数 |
-
----
-
-## 可用模型
-
-配置完成后，你可以选择以下模型：
-
-- `gemini-pro` —— 纯文本模型
-- `gemini-pro-vision` —— 多模态模型
-- `gemini-1.5-pro` —— 最新 Pro 模型
-- `gemini-1.5-flash` —— 快速响应模型
-
----
-
-## 使用方法
-
-1. 安装后进入任意对话
-2. 打开模型选择下拉
-3. 查找以 Pipe 名称前缀的模型
-4. 选择 Gemini 模型
-5. 开始聊天！
-
----
-
-## 获取 API Key
-
-1. 访问 [Google AI Studio](https://makersuite.google.com/app/apikey)
-2. 创建新的 API Key
-3. 复制并粘贴到插件配置中
-
-!!! warning "API Key 安全"
-    请妥善保管你的 API Key，不要公开或提交到版本库。
-
----
-
-## 伴随过滤器
-
-如需增强功能，可安装 [Gemini Manifold Companion](../filters/gemini-manifold-companion.md) 过滤器。
-
----
-
-## 运行要求
-
-!!! note "前置条件"
-    - OpenWebUI v0.3.0 及以上
-    - 有效的 Gemini API Key
-    - 可访问 Google AI API 的网络
-
----
-
-## 常见问题
-
-??? question "模型没有出现？"
-    请确认 API Key 配置正确且插件已启用。
-
-??? question "出现 API 错误？"
-    检查 Google AI Studio 中的 Key 有效性和额度限制。
-
-??? question "响应较慢？"
-    可尝试使用 `gemini-1.5-flash` 获得更快速度。
-
----
-
-## 源码
-
-[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/awesome-openwebui/tree/main/plugins/pipes/gemini_mainfold){ .md-button }

docs/plugins/pipes/index.md

@@ -15,19 +15,7 @@ Pipes allow you to:
 
 ## Available Pipe Plugins
 
-<div class="grid cards" markdown>
 
--   :material-google:{ .lg .middle } **Gemini Manifold**
-
-    ---
-
-    Integration pipeline for Google's Gemini models with full streaming support.
-
-    **Version:** 1.0.0
-
-    [:octicons-arrow-right-24: Documentation](gemini-manifold.md)
-
-</div>
 
 ---
 

docs/plugins/pipes/index.zh.md

@@ -15,19 +15,7 @@ Pipes 可以用于：
 
 ## 可用的 Pipe 插件
 
-<div class="grid cards" markdown>
 
--   :material-google:{ .lg .middle } **Gemini Manifold**
-
-    ---
-
-    面向 Google Gemini 的集成流水线，支持完整流式返回。
-
-    **版本：** 1.0.0
-
-    [:octicons-arrow-right-24: 查看文档](gemini-manifold.md)
-
-</div>
 
 ---
 

mkdocs.yml

@@ -97,14 +97,14 @@ plugins:
             Documentation Guide: 文档编写指南
             Smart Mind Map: 智能思维导图
             Smart Infographic: 智能信息图
-            Knowledge Card: 知识卡片
+            Flash Card: 闪记卡
             Export to Excel: 导出到 Excel
             Export to Word: 导出为 Word
             Summary: 摘要
             Async Context Compression: 异步上下文压缩
             Context Enhancement: 上下文增强
-            Gemini Manifold Companion: Gemini Manifold 伴侣
-            Gemini Manifold: Gemini Manifold
+            Multi-Model Context Merger: 多模型上下文合并
+            Web Gemini Multimodal Filter: Web Gemini 多模态过滤器
             MoE Prompt Refiner: MoE 提示词优化器
   - minify:
       minify_html: true
@@ -184,18 +184,17 @@ nav:
       - plugins/actions/index.md
       - Smart Mind Map: plugins/actions/smart-mind-map.md
       - Smart Infographic: plugins/actions/smart-infographic.md
-      - Knowledge Card: plugins/actions/knowledge-card.md
+      - Flash Card: plugins/actions/flash-card.md
       - Export to Excel: plugins/actions/export-to-excel.md
       - Export to Word: plugins/actions/export-to-word.md
-      - Summary: plugins/actions/summary.md
     - Filters:
       - plugins/filters/index.md
       - Async Context Compression: plugins/filters/async-context-compression.md
       - Context Enhancement: plugins/filters/context-enhancement.md
-      - Gemini Manifold Companion: plugins/filters/gemini-manifold-companion.md
+      - Multi-Model Context Merger: plugins/filters/multi-model-context-merger.md
+      - Web Gemini Multimodal Filter: plugins/filters/web-gemini-multimodel.md
     - Pipes:
       - plugins/pipes/index.md
-      - Gemini Manifold: plugins/pipes/gemini-manifold.md
     - Pipelines:
       - plugins/pipelines/index.md
       - MoE Prompt Refiner: plugins/pipelines/moe-prompt-refiner.md

plugins/README.md

@@ -124,10 +124,6 @@ Each plugin should include:
 Fu-Jie
 GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
 
-## License
-
-MIT License
-
 ---
 
 > **Note**: For detailed information about each plugin type, see the respective README files in each plugin type directory.

plugins/README_CN.md

@@ -124,10 +124,6 @@ plugins/
 Fu-Jie
 GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
 
-## 许可证
-
-MIT License
-
 ---
 
 > **注意**：有关每种插件类型的详细信息，请参阅每个插件类型目录中的相应 README 文件。

plugins/actions/README.md

@@ -230,7 +230,3 @@ except Exception as e:
 
 Fu-Jie
 GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
-
-## License
-
-MIT License

plugins/actions/README_CN.md

@@ -229,7 +229,3 @@ except Exception as e:
 
 Fu-Jie
 GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
-
-## 许可证
-
-MIT License

plugins/actions/deep-dive/README.md

@@ -1,6 +1,6 @@
 # 🌊 Deep Dive
 
-**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 1.0.0 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui)
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 1.0.0 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
 
 A comprehensive thinking lens that dives deep into any content - from context to logic, insights, and action paths.
 
@@ -81,3 +81,10 @@ The plugin generates a structured thinking timeline:
 
 - `deep_dive.py` - English version
 - `deep_dive_cn.py` - Chinese version (精读)
+
+## Troubleshooting ❓
+
+- **Plugin not working?**: Check if the filter/action is enabled in the model settings.
+- **Debug Logs**: Enable `SHOW_STATUS` in Valves to see progress updates.
+- **Error Messages**: If you see an error, please copy the full error message and report it.
+- **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)

plugins/actions/deep-dive/README_CN.md

@@ -1,6 +1,6 @@
 # 📖 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)
+**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 1.0.0 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
 
 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。
 
@@ -81,3 +81,10 @@
 
 - `deep_dive.py` - 英文版 (Deep Dive)
 - `deep_dive_cn.py` - 中文版 (精读)
+
+## 故障排除 (Troubleshooting) ❓
+
+- **插件不工作？**: 请检查是否在模型设置中启用了该过滤器/动作。
+- **调试日志**: 在 Valves 中启用 `SHOW_STATUS` 以查看进度更新。
+- **错误信息**: 如果看到错误，请复制完整的错误信息并报告。
+- **提交 Issue**: 如果遇到任何问题，请在 GitHub 上提交 Issue：[Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)

plugins/actions/deep-dive/deep_dive.py

@@ -1,8 +1,8 @@
 """
 title: Deep Dive
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 1.0.0
 icon_url: data:image/svg+xml;base64,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
 requirements: markdown
@@ -466,6 +466,10 @@ class Action:
             default=True,
             description="Whether to show operation status updates.",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="Whether to print debug logs in the browser console.",
+        )
         MODEL_ID: str = Field(
             default="",
             description="LLM Model ID for analysis. Empty = use current model.",
@@ -501,6 +505,42 @@ class Action:
             "user_language": user_data.get("language", "en-US"),
         }
 
+    def _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        Unified extraction of chat context information (chat_id, message_id).
+        Prioritizes extraction from body, then metadata.
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. Try to get from body
+        if isinstance(body, dict):
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id is usually 'id' in body
+
+            # Check body.metadata as fallback
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
+
+        # 2. Try to get from __metadata__ (as supplement)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
+
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
+
     def _process_llm_output(self, llm_output: str) -> Dict[str, str]:
         """Parse LLM output and convert to styled HTML."""
         # Extract sections using flexible regex
@@ -700,6 +740,26 @@ class Action:
                 {"type": "notification", "data": {"type": ntype, "content": content}}
             )
 
+    async def _emit_debug_log(self, emitter, title: str, data: dict):
+        """Print structured debug logs in the browser console"""
+        if not self.valves.SHOW_DEBUG_LOG or not emitter:
+            return
+
+        try:
+            import json
+
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
     def _remove_existing_html(self, content: str) -> str:
         """Removes existing plugin-generated HTML."""
         pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"

plugins/actions/deep-dive/deep_dive_cn.py

@@ -1,8 +1,8 @@
 """
 title: 精读
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 1.0.0
 icon_url: data:image/svg+xml;base64,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
 requirements: markdown
@@ -466,6 +466,10 @@ class Action:
             default=True,
             description="是否显示操作状态更新。",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="是否在浏览器控制台打印调试日志。",
+        )
         MODEL_ID: str = Field(
             default="",
             description="用于分析的 LLM 模型 ID。留空则使用当前模型。",
@@ -501,6 +505,42 @@ class Action:
             "user_language": user_data.get("language", "zh-CN"),
         }
 
+    def _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        统一提取聊天上下文信息 (chat_id, message_id)。
+        优先从 body 中提取，其次从 metadata 中提取。
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. 尝试从 body 获取
+        if isinstance(body, dict):
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id 在 body 中通常是 id
+
+            # 再次检查 body.metadata
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
+
+        # 2. 尝试从 __metadata__ 获取 (作为补充)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
+
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
+
     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
@@ -694,6 +734,26 @@ class Action:
                 {"type": "notification", "data": {"type": ntype, "content": content}}
             )
 
+    async def _emit_debug_log(self, 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 emitter:
+            return
+
+        try:
+            import json
+
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
     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]*?```"

plugins/actions/export_to_docx/README.md

@@ -1,6 +1,6 @@
 # 📝 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)
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 0.4.3 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
 
 Export conversation to Word (.docx) with **syntax highlighting**, **native math equations**, **Mermaid diagrams**, **citations**, and **enhanced table formatting**.
 
@@ -86,3 +86,10 @@ Export conversation to Word (.docx) with **syntax highlighting**, **native math
 - **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.
+
+## Troubleshooting ❓
+
+- **Plugin not working?**: Check if the filter/action is enabled in the model settings.
+- **Debug Logs**: Check the browser console (F12) for detailed logs if available.
+- **Error Messages**: If you see an error, please copy the full error message and report it.
+- **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)

plugins/actions/export_to_docx/README_CN.md

@@ -1,6 +1,6 @@
 # 📝 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)
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 0.4.3 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
 
 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**。
 
@@ -86,3 +86,10 @@
 - **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。
+
+## 故障排除 (Troubleshooting) ❓
+
+- **插件不工作？**: 请检查是否在模型设置中启用了该过滤器/动作。
+- **调试日志**: 请查看浏览器控制台 (F12) 获取详细日志（如果可用）。
+- **错误信息**: 如果看到错误，请复制完整的错误信息并报告。
+- **提交 Issue**: 如果遇到任何问题，请在 GitHub 上提交 Issue：[Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)

plugins/actions/export_to_docx/export_to_word.py

@@ -1,8 +1,8 @@
 """
 title: Export to Word (Enhanced)
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 0.4.3
 openwebui_id: fca6a315-2a45-42cc-8c96-55cbc85f87f2
 icon_url: data:image/svg+xml;base64,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
@@ -150,6 +150,14 @@ class Action:
             default="chat_title",
             description="Title Source: 'chat_title' (Chat Title), 'ai_generated' (AI Generated), 'markdown_title' (Markdown Title)",
         )
+        SHOW_STATUS: bool = Field(
+            default=True,
+            description="Whether to show operation status updates.",
+        )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="Whether to print debug logs in the browser console.",
+        )
 
         MAX_EMBED_IMAGE_MB: int = Field(
             default=20,
@@ -320,10 +328,100 @@ class Action:
                 return msg
         return msg
 
-    async def _send_notification(self, emitter: Callable, type: str, content: str):
-        await emitter(
-            {"type": "notification", "data": {"type": type, "content": content}}
-        )
+    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 _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        Unified extraction of chat context information (chat_id, message_id).
+        Prioritizes extraction from body, then metadata.
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. Try to get from body
+        if isinstance(body, dict):
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id is usually 'id' in body
+
+            # Check body.metadata as fallback
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
+
+        # 2. Try to get from __metadata__ (as supplement)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
+
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
+
+    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 (info, success, warning, error)."""
+        if emitter:
+            await emitter(
+                {"type": "notification", "data": {"type": ntype, "content": content}}
+            )
+
+    async def _emit_debug_log(self, emitter, title: str, data: dict):
+        """Print structured debug logs in the browser console"""
+        if not self.valves.SHOW_DEBUG_LOG or not emitter:
+            return
+
+        try:
+            import json
+
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
 
     async def action(
         self,
@@ -397,14 +495,15 @@ class Action:
                     message_content = self._strip_reasoning_blocks(message_content)
 
                 if not message_content or not message_content.strip():
-                    await self._send_notification(
-                        __event_emitter__, "error", self._get_msg("error_no_content")
+                    await self._emit_notification(
+                        __event_emitter__, self._get_msg("error_no_content"), "error"
                     )
                     return
 
                 # Generate filename
                 title = ""
-                chat_id = self.extract_chat_id(body, __metadata__)
+                chat_ctx = self._get_chat_context(body, __metadata__)
+                chat_id = chat_ctx["chat_id"]
 
                 # Fetch chat_title directly via chat_id as it's usually missing in body
                 chat_title = ""
@@ -873,10 +972,10 @@ class Action:
                     }
                 )
 
-                await self._send_notification(
+                await self._emit_notification(
                     __event_emitter__,
-                    "success",
                     self._get_msg("success", filename=filename),
+                    "success",
                 )
 
                 return {"message": "Download triggered"}
@@ -892,10 +991,10 @@ class Action:
                         },
                     }
                 )
-                await self._send_notification(
+                await self._emit_notification(
                     __event_emitter__,
-                    "error",
                     self._get_msg("error_export", error=str(e)),
+                    "error",
                 )
 
     async def generate_title_using_ai(

plugins/actions/export_to_docx/export_to_word_cn.py

@@ -1,8 +1,8 @@
 """
 title: 导出为 Word (增强版)
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 0.4.3
 openwebui_id: 8a6306c0-d005-4e46-aaae-8db3532c9ed5
 icon_url: data:image/svg+xml;base64,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
@@ -150,6 +150,14 @@ class Action:
             default="chat_title",
             description="Title Source: 'chat_title' (Chat Title), 'ai_generated' (AI Generated), 'markdown_title' (Markdown Title)",
         )
+        SHOW_STATUS: bool = Field(
+            default=True,
+            description="是否显示操作状态更新。",
+        )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="是否在浏览器控制台打印调试日志。",
+        )
 
         最大嵌入图片大小MB: int = Field(
             default=20,
@@ -320,10 +328,100 @@ class Action:
                 return msg
         return msg
 
-    async def _send_notification(self, emitter: Callable, type: str, content: str):
-        await emitter(
-            {"type": "notification", "data": {"type": type, "content": content}}
-        )
+    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 _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        统一提取聊天上下文信息 (chat_id, message_id)。
+        优先从 body 中提取，其次从 metadata 中提取。
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. 尝试从 body 获取
+        if isinstance(body, dict):
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id 在 body 中通常是 id
+
+            # 再次检查 body.metadata
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
+
+        # 2. 尝试从 __metadata__ 获取 (作为补充)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
+
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
+
+    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 (info, success, warning, error)."""
+        if emitter:
+            await emitter(
+                {"type": "notification", "data": {"type": ntype, "content": content}}
+            )
+
+    async def _emit_debug_log(self, 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 emitter:
+            return
+
+        try:
+            import json
+
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
 
     async def action(
         self,
@@ -395,14 +493,15 @@ class Action:
                     message_content = self._strip_reasoning_blocks(message_content)
 
                 if not message_content or not message_content.strip():
-                    await self._send_notification(
-                        __event_emitter__, "error", self._get_msg("error_no_content")
+                    await self._emit_notification(
+                        __event_emitter__, self._get_msg("error_no_content"), "error"
                     )
                     return
 
                 # Generate filename
                 title = ""
-                chat_id = self.extract_chat_id(body, __metadata__)
+                chat_ctx = self._get_chat_context(body, __metadata__)
+                chat_id = chat_ctx["chat_id"]
 
                 # Fetch chat_title directly via chat_id as it's usually missing in body
                 chat_title = ""
@@ -871,10 +970,10 @@ class Action:
                     }
                 )
 
-                await self._send_notification(
+                await self._emit_notification(
                     __event_emitter__,
-                    "success",
                     self._get_msg("success", filename=filename),
+                    "success",
                 )
 
                 return {"message": "Download triggered"}
@@ -890,10 +989,10 @@ class Action:
                         },
                     }
                 )
-                await self._send_notification(
+                await self._emit_notification(
                     __event_emitter__,
-                    "error",
                     self._get_msg("error_export", error=str(e)),
+                    "error",
                 )
 
     async def generate_title_using_ai(

plugins/actions/export_to_excel/export_to_excel.py

@@ -1,8 +1,8 @@
 """
 title: Export to Excel
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 0.3.7
 openwebui_id: 244b8f9d-7459-47d6-84d3-c7ae8e3ec710
 icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxwYXRoIGQ9Ik0xNSAySDZhMiAyIDAgMCAwLTIgMnYxNmEyIDIgMCAwIDAgMiAyaDEyYTIgMiAwIDAgMCAyLTJWN1oiLz48cGF0aCBkPSJNMTQgMnY0YTIgMiAwIDAgMCAyIDJoNCIvPjxwYXRoIGQ9Ik04IDEzaDIiLz48cGF0aCBkPSJNMTQgMTNoMiIvPjxwYXRoIGQ9Ik04IDE3aDIiLz48cGF0aCBkPSJNMTQgMTdoMiIvPjwvc3ZnPg==
@@ -32,6 +32,10 @@ class Action:
             default="chat_title",
             description="Title Source: 'chat_title' (Chat Title), 'ai_generated' (AI Generated), 'markdown_title' (Markdown Title)",
         )
+        SHOW_STATUS: bool = Field(
+            default=True,
+            description="Whether to show operation status updates.",
+        )
         EXPORT_SCOPE: Literal["last_message", "all_messages"] = Field(
             default="last_message",
             description="Export Scope: 'last_message' (Last Message Only), 'all_messages' (All Messages)",
@@ -40,14 +44,57 @@ class Action:
             default="",
             description="Model ID for AI title generation. Leave empty to use the current chat model.",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="Whether to print debug logs in the browser console.",
+        )
 
     def __init__(self):
         self.valves = self.Valves()
 
-    async def _send_notification(self, emitter: Callable, type: str, content: str):
-        await emitter(
-            {"type": "notification", "data": {"type": type, "content": content}}
-        )
+    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 (info, success, warning, error)."""
+        if emitter:
+            await emitter(
+                {"type": "notification", "data": {"type": ntype, "content": content}}
+            )
+
+    async def _emit_debug_log(self, emitter, title: str, data: dict):
+        """Print structured debug logs in the browser console"""
+        if not self.valves.SHOW_DEBUG_LOG or not emitter:
+            return
+
+        try:
+            import json
+
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
 
     async def action(
         self,
@@ -190,17 +237,18 @@ class Action:
                 # Notify user about the number of tables found
                 table_count = len(all_tables)
                 if self.valves.EXPORT_SCOPE == "all_messages":
-                    await self._send_notification(
+                    await self._emit_notification(
                         __event_emitter__,
-                        "info",
                         f"Found {table_count} table(s) in all messages.",
+                        "info",
                     )
                     # Wait a moment for user to see the notification before download dialog
                     await asyncio.sleep(1.5)
                 # Generate Workbook Title (Filename)
                 # Use the title of the chat, or the first header of the first message with tables
                 title = ""
-                chat_id = self.extract_chat_id(body, None)
+                chat_ctx = self._get_chat_context(body, None)
+                chat_id = chat_ctx["chat_id"]
                 chat_title = ""
                 if chat_id:
                     chat_title = await self.fetch_chat_title(chat_id, user_id)
@@ -330,8 +378,8 @@ class Action:
                         },
                     }
                 )
-                await self._send_notification(
-                    __event_emitter__, "error", "No tables found to export!"
+                await self._emit_notification(
+                    __event_emitter__, "No tables found to export!", "error"
                 )
                 raise e
             except Exception as e:
@@ -345,8 +393,8 @@ class Action:
                         },
                     }
                 )
-                await self._send_notification(
-                    __event_emitter__, "error", "No tables found to export!"
+                await self._emit_notification(
+                    __event_emitter__, "No tables found to export!", "error"
                 )
 
     async def generate_title_using_ai(
@@ -389,20 +437,20 @@ class Action:
             async def notification_task():
                 # Send initial notification immediately
                 if event_emitter:
-                    await self._send_notification(
+                    await self._emit_notification(
                         event_emitter,
-                        "info",
                         "AI is generating a filename for your Excel file...",
+                        "info",
                     )
 
                 # Subsequent notifications every 5 seconds
                 while True:
                     await asyncio.sleep(5)
                     if event_emitter:
-                        await self._send_notification(
+                        await self._emit_notification(
                             event_emitter,
-                            "info",
                             "Still generating filename, please be patient...",
+                            "info",
                         )
 
             # Run tasks concurrently
@@ -432,10 +480,10 @@ class Action:
         except Exception as e:
             print(f"Error generating title: {e}")
             if event_emitter:
-                await self._send_notification(
+                await self._emit_notification(
                     event_emitter,
-                    "warning",
                     f"AI title generation failed, using default title. Error: {str(e)}",
+                    "warning",
                 )
 
         return ""
@@ -450,24 +498,56 @@ class Action:
                 return match.group(1).strip()
         return ""
 
-    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") or body.get("id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+    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 = {}
 
-            for key in ("chat", "conversation"):
-                nested = body.get(key)
-                if isinstance(nested, dict):
-                    nested_id = nested.get("id") or nested.get("chat_id")
-                    if isinstance(nested_id, str) and nested_id.strip():
-                        return nested_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 ""
+        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 _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        Unified extraction of chat context information (chat_id, message_id).
+        Prioritizes extraction from body, then metadata.
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. Try to get from body
+        if isinstance(body, dict):
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id is usually 'id' in body
+
+            # Check body.metadata as fallback
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
+
+        # 2. Try to get from __metadata__ (as supplement)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
+
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
 
     async def fetch_chat_title(self, chat_id: str, user_id: str = "") -> str:
         """Fetch chat title from database by chat_id"""

plugins/actions/export_to_excel/export_to_excel_cn.py

@@ -1,8 +1,8 @@
 """
 title: 导出为 Excel
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 0.3.7
 icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxwYXRoIGQ9Ik0xNSAySDZhMiAyIDAgMCAwLTIgMnYxNmEyIDIgMCAwIDAgMiAyaDEyYTIgMiAwIDAgMCAyLTJWN1oiLz48cGF0aCBkPSJNMTQgMnY0YTIgMiAwIDAgMCAyIDJoNCIvPjxwYXRoIGQ9Ik04IDEzaDIiLz48cGF0aCBkPSJNMTQgMTNoMiIvPjxwYXRoIGQ9Ik04IDE3aDIiLz48cGF0aCBkPSJNMTQgMTdoMiIvPjwvc3ZnPg==
 description: 从聊天消息中提取表格并导出为 Excel (.xlsx) 文件，支持智能格式化。
@@ -31,6 +31,10 @@ class Action:
             default="chat_title",
             description="标题来源: 'chat_title' (对话标题), 'ai_generated' (AI生成), 'markdown_title' (Markdown标题)",
         )
+        SHOW_STATUS: bool = Field(
+            default=True,
+            description="是否显示操作状态更新。",
+        )
         EXPORT_SCOPE: Literal["last_message", "all_messages"] = Field(
             default="last_message",
             description="导出范围: 'last_message' (仅最后一条消息), 'all_messages' (所有消息)",
@@ -39,14 +43,57 @@ class Action:
             default="",
             description="AI 标题生成模型 ID。留空则使用当前对话模型。",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="是否在浏览器控制台打印调试日志。",
+        )
 
     def __init__(self):
         self.valves = self.Valves()
 
-    async def _send_notification(self, emitter: Callable, type: str, content: str):
-        await emitter(
-            {"type": "notification", "data": {"type": type, "content": content}}
-        )
+    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 (info, success, warning, error)."""
+        if emitter:
+            await emitter(
+                {"type": "notification", "data": {"type": ntype, "content": content}}
+            )
+
+    async def _emit_debug_log(self, 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 emitter:
+            return
+
+        try:
+            import json
+
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
 
     async def action(
         self,
@@ -180,17 +227,18 @@ class Action:
                 # 通知用户提取到的表格数量
                 table_count = len(all_tables)
                 if self.valves.EXPORT_SCOPE == "all_messages":
-                    await self._send_notification(
+                    await self._emit_notification(
                         __event_emitter__,
-                        "info",
                         f"从所有消息中提取到 {table_count} 个表格。",
+                        "info",
                     )
                     # 等待片刻让用户看到通知，再触发下载
                     await asyncio.sleep(1.5)
 
                 # Generate Workbook Title (Filename)
                 title = ""
-                chat_id = self.extract_chat_id(body, None)
+                chat_ctx = self._get_chat_context(body, None)
+                chat_id = chat_ctx["chat_id"]
                 chat_title = ""
                 if chat_id:
                     chat_title = await self.fetch_chat_title(chat_id, user_id)
@@ -318,8 +366,8 @@ class Action:
                         },
                     }
                 )
-                await self._send_notification(
-                    __event_emitter__, "error", "未找到可导出的表格！"
+                await self._emit_notification(
+                    __event_emitter__, "未找到可导出的表格！", "error"
                 )
                 raise e
             except Exception as e:
@@ -333,8 +381,8 @@ class Action:
                         },
                     }
                 )
-                await self._send_notification(
-                    __event_emitter__, "error", "未找到可导出的表格！"
+                await self._emit_notification(
+                    __event_emitter__, "未找到可导出的表格！", "error"
                 )
 
     async def generate_title_using_ai(
@@ -377,20 +425,20 @@ class Action:
             async def notification_task():
                 # 立即发送首次通知
                 if event_emitter:
-                    await self._send_notification(
+                    await self._emit_notification(
                         event_emitter,
-                        "info",
                         "AI 正在为您生成文件名，请稍候...",
+                        "info",
                     )
 
                 # 之后每5秒通知一次
                 while True:
                     await asyncio.sleep(5)
                     if event_emitter:
-                        await self._send_notification(
+                        await self._emit_notification(
                             event_emitter,
-                            "info",
                             "文件名生成中，请耐心等待...",
+                            "info",
                         )
 
             # 并发运行任务
@@ -420,10 +468,10 @@ class Action:
         except Exception as e:
             print(f"生成标题时出错: {e}")
             if event_emitter:
-                await self._send_notification(
+                await self._emit_notification(
                     event_emitter,
-                    "warning",
                     f"AI 文件名生成失败，将使用默认名称。错误: {str(e)}",
+                    "warning",
                 )
 
         return ""
@@ -438,24 +486,56 @@ class Action:
                 return match.group(1).strip()
         return ""
 
-    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") or body.get("id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+    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 = {}
 
-            for key in ("chat", "conversation"):
-                nested = body.get(key)
-                if isinstance(nested, dict):
-                    nested_id = nested.get("id") or nested.get("chat_id")
-                    if isinstance(nested_id, str) and nested_id.strip():
-                        return nested_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 ""
+        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 _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        统一提取聊天上下文信息 (chat_id, message_id)。
+        优先从 body 中提取，其次从 metadata 中提取。
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. 尝试从 body 获取
+        if isinstance(body, dict):
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id 在 body 中通常是 id
+
+            # 再次检查 body.metadata
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
+
+        # 2. 尝试从 __metadata__ 获取 (作为补充)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
+
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
 
     async def fetch_chat_title(self, chat_id: str, user_id: str = "") -> str:
         """通过 chat_id 从数据库获取对话标题"""

plugins/actions/flash-card/README.md

@@ -2,9 +2,18 @@
 
 Generate polished learning flashcards from any text—title, summary, key points, tags, and category—ready for review and sharing.
 
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 0.2.4 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
+
+## Preview 📸
+
 ![Flash Card Example](flash_card.png)
 
-## Highlights
+## What's New
+
+### v0.2.4
+- **Clean Output**: Removed debug messages from output.
+
+## Key Features 🔑
 
 - **One-click generation**: Drop in text, get a structured card.
 - **Concise extraction**: 3–5 key points and 2–4 tags automatically surfaced.
@@ -12,7 +21,14 @@ Generate polished learning flashcards from any text—title, summary, key points
 - **Progressive merge**: Multiple runs append cards into the same HTML container; enable clearing to reset.
 - **Status updates**: Live notifications for generating/done/error.
 
-## Parameters
+## How to Use 🛠️
+
+1. **Install**: Add the plugin to your OpenWebUI instance.
+2. **Configure**: Adjust settings in the Valves menu (optional).
+3. **Trigger**: Send text to the chat.
+4. **Result**: Watch status updates; the card HTML is embedded into the latest message.
+
+## Configuration (Valves) ⚙️
 
 | Param               | Description                                                  | Default |
 | ------------------- | ------------------------------------------------------------ | ------- |
@@ -23,34 +39,9 @@ Generate polished learning flashcards from any text—title, summary, key points
 | CLEAR_PREVIOUS_HTML | Whether to clear previous card HTML (otherwise append/merge) | false   |
 | MESSAGE_COUNT       | Use the latest N messages to build the card                  | 1       |
 
-## How to Use
+## Troubleshooting ❓
 
-1. Install and enable “Flash Card”.
-2. Send the text to the chat (multi-turn supported; governed by MESSAGE_COUNT).
-3. Watch status updates; the card HTML is embedded into the latest message.
-4. To regenerate from scratch, toggle CLEAR_PREVIOUS_HTML or resend text.
-
-## Output Format
-
-- JSON fields: `title`, `summary`, `key_points` (3–5), `tags` (2–4), `category`.
-- UI: gradient-styled card with tags, key-point list; supports stacking multiple cards.
-
-## Tips
-
-- Very short text triggers a prompt to add more; consider summarizing first.
-- Long text is accepted; for deep analysis, pre-condense with other tools before card creation.
-
-## Author
-
-Fu-Jie
-GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
-
-## License
-
-MIT License
-
-## Changelog
-
-### v0.2.4
-
-- Removed debug messages from output
+- **Plugin not working?**: Check if the filter/action is enabled in the model settings.
+- **Debug Logs**: Enable `SHOW_STATUS` in Valves to see progress updates.
+- **Error Messages**: If you see an error, please copy the full error message and report it.
+- **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)

plugins/actions/flash-card/README_CN.md

@@ -2,9 +2,18 @@
 
 快速将文本提炼为精美的学习记忆卡片，自动抽取标题、摘要、关键要点、标签和分类，适合复习与分享。
 
+**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 0.2.4 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
+
+## 预览 📸
+
 ![闪记卡示例](flash_card_cn.png)
 
-## 功能亮点
+## 更新日志
+
+### v0.2.4
+- **输出优化**: 移除输出中的调试信息。
+
+## 核心特性 🔑
 
 - **一键生成**：输入任意文本，直接产出结构化卡片。
 - **要点聚合**：自动提取 3-5 个记忆要点与 2-4 个标签。
@@ -12,7 +21,14 @@
 - **渐进合并**：多次调用会将新卡片合并到同一 HTML 容器中；如需重置可启用清空选项。
 - **状态提示**：实时推送“生成中/完成/错误”等状态与通知。
 
-## 参数说明
+## 使用方法 🛠️
+
+1. **安装**: 在插件市场安装并启用“闪记卡”。
+2. **配置**: 根据需要调整 Valves 设置（可选）。
+3. **触发**: 将待整理的文本发送到聊天框。
+4. **结果**: 等待状态提示，卡片将以 HTML 形式嵌入到最新消息中。
+
+## 配置参数 (Valves) ⚙️
 
 | 参数                | 说明                                  | 默认值 |
 | ------------------- | ------------------------------------- | ------ |
@@ -23,34 +39,9 @@
 | CLEAR_PREVIOUS_HTML | 是否清空旧的卡片 HTML（否则合并追加） | false  |
 | MESSAGE_COUNT       | 取最近 N 条消息生成卡片               | 1      |
 
-## 使用步骤
+## 故障排除 (Troubleshooting) ❓
 
-1. 在插件市场安装并启用“闪记卡”。
-2. 将待整理的文本发送到聊天框（可多轮对话，受 MESSAGE_COUNT 控制）。
-3. 等待状态提示，卡片将以 HTML 形式嵌入到最新消息中。
-4. 若需重新生成，开启 CLEAR_PREVIOUS_HTML 或直接重发文本。
-
-## 输出格式
-
-- JSON 字段：`title`、`summary`、`key_points`（3-5 条）、`tags`（2-4 条）、`category`。
-- 前端呈现：单卡片带渐变主题、标签胶囊、要点列表，可连续追加多张卡片。
-
-## 使用建议
-
-- 文本过短会提醒补充，可先汇总再生成卡片。
-- 长文本无需截断，直接生成；如需深度分析可先用其他工具精炼后再制作卡片。
-
-## 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
-
-### v0.2.4
-
-- 移除输出中的调试信息
+- **插件不工作？**: 请检查是否在模型设置中启用了该过滤器/动作。
+- **调试日志**: 在 Valves 中启用 `SHOW_STATUS` 以查看进度更新。
+- **错误信息**: 如果看到错误，请复制完整的错误信息并报告。
+- **提交 Issue**: 如果遇到任何问题，请在 GitHub 上提交 Issue：[Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)

plugins/actions/flash-card/flash_card.py

@@ -1,8 +1,8 @@
 """
 title: Flash Card
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 0.2.4
 openwebui_id: 65a2ea8f-2a13-4587-9d76-55eea0035cc8
 icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxwb2x5Z29uIHBvaW50cz0iMTIgMiAyIDcgMTIgMTIgMjIgNyAxMiAyIi8+PHBvbHlsaW5lIHBvaW50cz0iMiAxNyAxMiAyMiAyMiAxNyIvPjxwb2x5bGluZSBwb2ludHM9IjIgMTIgMTIgMTcgMjIgMTIiLz48L3N2Zz4=
@@ -89,6 +89,10 @@ class Action:
             default=True,
             description="Whether to show status updates in the chat interface.",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="Whether to print debug logs in the browser console.",
+        )
         CLEAR_PREVIOUS_HTML: bool = Field(
             default=False,
             description="Whether to force clear previous plugin results (if True, overwrites instead of merging).",
@@ -116,6 +120,42 @@ class Action:
             "user_language": user_data.get("language", "en-US"),
         }
 
+    def _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        Unified extraction of chat context information (chat_id, message_id).
+        Prioritizes extraction from body, then metadata.
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. Try to get from body
+        if isinstance(body, dict):
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id is usually 'id' in body
+
+            # Check body.metadata as fallback
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
+
+        # 2. Try to get from __metadata__ (as supplement)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
+
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
+
     async def action(
         self,
         body: dict,
@@ -331,6 +371,26 @@ Important Principles:
                 {"type": "notification", "data": {"type": ntype, "content": content}}
             )
 
+    async def _emit_debug_log(self, emitter, title: str, data: dict):
+        """Print structured debug logs in the browser console"""
+        if not self.valves.SHOW_DEBUG_LOG or not emitter:
+            return
+
+        try:
+            import json
+
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
     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]*?```"

plugins/actions/flash-card/flash_card_cn.py

@@ -1,8 +1,8 @@
 """
 title: 闪记卡 (Flash Card)
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 0.2.4
 openwebui_id: 4a31eac3-a3c4-4c30-9ca5-dab36b5fac65
 icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPjxwb2x5Z29uIHBvaW50cz0iMTIgMiAyIDcgMTIgMTIgMjIgNyAxMiAyIi8+PHBvbHlsaW5lIHBvaW50cz0iMiAxNyAxMiAyMiAyMiAxNyIvPjxwb2x5bGluZSBwb2ludHM9IjIgMTIgMTIgMTcgMjIgMTIiLz48L3N2Zz4=
@@ -86,6 +86,10 @@ class Action:
         SHOW_STATUS: bool = Field(
             default=True, description="是否在聊天界面显示状态更新。"
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="是否在浏览器控制台打印调试日志。",
+        )
         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）。",
@@ -113,6 +117,42 @@ class Action:
             "user_language": user_data.get("language", "zh-CN"),
         }
 
+    def _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        统一提取聊天上下文信息 (chat_id, message_id)。
+        优先从 body 中提取，其次从 metadata 中提取。
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. 尝试从 body 获取
+        if isinstance(body, dict):
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id 在 body 中通常是 id
+
+            # 再次检查 body.metadata
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
+
+        # 2. 尝试从 __metadata__ 获取 (作为补充)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
+
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
+
     async def action(
         self,
         body: dict,
@@ -314,6 +354,26 @@ class Action:
                 {"type": "notification", "data": {"type": ntype, "content": content}}
             )
 
+    async def _emit_debug_log(self, 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 emitter:
+            return
+
+        try:
+            import json
+
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
     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]*?```"

plugins/actions/infographic/README.md

@@ -1,11 +1,14 @@
 # 📊 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)
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 1.4.9 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
 
 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
+## 🔥 What's New in v1.4.9
 
+- 🎨 **70+ Official Templates**: Integrated comprehensive AntV infographic template library.
+- 🖼️ **Iconify & unDraw Support**: Richer visuals with official icons and illustrations.
+- 📏 **Visual Optimization**: Improved text wrapping, adaptive sizing, and layout refinement.
 - ✨ **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).
 
@@ -17,8 +20,8 @@ An Open WebUI plugin powered by the AntV Infographic engine. It transforms long
 ## ✨ Key Features
 
 - 🚀 **AI-Powered Transformation**: Automatically analyzes text logic, extracts key points, and generates structured charts.
-- 🎨 **Professional Templates**: Includes various AntV official templates: Lists, Trees, Mindmaps, Comparison Tables, Flowcharts, and Statistical Charts.
-- 🔍 **Auto-Icon Matching**: Built-in logic to search and match the most relevant Material Design Icons based on content.
+- 🎨 **70+ Professional Templates**: Includes various AntV official templates: Lists, Trees, Roadmaps, Timelines, Comparison Tables, SWOT, Quadrants, and Statistical Charts.
+- 🔍 **Auto-Icon Matching**: Built-in logic to search and match the most relevant icons (Iconify) and illustrations (unDraw).
 - 📥 **Multi-Format Export**: Download your infographics as **SVG**, **PNG**, or a **Standalone HTML** file.
 - 🌈 **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.
@@ -47,10 +50,19 @@ You can adjust the following parameters in the plugin settings to optimize the g
 
 | 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 |
+| **Sequence** | `sequence-timeline-simple`, `sequence-roadmap-vertical-simple`, `sequence-snake-steps-compact-card` | Timelines, Roadmaps, Processes |
+| **Lists** | `list-grid-candy-card-lite`, `list-row-horizontal-icon-arrow`, `list-column-simple-vertical-arrow` | Features, Bullet Points, Lists |
+| **Comparison** | `compare-binary-horizontal-underline-text-vs`, `compare-swot`, `quadrant-quarter-simple-card` | Pros/Cons, SWOT, Quadrants |
+| **Hierarchy** | `hierarchy-tree-tech-style-capsule-item`, `hierarchy-structure` | Org Charts, Structures |
+| **Charts** | `chart-column-simple`, `chart-bar-plain-text`, `chart-line-plain-text`, `chart-wordcloud` | Trends, Distributions, Metrics |
+
+## Troubleshooting ❓
+
+- **Plugin not working?**: Check if the filter/action is enabled in the model settings.
+- **Debug Logs**: Enable `SHOW_STATUS` in Valves to see progress updates.
+- **Error Messages**: If you see an error, please copy the full error message and report it.
+- **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)
+
 
 ## 📝 Syntax Example (For Advanced Users)
 

plugins/actions/infographic/README_CN.md

@@ -1,11 +1,14 @@
 # 📊 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)
+**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 1.4.9 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
 
 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
+## 🔥 v1.4.9 更新日志
 
+- 🎨 **70+ 官方模板**：全面集成 AntV 官方信息图模板库。
+- 🖼️ **图标与插图支持**：支持 Iconify 图标库与 unDraw 插图库，视觉效果更丰富。
+- 📏 **视觉优化**：改进文本换行逻辑，优化自适应尺寸，提升卡片布局精细度。
 - ✨ **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）。
 
@@ -17,8 +20,8 @@
 ## ✨ 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。
-- 🎨 **专业模板**：内置多种 AntV 官方模板，包括列表、树图、思维导图、对比图、流程图及统计图表等。
-- 🔍 **自动图标匹配**：内置图标搜索逻辑，根据内容自动匹配最相关的 Material Design Icons。
+- 🎨 **70+ 专业模板**：内置多种 AntV 官方模板，包括列表、树图、路线图、时间线、对比图、SWOT、象限图及统计图表等。
+- 🔍 **自动图标匹配**：内置图标搜索逻辑，支持 Iconify 图标和 unDraw 插图自动匹配。
 - 📥 **多格式导出**：支持一键下载为 **SVG**、**PNG** 或 **独立 HTML** 文件。
 - 🌈 **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。
@@ -47,10 +50,19 @@
 
 | 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 |
+| **时序与流程** | `sequence-timeline-simple`, `sequence-roadmap-vertical-simple`, `sequence-snake-steps-compact-card` | 时间线、路线图、步骤说明 |
+| **列表与网格** | `list-grid-candy-card-lite`, `list-row-horizontal-icon-arrow`, `list-column-simple-vertical-arrow` | 功能亮点、要点列举、清单 |
+| **对比与分析** | `compare-binary-horizontal-underline-text-vs`, `compare-swot`, `quadrant-quarter-simple-card` | 优劣势对比、SWOT 分析、象限图 |
+| **层级与结构** | `hierarchy-tree-tech-style-capsule-item`, `hierarchy-structure` | 组织架构、层级关系 |
+| **图表与数据** | `chart-column-simple`, `chart-bar-plain-text`, `chart-line-plain-text`, `chart-wordcloud` | 数据趋势、比例分布、数值对比 |
+
+## 故障排除 (Troubleshooting) ❓
+
+- **插件不工作？**: 请检查是否在模型设置中启用了该过滤器/动作。
+- **调试日志**: 在 Valves 中启用 `SHOW_STATUS` 以查看进度更新。
+- **错误信息**: 如果看到错误，请复制完整的错误信息并报告。
+- **提交 Issue**: 如果遇到任何问题，请在 GitHub 上提交 Issue：[Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)
+
 
 ## 📝 语法示例 (高级用户)
 

plugins/actions/infographic/README_EN.md

@@ -1,65 +0,0 @@
-# 📊 Smart Infographic (AntV)
-
-An Open WebUI plugin powered by the AntV Infographic engine. It transforms long text into professional, beautiful infographics with a single click.
-
-## ✨ Key Features
-
-- 🚀 **AI-Powered Transformation**: Automatically analyzes text logic, extracts key points, and generates structured charts.
-- 🎨 **Professional Templates**: Includes various AntV official templates: Lists, Trees, Mindmaps, Comparison Tables, Flowcharts, and Statistical Charts.
-- 🔍 **Auto-Icon Matching**: Built-in logic to search and match the most relevant Material Design Icons based on content.
-- 📥 **Multi-Format Export**: Download your infographics as **SVG**, **PNG**, or a **Standalone HTML** file.
-- 🌈 **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.
-2. **Trigger**: Enter your text in the chat, then click the **Action Button** (📊 icon) next to the input box.
-3. **AI Processing**: The AI analyzes the text and generates the infographic syntax.
-4. **Preview & Download**: Preview the result and use the download buttons below to save your infographic.
-
-## ⚙️ Configuration (Valves)
-
-You can adjust the following parameters in the plugin settings to optimize the generation:
-
-| Parameter | Default | Description |
-| :--- | :--- | :--- |
-| **Show Status (SHOW_STATUS)** | `True` | Whether to show real-time AI analysis and generation status in the chat. |
-| **Model ID (MODEL_ID)** | `Empty` | Specify the LLM model for text analysis. If empty, the current chat model is used. |
-| **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. |
-
-## 📝 Syntax Example (For Advanced Users)
-
-You can also input this syntax directly for AI to render:
-
-```infographic
-infographic list-grid
-data
-  title 🚀 Plugin Benefits
-  desc Why use the Smart Infographic plugin
-  items
-    - label Fast Generation
-      desc Convert text to charts in seconds
-    - 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

plugins/actions/infographic/infographic.py

@@ -1,9 +1,10 @@
 """
 title: 📊 Smart Infographic (AntV)
-author: jeff
+author: Fu-Jie
 author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPgogIDxsaW5lIHgxPSIxMiIgeTE9IjIwIiB4Mj0iMTIiIHkyPSIxMCIgLz4KICA8bGluZSB4MT0iMTgiIHkxPSIyMCIgeDI9IjE4IiB5Mj0iNCIgLz4KICA8bGluZSB4MT0iNiIgeTE9IjIwIiB4Mj0iNiIgeTI9IjE2IiAvPgo8L3N2Zz4=
-version: 1.4.1
+version: 1.4.9
 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.
 """
@@ -47,24 +48,63 @@ Infographic syntax is a Mermaid-like declarative syntax for describing infograph
 
 ### Template Library & Selection Guide
 
-Choose the most appropriate template based on the content structure:
+Choose the most appropriate template based on content structure.
 
-#### 1. List & Hierarchy
-- **List**: `list-grid` (Grid Cards), `list-vertical` (Vertical List)
-- **Tree**: `tree-vertical` (Vertical Tree), `tree-horizontal` (Horizontal Tree)
-- **Mindmap**: `mindmap` (Mind Map)
+**Template Selection Guidelines (Official):**
+- Strict sequential order (processes/steps/trends) → `sequence-*` series
+  - Timeline → `sequence-timeline-simple`
+  - Roadmap → `sequence-roadmap-vertical-simple`
+  - Zigzag steps → `sequence-horizontal-zigzag-underline-text`
+  - Snake steps → `sequence-snake-steps-compact-card`
+- Listing viewpoints → `list-row-horizontal-icon-arrow` or `list-column-simple-vertical-arrow`
+- Comparative analysis (A vs B) → `compare-binary-horizontal-underline-text-vs`
+- SWOT analysis → `compare-swot`
+- Hierarchical structure (tree) → `hierarchy-tree-tech-style-capsule-item`
+- Data charts → `chart-*` series
+- Quadrant analysis → `quadrant-quarter-simple-card`
+- Grid lists (bullet points) → `list-grid-candy-card-lite`
+- Relationship display → `relation-circle-icon-badge`
 
-#### 2. Sequence & Relationship
-- **Process**: `sequence-roadmap` (Roadmap), `sequence-zigzag` (Zigzag Process), `sequence-horizontal` (Horizontal Process)
-- **Relationship**: `relation-sankey` (Sankey Diagram), `relation-circle` (Circular Relationship)
+**Available Templates:**
 
-#### 3. Comparison & Analysis
-- **Comparison**: `compare-binary` (Binary Comparison), `list-grid` (Multi-item Grid Comparison)
-- **Analysis**: `compare-swot` (SWOT Analysis), `quadrant-quarter` (Quadrant Chart)
+*Sequence (时序/流程):*
+`sequence-timeline-simple`, `sequence-roadmap-vertical-simple`, `sequence-horizontal-zigzag-underline-text`, 
+`sequence-snake-steps-compact-card`, `sequence-zigzag-steps-underline-text`, `sequence-circular-simple`,
+`sequence-pyramid-simple`, `sequence-ascending-steps`
 
-#### 4. Charts & Data
-- **Statistics**: `statistic-card` (Statistic Cards)
-- **Charts**: `chart-bar` (Bar Chart), `chart-column` (Column Chart), `chart-line` (Line Chart), `chart-pie` (Pie Chart), `chart-doughnut` (Doughnut Chart), `chart-area` (Area Chart)
+*List (列表):*
+`list-grid-candy-card-lite`, `list-grid-badge-card`, `list-row-horizontal-icon-arrow`,
+`list-column-simple-vertical-arrow`, `list-column-done-list`
+
+*Compare (对比):*
+`compare-binary-horizontal-underline-text-vs`, `compare-binary-horizontal-simple-fold`,
+`compare-hierarchy-left-right-circle-node-pill-badge`, `compare-swot`
+
+*Hierarchy (层级):*
+`hierarchy-tree-tech-style-capsule-item`, `hierarchy-tree-curved-line-rounded-rect-node`, `hierarchy-structure`
+
+*Chart (图表):*
+`chart-column-simple`, `chart-bar-plain-text`, `chart-line-plain-text`, 
+`chart-pie-plain-text`, `chart-pie-donut-plain-text`, `chart-wordcloud`
+
+*Other:*
+`quadrant-quarter-simple-card`, `relation-circle-icon-badge`
+
+**Text Capacity by Template Type:**
+- HIGH capacity (long descriptions OK): `list-column-*`, `compare-binary-*`, `sequence-timeline-*`
+- MEDIUM capacity: `list-row-*`, `sequence-roadmap-*`
+- LOW capacity (short text only): `list-grid-*`, `hierarchy-*`, `sequence-steps`
+
+### Icon and Illustration Resources
+
+**Icons (Iconify):**
+- Format: `<collection>/<icon-name>`, e.g., `mdi/rocket-launch`
+- Popular: `mdi/*` (Material Design), `fa/*` (Font Awesome), `bi/*` (Bootstrap)
+- Examples: `mdi/code-tags`, `mdi/chart-line`, `mdi/account-group`, `mdi/cloud`
+
+**Illustrations (unDraw):**
+- Format: filename without .svg, e.g., `coding`, `team-work`
+- Use `illus` field instead of `icon`
 
 ### Data Structure Examples
 
@@ -211,6 +251,12 @@ data
 - `children`: Nested items (for trees, SWOT, etc.)
 - `illus`: Illustration icon (specific to some templates like Quadrant)
 
+### Content Refinement Principles
+1. **Brevity is King**: Infographics are visual. Keep text to a minimum.
+2. **Title Limit**: Keep `label` (item titles) under 15 characters (approx. 10 Chinese characters).
+3. **Description Limit**: Keep `desc` (item descriptions) under 40 characters (approx. 20 Chinese characters / 2 lines).
+4. **Impact**: Use strong verbs and nouns. Avoid filler words.
+
 ## Output Requirements
 1. **Language**: Output content in the user's language.
 2. **Format**: Wrap output in ```infographic ... ```.
@@ -218,6 +264,8 @@ data
 4. **Indentation**: Use 2 spaces.
 """
 
+import json
+
 USER_PROMPT_GENERATE_INFOGRAPHIC = """
 Please analyze the following text content and convert its core information into AntV Infographic syntax format.
 
@@ -233,9 +281,18 @@ User Language: {user_language}
 
 Please select the most appropriate infographic template based on text characteristics and output standard infographic syntax. Pay attention to correct indentation format (two spaces).
 
-**Important Note:** 
-- If using `list-grid` format, ensure each card's `desc` description is limited to **maximum 30 Chinese characters** (or **approximately 60 English characters**) to maintain visual consistency with all descriptions fitting in 2 lines.
-- Descriptions should be concise and highlight key points.
+**Visual Optimization Guide (MUST FOLLOW):**
+- **Point-based Generation:** Infographics are not articles. Extract KEYWORDS ONLY, avoid complete sentences.
+- **Main Title (`data.title`):** **MUST** be ≤ **15 Chinese characters** (or ≤30 English characters). Trim version numbers or details if needed.
+- **Subtitle (`data.desc`):** **MUST** be ≤ **20 Chinese characters** (or ≤40 English characters).
+- **Card Title (`label`):** **MUST** be ≤ **6 Chinese characters** (or ≤12 English characters). Use 2-4 keywords only.
+- **Card Description (`desc`):** **MUST** be ≤ **12 Chinese characters** (or ≤24 English characters). Use short phrases.
+
+⚠️ **CRITICAL**: If the original text is too long, you MUST rephrase and shorten it. Do NOT simply truncate with "...".
+Examples:
+- ❌ "多步任务与工具协作能力" → ✅ "多步任务协作"
+- ❌ "Open WebUI v0.7.x 重大版本更新" → ✅ "v0.7 核心更新"
+- ❌ "自动查找历史聊天记录" → ✅ "历史检索"
 """
 
 # =================================================================
@@ -340,8 +397,9 @@ CSS_TEMPLATE_INFOGRAPHIC = """
 .infographic-container-wrapper .infographic-render-container {
     border-radius: 8px;
     padding: 16px;
+    min-height: 600px;
     background: #fff;
-    overflow: visible; /* Ensure content is visible */
+    overflow: visible;
     transition: height 0.3s ease;
 }
 .infographic-render-container svg text {
@@ -349,35 +407,59 @@ CSS_TEMPLATE_INFOGRAPHIC = """
 }
 .infographic-render-container svg foreignObject {
     font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", sans-serif !important;
-    line-height: 1.4 !important;
+    line-height: 1.3 !important;
+    overflow: visible !important;
 }
 /* Main title styles */
 .infographic-render-container svg foreignObject[data-element-type="title"] > * {
-    font-size: 1.5em !important;
-    font-weight: bold !important;
-    line-height: 1.4 !important;
-    white-space: nowrap !important;
+    font-size: 1.3em !important;
+    font-weight: 800 !important;
+    line-height: 1.3 !important;
+    white-space: normal !important;
+    word-break: break-word !important;
+    display: -webkit-box !important;
+    -webkit-line-clamp: 2 !important;
+    -webkit-box-orient: vertical !important;
     overflow: hidden !important;
     text-overflow: ellipsis !important;
+    text-align: center !important;
 }
-/* Page subtitle and card title styles */
-.infographic-render-container svg foreignObject[data-element-type="desc"] > *,
-.infographic-render-container svg foreignObject[data-element-type="item-label"] > * {
-    font-size: 0.6em !important;
-    line-height: 1.4 !important;
-    white-space: nowrap !important;
-    overflow: hidden !important;
-    text-overflow: ellipsis !important;
-}
-/* Card title with extra bottom spacing */
-.infographic-render-container svg foreignObject[data-element-type="item-label"] > * {
-    padding-bottom: 8px !important;
+/* Page subtitle styles */
+.infographic-render-container svg foreignObject[data-element-type="desc"] > * {
+    font-size: 0.85em !important;
+    line-height: 1.3 !important;
+    white-space: normal !important;
+    word-break: break-word !important;
+    overflow: visible !important;
+    text-align: center !important;
     display: block !important;
+    color: var(--ig-muted-text-color) !important;
 }
-/* Card description text keeps normal wrapping */
+/* Card title styles */
+.infographic-render-container svg foreignObject[data-element-type="item-label"] > * {
+    font-size: 0.9em !important;
+    font-weight: 600 !important;
+    line-height: 1.3 !important;
+    white-space: normal !important;
+    word-break: break-word !important;
+    display: -webkit-box !important;
+    -webkit-line-clamp: 2 !important;
+    -webkit-box-orient: vertical !important;
+    overflow: hidden !important;
+    text-overflow: ellipsis !important;
+    padding-bottom: 2px !important;
+}
+/* Card description text */
 .infographic-render-container svg foreignObject[data-element-type="item-desc"] > * {
+    font-size: 0.8em !important;
     line-height: 1.4 !important;
     white-space: normal !important;
+    word-break: break-word !important;
+    display: -webkit-box !important;
+    -webkit-line-clamp: 2 !important;
+    -webkit-box-orient: vertical !important;
+    overflow: hidden !important;
+    text-overflow: ellipsis !important;
 }
 .infographic-container-wrapper .download-area {
     text-align: center;
@@ -533,37 +615,41 @@ SCRIPT_TEMPLATE_INFOGRAPHIC = """
             }}
         }}
 
-        // 2. Template Mapping Configuration
+        // 2. Template Mapping Configuration (Official AntV Structure IDs)
         const TEMPLATE_MAPPING = {{
-            // List & Hierarchy
+            // List & Hierarchy - map short names to full template names
             'list-grid': 'list-grid-compact-card',
+            'list-column': 'list-column-simple-vertical-arrow',
+            'list-row': 'list-row-simple-horizontal-arrow',
+            'hierarchy-tree': 'hierarchy-tree-tech-style-capsule-item',
+            
+            // Sequence & Timeline
+            'sequence-roadmap-vertical': 'sequence-roadmap-vertical-simple',
+            'sequence-timeline': 'sequence-timeline-simple',
+            'sequence-steps': 'sequence-steps-simple',
+            'sequence-horizontal-zigzag': 'sequence-horizontal-zigzag-simple',
+            
+            // Comparison
+            'compare-binary-horizontal': 'compare-binary-horizontal-simple-vs',
+            'compare-hierarchy-row': 'compare-hierarchy-row-simple',
+            
+            // Charts
+            'chart-column': 'chart-column-simple',
+            'quadrant': 'quadrant-quarter-simple-card',
+            
+            // Legacy mappings for backward compatibility
             '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 & Relationship
             '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',
-            
-            // Comparison & Analysis
             'compare-binary': 'compare-binary-horizontal-simple-vs',
-            'compare-swot': 'compare-swot',
-            'quadrant-quarter': 'quadrant-quarter-simple-card',
-            
-            // Charts & Data
-            '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'
         }};
 
+
         // 3. Apply Mapping Strategy
         for (const [key, value] of Object.entries(TEMPLATE_MAPPING)) {{
             const regex = new RegExp(`infographic\\\\s+${{key}}(?=\\\\s|$)`, 'i');
@@ -629,10 +715,48 @@ SCRIPT_TEMPLATE_INFOGRAPHIC = """
             containerEl.dataset.infographicRendered = 'true';
             console.log('[Infographic] Rendering complete');
 
-            // Auto-adjust height
+            // Auto-adjust height and tag elements
             setTimeout(() => {
                 const svg = containerEl.querySelector('svg');
                 if (svg) {
+                    // 1. Tag elements for CSS styling
+                    const fos = Array.from(svg.querySelectorAll('foreignObject'));
+                    let titleFound = false;
+                    let descFound = false;
+                    
+                    fos.forEach((fo) => {
+                        const text = fo.textContent.trim();
+                        if (!text || fo.querySelector('i') || (fo.querySelector('svg') && fo.querySelectorAll('*').length < 5)) {
+                            fo.setAttribute('data-element-type', 'icon');
+                            return;
+                        }
+                        
+                        // Dynamically increase height and width to accommodate wrapped text
+                        const currentHeight = parseInt(fo.getAttribute('height') || '0');
+                        if (currentHeight > 0 && currentHeight < 200) {
+                            fo.setAttribute('height', Math.round(currentHeight * 1.8).toString());
+                        }
+                        const currentWidth = parseInt(fo.getAttribute('width') || '0');
+                        if (currentWidth > 0 && currentWidth < 300) {
+                            fo.setAttribute('width', Math.max(Math.round(currentWidth * 1.2), 180).toString());
+                        }
+
+                        if (!titleFound) {
+                            fo.setAttribute('data-element-type', 'title');
+                            titleFound = true;
+                        } else if (!descFound) {
+                            fo.setAttribute('data-element-type', 'desc');
+                            descFound = true;
+                        } else {
+                            if (fo.querySelector('strong') || fo.style.fontWeight === 'bold' || text.length < 15) {
+                                fo.setAttribute('data-element-type', 'item-label');
+                            } else {
+                                fo.setAttribute('data-element-type', 'item-desc');
+                            }
+                        }
+                    });
+
+                    // 2. Adjust height
                     const bbox = svg.getBoundingClientRect();
                     let contentHeight = bbox.height;
                     if (svg.viewBox && svg.viewBox.baseVal && svg.viewBox.baseVal.height) {
@@ -826,49 +950,64 @@ class Action:
             default="image",
             description="Output mode: 'html' for interactive HTML, or 'image' to embed as Markdown image (default).",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="Whether to print debug logs in the browser console.",
+        )
 
     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"""
+    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 _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        Unified extraction of chat context information (chat_id, message_id).
+        Prioritizes extraction from body, then metadata.
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. Try to get from body
         if isinstance(body, dict):
-            chat_id = body.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id is usually 'id' in body
 
-            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()
+            # Check body.metadata as fallback
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
 
-        if isinstance(metadata, dict):
-            chat_id = metadata.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+        # 2. Try to get from __metadata__ (as supplement)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
 
-        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 ""
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
 
     def _extract_infographic_syntax(self, llm_output: str) -> str:
         """Extract infographic syntax from LLM output"""
@@ -897,6 +1036,24 @@ class Action:
                 {"type": "notification", "data": {"type": ntype, "content": content}}
             )
 
+    async def _emit_debug_log(self, emitter, title: str, data: dict):
+        """Print structured debug logs in the browser console"""
+        if not self.valves.SHOW_DEBUG_LOG or not emitter:
+            return
+
+        try:
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
     def _remove_existing_html(self, content: str) -> str:
         """Remove existing plugin-generated HTML code blocks from content"""
         pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"
@@ -1507,8 +1664,9 @@ class Action:
             # 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"))
+                chat_ctx = self._get_chat_context(body, __metadata__)
+                chat_id = chat_ctx["chat_id"]
+                message_id = chat_ctx["message_id"]
 
                 await self._emit_status(
                     __event_emitter__,

plugins/actions/infographic/infographic_cn.py

@@ -1,9 +1,10 @@
 """
 title: 📊 智能信息图 (AntV Infographic)
-author: jeff
+author: Fu-Jie
 author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPgogIDxsaW5lIHgxPSIxMiIgeTE9IjIwIiB4Mj0iMTIiIHkyPSIxMCIgLz4KICA8bGluZSB4MT0iMTgiIHkxPSIyMCIgeDI9IjE4IiB5Mj0iNCIgLz4KICA8bGluZSB4MT0iNiIgeTE9IjIwIiB4Mj0iNiIgeTI9IjE2IiAvPgo8L3N2Zz4=
-version: 1.4.1
+version: 1.4.9
 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。
 """
@@ -45,32 +46,61 @@ Infographic syntax is a Mermaid-like declarative syntax for describing infograph
 - ❌ Wrong: `children:` `items:` `data:` (with colons)
 - ✅ Correct: `children` `items` `data` (without colons)
 
-### Template Library & Selection Guide
+### 模板库与选择指南
 
-#### 1. List & Hierarchy (Text-heavy)
--   **Linear & Short (Steps/Phases)** -> `list-row-horizontal-icon-arrow`
--   **Linear & Long (Rankings/Details)** -> `list-vertical`
--   **Grouped / Parallel (Features/Catalog)** -> `list-grid`
--   **Hierarchical (Org Chart/Taxonomy)** -> `tree-vertical` or `tree-horizontal`
--   **Central Idea (Brainstorming)** -> `mindmap`
+根据内容结构选择最合适的模板。
 
-#### 2. Sequence & Relationship (Flow-based)
--   **Time-based (History/Plan)** -> `sequence-roadmap-vertical-simple`
--   **Process Flow (Complex)** -> `sequence-zigzag` or `sequence-horizontal`
--   **Resource Flow / Distribution** -> `relation-sankey`
--   **Circular Relationship** -> `relation-circle`
+**模板选择指南 (官方):**
+- 严格时序 (流程/步骤/趋势) → `sequence-*` 系列
+  - 时间线 → `sequence-timeline-simple`
+  - 路线图 → `sequence-roadmap-vertical-simple`
+  - 折线步骤 → `sequence-horizontal-zigzag-underline-text`
+  - 蛇形步骤 → `sequence-snake-steps-compact-card`
+- 列举要点 → `list-row-horizontal-icon-arrow` 或 `list-column-simple-vertical-arrow`
+- 对比分析 (A vs B) → `compare-binary-horizontal-underline-text-vs`
+- SWOT 分析 → `compare-swot`
+- 层级结构 (树状图) → `hierarchy-tree-tech-style-capsule-item`
+- 数据图表 → `chart-*` 系列
+- 象限分析 → `quadrant-quarter-simple-card`
+- 网格列表 → `list-grid-candy-card-lite`
+- 关系展示 → `relation-circle-icon-badge`
 
-#### 3. Comparison & Analysis
--   **Binary Comparison (A vs B)** -> `compare-binary`
--   **SWOT Analysis** -> `compare-swot`
--   **Quadrant Analysis (Importance vs Urgency)** -> `quadrant-quarter`
--   **Multi-item Grid Comparison** -> `list-grid` (use for comparing multiple items)
+**可用模板:**
 
-#### 4. Charts & Data (Metric-heavy)
--   **Key Metrics / Data Cards** -> `statistic-card`
--   **Distribution / Comparison** -> `chart-bar` or `chart-column`
--   **Trend over Time** -> `chart-line` or `chart-area`
--   **Proportion / Part-to-Whole** -> `chart-pie` or `chart-doughnut`
+*Sequence (时序/流程):*
+`sequence-timeline-simple`, `sequence-roadmap-vertical-simple`, `sequence-horizontal-zigzag-underline-text`, 
+`sequence-snake-steps-compact-card`, `sequence-zigzag-steps-underline-text`, `sequence-circular-simple`
+
+*List (列表):*
+`list-grid-candy-card-lite`, `list-grid-badge-card`, `list-row-horizontal-icon-arrow`,
+`list-column-simple-vertical-arrow`, `list-column-done-list`
+
+*Compare (对比):*
+`compare-binary-horizontal-underline-text-vs`, `compare-swot`
+
+*Hierarchy (层级):*
+`hierarchy-tree-tech-style-capsule-item`, `hierarchy-structure`
+
+*Chart (图表):*
+`chart-column-simple`, `chart-bar-plain-text`, `chart-pie-plain-text`, `chart-wordcloud`
+
+*Other:*
+`quadrant-quarter-simple-card`, `relation-circle-icon-badge`
+
+**按容量分类:**
+- 高容量 (长描述): `list-column-*`, `compare-binary-*`, `sequence-timeline-*`
+- 中容量: `list-row-*`, `sequence-roadmap-*`
+- 低容量 (短文本): `list-grid-*`, `hierarchy-*`
+
+### 图标和插图资源
+
+**图标 (Iconify):**
+- 格式: `<集合>/<图标名>`, 如 `mdi/rocket-launch`
+- 常用: `mdi/*`, `fa/*`, `bi/*`
+
+**插图 (unDraw):**
+- 格式: 文件名 (不含 .svg), 如 `coding`, `team-work`
+- 使用 `illus` 字段
 
 ### Infographic Syntax Guide
 
@@ -203,12 +233,20 @@ data
       desc Plan for next sprint
       illus mdi/star
 
+### Content Refinement Principles
+1. **Brevity is King**: Infographics are visual. Keep text to a minimum.
+2. **Title Limit**: Keep `label` (item titles) under 15 characters.
+3. **Description Limit**: Keep `desc` (item descriptions) under 25 characters (approx. 2 lines).
+4. **Impact**: Use strong verbs and nouns. Avoid filler words.
+
 ### Output Rules
 1.  **Strict Syntax**: Follow the indentation and formatting rules exactly.
 2.  **No Explanations**: Output ONLY the syntax code block.
 3.  **Language**: Use the user's requested language for content.
 """
 
+import json
+
 USER_PROMPT_GENERATE_INFOGRAPHIC = """
 请分析以下文本内容，将其核心信息转换为 AntV Infographic 语法格式。
 
@@ -224,9 +262,11 @@ USER_PROMPT_GENERATE_INFOGRAPHIC = """
 
 请根据文本特点选择最合适的信息图模板，并输出规范的 infographic 语法。注意保持正确的缩进格式（两个空格）。
 
-**重要提示：** 
-- 如果使用 `list-grid` 格式，请确保每个卡片的 `desc` 描述文字控制在 **30个汉字**（或约60个英文字符）**以内**，以保证所有卡片描述都只占用2行，维持视觉一致性。
-- 描述应简洁精炼，突出核心要点。
+**视觉优化指南：** 
+- **要点化生成：** 信息图不是文章。请将内容转化为“关键词+短语”的形式，严禁生成长难句。
+- **标题限制：** 每个卡片的 `label`（标题）请控制在 **8个汉字**以内。
+- **描述限制：** 每个卡片的 `desc`（描述）请控制在 **15个汉字**以内，确保即使在小屏幕上也能完整显示。
+- **结构化思维：** 优先使用并列、递进或对比结构，使信息一目了然。
 """
 
 # =================================================================
@@ -333,7 +373,7 @@ CSS_TEMPLATE_INFOGRAPHIC = """
     padding: 16px;
     min-height: 600px;
     background: #fff;
-    overflow: visible; /* Ensure content is visible */
+    overflow: visible;
     transition: height 0.3s ease;
 }
 .infographic-render-container svg text {
@@ -341,35 +381,58 @@ CSS_TEMPLATE_INFOGRAPHIC = """
 }
 .infographic-render-container svg foreignObject {
     font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "PingFang SC", "Hiragino Sans GB", "Microsoft YaHei", sans-serif !important;
-    line-height: 1.4 !important;
+    line-height: 1.3 !important;
+    overflow: visible !important;
 }
 /* 主标题样式 */
 .infographic-render-container svg foreignObject[data-element-type="title"] > * {
-    font-size: 1.5em !important;
-    font-weight: bold !important;
-    line-height: 1.4 !important;
-    white-space: nowrap !important;
-    overflow: hidden !important;
-    text-overflow: ellipsis !important;
-}
-/* 页面副标题和卡片标题样式 */
-.infographic-render-container svg foreignObject[data-element-type="desc"] > *,
-.infographic-render-container svg foreignObject[data-element-type="item-label"] > * {
-    font-size: 0.6em !important;
-    line-height: 1.4 !important;
-    white-space: nowrap !important;
-    overflow: hidden !important;
-    text-overflow: ellipsis !important;
-}
-/* 卡片标题额外增加底部间距 */
-.infographic-render-container svg foreignObject[data-element-type="item-label"] > * {
-    padding-bottom: 8px !important;
-    display: block !important;
-}
-/* 卡片描述文字保持正常换行 */
-.infographic-render-container svg foreignObject[data-element-type="item-desc"] > * {
-    line-height: 1.4 !important;
+    font-size: 1.3em !important;
+    font-weight: 800 !important;
+    line-height: 1.3 !important;
     white-space: normal !important;
+    word-break: break-word !important;
+    display: -webkit-box !important;
+    -webkit-line-clamp: 2 !important;
+    -webkit-box-orient: vertical !important;
+    overflow: hidden !important;
+    text-overflow: ellipsis !important;
+    text-align: center !important;
+}
+/* 页面副标题样式 */
+.infographic-render-container svg foreignObject[data-element-type="desc"] > * {
+    font-size: 0.85em !important;
+    line-height: 1.3 !important;
+    white-space: nowrap !important;
+    overflow: hidden !important;
+    text-overflow: ellipsis !important;
+    text-align: center !important;
+    display: block !important;
+    color: var(--ig-muted-text-color) !important;
+}
+/* 卡片标题样式 */
+.infographic-render-container svg foreignObject[data-element-type="item-label"] > * {
+    font-size: 0.9em !important;
+    font-weight: 600 !important;
+    line-height: 1.3 !important;
+    white-space: normal !important;
+    word-break: break-word !important;
+    display: -webkit-box !important;
+    -webkit-line-clamp: 2 !important;
+    -webkit-box-orient: vertical !important;
+    overflow: hidden !important;
+    text-overflow: ellipsis !important;
+    padding-bottom: 2px !important;
+}
+/* 卡片描述文字 */
+.infographic-render-container svg foreignObject[data-element-type="item-desc"] > * {
+    font-size: 0.82em !important;
+    line-height: 1.3 !important;
+    white-space: normal !important;
+    display: -webkit-box !important;
+    -webkit-line-clamp: 2 !important;
+    -webkit-box-orient: vertical !important;
+    overflow: hidden !important;
+    text-overflow: ellipsis !important;
 }
 .infographic-container-wrapper .download-area {
     text-align: center;
@@ -537,34 +600,36 @@ SCRIPT_TEMPLATE_INFOGRAPHIC = """
             }
         }
 
-        // 2. 模板映射配置
-        // 2. 模板映射配置
+        // 2. 模板映射配置 (官方 AntV 结构 ID)
         const TEMPLATE_MAPPING = {
-            // 列表与层级
+            // 列表与层级 - 短名称映射到完整模板名
             'list-grid': 'list-grid-compact-card',
+            'list-column': 'list-column-simple-vertical-arrow',
+            'list-row': 'list-row-simple-horizontal-arrow',
+            'hierarchy-tree': 'hierarchy-tree-tech-style-capsule-item',
+            
+            // 时序与时间线
+            'sequence-roadmap-vertical': 'sequence-roadmap-vertical-simple',
+            'sequence-timeline': 'sequence-timeline-simple',
+            'sequence-steps': 'sequence-steps-simple',
+            'sequence-horizontal-zigzag': 'sequence-horizontal-zigzag-simple',
+            
+            // 对比
+            'compare-binary-horizontal': 'compare-binary-horizontal-simple-vs',
+            'compare-hierarchy-row': 'compare-hierarchy-row-simple',
+            
+            // 图表
+            'chart-column': 'chart-column-simple',
+            'quadrant': 'quadrant-quarter-simple-card',
+            
+            // 向后兼容的旧映射
             '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',
-            
-            // 顺序与关系
             'sequence-roadmap': 'sequence-roadmap-vertical-simple',
             'sequence-zigzag': 'sequence-horizontal-zigzag-simple',
-            'sequence-horizontal': 'sequence-horizontal-zigzag-simple',
-            'relation-sankey': 'relation-sankey-simple', // 暂无直接对应，保留原值或需移除
-            'relation-circle': 'relation-circle-icon-badge',
-            
-            // 对比与分析
             'compare-binary': 'compare-binary-horizontal-simple-vs',
-            'compare-swot': 'compare-swot',
-            'quadrant-quarter': 'quadrant-quarter-simple-card',
-            
-            // 图表与数据
-            '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', // 暂无直接对应
             'chart-pie': 'chart-pie-plain-text',
             'chart-doughnut': 'chart-pie-donut-plain-text'
         };
@@ -657,10 +722,48 @@ SCRIPT_TEMPLATE_INFOGRAPHIC = """
             containerEl.dataset.infographicRendered = 'true';
             console.log('[Infographic] 渲染完成');
 
-            // 自动调整高度
+            // 自动调整高度与元素标记
             setTimeout(() => {
                 const svg = containerEl.querySelector('svg');
                 if (svg) {
+                    // 1. 标记元素以便 CSS 应用样式
+                    const fos = Array.from(svg.querySelectorAll('foreignObject'));
+                    let titleFound = false;
+                    let descFound = false;
+                    
+                    fos.forEach((fo) => {
+                        const text = fo.textContent.trim();
+                        if (!text || fo.querySelector('i') || (fo.querySelector('svg') && fo.querySelectorAll('*').length < 5)) {
+                            fo.setAttribute('data-element-type', 'icon');
+                            return;
+                        }
+                        
+                        // 动态增加高度和宽度，容纳换行后的文字
+                        const currentHeight = parseInt(fo.getAttribute('height') || '0');
+                        if (currentHeight > 0 && currentHeight < 200) {
+                            fo.setAttribute('height', Math.round(currentHeight * 1.8).toString());
+                        }
+                        const currentWidth = parseInt(fo.getAttribute('width') || '0');
+                        if (currentWidth > 0 && currentWidth < 300) {
+                            fo.setAttribute('width', Math.max(Math.round(currentWidth * 1.2), 180).toString());
+                        }
+
+                        if (!titleFound) {
+                            fo.setAttribute('data-element-type', 'title');
+                            titleFound = true;
+                        } else if (!descFound) {
+                            fo.setAttribute('data-element-type', 'desc');
+                            descFound = true;
+                        } else {
+                            if (fo.querySelector('strong') || fo.style.fontWeight === 'bold' || text.length < 15) {
+                                fo.setAttribute('data-element-type', 'item-label');
+                            } else {
+                                fo.setAttribute('data-element-type', 'item-desc');
+                            }
+                        }
+                    });
+
+                    // 2. 调整高度
                     const bbox = svg.getBoundingClientRect();
                     let contentHeight = bbox.height;
                     if (svg.viewBox && svg.viewBox.baseVal && svg.viewBox.baseVal.height) {
@@ -854,6 +957,10 @@ class Action:
             default="image",
             description="输出模式：'html' 为交互式HTML，'image' 将嵌入为Markdown图片（默认）。",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="是否在浏览器控制台打印调试日志。",
+        )
 
     def __init__(self):
         self.valves = self.Valves()
@@ -867,45 +974,56 @@ 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"""
+    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 _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        统一提取聊天上下文信息 (chat_id, message_id)。
+        优先从 body 中提取，其次从 metadata 中提取。
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. 尝试从 body 获取
         if isinstance(body, dict):
-            chat_id = body.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id 在 body 中通常是 id
 
-            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()
+            # 再次检查 body.metadata
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
 
-        if isinstance(metadata, dict):
-            chat_id = metadata.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+        # 2. 尝试从 __metadata__ 获取 (作为补充)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
 
-        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 ""
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
 
     def _extract_infographic_syntax(self, llm_output: str) -> str:
         """提取LLM输出中的infographic语法"""
@@ -958,6 +1076,24 @@ class Action:
                 {"type": "notification", "data": {"type": ntype, "content": content}}
             )
 
+    async def _emit_debug_log(self, 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 emitter:
+            return
+
+        try:
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
     def _remove_existing_html(self, content: str) -> str:
         """移除内容中已有的插件生成 HTML 代码块"""
         pattern = r"```html\s*<!-- OPENWEBUI_PLUGIN_OUTPUT -->[\s\S]*?```"
@@ -1562,8 +1698,9 @@ class Action:
             # 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"))
+                chat_ctx = self._get_chat_context(body, __metadata__)
+                chat_id = chat_ctx["chat_id"]
+                message_id = chat_ctx["message_id"]
 
                 await self._emit_status(
                     __event_emitter__,

plugins/actions/js-render-poc/README.md

@@ -1,170 +0,0 @@
-# Infographic to Markdown
-
-> **Version:** 1.0.0
-
-AI-powered infographic generator that renders SVG on the frontend and embeds it directly into Markdown as a Data URL image.
-
-## Overview
-
-This plugin combines the power of AI text analysis with AntV Infographic visualization to create beautiful infographics that are embedded directly into chat messages as Markdown images.
-
-### How It Works
-
-```
-┌─────────────────────────────────────────────────────────────┐
-│                    Open WebUI Plugin                         │
-├─────────────────────────────────────────────────────────────┤
-│  1. Python Action                                            │
-│     ├── Receive message content                              │
-│     ├── Call LLM to generate Infographic syntax              │
-│     └── Send __event_call__ to execute frontend JS           │
-├─────────────────────────────────────────────────────────────┤
-│  2. Browser JS (via __event_call__)                          │
-│     ├── Dynamically load AntV Infographic library            │
-│     ├── Render SVG offscreen                                 │
-│     ├── Export to Data URL via toDataURL()                   │
-│     └── Update message content via REST API                  │
-├─────────────────────────────────────────────────────────────┤
-│  3. Markdown Rendering                                       │
-│     └── Display ![description](data:image/svg+xml;base64,...) │
-└─────────────────────────────────────────────────────────────┘
-```
-
-## Features
-
-- 🤖 **AI-Powered**: Automatically analyzes text and selects the best infographic template
-- 📊 **Multiple Templates**: Supports 18+ infographic templates (lists, charts, comparisons, etc.)
-- 🖼️ **Self-Contained**: SVG/PNG embedded as Data URL, no external dependencies
-- 📝 **Markdown Native**: Results are pure Markdown images, compatible everywhere
-- 🔄 **API Writeback**: Updates message content via REST API for persistence
-
-## Plugins in This Directory
-
-### 1. `infographic_markdown.py` - Main Plugin ⭐
-- **Purpose**: Production use
-- **Features**: Full AI + AntV Infographic + Data URL embedding
-
-### 2. `js_render_poc.py` - Proof of Concept
-- **Purpose**: Learning and testing
-- **Features**: Simple SVG creation demo, `__event_call__` pattern
-
-## Configuration (Valves)
-
-| Parameter | Type | Default | Description |
-|-----------|------|---------|-------------|
-| `SHOW_STATUS` | bool | `true` | Show operation status updates |
-| `MODEL_ID` | string | `""` | LLM model ID (empty = use current model) |
-| `MIN_TEXT_LENGTH` | int | `50` | Minimum text length required |
-| `MESSAGE_COUNT` | int | `1` | Number of recent messages to use |
-| `SVG_WIDTH` | int | `800` | Width of generated SVG (pixels) |
-| `EXPORT_FORMAT` | string | `"svg"` | Export format: `svg` or `png` |
-
-## Supported Templates
-
-| Category | Template | Description |
-|----------|----------|-------------|
-| List | `list-grid` | Grid cards |
-| List | `list-vertical` | Vertical list |
-| Tree | `tree-vertical` | Vertical tree |
-| Tree | `tree-horizontal` | Horizontal tree |
-| Mind Map | `mindmap` | Mind map |
-| Process | `sequence-roadmap` | Roadmap |
-| Process | `sequence-zigzag` | Zigzag process |
-| Relation | `relation-sankey` | Sankey diagram |
-| Relation | `relation-circle` | Circular relation |
-| Compare | `compare-binary` | Binary comparison |
-| Analysis | `compare-swot` | SWOT analysis |
-| Quadrant | `quadrant-quarter` | Quadrant chart |
-| Chart | `chart-bar` | Bar chart |
-| Chart | `chart-column` | Column chart |
-| Chart | `chart-line` | Line chart |
-| Chart | `chart-pie` | Pie chart |
-| Chart | `chart-doughnut` | Doughnut chart |
-| Chart | `chart-area` | Area chart |
-
-## Syntax Examples
-
-### Grid List
-```infographic
-infographic list-grid
-data
-  title Project Overview
-  items
-    - label Module A
-      desc Description of module A
-    - label Module B
-      desc Description of module B
-```
-
-### Binary Comparison
-```infographic
-infographic compare-binary
-data
-  title Pros vs Cons
-  items
-    - label Pros
-      children
-        - label Strong R&D
-          desc Technology leadership
-    - label Cons
-      children
-        - label Weak brand
-          desc Insufficient marketing
-```
-
-### Bar Chart
-```infographic
-infographic chart-bar
-data
-  title Quarterly Revenue
-  items
-    - label Q1
-      value 120
-    - label Q2
-      value 150
-```
-
-## Technical Details
-
-### Data URL Embedding
-```javascript
-// SVG to Base64 Data URL
-const svgData = new XMLSerializer().serializeToString(svg);
-const base64 = btoa(unescape(encodeURIComponent(svgData)));
-const dataUri = "data:image/svg+xml;base64," + base64;
-
-// Markdown image syntax
-const markdownImage = `![description](${dataUri})`;
-```
-
-### AntV toDataURL API
-```javascript
-// Export as SVG (recommended, supports embedded resources)
-const svgUrl = await instance.toDataURL({
-    type: 'svg',
-    embedResources: true
-});
-
-// Export as PNG (more compatible but larger)
-const pngUrl = await instance.toDataURL({
-    type: 'png',
-    dpr: 2
-});
-```
-
-## Notes
-
-1. **Browser Compatibility**: Requires modern browsers with ES6+ and Fetch API support
-2. **Network Dependency**: First use requires loading AntV library from CDN
-3. **Data URL Size**: Base64 encoding increases size by ~33%
-4. **Chinese Fonts**: SVG export embeds fonts for correct display
-
-## Related Resources
-
-- [AntV Infographic Documentation](https://infographic.antv.vision/)
-- [Infographic API Reference](https://infographic.antv.vision/reference/infographic-api)
-- [Infographic Syntax Guide](https://infographic.antv.vision/learn/infographic-syntax)
-
-## License
-
-MIT License

plugins/actions/js-render-poc/README_CN.md

@@ -1,174 +0,0 @@
-# 信息图转 Markdown
-
-> **版本:** 1.0.0
-
-AI 驱动的信息图生成器，在前端渲染 SVG 并以 Data URL 图片格式直接嵌入到 Markdown 中。
-
-## 概述
-
-这个插件结合了 AI 文本分析能力和 AntV Infographic 可视化引擎，生成精美的信息图并以 Markdown 图片格式直接嵌入到聊天消息中。
-
-### 工作原理
-
-```
-┌─────────────────────────────────────────────────────────────┐
-│                    Open WebUI 插件                           │
-├─────────────────────────────────────────────────────────────┤
-│  1. Python Action                                            │
-│     ├── 接收消息内容                                          │
-│     ├── 调用 LLM 生成 Infographic 语法                        │
-│     └── 发送 __event_call__ 执行前端 JS                      │
-├─────────────────────────────────────────────────────────────┤
-│  2. 浏览器 JS (通过 __event_call__)                          │
-│     ├── 动态加载 AntV Infographic 库                          │
-│     ├── 离屏渲染 SVG                                          │
-│     ├── 使用 toDataURL() 导出 Data URL                        │
-│     └── 通过 REST API 更新消息内容                            │
-├─────────────────────────────────────────────────────────────┤
-│  3. Markdown 渲染                                            │
-│     └── 显示 ![描述](data:image/svg+xml;base64,...)          │
-└─────────────────────────────────────────────────────────────┘
-```
-
-## 功能特点
-
-- 🤖 **AI 驱动**: 自动分析文本并选择最佳的信息图模板
-- 📊 **多种模板**: 支持 18+ 种信息图模板（列表、图表、对比等）
-- 🖼️ **自包含**: SVG/PNG 以 Data URL 嵌入，无外部依赖
-- 📝 **Markdown 原生**: 结果是纯 Markdown 图片，兼容任何平台
-- 🔄 **API 回写**: 通过 REST API 更新消息内容实现持久化
-
-## 目录中的插件
-
-### 1. `infographic_markdown.py` - 主插件 ⭐
-- **用途**: 生产使用
-- **功能**: 完整的 AI + AntV Infographic + Data URL 嵌入
-
-### 2. `infographic_markdown_cn.py` - 主插件（中文版）
-- **用途**: 生产使用
-- **功能**: 与英文版相同，界面文字为中文
-
-### 3. `js_render_poc.py` - 概念验证
-- **用途**: 学习和测试
-- **功能**: 简单的 SVG 创建演示，`__event_call__` 模式
-
-## 配置选项 (Valves)
-
-| 参数 | 类型 | 默认值 | 描述 |
-|------|------|--------|------|
-| `SHOW_STATUS` | bool | `true` | 是否显示操作状态 |
-| `MODEL_ID` | string | `""` | LLM 模型 ID（空则使用当前模型） |
-| `MIN_TEXT_LENGTH` | int | `50` | 最小文本长度要求 |
-| `MESSAGE_COUNT` | int | `1` | 用于生成的最近消息数量 |
-| `SVG_WIDTH` | int | `800` | 生成的 SVG 宽度（像素） |
-| `EXPORT_FORMAT` | string | `"svg"` | 导出格式：`svg` 或 `png` |
-
-## 支持的模板
-
-| 类别 | 模板名称 | 描述 |
-|------|----------|------|
-| 列表 | `list-grid` | 网格卡片 |
-| 列表 | `list-vertical` | 垂直列表 |
-| 树形 | `tree-vertical` | 垂直树 |
-| 树形 | `tree-horizontal` | 水平树 |
-| 思维导图 | `mindmap` | 思维导图 |
-| 流程 | `sequence-roadmap` | 路线图 |
-| 流程 | `sequence-zigzag` | 折线流程 |
-| 关系 | `relation-sankey` | 桑基图 |
-| 关系 | `relation-circle` | 圆形关系 |
-| 对比 | `compare-binary` | 二元对比 |
-| 分析 | `compare-swot` | SWOT 分析 |
-| 象限 | `quadrant-quarter` | 四象限图 |
-| 图表 | `chart-bar` | 条形图 |
-| 图表 | `chart-column` | 柱状图 |
-| 图表 | `chart-line` | 折线图 |
-| 图表 | `chart-pie` | 饼图 |
-| 图表 | `chart-doughnut` | 环形图 |
-| 图表 | `chart-area` | 面积图 |
-
-## 语法示例
-
-### 网格列表
-```infographic
-infographic list-grid
-data
-  title 项目概览
-  items
-    - label 模块一
-      desc 这是第一个模块的描述
-    - label 模块二
-      desc 这是第二个模块的描述
-```
-
-### 二元对比
-```infographic
-infographic compare-binary
-data
-  title 优劣对比
-  items
-    - label 优势
-      children
-        - label 研发能力强
-          desc 技术领先
-    - label 劣势
-      children
-        - label 品牌曝光不足
-          desc 营销力度不够
-```
-
-### 条形图
-```infographic
-infographic chart-bar
-data
-  title 季度收入
-  items
-    - label Q1
-      value 120
-    - label Q2
-      value 150
-```
-
-## 技术细节
-
-### Data URL 嵌入
-```javascript
-// SVG 转 Base64 Data URL
-const svgData = new XMLSerializer().serializeToString(svg);
-const base64 = btoa(unescape(encodeURIComponent(svgData)));
-const dataUri = "data:image/svg+xml;base64," + base64;
-
-// Markdown 图片语法
-const markdownImage = `![描述](${dataUri})`;
-```
-
-### AntV toDataURL API
-```javascript
-// 导出 SVG（推荐，支持嵌入资源）
-const svgUrl = await instance.toDataURL({
-    type: 'svg',
-    embedResources: true
-});
-
-// 导出 PNG（更兼容但体积更大）
-const pngUrl = await instance.toDataURL({
-    type: 'png',
-    dpr: 2
-});
-```
-
-## 注意事项
-
-1. **浏览器兼容性**: 需要现代浏览器支持 ES6+ 和 Fetch API
-2. **网络依赖**: 首次使用需要从 CDN 加载 AntV Infographic 库
-3. **Data URL 大小**: Base64 编码会增加约 33% 的体积
-4. **中文字体**: SVG 导出时会嵌入字体以确保正确显示
-
-## 相关资源
-
-- [AntV Infographic 官方文档](https://infographic.antv.vision/)
-- [Infographic API 参考](https://infographic.antv.vision/reference/infographic-api)
-- [Infographic 语法规范](https://infographic.antv.vision/learn/infographic-syntax)
-
-## 许可证
-
-MIT License

plugins/actions/js-render-poc/infographic_markdown.py

@@ -1,592 +0,0 @@
-"""
-title: 📊 Infographic to Markdown
-author: Fu-Jie
-version: 1.0.0
-description: AI生成信息图语法，前端渲染SVG并转换为Markdown图片格式嵌入消息。支持AntV Infographic模板。
-"""
-
-import time
-import json
-import logging
-import re
-from typing import Optional, Callable, Awaitable, Any, Dict
-from pydantic import BaseModel, Field
-from fastapi import Request
-from datetime import datetime
-
-from open_webui.utils.chat import generate_chat_completion
-from open_webui.models.users import Users
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-# =================================================================
-# LLM Prompts
-# =================================================================
-
-SYSTEM_PROMPT_INFOGRAPHIC = """
-You are a professional infographic design expert who can analyze user-provided text content and convert it into AntV Infographic syntax format.
-
-## Infographic Syntax Specification
-
-Infographic syntax is a Mermaid-like declarative syntax for describing infographic templates, data, and themes.
-
-### Syntax Rules
-- Entry uses `infographic <template-name>`
-- Key-value pairs are separated by spaces, **absolutely NO colons allowed**
-- Use two spaces for indentation
-- Object arrays use `-` with line breaks
-
-⚠️ **IMPORTANT WARNING: This is NOT YAML format!**
-- ❌ Wrong: `children:` `items:` `data:` (with colons)
-- ✅ Correct: `children` `items` `data` (without colons)
-
-### Template Library & Selection Guide
-
-Choose the most appropriate template based on the content structure:
-
-#### 1. List & Hierarchy
-- **List**: `list-grid` (Grid Cards), `list-vertical` (Vertical List)
-- **Tree**: `tree-vertical` (Vertical Tree), `tree-horizontal` (Horizontal Tree)
-- **Mindmap**: `mindmap` (Mind Map)
-
-#### 2. Sequence & Relationship
-- **Process**: `sequence-roadmap` (Roadmap), `sequence-zigzag` (Zigzag Process)
-- **Relationship**: `relation-sankey` (Sankey Diagram), `relation-circle` (Circular)
-
-#### 3. Comparison & Analysis
-- **Comparison**: `compare-binary` (Binary Comparison)
-- **Analysis**: `compare-swot` (SWOT Analysis), `quadrant-quarter` (Quadrant Chart)
-
-#### 4. Charts & Data
-- **Charts**: `chart-bar`, `chart-column`, `chart-line`, `chart-pie`, `chart-doughnut`, `chart-area`
-
-### Data Structure Examples
-
-#### A. Standard List/Tree
-```infographic
-infographic list-grid
-data
-  title Project Modules
-  items
-    - label Module A
-      desc Description of A
-    - label Module B
-      desc Description of B
-```
-
-#### B. Binary Comparison
-```infographic
-infographic compare-binary
-data
-  title Advantages vs Disadvantages
-  items
-    - label Advantages
-      children
-        - label Strong R&D
-          desc Leading technology
-    - label Disadvantages
-      children
-        - label Weak brand
-          desc Insufficient marketing
-```
-
-#### C. Charts
-```infographic
-infographic chart-bar
-data
-  title Quarterly Revenue
-  items
-    - label Q1
-      value 120
-    - label Q2
-      value 150
-```
-
-### Common Data Fields
-- `label`: Main title/label (Required)
-- `desc`: Description text (max 30 Chinese chars / 60 English chars for `list-grid`)
-- `value`: Numeric value (for charts)
-- `children`: Nested items
-
-## Output Requirements
-1. **Language**: Output content in the user's language.
-2. **Format**: Wrap output in ```infographic ... ```.
-3. **No Colons**: Do NOT use colons after keys.
-4. **Indentation**: Use 2 spaces.
-"""
-
-USER_PROMPT_GENERATE = """
-Please analyze the following text content and convert its core information into AntV Infographic syntax format.
-
----
-**User Context:**
-User Name: {user_name}
-Current Date/Time: {current_date_time_str}
-User Language: {user_language}
----
-
-**Text Content:**
-{long_text_content}
-
-Please select the most appropriate infographic template based on text characteristics and output standard infographic syntax.
-
-**Important Note:** 
-- If using `list-grid` format, ensure each card's `desc` description is limited to **maximum 30 Chinese characters** (or **approximately 60 English characters**).
-- Descriptions should be concise and highlight key points.
-"""
-
-
-class Action:
-    class Valves(BaseModel):
-        SHOW_STATUS: bool = Field(
-            default=True, description="Show operation status updates in chat interface."
-        )
-        MODEL_ID: str = Field(
-            default="",
-            description="LLM model ID for text analysis. If empty, uses current conversation model.",
-        )
-        MIN_TEXT_LENGTH: int = Field(
-            default=50,
-            description="Minimum text length (characters) required for infographic analysis.",
-        )
-        MESSAGE_COUNT: int = Field(
-            default=1,
-            description="Number of recent messages to use for generation.",
-        )
-        SVG_WIDTH: int = Field(
-            default=800,
-            description="Width of generated SVG in pixels.",
-        )
-        EXPORT_FORMAT: str = Field(
-            default="svg",
-            description="Export format: 'svg' or 'png'.",
-        )
-
-    def __init__(self):
-        self.valves = self.Valves()
-
-    def _extract_chat_id(self, body: dict, metadata: Optional[dict]) -> str:
-        """Extract chat_id from body or metadata"""
-        if isinstance(body, dict):
-            chat_id = body.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
-
-            body_metadata = body.get("metadata", {})
-            if isinstance(body_metadata, dict):
-                chat_id = body_metadata.get("chat_id")
-                if isinstance(chat_id, str) and chat_id.strip():
-                    return chat_id.strip()
-
-        if isinstance(metadata, dict):
-            chat_id = metadata.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
-
-        return ""
-
-    def _extract_message_id(self, body: dict, metadata: Optional[dict]) -> str:
-        """Extract message_id from body or metadata"""
-        if isinstance(body, dict):
-            message_id = body.get("id")
-            if isinstance(message_id, str) and message_id.strip():
-                return message_id.strip()
-
-            body_metadata = body.get("metadata", {})
-            if isinstance(body_metadata, dict):
-                message_id = body_metadata.get("message_id")
-                if isinstance(message_id, str) and message_id.strip():
-                    return message_id.strip()
-
-        if isinstance(metadata, dict):
-            message_id = metadata.get("message_id")
-            if isinstance(message_id, str) and message_id.strip():
-                return message_id.strip()
-
-        return ""
-
-    def _extract_infographic_syntax(self, llm_output: str) -> str:
-        """Extract infographic syntax from LLM output"""
-        match = re.search(r"```infographic\s*(.*?)\s*```", llm_output, re.DOTALL)
-        if match:
-            return match.group(1).strip()
-        else:
-            logger.warning("LLM output did not follow expected format, treating entire output as syntax.")
-            return llm_output.strip()
-
-    def _extract_text_content(self, content) -> str:
-        """Extract text from message content, supporting multimodal formats"""
-        if isinstance(content, str):
-            return content
-        elif isinstance(content, list):
-            text_parts = []
-            for item in content:
-                if isinstance(item, dict) and item.get("type") == "text":
-                    text_parts.append(item.get("text", ""))
-                elif isinstance(item, str):
-                    text_parts.append(item)
-            return "\n".join(text_parts)
-        return str(content) if content else ""
-
-    async def _emit_status(self, emitter, description: str, done: bool = False):
-        """Send status update event"""
-        if self.valves.SHOW_STATUS and emitter:
-            await emitter(
-                {"type": "status", "data": {"description": description, "done": done}}
-            )
-
-    def _generate_js_code(
-        self,
-        unique_id: str,
-        chat_id: str,
-        message_id: str,
-        infographic_syntax: str,
-        svg_width: int,
-        export_format: str,
-    ) -> str:
-        """Generate JavaScript code for frontend SVG rendering"""
-        
-        # Escape the syntax for JS embedding
-        syntax_escaped = (
-            infographic_syntax
-            .replace("\\", "\\\\")
-            .replace("`", "\\`")
-            .replace("${", "\\${")
-            .replace("</script>", "<\\/script>")
-        )
-        
-        # Template mapping (same as infographic.py)
-        template_mapping_js = """
-        const TEMPLATE_MAPPING = {
-            'list-grid': 'list-grid-compact-card',
-            'list-vertical': 'list-column-simple-vertical-arrow',
-            'tree-vertical': 'hierarchy-tree-tech-style-capsule-item',
-            'tree-horizontal': 'hierarchy-tree-lr-tech-style-capsule-item',
-            'mindmap': 'hierarchy-mindmap-branch-gradient-capsule-item',
-            'sequence-roadmap': 'sequence-roadmap-vertical-simple',
-            'sequence-zigzag': 'sequence-horizontal-zigzag-simple',
-            'sequence-horizontal': 'sequence-horizontal-zigzag-simple',
-            'relation-sankey': 'relation-sankey-simple',
-            'relation-circle': 'relation-circle-icon-badge',
-            'compare-binary': 'compare-binary-horizontal-simple-vs',
-            'compare-swot': 'compare-swot',
-            'quadrant-quarter': 'quadrant-quarter-simple-card',
-            'statistic-card': 'list-grid-compact-card',
-            'chart-bar': 'chart-bar-plain-text',
-            'chart-column': 'chart-column-simple',
-            'chart-line': 'chart-line-plain-text',
-            'chart-area': 'chart-area-simple',
-            'chart-pie': 'chart-pie-plain-text',
-            'chart-doughnut': 'chart-pie-donut-plain-text'
-        };
-        """
-        
-        return f"""
-(async function() {{
-    const uniqueId = "{unique_id}";
-    const chatId = "{chat_id}";
-    const messageId = "{message_id}";
-    const svgWidth = {svg_width};
-    const exportFormat = "{export_format}";
-    
-    console.log("[Infographic Markdown] Starting render...");
-    console.log("[Infographic Markdown] chatId:", chatId, "messageId:", messageId);
-    
-    try {{
-        // Load AntV Infographic if not loaded
-        if (typeof AntVInfographic === 'undefined') {{
-            console.log("[Infographic Markdown] Loading AntV Infographic library...");
-            await new Promise((resolve, reject) => {{
-                const script = document.createElement('script');
-                script.src = 'https://unpkg.com/@antv/infographic@latest/dist/infographic.min.js';
-                script.onload = resolve;
-                script.onerror = reject;
-                document.head.appendChild(script);
-            }});
-            console.log("[Infographic Markdown] Library loaded.");
-        }}
-        
-        const {{ Infographic }} = AntVInfographic;
-        
-        // Get infographic syntax
-        let syntaxContent = `{syntax_escaped}`;
-        console.log("[Infographic Markdown] Original syntax:", syntaxContent.substring(0, 200) + "...");
-        
-        // Clean up syntax
-        const backtick = String.fromCharCode(96);
-        const prefix = backtick + backtick + backtick + 'infographic';
-        const simplePrefix = backtick + backtick + backtick;
-        
-        if (syntaxContent.toLowerCase().startsWith(prefix)) {{
-            syntaxContent = syntaxContent.substring(prefix.length).trim();
-        }} else if (syntaxContent.startsWith(simplePrefix)) {{
-            syntaxContent = syntaxContent.substring(simplePrefix.length).trim();
-        }}
-        
-        if (syntaxContent.endsWith(simplePrefix)) {{
-            syntaxContent = syntaxContent.substring(0, syntaxContent.length - simplePrefix.length).trim();
-        }}
-        
-        // Fix colons after keywords
-        syntaxContent = syntaxContent.replace(/^(data|items|children|theme|config):/gm, '$1');
-        syntaxContent = syntaxContent.replace(/(\\s)(children|items):/g, '$1$2');
-        
-        // Ensure infographic prefix
-        if (!syntaxContent.trim().toLowerCase().startsWith('infographic')) {{
-            syntaxContent = 'infographic list-grid\\n' + syntaxContent;
-        }}
-        
-        // Apply template mapping
-        {template_mapping_js}
-        
-        for (const [key, value] of Object.entries(TEMPLATE_MAPPING)) {{
-            const regex = new RegExp(`infographic\\\\s+${{key}}(?=\\\\s|$)`, 'i');
-            if (regex.test(syntaxContent)) {{
-                console.log(`[Infographic Markdown] Auto-mapping: ${{key}} -> ${{value}}`);
-                syntaxContent = syntaxContent.replace(regex, `infographic ${{value}}`);
-                break;
-            }}
-        }}
-        
-        console.log("[Infographic Markdown] Cleaned syntax:", syntaxContent.substring(0, 200) + "...");
-        
-        // Create offscreen container
-        const container = document.createElement('div');
-        container.id = 'infographic-offscreen-' + uniqueId;
-        container.style.cssText = 'position:absolute;left:-9999px;top:-9999px;width:' + svgWidth + 'px;';
-        document.body.appendChild(container);
-        
-        // Create and render infographic
-        const instance = new Infographic({{
-            container: '#' + container.id,
-            width: svgWidth,
-            padding: 24,
-        }});
-        
-        console.log("[Infographic Markdown] Rendering infographic...");
-        instance.render(syntaxContent);
-        
-        // Wait for render and export
-        await new Promise(resolve => setTimeout(resolve, 1000));
-        
-        let dataUrl;
-        if (exportFormat === 'png') {{
-            dataUrl = await instance.toDataURL({{ type: 'png', dpr: 2 }});
-        }} else {{
-            dataUrl = await instance.toDataURL({{ type: 'svg', embedResources: true }});
-        }}
-        
-        console.log("[Infographic Markdown] Data URL generated, length:", dataUrl.length);
-        
-        // Cleanup
-        instance.destroy();
-        document.body.removeChild(container);
-        
-        // Generate markdown image
-        const markdownImage = `![📊 AI 生成的信息图](${{dataUrl}})`;
-        
-        // Update message via API
-        if (chatId && messageId) {{
-            const token = localStorage.getItem("token");
-            
-            // Get current message content
-            const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
-                method: "GET",
-                headers: {{ "Authorization": `Bearer ${{token}}` }}
-            }});
-            
-            if (!getResponse.ok) {{
-                throw new Error("Failed to get chat data: " + getResponse.status);
-            }}
-            
-            const chatData = await getResponse.json();
-            let originalContent = "";
-            
-            if (chatData.chat && chatData.chat.messages) {{
-                const targetMsg = chatData.chat.messages.find(m => m.id === messageId);
-                if (targetMsg && targetMsg.content) {{
-                    originalContent = targetMsg.content;
-                }}
-            }}
-            
-            // Remove existing infographic images
-            const infographicPattern = /\\n*!\\[📊[^\\]]*\\]\\(data:image\\/[^)]+\\)/g;
-            let cleanedContent = originalContent.replace(infographicPattern, "");
-            cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
-            
-            // Append new image
-            const newContent = cleanedContent + "\\n\\n" + markdownImage;
-            
-            // Update message
-            const updateResponse = await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
-                method: "POST",
-                headers: {{
-                    "Content-Type": "application/json",
-                    "Authorization": `Bearer ${{token}}`
-                }},
-                body: JSON.stringify({{
-                    type: "chat:message",
-                    data: {{ content: newContent }}
-                }})
-            }});
-            
-            if (updateResponse.ok) {{
-                console.log("[Infographic Markdown] ✅ Message updated successfully!");
-            }} else {{
-                console.error("[Infographic Markdown] API error:", updateResponse.status);
-            }}
-        }} else {{
-            console.warn("[Infographic Markdown] ⚠️ Missing chatId or messageId");
-        }}
-        
-    }} catch (error) {{
-        console.error("[Infographic Markdown] Error:", error);
-    }}
-}})();
-"""
-
-    async def action(
-        self,
-        body: dict,
-        __user__: dict = None,
-        __event_emitter__=None,
-        __event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
-        __metadata__: Optional[dict] = None,
-        __request__: Request = None,
-    ) -> dict:
-        """
-        Generate infographic using AntV and embed as Markdown image.
-        """
-        logger.info("Action: Infographic to Markdown started")
-
-        # Get user information
-        if isinstance(__user__, (list, tuple)):
-            user_language = __user__[0].get("language", "en") if __user__ else "en"
-            user_name = __user__[0].get("name", "User") if __user__[0] else "User"
-            user_id = __user__[0].get("id", "unknown_user") if __user__ else "unknown_user"
-        elif isinstance(__user__, dict):
-            user_language = __user__.get("language", "en")
-            user_name = __user__.get("name", "User")
-            user_id = __user__.get("id", "unknown_user")
-        else:
-            user_language = "en"
-            user_name = "User"
-            user_id = "unknown_user"
-
-        # Get current time
-        now = datetime.now()
-        current_date_time_str = now.strftime("%Y-%m-%d %H:%M:%S")
-
-        try:
-            messages = body.get("messages", [])
-            if not messages:
-                raise ValueError("No messages available.")
-
-            # Get recent messages
-            message_count = min(self.valves.MESSAGE_COUNT, len(messages))
-            recent_messages = messages[-message_count:]
-
-            # Aggregate content
-            aggregated_parts = []
-            for msg in recent_messages:
-                text_content = self._extract_text_content(msg.get("content"))
-                if text_content:
-                    aggregated_parts.append(text_content)
-
-            if not aggregated_parts:
-                raise ValueError("No text content found in messages.")
-
-            long_text_content = "\n\n---\n\n".join(aggregated_parts)
-
-            # Remove existing HTML blocks
-            parts = re.split(r"```html.*?```", long_text_content, flags=re.DOTALL)
-            clean_content = ""
-            for part in reversed(parts):
-                if part.strip():
-                    clean_content = part.strip()
-                    break
-
-            if not clean_content:
-                clean_content = long_text_content.strip()
-
-            # Check minimum length
-            if len(clean_content) < self.valves.MIN_TEXT_LENGTH:
-                await self._emit_status(
-                    __event_emitter__,
-                    f"⚠️ 内容太短 ({len(clean_content)} 字符)，至少需要 {self.valves.MIN_TEXT_LENGTH} 字符",
-                    True,
-                )
-                return body
-
-            await self._emit_status(__event_emitter__, "📊 正在分析内容...", False)
-
-            # Generate infographic syntax via LLM
-            formatted_user_prompt = USER_PROMPT_GENERATE.format(
-                user_name=user_name,
-                current_date_time_str=current_date_time_str,
-                user_language=user_language,
-                long_text_content=clean_content,
-            )
-
-            target_model = self.valves.MODEL_ID or body.get("model")
-
-            llm_payload = {
-                "model": target_model,
-                "messages": [
-                    {"role": "system", "content": SYSTEM_PROMPT_INFOGRAPHIC},
-                    {"role": "user", "content": formatted_user_prompt},
-                ],
-                "stream": False,
-            }
-
-            user_obj = Users.get_user_by_id(user_id)
-            if not user_obj:
-                raise ValueError(f"Unable to get user object: {user_id}")
-
-            await self._emit_status(__event_emitter__, "📊 AI 正在生成信息图语法...", False)
-
-            llm_response = await generate_chat_completion(__request__, llm_payload, user_obj)
-
-            if not llm_response or "choices" not in llm_response or not llm_response["choices"]:
-                raise ValueError("Invalid LLM response.")
-
-            assistant_content = llm_response["choices"][0]["message"]["content"]
-            infographic_syntax = self._extract_infographic_syntax(assistant_content)
-
-            logger.info(f"Generated syntax: {infographic_syntax[:200]}...")
-
-            # Extract IDs for API callback
-            chat_id = self._extract_chat_id(body, __metadata__)
-            message_id = self._extract_message_id(body, __metadata__)
-            unique_id = f"ig_{int(time.time() * 1000)}"
-
-            await self._emit_status(__event_emitter__, "📊 正在渲染 SVG...", False)
-
-            # Execute JS to render and embed
-            if __event_call__:
-                js_code = self._generate_js_code(
-                    unique_id=unique_id,
-                    chat_id=chat_id,
-                    message_id=message_id,
-                    infographic_syntax=infographic_syntax,
-                    svg_width=self.valves.SVG_WIDTH,
-                    export_format=self.valves.EXPORT_FORMAT,
-                )
-
-                await __event_call__(
-                    {
-                        "type": "execute",
-                        "data": {"code": js_code},
-                    }
-                )
-
-            await self._emit_status(__event_emitter__, "✅ 信息图生成完成！", True)
-            logger.info("Infographic to Markdown completed")
-
-        except Exception as e:
-            error_message = f"Infographic generation failed: {str(e)}"
-            logger.error(error_message, exc_info=True)
-            await self._emit_status(__event_emitter__, f"❌ {error_message}", True)
-
-        return body

plugins/actions/js-render-poc/infographic_markdown_cn.py

@@ -1,592 +0,0 @@
-"""
-title: 📊 信息图转 Markdown
-author: Fu-Jie
-version: 1.0.0
-description: AI 生成信息图语法，前端渲染 SVG 并转换为 Markdown 图片格式嵌入消息。支持 AntV Infographic 模板。
-"""
-
-import time
-import json
-import logging
-import re
-from typing import Optional, Callable, Awaitable, Any, Dict
-from pydantic import BaseModel, Field
-from fastapi import Request
-from datetime import datetime
-
-from open_webui.utils.chat import generate_chat_completion
-from open_webui.models.users import Users
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-# =================================================================
-# LLM 提示词
-# =================================================================
-
-SYSTEM_PROMPT_INFOGRAPHIC = """
-你是一位专业的信息图设计专家，能够分析用户提供的文本内容并将其转换为 AntV Infographic 语法格式。
-
-## 信息图语法规范
-
-信息图语法是一种类似 Mermaid 的声明式语法，用于描述信息图模板、数据和主题。
-
-### 语法规则
-- 入口使用 `infographic <模板名>`
-- 键值对用空格分隔，**绝对不允许使用冒号**
-- 使用两个空格缩进
-- 对象数组使用 `-` 加换行
-
-⚠️ **重要警告：这不是 YAML 格式！**
-- ❌ 错误：`children:` `items:` `data:`（带冒号）
-- ✅ 正确：`children` `items` `data`（不带冒号）
-
-### 模板库与选择指南
-
-根据内容结构选择最合适的模板：
-
-#### 1. 列表与层级
-- **列表**：`list-grid`（网格卡片）、`list-vertical`（垂直列表）
-- **树形**：`tree-vertical`（垂直树）、`tree-horizontal`（水平树）
-- **思维导图**：`mindmap`（思维导图）
-
-#### 2. 序列与关系
-- **流程**：`sequence-roadmap`（路线图）、`sequence-zigzag`（折线流程）
-- **关系**：`relation-sankey`（桑基图）、`relation-circle`（圆形关系）
-
-#### 3. 对比与分析
-- **对比**：`compare-binary`（二元对比）
-- **分析**：`compare-swot`（SWOT 分析）、`quadrant-quarter`（象限图）
-
-#### 4. 图表与数据
-- **图表**：`chart-bar`、`chart-column`、`chart-line`、`chart-pie`、`chart-doughnut`、`chart-area`
-
-### 数据结构示例
-
-#### A. 标准列表/树形
-```infographic
-infographic list-grid
-data
-  title 项目模块
-  items
-    - label 模块 A
-      desc 模块 A 的描述
-    - label 模块 B
-      desc 模块 B 的描述
-```
-
-#### B. 二元对比
-```infographic
-infographic compare-binary
-data
-  title 优势与劣势
-  items
-    - label 优势
-      children
-        - label 研发能力强
-          desc 技术领先
-    - label 劣势
-      children
-        - label 品牌曝光弱
-          desc 营销不足
-```
-
-#### C. 图表
-```infographic
-infographic chart-bar
-data
-  title 季度收入
-  items
-    - label Q1
-      value 120
-    - label Q2
-      value 150
-```
-
-### 常用数据字段
-- `label`：主标题/标签（必填）
-- `desc`：描述文字（`list-grid` 最多 30 个中文字符）
-- `value`：数值（用于图表）
-- `children`：嵌套项
-
-## 输出要求
-1. **语言**：使用用户的语言输出内容。
-2. **格式**：用 ```infographic ... ``` 包裹输出。
-3. **无冒号**：键后面不要使用冒号。
-4. **缩进**：使用 2 个空格。
-"""
-
-USER_PROMPT_GENERATE = """
-请分析以下文本内容，将其核心信息转换为 AntV Infographic 语法格式。
-
----
-**用户上下文：**
-用户名：{user_name}
-当前时间：{current_date_time_str}
-用户语言：{user_language}
----
-
-**文本内容：**
-{long_text_content}
-
-请根据文本特征选择最合适的信息图模板，输出标准的信息图语法。
-
-**重要提示：** 
-- 如果使用 `list-grid` 格式，确保每个卡片的 `desc` 描述限制在 **最多 30 个中文字符**。
-- 描述应简洁，突出重点。
-"""
-
-
-class Action:
-    class Valves(BaseModel):
-        SHOW_STATUS: bool = Field(
-            default=True, description="在聊天界面显示操作状态更新。"
-        )
-        MODEL_ID: str = Field(
-            default="",
-            description="用于文本分析的 LLM 模型 ID。留空则使用当前对话模型。",
-        )
-        MIN_TEXT_LENGTH: int = Field(
-            default=50,
-            description="信息图分析所需的最小文本长度（字符数）。",
-        )
-        MESSAGE_COUNT: int = Field(
-            default=1,
-            description="用于生成的最近消息数量。",
-        )
-        SVG_WIDTH: int = Field(
-            default=800,
-            description="生成的 SVG 宽度（像素）。",
-        )
-        EXPORT_FORMAT: str = Field(
-            default="svg",
-            description="导出格式：'svg' 或 'png'。",
-        )
-
-    def __init__(self):
-        self.valves = self.Valves()
-
-    def _extract_chat_id(self, body: dict, metadata: Optional[dict]) -> str:
-        """从 body 或 metadata 中提取 chat_id"""
-        if isinstance(body, dict):
-            chat_id = body.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
-
-            body_metadata = body.get("metadata", {})
-            if isinstance(body_metadata, dict):
-                chat_id = body_metadata.get("chat_id")
-                if isinstance(chat_id, str) and chat_id.strip():
-                    return chat_id.strip()
-
-        if isinstance(metadata, dict):
-            chat_id = metadata.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
-
-        return ""
-
-    def _extract_message_id(self, body: dict, metadata: Optional[dict]) -> str:
-        """从 body 或 metadata 中提取 message_id"""
-        if isinstance(body, dict):
-            message_id = body.get("id")
-            if isinstance(message_id, str) and message_id.strip():
-                return message_id.strip()
-
-            body_metadata = body.get("metadata", {})
-            if isinstance(body_metadata, dict):
-                message_id = body_metadata.get("message_id")
-                if isinstance(message_id, str) and message_id.strip():
-                    return message_id.strip()
-
-        if isinstance(metadata, dict):
-            message_id = metadata.get("message_id")
-            if isinstance(message_id, str) and message_id.strip():
-                return message_id.strip()
-
-        return ""
-
-    def _extract_infographic_syntax(self, llm_output: str) -> str:
-        """从 LLM 输出中提取信息图语法"""
-        match = re.search(r"```infographic\s*(.*?)\s*```", llm_output, re.DOTALL)
-        if match:
-            return match.group(1).strip()
-        else:
-            logger.warning("LLM 输出未遵循预期格式，将整个输出作为语法处理。")
-            return llm_output.strip()
-
-    def _extract_text_content(self, content) -> str:
-        """从消息内容中提取文本，支持多模态格式"""
-        if isinstance(content, str):
-            return content
-        elif isinstance(content, list):
-            text_parts = []
-            for item in content:
-                if isinstance(item, dict) and item.get("type") == "text":
-                    text_parts.append(item.get("text", ""))
-                elif isinstance(item, str):
-                    text_parts.append(item)
-            return "\n".join(text_parts)
-        return str(content) if content else ""
-
-    async def _emit_status(self, emitter, description: str, done: bool = False):
-        """发送状态更新事件"""
-        if self.valves.SHOW_STATUS and emitter:
-            await emitter(
-                {"type": "status", "data": {"description": description, "done": done}}
-            )
-
-    def _generate_js_code(
-        self,
-        unique_id: str,
-        chat_id: str,
-        message_id: str,
-        infographic_syntax: str,
-        svg_width: int,
-        export_format: str,
-    ) -> str:
-        """生成用于前端 SVG 渲染的 JavaScript 代码"""
-        
-        # 转义语法以便嵌入 JS
-        syntax_escaped = (
-            infographic_syntax
-            .replace("\\", "\\\\")
-            .replace("`", "\\`")
-            .replace("${", "\\${")
-            .replace("</script>", "<\\/script>")
-        )
-        
-        # 模板映射
-        template_mapping_js = """
-        const TEMPLATE_MAPPING = {
-            'list-grid': 'list-grid-compact-card',
-            'list-vertical': 'list-column-simple-vertical-arrow',
-            'tree-vertical': 'hierarchy-tree-tech-style-capsule-item',
-            'tree-horizontal': 'hierarchy-tree-lr-tech-style-capsule-item',
-            'mindmap': 'hierarchy-mindmap-branch-gradient-capsule-item',
-            'sequence-roadmap': 'sequence-roadmap-vertical-simple',
-            'sequence-zigzag': 'sequence-horizontal-zigzag-simple',
-            'sequence-horizontal': 'sequence-horizontal-zigzag-simple',
-            'relation-sankey': 'relation-sankey-simple',
-            'relation-circle': 'relation-circle-icon-badge',
-            'compare-binary': 'compare-binary-horizontal-simple-vs',
-            'compare-swot': 'compare-swot',
-            'quadrant-quarter': 'quadrant-quarter-simple-card',
-            'statistic-card': 'list-grid-compact-card',
-            'chart-bar': 'chart-bar-plain-text',
-            'chart-column': 'chart-column-simple',
-            'chart-line': 'chart-line-plain-text',
-            'chart-area': 'chart-area-simple',
-            'chart-pie': 'chart-pie-plain-text',
-            'chart-doughnut': 'chart-pie-donut-plain-text'
-        };
-        """
-        
-        return f"""
-(async function() {{
-    const uniqueId = "{unique_id}";
-    const chatId = "{chat_id}";
-    const messageId = "{message_id}";
-    const svgWidth = {svg_width};
-    const exportFormat = "{export_format}";
-    
-    console.log("[信息图 Markdown] 开始渲染...");
-    console.log("[信息图 Markdown] chatId:", chatId, "messageId:", messageId);
-    
-    try {{
-        // 加载 AntV Infographic（如果尚未加载）
-        if (typeof AntVInfographic === 'undefined') {{
-            console.log("[信息图 Markdown] 正在加载 AntV Infographic 库...");
-            await new Promise((resolve, reject) => {{
-                const script = document.createElement('script');
-                script.src = 'https://unpkg.com/@antv/infographic@latest/dist/infographic.min.js';
-                script.onload = resolve;
-                script.onerror = reject;
-                document.head.appendChild(script);
-            }});
-            console.log("[信息图 Markdown] 库加载完成。");
-        }}
-        
-        const {{ Infographic }} = AntVInfographic;
-        
-        // 获取信息图语法
-        let syntaxContent = `{syntax_escaped}`;
-        console.log("[信息图 Markdown] 原始语法:", syntaxContent.substring(0, 200) + "...");
-        
-        // 清理语法
-        const backtick = String.fromCharCode(96);
-        const prefix = backtick + backtick + backtick + 'infographic';
-        const simplePrefix = backtick + backtick + backtick;
-        
-        if (syntaxContent.toLowerCase().startsWith(prefix)) {{
-            syntaxContent = syntaxContent.substring(prefix.length).trim();
-        }} else if (syntaxContent.startsWith(simplePrefix)) {{
-            syntaxContent = syntaxContent.substring(simplePrefix.length).trim();
-        }}
-        
-        if (syntaxContent.endsWith(simplePrefix)) {{
-            syntaxContent = syntaxContent.substring(0, syntaxContent.length - simplePrefix.length).trim();
-        }}
-        
-        // 修复关键字后的冒号
-        syntaxContent = syntaxContent.replace(/^(data|items|children|theme|config):/gm, '$1');
-        syntaxContent = syntaxContent.replace(/(\\s)(children|items):/g, '$1$2');
-        
-        // 确保有 infographic 前缀
-        if (!syntaxContent.trim().toLowerCase().startsWith('infographic')) {{
-            syntaxContent = 'infographic list-grid\\n' + syntaxContent;
-        }}
-        
-        // 应用模板映射
-        {template_mapping_js}
-        
-        for (const [key, value] of Object.entries(TEMPLATE_MAPPING)) {{
-            const regex = new RegExp(`infographic\\\\s+${{key}}(?=\\\\s|$)`, 'i');
-            if (regex.test(syntaxContent)) {{
-                console.log(`[信息图 Markdown] 自动映射: ${{key}} -> ${{value}}`);
-                syntaxContent = syntaxContent.replace(regex, `infographic ${{value}}`);
-                break;
-            }}
-        }}
-        
-        console.log("[信息图 Markdown] 清理后语法:", syntaxContent.substring(0, 200) + "...");
-        
-        // 创建离屏容器
-        const container = document.createElement('div');
-        container.id = 'infographic-offscreen-' + uniqueId;
-        container.style.cssText = 'position:absolute;left:-9999px;top:-9999px;width:' + svgWidth + 'px;';
-        document.body.appendChild(container);
-        
-        // 创建并渲染信息图
-        const instance = new Infographic({{
-            container: '#' + container.id,
-            width: svgWidth,
-            padding: 24,
-        }});
-        
-        console.log("[信息图 Markdown] 正在渲染信息图...");
-        instance.render(syntaxContent);
-        
-        // 等待渲染完成并导出
-        await new Promise(resolve => setTimeout(resolve, 1000));
-        
-        let dataUrl;
-        if (exportFormat === 'png') {{
-            dataUrl = await instance.toDataURL({{ type: 'png', dpr: 2 }});
-        }} else {{
-            dataUrl = await instance.toDataURL({{ type: 'svg', embedResources: true }});
-        }}
-        
-        console.log("[信息图 Markdown] Data URL 已生成，长度:", dataUrl.length);
-        
-        // 清理
-        instance.destroy();
-        document.body.removeChild(container);
-        
-        // 生成 Markdown 图片
-        const markdownImage = `![📊 AI 生成的信息图](${{dataUrl}})`;
-        
-        // 通过 API 更新消息
-        if (chatId && messageId) {{
-            const token = localStorage.getItem("token");
-            
-            // 获取当前消息内容
-            const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
-                method: "GET",
-                headers: {{ "Authorization": `Bearer ${{token}}` }}
-            }});
-            
-            if (!getResponse.ok) {{
-                throw new Error("获取对话数据失败: " + getResponse.status);
-            }}
-            
-            const chatData = await getResponse.json();
-            let originalContent = "";
-            
-            if (chatData.chat && chatData.chat.messages) {{
-                const targetMsg = chatData.chat.messages.find(m => m.id === messageId);
-                if (targetMsg && targetMsg.content) {{
-                    originalContent = targetMsg.content;
-                }}
-            }}
-            
-            // 移除已有的信息图图片
-            const infographicPattern = /\\n*!\\[📊[^\\]]*\\]\\(data:image\\/[^)]+\\)/g;
-            let cleanedContent = originalContent.replace(infographicPattern, "");
-            cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
-            
-            // 追加新图片
-            const newContent = cleanedContent + "\\n\\n" + markdownImage;
-            
-            // 更新消息
-            const updateResponse = await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
-                method: "POST",
-                headers: {{
-                    "Content-Type": "application/json",
-                    "Authorization": `Bearer ${{token}}`
-                }},
-                body: JSON.stringify({{
-                    type: "chat:message",
-                    data: {{ content: newContent }}
-                }})
-            }});
-            
-            if (updateResponse.ok) {{
-                console.log("[信息图 Markdown] ✅ 消息更新成功！");
-            }} else {{
-                console.error("[信息图 Markdown] API 错误:", updateResponse.status);
-            }}
-        }} else {{
-            console.warn("[信息图 Markdown] ⚠️ 缺少 chatId 或 messageId");
-        }}
-        
-    }} catch (error) {{
-        console.error("[信息图 Markdown] 错误:", error);
-    }}
-}})();
-"""
-
-    async def action(
-        self,
-        body: dict,
-        __user__: dict = None,
-        __event_emitter__=None,
-        __event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
-        __metadata__: Optional[dict] = None,
-        __request__: Request = None,
-    ) -> dict:
-        """
-        使用 AntV 生成信息图并作为 Markdown 图片嵌入。
-        """
-        logger.info("动作：信息图转 Markdown 开始")
-
-        # 获取用户信息
-        if isinstance(__user__, (list, tuple)):
-            user_language = __user__[0].get("language", "zh") if __user__ else "zh"
-            user_name = __user__[0].get("name", "用户") if __user__[0] else "用户"
-            user_id = __user__[0].get("id", "unknown_user") if __user__ else "unknown_user"
-        elif isinstance(__user__, dict):
-            user_language = __user__.get("language", "zh")
-            user_name = __user__.get("name", "用户")
-            user_id = __user__.get("id", "unknown_user")
-        else:
-            user_language = "zh"
-            user_name = "用户"
-            user_id = "unknown_user"
-
-        # 获取当前时间
-        now = datetime.now()
-        current_date_time_str = now.strftime("%Y-%m-%d %H:%M:%S")
-
-        try:
-            messages = body.get("messages", [])
-            if not messages:
-                raise ValueError("没有可用的消息。")
-
-            # 获取最近的消息
-            message_count = min(self.valves.MESSAGE_COUNT, len(messages))
-            recent_messages = messages[-message_count:]
-
-            # 聚合内容
-            aggregated_parts = []
-            for msg in recent_messages:
-                text_content = self._extract_text_content(msg.get("content"))
-                if text_content:
-                    aggregated_parts.append(text_content)
-
-            if not aggregated_parts:
-                raise ValueError("消息中未找到文本内容。")
-
-            long_text_content = "\n\n---\n\n".join(aggregated_parts)
-
-            # 移除已有的 HTML 块
-            parts = re.split(r"```html.*?```", long_text_content, flags=re.DOTALL)
-            clean_content = ""
-            for part in reversed(parts):
-                if part.strip():
-                    clean_content = part.strip()
-                    break
-
-            if not clean_content:
-                clean_content = long_text_content.strip()
-
-            # 检查最小长度
-            if len(clean_content) < self.valves.MIN_TEXT_LENGTH:
-                await self._emit_status(
-                    __event_emitter__,
-                    f"⚠️ 内容太短（{len(clean_content)} 字符），至少需要 {self.valves.MIN_TEXT_LENGTH} 字符",
-                    True,
-                )
-                return body
-
-            await self._emit_status(__event_emitter__, "📊 正在分析内容...", False)
-
-            # 通过 LLM 生成信息图语法
-            formatted_user_prompt = USER_PROMPT_GENERATE.format(
-                user_name=user_name,
-                current_date_time_str=current_date_time_str,
-                user_language=user_language,
-                long_text_content=clean_content,
-            )
-
-            target_model = self.valves.MODEL_ID or body.get("model")
-
-            llm_payload = {
-                "model": target_model,
-                "messages": [
-                    {"role": "system", "content": SYSTEM_PROMPT_INFOGRAPHIC},
-                    {"role": "user", "content": formatted_user_prompt},
-                ],
-                "stream": False,
-            }
-
-            user_obj = Users.get_user_by_id(user_id)
-            if not user_obj:
-                raise ValueError(f"无法获取用户对象：{user_id}")
-
-            await self._emit_status(__event_emitter__, "📊 AI 正在生成信息图语法...", False)
-
-            llm_response = await generate_chat_completion(__request__, llm_payload, user_obj)
-
-            if not llm_response or "choices" not in llm_response or not llm_response["choices"]:
-                raise ValueError("无效的 LLM 响应。")
-
-            assistant_content = llm_response["choices"][0]["message"]["content"]
-            infographic_syntax = self._extract_infographic_syntax(assistant_content)
-
-            logger.info(f"生成的语法：{infographic_syntax[:200]}...")
-
-            # 提取 API 回调所需的 ID
-            chat_id = self._extract_chat_id(body, __metadata__)
-            message_id = self._extract_message_id(body, __metadata__)
-            unique_id = f"ig_{int(time.time() * 1000)}"
-
-            await self._emit_status(__event_emitter__, "📊 正在渲染 SVG...", False)
-
-            # 执行 JS 进行渲染和嵌入
-            if __event_call__:
-                js_code = self._generate_js_code(
-                    unique_id=unique_id,
-                    chat_id=chat_id,
-                    message_id=message_id,
-                    infographic_syntax=infographic_syntax,
-                    svg_width=self.valves.SVG_WIDTH,
-                    export_format=self.valves.EXPORT_FORMAT,
-                )
-
-                await __event_call__(
-                    {
-                        "type": "execute",
-                        "data": {"code": js_code},
-                    }
-                )
-
-            await self._emit_status(__event_emitter__, "✅ 信息图生成完成！", True)
-            logger.info("信息图转 Markdown 完成")
-
-        except Exception as e:
-            error_message = f"信息图生成失败：{str(e)}"
-            logger.error(error_message, exc_info=True)
-            await self._emit_status(__event_emitter__, f"❌ {error_message}", True)
-
-        return body

plugins/actions/js-render-poc/js_render_poc.py

@@ -1,257 +0,0 @@
-"""
-title: JS Render PoC
-author: Fu-Jie
-version: 0.6.0
-description: Proof of concept for JS rendering + API write-back pattern. JS renders SVG and updates message via API.
-"""
-
-import time
-import json
-import logging
-from typing import Optional, Callable, Awaitable, Any
-from pydantic import BaseModel, Field
-from fastapi import Request
-
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-
-class Action:
-    class Valves(BaseModel):
-        pass
-
-    def __init__(self):
-        self.valves = self.Valves()
-
-    def _extract_chat_id(self, body: dict, metadata: Optional[dict]) -> str:
-        """Extract chat_id from body or metadata"""
-        if isinstance(body, dict):
-            # body["chat_id"] 是 chat_id
-            chat_id = body.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
-
-            body_metadata = body.get("metadata", {})
-            if isinstance(body_metadata, dict):
-                chat_id = body_metadata.get("chat_id")
-                if isinstance(chat_id, str) and chat_id.strip():
-                    return chat_id.strip()
-
-        if isinstance(metadata, dict):
-            chat_id = metadata.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
-
-        return ""
-
-    def _extract_message_id(self, body: dict, metadata: Optional[dict]) -> str:
-        """Extract message_id from body or metadata"""
-        if isinstance(body, dict):
-            # body["id"] 是 message_id
-            message_id = body.get("id")
-            if isinstance(message_id, str) and message_id.strip():
-                return message_id.strip()
-
-            body_metadata = body.get("metadata", {})
-            if isinstance(body_metadata, dict):
-                message_id = body_metadata.get("message_id")
-                if isinstance(message_id, str) and message_id.strip():
-                    return message_id.strip()
-
-        if isinstance(metadata, dict):
-            message_id = metadata.get("message_id")
-            if isinstance(message_id, str) and message_id.strip():
-                return message_id.strip()
-
-        return ""
-
-    async def action(
-        self,
-        body: dict,
-        __user__: dict = None,
-        __event_emitter__=None,
-        __event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
-        __metadata__: Optional[dict] = None,
-        __request__: Request = None,
-    ) -> dict:
-        """
-        PoC: Use __event_call__ to execute JS that renders SVG and updates message via API.
-        """
-        # 准备调试数据
-        body_for_log = {}
-        for k, v in body.items():
-            if k == "messages":
-                body_for_log[k] = f"[{len(v)} messages]"
-            else:
-                body_for_log[k] = v
-
-        body_json = json.dumps(body_for_log, ensure_ascii=False, default=str)
-        metadata_json = (
-            json.dumps(__metadata__, ensure_ascii=False, default=str)
-            if __metadata__
-            else "null"
-        )
-
-        # 转义 JSON 中的特殊字符以便嵌入 JS
-        body_json_escaped = (
-            body_json.replace("\\", "\\\\").replace("`", "\\`").replace("${", "\\${")
-        )
-        metadata_json_escaped = (
-            metadata_json.replace("\\", "\\\\")
-            .replace("`", "\\`")
-            .replace("${", "\\${")
-        )
-
-        chat_id = self._extract_chat_id(body, __metadata__)
-        message_id = self._extract_message_id(body, __metadata__)
-
-        unique_id = f"poc_{int(time.time() * 1000)}"
-
-        if __event_emitter__:
-            await __event_emitter__(
-                {
-                    "type": "status",
-                    "data": {"description": "🔄 正在渲染...", "done": False},
-                }
-            )
-
-        if __event_call__:
-            await __event_call__(
-                {
-                    "type": "execute",
-                    "data": {
-                        "code": f"""
-(async function() {{
-    const uniqueId = "{unique_id}";
-    const chatId = "{chat_id}";
-    const messageId = "{message_id}";
-    
-    // ===== DEBUG: 输出 Python 端的数据 =====
-    console.log("[JS Render PoC] ===== DEBUG INFO (from Python) =====");
-    console.log("[JS Render PoC] body:", `{body_json_escaped}`);
-    console.log("[JS Render PoC] __metadata__:", `{metadata_json_escaped}`);
-    console.log("[JS Render PoC] Extracted: chatId=", chatId, "messageId=", messageId);
-    console.log("[JS Render PoC] =========================================");
-    
-    try {{
-        console.log("[JS Render PoC] Starting SVG render...");
-        
-        // Create SVG
-        const svg = document.createElementNS("http://www.w3.org/2000/svg", "svg");
-        svg.setAttribute("width", "200");
-        svg.setAttribute("height", "200");
-        svg.setAttribute("viewBox", "0 0 200 200");
-        svg.setAttribute("xmlns", "http://www.w3.org/2000/svg");
-        
-        const defs = document.createElementNS("http://www.w3.org/2000/svg", "defs");
-        const gradient = document.createElementNS("http://www.w3.org/2000/svg", "linearGradient");
-        gradient.setAttribute("id", "grad-" + uniqueId);
-        gradient.innerHTML = `
-            <stop offset="0%" style="stop-color:#1e88e5;stop-opacity:1" />
-            <stop offset="100%" style="stop-color:#43a047;stop-opacity:1" />
-        `;
-        defs.appendChild(gradient);
-        svg.appendChild(defs);
-        
-        const circle = document.createElementNS("http://www.w3.org/2000/svg", "circle");
-        circle.setAttribute("cx", "100");
-        circle.setAttribute("cy", "100");
-        circle.setAttribute("r", "80");
-        circle.setAttribute("fill", `url(#grad-${{uniqueId}})`);
-        svg.appendChild(circle);
-        
-        const text = document.createElementNS("http://www.w3.org/2000/svg", "text");
-        text.setAttribute("x", "100");
-        text.setAttribute("y", "105");
-        text.setAttribute("text-anchor", "middle");
-        text.setAttribute("fill", "white");
-        text.setAttribute("font-size", "16");
-        text.setAttribute("font-weight", "bold");
-        text.textContent = "PoC Success!";
-        svg.appendChild(text);
-        
-        // Convert to Base64 Data URI
-        const svgData = new XMLSerializer().serializeToString(svg);
-        const base64 = btoa(unescape(encodeURIComponent(svgData)));
-        const dataUri = "data:image/svg+xml;base64," + base64;
-        
-        console.log("[JS Render PoC] SVG rendered, data URI length:", dataUri.length);
-        
-        // Call API - 完全替换方案（更稳定）
-        if (chatId && messageId) {{
-            const token = localStorage.getItem("token");
-            
-            // 1. 获取当前消息内容
-            const getResponse = await fetch(`/api/v1/chats/${{chatId}}`, {{
-                method: "GET",
-                headers: {{ "Authorization": `Bearer ${{token}}` }}
-            }});
-            
-            if (!getResponse.ok) {{
-                throw new Error("Failed to get chat data: " + getResponse.status);
-            }}
-            
-            const chatData = await getResponse.json();
-            console.log("[JS Render PoC] Got chat data");
-            
-            let originalContent = "";
-            if (chatData.chat && chatData.chat.messages) {{
-                const targetMsg = chatData.chat.messages.find(m => m.id === messageId);
-                if (targetMsg && targetMsg.content) {{
-                    originalContent = targetMsg.content;
-                    console.log("[JS Render PoC] Found original content, length:", originalContent.length);
-                }}
-            }}
-            
-            // 2. 移除已存在的 PoC 图片（如果有的话）
-            // 匹配 ![JS Render PoC 生成的 SVG](data:...) 格式
-            const pocImagePattern = /\\n*!\\[JS Render PoC[^\\]]*\\]\\(data:image\\/svg\\+xml;base64,[^)]+\\)/g;
-            let cleanedContent = originalContent.replace(pocImagePattern, "");
-            // 移除可能残留的多余空行
-            cleanedContent = cleanedContent.replace(/\\n{{3,}}/g, "\\n\\n").trim();
-            
-            if (cleanedContent !== originalContent) {{
-                console.log("[JS Render PoC] Removed existing PoC image(s)");
-            }}
-            
-            // 3. 添加新的 Markdown 图片
-            const markdownImage = `![JS Render PoC 生成的 SVG](${{dataUri}})`;
-            const newContent = cleanedContent + "\\n\\n" + markdownImage;
-            
-            // 3. 使用 chat:message 完全替换
-            const updateResponse = await fetch(`/api/v1/chats/${{chatId}}/messages/${{messageId}}/event`, {{
-                method: "POST",
-                headers: {{
-                    "Content-Type": "application/json",
-                    "Authorization": `Bearer ${{token}}`
-                }},
-                body: JSON.stringify({{
-                    type: "chat:message",
-                    data: {{ content: newContent }}
-                }})
-            }});
-            
-            if (updateResponse.ok) {{
-                console.log("[JS Render PoC] ✅ Message updated successfully!");
-            }} else {{
-                console.error("[JS Render PoC] API error:", updateResponse.status, await updateResponse.text());
-            }}
-        }} else {{
-            console.warn("[JS Render PoC] ⚠️ Missing chatId or messageId, cannot persist.");
-        }}
-        
-    }} catch (error) {{
-        console.error("[JS Render PoC] Error:", error);
-    }}
-}})();
-                        """
-                    },
-                }
-            )
-
-        if __event_emitter__:
-            await __event_emitter__(
-                {"type": "status", "data": {"description": "✅ 渲染完成", "done": True}}
-            )
-
-        return body

plugins/actions/smart-mind-map/README.md

@@ -1,14 +1,10 @@
 # Smart Mind Map - Mind Mapping Generation Plugin
 
-**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.
-
 Smart Mind Map is a powerful OpenWebUI action plugin that intelligently analyzes long-form text content and automatically generates interactive mind maps, helping users structure and visualize knowledge.
 
----
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 0.9.1 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
 
-## 🔥 What's New in v0.9.1
+## What's New in v0.9.1
 
 **New Feature: Image Output Mode**
 
@@ -18,362 +14,51 @@ Smart Mind Map is a powerful OpenWebUI action plugin that intelligently analyzes
 - **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 |
+## Key Features 🔑
 
----
+- ✅ **Intelligent Text Analysis**: Automatically identifies core themes, key concepts, and hierarchical structures.
+- ✅ **Interactive Visualization**: Generates beautiful interactive mind maps based on Markmap.js.
+- ✅ **High-Resolution PNG Export**: Export mind maps as high-quality PNG images (9x scale).
+- ✅ **Complete Control Panel**: Zoom controls, expand level selection, and fullscreen mode.
+- ✅ **Theme Switching**: Manual theme toggle button with automatic theme detection.
+- ✅ **Image Output Mode**: Generate static SVG images embedded directly in Markdown for cleaner history.
 
-## Core Features
+## How to Use 🛠️
 
-- ✅ **Intelligent Text Analysis**: Automatically identifies core themes, key concepts, and hierarchical structures
-- ✅ **Interactive Visualization**: Generates beautiful interactive mind maps based on Markmap.js
-- ✅ **High-Resolution PNG Export**: Export mind maps as high-quality PNG images (9x scale, ~1-2MB file size)
-- ✅ **Complete Control Panel**: Zoom controls (+/-/reset), expand level selection (All/2/3 levels), and fullscreen mode
-- ✅ **Theme Switching**: Manual theme toggle button (light/dark) with automatic theme detection
-- ✅ **Dark Mode Support**: Full dark mode support with automatic detection and manual override
-- ✅ **Multi-language Support**: Automatically adjusts output based on user language
-- ✅ **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)
+1. **Install**: Upload the `smart_mind_map.py` file in OpenWebUI Admin Settings -> Plugins -> Actions.
+2. **Configure**: Ensure you have an LLM model configured (e.g., `gemini-2.5-flash`).
+3. **Trigger**: Enable the "Smart Mind Map" action in chat settings and send text (at least 100 characters).
+4. **Result**: The mind map will be rendered directly in the chat interface.
 
----
-
-## How It Works
-
-1. **Text Extraction**: Extracts text content from user messages (automatically filters HTML code blocks)
-2. **Intelligent Analysis**: Analyzes text structure using the configured LLM model
-3. **Markdown Generation**: Converts analysis results to Markmap-compatible Markdown format
-4. **Visual Rendering**: Renders the mind map using Markmap.js in an HTML template with optimized font hierarchy (H1: 22px bold, H2: 18px bold)
-5. **Interactive Display**: Presents the mind map to users in an interactive format with complete control panel
-6. **Theme Detection**: Automatically detects and applies the current OpenWebUI theme (light/dark mode)
-7. **Export Options**: Provides PNG (high-resolution), SVG, and Markdown export functionality
-
----
-
-## Installation and Configuration
-
-### 1. Plugin Installation
-
-1. Download the `smart_mind_map_cn.py` file to your local computer
-2. In OpenWebUI Admin Settings, find the "Plugins" section
-3. Select "Actions" type
-4. Upload the downloaded file
-5. Refresh the page, and the plugin will be available
-
-### 2. Model Configuration
-
-The plugin requires access to an LLM model for text analysis. Please ensure:
-
-- Your OpenWebUI instance has at least one available LLM model configured
-- Recommended to use fast, economical models (e.g., `gemini-2.5-flash`) for the best experience
-- Configure the `LLM_MODEL_ID` parameter in the plugin settings
-
-### 3. Plugin Activation
-
-Select the "Smart Mind Map" action plugin in chat settings to enable it.
-
-### 4. Theme Color Consistency (Optional)
-
-To keep the mind map visually consistent with the OpenWebUI theme colors, enable same-origin access for artifacts in OpenWebUI:
-
-- **Configuration Location**: In OpenWebUI User Settings: **Interface** → **Artifacts** → **iframe Sandbox Allow Same Origin**
-- **Enable Option**: Check the "Allow same-origin access for artifacts" / "iframe sandbox allow-same-origin" option
-- **Sandbox Attributes**: Ensure the iframe's sandbox attribute includes both `allow-same-origin` and `allow-scripts`
-
-Once enabled, the mind map will automatically detect and apply the current OpenWebUI theme (light/dark) without any manual configuration.
-
----
-
-## Configuration Parameters
-
-You can adjust the following parameters in the plugin's settings (Valves):
+## Configuration (Valves) ⚙️
 
 | Parameter | Default | Description |
 | :--- | :--- | :--- |
-| `show_status` | `true` | Whether to display operation status updates in the chat interface (e.g., "Analyzing..."). |
-| `LLM_MODEL_ID` | `gemini-2.5-flash` | LLM model ID for text analysis. Recommended to use fast and economical models. |
-| `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. |
+| `show_status` | `true` | Whether to display operation status updates. |
+| `LLM_MODEL_ID` | `gemini-2.5-flash` | LLM model ID for text analysis. |
+| `MIN_TEXT_LENGTH` | `100` | Minimum text length required for analysis. |
+| `CLEAR_PREVIOUS_HTML` | `false` | Whether to clear previous plugin-generated HTML content. |
+| `MESSAGE_COUNT` | `1` | Number of recent messages to use for generation (1-5). |
+| `OUTPUT_MODE` | `html` | Output mode: `html` (interactive) or `image` (static). |
 
----
+## Troubleshooting ❓
 
-## Usage
-
-### Basic Usage
-
-1. Enable the "Smart Mind Map" action in chat settings
-2. Input or paste long-form text content (at least 100 characters) in the conversation
-3. After sending the message, the plugin will automatically analyze and generate a mind map
-4. The mind map will be rendered directly in the chat interface
-
-### Usage Example
-
-**Input Text:**
-
-```
-Artificial Intelligence (AI) is a branch of computer science dedicated to creating systems capable of performing tasks that typically require human intelligence.
-Main application areas include:
-1. Machine Learning - Enables computers to learn from data
-2. Natural Language Processing - Understanding and generating human language
-3. Computer Vision - Recognizing and processing images
-4. Robotics - Creating intelligent systems that can interact with the physical world
-```
-
-**Generated Result:**
-The plugin will generate an interactive mind map centered on "Artificial Intelligence", including major application areas and their sub-concepts.
-
-### Export Features
-
-Generated mind maps support three export methods:
-
-1. **Download PNG**: Click the "📥 Download PNG" button to export the mind map as a high-resolution PNG image (9x scale, ~1-2MB file size)
-2. **Copy SVG Code**: Click the "Copy SVG Code" button to copy the mind map in SVG format to the clipboard
-3. **Copy Markdown**: Click the "Copy Markdown" button to copy the raw Markdown format to the clipboard
-
-### Control Panel
-
-The interactive mind map includes a comprehensive control panel:
-
-- **Zoom Controls**: `+` (zoom in), `-` (zoom out), `↻` (reset view)
-- **Expand Level**: Switch between "All", "2 Levels", "3 Levels" to control node expansion depth
-- **Fullscreen**: Enter fullscreen mode for better viewing experience
-- **Theme Toggle**: Manually switch between light and dark themes
+- **Plugin not working?**: Check if the action is enabled in the chat settings.
+- **Text too short**: Ensure input text contains at least 100 characters.
+- **Rendering failed**: Check browser console for errors related to Markmap.js or D3.js.
+- **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)
 
 ---
 
 ## Technical Architecture
 
-### Frontend Rendering
-
-- **Markmap.js**: Open-source mind mapping rendering engine
-- **D3.js**: Data visualization foundation library
-- **Responsive Design**: Adapts to different screen sizes
-- **Font Hierarchy**: Optimized typography with H1 (22px bold) and H2 (18px bold) for better readability
-
-### PNG Export Technology
-
-- **SVG to Canvas Conversion**: Converts mind map SVG to canvas for PNG export
-- **ForeignObject Handling**: Properly processes HTML content within SVG elements
-- **High Resolution**: 9x scale factor for print-quality output (~1-2MB file size)
-- **Theme Preservation**: Maintains current theme (light/dark) in exported PNG
-
-### Theme Detection Mechanism
-
-Automatically detects and applies themes with a 4-level priority:
-
-1. **Explicit Toggle**: User manually clicks theme toggle button (highest priority)
-2. **Meta Tag**: Reads `<meta name="theme-color">` from parent document
-3. **Class/Data-Theme**: Checks `class` or `data-theme` attributes on parent HTML/body
-4. **System Preference**: Falls back to `prefers-color-scheme` media query
-
-### Backend Processing
-
-- **LLM Integration**: Calls configured models via `generate_chat_completion`
-- **Text Preprocessing**: Automatically filters HTML code blocks, extracts plain text content
-- **Format Conversion**: Converts LLM output to Markmap-compatible Markdown format
-
-### Security Enhancements
-
-- **XSS Protection**: Automatically escapes `</script>` tags to prevent script injection
-- **Input Validation**: Checks text length to avoid invalid requests
-- **Non-Bubbling Events**: Button clicks use `stopPropagation()` to prevent navigation interception
-
----
-
-## Troubleshooting
-
-### Issue: Plugin Won't Start
-
-**Solution:**
-
-- Check OpenWebUI logs for error messages
-- Confirm the plugin is correctly uploaded and enabled
-- Verify OpenWebUI version supports action plugins
-
-### Issue: Text Content Too Short
-
-**Symptom:** Prompt shows "Text content is too short for effective analysis"
-
-**Solution:**
-
-- Ensure input text contains at least 100 characters (default configuration)
-- Lower the `MIN_TEXT_LENGTH` parameter value in plugin settings
-- Provide more detailed, structured text content
-
-### Issue: Mind Map Not Generated
-
-**Solution:**
-
-- Check if `LLM_MODEL_ID` is configured correctly
-- Confirm the configured model is available in OpenWebUI
-- Review backend logs for LLM call failures
-- Verify user has sufficient permissions to access the configured model
-
-### Issue: Mind Map Display Error
-
-**Symptom:** Shows "⚠️ Mind map rendering failed"
-
-**Solution:**
-
-- Check browser console for error messages
-- Confirm Markmap.js and D3.js libraries are loading correctly
-- Verify generated Markdown format conforms to Markmap specifications
-- Try refreshing the page to re-render
-
-### Issue: PNG Export Not Working
-
-**Symptom:** PNG download button doesn't work or produces blank/corrupted images
-
-**Solution:**
-
-- Ensure browser supports HTML5 Canvas API (all modern browsers do)
-- Check browser console for errors related to `toDataURL()` or canvas rendering
-- Verify the mind map is fully rendered before clicking export
-- Try refreshing the page and re-generating the mind map
-- Use Chrome or Firefox for best PNG export compatibility
-
-### Issue: Theme Not Auto-Detected
-
-**Symptom:** Mind map doesn't match OpenWebUI theme colors
-
-**Solution:**
-
-- Enable "iframe Sandbox Allow Same Origin" in OpenWebUI Settings → Interface → Artifacts
-- Verify the iframe's sandbox attribute includes both `allow-same-origin` and `allow-scripts`
-- Ensure parent document has `<meta name="theme-color">` tag or theme class/attribute
-- Use the manual theme toggle button to override automatic detection
-- Check browser console for cross-origin errors
-
-### Issue: Export Function Not Working
-
-**Solution:**
-
-- Confirm browser supports Clipboard API
-- Check if browser is blocking clipboard access permissions
-- Use modern browsers (Chrome, Firefox, Edge, etc.)
-
----
+- **Markmap.js**: Open-source mind mapping rendering engine.
+- **PNG Export**: 9x scale factor for print-quality output (~1-2MB file size).
+- **Theme Detection**: 4-level priority detection (Manual > Meta > Class > System).
+- **Security**: XSS protection and input validation.
 
 ## Best Practices
 
-1. **Text Preparation**
-   - Provide text content with clear structure and distinct hierarchies
-   - Use paragraphs, lists, and other formatting to help LLM understand text structure
-   - Avoid excessively lengthy or unstructured text
-
-2. **Model Selection**
-   - For daily use, recommend fast models like `gemini-2.5-flash`
-   - For complex text analysis, use more powerful models (e.g., GPT-4)
-   - Balance speed and analysis quality based on needs
-
-3. **Performance Optimization**
-   - Set `MIN_TEXT_LENGTH` appropriately to avoid processing text that's too short
-   - For particularly long texts, consider summarizing before generating mind maps
-   - Disable `show_status` in production environments to reduce interface updates
-
-4. **Export Quality**
-   - **PNG Export**: Best for presentations, documents, and sharing (9x resolution suitable for printing)
-   - **SVG Export**: Best for further editing in vector graphics tools (infinite scalability)
-   - **Markdown Export**: Best for version control, collaboration, and regeneration
-
-5. **Theme Consistency**
-   - Enable same-origin access for automatic theme detection
-   - Use manual theme toggle if automatic detection fails
-   - Export PNG after switching to desired theme for consistent visuals
-
----
-
-## Requirements
-
-This plugin uses only OpenWebUI's built-in dependencies. **No additional packages need to be installed.**
-
----
-
-## 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
-
-### v0.8.0 (Previous Version)
-
-**Major Features:**
-
-- Added high-resolution PNG export (9x scale, ~1-2MB file size)
-- Implemented complete control panel with zoom controls (+/-/reset)
-- Added expand level selection (All/2/3 levels)
-- Integrated fullscreen mode with auto-fit
-- Added manual theme toggle button (light/dark)
-- Implemented automatic theme detection with 4-level priority
-
-**Improvements:**
-
-- Optimized font hierarchy (H1: 22px bold, H2: 18px bold)
-- Enhanced dark mode with full theme support
-- Improved PNG export technology (SVG to Canvas with foreignObject handling)
-- Added theme preservation in exported PNG images
-- Enhanced security with non-bubbling button events
-
-**Bug Fixes:**
-
-- Fixed theme detection in cross-origin iframes
-- Resolved PNG export issues with HTML content in SVG
-- Improved compatibility with OpenWebUI theme system
-
-### v0.7.2
-
-- Optimized text extraction logic, automatically filters HTML code blocks
-- Improved error handling and user feedback
-- Enhanced export functionality compatibility
-- Optimized UI styling and interactive experience
-
----
-
-## License
-
-This plugin is released under the MIT License.
-
-## Contributing
-
-Welcome to submit issue reports and improvement suggestions! Please visit the project repository: [awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
-
----
-
-## Related Resources
-
-- [Markmap Official Website](https://markmap.js.org/)
-- [OpenWebUI Documentation](https://docs.openwebui.com/)
-- [D3.js Official Website](https://d3js.org/)
+1. **Text Preparation**: Provide text with clear structure and distinct hierarchies.
+2. **Model Selection**: Use fast models like `gemini-2.5-flash` for daily use.
+3. **Export Quality**: Use PNG for presentations and SVG for further editing.

plugins/actions/smart-mind-map/README_CN.md

@@ -1,14 +1,10 @@
 # 思维导图 - 思维导图生成插件
 
-**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。
-
 思维导图是一个强大的 OpenWebUI 动作插件，能够智能分析长篇文本内容，自动生成交互式思维导图，帮助用户结构化和可视化知识。
 
----
+**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 0.9.1 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
 
-## 🔥 v0.9.1 更新亮点
+## v0.9.1 更新亮点
 
 **新功能：图片输出模式**
 
@@ -18,362 +14,51 @@
 - **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。
+- ✅ **交互式可视化**：基于 Markmap.js 生成美观的交互式思维导图。
+- ✅ **高分辨率 PNG 导出**：导出高质量的 PNG 图片（9 倍分辨率）。
+- ✅ **完整控制面板**：缩放控制、展开层级选择、全屏模式。
+- ✅ **主题切换**：手动主题切换按钮与自动主题检测。
+- ✅ **图片输出模式**：生成静态 SVG 图片直接嵌入 Markdown，聊天记录更简洁。
 
-## 核心特性
+## 使用方法 🛠️
 
-- ✅ **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
-- ✅ **交互式可视化**：基于 Markmap.js 生成美观的交互式思维导图
-- ✅ **高分辨率 PNG 导出**：导出高质量的 PNG 图片（9 倍分辨率，约 1-2MB 文件大小）
-- ✅ **完整控制面板**：缩放控制（+/-/重置）、展开层级选择（全部/2级/3级）、全屏模式
-- ✅ **主题切换**：手动主题切换按钮（亮色/暗色）与自动主题检测
-- ✅ **深色模式支持**：完整的深色模式支持，自动检测与手动覆盖
-- ✅ **多语言支持**：根据用户语言自动调整输出
-- ✅ **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）
+1. **安装**: 在 OpenWebUI 管理员设置 -> 插件 -> 动作中上传 `smart_mind_map_cn.py`。
+2. **配置**: 确保配置了 LLM 模型（如 `gemini-2.5-flash`）。
+3. **触发**: 在聊天设置中启用“思维导图”动作，并发送文本（至少 100 字符）。
+4. **结果**: 思维导图将在聊天界面中直接渲染显示。
 
----
-
-## 工作原理
-
-1. **文本提取**：从用户消息中提取文本内容（自动过滤 HTML 代码块）
-2. **智能分析**：使用配置的 LLM 模型分析文本结构
-3. **Markdown 生成**：将分析结果转换为 Markmap 兼容的 Markdown 格式
-4. **可视化渲染**：在 HTML 模板中使用 Markmap.js 渲染思维导图，并优化字体层级（H1：22px 粗体，H2：18px 粗体）
-5. **交互展示**：以可交互的形式展示给用户，并提供完整的控制面板
-6. **主题检测**：自动检测并应用当前 OpenWebUI 的主题（亮色/暗色模式）
-7. **导出选项**：提供 PNG（高分辨率）、SVG 和 Markdown 导出功能
-
----
-
-## 安装与配置
-
-### 1. 插件安装
-
-1. 下载 `smart_mind_map_cn.py` 文件到本地
-2. 在 OpenWebUI 管理员设置中找到"插件"（Plugins）部分
-3. 选择"动作"（Actions）类型
-4. 上传下载的文件
-5. 刷新页面，插件即可使用
-
-### 2. 模型配置
-
-插件需要访问 LLM 模型来分析文本。请确保：
-
-- 您的 OpenWebUI 实例中配置了至少一个可用的 LLM 模型
-- 推荐使用快速、经济的模型（如 `gemini-2.5-flash`）来获得最佳体验
-- 在插件设置中配置 `LLM_MODEL_ID` 参数
-
-### 3. 插件启用
-
-在聊天设置中选择"思维导图"动作插件即可启用。
-
-### 4. 主题颜色风格一致性（可选）
-
-为了使思维导图与 OpenWebUI 主题颜色风格保持一致，需要在 OpenWebUI 中启用 artifact 的同源访问：
-
-- **配置位置**：在 OpenWebUI 用户设置中找到"界面"→"产物"部分（Settings → Interface → Products/Artifacts）
-- **启用选项**：勾选 "iframe 沙盒允许同源访问"（Allow same-origin access for artifacts / iframe sandbox allow-same-origin）
-- **沙箱属性**：确保 iframe 的 sandbox 属性包含 `allow-same-origin` 和 `allow-scripts`
-
-启用后，思维导图会自动检测并应用 OpenWebUI 的当前主题（亮色/暗色），无需手动配置。
-
----
-
-## 配置参数
-
-您可以在插件的设置（Valves）中调整以下参数：
+## 配置参数 (Valves) ⚙️
 
 | 参数 | 默认值 | 描述 |
 | :--- | :--- | :--- |
-| `show_status` | `true` | 是否在聊天界面显示操作状态更新（如"正在分析..."）。 |
-| `LLM_MODEL_ID` | `gemini-2.5-flash` | 用于文本分析的 LLM 模型 ID。推荐使用快速且经济的模型。 |
-| `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。 |
+| `show_status` | `true` | 是否在聊天界面显示操作状态更新。 |
+| `LLM_MODEL_ID` | `gemini-2.5-flash` | 用于文本分析的 LLM 模型 ID。 |
+| `MIN_TEXT_LENGTH` | `100` | 进行思维导图分析所需的最小文本长度。 |
+| `CLEAR_PREVIOUS_HTML` | `false` | 在生成新的思维导图时，是否清除之前的 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。 |
+| `OUTPUT_MODE` | `html` | 输出模式：`html`（交互式）或 `image`（静态图片）。 |
 
----
+## 故障排除 (Troubleshooting) ❓
 
-## 使用方法
-
-### 基本使用
-
-1. 在聊天设置中启用"思维导图"动作
-2. 在对话中输入或粘贴长篇文本内容（至少 100 字符）
-3. 发送消息后，插件会自动分析并生成思维导图
-4. 思维导图将在聊天界面中直接渲染显示
-
-### 使用示例
-
-**输入文本：**
-
-```
-人工智能（AI）是计算机科学的一个分支，致力于创建能够执行通常需要人类智能的任务的系统。
-主要应用领域包括：
-1. 机器学习 - 使计算机能够从数据中学习
-2. 自然语言处理 - 理解和生成人类语言
-3. 计算机视觉 - 识别和处理图像
-4. 机器人技术 - 创建能够与物理世界交互的智能系统
-```
-
-**生成结果：**
-插件会生成一个以"人工智能"为中心主题的交互式思维导图，包含主要应用领域及其子概念。
-
-### 导出功能
-
-生成的思维导图支持三种导出方式：
-
-1. **下载 PNG**：点击“📥 下载 PNG”按钮，可将思维导图导出为高分辨率 PNG 图片（9 倍分辨率，约 1-2MB 文件大小）
-2. **复制 SVG 代码**：点击“复制 SVG 代码”按钮，可将思维导图的 SVG 格式复制到剪贴板
-3. **复制 Markdown**：点击“复制 Markdown”按钮，可将原始 Markdown 格式复制到剪贴板
-
-### 控制面板
-
-交互式思维导图包含完整的控制面板：
-
-- **缩放控制**：`+`（放大）、`-`（缩小）、`↻`（重置视图）
-- **展开层级**：在“全部”、“2 级”、“3 级”之间切换，控制节点展开深度
-- **全屏模式**：进入全屏模式，获得更好的查看体验
-- **主题切换**：手动在亮色和暗色主题之间切换
+- **插件无法启动**：检查 OpenWebUI 日志，确认插件已正确上传并启用。
+- **文本内容过短**：确保输入的文本至少包含 100 个字符。
+- **渲染失败**：检查浏览器控制台，确认 Markmap.js 和 D3.js 库是否正确加载。
+- **提交 Issue**: 如果遇到任何问题，请在 GitHub 上提交 Issue：[Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)
 
 ---
 
 ## 技术架构
 
-### 前端渲染
-
-- **Markmap.js**：开源的思维导图渲染引擎
-- **D3.js**：数据可视化基础库
-- **响应式设计**：适配不同屏幕尺寸
-- **字体层级**：优化的字体排版，H1（22px 粗体）和 H2（18px 粗体），提供更好的可读性
-
-### PNG 导出技术
-
-- **SVG 转 Canvas**：将思维导图 SVG 转换为 Canvas 以导出 PNG
-- **ForeignObject 处理**：正确处理 SVG 元素中的 HTML 内容
-- **高分辨率**：9 倍缩放因子，输出打印级质量（约 1-2MB 文件大小）
-- **主题保持**：在导出的 PNG 中保持当前主题（亮色/暗色）
-
-### 主题检测机制
-
-自动检测并应用主题，具有 4 级优先级：
-
-1. **显式切换**：用户手动点击主题切换按钮（最高优先级）
-2. **Meta 标签**：从父文档读取 `<meta name="theme-color">`
-3. **Class/Data-Theme**：检查父文档 HTML/body 的 `class` 或 `data-theme` 属性
-4. **系统偏好**：回退到 `prefers-color-scheme` 媒体查询
-
-### 后端处理
-
-- **LLM 集成**：通过 `generate_chat_completion` 调用配置的模型
-- **文本预处理**：自动过滤 HTML 代码块，提取纯文本内容
-- **格式转换**：将 LLM 输出转换为 Markmap 兼容的 Markdown 格式
-
-### 安全性增强
-
-- **XSS 防护**：自动转义 `</script>` 标签，防止脚本注入
-- **输入验证**：检查文本长度，避免无效请求
-- **非冒泡事件**：按钮点击使用 `stopPropagation()` 防止导航拦截
-
----
-
-## 故障排除
-
-### 问题：插件无法启动
-
-**解决方案：**
-
-- 检查 OpenWebUI 日志，查看是否有错误信息
-- 确认插件已正确上传并启用
-- 验证 OpenWebUI 版本是否支持动作插件
-
-### 问题：文本内容过短
-
-**现象：** 提示"文本内容过短，无法进行有效分析"
-
-**解决方案：**
-
-- 确保输入的文本至少包含 100 个字符（默认配置）
-- 可以在插件设置中降低 `MIN_TEXT_LENGTH` 参数值
-- 提供更详细、结构化的文本内容
-
-### 问题：思维导图未生成
-
-**解决方案：**
-
-- 检查 `LLM_MODEL_ID` 是否配置正确
-- 确认配置的模型在 OpenWebUI 中可用
-- 查看后端日志，检查是否有 LLM 调用失败的错误
-- 验证用户是否有足够的权限访问配置的模型
-
-### 问题：思维导图显示错误
-
-**现象：** 显示"⚠️ 思维导图渲染失败"
-
-**解决方案：**
-
-- 检查浏览器控制台的错误信息
-- 确认 Markmap.js 和 D3.js 库是否正确加载
-- 验证生成的 Markdown 格式是否符合 Markmap 规范
-- 尝试刷新页面重新渲染
-
-### 问题：PNG 导出不工作
-
-**现象：**PNG 下载按钮不工作或生成空白/损坏的图片
-
-**解决方案：**
-
-- 确保浏览器支持 HTML5 Canvas API（所有现代浏览器都支持）
-- 检查浏览器控制台是否有与 `toDataURL()` 或 Canvas 渲染相关的错误
-- 确保思维导图在点击导出前已完全渲染
-- 尝试刷新页面并重新生成思维导图
-- 使用 Chrome 或 Firefox，获得最佳 PNG 导出兼容性
-
-### 问题：主题未自动检测
-
-**现象：**思维导图不匹配 OpenWebUI 主题颜色
-
-**解决方案：**
-
-- 在 OpenWebUI 设置 → 界面 → 产物中，启用“iframe 沙盒允许同源访问”
-- 验证 iframe 的 sandbox 属性包含 `allow-same-origin` 和 `allow-scripts`
-- 确保父文档有 `<meta name="theme-color">` 标签或主题 class/属性
-- 使用手动主题切换按钮覆盖自动检测
-- 检查浏览器控制台是否有跨域错误
-
-### 问题：导出功能不工作
-
-**解决方案：**
-
-- 确认浏览器支持剪贴板 API
-- 检查浏览器是否阻止了剪贴板访问权限
-- 使用现代浏览器（Chrome、Firefox、Edge 等）
-
----
+- **Markmap.js**：开源的思维导图渲染引擎。
+- **PNG 导出技术**：9 倍缩放因子，输出打印级质量。
+- **主题检测机制**：4 级优先级检测（手动 > Meta > Class > 系统）。
+- **安全性增强**：XSS 防护与输入验证。
 
 ## 最佳实践
 
-1. **文本准备**
-   - 提供结构清晰、层次分明的文本内容
-   - 使用段落、列表等格式帮助 LLM 理解文本结构
-   - 避免过于冗长或无结构的文本
-
-2. **模型选择**
-   - 对于日常使用，推荐 `gemini-2.5-flash` 等快速模型
-   - 对于复杂文本分析，可以使用更强大的模型（如 GPT-4）
-   - 根据需求平衡速度和分析质量
-
-3. **性能优化**
-   - 合理设置 `MIN_TEXT_LENGTH`，避免处理过短的文本
-   - 对于特别长的文本，考虑先进行摘要再生成思维导图
-   - 在生产环境中关闭 `show_status` 以减少界面更新
-
-4. **导出质量**
-   - **PNG 导出**：最适合演示、文档和分享（9 倍分辨率适合打印）
-   - **SVG 导出**：最适合在矢量图形工具中进一步编辑（无限缩放）
-   - **Markdown 导出**：最适合版本控制、协作和重新生成
-
-5. **主题一致性**
-   - 启用同源访问以实现自动主题检测
-   - 如果自动检测失败，使用手动主题切换
-   - 在切换到所需主题后导出 PNG，以保持视觉一致性
-
----
-
-## 依赖要求
-
-本插件仅使用 OpenWebUI 的内置依赖，**无需安装额外的软件包。**
-
----
-
-## 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
-
-### v0.8.0 (Previous Version)
-
-**主要功能：**
-
-- 添加高分辨率 PNG 导出（9 倍分辨率，约 1-2MB 文件大小）
-- 实现完整的控制面板，包含缩放控制（+/-/重置）
-- 添加展开层级选择（全部/2级/3级）
-- 集成全屏模式，自动适应
-- 添加手动主题切换按钮（亮色/暗色）
-- 实现 4 级优先级的自动主题检测
-
-**改进项：**
-
-- 优化字体层级（H1：22px 粗体，H2：18px 粗体）
-- 增强深色模式，完整的主题支持
-- 改进 PNG 导出技术（SVG 转 Canvas，处理 foreignObject）
-- 在导出的 PNG 图片中保持主题
-- 增强安全性，按钮事件使用非冒泡机制
-
-**Bug 修复：**
-
-- 修复跨域 iframe 中的主题检测问题
-- 解决 SVG 中 HTML 内容的 PNG 导出问题
-- 改进与 OpenWebUI 主题系统的兼容性
-
-### v0.7.2
-
-- 优化文本提取逻辑，自动过滤 HTML 代码块
-- 改进错误处理和用户反馈
-- 增强导出功能的兼容性
-- 优化 UI 样式和交互体验
-
----
-
-## 许可证
-
-本插件采用 MIT 许可证发布。
-
-## 贡献
-
-欢迎提交问题报告和改进建议！请访问项目仓库：[awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
-
----
-
-## 相关资源
-
-- [Markmap 官方网站](https://markmap.js.org/)
-- [OpenWebUI 文档](https://docs.openwebui.com/)
-- [D3.js 官方网站](https://d3js.org/)
+1. **文本准备**：提供结构清晰、层次分明的文本内容。
+2. **模型选择**：日常使用推荐 `gemini-2.5-flash` 等快速模型。
+3. **导出质量**：PNG 适合演示分享，SVG 适合进一步矢量编辑。

plugins/actions/smart-mind-map/smart_mind_map.py

@@ -1,7 +1,8 @@
 """
 title: Smart Mind Map
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 funding_url: https://github.com/Fu-Jie/awesome-openwebui
 version: 0.9.1
 openwebui_id: 3094c59a-b4dd-4e0c-9449-15e2dd547dc4
@@ -49,6 +50,8 @@ Please strictly follow these guidelines:
     ```
 """
 
+import json
+
 USER_PROMPT_GENERATE_MINDMAP = """
 Please analyze the following long-form text and structure its core themes, key concepts, branches, and sub-branches into standard Markdown list syntax for Markmap.js rendering.
 
@@ -791,6 +794,10 @@ class Action:
             default="html",
             description="Output mode: 'html' for interactive HTML (default), or 'image' to embed as Markdown image.",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="Whether to print debug logs in the browser console.",
+        )
 
     def __init__(self):
         self.valves = self.Valves()
@@ -819,45 +826,41 @@ 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"""
+    def _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        Unified extraction of chat context information (chat_id, message_id).
+        Prioritizes extraction from body, then metadata.
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. Try to get from body
         if isinstance(body, dict):
-            chat_id = body.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id is usually 'id' in body
 
-            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()
+            # Check body.metadata as fallback
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
 
-        if isinstance(metadata, dict):
-            chat_id = metadata.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+        # 2. Try to get from __metadata__ (as supplement)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
 
-        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 ""
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
 
     def _extract_markdown_syntax(self, llm_output: str) -> str:
         match = re.search(r"```markdown\s*(.*?)\s*```", llm_output, re.DOTALL)
@@ -884,6 +887,42 @@ class Action:
                 {"type": "notification", "data": {"type": ntype, "content": content}}
             )
 
+    async def _emit_debug_log(self, emitter, title: str, data: dict):
+        """Print structured debug logs in the browser console"""
+        if not self.valves.SHOW_DEBUG_LOG or not emitter:
+            return
+
+        try:
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
+    async def _emit_debug_log(self, emitter, title: str, data: dict):
+        """Print structured debug logs in the browser console"""
+        if not self.valves.SHOW_DEBUG_LOG or not emitter:
+            return
+
+        try:
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
     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]*?```"
@@ -1515,8 +1554,9 @@ class Action:
             # 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__)
+                chat_ctx = self._get_chat_context(body, __metadata__)
+                chat_id = chat_ctx["chat_id"]
+                message_id = chat_ctx["message_id"]
 
                 await self._emit_status(
                     __event_emitter__,

plugins/actions/smart-mind-map/smart_mind_map_cn.py

@@ -1,8 +1,8 @@
 """
 title: 思维导图
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie
-funding_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/awesome-openwebui
+funding_url: https://github.com/open-webui
 version: 0.9.1
 openwebui_id: 8d4b097b-219b-4dd2-b509-05fbe6388335
 icon_url: data:image/svg+xml;base64,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
@@ -49,6 +49,8 @@ SYSTEM_PROMPT_MINDMAP_ASSISTANT = """
     ```
 """
 
+import json
+
 USER_PROMPT_GENERATE_MINDMAP = """
 请分析以下长篇文本,并将其核心主题、关键概念、分支和子分支结构化为标准的Markdown列表语法,以供Markmap.js渲染。
 
@@ -790,6 +792,10 @@ class Action:
             default="html",
             description="输出模式: 'html' 为交互式HTML(默认),'image' 为嵌入Markdown图片。",
         )
+        SHOW_DEBUG_LOG: bool = Field(
+            default=False,
+            description="是否在浏览器控制台打印调试日志。",
+        )
 
     def __init__(self):
         self.valves = self.Valves()
@@ -818,45 +824,41 @@ 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"""
+    def _get_chat_context(
+        self, body: dict, __metadata__: Optional[dict] = None
+    ) -> Dict[str, str]:
+        """
+        统一提取聊天上下文信息 (chat_id, message_id)。
+        优先从 body 中提取，其次从 metadata 中提取。
+        """
+        chat_id = ""
+        message_id = ""
+
+        # 1. 尝试从 body 获取
         if isinstance(body, dict):
-            chat_id = body.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+            chat_id = body.get("chat_id", "")
+            message_id = body.get("id", "")  # message_id 在 body 中通常是 id
 
-            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()
+            # 再次检查 body.metadata
+            if not chat_id or not message_id:
+                body_metadata = body.get("metadata", {})
+                if isinstance(body_metadata, dict):
+                    if not chat_id:
+                        chat_id = body_metadata.get("chat_id", "")
+                    if not message_id:
+                        message_id = body_metadata.get("message_id", "")
 
-        if isinstance(metadata, dict):
-            chat_id = metadata.get("chat_id")
-            if isinstance(chat_id, str) and chat_id.strip():
-                return chat_id.strip()
+        # 2. 尝试从 __metadata__ 获取 (作为补充)
+        if __metadata__ and isinstance(__metadata__, dict):
+            if not chat_id:
+                chat_id = __metadata__.get("chat_id", "")
+            if not message_id:
+                message_id = __metadata__.get("message_id", "")
 
-        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 ""
+        return {
+            "chat_id": str(chat_id).strip(),
+            "message_id": str(message_id).strip(),
+        }
 
     def _extract_markdown_syntax(self, llm_output: str) -> str:
         match = re.search(r"```markdown\s*(.*?)\s*```", llm_output, re.DOTALL)
@@ -881,6 +883,24 @@ class Action:
                 {"type": "notification", "data": {"type": ntype, "content": content}}
             )
 
+    async def _emit_debug_log(self, 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 emitter:
+            return
+
+        try:
+            js_code = f"""
+                (async function() {{
+                    console.group("🛠️ {title}");
+                    console.log({json.dumps(data, ensure_ascii=False)});
+                    console.groupEnd();
+                }})();
+            """
+
+            await emitter({"type": "execute", "data": {"code": js_code}})
+        except Exception as e:
+            print(f"Error emitting debug log: {e}")
+
     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]*?```"
@@ -1508,8 +1528,9 @@ class Action:
             # 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__)
+                chat_ctx = self._get_chat_context(body, __metadata__)
+                chat_id = chat_ctx["chat_id"]
+                message_id = chat_ctx["message_id"]
 
                 await self._emit_status(
                     __event_emitter__,

plugins/actions/summary/README.md

@@ -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

plugins/actions/summary/README_CN.md

@@ -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

plugins/actions/summary/summary.py

@@ -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>&copy; {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

plugins/actions/summary/summary_cn.py

@@ -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>&copy; {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

plugins/filters/README.md

@@ -48,7 +48,3 @@ When adding a new filter, please follow these steps:
 
 Fu-Jie
 GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
-
-## License
-
-MIT License

plugins/filters/README_CN.md

@@ -70,7 +70,3 @@
 
 Fu-Jie
 GitHub: [Fu-Jie/awesome-openwebui](https://github.com/Fu-Jie/awesome-openwebui)
-
-## 许可证
-
-MIT License

plugins/filters/async-context-compression/README.md

@@ -1,15 +1,26 @@
 # Async Context Compression Filter
 
-**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 1.1.0 | **License:** MIT
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 1.1.3 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
 
 This filter reduces token consumption in long conversations through intelligent summarization and message compression while keeping conversations coherent.
 
-## What's new in 1.1.0 
+## What's new in 1.1.3
+- **Improved Compatibility**: Changed summary injection role from `user` to `assistant` for better compatibility across different LLMs.
+- **Enhanced Stability**: Fixed a race condition in state management that could cause "inlet state not found" warnings in high-concurrency scenarios.
+- **Bug Fixes**: Corrected default model handling to prevent misleading logs when no model is specified.
+
+## What's new in 1.1.2
+
+- **Open WebUI v0.7.x Compatibility**: Resolved a critical database session binding error affecting Open WebUI v0.7.x users. The plugin now dynamically discovers the database engine and session context, ensuring compatibility across versions.
+- **Enhanced Error Reporting**: Errors during background summary generation are now reported via both the status bar and browser console.
+- **Robust Model Handling**: Improved handling of missing or invalid model IDs to prevent crashes.
+
+## What's new in 1.1.1
+
+- **Frontend Debugging**: Added `show_debug_log` option to print debug info to the browser console (F12).
+- **Optimized Compression**: Improved token calculation logic to prevent aggressive truncation of history, ensuring more context is retained.
+
 
-- Reuses Open WebUI's shared database connection by default (no custom engine or env vars required).
-- Token-based thresholds (`compression_threshold_tokens`, `max_context_tokens`) for safer long-context handling.
-- Per-model overrides via `model_thresholds` for mixed-model workflows.
-- Documentation now mirrors the latest async workflow and retention-first injection.
 
 ---
 
@@ -54,12 +65,10 @@ It is recommended to keep this filter early in the chain so it runs before filte
 | `summary_temperature`          | `0.3`    | Randomness for summary generation. Lower is more deterministic.                                                                                                       |
 | `model_thresholds`             | `{}`     | Per-model overrides for `compression_threshold_tokens` and `max_context_tokens` (useful for mixed models).                                                            |
 | `debug_mode`                   | `true`   | Log verbose debug info. Set to `false` in production.                                                                                                                 |
+| `show_debug_log`               | `false`  | Print debug logs to browser console (F12). Useful for frontend debugging.                                                                                             |
 
 ---
 
-## Troubleshooting
-
-- **Database table not created**: Ensure Open WebUI is configured with a database and check Open WebUI logs for errors.
-- **Summary not generated**: Confirm `compression_threshold_tokens` was hit and `summary_model` is compatible. Review logs for details.
 - **Initial system prompt is lost**: Keep `keep_first` greater than 0 to protect the initial message.
 - **Compression effect is weak**: Raise `compression_threshold_tokens` or lower `keep_first` / `keep_last` to allow more aggressive compression.
+- **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)

plugins/filters/async-context-compression/README_CN.md

@@ -1,17 +1,28 @@
 # 异步上下文压缩过滤器
 
-**作者:** [Fu-Jie](https://github.com/Fu-Jie) | **版本:** 1.2.0 | **许可证:** MIT
+**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 1.1.3 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
 
 > **重要提示**：为了确保所有过滤器的可维护性和易用性，每个过滤器都应附带清晰、完整的文档，以确保其功能、配置和使用方法得到充分说明。
 
 本过滤器通过智能摘要和消息压缩技术，在保持对话连贯性的同时，显著降低长对话的 Token 消耗。
 
-## 1.1.0 版本更新
+## 1.1.3 版本更新
+- **兼容性提升**: 将摘要注入角色从 `user` 改为 `assistant`，以提高在不同 LLM 之间的兼容性。
+- **稳定性增强**: 修复了状态管理中的竞态条件，解决了高并发场景下可能出现的“无法获取 inlet 状态”警告。
+- **Bug 修复**: 修正了默认模型处理逻辑，防止在未指定模型时产生误导性日志。
+
+## 1.1.2 版本更新
+
+- **Open WebUI v0.7.x 兼容性**: 修复了影响 Open WebUI v0.7.x 用户的严重数据库会话绑定错误。插件现在动态发现数据库引擎和会话上下文，确保跨版本兼容性。
+- **增强错误报告**: 后台摘要生成过程中的错误现在会通过状态栏和浏览器控制台同时报告。
+- **健壮的模型处理**: 改进了对缺失或无效模型 ID 的处理，防止程序崩溃。
+
+## 1.1.1 版本更新
+
+- **前端调试**: 新增 `show_debug_log` 选项，支持在浏览器控制台 (F12) 打印调试信息。
+- **压缩优化**: 优化 Token 计算逻辑，防止历史记录被过度截断，保留更多上下文。
+
 
-- 默认复用 OpenWebUI 内置数据库连接，无需自建引擎、无需配置 `DATABASE_URL`。
-- 基于 Token 的阈值控制（`compression_threshold_tokens`、`max_context_tokens`），长上下文更安全。
-- 支持 `model_thresholds` 为不同模型设置专属阈值，适合混用多模型场景。
-- 文档同步最新异步工作流与“先保留再注入”策略。
 
 ---
 
@@ -94,11 +105,13 @@
 - **默认值**: `true`
 - **描述**: 是否在 Open WebUI 的控制台日志中打印详细的调试信息（如 Token 计数、压缩进度、数据库操作等）。生产环境建议设为 `false`。
 
+#### `show_debug_log`
+
+- **默认值**: `false`
+- **描述**: 是否在浏览器控制台 (F12) 打印调试日志。便于前端调试。
+
 ---
 
-## 故障排除
-
-- **数据库表未创建**：确保 Open WebUI 已配置数据库，并查看日志获取错误信息。
-- **摘要未生成**：检查是否达到 `compression_threshold_tokens`，确认 `summary_model` 可用，并查看日志。
 - **初始系统提示丢失**：将 `keep_first` 设置为大于 0。
 - **压缩效果不明显**：提高 `compression_threshold_tokens`，或降低 `keep_first` / `keep_last` 以增强压缩力度。
+- **提交 Issue**: 如果遇到任何问题，请在 GitHub 上提交 Issue：[Awesome OpenWebUI Issues](https://github.com/Fu-Jie/awesome-openwebui/issues)