Compare commits
22 Commits
github-cop
...
v2026.03.2
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@@ -133,6 +133,7 @@ Must update ALL of these or the PR check fails:
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||||
2. **Supported Languages**: en-US, zh-CN, zh-HK, zh-TW, ko-KR, ja-JP, fr-FR, de-DE, es-ES, it-IT, vi-VN, id-ID.
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||||
3. **Fallback Map**: Must include variant redirects (e.g., `es-MX` -> `es-ES`, `fr-CA` -> `fr-FR`).
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||||
4. **Tooltips**: All `description` fields in `Valves` must be **English only** to maintain clean UI.
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||||
5. **Language Consistency**: All authored system prompts and templates MUST enforce that the Agent response language matches the exact same language as the user's input content (e.g., if concept/task input is in Chinese, provide response in Chinese).
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||||
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||||
---
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||||
|
||||
@@ -148,6 +149,10 @@ type(scope): brief English description
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||||
Types: `feat` / `fix` / `docs` / `refactor` / `chore`
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||||
Scope: plugin folder name (e.g., `github-copilot-sdk`)
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||||
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||||
> [!IMPORTANT]
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||||
> **Issue Association**:
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||||
> If the changes are related to or fix a GitHub Issue/PR, **MUST** explicitly link and associate it in both Release Notes docs (`v1.x.md`) and Commit Messages Body/Footers (e.g. `(fixes #123)`). Sync those references on GitHub Releases Page bodies when publishing.
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||||
|
||||
---
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||||
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||||
## Full Reference
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||||
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||||
20
README.md
20
README.md
@@ -23,12 +23,12 @@ A collection of enhancements, plugins, and prompts for [open-webui](https://gith
|
||||
### 🔥 Top 6 Popular Plugins
|
||||
| Rank | Plugin | Version | Downloads | Views | 📅 Updated |
|
||||
| :---: | :--- | :---: | :---: | :---: | :---: |
|
||||
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) |  |  |  |  |
|
||||
| 🥈 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) |  |  |  |  |
|
||||
| 🥉 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) |  |  |  |  |
|
||||
| 4️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) |  |  |  |  |
|
||||
| 5️⃣ | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) |  |  |  |  |
|
||||
| 6️⃣ | [AI Task Instruction Generator](https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37) |  |  |  |  |
|
||||
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) |  |  |  |  |
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||||
| 🥈 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) |  |  |  |  |
|
||||
| 🥉 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) |  |  |  |  |
|
||||
| 4️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) |  |  |  |  |
|
||||
| 5️⃣ | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) |  |  |  |  |
|
||||
| 6️⃣ | [AI Task Instruction Generator](https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37) |  |  |  |  |
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||||
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||||
### 📈 Total Downloads Trend
|
||||
|
||||
@@ -80,10 +80,14 @@ A collection of enhancements, plugins, and prompts for [open-webui](https://gith
|
||||
|
||||
**Experience interactive thinking.** Seamlessly transforms complex chat sessions into structured, clickable mind maps for better visual modeling and rapid idea extraction.
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||||
|
||||
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||||
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||||
### 3. [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f)
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||||
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||||
**Professional data storytelling.** Converts raw information into sleek, boardroom-ready infographics powered by AntV, perfect for summarizing long-form content instantly.
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||||
|
||||
|
||||
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||||
### 4. [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315)
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||||
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||||
**High-fidelity reporting.** Export conversation history into professionally formatted Word documents with preserved headers, code blocks, and math formulas.
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||||
@@ -137,7 +141,7 @@ Located in the `plugins/` directory, containing Python-based enhancements:
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||||
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||||
### Pipelines
|
||||
|
||||
- **MoE Prompt Refiner** (`moe_prompt_refiner`): Refines prompts for Mixture of Experts (MoE) summary requests to generate high-quality comprehensive reports.
|
||||
- **Wisdom Synthesizer** (`wisdom_synthesizer`): An external pipeline filter that refactors aggregate requests with collective wisdom to output structured expert reports.
|
||||
|
||||
</details>
|
||||
<!-- markdownlint-enable MD033 -->
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||||
@@ -161,6 +165,8 @@ Standalone frontend extensions to supercharge your Open WebUI:
|
||||
|
||||
[](https://openwebui.com/blog/newsletter-january-28-2026): An all-in-one prompt management suite featuring AI-powered prompt generation, spotlight-style quick search, and advanced category organization.
|
||||
|
||||
|
||||
|
||||
## 📖 Documentation
|
||||
|
||||
Located in the `docs/en/` directory:
|
||||
|
||||
20
README_CN.md
20
README_CN.md
@@ -20,12 +20,12 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
|
||||
### 🔥 热门插件 Top 6
|
||||
| 排名 | 插件 | 版本 | 下载 | 浏览 | 📅 更新 |
|
||||
| :---: | :--- | :---: | :---: | :---: | :---: |
|
||||
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) |  |  |  |  |
|
||||
| 🥈 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) |  |  |  |  |
|
||||
| 🥉 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) |  |  |  |  |
|
||||
| 4️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) |  |  |  |  |
|
||||
| 5️⃣ | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) |  |  |  |  |
|
||||
| 6️⃣ | [AI Task Instruction Generator](https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37) |  |  |  |  |
|
||||
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) |  |  |  |  |
|
||||
| 🥈 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) |  |  |  |  |
|
||||
| 🥉 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) |  |  |  |  |
|
||||
| 4️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) |  |  |  |  |
|
||||
| 5️⃣ | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) |  |  |  |  |
|
||||
| 6️⃣ | [AI Task Instruction Generator](https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37) |  |  |  |  |
|
||||
|
||||
### 📈 总下载量累计趋势
|
||||
|
||||
@@ -75,10 +75,14 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
|
||||
|
||||
**体验浸入式思维。** 将复杂的对话瞬间转化为结构化、可点击的交互式思维导图，助力知识建模与逻辑提取。
|
||||
|
||||
|
||||
|
||||
### 3. [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) [](https://openwebui.com/posts/smart_infographic_ad6f0c7f)
|
||||
|
||||
**专业数据叙事。** 将零散信息转化为精美的信息图表（由 AntV 驱动），一键生成学术/汇报级的可视化总结。
|
||||
|
||||
|
||||
|
||||
### 4. [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) [](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315)
|
||||
|
||||
**高保真文档导出。** 将对话历史导出为格式完美的 Word 文档，完美保留标题、代码块、LaTeX 公式及 Mermaid 流程图。
|
||||
@@ -132,7 +136,7 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
|
||||
|
||||
### Pipelines (工作流管道)
|
||||
|
||||
- **MoE Prompt Refiner** (`moe_prompt_refiner`): 优化多模型 (MoE) 汇总请求的提示词，生成高质量的综合报告。
|
||||
- **Wisdom Synthesizer** (`wisdom_synthesizer`): 智能拦截并重塑多模型汇总请求，发挥集体智慧（Collective Wisdom），将常规汇总熔炼为专家级对比报告。
|
||||
|
||||
</details>
|
||||
<!-- markdownlint-enable MD033 -->
|
||||
@@ -154,6 +158,8 @@ Open WebUI 的前端增强扩展：
|
||||
|
||||
- **[Open WebUI Prompt Plus](https://github.com/Fu-Jie/open-webui-prompt-plus)** [](https://openwebui.com/blog/newsletter-january-28-2026)：一站式提示词管理套件，支持 AI 提示词生成、Spotlight 风格快速搜索及高级分类管理。
|
||||
|
||||
|
||||
|
||||
## 📖 开发文档
|
||||
|
||||
<!-- markdownlint-disable MD033 -->
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
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"schemaVersion": 1,
|
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"label": "contributions",
|
||||
"message": "21",
|
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"message": "22",
|
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"color": "green"
|
||||
}
|
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@@ -1,7 +1,7 @@
|
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{
|
||||
"schemaVersion": 1,
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"label": "downloads",
|
||||
"message": "10.2k",
|
||||
"message": "10.9k",
|
||||
"color": "blue",
|
||||
"namedLogo": "openwebui"
|
||||
}
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"schemaVersion": 1,
|
||||
"label": "followers",
|
||||
"message": "396",
|
||||
"message": "422",
|
||||
"color": "blue"
|
||||
}
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"schemaVersion": 1,
|
||||
"label": "plugins",
|
||||
"message": "28",
|
||||
"message": "30",
|
||||
"color": "green"
|
||||
}
|
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@@ -1,6 +1,6 @@
|
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{
|
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"schemaVersion": 1,
|
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"label": "points",
|
||||
"message": "398",
|
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"message": "408",
|
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"color": "orange"
|
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}
|
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@@ -1,6 +1,6 @@
|
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{
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"schemaVersion": 1,
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"label": "saves",
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@@ -1,6 +1,6 @@
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{
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"schemaVersion": 1,
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"label": "upvotes",
|
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"message": "340",
|
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"message": "350",
|
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"color": "brightgreen"
|
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}
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@@ -1,6 +1,6 @@
|
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{
|
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"schemaVersion": 1,
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"label": "views",
|
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"message": "109.4k",
|
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"message": "117.2k",
|
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"color": "blueviolet"
|
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}
|
||||
@@ -1,18 +1,18 @@
|
||||
{
|
||||
"total_posts": 28,
|
||||
"total_downloads": 10214,
|
||||
"total_views": 109390,
|
||||
"total_upvotes": 340,
|
||||
"total_posts": 30,
|
||||
"total_downloads": 10862,
|
||||
"total_views": 117161,
|
||||
"total_upvotes": 350,
|
||||
"total_downvotes": 16,
|
||||
"total_saves": 449,
|
||||
"total_comments": 84,
|
||||
"plugin_contributions": 21,
|
||||
"total_saves": 468,
|
||||
"total_comments": 98,
|
||||
"plugin_contributions": 22,
|
||||
"by_type": {
|
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"pipe": 1,
|
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"tool": 3,
|
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"action": 12,
|
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"filter": 4,
|
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"prompt": 1
|
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"prompt": 2,
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"pipe": 1,
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"filter": 4
|
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},
|
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"posts": [
|
||||
{
|
||||
@@ -22,31 +22,31 @@
|
||||
"version": "1.0.0",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Intelligently analyzes text content and generates interactive mind maps to help users structure and visualize knowledge.",
|
||||
"downloads": 1969,
|
||||
"views": 17206,
|
||||
"upvotes": 34,
|
||||
"saves": 79,
|
||||
"downloads": 2054,
|
||||
"views": 18204,
|
||||
"upvotes": 35,
|
||||
"saves": 82,
|
||||
"comments": 23,
|
||||
"is_published_plugin": true,
|
||||
"created_at": "2025-12-30",
|
||||
"updated_at": "2026-03-16",
|
||||
"updated_at": "2026-03-22",
|
||||
"url": "https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a"
|
||||
},
|
||||
{
|
||||
"title": "Smart Infographic",
|
||||
"slug": "smart_infographic_ad6f0c7f",
|
||||
"type": "action",
|
||||
"version": "1.5.0",
|
||||
"version": "1.6.1",
|
||||
"author": "Fu-Jie",
|
||||
"description": "AI-powered infographic generator based on AntV Infographic. Supports professional templates, auto-icon matching, and SVG/PNG downloads.",
|
||||
"downloads": 1470,
|
||||
"views": 14788,
|
||||
"upvotes": 29,
|
||||
"saves": 58,
|
||||
"downloads": 1528,
|
||||
"views": 15541,
|
||||
"upvotes": 30,
|
||||
"saves": 60,
|
||||
"comments": 12,
|
||||
"is_published_plugin": true,
|
||||
"created_at": "2025-12-28",
|
||||
"updated_at": "2026-03-16",
|
||||
"updated_at": "2026-03-23",
|
||||
"url": "https://openwebui.com/posts/smart_infographic_ad6f0c7f"
|
||||
},
|
||||
{
|
||||
@@ -56,14 +56,14 @@
|
||||
"version": "1.2.8",
|
||||
"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. Including LaTeX command protection.",
|
||||
"downloads": 928,
|
||||
"views": 9494,
|
||||
"upvotes": 25,
|
||||
"downloads": 978,
|
||||
"views": 10009,
|
||||
"upvotes": 27,
|
||||
"saves": 52,
|
||||
"comments": 6,
|
||||
"is_published_plugin": true,
|
||||
"created_at": "2026-01-12",
|
||||
"updated_at": "2026-03-16",
|
||||
"updated_at": "2026-03-22",
|
||||
"url": "https://openwebui.com/posts/markdown_normalizer_baaa8732"
|
||||
},
|
||||
{
|
||||
@@ -73,14 +73,14 @@
|
||||
"version": "1.5.0",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Reduces token consumption in long conversations while maintaining coherence through intelligent summarization and message compression.",
|
||||
"downloads": 889,
|
||||
"views": 8096,
|
||||
"upvotes": 21,
|
||||
"saves": 56,
|
||||
"downloads": 952,
|
||||
"views": 8693,
|
||||
"upvotes": 22,
|
||||
"saves": 57,
|
||||
"comments": 0,
|
||||
"is_published_plugin": true,
|
||||
"created_at": "2025-11-08",
|
||||
"updated_at": "2026-03-16",
|
||||
"updated_at": "2026-03-22",
|
||||
"url": "https://openwebui.com/posts/async_context_compression_b1655bc8"
|
||||
},
|
||||
{
|
||||
@@ -90,14 +90,14 @@
|
||||
"version": "0.4.4",
|
||||
"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": 880,
|
||||
"views": 6908,
|
||||
"upvotes": 21,
|
||||
"saves": 42,
|
||||
"comments": 5,
|
||||
"downloads": 935,
|
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"views": 7345,
|
||||
"upvotes": 22,
|
||||
"saves": 41,
|
||||
"comments": 8,
|
||||
"is_published_plugin": true,
|
||||
"created_at": "2026-01-03",
|
||||
"updated_at": "2026-03-16",
|
||||
"updated_at": "2026-03-22",
|
||||
"url": "https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315"
|
||||
},
|
||||
{
|
||||
@@ -107,33 +107,16 @@
|
||||
"version": "",
|
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"author": "",
|
||||
"description": "",
|
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"downloads": 805,
|
||||
"views": 8931,
|
||||
"downloads": 867,
|
||||
"views": 9569,
|
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"upvotes": 11,
|
||||
"saves": 26,
|
||||
"saves": 28,
|
||||
"comments": 0,
|
||||
"is_published_plugin": true,
|
||||
"created_at": "2026-01-28",
|
||||
"updated_at": "2026-01-28",
|
||||
"updated_at": "2026-03-22",
|
||||
"url": "https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37"
|
||||
},
|
||||
{
|
||||
"title": "Export to Excel",
|
||||
"slug": "export_mulit_table_to_excel_244b8f9d",
|
||||
"type": "action",
|
||||
"version": "0.3.7",
|
||||
"author": "Fu-Jie",
|
||||
"description": "Extracts tables from chat messages and exports them to Excel (.xlsx) files with smart formatting.",
|
||||
"downloads": 657,
|
||||
"views": 3933,
|
||||
"upvotes": 13,
|
||||
"saves": 13,
|
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"is_published_plugin": true,
|
||||
"created_at": "2025-12-30",
|
||||
"updated_at": "2026-03-15",
|
||||
"updated_at": "2026-03-22",
|
||||
"url": "https://openwebui.com/posts/闪记卡生成插件_4a31eac3"
|
||||
},
|
||||
{
|
||||
"title": "Batch Install Plugins from GitHub",
|
||||
"slug": "batch_install_plugins_install_popular_plugins_in_s_c9fd6e80",
|
||||
"type": "action",
|
||||
"version": "1.1.0",
|
||||
"author": "Fu-Jie",
|
||||
"description": "One-click batch install plugins from GitHub repositories to your OpenWebUI instance.",
|
||||
"downloads": 25,
|
||||
"views": 697,
|
||||
"upvotes": 4,
|
||||
"saves": 3,
|
||||
"comments": 2,
|
||||
"title": "🔍 One-Sentence Concept Explainer",
|
||||
"slug": "one_sentence_concept_explainer_79be55d3",
|
||||
"type": "prompt",
|
||||
"version": "",
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 3,
|
||||
"views": 169,
|
||||
"upvotes": 1,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"is_published_plugin": true,
|
||||
"created_at": "2026-03-15",
|
||||
"updated_at": "2026-03-16",
|
||||
"url": "https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80"
|
||||
"created_at": "2026-03-22",
|
||||
"updated_at": "2026-03-22",
|
||||
"url": "https://openwebui.com/posts/one_sentence_concept_explainer_79be55d3"
|
||||
},
|
||||
{
|
||||
"title": "🧠 Wisdom Synthesizer (Collective Wisdom Synthesizer)",
|
||||
"slug": "wisdom_synthesizer_collective_wisdom_synthesizer_f7c0d0fe",
|
||||
"type": "action",
|
||||
"version": "",
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 0,
|
||||
"views": 99,
|
||||
"upvotes": 1,
|
||||
"saves": 0,
|
||||
"comments": 0,
|
||||
"is_published_plugin": false,
|
||||
"created_at": "2026-03-22",
|
||||
"updated_at": "2026-03-22",
|
||||
"url": "https://openwebui.com/posts/wisdom_synthesizer_collective_wisdom_synthesizer_f7c0d0fe"
|
||||
},
|
||||
{
|
||||
"title": "An Unconventional Use of Open Terminal ⚡",
|
||||
@@ -380,9 +414,9 @@
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 0,
|
||||
"views": 3490,
|
||||
"upvotes": 7,
|
||||
"saves": 1,
|
||||
"views": 3817,
|
||||
"upvotes": 8,
|
||||
"saves": 3,
|
||||
"comments": 2,
|
||||
"is_published_plugin": false,
|
||||
"created_at": "2026-03-06",
|
||||
@@ -397,8 +431,8 @@
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 0,
|
||||
"views": 1850,
|
||||
"upvotes": 5,
|
||||
"views": 1902,
|
||||
"upvotes": 6,
|
||||
"saves": 1,
|
||||
"comments": 0,
|
||||
"is_published_plugin": false,
|
||||
@@ -414,8 +448,8 @@
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 0,
|
||||
"views": 2827,
|
||||
"upvotes": 8,
|
||||
"views": 2911,
|
||||
"upvotes": 9,
|
||||
"saves": 4,
|
||||
"comments": 1,
|
||||
"is_published_plugin": false,
|
||||
@@ -431,7 +465,7 @@
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 0,
|
||||
"views": 2454,
|
||||
"views": 2471,
|
||||
"upvotes": 7,
|
||||
"saves": 5,
|
||||
"comments": 0,
|
||||
@@ -448,9 +482,9 @@
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 0,
|
||||
"views": 2042,
|
||||
"upvotes": 14,
|
||||
"saves": 24,
|
||||
"views": 2149,
|
||||
"upvotes": 15,
|
||||
"saves": 26,
|
||||
"comments": 9,
|
||||
"is_published_plugin": false,
|
||||
"created_at": "2026-01-25",
|
||||
@@ -465,7 +499,7 @@
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 0,
|
||||
"views": 273,
|
||||
"views": 279,
|
||||
"upvotes": 2,
|
||||
"saves": 0,
|
||||
"comments": 0,
|
||||
@@ -482,9 +516,9 @@
|
||||
"author": "",
|
||||
"description": "",
|
||||
"downloads": 0,
|
||||
"views": 1599,
|
||||
"upvotes": 16,
|
||||
"saves": 13,
|
||||
"views": 1638,
|
||||
"upvotes": 17,
|
||||
"saves": 14,
|
||||
"comments": 2,
|
||||
"is_published_plugin": false,
|
||||
"created_at": "2026-01-10",
|
||||
@@ -497,11 +531,11 @@
|
||||
"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": 367,
|
||||
"following": 7,
|
||||
"total_points": 378,
|
||||
"post_points": 314,
|
||||
"comment_points": 64,
|
||||
"contributions": 76
|
||||
"followers": 419,
|
||||
"following": 9,
|
||||
"total_points": 407,
|
||||
"post_points": 336,
|
||||
"comment_points": 71,
|
||||
"contributions": 89
|
||||
}
|
||||
}
|
||||
@@ -8,7 +8,7 @@
|
||||
> *Blue: Downloads | Purple: Views (Real-time dynamic)*
|
||||
|
||||
### 📂 Content Distribution
|
||||
|
||||
|
||||
|
||||
|
||||
## 📈 Overview
|
||||
@@ -26,41 +26,43 @@
|
||||
|
||||
## 📂 By Type
|
||||
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
|
||||
## 📋 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 |  |  |  |  |  | 2026-03-16 |
|
||||
| 2 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 3 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | filter |  |  |  |  |  | 2026-03-16 |
|
||||
| 4 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter |  |  |  |  |  | 2026-03-16 |
|
||||
| 5 | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 6 | [AI Task Instruction Generator](https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37) | prompt |  |  |  |  |  | 2026-01-28 |
|
||||
| 7 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 8 | [OpenWebUI Skills Manager Tool](https://openwebui.com/posts/openwebui_skills_manager_tool_b4bce8e4) | tool |  |  |  |  |  | 2026-03-19 |
|
||||
| 9 | [GitHub Copilot Official SDK Pipe](https://openwebui.com/posts/github_copilot_official_sdk_pipe_ce96f7b4) | pipe |  |  |  |  |  | 2026-03-19 |
|
||||
| 10 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 2 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action |  |  |  |  |  | 2026-03-23 |
|
||||
| 3 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | filter |  |  |  |  |  | 2026-03-22 |
|
||||
| 4 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter |  |  |  |  |  | 2026-03-22 |
|
||||
| 5 | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 6 | [AI Task Instruction Generator](https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37) | prompt |  |  |  |  |  | 2026-03-22 |
|
||||
| 7 | [OpenWebUI Skills Manager Tool](https://openwebui.com/posts/openwebui_skills_manager_tool_b4bce8e4) | tool |  |  |  |  |  | 2026-03-23 |
|
||||
| 8 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 9 | [GitHub Copilot Official SDK Pipe](https://openwebui.com/posts/github_copilot_official_sdk_pipe_ce96f7b4) | pipe |  |  |  |  |  | 2026-03-22 |
|
||||
| 10 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 11 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action |  |  |  |  |  | 2026-01-08 |
|
||||
| 12 | [🧠 Smart Mind Map Tool: Auto-Generate Interactive Knowledge Graphs](https://openwebui.com/posts/smart_mind_map_tool_auto_generate_interactive_know_d25f4e3d) | tool |  |  |  |  |  | 2026-03-05 |
|
||||
| 13 | [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 |  |  |  |  |  | 2026-03-16 |
|
||||
| 14 | [📂 Folder Memory – Auto-Evolving Project Context](https://openwebui.com/posts/folder_memory_auto_evolving_project_context_4a9875b2) | filter |  |  |  |  |  | 2026-01-20 |
|
||||
| 15 | [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) | tool |  |  |  |  |  | 2026-03-19 |
|
||||
| 16 | [GitHub Copilot SDK Files Filter](https://openwebui.com/posts/github_copilot_sdk_files_filter_403a62ee) | filter |  |  |  |  |  | 2026-03-16 |
|
||||
| 17 | [智能信息图](https://openwebui.com/posts/智能信息图_e04a48ff) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 13 | [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) | tool |  |  |  |  |  | 2026-03-23 |
|
||||
| 14 | [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 |  |  |  |  |  | 2026-03-22 |
|
||||
| 15 | [📂 Folder Memory – Auto-Evolving Project Context](https://openwebui.com/posts/folder_memory_auto_evolving_project_context_4a9875b2) | filter |  |  |  |  |  | 2026-01-20 |
|
||||
| 16 | [GitHub Copilot SDK Files Filter](https://openwebui.com/posts/github_copilot_sdk_files_filter_403a62ee) | filter |  |  |  |  |  | 2026-03-22 |
|
||||
| 17 | [智能信息图](https://openwebui.com/posts/智能信息图_e04a48ff) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 18 | [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 |  |  |  |  |  | 2026-02-13 |
|
||||
| 19 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | action |  |  |  |  |  | 2026-02-13 |
|
||||
| 20 | [精读](https://openwebui.com/posts/精读_99830b0f) | action |  |  |  |  |  | 2026-01-08 |
|
||||
| 21 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 22 | [An Unconventional Use of Open Terminal ⚡](https://openwebui.com/posts/an_unconventional_use_of_open_terminal_35498f8f) | action |  |  |  |  |  | 2026-03-07 |
|
||||
| 23 | [🚀 GitHub Copilot SDK Pipe v0.9.0: Skills & RichUI](https://openwebui.com/posts/github_copilot_sdk_pipe_v090_copilot_sdk_skills_co_99a42452) | pipe |  |  |  |  |  | 2026-02-28 |
|
||||
| 24 | [🚀 GitHub Copilot SDK Pipe v0.7.0: Skills & Rich UI 🛠️](https://openwebui.com/posts/github_copilot_sdk_pipe_v070_native_tool_ui_zero_c_4af38131) | pipe |  |  |  |  |  | 2026-02-28 |
|
||||
| 25 | [🚀 GitHub Copilot SDK Pipe: AI That Executes, Not Just Talks](https://openwebui.com/posts/github_copilot_sdk_for_openwebui_elevate_your_ai_t_a140f293) | pipe |  |  |  |  |  | 2026-02-10 |
|
||||
| 26 | [🚀 Open WebUI Prompt Plus: AI-Powered Prompt Manager](https://openwebui.com/posts/open_webui_prompt_plus_ai_powered_prompt_manager_s_15fa060e) | action |  |  |  |  |  | 2026-01-28 |
|
||||
| 27 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | review |  |  |  |  |  | 2026-01-14 |
|
||||
| 28 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | action |  |  |  |  |  | 2026-01-10 |
|
||||
| 21 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 22 | [🔍 One-Sentence Concept Explainer](https://openwebui.com/posts/one_sentence_concept_explainer_79be55d3) | prompt |  |  |  |  |  | 2026-03-22 |
|
||||
| 23 | [🧠 Wisdom Synthesizer (Collective Wisdom Synthesizer)](https://openwebui.com/posts/wisdom_synthesizer_collective_wisdom_synthesizer_f7c0d0fe) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 24 | [An Unconventional Use of Open Terminal ⚡](https://openwebui.com/posts/an_unconventional_use_of_open_terminal_35498f8f) | action |  |  |  |  |  | 2026-03-07 |
|
||||
| 25 | [🚀 GitHub Copilot SDK Pipe v0.9.0: Skills & RichUI](https://openwebui.com/posts/github_copilot_sdk_pipe_v090_copilot_sdk_skills_co_99a42452) | pipe |  |  |  |  |  | 2026-02-28 |
|
||||
| 26 | [🚀 GitHub Copilot SDK Pipe v0.7.0: Skills & Rich UI 🛠️](https://openwebui.com/posts/github_copilot_sdk_pipe_v070_native_tool_ui_zero_c_4af38131) | pipe |  |  |  |  |  | 2026-02-28 |
|
||||
| 27 | [🚀 GitHub Copilot SDK Pipe: AI That Executes, Not Just Talks](https://openwebui.com/posts/github_copilot_sdk_for_openwebui_elevate_your_ai_t_a140f293) | pipe |  |  |  |  |  | 2026-02-10 |
|
||||
| 28 | [🚀 Open WebUI Prompt Plus: AI-Powered Prompt Manager](https://openwebui.com/posts/open_webui_prompt_plus_ai_powered_prompt_manager_s_15fa060e) | action |  |  |  |  |  | 2026-01-28 |
|
||||
| 29 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | review |  |  |  |  |  | 2026-01-14 |
|
||||
| 30 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | action |  |  |  |  |  | 2026-01-10 |
|
||||
|
||||
@@ -8,7 +8,7 @@
|
||||
> *蓝色: 总下载量 | 紫色: 总浏览量 (实时动态生成)*
|
||||
|
||||
### 📂 内容分类占比 (Distribution)
|
||||
|
||||
|
||||
|
||||
|
||||
## 📈 总览
|
||||
@@ -26,41 +26,43 @@
|
||||
|
||||
## 📂 按类型分类
|
||||
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
- 
|
||||
|
||||
## 📋 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 |  |  |  |  |  | 2026-03-16 |
|
||||
| 2 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 3 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | filter |  |  |  |  |  | 2026-03-16 |
|
||||
| 4 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter |  |  |  |  |  | 2026-03-16 |
|
||||
| 5 | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 6 | [AI Task Instruction Generator](https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37) | prompt |  |  |  |  |  | 2026-01-28 |
|
||||
| 7 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 8 | [OpenWebUI Skills Manager Tool](https://openwebui.com/posts/openwebui_skills_manager_tool_b4bce8e4) | tool |  |  |  |  |  | 2026-03-19 |
|
||||
| 9 | [GitHub Copilot Official SDK Pipe](https://openwebui.com/posts/github_copilot_official_sdk_pipe_ce96f7b4) | pipe |  |  |  |  |  | 2026-03-19 |
|
||||
| 10 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 2 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action |  |  |  |  |  | 2026-03-23 |
|
||||
| 3 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | filter |  |  |  |  |  | 2026-03-22 |
|
||||
| 4 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | filter |  |  |  |  |  | 2026-03-22 |
|
||||
| 5 | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 6 | [AI Task Instruction Generator](https://openwebui.com/posts/ai_task_instruction_generator_9bab8b37) | prompt |  |  |  |  |  | 2026-03-22 |
|
||||
| 7 | [OpenWebUI Skills Manager Tool](https://openwebui.com/posts/openwebui_skills_manager_tool_b4bce8e4) | tool |  |  |  |  |  | 2026-03-23 |
|
||||
| 8 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 9 | [GitHub Copilot Official SDK Pipe](https://openwebui.com/posts/github_copilot_official_sdk_pipe_ce96f7b4) | pipe |  |  |  |  |  | 2026-03-22 |
|
||||
| 10 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 11 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action |  |  |  |  |  | 2026-01-08 |
|
||||
| 12 | [🧠 Smart Mind Map Tool: Auto-Generate Interactive Knowledge Graphs](https://openwebui.com/posts/smart_mind_map_tool_auto_generate_interactive_know_d25f4e3d) | tool |  |  |  |  |  | 2026-03-05 |
|
||||
| 13 | [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 |  |  |  |  |  | 2026-03-16 |
|
||||
| 14 | [📂 Folder Memory – Auto-Evolving Project Context](https://openwebui.com/posts/folder_memory_auto_evolving_project_context_4a9875b2) | filter |  |  |  |  |  | 2026-01-20 |
|
||||
| 15 | [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) | tool |  |  |  |  |  | 2026-03-19 |
|
||||
| 16 | [GitHub Copilot SDK Files Filter](https://openwebui.com/posts/github_copilot_sdk_files_filter_403a62ee) | filter |  |  |  |  |  | 2026-03-16 |
|
||||
| 17 | [智能信息图](https://openwebui.com/posts/智能信息图_e04a48ff) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 13 | [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) | tool |  |  |  |  |  | 2026-03-23 |
|
||||
| 14 | [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 |  |  |  |  |  | 2026-03-22 |
|
||||
| 15 | [📂 Folder Memory – Auto-Evolving Project Context](https://openwebui.com/posts/folder_memory_auto_evolving_project_context_4a9875b2) | filter |  |  |  |  |  | 2026-01-20 |
|
||||
| 16 | [GitHub Copilot SDK Files Filter](https://openwebui.com/posts/github_copilot_sdk_files_filter_403a62ee) | filter |  |  |  |  |  | 2026-03-22 |
|
||||
| 17 | [智能信息图](https://openwebui.com/posts/智能信息图_e04a48ff) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 18 | [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 |  |  |  |  |  | 2026-02-13 |
|
||||
| 19 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | action |  |  |  |  |  | 2026-02-13 |
|
||||
| 20 | [精读](https://openwebui.com/posts/精读_99830b0f) | action |  |  |  |  |  | 2026-01-08 |
|
||||
| 21 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action |  |  |  |  |  | 2026-03-16 |
|
||||
| 22 | [An Unconventional Use of Open Terminal ⚡](https://openwebui.com/posts/an_unconventional_use_of_open_terminal_35498f8f) | action |  |  |  |  |  | 2026-03-07 |
|
||||
| 23 | [🚀 GitHub Copilot SDK Pipe v0.9.0: Skills & RichUI](https://openwebui.com/posts/github_copilot_sdk_pipe_v090_copilot_sdk_skills_co_99a42452) | pipe |  |  |  |  |  | 2026-02-28 |
|
||||
| 24 | [🚀 GitHub Copilot SDK Pipe v0.7.0: Skills & Rich UI 🛠️](https://openwebui.com/posts/github_copilot_sdk_pipe_v070_native_tool_ui_zero_c_4af38131) | pipe |  |  |  |  |  | 2026-02-28 |
|
||||
| 25 | [🚀 GitHub Copilot SDK Pipe: AI That Executes, Not Just Talks](https://openwebui.com/posts/github_copilot_sdk_for_openwebui_elevate_your_ai_t_a140f293) | pipe |  |  |  |  |  | 2026-02-10 |
|
||||
| 26 | [🚀 Open WebUI Prompt Plus: AI-Powered Prompt Manager](https://openwebui.com/posts/open_webui_prompt_plus_ai_powered_prompt_manager_s_15fa060e) | action |  |  |  |  |  | 2026-01-28 |
|
||||
| 27 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | review |  |  |  |  |  | 2026-01-14 |
|
||||
| 28 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | action |  |  |  |  |  | 2026-01-10 |
|
||||
| 21 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 22 | [🔍 One-Sentence Concept Explainer](https://openwebui.com/posts/one_sentence_concept_explainer_79be55d3) | prompt |  |  |  |  |  | 2026-03-22 |
|
||||
| 23 | [🧠 Wisdom Synthesizer (Collective Wisdom Synthesizer)](https://openwebui.com/posts/wisdom_synthesizer_collective_wisdom_synthesizer_f7c0d0fe) | action |  |  |  |  |  | 2026-03-22 |
|
||||
| 24 | [An Unconventional Use of Open Terminal ⚡](https://openwebui.com/posts/an_unconventional_use_of_open_terminal_35498f8f) | action |  |  |  |  |  | 2026-03-07 |
|
||||
| 25 | [🚀 GitHub Copilot SDK Pipe v0.9.0: Skills & RichUI](https://openwebui.com/posts/github_copilot_sdk_pipe_v090_copilot_sdk_skills_co_99a42452) | pipe |  |  |  |  |  | 2026-02-28 |
|
||||
| 26 | [🚀 GitHub Copilot SDK Pipe v0.7.0: Skills & Rich UI 🛠️](https://openwebui.com/posts/github_copilot_sdk_pipe_v070_native_tool_ui_zero_c_4af38131) | pipe |  |  |  |  |  | 2026-02-28 |
|
||||
| 27 | [🚀 GitHub Copilot SDK Pipe: AI That Executes, Not Just Talks](https://openwebui.com/posts/github_copilot_sdk_for_openwebui_elevate_your_ai_t_a140f293) | pipe |  |  |  |  |  | 2026-02-10 |
|
||||
| 28 | [🚀 Open WebUI Prompt Plus: AI-Powered Prompt Manager](https://openwebui.com/posts/open_webui_prompt_plus_ai_powered_prompt_manager_s_15fa060e) | action |  |  |  |  |  | 2026-01-28 |
|
||||
| 29 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | review |  |  |  |  |  | 2026-01-14 |
|
||||
| 30 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | action |  |  |  |  |  | 2026-01-10 |
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
A comprehensive thinking lens that dives deep into any content - from context to logic, insights, and action paths.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## 🔥 What's New in v1.0.0
|
||||
|
||||
- ✨ **Thinking Chain Structure**: Moves from surface understanding to deep strategic action.
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
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。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🔥 v1.0.0 更新内容
|
||||
|
||||
- ✨ **思维链结构**: 从表面理解一步步深入到战略行动。
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
Export conversation to Word (.docx) with **syntax highlighting**, **native math equations**, **Mermaid diagrams**, **citations**, and **enhanced table formatting**.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## 🔥 What's New in v0.4.4
|
||||
|
||||
- 🧹 **Content Cleanup**: Enhanced stripping of `<details>` blocks (often used for tool calls/thinking process) to ensure a clean final document.
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
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**。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🔥 v0.4.4 更新内容
|
||||
|
||||
- 🧹 **内容清理加强**: 增强了对 `<details>` 块（通常包含工具调用或思考过程）的清理，确保最终文档整洁。
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
Export chat history to an Excel (.xlsx) file directly from the chat interface.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## 🔥 What's New in v0.3.6
|
||||
|
||||
- **OpenWebUI-Style Theme**: Modern dark header (#1f2937) with light gray zebra striping for better readability.
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
将对话历史直接导出为 Excel (.xlsx) 文件。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🔥 最新更新 v0.3.6
|
||||
|
||||
- **OpenWebUI 风格主题**：现代深灰表头（#1f2937）与浅灰斑马纹，提升可读性。
|
||||
|
||||
@@ -8,6 +8,19 @@ Generate polished learning flashcards from any text—title, summary, key points
|
||||
|  |  |  |  |  |  |  |
|
||||
| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## What's New
|
||||
|
||||
### v0.2.4
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|  |  |  |  |  |  |  |
|
||||
| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🔥 最新更新 v0.2.4
|
||||
|
||||
* **输出优化**: 移除输出中的调试信息。
|
||||
|
||||
@@ -33,7 +33,7 @@ Actions are interactive plugins that:
|
||||
|
||||
Transform text into professional infographics using AntV visualization engine with various templates.
|
||||
|
||||
**Version:** 1.5.0
|
||||
**Version:** 1.6.0
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](smart-infographic.md)
|
||||
|
||||
|
||||
@@ -33,7 +33,7 @@ Actions 是交互式插件，能够：
|
||||
|
||||
使用 AntV 可视化引擎，将文本转成专业的信息图。
|
||||
|
||||
**版本：** 1.4.9
|
||||
**版本：** 1.6.0
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](smart-infographic.md)
|
||||
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Smart Infographic
|
||||
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.5.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.6.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
@@ -8,7 +8,20 @@
|
||||
|
||||
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 v1.5.0
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## 🔥 What's New in v1.6.0
|
||||
|
||||
- 🌐 **Smart Language Detection**: Automatically detects the accurate UI language from your browser.
|
||||
- 🗣️ **Context-Aware Generation**: Generated infographics now strictly follow the language of your input content (e.g., input Japanese -> output Japanese infographic).
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# 智能信息图
|
||||
|
||||
| 作者：[Fu-Jie](https://github.com/Fu-Jie) · v1.5.0 | [⭐ 点个 Star 支持项目](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| 作者：[Fu-Jie](https://github.com/Fu-Jie) · v1.6.0 | [⭐ 点个 Star 支持项目](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
@@ -8,7 +8,20 @@
|
||||
|
||||
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。
|
||||
|
||||
## 🔥 最新更新 v1.5.0
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🔥 最新更新 v1.6.0
|
||||
|
||||
- 🌐 **智能语言检测**：自动从浏览器准确识别当前界面语言设置。
|
||||
- 🗣️ **上下文感知生成**：生成的信息图内容现在严格跟随用户输入内容的语言（例如：输入日语 -> 生成日语信息图）。
|
||||
|
||||
@@ -10,6 +10,19 @@ Smart Mind Map is a powerful OpenWebUI action plugin that intelligently analyzes
|
||||
|
||||
> 🏆 **Featured by OpenWebUI Official** — This plugin was recommended in the official OpenWebUI Community Newsletter: [February 3, 2026](https://openwebui.com/blog/open-webui-community-newsletter-february-3rd-2026)
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## What's New in v1.0.0
|
||||
|
||||
### Direct Embed & UI Refinements
|
||||
|
||||
@@ -10,6 +10,19 @@
|
||||
|
||||
> 🏆 **OpenWebUI 官方推荐** — 本插件获得 OpenWebUI 社区 Newsletter 官方推荐：[2026 年 2 月 3 日](https://openwebui.com/blog/open-webui-community-newsletter-february-3rd-2026)
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## v1.0.0 最新更新
|
||||
|
||||
### 嵌入式直出与 UI 细节全线重构
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Async Context Compression Filter
|
||||
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.5.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.6.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
@@ -8,6 +8,25 @@
|
||||
|
||||
This filter reduces token consumption in long conversations through intelligent summarization and message compression while keeping conversations coherent.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## What's new in 1.6.0
|
||||
|
||||
- **Fixed `keep_first` Logic**: Re-defined `keep_first` to protect the first N **non-system** messages plus all interleaved system messages. This ensures initial context (e.g., identity, task instructions) is preserved correctly.
|
||||
- **Absolute System Message Protection**: System messages are now strictly excluded from compression. Any system message encountered in the history (even late-injected ones) is preserved as an original message in the final context.
|
||||
- **Improved Context Assembly**: Summaries now only target User and Assistant dialogue, ensuring that system instructions injected by other plugins are never "eaten" by the summarizer.
|
||||
|
||||
## What's new in 1.5.0
|
||||
|
||||
- **External Chat Reference Summaries**: Added support for referenced chat context blocks that can reuse cached summaries, inject small referenced chats directly, or generate summaries for larger referenced chats before injection.
|
||||
@@ -41,6 +60,10 @@ This filter reduces token consumption in long conversations through intelligent
|
||||
|
||||
## What This Fixes
|
||||
|
||||
- **Problem: System Messages being summarized/lost.**
|
||||
Previously, the filter could include system messages (especially those injected late by other plugins) in its summarization zone, causing important instructions to be lost. Now, all system messages are strictly preserved in their original role and never summarized.
|
||||
- **Problem: Incorrect `keep_first` behavior.**
|
||||
Previously, `keep_first` simply took the first $N$ messages. If those were only system messages, the initial user/assistant messages (which are often important for context) would be summarized. Now, `keep_first` ensures that $N$ non-system messages are protected.
|
||||
- **Problem 1: A referenced chat could break the current request.**
|
||||
Before, if the filter needed to summarize a referenced chat and that LLM call failed, the current chat could fail with it. Now it degrades gracefully and injects direct context instead.
|
||||
- **Problem 2: Some referenced chats were being cut too aggressively.**
|
||||
@@ -128,7 +151,7 @@ flowchart TD
|
||||
| `priority` | `10` | Execution order; lower runs earlier. |
|
||||
| `compression_threshold_tokens` | `64000` | Trigger asynchronous summary when total tokens exceed this value. Set to 50%-70% of your model's context window. |
|
||||
| `max_context_tokens` | `128000` | Hard cap for context; older messages (except protected ones) are dropped if exceeded. |
|
||||
| `keep_first` | `1` | Always keep the first N messages (protects system prompts). |
|
||||
| `keep_first` | `1` | Number of initial **non-system** messages to always keep (plus all preceding system prompts). |
|
||||
| `keep_last` | `6` | Always keep the last N messages to preserve recent context. |
|
||||
| `summary_model` | `None` | Model for summaries. Strongly recommended to set a fast, economical model (e.g., `gemini-2.5-flash`, `deepseek-v3`). Falls back to the current chat model when empty. |
|
||||
| `summary_model_max_context` | `0` | Input context window used to fit summary requests. If `0`, falls back to `model_thresholds` or global `max_context_tokens`. |
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# 异步上下文压缩过滤器
|
||||
|
||||
| 作者：[Fu-Jie](https://github.com/Fu-Jie) · v1.5.0 | [⭐ 点个 Star 支持项目](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| 作者：[Fu-Jie](https://github.com/Fu-Jie) · v1.6.0 | [⭐ 点个 Star 支持项目](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
@@ -10,6 +10,25 @@
|
||||
|
||||
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。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 1.6.0 版本更新
|
||||
|
||||
- **修正 `keep_first` 逻辑**：重新定义了 `keep_first` 的功能，现在它负责保护前 N 条**非系统消息**（以及它们之前的所有系统提示词）。这确保了初始对话背景（如身份设定、任务说明）能被正确保留。
|
||||
- **系统消息绝对保护**：系统消息现在被严格排除在压缩范围之外。历史记录中遇到的任何系统消息（甚至是后期注入的消息）都会作为原始消息保留在最终上下文中。
|
||||
- **改进的上下文组装**：摘要现在仅针对用户和助手的对话，确保其他插件注入的系统指令永远不会被摘要器“吃掉”。
|
||||
|
||||
## 1.5.0 版本更新
|
||||
|
||||
- **外部聊天引用摘要**: 新增对引用聊天上下文的摘要支持。现在可以复用缓存摘要、直接注入较小引用聊天，或先为较大的引用聊天生成摘要再注入。
|
||||
@@ -39,12 +58,14 @@
|
||||
- ✅ **智能模型匹配**: 自定义模型自动继承基础模型的阈值配置。
|
||||
- ⚠ **多模态支持**: 图片内容会被保留，但其 Token **不参与计算**。请相应调整阈值。
|
||||
|
||||
详细的工作原理和更长说明仍可参考 [工作流程指南](https://github.com/Fu-Jie/openwebui-extensions/blob/main/plugins/filters/async-context-compression/WORKFLOW_GUIDE_CN.md)。
|
||||
|
||||
---
|
||||
|
||||
## 这次解决了什么问题（通俗版）
|
||||
|
||||
- **问题：系统消息被摘要或丢失。**
|
||||
以前，过滤器可能会将被引用或后期注入的系统消息包含在摘要区域内，导致重要的指令丢失。现在，所有系统消息都严格按原样保留，永不被摘要。
|
||||
- **问题：`keep_first` 逻辑不符合预期。**
|
||||
以前 `keep_first` 只是简单提取前 N 条消息。如果前几条全是系统消息，初始的问答（通常对上下文很重要）就会被压缩掉。现在 `keep_first` 确保保护 N 条非系统消息。
|
||||
- **问题 1：引用别的聊天时，摘要失败可能把当前对话一起弄挂。**
|
||||
以前如果过滤器需要先帮被引用聊天做摘要，而这一步的 LLM 调用失败了，当前请求也可能直接失败。现在改成了“能摘要就摘要，失败就退回直接塞上下文”，当前对话不会被一起拖死。
|
||||
- **问题 2：有些被引用聊天被截得太早，信息丢得太多。**
|
||||
@@ -72,11 +93,11 @@ flowchart TD
|
||||
F -- 是 --> G[直接复用缓存摘要]
|
||||
F -- 否 --> H{能直接放进当前预算?}
|
||||
H -- 是 --> I[直接注入完整引用聊天文本]
|
||||
H -- 否 --> J[准备引用聊天的摘要输入]
|
||||
H -- No --> J[准备引用聊天的摘要输入]
|
||||
|
||||
J --> K{引用聊天摘要调用成功?}
|
||||
K -- 是 --> L[注入生成后的引用摘要]
|
||||
K -- 否 --> M[回退为直接注入上下文]
|
||||
K -- No --> M[回退为直接注入上下文]
|
||||
|
||||
G --> D
|
||||
I --> D
|
||||
@@ -136,7 +157,7 @@ flowchart TD
|
||||
| `priority` | `10` | 过滤器执行顺序，数值越小越先执行。 |
|
||||
| `compression_threshold_tokens` | `64000` | **重要**: 当上下文总 Token 超过此值时后台生成摘要，建议设为模型上下文窗口的 50%-70%。 |
|
||||
| `max_context_tokens` | `128000` | **重要**: 上下文硬上限，超过即移除最早消息（保留受保护消息）。 |
|
||||
| `keep_first` | `1` | 始终保留对话开始的 N 条消息，保护系统提示或环境变量。 |
|
||||
| `keep_first` | `1` | 始终保留对话开始的 N 条**非系统消息**（以及它们之前的所有系统提示词）。 |
|
||||
| `keep_last` | `6` | 始终保留对话末尾的 N 条消息，确保最近上下文连贯。 |
|
||||
|
||||
### 摘要生成配置
|
||||
|
||||
@@ -2,6 +2,19 @@
|
||||
|
||||
A specialized filter for OpenWebUI that displays real-time metadata (display name, token capacity, and remaining quota) for models managed via the Antigravity Auth API.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install "Auth Model Info Filter" from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, confirm this plugin and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## Features
|
||||
|
||||
- **Automatic Metadata Injection**: Displays model details in the status bar of the chat interface.
|
||||
|
||||
@@ -2,6 +2,19 @@
|
||||
|
||||
一个专为 OpenWebUI 设计的过滤器插件，用于显示通过 Antigravity Auth API 管理的模型的实时元数据（显示名称、Token 容量和剩余配额）。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装“模型授权信息过滤器 (Auth Model Info Filter)”
|
||||
```
|
||||
|
||||
当选择弹窗打开后，确认当前插件并继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 功能特性
|
||||
|
||||
- **自动元数据注入**: 在聊天界面的状态栏显示模型详细信息。
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
Automatically tracks and persists the mapping between user IDs and chat IDs for seamless session management.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## Key Features
|
||||
|
||||
🔄 **Automatic Tracking** - Captures user_id and chat_id on every message without manual intervention
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
自动追踪并持久化用户 ID 与聊天 ID 的映射关系，实现无缝的会话管理。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 核心功能
|
||||
|
||||
🔄 **自动追踪** - 无需手动干预，在每条消息上自动捕获 user_id 和 chat_id
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
**Folder Memory** is an intelligent context filter plugin for OpenWebUI. It automatically extracts consistent "Project Rules" from ongoing conversations within a folder and injects them back into the folder's system prompt.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## 🔥 What's New in v0.1.0
|
||||
|
||||
- **Initial Release**: Automated "Project Rules" management for OpenWebUI folders.
|
||||
|
||||
@@ -10,6 +10,19 @@
|
||||
|
||||
这确保了该文件夹内的所有未来对话都能共享相同的进化上下文和规则，无需手动更新。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🔥 最新更新 v0.1.0
|
||||
|
||||
- **首个版本发布**：专注于自动化的“项目规则”管理。
|
||||
|
||||
@@ -10,6 +10,19 @@ This is a dedicated **companion filter plugin** designed specifically for the [G
|
||||
|
||||
Its core mission is to **protect user-uploaded files from being "pre-processed" by the OpenWebUI core system, ensuring that the Copilot Agent receives the raw files for autonomous analysis.**
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## ✨ v0.1.3 Updates (What's New)
|
||||
|
||||
- **🔍 BYOK Model ID Matching Fixed**: Now correctly identifies models in `github_copilot_official_sdk_pipe.xxx` format via prefix matching, in addition to keyword fallback for backward compatibility. (v0.1.3)
|
||||
|
||||
@@ -10,6 +10,19 @@
|
||||
|
||||
它的核心使命是：**保护用户上传的文件不被 OpenWebUI 核心系统“抢先处理”，确保 Copilot Agent 能够接收到原始文件并进行自主分析。**
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## ✨ 0.1.3 更新内容 (What's New)
|
||||
|
||||
- **🔍 BYOK 模型 ID 匹配修复**: 新增前缀匹配（`github_copilot_official_sdk_pipe.xxx` 格式），修复 BYOK 模型无法被正确识别的问题，关键词兜底保持向后兼容。(v0.1.3)
|
||||
|
||||
@@ -22,7 +22,7 @@ Filters act as middleware in the message pipeline:
|
||||
|
||||
Reduces token consumption in long conversations with safer summary fallbacks and clearer failure visibility.
|
||||
|
||||
**Version:** 1.5.0
|
||||
**Version:** 1.6.0
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](async-context-compression.md)
|
||||
|
||||
|
||||
@@ -22,7 +22,7 @@ Filter 充当消息管线中的中间件：
|
||||
|
||||
通过更稳健的摘要回退和更清晰的失败提示，降低长对话的 token 消耗并保持连贯性。
|
||||
|
||||
**版本：** 1.5.0
|
||||
**版本：** 1.6.0
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](async-context-compression.zh.md)
|
||||
|
||||
|
||||
@@ -13,6 +13,19 @@ A powerful, context-aware content normalizer filter for Open WebUI designed to f
|
||||
|
||||
---
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## 🔥 What's New in v1.2.8
|
||||
* **Safe-by-Default Strategy**: The `enable_escape_fix` feature is now **disabled by default**. This prevents unwanted modifications to valid technical text like Windows file paths (`C:\new\test`) or complex LaTeX formulas.
|
||||
* **LaTeX Parsing Fix**: Improved the logic for identifying display math (`$$ ... $$`). Fixed a bug where LaTeX commands starting with `\n` (like `\nabla`) were incorrectly treated as newlines.
|
||||
|
||||
@@ -14,6 +14,19 @@
|
||||
|
||||
---
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🔥 最新更新 v1.2.8
|
||||
* **“默认安全”策略 (Safe-by-Default)**：`enable_escape_fix` 功能现在**默认禁用**。这能有效防止插件在未经授权的情况下误改 Windows 路径 (`C:\new\test`) 或复杂的 LaTeX 公式。
|
||||
* **LaTeX 解析优化**：重构了显示数学公式 (`$$ ... $$`) 的识别逻辑。修复了 LaTeX 命令如果以 `\n` 开头（如 `\nabla`）会被错误识别为换行符的 Bug。
|
||||
|
||||
@@ -17,15 +17,12 @@ Pipelines extend beyond simple transformations to implement:
|
||||
|
||||
<div class="grid cards" markdown>
|
||||
|
||||
- :material-view-module:{ .lg .middle } **MoE Prompt Refiner**
|
||||
- :material-view-module:{ .lg .middle } **Wisdom Synthesizer**
|
||||
[:octicons-tag-24: v0.1.0](https://github.com/Fu-Jie/open-webui-pipeline-wisdom-synthesizer){ .bubble }
|
||||
|
||||
---
|
||||
An external pipeline filter that refactors aggregate requests with collective wisdom to output structured expert reports.
|
||||
|
||||
Refines prompts for Mixture of Experts (MoE) summary requests to generate high-quality comprehensive reports.
|
||||
|
||||
**Version:** 1.0.0
|
||||
|
||||
[:octicons-arrow-right-24: Documentation](moe-prompt-refiner.md)
|
||||
[:octicons-arrow-right-24: Documentation](wisdom-synthesizer.md)
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
@@ -17,15 +17,12 @@ Pipelines 不仅是简单转换，还可以实现：
|
||||
|
||||
<div class="grid cards" markdown>
|
||||
|
||||
- :material-view-module:{ .lg .middle } **MoE Prompt Refiner**
|
||||
- :material-view-module:{ .lg .middle } **Wisdom Synthesizer**
|
||||
[:octicons-tag-24: v0.1.0](https://github.com/Fu-Jie/open-webui-pipeline-wisdom-synthesizer){ .bubble }
|
||||
|
||||
---
|
||||
智能拦截并重构多模型汇总请求，发挥集体智慧（Collective Wisdom），将常规汇总熔炼为专家级对比报告。
|
||||
|
||||
为 Mixture of Experts（MoE）汇总请求优化提示词，生成高质量综合报告。
|
||||
|
||||
**版本：** 1.0.0
|
||||
|
||||
[:octicons-arrow-right-24: 查看文档](moe-prompt-refiner.md)
|
||||
[:octicons-arrow-right-24: 查看文档](wisdom-synthesizer.md)
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
@@ -1,109 +0,0 @@
|
||||
# MoE Prompt Refiner
|
||||
|
||||
<span class="category-badge pipeline">Pipeline</span>
|
||||
<span class="version-badge">v1.0.0</span>
|
||||
|
||||
Refines prompts for Mixture of Experts (MoE) summary requests to generate high-quality comprehensive reports.
|
||||
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
The MoE Prompt Refiner is an advanced pipeline that optimizes prompts before sending them to multiple expert models, then synthesizes the responses into comprehensive, high-quality reports.
|
||||
|
||||
## Features
|
||||
|
||||
- :material-view-module: **Multi-Model**: Leverages multiple AI models
|
||||
- :material-text-search: **Prompt Optimization**: Refines prompts for best results
|
||||
- :material-merge: **Response Synthesis**: Combines expert responses
|
||||
- :material-file-document: **Report Generation**: Creates structured reports
|
||||
|
||||
---
|
||||
|
||||
## Installation
|
||||
|
||||
1. Download the pipeline file: [`moe_prompt_refiner.py`](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/pipelines)
|
||||
2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
|
||||
3. Configure expert models and settings
|
||||
4. Enable the pipeline
|
||||
|
||||
---
|
||||
|
||||
## How It Works
|
||||
|
||||
```mermaid
|
||||
graph TD
|
||||
A[User Prompt] --> B[Prompt Refiner]
|
||||
B --> C[Expert Model 1]
|
||||
B --> D[Expert Model 2]
|
||||
B --> E[Expert Model N]
|
||||
C --> F[Response Synthesizer]
|
||||
D --> F
|
||||
E --> F
|
||||
F --> G[Comprehensive Report]
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Configuration
|
||||
|
||||
| Option | Type | Default | Description |
|
||||
|--------|------|---------|-------------|
|
||||
| `expert_models` | list | `[]` | List of models to consult |
|
||||
| `synthesis_model` | string | `"auto"` | Model for synthesizing responses |
|
||||
| `report_format` | string | `"markdown"` | Output format |
|
||||
|
||||
---
|
||||
|
||||
## Use Cases
|
||||
|
||||
- **Research Reports**: Gather insights from multiple AI perspectives
|
||||
- **Comprehensive Analysis**: Multi-faceted problem analysis
|
||||
- **Decision Support**: Balanced recommendations from diverse models
|
||||
- **Content Creation**: Rich, multi-perspective content
|
||||
|
||||
---
|
||||
|
||||
## Example
|
||||
|
||||
**Input Prompt:**
|
||||
```
|
||||
Analyze the pros and cons of microservices architecture
|
||||
```
|
||||
|
||||
**Output Report:**
|
||||
```markdown
|
||||
# Microservices Architecture Analysis
|
||||
|
||||
## Executive Summary
|
||||
Based on analysis from multiple expert perspectives...
|
||||
|
||||
## Advantages
|
||||
1. **Scalability** (Expert A)...
|
||||
2. **Technology Flexibility** (Expert B)...
|
||||
|
||||
## Disadvantages
|
||||
1. **Complexity** (Expert A)...
|
||||
2. **Distributed System Challenges** (Expert C)...
|
||||
|
||||
## Recommendations
|
||||
Synthesized recommendations based on expert consensus...
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Requirements
|
||||
|
||||
!!! note "Prerequisites"
|
||||
- OpenWebUI v0.3.0 or later
|
||||
- Access to multiple LLM models
|
||||
- Sufficient API quotas for multi-model queries
|
||||
|
||||
!!! warning "Resource Usage"
|
||||
This pipeline makes multiple API calls per request. Monitor your usage and costs.
|
||||
|
||||
---
|
||||
|
||||
## Source Code
|
||||
|
||||
[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/pipelines){ .md-button }
|
||||
@@ -1,109 +0,0 @@
|
||||
# MoE Prompt Refiner
|
||||
|
||||
<span class="category-badge pipeline">Pipeline</span>
|
||||
<span class="version-badge">v1.0.0</span>
|
||||
|
||||
为 Mixture of Experts（MoE）汇总请求优化提示词，生成高质量的综合报告。
|
||||
|
||||
---
|
||||
|
||||
## 概览
|
||||
|
||||
MoE Prompt Refiner 是一个高级 Pipeline，会在将请求发送给多个专家模型前先优化提示词，然后综合各模型回复，输出结构化的高质量报告。
|
||||
|
||||
## 功能特性
|
||||
|
||||
- :material-view-module: **多模型**：同时利用多个 AI 模型
|
||||
- :material-text-search: **提示词优化**：在发送前优化 prompt 获得更好结果
|
||||
- :material-merge: **结果合成**：整合专家回复
|
||||
- :material-file-document: **报告生成**：输出结构化报告
|
||||
|
||||
---
|
||||
|
||||
## 安装
|
||||
|
||||
1. 下载 Pipeline 文件：[`moe_prompt_refiner.py`](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/pipelines)
|
||||
2. 上传到 OpenWebUI：**Admin Panel** → **Settings** → **Functions**
|
||||
3. 配置专家模型及相关参数
|
||||
4. 启用该 Pipeline
|
||||
|
||||
---
|
||||
|
||||
## 工作流程
|
||||
|
||||
```mermaid
|
||||
graph TD
|
||||
A[User Prompt] --> B[Prompt Refiner]
|
||||
B --> C[Expert Model 1]
|
||||
B --> D[Expert Model 2]
|
||||
B --> E[Expert Model N]
|
||||
C --> F[Response Synthesizer]
|
||||
D --> F
|
||||
E --> F
|
||||
F --> G[Comprehensive Report]
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 配置项
|
||||
|
||||
| 选项 | 类型 | 默认值 | 说明 |
|
||||
|--------|------|---------|-------------|
|
||||
| `expert_models` | list | `[]` | 需要咨询的模型列表 |
|
||||
| `synthesis_model` | string | `"auto"` | 用于综合回复的模型 |
|
||||
| `report_format` | string | `"markdown"` | 输出格式 |
|
||||
|
||||
---
|
||||
|
||||
## 适用场景
|
||||
|
||||
- **研究报告**：从多个 AI 视角收集洞见
|
||||
- **综合分析**：多角度问题拆解
|
||||
- **决策支持**：获得多模型的平衡建议
|
||||
- **内容创作**：生成多视角的丰富内容
|
||||
|
||||
---
|
||||
|
||||
## 示例
|
||||
|
||||
**输入 Prompt：**
|
||||
```
|
||||
Analyze the pros and cons of microservices architecture
|
||||
```
|
||||
|
||||
**输出报告：**
|
||||
```markdown
|
||||
# Microservices Architecture Analysis
|
||||
|
||||
## Executive Summary
|
||||
Based on analysis from multiple expert perspectives...
|
||||
|
||||
## Advantages
|
||||
1. **Scalability** (Expert A)...
|
||||
2. **Technology Flexibility** (Expert B)...
|
||||
|
||||
## Disadvantages
|
||||
1. **Complexity** (Expert A)...
|
||||
2. **Distributed System Challenges** (Expert C)...
|
||||
|
||||
## Recommendations
|
||||
Synthesized recommendations based on expert consensus...
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 运行要求
|
||||
|
||||
!!! note "前置条件"
|
||||
- OpenWebUI v0.3.0 及以上
|
||||
- 可以访问多个 LLM 模型
|
||||
- 有足够的 API 配额支撑多模型请求
|
||||
|
||||
!!! warning "资源消耗"
|
||||
此 Pipeline 每次请求会进行多次 API 调用，请关注用量与成本。
|
||||
|
||||
---
|
||||
|
||||
## 源码
|
||||
|
||||
[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/pipelines){ .md-button }
|
||||
73
docs/plugins/pipelines/wisdom-synthesizer.md
Normal file
73
docs/plugins/pipelines/wisdom-synthesizer.md
Normal file
@@ -0,0 +1,73 @@
|
||||
# Wisdom Synthesizer (Collective Wisdom Synthesizer)
|
||||
|
||||
An external pipeline filter (Pipeline/Filter) for **Open WebUI** that intercepts multi-model aggregate requests to leverage collective wisdom, reshaping **basic and linear aggregate outputs** into structured, high-contrast **expert analysis reports**.
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## 🚀 Key Features
|
||||
|
||||
* **Smart Interception**: Automatically catches Open WebUI's “Summarize various models' responses” requests.
|
||||
* **Dynamic Parsing**: Strips away generic formatting and precisely extracts the **original user query** and **each model's individual response**.
|
||||
* **Wisdom Fusion**: Directs the summary model to act as a “Chief Analyst”, enforcing a critical evaluation workflow instead of generic merging.
|
||||
* **Standardized Output Structure**: Guarantees output layout includes:
|
||||
* **【Core Consensus】**: Aggregated common ground across models.
|
||||
* **【Key Divergences】**: Comparative breakdown of different perspectives/approaches.
|
||||
* **【Unique Insights】**: Spotlighting innovative points found in a single model.
|
||||
* **【Synthesis & Recommendation】**: An action-oriented, blended strategy set.
|
||||
|
||||
---
|
||||
|
||||
## 📦 Installation & Usage (Pipelines Mode)
|
||||
|
||||
> [!IMPORTANT]
|
||||
> **Prerequisite**:
|
||||
> This plugin relies on the official **[open-webui/pipelines](https://github.com/open-webui/pipelines)** framework. Please ensure your Open WebUI backend is already connected to an active `pipelines` runner environment beforehand.
|
||||
|
||||
This plugin runs as a single-file pipeline filter component and supports importing with just a single click:
|
||||
|
||||
### 🚀 One-Click Import via URL (Recommended 🌟)
|
||||
|
||||
1. Log into your Open WebUI board, go to **Admin settings** -> **Pipelines** tab.
|
||||
2. Click **“Add Pipeline”** and paste the **GitHub Raw link** of `wisdom_synthesizer.py` into the address bar.
|
||||
3. Save configurations to load automatically.
|
||||
|
||||
Below is the visual operational guide for getting it loaded:
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## ⚙️ Valves Configuration
|
||||
|
||||
Configuration items inside safe Valves toggles:
|
||||
|
||||
| Parameter | Default | Description |
|
||||
| :--- | :--- | :--- |
|
||||
| `pipelines` | `["*"]` | Target model IDs to apply this Filter to *（Keep default for global）* |
|
||||
| `priority` | `0` | Filter pipeline execution order priority (lower numbers execute first). |
|
||||
| `model_id` | `None` | (Optional) Force the summarize job to run on a dedicated high-spec summary model. |
|
||||
| `trigger_prefix` | `You have been provided...` | Pre-set phrase to trigger interception. Usually requires no changes. |
|
||||
| `query_start_marker` | `'the latest user query: "'` | Anchor used to locate the start of the original query. |
|
||||
| `query_end_marker` | `'"\n\nYour task is to'` | Anchor used to locate the end of the original query. |
|
||||
| `response_start_marker` | `"Responses from models: "` | Anchor used to locate where the model responses begin. |
|
||||
|
||||
> [!TIP]
|
||||
> **Configuration Tip**:
|
||||
> The default `["*"]` allows the filter to securely adapt to any aggregator models chosen on the fly. In most scenarios, **keeping this default configuration** is highly recommended.
|
||||
|
||||
---
|
||||
|
||||
## 🤝 Related Projects
|
||||
|
||||
If you're building inside the Open WebUI ecosystem, you might find my other plugins sets helpful:
|
||||
|
||||
* 🚀 **[openwebui-extensions](https://github.com/Fu-Jie/openwebui-extensions)** —— A comprehensive collection of Actions, Pipes, and Tools to supercharge your workspace.
|
||||
* 🪄 **[open-webui-prompt-plus](https://github.com/Fu-Jie/open-webui-prompt-plus)** —— Enhances Prompt engineering with AI-powered generators, Spotlight-style searches, and interactive forms.
|
||||
|
||||
---
|
||||
|
||||
## 📄 License
|
||||
|
||||
[MIT License](LICENSE)
|
||||
73
docs/plugins/pipelines/wisdom-synthesizer.zh.md
Normal file
73
docs/plugins/pipelines/wisdom-synthesizer.zh.md
Normal file
@@ -0,0 +1,73 @@
|
||||
# Wisdom Synthesizer (集体智慧合成器)
|
||||
|
||||
专为 **Open WebUI** 设计的外置管道过滤器（Pipeline/Filter），旨在通过智能拦截并重构多模型汇总请求，发挥集体智慧（Collective Wisdom），将原本较为**基础和扁平的常规汇总**熔炼为结构清晰、具备多维对比度的**专家级综合分析报告**。
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## 🚀 核心功能
|
||||
|
||||
* **智能拦截**：自动捕获 Open WebUI 的“汇总多模型响应”请求（通过内置前缀触发）。
|
||||
* **动态解析**：剥离多余格式，精准提取**原始用户问题**与**各模型的独立回答**。
|
||||
* **智慧融合**：摒弃基础的模型合并，强制总结模型扮演“首席分析师”，发挥集体智慧审视全局。
|
||||
* **规范输出**：将汇总响应熔炼为以下结构：
|
||||
* **【核心共识】**: 提炼模型间的相同点。
|
||||
* **【关键分歧】**: 对比不同视角的碰撞。
|
||||
* **【独特洞察】**: 发现单一模型闪光点。
|
||||
* **【综合建议】**: 最终形成有弹性的熔铸方案。
|
||||
|
||||
---
|
||||
|
||||
## 📦 安装与使用 (Pipelines 模式)
|
||||
|
||||
> [!IMPORTANT]
|
||||
> **前提条件**：
|
||||
> 本插件依赖于 Open WebUI 官方的 **[open-webui/pipelines](https://github.com/open-webui/pipelines)** 框架插件系统。请确保你的 Open WebUI 后端已经架设好或已连接底层的 `pipelines` 服务端环境。
|
||||
|
||||
本插件为单文件管道过滤组件，支持在面板中一键拉取安装：
|
||||
|
||||
### 🚀 通过 URL 一键导入 (推荐 🌟)
|
||||
|
||||
1. 登录你的 Open WebUI 后台，进入 **管理员设置** -> **Pipelines** 选项卡。
|
||||
2. 点击 **“添加 Pipeline”**，并在地址栏中复制贴入此仓库中 `wisdom_synthesizer.py` 的 **GitHub Raw 链接**。
|
||||
3. 点击 **保存** 即可成功加载。
|
||||
|
||||
以下是操作动态演示：
|
||||
|
||||
|
||||
|
||||
---
|
||||
|
||||
## ⚙️ Valves 管道配置
|
||||
|
||||
进入管道配置项，可动态调整以下参数：
|
||||
|
||||
| 参数 | 默认值 | 说明 |
|
||||
| :--- | :--- | :--- |
|
||||
| `pipelines` | `["*"]` | 应用此 Filter 的目标模型 ID *（如果要全局生效保持默认）* |
|
||||
| `priority` | `0` | 过滤器管道执行优先级（数字越小，越优先执行） |
|
||||
| `model_id` | `None` | (可选) 强制将汇总任务流向你指定的某个专用高性能总结模型 |
|
||||
| `trigger_prefix` | `You have been provided...` | 用于触发拦截的提示词起始句柄前缀。一般无需修改 |
|
||||
| `query_start_marker` | `'the latest user query: "'` | 解析原始查询的起始标记锚点 |
|
||||
| `query_end_marker` | `'"\n\nYour task is to'` | 解析原始查询的结束标记锚点 |
|
||||
| `response_start_marker` | `"Responses from models: "` | 解析各个模型独立响应的起始锚点标志 |
|
||||
|
||||
> [!TIP]
|
||||
> **配置建议**：
|
||||
> 默认值 `["*"]` 可在所有选定的汇总模型上自适应生效。在绝大多数情况下，你**仅需保持此默认参数**便可保障全局自适应拦截。
|
||||
|
||||
---
|
||||
|
||||
## 🤝 友情链接 (Related Projects)
|
||||
|
||||
如果你对 Open WebUI 的扩展生态感兴趣，欢迎关注我的其它开源方案：
|
||||
|
||||
* 🚀 **[openwebui-extensions](https://github.com/Fu-Jie/openwebui-extensions)** —— 包含各种增强 Actions、Pipes、Tools 等一篮子开源插件合集，助你解锁更多黑魔法。
|
||||
* 🪄 **[open-webui-prompt-plus](https://github.com/Fu-Jie/open-webui-prompt-plus)** —— 包含 AI 驱动的提示词生成器、Spotlight 搜索框及交互变量表单，极速拉满提示词工程。
|
||||
|
||||
---
|
||||
|
||||
## 📄 开源许可
|
||||
|
||||
[MIT License](LICENSE)
|
||||
@@ -8,6 +8,23 @@
|
||||
|
||||
One-click batch install plugins from GitHub repositories to your OpenWebUI instance.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
After you install [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) once, you can also use it to reinstall or update itself with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
> [!TIP]
|
||||
> **💡 Looking to batch install or manage Workspace Skills?**
|
||||
> This plugin specializes in installing global function-based plugins (Pipe, Filter, Tool, Action). If you need to manage your AI assistant's dedicated Skills, use our companion tool [OpenWebUI Skills Manager](https://openwebui.com/posts/openwebui_skills_manager_tool_b4bce8e4), which provides full CRUD capabilities, batch discovery, and interactive selection dialogs.
|
||||
|
||||
## Key Features
|
||||
|
||||
- **One-Click Install**: Install all plugins with a single command
|
||||
|
||||
@@ -8,6 +8,23 @@
|
||||
|
||||
一键将 GitHub 仓库中的插件批量安装到你的 OpenWebUI 实例。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
当你已经安装过一次 [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) 后，也可以用同一句来重新安装或更新它自己：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
> [!TIP]
|
||||
> **💡 想要批量安装/管理 Workspace 技能 (Skills)？**
|
||||
> 本插件专注安装全局函数型插件（Pipe/Filter/Tool/Action）。如果你需要管理 AI 助手的专属技能，请使用同系列的 [OpenWebUI Skills Manager](https://openwebui.com/posts/openwebui_skills_manager_tool_b4bce8e4) 工具，它具备完整的增删改查、批量发现及可视化浮层点选能力。
|
||||
|
||||
## 主要功能
|
||||
|
||||
- 一键安装：单个命令安装所有插件
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
A standalone OpenWebUI Tool plugin to manage native **Workspace > Skills** for any model.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## What's New
|
||||
|
||||
- **🤖 Automatic Repo Root Discovery**: Install any GitHub repo by providing just the root URL (e.g., `https://github.com/owner/repo`). System auto-converts to discovery mode and installs all skills.
|
||||
@@ -15,6 +28,10 @@ A standalone OpenWebUI Tool plugin to manage native **Workspace > Skills** for a
|
||||
- Added GitHub skills-directory auto-discovery for `install_skill` (e.g., `.../tree/main/skills`) to install all child skills in one request.
|
||||
- Fixed language detection with robust frontend-first fallback (`__event_call__` + timeout), request header fallback, and profile fallback.
|
||||
|
||||
> [!TIP]
|
||||
> **💡 Looking to batch install global plugins (Actions, Filters, Pipes, Tools)?**
|
||||
> This plugin specializes in managing Workspace Skills for your assistants. If you need to install and manage global function-based plugins, use our companion tool [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) for an optimized installation workflow.
|
||||
|
||||
## Key Features
|
||||
|
||||
- **🌐 Model-agnostic**: Can be enabled for any model that supports OpenWebUI Tools.
|
||||
|
||||
@@ -8,6 +8,19 @@
|
||||
|
||||
一个 OpenWebUI 原生 Tool 插件，用于让任意模型直接管理 **Workspace > Skills**。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 最新更新
|
||||
|
||||
- **🤖 自动发现仓库根目录**：现在可以直接提供 GitHub 仓库根 URL（如 `https://github.com/owner/repo`），系统会自动转换为发现模式并安装所有 skill。
|
||||
@@ -15,6 +28,10 @@
|
||||
- `install_skill` 新增 GitHub 技能目录自动发现（例如 `.../tree/main/skills`），可一键安装目录下所有子技能。
|
||||
- 修复语言获取逻辑：前端优先（`__event_call__` + 超时保护），并回退到请求头与用户资料。
|
||||
|
||||
> [!TIP]
|
||||
> **💡 想要批量安装/管理全局插件 (Actions, Filters, Pipes, Tools)？**
|
||||
> 本插件专注管理工作区的 AI 技能 (Skills)。如果你需要安装和管理全局函数型插件，请使用同系列的 [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) 工具，不仅安装体验极致，而且完美接轨系统扩展体系。
|
||||
|
||||
## 核心特性
|
||||
|
||||
- **🌐 全模型可用**：只要模型启用了 OpenWebUI Tools，即可调用。
|
||||
|
||||
@@ -12,6 +12,19 @@ Smart Mind Map Tool is the tool version of the popular Smart Mind Map action plu
|
||||
|
||||
---
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## Why is there a Tool version?
|
||||
|
||||
1. **Powered by OpenWebUI 0.8.0 Rich UI**: Previous versions of OpenWebUI did not support embedding custom HTML/iframes directly into the chat stream. Starting with 0.8.0, the platform introduced full Rich UI rendering support for **both Actions and Tools**, unleashing interactive frontend possibilities.
|
||||
|
||||
@@ -12,6 +12,19 @@
|
||||
|
||||
---
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🚀 为什么会有工具（Tool）版本？
|
||||
|
||||
1. **得益于 OpenWebUI 0.8.0 的 Rich UI 特性**：在以前的版本中，是不支持直接将自定义的 HTML/iframe 嵌入到对话流中的。而从 0.8.0 开始，平台不仅支持了这种顺滑的前端组件直出（Rich UI），而且同时对 **Action** 和 **Tool** 开放了该能力。
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Prompts
|
||||
|
||||
Discover carefully crafted system prompts to enhance your AI interactions.
|
||||
Discover carefully crafted system prompts to enhance your AI interactions and task orchestration.
|
||||
|
||||
---
|
||||
|
||||
@@ -23,7 +23,7 @@ Prompts are pre-written instructions that guide AI behavior. A well-crafted prom
|
||||
|
||||
---
|
||||
|
||||
Browse all available prompts organized by category with one-click copy functionality.
|
||||
Browse all available dynamic prompts templates with variables and manifest detail.
|
||||
|
||||
[:octicons-arrow-right-24: Open Library](library.md)
|
||||
|
||||
@@ -31,54 +31,26 @@ Prompts are pre-written instructions that guide AI behavior. A well-crafted prom
|
||||
|
||||
---
|
||||
|
||||
## Quick Access by Category
|
||||
## 📋 Available Prompts
|
||||
|
||||
### :material-code-braces: Coding & Development
|
||||
### 🔧 [AI Task Instruction Generator](library.md#ai-task-instruction-generator)
|
||||
Convert vague requirements into precise, AI-executable instructions. Fits standard prompt orchestration workflows.
|
||||
`Command: /ai-task-instruction`
|
||||
|
||||
Perfect for programming assistance, code review, and debugging.
|
||||
|
||||
- [Senior Developer Assistant](library.md#senior-developer-assistant)
|
||||
- [Code Debugger](library.md#code-debugger)
|
||||
- [Code Explainer](library.md#code-explainer)
|
||||
|
||||
### :material-bullhorn: Marketing & Content
|
||||
|
||||
For content creation, copywriting, and marketing strategies.
|
||||
|
||||
- [Content Writer](library.md#content-writer)
|
||||
- [Marketing Strategist](library.md#marketing-strategist)
|
||||
|
||||
### :material-file-document: Writing & Editing
|
||||
|
||||
Academic writing, paper polishing, and document editing.
|
||||
|
||||
- [Academic Paper Polisher](library.md#academic-paper-polisher)
|
||||
- [Document Formatter](library.md#document-formatter)
|
||||
|
||||
### :material-theater: Role Play & Creative
|
||||
|
||||
Creative scenarios, storytelling, and interactive experiences.
|
||||
|
||||
- [Character Role Player](library.md#character-role-player)
|
||||
- [Story Collaborator](library.md#story-collaborator)
|
||||
### 🔍 [One-Sentence Concept Explainer](library.md#one-sentence-concept-explainer)
|
||||
Explain advanced ideas in exactly one clear sentence adapting for any user tier.
|
||||
`Command: /one-sentence-concept-explainer`
|
||||
|
||||
---
|
||||
|
||||
## How to Use
|
||||
|
||||
### Method 1: System Prompt
|
||||
### Method: System prompt / In-Chat Command
|
||||
|
||||
1. Copy the prompt from the [Library](library.md)
|
||||
2. Go to OpenWebUI **Settings** → **Personalization**
|
||||
3. Paste in the **System Prompt** field
|
||||
4. Save and start a new conversation
|
||||
|
||||
### Method 2: In-Chat Prompt
|
||||
|
||||
1. Copy the prompt from the [Library](library.md)
|
||||
2. In any conversation, click the **Prompt** button
|
||||
3. Paste and save as a reusable prompt
|
||||
4. Select it from your saved prompts anytime
|
||||
1. Go to the [Library](library.md) or root `/prompts` folder to copy the prompt code.
|
||||
2. In OpenWebUI dashboard, navigate to **Workspace** -> **Prompts** and click **Create Prompt**.
|
||||
3. Paste the content and save.
|
||||
4. Type title or `/` follow with command name to activate in discussion.
|
||||
|
||||
---
|
||||
|
||||
@@ -90,9 +62,6 @@ Creative scenarios, storytelling, and interactive experiences.
|
||||
!!! tip "Iteration"
|
||||
If the AI's response isn't quite right, refine the prompt and try again. Small changes can have big impacts.
|
||||
|
||||
!!! tip "Specificity"
|
||||
The more specific your prompt, the better the results. Include examples, constraints, and desired output formats.
|
||||
|
||||
---
|
||||
|
||||
## Contribute
|
||||
|
||||
@@ -1,17 +1,17 @@
|
||||
# 提示词
|
||||
# Prompts
|
||||
|
||||
发现精心编写的系统提示词，提升你的 AI 交互体验。
|
||||
发现精心调优的系统提示词（System Prompts），用于提升 AI 交互效率与任务编排结果。
|
||||
|
||||
---
|
||||
|
||||
## 什么是提示词？
|
||||
## 什么是提示词 (Prompts)？
|
||||
|
||||
提示词是预先编写的指令，用来引导 AI 的行为。好的提示词可以：
|
||||
提示词是引导 AI 行为的预设指令或模板。一个优秀的提示词可以：
|
||||
|
||||
- :material-target: 聚焦 AI 在特定任务上
|
||||
- :material-format-quote-close: 设定期望的语气与风格
|
||||
- :material-school: 明确专业领域与知识边界
|
||||
- :material-shield-check: 增加安全与质量规范
|
||||
- :material-target: **精准聚焦任务**。
|
||||
- :material-format-quote-close: **设定语气与输出风格**。
|
||||
- :material-school: **确立领域专家知识边界**。
|
||||
- :material-shield-check: **增加安全、负面约束和质量控制**。
|
||||
|
||||
---
|
||||
|
||||
@@ -19,84 +19,53 @@
|
||||
|
||||
<div class="grid cards" markdown>
|
||||
|
||||
- :material-library:{ .lg .middle } **完整提示词库**
|
||||
- :material-library:{ .lg .middle } **完整提示词库 (Full Library)**
|
||||
|
||||
---
|
||||
|
||||
按类别查看所有可用提示词，并支持一键复制。
|
||||
浏览我们收录的包含动态变量、触发命令和安装说明的全部提示词合集。
|
||||
|
||||
[:octicons-arrow-right-24: 打开提示词库](library.md)
|
||||
[:octicons-arrow-right-24: 打开词库](library.md)
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
## 分类快速访问
|
||||
## 📋 可用提示词列表
|
||||
|
||||
### :material-code-braces: 编程与开发
|
||||
### 🔧 [AI 任务指令生成器 (AI Task Instruction Generator)](library.md#ai-task-instruction-generator)
|
||||
将模糊的需求转换为精确、高度结构化的 AI 可执行指令，规范工作流。
|
||||
`触发指令: /ai-task-instruction`
|
||||
|
||||
用于编程助手、代码审查和调试。
|
||||
|
||||
- [Senior Developer Assistant](library.md#senior-developer-assistant)
|
||||
- [Code Debugger](library.md#code-debugger)
|
||||
- [Code Explainer](library.md#code-explainer)
|
||||
|
||||
### :material-bullhorn: 营销与内容
|
||||
|
||||
适用于内容创作、文案撰写与营销策略。
|
||||
|
||||
- [Content Writer](library.md#content-writer)
|
||||
- [Marketing Strategist](library.md#marketing-strategist)
|
||||
|
||||
### :material-file-document: 写作与编辑
|
||||
|
||||
学术写作、论文润色与文档编辑。
|
||||
|
||||
- [Academic Paper Polisher](library.md#academic-paper-polisher)
|
||||
- [Document Formatter](library.md#document-formatter)
|
||||
|
||||
### :material-theater: 角色扮演与创意
|
||||
|
||||
创意场景、故事讲述与互动体验。
|
||||
|
||||
- [Character Role Player](library.md#character-role-player)
|
||||
- [Story Collaborator](library.md#story-collaborator)
|
||||
### 🔍 [一句话概念解释器 (One-Sentence Concept Explainer)](library.md#one-sentence-concept-explainer)
|
||||
将极其复杂的概念，针对不同级别受众，提炼为精准生动的“一句话”科普。
|
||||
`触发指令: /one-sentence-concept-explainer`
|
||||
|
||||
---
|
||||
|
||||
## 使用方法
|
||||
## 如何使用
|
||||
|
||||
### 方式一：设置为 System Prompt
|
||||
### 方法: 系统提示词 / 快捷指令
|
||||
|
||||
1. 从 [提示词库](library.md) 复制提示词
|
||||
2. 前往 OpenWebUI **Settings** → **Personalization**
|
||||
3. 粘贴到 **System Prompt** 输入框
|
||||
4. 保存并开始新对话
|
||||
|
||||
### 方式二：聊天内快捷提示词
|
||||
|
||||
1. 从 [提示词库](library.md) 复制提示词
|
||||
2. 在任意对话中点击 **Prompt** 按钮
|
||||
3. 粘贴并保存为可复用提示词
|
||||
4. 需要时从已保存的列表中选择
|
||||
1. 访问 [提示词库](library.md) 或项目根目录下的 `/prompts` 文件夹复制模板代码。
|
||||
2. 在 OpenWebUI 的 **Workspace** -> **Prompts** 页面点击 **Create Prompt**。
|
||||
3. 粘贴代码，设置标题（和命令触发词）。
|
||||
4. 在任何会话聊天框中，键入提示词标题或以 `/` 呼出触发指令即可调用！
|
||||
|
||||
---
|
||||
|
||||
## 最佳实践
|
||||
|
||||
!!! tip "可定制"
|
||||
根据自己的需求自由修改提示词，添加上下文、调整语气，或组合多个提示词。
|
||||
!!! tip "按需定制 (Customization)"
|
||||
您可以随时根据特定场景修改提示词字段、微调语气词或设置更严格的负面 Prompt (Negative Prompts)。
|
||||
|
||||
!!! tip "迭代"
|
||||
如果回复不理想，微调提示词再试一次。小改动可能带来大提升。
|
||||
|
||||
!!! tip "具体化"
|
||||
越具体的提示词，效果越好。加入示例、约束及期望输出格式。
|
||||
!!! tip "持续迭代"
|
||||
如果 AI 输出并不完全让您满意，调整一两个修饰词或限制，就会产生巨大的性能提升差异。
|
||||
|
||||
---
|
||||
|
||||
## 参与贡献
|
||||
## 贡献
|
||||
|
||||
有好的提示词？欢迎分享给社区！
|
||||
有好的 prompt 的想法？欢迎提交 PR 一起共享！
|
||||
|
||||
[:octicons-heart-fill-24:{ .heart } 提交提示词](../contributing.md){ .md-button }
|
||||
[:octicons-heart-fill-24:{ .heart } 贡献 Prompt](../contributing.md){ .md-button }
|
||||
|
||||
@@ -1,344 +1,87 @@
|
||||
# Prompt Library
|
||||
|
||||
Welcome to the OpenWebUI Extensions Prompt Library! Find carefully crafted prompts for various use cases.
|
||||
Carefully crafted prompts with dynamic variables supporting OpenWebUI variables and design workflows.
|
||||
|
||||
---
|
||||
|
||||
## Browse by Category
|
||||
## 🔧 AI Task Instruction Generator
|
||||
|
||||
<div class="grid cards" markdown>
|
||||
Convert vague or unstructured requirements into precise, structured instructions optimized for AI agent execution.
|
||||
|
||||
- :material-code-braces:{ .lg .middle } **Coding & Development**
|
||||
- **Command**: `/ai-task-instruction`
|
||||
- **Author**: Fu-Jie
|
||||
- **Community Link**: [OpenWebUI Post](https://openwebui.com/posts/9bab8b37-5c43-48e6-988b-946564510b91)
|
||||
|
||||
---
|
||||
### ⚙️ Variables
|
||||
|
||||
Programming assistance, code review, debugging, and development best practices.
|
||||
| Variable | Type | Options / Default | Description |
|
||||
| :--- | :--- | :--- | :--- |
|
||||
| `target_role` | `text` | `AI Assistant` | The persona or role the agent should adopt. |
|
||||
| `complexity` | `select` | `Basic`, **`Intermediate`**, `Advanced` | Level of depth the output template should contain. |
|
||||
| `output_style` | `select` | **`Markdown Template`**, `JSON`, `Step-by` | Structured style for the resulting prompt framework. |
|
||||
| `requirements` | `textarea`| Required | The unstructured tasks or instructions from the user. |
|
||||
|
||||
[:octicons-arrow-right-24: Browse Coding Prompts](#coding-development)
|
||||
### 📝 Prompt Code
|
||||
|
||||
- :material-bullhorn:{ .lg .middle } **Marketing & Content**
|
||||
```markdown
|
||||
# AI Task Instruction Generator
|
||||
|
||||
---
|
||||
You are an expert Prompt Engineer and Task Architect. Your objective is to transform vague or unstructured natural language requirements into precise, structured instructions optimized for AI agent execution.
|
||||
|
||||
Content creation, copywriting, brand messaging, and marketing strategies.
|
||||
## Input Data
|
||||
**Target Agent Role**: {{target_role | text:default="AI Assistant":placeholder="e.g., Senior Python Developer, Marketing Expert"}}
|
||||
**Task Complexity**: {{complexity | select:options=["Basic","Intermediate","Advanced"]:default="Intermediate"}}
|
||||
**Preferred Output Format**: {{output_style | select:options=["Markdown Template","JSON Protocol","Step-by-Step Guide"]:default="Markdown Template"}}
|
||||
|
||||
[:octicons-arrow-right-24: Browse Marketing Prompts](#marketing-content)
|
||||
**Natural Language Requirements**:
|
||||
"""
|
||||
{{requirements | textarea:placeholder="Paste the raw task description or requirements here..."}}
|
||||
"""
|
||||
|
||||
- :material-file-document:{ .lg .middle } **Writing & Editing**
|
||||
## Generation Guidelines
|
||||
1. **Role Definition**: Assign a specific, expert persona suitable for the task.
|
||||
2. **Objective Clarity**: Clearly state the primary goal.
|
||||
3. **Contextualization**: Provide necessary background based on the input.
|
||||
4. **Step-by-Step Execution**: Break the task down into logical, atomic steps.
|
||||
5. **Constraints & Rules**: Explicitly list any negative constraints or formatting rules.
|
||||
6. **Output Specification**: Define exactly what the final result should look like.
|
||||
7. **Language Consistency**: You MUST generate the structured instructions in the same language as the natural language requirements input by the user (e.g., if the requirements are in Chinese, generate the response in Chinese).
|
||||
|
||||
---
|
||||
|
||||
Academic writing, paper polishing, grammar checking, and document editing.
|
||||
|
||||
[:octicons-arrow-right-24: Browse Writing Prompts](#writing-editing)
|
||||
|
||||
- :material-theater:{ .lg .middle } **Role Play & Creative**
|
||||
|
||||
---
|
||||
|
||||
Character roles, creative scenarios, and interactive storytelling.
|
||||
|
||||
[:octicons-arrow-right-24: Browse Creative Prompts](#role-play-creative)
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
## How to Use Prompts
|
||||
|
||||
1. Find a prompt below that matches your needs
|
||||
2. Click the **Copy** button on the code block
|
||||
3. In OpenWebUI, click the "Prompt" button or paste as a System Prompt
|
||||
4. Customize the prompt if needed
|
||||
5. Start your conversation!
|
||||
|
||||
---
|
||||
|
||||
## Coding & Development { #coding-development }
|
||||
|
||||
### 🔧 Senior Developer Assistant
|
||||
|
||||
An expert programming assistant that provides clean, well-documented code.
|
||||
|
||||
```text
|
||||
You are an expert senior software developer with extensive experience across multiple programming languages and frameworks. Your role is to:
|
||||
|
||||
1. Write clean, efficient, and well-documented code
|
||||
2. Follow best practices and design patterns
|
||||
3. Provide clear explanations for complex concepts
|
||||
4. Suggest improvements and optimizations
|
||||
5. Consider edge cases and error handling
|
||||
|
||||
When writing code:
|
||||
- Use meaningful variable and function names
|
||||
- Include comments for complex logic
|
||||
- Follow the language's style guidelines
|
||||
- Provide usage examples when appropriate
|
||||
|
||||
When reviewing code:
|
||||
- Identify potential bugs and security issues
|
||||
- Suggest performance improvements
|
||||
- Check for code maintainability
|
||||
- Recommend refactoring when beneficial
|
||||
|
||||
Always explain your reasoning and be ready to iterate based on feedback.
|
||||
Please generate the structured instructions now, strictly following the **{{output_style}}** format.
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 🐛 Code Debugger
|
||||
## 🔍 One-Sentence Concept Explainer
|
||||
|
||||
A systematic approach to debugging code issues.
|
||||
Explain advanced ideas in exactly one clear, punchy, and accurate sentence adapted for a selected audience tier.
|
||||
|
||||
```text
|
||||
You are an expert code debugger. When presented with code that has issues:
|
||||
- **Command**: `/one-sentence-concept-explainer`
|
||||
- **Author**: Fu-Jie
|
||||
|
||||
1. **Analyze**: First, read through the code carefully to understand its purpose
|
||||
2. **Identify**: Locate potential bugs, errors, or issues
|
||||
3. **Explain**: Clearly describe what's wrong and why it's problematic
|
||||
4. **Fix**: Provide the corrected code with explanations
|
||||
5. **Prevent**: Suggest best practices to avoid similar issues
|
||||
### ⚙️ Variables
|
||||
|
||||
Debug approach:
|
||||
- Check for syntax errors first
|
||||
- Verify logic flow and conditions
|
||||
- Look for edge cases and boundary conditions
|
||||
- Examine variable scope and lifecycle
|
||||
- Consider thread safety if applicable
|
||||
- Check error handling completeness
|
||||
| Variable | Type | Options / Default | Description |
|
||||
| :--- | :--- | :--- | :--- |
|
||||
| `concept` | `text` | Required | The concept to explain (e.g., Quantum Computing). |
|
||||
| `audience`| `select` | **`General Audience`**, `Child (ELI5)`, `Expert`, `Executive` | Destination audience profile. |
|
||||
| `tone` | `select` | **`Professional`**, `Analogical`, `Inspirational`, `Humorous` | Style with which the explanation speaks. |
|
||||
|
||||
Format your response:
|
||||
- 🔴 **Issue Found**: Description of the problem
|
||||
- 🔍 **Root Cause**: Why this happened
|
||||
- ✅ **Solution**: Fixed code with explanation
|
||||
- 💡 **Prevention**: Tips to avoid this in future
|
||||
### 📝 Prompt Code
|
||||
|
||||
```markdown
|
||||
# One-Sentence Concept Explainer
|
||||
|
||||
You are an expert communicator specializing in radical simplicity. Your task is to explain the following concept in exactly one clear, punchy, and accurate sentence.
|
||||
|
||||
## Configuration
|
||||
- **Concept**: {{concept | text:placeholder="Enter the concept (e.g., Quantum Entanglement)"}}
|
||||
- **Target Audience**: {{audience | select:options=["General Audience","Child (ELI5)","Expert","Business Executive"]:default="General Audience"}}
|
||||
- **Tone**: {{tone | select:options=["Professional","Analogical","Inspirational","Humorous"]:default="Professional"}}
|
||||
|
||||
## Instructions
|
||||
1. Provide the explanation in the same language as the concept provided by the user (e.g., if the concept is in Chinese, provide explanation in Chinese).
|
||||
2. Ensure the response is strictly limited to one sentence.
|
||||
3. Capture the core essence of the concept while adjusting the complexity for the selected audience.
|
||||
4. If an analogy is requested, ensure it is relatable and accurate.
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 📚 Code Explainer
|
||||
|
||||
Break down complex code into understandable explanations.
|
||||
|
||||
```text
|
||||
You are a patient and thorough code educator. When explaining code:
|
||||
|
||||
1. Start with a high-level overview of what the code does
|
||||
2. Break down the code into logical sections
|
||||
3. Explain each section step by step
|
||||
4. Use analogies and real-world examples when helpful
|
||||
5. Highlight important patterns or techniques used
|
||||
6. Point out any clever tricks or non-obvious behavior
|
||||
|
||||
Adjust your explanation based on:
|
||||
- The apparent complexity of the code
|
||||
- The user's indicated experience level
|
||||
- The programming language conventions
|
||||
|
||||
Always encourage questions and provide additional resources when appropriate.
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Marketing & Content { #marketing-content }
|
||||
|
||||
### 📝 Content Writer
|
||||
|
||||
Create engaging content for various platforms and purposes.
|
||||
|
||||
```text
|
||||
You are an experienced content writer and marketing specialist. Your role is to create compelling, engaging content tailored to specific audiences and platforms.
|
||||
|
||||
When creating content:
|
||||
1. **Understand the Goal**: Clarify the purpose (inform, persuade, entertain)
|
||||
2. **Know the Audience**: Consider demographics, interests, pain points
|
||||
3. **Match the Platform**: Adapt tone and format for the medium
|
||||
4. **Hook the Reader**: Start with compelling openings
|
||||
5. **Deliver Value**: Provide useful, actionable information
|
||||
6. **Call to Action**: Guide readers to the next step
|
||||
|
||||
Writing principles:
|
||||
- Use clear, concise language
|
||||
- Break up text for readability
|
||||
- Include relevant examples
|
||||
- Optimize for SEO when appropriate
|
||||
- Maintain brand voice consistency
|
||||
|
||||
Available formats:
|
||||
- Blog posts and articles
|
||||
- Social media content
|
||||
- Email campaigns
|
||||
- Product descriptions
|
||||
- Landing page copy
|
||||
- Press releases
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 🎯 Marketing Strategist
|
||||
|
||||
Develop comprehensive marketing strategies and campaigns.
|
||||
|
||||
```text
|
||||
You are a strategic marketing consultant with expertise in digital marketing, brand development, and campaign optimization.
|
||||
|
||||
Your approach:
|
||||
1. **Analysis**: Understand the business, market, and competition
|
||||
2. **Goals**: Define clear, measurable objectives
|
||||
3. **Strategy**: Develop a comprehensive plan
|
||||
4. **Tactics**: Recommend specific actions and channels
|
||||
5. **Metrics**: Identify KPIs and measurement methods
|
||||
|
||||
Areas of expertise:
|
||||
- Digital marketing (SEO, SEM, Social Media)
|
||||
- Content marketing and strategy
|
||||
- Brand positioning and messaging
|
||||
- Customer journey mapping
|
||||
- Marketing automation
|
||||
- Analytics and optimization
|
||||
|
||||
When providing advice:
|
||||
- Base recommendations on data and best practices
|
||||
- Consider budget constraints
|
||||
- Prioritize high-impact activities
|
||||
- Provide actionable next steps
|
||||
- Include success metrics
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Writing & Editing { #writing-editing }
|
||||
|
||||
### ✍️ Academic Paper Polisher
|
||||
|
||||
Improve academic writing for clarity, style, and impact.
|
||||
|
||||
```text
|
||||
You are an expert academic editor specializing in research paper improvement. Your role is to enhance academic writing while maintaining the author's voice and intent.
|
||||
|
||||
Editing focus areas:
|
||||
1. **Clarity**: Simplify complex sentences without losing meaning
|
||||
2. **Conciseness**: Remove redundancy and wordiness
|
||||
3. **Flow**: Improve transitions and logical progression
|
||||
4. **Grammar**: Correct errors and improve syntax
|
||||
5. **Style**: Ensure consistency and appropriate academic tone
|
||||
|
||||
Specific improvements:
|
||||
- Active voice where appropriate
|
||||
- Precise word choice
|
||||
- Parallel structure
|
||||
- Clear topic sentences
|
||||
- Effective paragraph organization
|
||||
- Proper citation integration
|
||||
|
||||
Format your feedback:
|
||||
- Provide the edited text
|
||||
- Highlight major changes with explanations
|
||||
- Suggest alternatives when appropriate
|
||||
- Maintain the original meaning and intent
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 📄 Document Formatter
|
||||
|
||||
Professional document formatting and structure.
|
||||
|
||||
```text
|
||||
You are a professional document specialist. Help users create well-structured, properly formatted documents.
|
||||
|
||||
Services:
|
||||
1. **Structure**: Organize content logically
|
||||
2. **Format**: Apply consistent formatting
|
||||
3. **Style**: Ensure professional appearance
|
||||
4. **Templates**: Provide document templates
|
||||
5. **Standards**: Follow industry conventions
|
||||
|
||||
Document types:
|
||||
- Business reports
|
||||
- Technical documentation
|
||||
- Proposals and pitches
|
||||
- Meeting minutes
|
||||
- Standard operating procedures
|
||||
- User guides and manuals
|
||||
|
||||
When formatting:
|
||||
- Use clear headings and hierarchy
|
||||
- Include appropriate white space
|
||||
- Create scannable bullet points
|
||||
- Add tables and visuals when helpful
|
||||
- Ensure accessibility
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Role Play & Creative { #role-play-creative }
|
||||
|
||||
### 🎭 Character Role Player
|
||||
|
||||
Engaging interactive role-play experiences.
|
||||
|
||||
```text
|
||||
You are a skilled role-play facilitator capable of embodying various characters and scenarios.
|
||||
|
||||
Guidelines:
|
||||
1. **Stay in Character**: Maintain consistent personality and knowledge
|
||||
2. **Be Reactive**: Respond naturally to user inputs
|
||||
3. **Build the World**: Add relevant details and atmosphere
|
||||
4. **Advance the Story**: Keep the narrative moving forward
|
||||
5. **Respect Boundaries**: Keep content appropriate
|
||||
|
||||
Character elements:
|
||||
- Distinct voice and mannerisms
|
||||
- Consistent background and motivations
|
||||
- Realistic knowledge limitations
|
||||
- Emotional depth and reactions
|
||||
- Growth and development over time
|
||||
|
||||
Scenarios available:
|
||||
- Historical figures
|
||||
- Fictional characters
|
||||
- Professional roles (interview practice)
|
||||
- Language practice partners
|
||||
- Creative storytelling
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 📖 Story Collaborator
|
||||
|
||||
Collaborative creative writing and storytelling.
|
||||
|
||||
```text
|
||||
You are a creative writing partner and story collaborator. Help users develop and write engaging narratives.
|
||||
|
||||
Collaboration modes:
|
||||
1. **Co-writing**: Take turns writing story segments
|
||||
2. **Brainstorming**: Generate ideas and plot points
|
||||
3. **Development**: Flesh out characters and settings
|
||||
4. **Editing**: Improve existing creative writing
|
||||
5. **Feedback**: Provide constructive critique
|
||||
|
||||
Story elements to develop:
|
||||
- Compelling characters with depth
|
||||
- Engaging plots with tension
|
||||
- Vivid settings and world-building
|
||||
- Natural dialogue
|
||||
- Meaningful themes
|
||||
- Satisfying resolutions
|
||||
|
||||
When collaborating:
|
||||
- Match the user's style and tone
|
||||
- Offer suggestions, not dictations
|
||||
- Build on their ideas
|
||||
- Keep the story consistent
|
||||
- Encourage creativity
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Submit Your Prompts
|
||||
|
||||
Have a great prompt to share? We'd love to include it!
|
||||
|
||||
[:octicons-heart-fill-24:{ .heart } Contribute a Prompt](../contributing.md){ .md-button }
|
||||
|
||||
@@ -1,344 +1,87 @@
|
||||
# 提示词库
|
||||
# 提示词库 (Prompt Library)
|
||||
|
||||
欢迎来到 OpenWebUI Extensions 提示词库！在这里可以找到针对不同场景精心设计的提示词。
|
||||
包含精心调优的带有动态变量（Dynamic Variables）的系统提示词，支持 OpenWebUI 官方的原生语法解析。
|
||||
|
||||
---
|
||||
|
||||
## 按分类浏览
|
||||
## 🔧 AI 任务指令生成器 (AI Task Instruction Generator)
|
||||
|
||||
<div class="grid cards" markdown>
|
||||
将模糊的通用需求或无结构自然语言，转换为精确、结构化且高度优化的 AI 任务指令框架。
|
||||
|
||||
- :material-code-braces:{ .lg .middle } **编程与开发**
|
||||
- **触发指令**: `/ai-task-instruction`
|
||||
- **作者**: Fu-Jie
|
||||
- **社区链接**: [OpenWebUI Post](https://openwebui.com/posts/9bab8b37-5c43-48e6-988b-946564510b91)
|
||||
|
||||
---
|
||||
### ⚙️ 动态变量 (Variables)
|
||||
|
||||
编程辅助、代码审查、调试与工程最佳实践。
|
||||
| 变量名 | 类型 | 选项 / 默认值 | 描述说明 |
|
||||
| :--- | :--- | :--- | :--- |
|
||||
| `target_role` | `text` | `AI Assistant` | 目标 Agent 应扮演的专家角色。 |
|
||||
| `complexity` | `select` | `Basic`, **`Intermediate`**, `Advanced` | 输出结果的拆解深度。 |
|
||||
| `output_style` | `select` | **`Markdown Template`**, `JSON`, `Step-by-Step` | 提示词的结构化展示样式。 |
|
||||
| `requirements` | `textarea`| 必填 | 用户输入的原始自然语言需求文本。 |
|
||||
|
||||
[:octicons-arrow-right-24: 查看编程提示词](#coding-development)
|
||||
### 📝 提示词代码
|
||||
|
||||
- :material-bullhorn:{ .lg .middle } **营销与内容**
|
||||
```markdown
|
||||
# AI Task Instruction Generator
|
||||
|
||||
---
|
||||
You are an expert Prompt Engineer and Task Architect. Your objective is to transform vague or unstructured natural language requirements into precise, structured instructions optimized for AI agent execution.
|
||||
|
||||
内容创作、文案撰写、品牌信息与营销策略。
|
||||
## Input Data
|
||||
**Target Agent Role**: {{target_role | text:default="AI Assistant":placeholder="e.g., Senior Python Developer, Marketing Expert"}}
|
||||
**Task Complexity**: {{complexity | select:options=["Basic","Intermediate","Advanced"]:default="Intermediate"}}
|
||||
**Preferred Output Format**: {{output_style | select:options=["Markdown Template","JSON Protocol","Step-by-Step Guide"]:default="Markdown Template"}}
|
||||
|
||||
[:octicons-arrow-right-24: 查看营销提示词](#marketing-content)
|
||||
**Natural Language Requirements**:
|
||||
"""
|
||||
{{requirements | textarea:placeholder="Paste the raw task description or requirements here..."}}
|
||||
"""
|
||||
|
||||
- :material-file-document:{ .lg .middle } **写作与编辑**
|
||||
## Generation Guidelines
|
||||
1. **Role Definition**: Assign a specific, expert persona suitable for the task.
|
||||
2. **Objective Clarity**: Clearly state the primary goal.
|
||||
3. **Contextualization**: Provide necessary background based on the input.
|
||||
4. **Step-by-Step Execution**: Break the task down into logical, atomic steps.
|
||||
5. **Constraints & Rules**: Explicitly list any negative constraints or formatting rules.
|
||||
6. **Output Specification**: Define exactly what the final result should look like.
|
||||
7. **Language Consistency**: You MUST generate the structured instructions in the same language as the natural language requirements input by the user (e.g., if the requirements are in Chinese, generate the response in Chinese).
|
||||
|
||||
---
|
||||
|
||||
学术写作、论文润色、语法检查与文档编辑。
|
||||
|
||||
[:octicons-arrow-right-24: 查看写作提示词](#writing-editing)
|
||||
|
||||
- :material-theater:{ .lg .middle } **角色扮演与创意**
|
||||
|
||||
---
|
||||
|
||||
角色扮演、创意场景与互动式故事。
|
||||
|
||||
[:octicons-arrow-right-24: 查看创意提示词](#role-play-creative)
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
## 如何使用提示词
|
||||
|
||||
1. 找到符合需求的提示词
|
||||
2. 点击代码块的 **Copy** 按钮复制
|
||||
3. 在 OpenWebUI 中点击 "Prompt" 按钮，或作为 System Prompt 粘贴
|
||||
4. 如有需要可自行调整提示词内容
|
||||
5. 开始你的对话！
|
||||
|
||||
---
|
||||
|
||||
## Coding & Development { #coding-development }
|
||||
|
||||
### 🔧 Senior Developer Assistant
|
||||
|
||||
高级编程助手，为你提供清晰且带注释的代码。
|
||||
|
||||
```text
|
||||
You are an expert senior software developer with extensive experience across multiple programming languages and frameworks. Your role is to:
|
||||
|
||||
1. Write clean, efficient, and well-documented code
|
||||
2. Follow best practices and design patterns
|
||||
3. Provide clear explanations for complex concepts
|
||||
4. Suggest improvements and optimizations
|
||||
5. Consider edge cases and error handling
|
||||
|
||||
When writing code:
|
||||
- Use meaningful variable and function names
|
||||
- Include comments for complex logic
|
||||
- Follow the language's style guidelines
|
||||
- Provide usage examples when appropriate
|
||||
|
||||
When reviewing code:
|
||||
- Identify potential bugs and security issues
|
||||
- Suggest performance improvements
|
||||
- Check for code maintainability
|
||||
- Recommend refactoring when beneficial
|
||||
|
||||
Always explain your reasoning and be ready to iterate based on feedback.
|
||||
Please generate the structured instructions now, strictly following the **{{output_style}}** format.
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 🐛 Code Debugger
|
||||
## 🔍 一句话概念解释器 (One-Sentence Concept Explainer)
|
||||
|
||||
系统化的代码排查流程。
|
||||
将任何高级或抽象的概念，针对不同级别受众，提炼为精准生动的“一句话”科普。
|
||||
|
||||
```text
|
||||
You are an expert code debugger. When presented with code that has issues:
|
||||
- **触发指令**: `/one-sentence-concept-explainer`
|
||||
- **作者**: Fu-Jie
|
||||
|
||||
1. **Analyze**: First, read through the code carefully to understand its purpose
|
||||
2. **Identify**: Locate potential bugs, errors, or issues
|
||||
3. **Explain**: Clearly describe what's wrong and why it's problematic
|
||||
4. **Fix**: Provide the corrected code with explanations
|
||||
5. **Prevent**: Suggest best practices to avoid similar issues
|
||||
### ⚙️ 动态变量 (Variables)
|
||||
|
||||
Debug approach:
|
||||
- Check for syntax errors first
|
||||
- Verify logic flow and conditions
|
||||
- Look for edge cases and boundary conditions
|
||||
- Examine variable scope and lifecycle
|
||||
- Consider thread safety if applicable
|
||||
- Check error handling completeness
|
||||
| 变量名 | 类型 | 选项 / 默认值 | 描述说明 |
|
||||
| :--- | :--- | :--- | :--- |
|
||||
| `concept` | `text` | 必填 | 要解释的概念（例如：量子纠缠）。 |
|
||||
| `audience`| `select` | **`General Audience`**, `Child (ELI5)`, `Expert`, `Executive` | 解释应当适配的目标受众群体。 |
|
||||
| `tone` | `select` | **`Professional`**, `Analogical`, `Inspirational`, `Humorous` | 解释所采用的词句风格和语气倾向。 |
|
||||
|
||||
Format your response:
|
||||
- 🔴 **Issue Found**: Description of the problem
|
||||
- 🔍 **Root Cause**: Why this happened
|
||||
- ✅ **Solution**: Fixed code with explanation
|
||||
- 💡 **Prevention**: Tips to avoid this in future
|
||||
### 📝 提示词代码
|
||||
|
||||
```markdown
|
||||
# One-Sentence Concept Explainer
|
||||
|
||||
You are an expert communicator specializing in radical simplicity. Your task is to explain the following concept in exactly one clear, punchy, and accurate sentence.
|
||||
|
||||
## Configuration
|
||||
- **Concept**: {{concept | text:placeholder="Enter the concept (e.g., Quantum Entanglement)"}}
|
||||
- **Target Audience**: {{audience | select:options=["General Audience","Child (ELI5)","Expert","Business Executive"]:default="General Audience"}}
|
||||
- **Tone**: {{tone | select:options=["Professional","Analogical","Inspirational","Humorous"]:default="Professional"}}
|
||||
|
||||
## Instructions
|
||||
1. Provide the explanation in the same language as the concept provided by the user (e.g., if the concept is in Chinese, provide explanation in Chinese).
|
||||
2. Ensure the response is strictly limited to one sentence.
|
||||
3. Capture the core essence of the concept while adjusting the complexity for the selected audience.
|
||||
4. If an analogy is requested, ensure it is relatable and accurate.
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 📚 Code Explainer
|
||||
|
||||
将复杂代码拆解为易理解的讲解。
|
||||
|
||||
```text
|
||||
You are a patient and thorough code educator. When explaining code:
|
||||
|
||||
1. Start with a high-level overview of what the code does
|
||||
2. Break down the code into logical sections
|
||||
3. Explain each section step by step
|
||||
4. Use analogies and real-world examples when helpful
|
||||
5. Highlight important patterns or techniques used
|
||||
6. Point out any clever tricks or non-obvious behavior
|
||||
|
||||
Adjust your explanation based on:
|
||||
- The apparent complexity of the code
|
||||
- The user's indicated experience level
|
||||
- The programming language conventions
|
||||
|
||||
Always encourage questions and provide additional resources when appropriate.
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Marketing & Content { #marketing-content }
|
||||
|
||||
### 📝 Content Writer
|
||||
|
||||
面向不同平台的内容创作。
|
||||
|
||||
```text
|
||||
You are an experienced content writer and marketing specialist. Your role is to create compelling, engaging content tailored to specific audiences and platforms.
|
||||
|
||||
When creating content:
|
||||
1. **Understand the Goal**: Clarify the purpose (inform, persuade, entertain)
|
||||
2. **Know the Audience**: Consider demographics, interests, pain points
|
||||
3. **Match the Platform**: Adapt tone and format for the medium
|
||||
4. **Hook the Reader**: Start with compelling openings
|
||||
5. **Deliver Value**: Provide useful, actionable information
|
||||
6. **Call to Action**: Guide readers to the next step
|
||||
|
||||
Writing principles:
|
||||
- Use clear, concise language
|
||||
- Break up text for readability
|
||||
- Include relevant examples
|
||||
- Optimize for SEO when appropriate
|
||||
- Maintain brand voice consistency
|
||||
|
||||
Available formats:
|
||||
- Blog posts and articles
|
||||
- Social media content
|
||||
- Email campaigns
|
||||
- Product descriptions
|
||||
- Landing page copy
|
||||
- Press releases
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 🎯 Marketing Strategist
|
||||
|
||||
制定整体营销策略与活动。
|
||||
|
||||
```text
|
||||
You are a strategic marketing consultant with expertise in digital marketing, brand development, and campaign optimization.
|
||||
|
||||
Your approach:
|
||||
1. **Analysis**: Understand the business, market, and competition
|
||||
2. **Goals**: Define clear, measurable objectives
|
||||
3. **Strategy**: Develop a comprehensive plan
|
||||
4. **Tactics**: Recommend specific actions and channels
|
||||
5. **Metrics**: Identify KPIs and measurement methods
|
||||
|
||||
Areas of expertise:
|
||||
- Digital marketing (SEO, SEM, Social Media)
|
||||
- Content marketing and strategy
|
||||
- Brand positioning and messaging
|
||||
- Customer journey mapping
|
||||
- Marketing automation
|
||||
- Analytics and optimization
|
||||
|
||||
When providing advice:
|
||||
- Base recommendations on data and best practices
|
||||
- Consider budget constraints
|
||||
- Prioritize high-impact activities
|
||||
- Provide actionable next steps
|
||||
- Include success metrics
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Writing & Editing { #writing-editing }
|
||||
|
||||
### ✍️ Academic Paper Polisher
|
||||
|
||||
提升学术写作的清晰度、风格与影响力。
|
||||
|
||||
```text
|
||||
You are an expert academic editor specializing in research paper improvement. Your role is to enhance academic writing while maintaining the author's voice and intent.
|
||||
|
||||
Editing focus areas:
|
||||
1. **Clarity**: Simplify complex sentences without losing meaning
|
||||
2. **Conciseness**: Remove redundancy and wordiness
|
||||
3. **Flow**: Improve transitions and logical progression
|
||||
4. **Grammar**: Correct errors and improve syntax
|
||||
5. **Style**: Ensure consistency and appropriate academic tone
|
||||
|
||||
Specific improvements:
|
||||
- Active voice where appropriate
|
||||
- Precise word choice
|
||||
- Parallel structure
|
||||
- Clear topic sentences
|
||||
- Effective paragraph organization
|
||||
- Proper citation integration
|
||||
|
||||
Format your feedback:
|
||||
- Provide the edited text
|
||||
- Highlight major changes with explanations
|
||||
- Suggest alternatives when appropriate
|
||||
- Maintain the original meaning and intent
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 📄 Document Formatter
|
||||
|
||||
帮助你创建结构良好、格式统一的文档。
|
||||
|
||||
```text
|
||||
You are a professional document specialist. Help users create well-structured, properly formatted documents.
|
||||
|
||||
Services:
|
||||
1. **Structure**: Organize content logically
|
||||
2. **Format**: Apply consistent formatting
|
||||
3. **Style**: Ensure professional appearance
|
||||
4. **Templates**: Provide document templates
|
||||
5. **Standards**: Follow industry conventions
|
||||
|
||||
Document types:
|
||||
- Business reports
|
||||
- Technical documentation
|
||||
- Proposals and pitches
|
||||
- Meeting minutes
|
||||
- Standard operating procedures
|
||||
- User guides and manuals
|
||||
|
||||
When formatting:
|
||||
- Use clear headings and hierarchy
|
||||
- Include appropriate white space
|
||||
- Create scannable bullet points
|
||||
- Add tables and visuals when helpful
|
||||
- Ensure accessibility
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Role Play & Creative { #role-play-creative }
|
||||
|
||||
### 🎭 Character Role Player
|
||||
|
||||
沉浸式的角色扮演体验。
|
||||
|
||||
```text
|
||||
You are a skilled role-play facilitator capable of embodying various characters and scenarios.
|
||||
|
||||
Guidelines:
|
||||
1. **Stay in Character**: Maintain consistent personality and knowledge
|
||||
2. **Be Reactive**: Respond naturally to user inputs
|
||||
3. **Build the World**: Add relevant details and atmosphere
|
||||
4. **Advance the Story**: Keep the narrative moving forward
|
||||
5. **Respect Boundaries**: Keep content appropriate
|
||||
|
||||
Character elements:
|
||||
- Distinct voice and mannerisms
|
||||
- Consistent background and motivations
|
||||
- Realistic knowledge limitations
|
||||
- Emotional depth and reactions
|
||||
- Growth and development over time
|
||||
|
||||
Scenarios available:
|
||||
- Historical figures
|
||||
- Fictional characters
|
||||
- Professional roles (interview practice)
|
||||
- Language practice partners
|
||||
- Creative storytelling
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### 📖 Story Collaborator
|
||||
|
||||
与你协作创作故事和叙事。
|
||||
|
||||
```text
|
||||
You are a creative writing partner and story collaborator. Help users develop and write engaging narratives.
|
||||
|
||||
Collaboration modes:
|
||||
1. **Co-writing**: Take turns writing story segments
|
||||
2. **Brainstorming**: Generate ideas and plot points
|
||||
3. **Development**: Flesh out characters and settings
|
||||
4. **Editing**: Improve existing creative writing
|
||||
5. **Feedback**: Provide constructive critique
|
||||
|
||||
Story elements to develop:
|
||||
- Compelling characters with depth
|
||||
- Engaging plots with tension
|
||||
- Vivid settings and world-building
|
||||
- Natural dialogue
|
||||
- Meaningful themes
|
||||
- Satisfying resolutions
|
||||
|
||||
When collaborating:
|
||||
- Match the user's style and tone
|
||||
- Offer suggestions, not dictations
|
||||
- Build on their ideas
|
||||
- Keep the story consistent
|
||||
- Encourage creativity
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 提交你的提示词
|
||||
|
||||
有好用的提示词？欢迎分享！
|
||||
|
||||
[:octicons-heart-fill-24:{ .heart } 贡献提示词](../contributing.md){ .md-button }
|
||||
|
||||
@@ -199,7 +199,7 @@ nav:
|
||||
- plugins/pipes/index.md
|
||||
- Pipelines:
|
||||
- plugins/pipelines/index.md
|
||||
- MoE Prompt Refiner: plugins/pipelines/moe-prompt-refiner.md
|
||||
- Wisdom Synthesizer: plugins/pipelines/wisdom-synthesizer.md
|
||||
- Prompts:
|
||||
- prompts/index.md
|
||||
- prompts/library.md
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# Smart Infographic
|
||||
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.5.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.6.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
@@ -21,7 +21,7 @@ When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## 🔥 What's New in v1.5.0
|
||||
## 🔥 What's New in v1.6.0
|
||||
|
||||
- 🌐 **Smart Language Detection**: Automatically detects the accurate UI language from your browser.
|
||||
- 🗣️ **Context-Aware Generation**: Generated infographics now strictly follow the language of your input content (e.g., input Japanese -> output Japanese infographic).
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# 智能信息图
|
||||
|
||||
| 作者：[Fu-Jie](https://github.com/Fu-Jie) · v1.5.0 | [⭐ 点个 Star 支持项目](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| 作者：[Fu-Jie](https://github.com/Fu-Jie) · v1.6.0 | [⭐ 点个 Star 支持项目](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
@@ -21,7 +21,7 @@
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 🔥 最新更新 v1.5.0
|
||||
## 🔥 最新更新 v1.6.0
|
||||
|
||||
- 🌐 **智能语言检测**：自动从浏览器准确识别当前界面语言设置。
|
||||
- 🗣️ **上下文感知生成**：生成的信息图内容现在严格跟随用户输入内容的语言（例如：输入日语 -> 生成日语信息图）。
|
||||
|
||||
@@ -4,7 +4,7 @@ author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie/openwebui-extensions
|
||||
funding_url: https://github.com/open-webui
|
||||
icon_url: data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9ImN1cnJlbnRDb2xvciIgc3Ryb2tlLXdpZHRoPSIyIiBzdHJva2UtbGluZWNhcD0icm91bmQiIHN0cm9rZS1saW5lam9pbj0icm91bmQiPgogIDxsaW5lIHgxPSIxMiIgeTE9IjIwIiB4Mj0iMTIiIHkyPSIxMCIgLz4KICA8bGluZSB4MT0iMTgiIHkxPSIyMCIgeDI9IjE4IiB5Mj0iNCIgLz4KICA8bGluZSB4MT0iNiIgeTE9IjIwIiB4Mj0iNiIgeTI9IjE2IiAvPgo8L3N2Zz4=
|
||||
version: 1.5.0
|
||||
version: 1.6.1
|
||||
openwebui_id: ad6f0c7f-c571-4dea-821d-8e71697274cf
|
||||
description: AI-powered infographic generator based on AntV Infographic. Supports professional templates, auto-icon matching, and SVG/PNG downloads.
|
||||
"""
|
||||
@@ -16,6 +16,7 @@ import time
|
||||
import re
|
||||
from fastapi import Request
|
||||
from datetime import datetime
|
||||
import asyncio
|
||||
|
||||
from open_webui.utils.chat import generate_chat_completion
|
||||
from open_webui.models.users import Users
|
||||
@@ -25,6 +26,477 @@ logging.basicConfig(
|
||||
)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
TRANSLATIONS = {
|
||||
"en-US": {
|
||||
"status_starting": "Smart Infographic is starting, generating infographic for you...",
|
||||
"error_no_content": "Unable to retrieve valid user message content.",
|
||||
"error_text_too_short": "Text content is too short ({len} characters), unable to perform effective analysis. Please provide at least {min_len} characters of text.",
|
||||
"status_analyzing": "Smart Infographic: Analyzing text structure in depth...",
|
||||
"status_drawing": "Smart Infographic: Drawing completed!",
|
||||
"notification_success": "Mind map has been generated, {user_name}!",
|
||||
"error_processing": "Smart Infographic processing failed: {error}",
|
||||
"error_user_facing": "Sorry, Smart Infographic encountered an error during processing: {error}.\nPlease check the Open WebUI backend logs for more details.",
|
||||
"status_failed": "Smart Infographic: Processing failed.",
|
||||
"notification_failed": "Smart Infographic generation failed, {user_name}!",
|
||||
"status_rendering_image": "Smart Infographic: Rendering image...",
|
||||
"status_image_generated": "Smart Infographic: Image generated!",
|
||||
"notification_image_success": "Mind map image has been generated, {user_name}!",
|
||||
"ui_title": "🧠 Smart Infographic",
|
||||
"ui_user": "User:",
|
||||
"ui_time": "Time:",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "Reset",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "Expand Level",
|
||||
"ui_depth_all": "Expand All",
|
||||
"ui_depth_2": "Level 2",
|
||||
"ui_depth_3": "Level 3",
|
||||
"ui_fullscreen": "Fullscreen",
|
||||
"ui_theme": "Theme",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ Unable to load infographic: Missing valid content.",
|
||||
"html_error_load_failed": "⚠️ Resource loading failed, please try again later.",
|
||||
"js_done": "Done",
|
||||
"js_failed": "Failed",
|
||||
"js_generating": "Generating...",
|
||||
"js_filename": "infographic.png",
|
||||
"js_upload_failed": "Upload failed: ",
|
||||
"md_image_alt": "🧠 Infographic",
|
||||
},
|
||||
"zh-CN": {
|
||||
"status_starting": "信息图已启动，正在为您生成信息图...",
|
||||
"error_no_content": "无法获取有效的用户消息内容。",
|
||||
"error_text_too_short": "文本内容过短（{len}字符），无法进行有效分析。请提供至少{min_len}字符的文本。",
|
||||
"status_analyzing": "信息图：深入分析文本结构...",
|
||||
"status_drawing": "信息图：绘制完成！",
|
||||
"notification_success": "信息图已生成，{user_name}！",
|
||||
"error_processing": "信息图处理失败：{error}",
|
||||
"error_user_facing": "抱歉，信息图在处理时遇到错误：{error}。\n请检查Open WebUI后端日志获取更多详情。",
|
||||
"status_failed": "信息图：处理失败。",
|
||||
"notification_failed": "信息图生成失败，{user_name}！",
|
||||
"status_rendering_image": "信息图：正在渲染图片...",
|
||||
"status_image_generated": "信息图：图片已生成！",
|
||||
"notification_image_success": "信息图图片已生成，{user_name}！",
|
||||
"ui_title": "🧠 智能信息图",
|
||||
"ui_user": "用户：",
|
||||
"ui_time": "时间：",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "缩小",
|
||||
"ui_zoom_reset": "重置",
|
||||
"ui_zoom_in": "放大",
|
||||
"ui_depth_select": "展开层级",
|
||||
"ui_depth_all": "全部展开",
|
||||
"ui_depth_2": "展开 2 级",
|
||||
"ui_depth_3": "展开 3 级",
|
||||
"ui_fullscreen": "全屏",
|
||||
"ui_theme": "主题",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ 无法加载信息图：缺少有效内容。",
|
||||
"html_error_load_failed": "⚠️ 资源加载失败，请稍后重试。",
|
||||
"js_done": "完成",
|
||||
"js_failed": "失败",
|
||||
"js_generating": "生成中...",
|
||||
"js_filename": "信息图.png",
|
||||
"js_upload_failed": "上传失败：",
|
||||
"md_image_alt": "🧠 信息图",
|
||||
},
|
||||
"zh-HK": {
|
||||
"status_starting": "信息圖已啟動，正在為您生成信息圖...",
|
||||
"error_no_content": "無法獲取有效的用戶消息內容。",
|
||||
"error_text_too_short": "文本內容過短（{len}字元），無法進行有效分析。請提供至少{min_len}字元的文本。",
|
||||
"status_analyzing": "信息圖：深入分析文本結構...",
|
||||
"status_drawing": "信息圖：繪製完成！",
|
||||
"notification_success": "信息圖已生成，{user_name}！",
|
||||
"error_processing": "信息圖處理失敗：{error}",
|
||||
"error_user_facing": "抱歉，信息圖在處理時遇到錯誤：{error}。\n請檢查Open WebUI後端日誌獲取更多詳情。",
|
||||
"status_failed": "信息圖：處理失敗。",
|
||||
"notification_failed": "信息圖生成失敗，{user_name}！",
|
||||
"status_rendering_image": "信息圖：正在渲染圖片...",
|
||||
"status_image_generated": "信息圖：圖片已生成！",
|
||||
"notification_image_success": "信息圖圖片已生成，{user_name}！",
|
||||
"ui_title": "🧠 智能信息圖",
|
||||
"ui_user": "用戶：",
|
||||
"ui_time": "時間：",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "縮小",
|
||||
"ui_zoom_reset": "重置",
|
||||
"ui_zoom_in": "放大",
|
||||
"ui_depth_select": "展開層級",
|
||||
"ui_depth_all": "全部展開",
|
||||
"ui_depth_2": "展開 2 級",
|
||||
"ui_depth_3": "展開 3 級",
|
||||
"ui_fullscreen": "全屏",
|
||||
"ui_theme": "主題",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ 無法加載信息圖：缺少有效內容。",
|
||||
"html_error_load_failed": "⚠️ 資源加載失敗，請稍後重試。",
|
||||
"js_done": "完成",
|
||||
"js_failed": "失敗",
|
||||
"js_generating": "生成中...",
|
||||
"js_filename": "信息圖.png",
|
||||
"js_upload_failed": "上傳失敗：",
|
||||
"md_image_alt": "🧠 信息圖",
|
||||
},
|
||||
"zh-TW": {
|
||||
"status_starting": "信息圖已啟動，正在為您生成信息圖...",
|
||||
"error_no_content": "無法獲取有效的用戶消息內容。",
|
||||
"error_text_too_short": "文本內容過短（{len}字元），無法進行有效分析。請提供至少{min_len}字元的文本。",
|
||||
"status_analyzing": "信息圖：深入分析文本結構...",
|
||||
"status_drawing": "信息圖：繪製完成！",
|
||||
"notification_success": "信息圖已生成，{user_name}！",
|
||||
"error_processing": "信息圖處理失敗：{error}",
|
||||
"error_user_facing": "抱歉，信息圖在處理時遇到錯誤：{error}。\n請檢查Open WebUI後端日誌獲取更多詳情。",
|
||||
"status_failed": "信息圖：處理失敗。",
|
||||
"notification_failed": "信息圖生成失敗，{user_name}！",
|
||||
"status_rendering_image": "信息圖：正在渲染圖片...",
|
||||
"status_image_generated": "信息圖：圖片已生成！",
|
||||
"notification_image_success": "信息圖圖片已生成，{user_name}！",
|
||||
"ui_title": "🧠 智能信息圖",
|
||||
"ui_user": "用戶：",
|
||||
"ui_time": "時間：",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "縮小",
|
||||
"ui_zoom_reset": "重置",
|
||||
"ui_zoom_in": "放大",
|
||||
"ui_depth_select": "展開層級",
|
||||
"ui_depth_all": "全部展開",
|
||||
"ui_depth_2": "展開 2 級",
|
||||
"ui_depth_3": "展開 3 級",
|
||||
"ui_fullscreen": "全屏",
|
||||
"ui_theme": "主題",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ 無法加載信息圖：缺少有效內容。",
|
||||
"html_error_load_failed": "⚠️ 資源加載失敗，請稍後重試。",
|
||||
"js_done": "完成",
|
||||
"js_failed": "失敗",
|
||||
"js_generating": "生成中...",
|
||||
"js_filename": "信息圖.png",
|
||||
"js_upload_failed": "上傳失敗：",
|
||||
"md_image_alt": "🧠 信息圖",
|
||||
},
|
||||
"ko-KR": {
|
||||
"status_starting": "스마트 마인드맵이 시작되었습니다, 마인드맵을 생성 중입니다...",
|
||||
"error_no_content": "유효한 사용자 메시지 내용을 가져올 수 없습니다.",
|
||||
"error_text_too_short": "텍스트 내용이 너무 짧아({len}자), 효과적인 분석을 수행할 수 없습니다. 최소 {min_len}자 이상의 텍스트를 제공해 주세요.",
|
||||
"status_analyzing": "스마트 마인드맵: 텍스트 구조 심층 분석 중...",
|
||||
"status_drawing": "스마트 마인드맵: 그리기 완료!",
|
||||
"notification_success": "마인드맵이 생성되었습니다, {user_name}님!",
|
||||
"error_processing": "스마트 마인드맵 처리 실패: {error}",
|
||||
"error_user_facing": "죄송합니다, 스마트 마인드맵 처리 중 오류가 발생했습니다: {error}.\n자세한 내용은 Open WebUI 백엔드 로그를 확인해 주세요.",
|
||||
"status_failed": "스마트 마인드맵: 처리 실패.",
|
||||
"notification_failed": "스마트 마인드맵 생성 실패, {user_name}님!",
|
||||
"status_rendering_image": "스마트 마인드맵: 이미지 렌더링 중...",
|
||||
"status_image_generated": "스마트 마인드맵: 이미지 생성됨!",
|
||||
"notification_image_success": "마인드맵 이미지가 생성되었습니다, {user_name}님!",
|
||||
"ui_title": "🧠 스마트 마인드맵",
|
||||
"ui_user": "사용자:",
|
||||
"ui_time": "시간:",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "초기화",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "레벨 확장",
|
||||
"ui_depth_all": "모두 확장",
|
||||
"ui_depth_2": "레벨 2",
|
||||
"ui_depth_3": "레벨 3",
|
||||
"ui_fullscreen": "전체 화면",
|
||||
"ui_theme": "테마",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ 마인드맵을 로드할 수 없습니다: 유효한 내용이 없습니다.",
|
||||
"html_error_load_failed": "⚠️ 리소스 로드 실패, 나중에 다시 시도해 주세요.",
|
||||
"js_done": "완료",
|
||||
"js_failed": "실패",
|
||||
"js_generating": "생성 중...",
|
||||
"js_filename": "infographic.png",
|
||||
"js_upload_failed": "업로드 실패: ",
|
||||
"md_image_alt": "🧠 마인드맵",
|
||||
},
|
||||
"ja-JP": {
|
||||
"status_starting": "スマートマインドマップが起動しました。マインドマップを生成しています...",
|
||||
"error_no_content": "有効なユーザーメッセージの内容を取得できませんでした。",
|
||||
"error_text_too_short": "テキストの内容が短すぎるため（{len}文字）、効果的な分析を実行できません。少なくとも{min_len}文字のテキストを提供してください。",
|
||||
"status_analyzing": "スマートマインドマップ：テキスト構造を詳細に分析中...",
|
||||
"status_drawing": "スマートマインドマップ：描画完了！",
|
||||
"notification_success": "マインドマップが生成されました、{user_name}さん！",
|
||||
"error_processing": "スマートマインドマップ処理失敗：{error}",
|
||||
"error_user_facing": "申し訳ありません、スマートマインドマップの処理中にエラーが発生しました：{error}。\n詳細については、Open WebUIバックエンドログを確認してください。",
|
||||
"status_failed": "スマートマインドマップ：処理失敗。",
|
||||
"notification_failed": "スマートマインドマップ生成失敗、{user_name}さん！",
|
||||
"status_rendering_image": "スマートマインドマップ：画像レンダリング中...",
|
||||
"status_image_generated": "スマートマインドマップ：画像生成完了！",
|
||||
"notification_image_success": "マインドマップ画像が生成されました、{user_name}さん！",
|
||||
"ui_title": "🧠 スマートマインドマップ",
|
||||
"ui_user": "ユーザー：",
|
||||
"ui_time": "時間：",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "リセット",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "レベル展開",
|
||||
"ui_depth_all": "すべて展開",
|
||||
"ui_depth_2": "レベル2",
|
||||
"ui_depth_3": "レベル3",
|
||||
"ui_fullscreen": "全画面",
|
||||
"ui_theme": "テーマ",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ マインドマップを読み込めません：有効なコンテンツがありません。",
|
||||
"html_error_load_failed": "⚠️ リソースの読み込みに失敗しました。後でもう一度お試しください。",
|
||||
"js_done": "完了",
|
||||
"js_failed": "失敗",
|
||||
"js_generating": "生成中...",
|
||||
"js_filename": "infographic.png",
|
||||
"js_upload_failed": "アップロード失敗：",
|
||||
"md_image_alt": "🧠 マインドマップ",
|
||||
},
|
||||
"fr-FR": {
|
||||
"status_starting": "Smart Infographic démarre, génération de la carte heuristique en cours...",
|
||||
"error_no_content": "Impossible de récupérer le contenu valide du message utilisateur.",
|
||||
"error_text_too_short": "Le contenu du texte est trop court ({len} caractères), impossible d'effectuer une analyse efficace. Veuillez fournir au moins {min_len} caractères de texte.",
|
||||
"status_analyzing": "Smart Infographic : Analyse approfondie de la structure du texte...",
|
||||
"status_drawing": "Smart Infographic : Dessin terminé !",
|
||||
"notification_success": "La carte heuristique a été générée, {user_name} !",
|
||||
"error_processing": "Échec du traitement de Smart Infographic : {error}",
|
||||
"error_user_facing": "Désolé, Smart Infographic a rencontré une erreur lors du traitement : {error}.\nVeuillez vérifier les journaux backend d'Open WebUI pour plus de détails.",
|
||||
"status_failed": "Smart Infographic : Échec du traitement.",
|
||||
"notification_failed": "Échec de la génération de la carte heuristique, {user_name} !",
|
||||
"status_rendering_image": "Smart Infographic : Rendu de l'image...",
|
||||
"status_image_generated": "Smart Infographic : Image générée !",
|
||||
"notification_image_success": "L'image de la carte heuristique a été générée, {user_name} !",
|
||||
"ui_title": "🧠 Smart Infographic",
|
||||
"ui_user": "Utilisateur :",
|
||||
"ui_time": "Heure :",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "Rénitialiser",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "Niveau d'expansion",
|
||||
"ui_depth_all": "Tout développer",
|
||||
"ui_depth_2": "Niveau 2",
|
||||
"ui_depth_3": "Niveau 3",
|
||||
"ui_fullscreen": "Plein écran",
|
||||
"ui_theme": "Thème",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ Impossible de charger la carte heuristique : contenu valide manquant.",
|
||||
"html_error_load_failed": "⚠️ Échec du chargement des ressources, veuillez réessayer plus tard.",
|
||||
"js_done": "Terminé",
|
||||
"js_failed": "Échec",
|
||||
"js_generating": "Génération...",
|
||||
"js_filename": "carte_heuristique.png",
|
||||
"js_upload_failed": "Échec du téléchargement : ",
|
||||
"md_image_alt": "🧠 Carte Heuristique",
|
||||
},
|
||||
"de-DE": {
|
||||
"status_starting": "Smart Infographic startet, Infographic wird für Sie erstellt...",
|
||||
"error_no_content": "Gültiger Inhalt der Benutzernachricht konnte nicht abgerufen werden.",
|
||||
"error_text_too_short": "Der Textinhalt ist zu kurz ({len} Zeichen), eine effektive Analyse ist nicht möglich. Bitte geben Sie mindestens {min_len} Zeichen Text an.",
|
||||
"status_analyzing": "Smart Infographic: Detaillierte Analyse der Textstruktur...",
|
||||
"status_drawing": "Smart Infographic: Zeichnen abgeschlossen!",
|
||||
"notification_success": "Infographic wurde erstellt, {user_name}!",
|
||||
"error_processing": "Smart Infographic Verarbeitung fehlgeschlagen: {error}",
|
||||
"error_user_facing": "Entschuldigung, bei der Verarbeitung von Smart Infographic ist ein Fehler aufgetreten: {error}.\nBitte überprüfen Sie die Open WebUI Backend-Protokolle für weitere Details.",
|
||||
"status_failed": "Smart Infographic: Verarbeitung fehlgeschlagen.",
|
||||
"notification_failed": "Erstellung der Infographic fehlgeschlagen, {user_name}!",
|
||||
"status_rendering_image": "Smart Infographic: Bild wird gerendert...",
|
||||
"status_image_generated": "Smart Infographic: Bild erstellt!",
|
||||
"notification_image_success": "Infographic-Bild wurde erstellt, {user_name}!",
|
||||
"ui_title": "🧠 Smart Infographic",
|
||||
"ui_user": "Benutzer:",
|
||||
"ui_time": "Zeit:",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "Zurücksetzen",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "Ebene erweitern",
|
||||
"ui_depth_all": "Alles erweitern",
|
||||
"ui_depth_2": "Ebene 2",
|
||||
"ui_depth_3": "Ebene 3",
|
||||
"ui_fullscreen": "Vollbild",
|
||||
"ui_theme": "Thema",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ Infographic kann nicht geladen werden: Gültiger Inhalt fehlt.",
|
||||
"html_error_load_failed": "⚠️ Ressourcenladen fehlgeschlagen, bitte versuchen Sie es später erneut.",
|
||||
"js_done": "Fertig",
|
||||
"js_failed": "Fehlgeschlagen",
|
||||
"js_generating": "Generiere...",
|
||||
"js_filename": "infographic.png",
|
||||
"js_upload_failed": "Upload fehlgeschlagen: ",
|
||||
"md_image_alt": "🧠 Infographic",
|
||||
},
|
||||
"es-ES": {
|
||||
"status_starting": "Smart Infographic se está iniciando, generando mapa mental para usted...",
|
||||
"error_no_content": "No se puede recuperar el contenido válido del mensaje del usuario.",
|
||||
"error_text_too_short": "El contenido del texto es demasiado corto ({len} caracteres), no se puede realizar un análisis efectivo. Proporcione al menos {min_len} caracteres de texto.",
|
||||
"status_analyzing": "Smart Infographic: Analizando la estructura del texto en profundidad...",
|
||||
"status_drawing": "Smart Infographic: ¡Dibujo completado!",
|
||||
"notification_success": "¡El mapa mental ha sido generado, {user_name}!",
|
||||
"error_processing": "Falló el procesamiento de Smart Infographic: {error}",
|
||||
"error_user_facing": "Lo sentimos, Smart Infographic encontró un error durante el procesamiento: {error}.\nConsulte los registros del backend de Open WebUI para más detalles.",
|
||||
"status_failed": "Smart Infographic: Procesamiento fallido.",
|
||||
"notification_failed": "¡La generación del mapa mental falló, {user_name}!",
|
||||
"status_rendering_image": "Smart Infographic: Renderizando imagen...",
|
||||
"status_image_generated": "Smart Infographic: ¡Imagen generada!",
|
||||
"notification_image_success": "¡La imagen del mapa mental ha sido generada, {user_name}!",
|
||||
"ui_title": "🧠 Smart Infographic",
|
||||
"ui_user": "Usuario:",
|
||||
"ui_time": "Hora:",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "Restablecer",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "Expandir Nivel",
|
||||
"ui_depth_all": "Expandir Todo",
|
||||
"ui_depth_2": "Nivel 2",
|
||||
"ui_depth_3": "Nivel 3",
|
||||
"ui_fullscreen": "Pantalla completa",
|
||||
"ui_theme": "Tema",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ No se puede cargar el mapa mental: Falta contenido válido.",
|
||||
"html_error_load_failed": "⚠️ Falló la carga de recursos, inténtelo de nuevo más tarde.",
|
||||
"js_done": "Hecho",
|
||||
"js_failed": "Fallido",
|
||||
"js_generating": "Generando...",
|
||||
"js_filename": "mapa_mental.png",
|
||||
"js_upload_failed": "Carga fallida: ",
|
||||
"md_image_alt": "🧠 Mapa Mental",
|
||||
},
|
||||
"it-IT": {
|
||||
"status_starting": "Smart Infographic si sta avviando, generazione mappa mentale in corso...",
|
||||
"error_no_content": "Impossibile recuperare il contenuto valido del messaggio utente.",
|
||||
"error_text_too_short": "Il testo è troppo breve ({len} caratteri), impossibile eseguire un'analisi efficace. Fornire almeno {min_len} caratteri di testo.",
|
||||
"status_analyzing": "Smart Infographic: Analisi approfondita della struttura del testo...",
|
||||
"status_drawing": "Smart Infographic: Disegno completato!",
|
||||
"notification_success": "La mappa mentale è stata generata, {user_name}!",
|
||||
"error_processing": "Elaborazione Smart Infographic fallita: {error}",
|
||||
"error_user_facing": "Spiacenti, Smart Infographic ha riscontrato un errore durante l'elaborazione: {error}.\nControllare i log del backend di Open WebUI per ulteriori dettagli.",
|
||||
"status_failed": "Smart Infographic: Elaborazione fallita.",
|
||||
"notification_failed": "Generazione mappa mentale fallita, {user_name}!",
|
||||
"status_rendering_image": "Smart Infographic: Rendering immagine...",
|
||||
"status_image_generated": "Smart Infographic: Immagine generata!",
|
||||
"notification_image_success": "L'immagine della mappa mentale è stata generata, {user_name}!",
|
||||
"ui_title": "🧠 Smart Infographic",
|
||||
"ui_user": "Utente:",
|
||||
"ui_time": "Ora:",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "Reimposta",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "Espandi Livello",
|
||||
"ui_depth_all": "Espandi Tutto",
|
||||
"ui_depth_2": "Livello 2",
|
||||
"ui_depth_3": "Livello 3",
|
||||
"ui_fullscreen": "Schermo intero",
|
||||
"ui_theme": "Tema",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ Impossibile caricare la mappa mentale: Contenuto valido mancante.",
|
||||
"html_error_load_failed": "⚠️ Caricamento risorse fallito, riprovare più tardi.",
|
||||
"js_done": "Fatto",
|
||||
"js_failed": "Fallito",
|
||||
"js_generating": "Generazione...",
|
||||
"js_filename": "mappa_mentale.png",
|
||||
"js_upload_failed": "Caricamento fallito: ",
|
||||
"md_image_alt": "🧠 Mappa Mentale",
|
||||
},
|
||||
"vi-VN": {
|
||||
"status_starting": "Smart Infographic đang khởi động, đang tạo sơ đồ tư duy cho bạn...",
|
||||
"error_no_content": "Không thể lấy nội dung tin nhắn người dùng hợp lệ.",
|
||||
"error_text_too_short": "Nội dung văn bản quá ngắn ({len} ký tự), không thể thực hiện phân tích hiệu quả. Vui lòng cung cấp ít nhất {min_len} ký tự văn bản.",
|
||||
"status_analyzing": "Smart Infographic: Phân tích sâu cấu trúc văn bản...",
|
||||
"status_drawing": "Smart Infographic: Vẽ hoàn tất!",
|
||||
"notification_success": "Sơ đồ tư duy đã được tạo, {user_name}!",
|
||||
"error_processing": "Xử lý Smart Infographic thất bại: {error}",
|
||||
"error_user_facing": "Xin lỗi, Smart Infographic đã gặp lỗi trong quá trình xử lý: {error}.\nVui lòng kiểm tra nhật ký backend Open WebUI để biết thêm chi tiết.",
|
||||
"status_failed": "Smart Infographic: Xử lý thất bại.",
|
||||
"notification_failed": "Tạo sơ đồ tư duy thất bại, {user_name}!",
|
||||
"status_rendering_image": "Smart Infographic: Đang render hình ảnh...",
|
||||
"status_image_generated": "Smart Infographic: Hình ảnh đã tạo!",
|
||||
"notification_image_success": "Hình ảnh sơ đồ tư duy đã được tạo, {user_name}!",
|
||||
"ui_title": "🧠 Smart Infographic",
|
||||
"ui_user": "Người dùng:",
|
||||
"ui_time": "Thời gian:",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "Đặt lại",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "Mở rộng Cấp độ",
|
||||
"ui_depth_all": "Mở rộng Tất cả",
|
||||
"ui_depth_2": "Cấp độ 2",
|
||||
"ui_depth_3": "Cấp độ 3",
|
||||
"ui_fullscreen": "Toàn màn hình",
|
||||
"ui_theme": "Chủ đề",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ Không thể tải sơ đồ tư duy: Thiếu nội dung hợp lệ.",
|
||||
"html_error_load_failed": "⚠️ Tải tài nguyên thất bại, vui lòng thử lại sau.",
|
||||
"js_done": "Xong",
|
||||
"js_failed": "Thất bại",
|
||||
"js_generating": "Đang tạo...",
|
||||
"js_filename": "sodo_tuduy.png",
|
||||
"js_upload_failed": "Tải lên thất bại: ",
|
||||
"md_image_alt": "🧠 Sơ đồ Tư duy",
|
||||
},
|
||||
"id-ID": {
|
||||
"status_starting": "Smart Infographic sedang dimulai, membuat peta pikiran untuk Anda...",
|
||||
"error_no_content": "Tidak dapat mengambil konten pesan pengguna yang valid.",
|
||||
"error_text_too_short": "Konten teks terlalu pendek ({len} karakter), tidak dapat melakukan analisis efektif. Harap berikan setidaknya {min_len} karakter teks.",
|
||||
"status_analyzing": "Smart Infographic: Menganalisis struktur teks secara mendalam...",
|
||||
"status_drawing": "Smart Infographic: Menggambar selesai!",
|
||||
"notification_success": "Peta pikiran telah dibuat, {user_name}!",
|
||||
"error_processing": "Pemrosesan Smart Infographic gagal: {error}",
|
||||
"error_user_facing": "Maaf, Smart Infographic mengalami kesalahan saat memproses: {error}.\nSilakan periksa log backend Open WebUI untuk detail lebih lanjut.",
|
||||
"status_failed": "Smart Infographic: Pemrosesan gagal.",
|
||||
"notification_failed": "Pembuatan peta pikiran gagal, {user_name}!",
|
||||
"status_rendering_image": "Smart Infographic: Merender gambar...",
|
||||
"status_image_generated": "Smart Infographic: Gambar dibuat!",
|
||||
"notification_image_success": "Gambar peta pikiran telah dibuat, {user_name}!",
|
||||
"ui_title": "🧠 Smart Infographic",
|
||||
"ui_user": "Pengguna:",
|
||||
"ui_time": "Waktu:",
|
||||
"ui_download_png": "PNG",
|
||||
"ui_download_svg": "SVG",
|
||||
"ui_download_md": "Markdown",
|
||||
"ui_zoom_out": "-",
|
||||
"ui_zoom_reset": "Atur Ulang",
|
||||
"ui_zoom_in": "+",
|
||||
"ui_depth_select": "Perluas Level",
|
||||
"ui_depth_all": "Perluas Semua",
|
||||
"ui_depth_2": "Level 2",
|
||||
"ui_depth_3": "Level 3",
|
||||
"ui_fullscreen": "Layar Penuh",
|
||||
"ui_theme": "Tema",
|
||||
"ui_footer": "<b>Powered by</b> <a href='https://markmap.js.org/' target='_blank' rel='noopener noreferrer'>Markmap</a>",
|
||||
"html_error_missing_content": "⚠️ Tidak dapat memuat peta pikiran: Konten valid hilang.",
|
||||
"html_error_load_failed": "⚠️ Gagal memuat sumber daya, silakan coba lagi nanti.",
|
||||
"js_done": "Selesai",
|
||||
"js_failed": "Gagal",
|
||||
"js_generating": "Membuat...",
|
||||
"js_filename": "peta_pikiran.png",
|
||||
"js_upload_failed": "Unggah gagal: ",
|
||||
"md_image_alt": "🧠 Peta Pikiran",
|
||||
},
|
||||
}
|
||||
|
||||
# =================================================================
|
||||
# LLM Prompts
|
||||
# =================================================================
|
||||
@@ -35,6 +507,7 @@ You are a professional infographic design expert who can analyze user-provided t
|
||||
## Important Language Rule
|
||||
- **GENERATE CONTENT IN INPUT LANGUAGE**: You must generate the text content of the infographic in the **exact same language** as the user's input content (the text you are analyzing).
|
||||
- **Format Consistency**: Even if this system prompt is in English, if the user input is in Chinese, the infographic content must be in Chinese. If input is Japanese, output Japanese.
|
||||
- **If Unsure**: If the language is ambiguous, mixed, or cannot be clearly determined from the context, default to **English** for the infographic content.
|
||||
|
||||
## Infographic Syntax Specification
|
||||
|
||||
@@ -92,7 +565,7 @@ Choose the most appropriate template based on content structure.
|
||||
`chart-pie-plain-text`, `chart-pie-donut-plain-text`, `chart-wordcloud`
|
||||
|
||||
*Other:*
|
||||
`quadrant-quarter-simple-card`, `relation-circle-icon-badge`
|
||||
`quadrant-quarter-simple-card`, `relation-circle-icon-badge`, `relation-dagre-flow-tb-simple-circle-node`
|
||||
|
||||
**Text Capacity by Template Type:**
|
||||
- HIGH capacity (long descriptions OK): `list-column-*`, `compare-binary-*`, `sequence-timeline-*`
|
||||
@@ -110,6 +583,19 @@ Choose the most appropriate template based on content structure.
|
||||
- Format: filename without .svg, e.g., `coding`, `team-work`
|
||||
- Use `illus` field instead of `icon`
|
||||
|
||||
### 📊 Template to Data Field Mapping (CRITICAL)
|
||||
For maximum rendering speed and stability, match the list identifier to the template kind structure. Do NOT just use `items` if a specific field exists:
|
||||
|
||||
| Template Prefix | Data Field Identifier | Core Variables on Items |
|
||||
| :--- | :--- | :--- |
|
||||
| `list-*` | **`lists`** | `label`, `desc`, `icon` |
|
||||
| `sequence-*` | **`sequences`** | `label`, `desc` |
|
||||
| `compare-*` | **`compares`** | `label`, `value`, `children` |
|
||||
| `chart-*` | **`values`** | `label`, `value` |
|
||||
| `hierarchy-*` | **`root` + `children`** | 嵌套嵌套组合 |
|
||||
|
||||
*Note: `items` can be used as a universal fallback adapter if template categorization is ambiguous.*
|
||||
|
||||
### Data Structure Examples
|
||||
|
||||
#### A. Standard List/Tree (Default)
|
||||
@@ -250,11 +736,23 @@ data
|
||||
### Common Data Fields
|
||||
- `label`: Main title/label (Required)
|
||||
- `desc`: Description text
|
||||
- `value`: Numeric value (for charts)
|
||||
- `value`: Numeric value. **ONLY displayed on `chart-*` series templates**. For cards or lists, put data into `desc` instead.
|
||||
- `icon`: Icon name (e.g., `mdi/home`, `mdi/account`) or `ref:search:<keyword>`
|
||||
- `children`: Nested items (for trees, SWOT, etc.)
|
||||
- `illus`: Illustration icon (specific to some templates like Quadrant)
|
||||
|
||||
### 📊 Data & Numeric Fields Standard
|
||||
1. **Value Specification**: `value` MUST be a **pure number** (integer or float), without any symbols like `$`, `%`, or `¥`.
|
||||
2. **Units Placement**: Put units or currency symbols into the `label` or `desc` instead.
|
||||
- ❌ Wrong: `value $1.234` / `value 5.2%`
|
||||
- ✅ Correct: `label USD ($)` -> `value 1.234` OR `label Rate` -> `desc 5.2%`
|
||||
|
||||
### ⚠️ Strict Styling & Layout Rules
|
||||
1. **Color Palette (`palette`)**: MUST use space-separated naked Hex values. Do NOT use quotes (`"`) or commas (`,`).
|
||||
- ✅ Correct: `palette #4f46e5 #06b6d4 #10b981`
|
||||
- ❌ Wrong: `palette "#4f46e5", "#06b6d4"`
|
||||
2. **Binary Compare (`compare-binary-*`)**: The root of `compares` tree MUST contain **EXACTLY TWO** comparison objects.
|
||||
|
||||
### 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).
|
||||
@@ -262,7 +760,7 @@ data
|
||||
4. **Impact**: Use strong verbs and nouns. Avoid filler words.
|
||||
|
||||
## Output Requirements
|
||||
1. **Language**: Output content in the user's language.
|
||||
1. **Language**: Follow the **Important Language Rule** (Generate content in the **exact same language** as the input text content; do NOT force it to match the status parameter).
|
||||
2. **Format**: Wrap output in ```infographic ... ```.
|
||||
3. **No Colons**: Do NOT use colons after keys.
|
||||
4. **Indentation**: Use 2 spaces.
|
||||
@@ -278,6 +776,7 @@ Please analyze the following text content and convert its core information into
|
||||
User Name: {user_name}
|
||||
Current Date/Time: {current_date_time_str}
|
||||
User Language: {user_language}
|
||||
OpenWebUI Theme: {user_theme}
|
||||
---
|
||||
|
||||
**Text Content:**
|
||||
@@ -285,12 +784,17 @@ 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).
|
||||
|
||||
⚠️ **Language Consistency Rule (CRITICAL)**:
|
||||
The title, desc, labels, and text items in your output **MUST STRICTLY MATCH the primary language of the original {long_text_content}**. Do NOT translate the content just to match default status parameters. If the language is ambiguous or mixed, default to **English** for output content nodes.
|
||||
|
||||
**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.
|
||||
- **Numeric Strictness:** `value` MUST be a pure number (no `$`, `%`, etc.). Append units to `label` or `desc` instead.
|
||||
- **Dynamic Selection:** For multiple stats/currencies, use structures like `list-grid-*` or `list-row-*` for dense layouts.
|
||||
|
||||
⚠️ **CRITICAL**: If the original text is too long, you MUST rephrase and shorten it. Do NOT simply truncate with "...".
|
||||
Examples:
|
||||
@@ -365,10 +869,22 @@ CSS_TEMPLATE_INFOGRAPHIC = """
|
||||
--ig-border-color: #e2e8f0;
|
||||
--ig-header-gradient: linear-gradient(135deg, #6366f1, #8b5cf6);
|
||||
}
|
||||
.infographic-container-wrapper.dark {
|
||||
--ig-primary-color: #818cf8;
|
||||
--ig-secondary-color: #a78bfa;
|
||||
--ig-tertiary-color: #34d399;
|
||||
--ig-background-color: #0f172a;
|
||||
--ig-card-bg-color: #1e293b;
|
||||
--ig-text-color: #f8fafc;
|
||||
--ig-muted-text-color: #94a3b8;
|
||||
--ig-border-color: #334155;
|
||||
--ig-header-gradient: linear-gradient(135deg, #4338ca, #6d28d9);
|
||||
}
|
||||
.infographic-container-wrapper {
|
||||
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
|
||||
line-height: 1.6;
|
||||
color: var(--ig-text-color);
|
||||
background-color: var(--ig-background-color);
|
||||
height: 100%;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
@@ -387,7 +903,7 @@ CSS_TEMPLATE_INFOGRAPHIC = """
|
||||
.infographic-container-wrapper .user-context {
|
||||
font-size: 0.8em;
|
||||
color: var(--ig-muted-text-color);
|
||||
background-color: #f1f5f9;
|
||||
background-color: var(--ig-card-bg-color);
|
||||
padding: 8px 16px;
|
||||
display: flex;
|
||||
justify-content: space-around;
|
||||
@@ -402,7 +918,7 @@ CSS_TEMPLATE_INFOGRAPHIC = """
|
||||
border-radius: 8px;
|
||||
padding: 16px;
|
||||
min-height: 600px;
|
||||
background: #fff;
|
||||
background: var(--ig-card-bg-color);
|
||||
overflow: visible;
|
||||
transition: height 0.3s ease;
|
||||
}
|
||||
@@ -414,6 +930,12 @@ CSS_TEMPLATE_INFOGRAPHIC = """
|
||||
line-height: 1.3 !important;
|
||||
overflow: visible !important;
|
||||
}
|
||||
.infographic-container-wrapper.dark .infographic-render-container svg text {
|
||||
fill: var(--ig-text-color) !important;
|
||||
}
|
||||
.infographic-container-wrapper.dark .infographic-render-container svg foreignObject * {
|
||||
color: var(--ig-text-color) !important;
|
||||
}
|
||||
/* Main title styles */
|
||||
.infographic-render-container svg foreignObject[data-element-type="title"] > * {
|
||||
font-size: 1.3em !important;
|
||||
@@ -640,6 +1162,7 @@ SCRIPT_TEMPLATE_INFOGRAPHIC = """
|
||||
// Charts
|
||||
'chart-column': 'chart-column-simple',
|
||||
'quadrant': 'quadrant-quarter-simple-card',
|
||||
'relation-dagre': 'relation-dagre-flow-tb-simple-circle-node',
|
||||
|
||||
// Legacy mappings for backward compatibility
|
||||
'list-vertical': 'list-column-simple-vertical-arrow',
|
||||
@@ -701,6 +1224,24 @@ SCRIPT_TEMPLATE_INFOGRAPHIC = """
|
||||
return;
|
||||
}}
|
||||
|
||||
// --- Auto Theme Loading ---
|
||||
try {{
|
||||
const html = document.documentElement;
|
||||
const body = document.body;
|
||||
const htmlClass = html ? html.className : '';
|
||||
const bodyClass = body ? body.className : '';
|
||||
const htmlDataTheme = html ? html.getAttribute('data-theme') : '';
|
||||
|
||||
const wrapper = containerEl.closest('.infographic-container-wrapper');
|
||||
if (wrapper) {{
|
||||
if (htmlDataTheme === 'dark' || bodyClass.includes('dark') || htmlClass.includes('dark')) {{
|
||||
wrapper.classList.add('dark');
|
||||
}}
|
||||
}}
|
||||
}} catch (e) {{
|
||||
console.warn('[Infographic] Failed to apply theme class', e);
|
||||
}}
|
||||
|
||||
try {{
|
||||
const {{ Infographic }} = AntVInfographic;
|
||||
|
||||
@@ -961,13 +1502,24 @@ class Action:
|
||||
|
||||
def __init__(self):
|
||||
self.valves = self.Valves()
|
||||
# Fallback mapping for variants not in TRANSLATIONS keys
|
||||
self.fallback_map = {
|
||||
"es-AR": "es-ES",
|
||||
"es-MX": "es-ES",
|
||||
"fr-CA": "fr-FR",
|
||||
"en-CA": "en-US",
|
||||
"en-GB": "en-US",
|
||||
"en-AU": "en-US",
|
||||
"de-AT": "de-DE",
|
||||
}
|
||||
|
||||
async def _get_user_context(
|
||||
self,
|
||||
__user__: Optional[Dict[str, Any]],
|
||||
__event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
|
||||
__request__: Optional[Request] = None,
|
||||
) -> Dict[str, str]:
|
||||
"""Safely extracts user context information."""
|
||||
"""Extract basic user context with safe fallbacks."""
|
||||
if isinstance(__user__, (list, tuple)):
|
||||
user_data = __user__[0] if __user__ else {}
|
||||
elif isinstance(__user__, dict):
|
||||
@@ -977,32 +1529,123 @@ class Action:
|
||||
|
||||
user_id = user_data.get("id", "unknown_user")
|
||||
user_name = user_data.get("name", "User")
|
||||
# Default from profile
|
||||
user_language = user_data.get("language", "en-US")
|
||||
user_theme = "light"
|
||||
|
||||
# Level 1 Fallback: Accept-Language from __request__ headers
|
||||
if (
|
||||
__request__
|
||||
and hasattr(__request__, "headers")
|
||||
and "accept-language" in __request__.headers
|
||||
):
|
||||
raw_lang = __request__.headers.get("accept-language", "")
|
||||
if raw_lang:
|
||||
user_language = raw_lang.split(",")[0].split(";")[0]
|
||||
|
||||
# Priority: Document Lang > LocalStorage (Frontend) > Browser > Request Header > Profile
|
||||
if __event_call__:
|
||||
try:
|
||||
js_code = """
|
||||
return (
|
||||
localStorage.getItem('locale') ||
|
||||
localStorage.getItem('language') ||
|
||||
navigator.language ||
|
||||
'en-US'
|
||||
);
|
||||
try {
|
||||
const html = document.documentElement;
|
||||
const body = document.body;
|
||||
const htmlClass = html ? html.className : '';
|
||||
const bodyClass = body ? body.className : '';
|
||||
const htmlDataTheme = html ? html.getAttribute('data-theme') : '';
|
||||
|
||||
let theme = 'light';
|
||||
|
||||
// 1. Check parent document's html/body class or data-theme
|
||||
if (htmlDataTheme === 'dark' || bodyClass.includes('dark') || htmlClass.includes('dark')) {
|
||||
theme = 'dark';
|
||||
} else if (htmlDataTheme === 'light' || bodyClass.includes('light') || htmlClass.includes('light')) {
|
||||
theme = 'light';
|
||||
} else {
|
||||
// 2. Check meta theme-color luma
|
||||
const metas = document.querySelectorAll('meta[name="theme-color"]');
|
||||
let foundMeta = false;
|
||||
if (metas.length > 0) {
|
||||
const color = metas[metas.length - 1].content.trim();
|
||||
const m = color.match(/^#?([0-9a-f]{6})$/i);
|
||||
if (m) {
|
||||
const hex = m[1];
|
||||
const r = parseInt(hex.slice(0, 2), 16);
|
||||
const g = parseInt(hex.slice(2, 4), 16);
|
||||
const b = parseInt(hex.slice(4, 6), 16);
|
||||
const luma = (0.2126 * r + 0.7152 * g + 0.0722 * b) / 255;
|
||||
theme = luma < 0.5 ? 'dark' : 'light';
|
||||
foundMeta = true;
|
||||
}
|
||||
}
|
||||
// 3. Check system preference
|
||||
if (!foundMeta && window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches) {
|
||||
theme = 'dark';
|
||||
}
|
||||
}
|
||||
|
||||
const lang = document.documentElement.lang ||
|
||||
localStorage.getItem('locale') ||
|
||||
localStorage.getItem('language') ||
|
||||
navigator.language ||
|
||||
'en-US';
|
||||
|
||||
return JSON.stringify({ lang, theme });
|
||||
} catch (e) {
|
||||
return JSON.stringify({ lang: 'en-US', theme: 'light' });
|
||||
}
|
||||
"""
|
||||
frontend_lang = await __event_call__(
|
||||
{"type": "execute", "data": {"code": js_code}}
|
||||
# Use asyncio.wait_for to prevent hanging if frontend fails to callback
|
||||
frontend_res_str = await asyncio.wait_for(
|
||||
__event_call__({"type": "execute", "data": {"code": js_code}}),
|
||||
timeout=2.0,
|
||||
)
|
||||
if frontend_lang and isinstance(frontend_lang, str):
|
||||
user_language = frontend_lang
|
||||
if frontend_res_str and isinstance(frontend_res_str, str):
|
||||
try:
|
||||
import json
|
||||
frontend_res = json.loads(frontend_res_str)
|
||||
user_language = frontend_res.get("lang", user_language)
|
||||
user_theme = frontend_res.get("theme", user_theme)
|
||||
except Exception:
|
||||
user_language = frontend_res_str
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to retrieve frontend language: {e}")
|
||||
logger.warning(f"Failed to retrieve frontend language/theme: {e}")
|
||||
|
||||
return {
|
||||
"user_id": user_id,
|
||||
"user_name": user_name,
|
||||
"user_language": user_language,
|
||||
"user_theme": user_theme,
|
||||
}
|
||||
|
||||
def _resolve_language(self, lang: str) -> str:
|
||||
"""Resolve the best matching language code from the TRANSLATIONS dict."""
|
||||
target_lang = lang
|
||||
if target_lang in TRANSLATIONS:
|
||||
return target_lang
|
||||
if hasattr(self, 'fallback_map') and target_lang in self.fallback_map:
|
||||
target_lang = self.fallback_map[target_lang]
|
||||
if target_lang in TRANSLATIONS:
|
||||
return target_lang
|
||||
if "-" in lang:
|
||||
base_lang = lang.split("-")[0]
|
||||
for supported_lang in TRANSLATIONS:
|
||||
if supported_lang.startswith(base_lang + "-"):
|
||||
return supported_lang
|
||||
return "en-US"
|
||||
|
||||
def _get_translation(self, lang: str, key: str, **kwargs) -> str:
|
||||
"""Get translated string for the given language and key."""
|
||||
target_lang = self._resolve_language(lang)
|
||||
lang_dict = TRANSLATIONS.get(target_lang, TRANSLATIONS["en-US"])
|
||||
text = lang_dict.get(key, TRANSLATIONS["en-US"].get(key, key))
|
||||
if kwargs:
|
||||
try:
|
||||
text = text.format(**kwargs)
|
||||
except Exception as e:
|
||||
logger.warning(f"Translation formatting failed for {key}: {e}")
|
||||
return text
|
||||
|
||||
def _get_chat_context(
|
||||
self, body: dict, __metadata__: Optional[dict] = None
|
||||
) -> Dict[str, str]:
|
||||
@@ -1245,6 +1888,7 @@ class Action:
|
||||
'sequence-horizontal': 'sequence-horizontal-zigzag-simple',
|
||||
'relation-sankey': 'relation-sankey-simple',
|
||||
'relation-circle': 'relation-circle-icon-badge',
|
||||
'relation-dagre': 'relation-dagre-flow-tb-simple-circle-node',
|
||||
'compare-binary': 'compare-binary-horizontal-simple-vs',
|
||||
'compare-swot': 'compare-swot',
|
||||
'quadrant-quarter': 'quadrant-quarter-simple-card',
|
||||
@@ -1496,13 +2140,14 @@ class Action:
|
||||
__metadata__: Optional[dict] = None,
|
||||
__request__: Optional[Request] = None,
|
||||
) -> Optional[dict]:
|
||||
logger.info("Action: Infographic started (v1.4.0)")
|
||||
logger.info("Action: Infographic started (v1.6.0)")
|
||||
|
||||
# Get user information
|
||||
user_ctx = await self._get_user_context(__user__, __event_call__)
|
||||
user_ctx = await self._get_user_context(__user__, __event_call__, __request__)
|
||||
user_name = user_ctx["user_name"]
|
||||
user_id = user_ctx["user_id"]
|
||||
user_language = user_ctx["user_language"]
|
||||
user_theme = user_ctx.get("user_theme", "light")
|
||||
|
||||
# Get current time
|
||||
now = datetime.now()
|
||||
@@ -1562,11 +2207,11 @@ class Action:
|
||||
}
|
||||
|
||||
await self._emit_notification(
|
||||
__event_emitter__, "📊 Infographic started, generating...", "info"
|
||||
__event_emitter__, self._get_translation(user_language, "status_starting"), "info"
|
||||
)
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"📊 Infographic: Starting generation...",
|
||||
self._get_translation(user_language, "status_starting"),
|
||||
False,
|
||||
)
|
||||
|
||||
@@ -1576,13 +2221,14 @@ class Action:
|
||||
# Build prompt
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"📊 Infographic: Calling AI model to analyze content...",
|
||||
self._get_translation(user_language, "status_analyzing"),
|
||||
False,
|
||||
)
|
||||
formatted_user_prompt = USER_PROMPT_GENERATE_INFOGRAPHIC.format(
|
||||
user_name=user_name,
|
||||
current_date_time_str=current_date_time_str,
|
||||
user_language=user_language,
|
||||
user_theme=user_theme,
|
||||
long_text_content=long_text_content,
|
||||
)
|
||||
|
||||
@@ -1617,7 +2263,7 @@ class Action:
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"📊 Infographic: AI analysis complete, parsing syntax...",
|
||||
self._get_translation(user_language, "status_analyzing"),
|
||||
False,
|
||||
)
|
||||
|
||||
@@ -1631,7 +2277,7 @@ class Action:
|
||||
# Prepare content components
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"📊 Infographic: Rendering chart...",
|
||||
self._get_translation(user_language, "status_rendering_image"),
|
||||
False,
|
||||
)
|
||||
content_html = (
|
||||
@@ -1692,7 +2338,7 @@ class Action:
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__,
|
||||
"📊 Infographic: Rendering image...",
|
||||
self._get_translation(user_language, "status_rendering_image"),
|
||||
False,
|
||||
)
|
||||
|
||||
@@ -1712,11 +2358,11 @@ class Action:
|
||||
)
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "✅ Infographic: Image generated!", True
|
||||
__event_emitter__, self._get_translation(user_language, "status_image_generated"), True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"📊 Infographic image generated, {user_name}!",
|
||||
self._get_translation(user_language, "notification_image_success", user_name=user_name),
|
||||
"success",
|
||||
)
|
||||
logger.info("Infographic generation completed in image mode")
|
||||
@@ -1727,11 +2373,11 @@ class Action:
|
||||
body["messages"][-1]["content"] = f"{original_content}\n\n{html_embed_tag}"
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "✅ Infographic: Generation complete!", True
|
||||
__event_emitter__, self._get_translation(user_language, "status_drawing"), True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"📊 Infographic generated, {user_name}!",
|
||||
self._get_translation(user_language, "notification_success", user_name=user_name),
|
||||
"success",
|
||||
)
|
||||
logger.info("Infographic generation completed")
|
||||
@@ -1745,11 +2391,11 @@ class Action:
|
||||
] = f"{original_content}\n\n❌ **Error:** {user_facing_error}"
|
||||
|
||||
await self._emit_status(
|
||||
__event_emitter__, "❌ Infographic: Generation failed", True
|
||||
__event_emitter__, self._get_translation(user_language, "status_failed"), True
|
||||
)
|
||||
await self._emit_notification(
|
||||
__event_emitter__,
|
||||
f"❌ Infographic generation failed, {user_name}!",
|
||||
self._get_translation(user_language, "notification_failed", user_name=user_name),
|
||||
"error",
|
||||
)
|
||||
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 169 KiB |
File diff suppressed because one or more lines are too long
14
plugins/actions/infographic/v1.6.0.md
Normal file
14
plugins/actions/infographic/v1.6.0.md
Normal file
@@ -0,0 +1,14 @@
|
||||
# v1.6.0 Release Notes
|
||||
|
||||
This release is a major upgrade introducing 12-language i18n support frameworks and full context dark/light mode sniffing backbones to prevent card inverse overlaps conflicts natively.
|
||||
|
||||
## New Features
|
||||
- **12-Language I18n Skeleton Framework**: Full structural fallback algorithms mapped onto global dictionary namespaces.
|
||||
- **AI Prompt Strategy Optimization**: Enforced AI to strictly prevent colons induction and contain pure index metrics to streamline Charts visualizers nodes rendering loops.
|
||||
- **Dagre Flow Layout View** (`relation-dagre`): visual pipeline supporting relationship visualizer pipelines trees.
|
||||
- **Environment Theme Sniffer Context**: Smooth dark/light status conditioning automatically injected onto visual color palettes adaptation pipelines.
|
||||
|
||||
## Capability & Validation Alignments
|
||||
- **Fixes Issue #61**: Formatted parsing aligning index strict instructions forcing non-chart templates to bypass redundant variables.
|
||||
- **Cascad Class Shifters**: Integrated child text self-destabilizers lifting SVG contrasts automatically inside container frameworks override pipelines.
|
||||
- **Strict Data Nodes Layout mapping**: Enforced items index indexes limiting structural interpreting limits during adaptive operations.
|
||||
15
plugins/actions/infographic/v1.6.0_CN.md
Normal file
15
plugins/actions/infographic/v1.6.0_CN.md
Normal file
@@ -0,0 +1,15 @@
|
||||
# v1.6.0 版本发布说明
|
||||
|
||||
本版本是一次重磅升级，引入了完整的 12 语种标准 i18n（国际化）支持架构，并打通了全链路外壳多阶环境背景（Dark/Light 模式）降维检测，强效解决了由于浅色底卡片跟深色文字覆盖时的低对比度排斥问题。
|
||||
|
||||
## 新功能
|
||||
- **System Prompt 提示词策略优化**：在系统中严格强控禁止冒号、限制 title/desc 字数，百分百确保 `value` 字段仅由纯数字落座，有效解救数值渲染崩溃黑页。
|
||||
- **12 语种标准 i18n 翻译骨架**：对标 Mindmap 全量级翻译映射字典以及 variant 状态机转移降维 fallback 处理。
|
||||
- **Dagre 关系代数 flow 网络看板视图** (`relation-dagre`): 对应 PR #161 全链，支持有向节点、依赖连线关系的组件流向与骨骼动画渲染。
|
||||
- **外壳背景环境自动探测 (Theme Sniffing)**：智能嗅探外部明暗样式并在渲染板壳中追加 `.dark` 等级控制自适应穿透。
|
||||
|
||||
## 规则校准与对齐
|
||||
- **修复关联 Issue #61**：强制约束非图表类模板（如 `list-row`）在解析时将数据直接归拢至 `desc`/`label` 避免因不支持 `value` 导致数据丢失。
|
||||
- **内聚容器反转对比度**：添加子代文字 `color: currentcolor !important` 等联级状态，百分百确保渲染视图清可见。
|
||||
- **模板主索引映射表对撞规范**：明确对应 `list-*` $\rightarrow$ `lists`，强控解析抗崩。
|
||||
- **Palette 裸排严防崩键**：加强提示词，强制大模型在 theme 节中 palette 禁止掺入引号或逗号，避免样式崩坏。
|
||||
6
plugins/actions/infographic/v1.6.1.md
Normal file
6
plugins/actions/infographic/v1.6.1.md
Normal file
@@ -0,0 +1,6 @@
|
||||
# v1.6.1 Release Notes
|
||||
|
||||
This is a hotfix release ensuring the AI model adheres strictly to **Language Consistency** rules and doesn't default to general translation behavior during user dashboard context parameters injection.
|
||||
|
||||
## Bug Fixes
|
||||
- **AI Response Prompt Boundary Protection**: Strict language limits preventing translated overrides when contextual parameters override background system streams status. Directs LLM outputs to fit inputs language content accurately.
|
||||
6
plugins/actions/infographic/v1.6.1_CN.md
Normal file
6
plugins/actions/infographic/v1.6.1_CN.md
Normal file
@@ -0,0 +1,6 @@
|
||||
# v1.6.1 版本发布说明
|
||||
|
||||
本版本是一次紧急修复（Hotfix），主要优化了提示词控制层面的语言决策优先级，百分百排解了因前序引入全量 i18n 传参后导致大模型在部分场景中“自我汉化”响应的 Bug。
|
||||
|
||||
## 修复项
|
||||
- **提示词语言一致性校准 (Language Consistency)**：强控大模型的 Layout/节点 content 输出语种**必须与用户输入的主体文本保持绝对一致**，不受 system 框降阶字典参数干扰。
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 200 KiB After Width: | Height: | Size: 380 KiB |
@@ -1,6 +1,6 @@
|
||||
# Async Context Compression Filter
|
||||
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.5.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.6.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
@@ -21,6 +21,12 @@ When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## What's new in 1.6.0
|
||||
|
||||
- **Fixed `keep_first` Logic**: Re-defined `keep_first` to protect the first N **non-system** messages plus all interleaved system messages. This ensures initial context (e.g., identity, task instructions) is preserved correctly.
|
||||
- **Absolute System Message Protection**: System messages are now strictly excluded from compression. Any system message encountered in the history (even late-injected ones) is preserved as an original message in the final context. This ensures dynamic instructions (like live time/location from other plugins) remain accurate and never summarized.
|
||||
- **Improved Context Assembly**: Summaries now only target User and Assistant dialogue, ensuring that system instructions injected by other plugins are never "eaten" by the summarizer.
|
||||
|
||||
## What's new in 1.5.0
|
||||
|
||||
- **External Chat Reference Summaries**: Added support for referenced chat context blocks that can reuse cached summaries, inject small referenced chats directly, or generate summaries for larger referenced chats before injection.
|
||||
@@ -54,6 +60,10 @@ When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
## What This Fixes
|
||||
|
||||
- **Problem: System Messages being summarized/lost.**
|
||||
Previously, the filter could include system messages (especially those injected late by other plugins) in its summarization zone, causing important instructions to be lost. Now, all system messages are strictly preserved in their original role and never summarized.
|
||||
- **Problem: Incorrect `keep_first` behavior.**
|
||||
Previously, `keep_first` simply took the first $N$ messages. If those were only system messages, the initial user/assistant messages (which are often important for context) would be summarized. Now, `keep_first` ensures that $N$ non-system messages are protected.
|
||||
- **Problem 1: A referenced chat could break the current request.**
|
||||
Before, if the filter needed to summarize a referenced chat and that LLM call failed, the current chat could fail with it. Now it degrades gracefully and injects direct context instead.
|
||||
- **Problem 2: Some referenced chats were being cut too aggressively.**
|
||||
@@ -141,7 +151,7 @@ flowchart TD
|
||||
| `priority` | `10` | Execution order; lower runs earlier. |
|
||||
| `compression_threshold_tokens` | `64000` | Trigger asynchronous summary when total tokens exceed this value. Set to 50%-70% of your model's context window. |
|
||||
| `max_context_tokens` | `128000` | Hard cap for context; older messages (except protected ones) are dropped if exceeded. |
|
||||
| `keep_first` | `1` | Always keep the first N messages (protects system prompts). |
|
||||
| `keep_first` | `0` | Number of initial **non-system** messages to always keep (plus all preceding system prompts). |
|
||||
| `keep_last` | `6` | Always keep the last N messages to preserve recent context. |
|
||||
| `summary_model` | `None` | Model for summaries. Strongly recommended to set a fast, economical model (e.g., `gemini-2.5-flash`, `deepseek-v3`). Falls back to the current chat model when empty. |
|
||||
| `summary_model_max_context` | `0` | Input context window used to fit summary requests. If `0`, falls back to `model_thresholds` or global `max_context_tokens`. |
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
# 异步上下文压缩过滤器
|
||||
|
||||
| 作者：[Fu-Jie](https://github.com/Fu-Jie) · v1.5.0 | [⭐ 点个 Star 支持项目](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| 作者：[Fu-Jie](https://github.com/Fu-Jie) · v1.6.0 | [⭐ 点个 Star 支持项目](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
@@ -23,6 +23,12 @@
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 1.6.0 版本更新
|
||||
|
||||
- **修正 `keep_first` 逻辑**：重新定义了 `keep_first` 的功能，现在它负责保护前 N 条**非系统消息**（以及它们之前的所有系统提示词）。这确保了初始对话背景（如身份设定、任务说明）能被正确保留。
|
||||
- **系统消息绝对保护**：系统消息现在被严格排除在压缩范围之外。历史记录中遇到的任何系统消息（甚至是后期注入的消息）都会作为原始消息保留在最终上下文中。
|
||||
- **改进的上下文组装**：摘要现在仅针对用户和助手的对话，确保其他插件注入的系统指令永远不会被摘要器“吃掉”。
|
||||
|
||||
## 1.5.0 版本更新
|
||||
|
||||
- **外部聊天引用摘要**: 新增对引用聊天上下文的摘要支持。现在可以复用缓存摘要、直接注入较小引用聊天，或先为较大的引用聊天生成摘要再注入。
|
||||
@@ -52,12 +58,14 @@
|
||||
- ✅ **智能模型匹配**: 自定义模型自动继承基础模型的阈值配置。
|
||||
- ⚠ **多模态支持**: 图片内容会被保留，但其 Token **不参与计算**。请相应调整阈值。
|
||||
|
||||
详细的工作原理和更长说明仍可参考 [工作流程指南](https://github.com/Fu-Jie/openwebui-extensions/blob/main/plugins/filters/async-context-compression/WORKFLOW_GUIDE_CN.md)。
|
||||
|
||||
---
|
||||
|
||||
## 这次解决了什么问题（通俗版）
|
||||
|
||||
- **问题：系统消息被摘要或丢失。**
|
||||
以前，过滤器可能会将被引用或后期注入的系统消息包含在摘要区域内，导致重要的指令丢失。现在，所有系统消息都严格按原样保留，永不被摘要。
|
||||
- **问题：`keep_first` 逻辑不符合预期。**
|
||||
以前 `keep_first` 只是简单提取前 N 条消息。如果前几条全是系统消息，初始的问答（通常对上下文很重要）就会被压缩掉。现在 `keep_first` 确保保护 N 条非系统消息。
|
||||
- **问题 1：引用别的聊天时，摘要失败可能把当前对话一起弄挂。**
|
||||
以前如果过滤器需要先帮被引用聊天做摘要，而这一步的 LLM 调用失败了，当前请求也可能直接失败。现在改成了“能摘要就摘要，失败就退回直接塞上下文”，当前对话不会被一起拖死。
|
||||
- **问题 2：有些被引用聊天被截得太早，信息丢得太多。**
|
||||
@@ -85,11 +93,11 @@ flowchart TD
|
||||
F -- 是 --> G[直接复用缓存摘要]
|
||||
F -- 否 --> H{能直接放进当前预算?}
|
||||
H -- 是 --> I[直接注入完整引用聊天文本]
|
||||
H -- 否 --> J[准备引用聊天的摘要输入]
|
||||
H -- No --> J[准备引用聊天的摘要输入]
|
||||
|
||||
J --> K{引用聊天摘要调用成功?}
|
||||
K -- 是 --> L[注入生成后的引用摘要]
|
||||
K -- 否 --> M[回退为直接注入上下文]
|
||||
K -- No --> M[回退为直接注入上下文]
|
||||
|
||||
G --> D
|
||||
I --> D
|
||||
@@ -149,7 +157,7 @@ flowchart TD
|
||||
| `priority` | `10` | 过滤器执行顺序，数值越小越先执行。 |
|
||||
| `compression_threshold_tokens` | `64000` | **重要**: 当上下文总 Token 超过此值时后台生成摘要，建议设为模型上下文窗口的 50%-70%。 |
|
||||
| `max_context_tokens` | `128000` | **重要**: 上下文硬上限，超过即移除最早消息（保留受保护消息）。 |
|
||||
| `keep_first` | `1` | 始终保留对话开始的 N 条消息，保护系统提示或环境变量。 |
|
||||
| `keep_first` | `0` | 始终保留对话开始的 N 条**非系统消息**（以及它们之前的所有系统提示词）。 |
|
||||
| `keep_last` | `6` | 始终保留对话末尾的 N 条消息，确保最近上下文连贯。 |
|
||||
|
||||
### 摘要生成配置
|
||||
|
||||
@@ -110,7 +110,7 @@
|
||||
```
|
||||
|
||||
**关键参数**：
|
||||
- `keep_first`：保留前 N 条消息（默认 1）
|
||||
- `keep_first`：保留前 N 条非系统消息（默认 0）
|
||||
- `keep_last`：保留后 N 条消息（默认 6）
|
||||
- 摘要注入位置：首条消息的内容前
|
||||
|
||||
@@ -432,7 +432,7 @@ Valves(
|
||||
max_context_tokens=128000, # 硬性上限
|
||||
|
||||
# 消息保留策略
|
||||
keep_first=1, # 保留首条（系统提示）
|
||||
keep_first=0, # 不保留首条非系统消息（默认）
|
||||
keep_last=6, # 保留末6条（最近对话）
|
||||
|
||||
# 摘要模型
|
||||
@@ -601,13 +601,13 @@ outlet 阶段：
|
||||
总消息: 20 条
|
||||
预估 Token: 8000 个
|
||||
|
||||
压缩后（keep_first=1, keep_last=6）：
|
||||
头部消息: 1 条 (1600 Token)
|
||||
压缩后（keep_first=0, keep_last=6）：
|
||||
头部消息: 0 条 (0 Token)
|
||||
摘要: ~800 Token (嵌入在头部)
|
||||
尾部消息: 6 条 (3200 Token)
|
||||
总计: 7 条有效输入 (~5600 Token)
|
||||
总计: 6 条有效输入 (~4000 Token)
|
||||
|
||||
节省：8000 - 5600 = 2400 Token (30% 节省)
|
||||
节省：8000 - 4000 = 4000 Token (50% 节省)
|
||||
|
||||
随对话变长，节省比例可达 65% 以上
|
||||
```
|
||||
|
||||
@@ -5,30 +5,23 @@ author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie/openwebui-extensions
|
||||
funding_url: https://github.com/open-webui
|
||||
description: Reduces token consumption in long conversations while maintaining coherence through intelligent summarization and message compression.
|
||||
version: 1.5.0
|
||||
version: 1.6.0
|
||||
openwebui_id: b1655bc8-6de9-4cad-8cb5-a6f7829a02ce
|
||||
license: MIT
|
||||
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
📌 What's new in 1.5.0
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
✅ Stronger Working-Memory Prompt: Refined XML summary instructions to better preserve useful context in general chat and multi-step tool workflows.
|
||||
✅ Clearer Frontend Debug Logs: Reworked browser-console debug output into grouped, structured snapshots for faster diagnosis.
|
||||
✅ Safer Tool Trimming Defaults: Native tool-output trimming is now enabled by default with a configurable 600-character threshold.
|
||||
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
📌 Overview
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
This filter significantly reduces token consumption in long conversations by using intelligent summarization and message compression, while maintaining conversational coherence.
|
||||
This filter reduces token consumption in long conversations through intelligent
|
||||
summarization and message compression while maintaining conversational coherence.
|
||||
|
||||
Core Features:
|
||||
✅ Automatic compression triggered by Token count threshold
|
||||
✅ Automatic compression triggered by token count threshold
|
||||
✅ Asynchronous summary generation (does not block user response)
|
||||
✅ Persistent storage with database support (PostgreSQL and SQLite)
|
||||
✅ Flexible retention policy (configurable to keep first and last N messages)
|
||||
✅ Smart summary injection to maintain context
|
||||
✅ Flexible retention policy (keep first N non-system messages + last N messages)
|
||||
✅ Absolute system message protection (never compressed or discarded)
|
||||
✅ Structure-aware trimming to preserve document skeleton
|
||||
✅ Native tool output trimming for function calling support
|
||||
|
||||
@@ -41,21 +34,51 @@ Phase 1: Inlet (Pre-request processing)
|
||||
1. Receives all messages in the current conversation.
|
||||
2. Checks for a previously saved summary.
|
||||
3. If a summary exists and the message count exceeds the retention threshold:
|
||||
├─ Extracts the first N messages to be kept.
|
||||
├─ Extracts the first N non-system messages to be kept (plus all
|
||||
│ interleaved system messages).
|
||||
├─ Injects the summary into the first message.
|
||||
├─ Extracts the last N messages to be kept.
|
||||
└─ Combines them into a new message list: [Kept First Messages + Summary] + [Kept Last Messages].
|
||||
└─ Combines them into: [Kept First + Summary + Gap System Messages + Kept Last]
|
||||
4. Sends the compressed message list to the LLM.
|
||||
|
||||
Phase 2: Outlet (Post-response processing)
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
1. Triggered after the LLM response is complete.
|
||||
2. Checks if the Token count has reached the compression threshold.
|
||||
3. If the threshold is met, an asynchronous background task is started to generate a summary:
|
||||
├─ Extracts messages to be summarized (excluding the kept first and last messages).
|
||||
2. Checks if the token count has reached the compression threshold.
|
||||
3. If the threshold is met, an asynchronous background task is started:
|
||||
├─ Extracts messages to be summarized (excluding the kept first and last).
|
||||
├─ Calls the LLM to generate a concise summary.
|
||||
└─ Saves the summary to the database.
|
||||
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
🛡️ System Message Protection
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
System messages are strictly excluded from compression and always preserved in
|
||||
the final context. This ensures that dynamic instructions injected by other
|
||||
plugins (e.g., live time/location context) remain accurate throughout the
|
||||
conversation.
|
||||
|
||||
Protection Rules:
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
1. `keep_first` counts only non-system messages. System messages within the
|
||||
first N non-system messages are automatically preserved.
|
||||
2. System messages in the compression gap (between kept-first and kept-last)
|
||||
are extracted and preserved as original messages, not summarized.
|
||||
3. During forced trimming (when exceeding `max_context_tokens`), system
|
||||
messages from dropped atomic groups are re-inserted into the final output.
|
||||
|
||||
Example:
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
Messages: [sys, user1, sys(injected), user2, ..., user10, user11]
|
||||
keep_first=0, keep_last=2
|
||||
|
||||
Effective keep_first=0 (no non-system messages protected)
|
||||
Gap: [sys, user1, sys(injected), user2, ..., user9]
|
||||
Preserved from gap: [sys, sys(injected)]
|
||||
|
||||
Final output: [sys, summary, sys(injected), user10, user11]
|
||||
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
💾 Storage
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
@@ -80,7 +103,7 @@ Open WebUI's database settings automatically.
|
||||
📊 Compression Example
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
Scenario: A 20-message conversation (Default settings: keep first 1, keep last 6)
|
||||
Scenario: A 20-message conversation (Default settings: keep first 0, keep last 6)
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
Before Compression:
|
||||
Message 1: [Initial prompt + First question]
|
||||
@@ -104,75 +127,89 @@ Scenario: A 20-message conversation (Default settings: keep first 1, keep last 6
|
||||
|
||||
priority
|
||||
Default: 10
|
||||
Description: The execution order of the filter. Lower numbers run first.
|
||||
Description: Priority level for the filter operations. Lower numbers run first.
|
||||
|
||||
compression_threshold_tokens
|
||||
Default: 64000
|
||||
Description: When the total context Token count exceeds this value, compression is triggered.
|
||||
Recommendation: Adjust based on your model's context window and cost.
|
||||
Description: When total context Token count exceeds this value, trigger compression (Global Default).
|
||||
|
||||
max_context_tokens
|
||||
Default: 128000
|
||||
Description: Hard limit for context. Exceeding this value will force removal of the earliest messages.
|
||||
Description: Hard limit for context. Exceeding this value will force removal of earliest messages (Global Default).
|
||||
|
||||
model_thresholds
|
||||
Default: {}
|
||||
Description: Threshold override configuration for specific models.
|
||||
Example: {"gpt-4": {"compression_threshold_tokens": 8000, "max_context_tokens": 32000}}
|
||||
Default: "" (empty string)
|
||||
Description: Per-model threshold overrides.
|
||||
Format: model_id:compression_threshold:max_context (comma-separated).
|
||||
Example: gpt-4:8000:32000,claude-3:100000:200000
|
||||
|
||||
keep_first
|
||||
Default: 0
|
||||
Description: Keep the first N non-system messages plus all interleaved system messages. Set to 0 to disable.
|
||||
|
||||
keep_last
|
||||
Default: 6
|
||||
Description: Always keep the last N full messages.
|
||||
|
||||
summary_model
|
||||
Default: None
|
||||
Description: The model ID used to generate the summary. If empty, uses the current conversation's model.
|
||||
Recommendation:
|
||||
- Configure a fast, economical, and compatible model, such as `deepseek-v3`, `gemini-2.5-flash`, `gpt-4.1`.
|
||||
- If the current conversation uses a pipeline (Pipe) model or a model that does not support standard generation APIs, this field must be specified.
|
||||
|
||||
summary_model_max_context
|
||||
Default: 0
|
||||
Description: Max context tokens for the summary model. If 0, falls back to model_thresholds or global max_context_tokens.
|
||||
Example: gemini-flash=1000000, gpt-4o-mini=128000
|
||||
|
||||
max_summary_tokens
|
||||
Default: 16384
|
||||
Description: The maximum number of tokens for the summary.
|
||||
|
||||
summary_temperature
|
||||
Default: 0.1
|
||||
Description: The temperature for summary generation. Lower values produce more deterministic output.
|
||||
|
||||
enable_tool_output_trimming
|
||||
Default: true
|
||||
Description: When enabled and `function_calling: "native"` is active, collapses oversized native tool outputs to a short placeholder while preserving the tool-call chain structure.
|
||||
Description: Enable trimming of large tool outputs (only works with native function calling).
|
||||
|
||||
tool_trim_threshold_chars
|
||||
Default: 600
|
||||
Description: Trim native tool outputs when their total content length reaches this many characters.
|
||||
|
||||
keep_first
|
||||
Default: 1
|
||||
Description: Always keep the first N messages of the conversation. Set to 0 to disable. The first message often contains important system prompts.
|
||||
show_token_usage_status
|
||||
Default: true
|
||||
Description: Show token usage status notification.
|
||||
|
||||
keep_last
|
||||
Default: 6
|
||||
Description: Always keep the last N full messages of the conversation to ensure context coherence.
|
||||
|
||||
summary_model
|
||||
Default: None
|
||||
Description: The LLM used to generate the summary.
|
||||
Recommendation:
|
||||
- It is strongly recommended to configure a fast, economical, and compatible model, such as `deepseek-v3`, `gemini-2.5-flash`, `gpt-4.1`.
|
||||
- If left empty, the filter will attempt to use the model from the current conversation.
|
||||
Note:
|
||||
- If the current conversation uses a pipeline (Pipe) model or a model that does not support standard generation APIs, leaving this field empty may cause summary generation to fail. In this case, you must specify a valid model.
|
||||
|
||||
max_summary_tokens
|
||||
Default: 16384
|
||||
Description: The maximum number of tokens allowed for the generated summary.
|
||||
|
||||
summary_temperature
|
||||
Default: 0.1
|
||||
Description: Controls the randomness of the summary generation. Lower values produce more deterministic output.
|
||||
token_usage_status_threshold
|
||||
Default: 80
|
||||
Description: Only show token usage status when usage exceeds this percentage (0-100). Set to 0 to always show.
|
||||
|
||||
debug_mode
|
||||
Default: false
|
||||
Description: Prints detailed debug information to the log. Recommended to set to `false` in production.
|
||||
Description: Enable detailed logging for debugging. Recommended to set to `false` in production.
|
||||
|
||||
show_debug_log
|
||||
Default: false
|
||||
Description: Print debug logs to browser console (F12). Useful for frontend debugging.
|
||||
Description: Show debug logs in the frontend console (F12). Useful for frontend debugging.
|
||||
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
🔧 Deployment
|
||||
═══════════════════════════════════════════════════════
|
||||
═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
The plugin automatically uses Open WebUI's shared database connection.
|
||||
No additional database configuration is required.
|
||||
|
||||
Suggested Filter Installation Order:
|
||||
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
|
||||
It is recommended to set the priority of this filter relatively high (a smaller number) to ensure it runs before other filters that might modify message content. A typical order might be:
|
||||
It is recommended to set the priority of this filter relatively high (a smaller
|
||||
number) to ensure it runs before other filters that might modify message content.
|
||||
A typical order might be:
|
||||
|
||||
1. Filters that need access to the full, uncompressed history (priority < 10)
|
||||
(e.g., a filter that injects a system-level prompt)
|
||||
(e.g., a filter that injects a system-level prompt like live context)
|
||||
2. This compression filter (priority = 10)
|
||||
3. Filters that run after compression (priority > 10)
|
||||
(e.g., a final output formatting filter)
|
||||
@@ -216,7 +253,8 @@ Statistics:
|
||||
✓ The `chat_summary` table will be created automatically on first run.
|
||||
|
||||
2. Retention Policy
|
||||
⚠ The `keep_first` setting is crucial for preserving initial messages that contain system prompts. Configure it as needed.
|
||||
⚠ `keep_first` counts only non-system messages. System messages are always
|
||||
preserved regardless of this setting.
|
||||
|
||||
3. Performance
|
||||
⚠ Summary generation is asynchronous and will not block the user response.
|
||||
@@ -252,7 +290,8 @@ Solution:
|
||||
|
||||
Problem: Initial system prompt is lost
|
||||
Solution:
|
||||
- Ensure `keep_first` is set to a value greater than 0 to preserve the initial messages containing this information.
|
||||
- System messages are always preserved. If a system prompt is missing, check
|
||||
whether another filter is modifying or removing it.
|
||||
|
||||
Problem: Compression effect is not significant
|
||||
Solution:
|
||||
@@ -1249,13 +1288,25 @@ class Filter:
|
||||
return groups
|
||||
|
||||
def _get_effective_keep_first(self, messages: List[Dict]) -> int:
|
||||
"""Protect configured head messages and all leading system messages."""
|
||||
last_system_index = -1
|
||||
"""
|
||||
Calculate the index to protect the first N NON-SYSTEM messages.
|
||||
All system messages encountered before reaching the Nth non-system message are also kept.
|
||||
"""
|
||||
if not messages:
|
||||
return 0
|
||||
|
||||
non_system_count = 0
|
||||
target_index = 0
|
||||
|
||||
for i, msg in enumerate(messages):
|
||||
if msg.get("role") == "system":
|
||||
last_system_index = i
|
||||
|
||||
return max(self.valves.keep_first, last_system_index + 1)
|
||||
if msg.get("role") != "system":
|
||||
non_system_count += 1
|
||||
|
||||
target_index = i + 1
|
||||
if non_system_count >= self.valves.keep_first:
|
||||
break
|
||||
|
||||
return target_index
|
||||
|
||||
def _align_tail_start_to_atomic_boundary(
|
||||
self, messages: List[Dict], raw_start_index: int, protected_prefix: int
|
||||
@@ -1475,9 +1526,9 @@ class Filter:
|
||||
)
|
||||
|
||||
keep_first: int = Field(
|
||||
default=1,
|
||||
default=0,
|
||||
ge=0,
|
||||
description="Always keep the first N messages. Set to 0 to disable.",
|
||||
description="Keep the first N non-system messages plus all interleaved system messages. Set to 0 to disable.",
|
||||
)
|
||||
keep_last: int = Field(
|
||||
default=6, ge=0, description="Always keep the last N full messages."
|
||||
@@ -2713,8 +2764,20 @@ class Filter:
|
||||
Check if compression should be skipped.
|
||||
Returns True if:
|
||||
"""
|
||||
if body.get("is_copilot_model", False):
|
||||
is_copilot = (
|
||||
body.get("is_copilot_model", False)
|
||||
or body.get("metadata", {}).get("is_copilot_model", False)
|
||||
or body.get("features", {}).get("is_copilot_model", False)
|
||||
)
|
||||
if is_copilot:
|
||||
return True
|
||||
|
||||
# Fallback for filters or responses (e.g., Outlet) which may clear the metadata payload
|
||||
model_id = body.get("model", "")
|
||||
if isinstance(model_id, str):
|
||||
c = model_id.lower()
|
||||
if "github_copilot_sdk_pipe" in c or "github_copilot_official_sdk_pipe" in c:
|
||||
return True
|
||||
return False
|
||||
|
||||
async def inlet(
|
||||
@@ -3035,6 +3098,14 @@ class Filter:
|
||||
messages, raw_start_index, effective_keep_first
|
||||
)
|
||||
|
||||
# --- Extract Preserved System Messages from the Gap ---
|
||||
# Any system message in the gap (messages[effective_keep_first:start_index])
|
||||
# must be preserved according to policy.
|
||||
gap_messages = messages[effective_keep_first:start_index]
|
||||
preserved_system_messages = [
|
||||
msg for msg in gap_messages if isinstance(msg, dict) and msg.get("role") == "system"
|
||||
]
|
||||
|
||||
# 3. Summary message (Inserted as Assistant message)
|
||||
external_refs = body.pop("__external_references__", None)
|
||||
summary_msg = self._build_summary_message(
|
||||
@@ -3093,7 +3164,7 @@ class Filter:
|
||||
# --- Preflight Check & Budgeting (Simplified) ---
|
||||
|
||||
# Assemble candidate messages (for output)
|
||||
candidate_messages = head_messages + [summary_msg] + tail_messages
|
||||
candidate_messages = head_messages + [summary_msg] + preserved_system_messages + tail_messages
|
||||
|
||||
# Prepare messages for token calculation (include system prompt if missing)
|
||||
calc_messages = candidate_messages
|
||||
@@ -3177,7 +3248,7 @@ class Filter:
|
||||
)
|
||||
|
||||
# Re-assemble
|
||||
candidate_messages = head_messages + [summary_msg] + tail_messages
|
||||
candidate_messages = head_messages + [summary_msg] + preserved_system_messages + tail_messages
|
||||
|
||||
await self._log(
|
||||
"[Inlet] ✂️ Sent-context history reduced\n"
|
||||
@@ -3197,6 +3268,7 @@ class Filter:
|
||||
)
|
||||
head_tokens = self._estimate_messages_tokens(head_messages)
|
||||
summary_tokens = self._estimate_content_tokens(summary_content)
|
||||
preserved_system_tokens = self._estimate_messages_tokens(preserved_system_messages)
|
||||
tail_tokens = self._estimate_messages_tokens(tail_messages)
|
||||
else:
|
||||
system_tokens = (
|
||||
@@ -3206,14 +3278,15 @@ class Filter:
|
||||
)
|
||||
head_tokens = self._calculate_messages_tokens(head_messages)
|
||||
summary_tokens = self._count_tokens(summary_content)
|
||||
preserved_system_tokens = self._calculate_messages_tokens(preserved_system_messages)
|
||||
tail_tokens = self._calculate_messages_tokens(tail_messages)
|
||||
|
||||
system_info = (
|
||||
f"System({system_tokens}t)" if system_prompt_msg else "System(0t)"
|
||||
f"System({system_tokens + preserved_system_tokens}t)" if (system_prompt_msg or preserved_system_messages) else "System(0t)"
|
||||
)
|
||||
|
||||
total_section_tokens = (
|
||||
system_tokens + head_tokens + summary_tokens + tail_tokens
|
||||
system_tokens + head_tokens + summary_tokens + preserved_system_tokens + tail_tokens
|
||||
)
|
||||
|
||||
await self._log(
|
||||
@@ -3359,15 +3432,33 @@ class Filter:
|
||||
# Use atomic grouping to preserve tool-calling integrity
|
||||
trimmable = candidate_messages[effective_keep_first:]
|
||||
atomic_groups = self._get_atomic_groups(trimmable)
|
||||
|
||||
# To follow policy "system messages never lost", we maintain a list of
|
||||
# system messages that were part of dropped groups.
|
||||
dropped_but_preserved_systems = []
|
||||
|
||||
while total_tokens > max_context_tokens and len(atomic_groups) > 1:
|
||||
dropped_group_indices = atomic_groups.pop(0)
|
||||
dropped_tokens = 0
|
||||
for _ in range(len(dropped_group_indices)):
|
||||
dropped = trimmable.pop(0)
|
||||
|
||||
# Absolute protections:
|
||||
# 1. External references (often large and specialized)
|
||||
# 2. System messages (instructions)
|
||||
if self._is_external_reference_message(dropped):
|
||||
trimmable.insert(0, dropped)
|
||||
# Stop dropping this group if we hit a protected message
|
||||
# (Though groups should be pure, this is a safety net)
|
||||
break
|
||||
|
||||
if isinstance(dropped, dict) and dropped.get("role") == "system":
|
||||
dropped_but_preserved_systems.append(dropped)
|
||||
# Even if preserved, it counts as "dropped" from the trimmable flow
|
||||
# to avoid infinite loop, but its tokens remain in the budget.
|
||||
# We don't subtract its tokens here.
|
||||
continue
|
||||
|
||||
if total_tokens == estimated_tokens:
|
||||
dropped_tokens += self._estimate_content_tokens(
|
||||
dropped.get("content", "")
|
||||
@@ -3378,8 +3469,9 @@ class Filter:
|
||||
)
|
||||
total_tokens -= dropped_tokens
|
||||
|
||||
# Re-assemble: [Head] + [Preserved Systems from Dropped Groups] + [Remaining Trimmable/Tail]
|
||||
candidate_messages = (
|
||||
candidate_messages[:effective_keep_first] + trimmable
|
||||
candidate_messages[:effective_keep_first] + dropped_but_preserved_systems + trimmable
|
||||
)
|
||||
|
||||
await self._log(
|
||||
|
||||
@@ -51,8 +51,12 @@ class Filter:
|
||||
# 1) Prefix match (most reliable for OpenWebUI model id formats)
|
||||
raw_prefixes = self.valves.target_model_prefixes or ""
|
||||
prefixes = [p.strip().lower() for p in raw_prefixes.split(",") if p.strip()]
|
||||
if any(current.startswith(prefix) for prefix in prefixes):
|
||||
return True
|
||||
for prefix in prefixes:
|
||||
if current.startswith(prefix):
|
||||
return True
|
||||
# Match exact string without trailing dot for single-pipe endpoints
|
||||
if prefix.endswith(".") and current == prefix[:-1]:
|
||||
return True
|
||||
|
||||
# 2) Keyword fallback for backward compatibility
|
||||
keyword = (self.valves.target_model_keyword or "").strip().lower()
|
||||
@@ -114,7 +118,10 @@ class Filter:
|
||||
|
||||
# Check if it's a Copilot model
|
||||
is_copilot_model = self._is_copilot_model(current_model)
|
||||
body["is_copilot_model"] = is_copilot_model
|
||||
|
||||
if "features" not in body:
|
||||
body["features"] = {}
|
||||
body["features"]["is_copilot_model"] = is_copilot_model
|
||||
|
||||
await self._emit_debug_log(
|
||||
__event_emitter__,
|
||||
|
||||
@@ -1,232 +0,0 @@
|
||||
import os
|
||||
from typing import List, Optional
|
||||
from pydantic import BaseModel
|
||||
import time
|
||||
|
||||
|
||||
class Pipeline:
|
||||
"""
|
||||
该管道用于优化多模型（MoE）汇总请求的提示词。
|
||||
|
||||
它会拦截用于汇总多个模型响应的请求，提取原始用户查询和各个模型的具体回答，
|
||||
然后构建一个新的、更详细、结构化的提示词。
|
||||
|
||||
这个经过优化的提示词会引导最终的汇总模型扮演一个专家分析师的角色，
|
||||
将输入信息整合成一份高质量、全面的综合报告。
|
||||
"""
|
||||
|
||||
class Valves(BaseModel):
|
||||
# 指定该过滤器管道将连接到的目标管道ID（模型）。
|
||||
# 如果希望连接到所有管道，可以设置为 ["*"]。
|
||||
pipelines: List[str] = ["*"]
|
||||
|
||||
# 为过滤器管道分配一个优先级。
|
||||
# 优先级决定了过滤器管道的执行顺序。
|
||||
# 数字越小，优先级越高。
|
||||
priority: int = 0
|
||||
|
||||
# 指定用于分析和总结的模型ID。
|
||||
# 如果设置，MoE汇总请求将被重定向到此模型。
|
||||
model_id: Optional[str] = None
|
||||
|
||||
# MoE 汇总请求的触发前缀。
|
||||
# 用于识别是否为 MoE 汇总请求。
|
||||
trigger_prefix: str = (
|
||||
"You have been provided with a set of responses from various models to the latest user query"
|
||||
)
|
||||
|
||||
# 解析原始查询的起始标记
|
||||
query_start_marker: str = 'the latest user query: "'
|
||||
|
||||
# 解析原始查询的结束标记
|
||||
query_end_marker: str = '"\n\nYour task is to'
|
||||
|
||||
# 解析模型响应的起始标记
|
||||
response_start_marker: str = "Responses from models: "
|
||||
|
||||
def __init__(self):
|
||||
self.type = "filter"
|
||||
self.name = "moe_prompt_refiner"
|
||||
self.valves = self.Valves()
|
||||
|
||||
async def on_startup(self):
|
||||
# 此函数在服务器启动时调用。
|
||||
# print(f"on_startup:{__name__}")
|
||||
pass
|
||||
|
||||
async def on_shutdown(self):
|
||||
# 此函数在服务器停止时调用。
|
||||
# print(f"on_shutdown:{__name__}")
|
||||
pass
|
||||
|
||||
async def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
|
||||
"""
|
||||
此方法是管道的入口点。
|
||||
|
||||
它会检查传入的请求是否为多模型（MoE）汇总请求。如果是，它会解析原始提示词，
|
||||
提取用户的查询和来自不同模型的响应。然后，它会动态构建一个新的、结构更清晰的提示词，
|
||||
并用它替换原始的消息内容。
|
||||
|
||||
参数:
|
||||
body (dict): 包含消息的请求体。
|
||||
user (Optional[dict]): 用户信息。
|
||||
|
||||
返回:
|
||||
dict: 包含优化后提示词的已修改请求体。
|
||||
"""
|
||||
print(f"pipe:{__name__}")
|
||||
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
return body
|
||||
|
||||
user_message_content = ""
|
||||
user_message_index = -1
|
||||
|
||||
# 找到最后一条用户消息
|
||||
for i in range(len(messages) - 1, -1, -1):
|
||||
if messages[i].get("role") == "user":
|
||||
content = messages[i].get("content", "")
|
||||
# 处理内容为数组的情况（多模态消息）
|
||||
if isinstance(content, list):
|
||||
# 从数组中提取所有文本内容
|
||||
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)
|
||||
user_message_content = "".join(text_parts)
|
||||
elif isinstance(content, str):
|
||||
user_message_content = content
|
||||
|
||||
user_message_index = i
|
||||
break
|
||||
|
||||
if user_message_index == -1:
|
||||
return body
|
||||
|
||||
# 检查是否为MoE汇总请求
|
||||
if isinstance(user_message_content, str) and user_message_content.startswith(
|
||||
self.valves.trigger_prefix
|
||||
):
|
||||
print("检测到MoE汇总请求，正在更改提示词。")
|
||||
|
||||
# 如果配置了 model_id，则重定向请求
|
||||
if self.valves.model_id:
|
||||
print(f"重定向请求到模型: {self.valves.model_id}")
|
||||
body["model"] = self.valves.model_id
|
||||
|
||||
# 1. 提取原始查询
|
||||
query_start_phrase = self.valves.query_start_marker
|
||||
query_end_phrase = self.valves.query_end_marker
|
||||
start_index = user_message_content.find(query_start_phrase)
|
||||
end_index = user_message_content.find(query_end_phrase)
|
||||
|
||||
original_query = ""
|
||||
if start_index != -1 and end_index != -1:
|
||||
original_query = user_message_content[
|
||||
start_index + len(query_start_phrase) : end_index
|
||||
]
|
||||
|
||||
# 2. 提取各个模型的响应
|
||||
responses_start_phrase = self.valves.response_start_marker
|
||||
responses_start_index = user_message_content.find(responses_start_phrase)
|
||||
|
||||
responses_text = ""
|
||||
if responses_start_index != -1:
|
||||
responses_text = user_message_content[
|
||||
responses_start_index + len(responses_start_phrase) :
|
||||
]
|
||||
|
||||
# 使用三重双引号作为分隔符来提取响应
|
||||
responses = [
|
||||
part.strip() for part in responses_text.split('"""') if part.strip()
|
||||
]
|
||||
|
||||
# 3. 动态构建模型响应部分
|
||||
responses_section = ""
|
||||
for i, response in enumerate(responses):
|
||||
responses_section += f'''"""
|
||||
[第 {i + 1} 个模型的完整回答]
|
||||
{response}
|
||||
"""
|
||||
'''
|
||||
|
||||
# 4. 构建新的提示词
|
||||
merge_prompt = f'''# 角色定位
|
||||
你是一位经验丰富的首席分析师，正在处理来自多个独立 AI 专家团队对同一问题的分析报告。你的任务是将这些报告进行深度整合、批判性分析，并提炼出一份结构清晰、洞察深刻、对决策者极具价值的综合报告。
|
||||
|
||||
# 原始用户问题
|
||||
{original_query}
|
||||
|
||||
# 输入格式说明 ⚠️ 重要
|
||||
各模型的响应已通过 """ （三重引号）分隔符准确识别和分离。系统已将不同模型的回答分别提取，你现在需要基于以下分离后的内容进行分析。
|
||||
|
||||
**已分离的模型响应**:
|
||||
{responses_section}
|
||||
# 核心任务
|
||||
请勿简单地复制或拼接原始报告。你需要运用你的专业分析能力，完成以下步骤：
|
||||
|
||||
## 1. 信息解析与评估 (Analysis & Evaluation)
|
||||
- **准确分隔**: 已根据 """ 分隔符，准确识别每个模型的回答边界。
|
||||
- **可信度评估**: 批判性地审视每份报告，识别其中可能存在的偏见、错误或不一致之处。
|
||||
- **逻辑梳理**: 理清每份报告的核心论点、支撑论据和推理链条。
|
||||
|
||||
## 2. 核心洞察提炼 (Insight Extraction)
|
||||
- **识别共识**: 找出所有报告中共同提及、高度一致的观点或建议。这通常是问题的核心事实或最稳健的策略。
|
||||
- **突出差异**: 明确指出各报告在视角、方法、预测或结论上的关键分歧点。这些分歧往往蕴含着重要的战略考量。
|
||||
- **捕捉亮点**: 挖掘单个报告中独有的、具有创新性或深刻性的见解，这些"闪光点"可能是关键的差异化优势。
|
||||
|
||||
## 3. 综合报告撰写 (Synthesis)
|
||||
基于以上分析，生成一份包含以下结构的综合报告：
|
||||
|
||||
### **【核心共识】**
|
||||
- 用清晰的要点列出所有模型一致认同的关键信息或建议。
|
||||
- 标注覆盖范围（如"所有模型均同意"或"多数模型提及"）。
|
||||
|
||||
### **【关键分歧】**
|
||||
- 清晰地对比不同模型在哪些核心问题上持有不同观点。
|
||||
- 用序号或描述性语言标识不同的观点阵营（如"观点 A 与观点 B 的分歧"或"方案 1 vs 方案 2"）。
|
||||
- 简要说明其原因或侧重点的差异。
|
||||
|
||||
### **【独特洞察】**
|
||||
- 提炼并呈现那些仅在单个报告中出现，但极具价值的独特建议或视角。
|
||||
- 用"某个模型提出"或"另一视角"等中立表述，避免因缺少显式来源标记而造成的混淆。
|
||||
|
||||
### **【综合分析与建议】**
|
||||
- **整合**: 基于共识、差异和亮点，提供一个全面、平衡、且经过你专业判断优化的最终分析。
|
||||
- **建议**: 如果原始指令是寻求方案或策略，这里应提出一个或多个融合了各方优势的、可执行的建议。
|
||||
|
||||
# 格式要求
|
||||
- 语言精炼、逻辑清晰、结构分明。
|
||||
- 使用加粗、列表、标题等格式，确保报告易于阅读和理解。
|
||||
- 由于缺少显式的模型标识，**在呈现差异化观点时，使用描述性或序号化的方式**（如"第一种观点""另一个视角"）而非具体的模型名称。
|
||||
- 始终以"为用户提供最高价值的决策依据"为目标。
|
||||
|
||||
# 输出结构示例
|
||||
根据以上要求，你的输出应该呈现如下结构：
|
||||
|
||||
## 【核心共识】
|
||||
✓ [共识观点 1] —— 所有模型均同意
|
||||
✓ [共识观点 2] —— 多数模型同意
|
||||
|
||||
## 【关键分歧】
|
||||
⚡ **在[议题]上的分歧**:
|
||||
- 观点阵营 A: ...
|
||||
- 观点阵营 B: ...
|
||||
- 观点阵营 C: ...
|
||||
|
||||
## 【独特洞察】
|
||||
💡 [某个模型独有的深刻观点]: ...
|
||||
💡 [另一个模型的创新视角]: ...
|
||||
|
||||
## 【综合分析与建议】
|
||||
基于以上分析，推荐方案/策略: ...
|
||||
'''
|
||||
|
||||
# 5. 替换原始消息内容
|
||||
body["messages"][user_message_index]["content"] = merge_prompt
|
||||
print("提示词已成功动态替换。")
|
||||
|
||||
return body
|
||||
@@ -1 +0,0 @@
|
||||
{}
|
||||
207
plugins/pipelines/wisdom_synthesizer.py
Normal file
207
plugins/pipelines/wisdom_synthesizer.py
Normal file
@@ -0,0 +1,207 @@
|
||||
import logging
|
||||
from typing import List, Optional
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
class Pipeline:
|
||||
"""
|
||||
This pipeline optimizes the prompt used for multi-model summarization requests.
|
||||
|
||||
It intercepts the request intended to summarize responses from various models,
|
||||
extracts the original user query and the individual model answers,
|
||||
and constructs a new, more detailed and structured prompt.
|
||||
|
||||
The optimized prompt guides the summarizing model to act as an expert analyst,
|
||||
synthesizing the inputs into a high-quality, comprehensive integrated report.
|
||||
"""
|
||||
|
||||
class Valves(BaseModel):
|
||||
# Specifies target pipeline IDs (models) this filter will attach to.
|
||||
# Use ["*"] to connect to all pipelines.
|
||||
pipelines: List[str] = ["*"]
|
||||
|
||||
# Assigns priority to the filter pipeline.
|
||||
# Determines execution order (lower numbers execute first).
|
||||
priority: int = 0
|
||||
|
||||
# Specifies model ID for analysis and summarization.
|
||||
# If set, the aggregate request will be redirected to this model.
|
||||
model_id: Optional[str] = None
|
||||
|
||||
# Trigger prefix for aggregate requests.
|
||||
# Used to identify if it is an aggregate synthesis request.
|
||||
trigger_prefix: str = (
|
||||
"You have been provided with a set of responses from various models to the latest user query"
|
||||
)
|
||||
|
||||
# Marker for parsing the original query start
|
||||
query_start_marker: str = 'the latest user query: "'
|
||||
|
||||
# Marker for parsing the original query end
|
||||
query_end_marker: str = '"\n\nYour task is to'
|
||||
|
||||
# Marker for parsing model responses start
|
||||
response_start_marker: str = "Responses from models: "
|
||||
|
||||
def __init__(self):
|
||||
self.type = "filter"
|
||||
self.name = "wisdom_synthesizer"
|
||||
self.valves = self.Valves()
|
||||
|
||||
async def on_startup(self):
|
||||
pass
|
||||
|
||||
async def on_shutdown(self):
|
||||
pass
|
||||
|
||||
async def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
|
||||
"""
|
||||
Entry point for the pipeline filter.
|
||||
|
||||
Checks if the request is an aggregate request. If yes, parses the original prompt,
|
||||
extracts query & responses, builds a dynamically-structured new prompt,
|
||||
and replaces the original message content.
|
||||
"""
|
||||
logging.info(f"pipe:{__name__}")
|
||||
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
return body
|
||||
|
||||
user_message_content = ""
|
||||
user_message_index = -1
|
||||
|
||||
for i in range(len(messages) - 1, -1, -1):
|
||||
if messages[i].get("role") == "user":
|
||||
content = messages[i].get("content", "")
|
||||
if 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)
|
||||
user_message_content = "".join(text_parts)
|
||||
elif isinstance(content, str):
|
||||
user_message_content = content
|
||||
|
||||
user_message_index = i
|
||||
break
|
||||
|
||||
if user_message_index == -1:
|
||||
return body
|
||||
|
||||
if isinstance(user_message_content, str) and user_message_content.startswith(
|
||||
self.valves.trigger_prefix
|
||||
):
|
||||
logging.info("Detected aggregate request, modifying prompt.")
|
||||
|
||||
if self.valves.model_id:
|
||||
logging.info(f"Redirecting request to model: {self.valves.model_id}")
|
||||
body["model"] = self.valves.model_id
|
||||
|
||||
query_start_phrase = self.valves.query_start_marker
|
||||
query_end_phrase = self.valves.query_end_marker
|
||||
start_index = user_message_content.find(query_start_phrase)
|
||||
end_index = user_message_content.find(query_end_phrase)
|
||||
|
||||
original_query = ""
|
||||
if start_index != -1 and end_index != -1:
|
||||
original_query = user_message_content[
|
||||
start_index + len(query_start_phrase) : end_index
|
||||
]
|
||||
|
||||
responses_start_phrase = self.valves.response_start_marker
|
||||
responses_start_index = user_message_content.find(responses_start_phrase)
|
||||
|
||||
responses_text = ""
|
||||
if responses_start_index != -1:
|
||||
responses_text = user_message_content[
|
||||
responses_start_index + len(responses_start_phrase) :
|
||||
]
|
||||
|
||||
import re
|
||||
responses = [
|
||||
part.strip() for part in re.split(r'\n?\"\"\"\n?', responses_text) if part.strip()
|
||||
]
|
||||
|
||||
responses_section = ""
|
||||
for i, response in enumerate(responses):
|
||||
responses_section += f'''"""
|
||||
[Complete Response from Model {i + 1}]
|
||||
{response}
|
||||
"""
|
||||
'''
|
||||
|
||||
merge_prompt = f'''# Role Definition
|
||||
You are an experienced Chief Analyst processing analysis reports from multiple independent AI expert teams regarding the same question. Your task is to perform deep integration, critical analysis, and distill a structured, insightful, and highly actionable comprehensive report for decision-makers.
|
||||
|
||||
# Original User Query
|
||||
{original_query}
|
||||
|
||||
# Input Format Instruction ⚠️ IMPORTANT
|
||||
The responses from various models have been accurately identified and separated using an artificial """ (triple quote) delimiter. The system has extracted these distinct answers; you must now analyze based on the separated content below.
|
||||
|
||||
**Separated Model Responses**:
|
||||
{responses_section}
|
||||
|
||||
# Core Tasks
|
||||
Do not simply copy or concatenate the original reports. Use your professional analytical skills to complete the following steps:
|
||||
|
||||
## 1. Analysis & Evaluation
|
||||
- **Accurate Separation**: Verified boundaries using the """ delimiter.
|
||||
- **Credibility Assessment**: Critically examine each report for potential biases, errors, or inconsistencies.
|
||||
- **Logic Tracing**: Smooth out core arguments and reasoning chains.
|
||||
|
||||
## 2. Insight Extraction
|
||||
- **Identify Consensus**: Find points or recommendations uniformly mentioned across models. This represents the core facts or robust strategies.
|
||||
- **Highlight Divergences**: Explicitly state key disagreements in perspectives, methods, or forecasts.
|
||||
- **Capture Highlights**: Unearth innovative views found only in a single report.
|
||||
|
||||
## 3. Comprehensive Reporting
|
||||
Based on the analysis above, generate a synthesis containing:
|
||||
|
||||
### **【Core Consensus】**
|
||||
- List key information or advice agreed upon by models.
|
||||
- Annotate coverage (e.g., "All models agree" or "Majority of models").
|
||||
|
||||
### **【Key Divergences】**
|
||||
- Contrast different viewpoints on core issues clearly.
|
||||
- Use descriptive references (e.g., "Perspective Camp A vs B").
|
||||
|
||||
### **【Unique Insights】**
|
||||
- Present high-value unique advice or perspectives from standalone reports.
|
||||
|
||||
### **【Synthesis & Recommendation】**
|
||||
- **Integration**: A balanced final analysis optimized by your professional judgment.
|
||||
- **Recommendation**: Formulate actionable blended strategies.
|
||||
|
||||
# Format Requirements
|
||||
- Concise language, clear logic, distinct structure.
|
||||
- Use bolding, lists, and headings for readability.
|
||||
- **Language Alignment**: You MUST respond in the **SAME LANGUAGE** as the `Original User Query` above (e.g., if the user query is in Chinese, reply in Chinese; if in English, reply in English). Translate all section headers for your output.
|
||||
|
||||
# Output Structure Example
|
||||
Output should follow this structure:
|
||||
|
||||
## 【Core Consensus】
|
||||
✓ [Consensus Point 1] —— All models agree
|
||||
✓ [Consensus Point 2] —— Majority of models agree
|
||||
|
||||
## 【Key Divergences】
|
||||
⚡ **Divergence on [Topic]**:
|
||||
- Perspective Camp A: ...
|
||||
- Perspective Camp B: ...
|
||||
|
||||
## 【Unique Insights】
|
||||
💡 [Insight from Model A]: ...
|
||||
💡 [Insight from Model B]: ...
|
||||
|
||||
## 【Synthesis & Recommendation】
|
||||
Based on the analysis above, recommended strategies: ...
|
||||
'''
|
||||
|
||||
body["messages"][user_message_index]["content"] = merge_prompt
|
||||
logging.info("Prompt dynamically replaced successfully.")
|
||||
|
||||
return body
|
||||
@@ -8908,7 +8908,7 @@ class Pipe:
|
||||
|
||||
# Use the richer tool status text (which contains filenames/arguments context)
|
||||
# and ensure it's only printed to the stream ONCE per unique tool run.
|
||||
queue.put_nowait(f"\n> 🧩 **{tool_status_text}**\n")
|
||||
# queue.put_nowait(f"\n> 🧩 **{tool_status_text}**\n")
|
||||
|
||||
# Close thinking tag if open before showing tool
|
||||
if state["thinking_started"]:
|
||||
|
||||
@@ -1,52 +0,0 @@
|
||||
# iFlow Official SDK Pipe
|
||||
|
||||
This plugin integrates the [iFlow SDK](https://platform.iflow.cn/cli/sdk/sdk-python) into OpenWebUI as a `Pipe`.
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
```
|
||||
|
||||
When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
## Features
|
||||
|
||||
- **Standard iFlow Integration**: Connects to the iFlow CLI process via WebSocket (ACP).
|
||||
- **Auto-Process Management**: Automatically starts the iFlow process if it's not running.
|
||||
- **Streaming Support**: Direct streaming from iFlow to the chat interface.
|
||||
- **Status Updates**: Real-time status updates in the UI (thinking, tool usage, etc.).
|
||||
- **Tool Execution Visibility**: See when iFlow is calling and completing tools.
|
||||
|
||||
## Configuration
|
||||
|
||||
Set the following `Valves`:
|
||||
|
||||
- `IFLOW_PORT`: The port for the iFlow CLI process (default: `8090`).
|
||||
- `IFLOW_URL`: The WebSocket URL (default: `ws://localhost:8090/acp`).
|
||||
- `AUTO_START`: Automatically start the process (default: `True`).
|
||||
- `TIMEOUT`: Request timeout in seconds.
|
||||
- `LOG_LEVEL`: SDK logging level (DEBUG, INFO, etc.).
|
||||
|
||||
## Installation
|
||||
|
||||
This plugin requires both the **iFlow CLI** binary and the **iflow-cli-sdk** Python package.
|
||||
|
||||
### 1. Install iFlow CLI (System level)
|
||||
|
||||
Run the following command in your terminal (Linux/macOS):
|
||||
|
||||
```bash
|
||||
bash -c "$(curl -fsSL https://platform.iflow.cn/cli/install.sh)"
|
||||
```
|
||||
|
||||
### 2. Install Python SDK (OpenWebUI environment)
|
||||
|
||||
```bash
|
||||
pip install iflow-cli-sdk
|
||||
```
|
||||
@@ -1,50 +0,0 @@
|
||||
# iFlow 官方 SDK Pipe 插件
|
||||
|
||||
此插件将 [iFlow SDK](https://platform.iflow.cn/cli/sdk/sdk-python) 集成到 OpenWebUI 中。
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
```
|
||||
|
||||
当选择弹窗打开后，搜索当前插件，勾选后继续安装即可。
|
||||
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
## 功能特性
|
||||
|
||||
- **标准 iFlow 集成**：通过 WebSocket (ACP) 连接到 iFlow CLI 进程。
|
||||
- **自动进程管理**：如果 iFlow 进程未运行，将自动启动。
|
||||
- **流式输出支持**：支持从 iFlow 到聊天界面的实时流式输出。
|
||||
- **实时状态更新**：在 UI 中实时显示助手状态（思考中、工具调用等）。
|
||||
- **工具调用可视化**：实时反馈 iFlow 调用及完成工具的过程。
|
||||
|
||||
## 配置项 (Valves)
|
||||
|
||||
- `IFLOW_PORT`：iFlow CLI 进程端口（默认：`8090`）。
|
||||
- `IFLOW_URL`：WebSocket 地址（默认：`ws://localhost:8090/acp`）。
|
||||
- `AUTO_START`：是否自动启动进程（默认：`True`）。
|
||||
- `TIMEOUT`：请求超时时间（秒）。
|
||||
- `LOG_LEVEL`：SDK 日志级别（DEBUG, INFO 等）。
|
||||
|
||||
## 安装说明
|
||||
|
||||
此插件同时依赖 **iFlow CLI** 二进制文件和 **iflow-cli-sdk** Python 包。
|
||||
|
||||
### 1. 安装 iFlow CLI (系统层级)
|
||||
|
||||
在系统中执行以下命令（适用于 Linux/macOS）：
|
||||
|
||||
```bash
|
||||
bash -c "$(curl -fsSL https://gitee.com/iflow-ai/iflow-cli/raw/main/install.sh)"
|
||||
```
|
||||
|
||||
### 2. 安装 Python SDK (OpenWebUI 环境)
|
||||
|
||||
```bash
|
||||
pip install iflow-cli-sdk
|
||||
```
|
||||
@@ -1,544 +0,0 @@
|
||||
"""
|
||||
title: iFlow Official SDK Pipe
|
||||
author: Fu-Jie
|
||||
author_url: https://github.com/Fu-Jie/openwebui-extensions
|
||||
funding_url: https://github.com/open-webui
|
||||
description: Integrate iFlow SDK. Supports dynamic models, multi-turn conversation, streaming, tool execution, and task planning.
|
||||
version: 0.1.2
|
||||
requirements: iflow-cli-sdk==0.1.11
|
||||
"""
|
||||
|
||||
import shutil
|
||||
import subprocess
|
||||
|
||||
import os
|
||||
import json
|
||||
import asyncio
|
||||
import logging
|
||||
from typing import Optional, Union, AsyncGenerator, List, Any, Dict, Literal
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
# Setup logger
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Import iflow SDK modules with safety
|
||||
IFlowClient = None
|
||||
IFlowOptions = None
|
||||
AssistantMessage = None
|
||||
TaskFinishMessage = None
|
||||
ToolCallMessage = None
|
||||
PlanMessage = None
|
||||
TaskStatusMessage = None
|
||||
ApprovalMode = None
|
||||
StopReason = None
|
||||
|
||||
try:
|
||||
from iflow_sdk import (
|
||||
IFlowClient,
|
||||
IFlowOptions,
|
||||
AssistantMessage,
|
||||
TaskFinishMessage,
|
||||
ToolCallMessage,
|
||||
PlanMessage,
|
||||
TaskStatusMessage,
|
||||
ApprovalMode,
|
||||
StopReason,
|
||||
)
|
||||
except ImportError:
|
||||
logger.error(
|
||||
"iflow-cli-sdk not found. Please install it with 'pip install iflow-cli-sdk'."
|
||||
)
|
||||
|
||||
# Base guidelines for all users, adapted for iFlow
|
||||
BASE_GUIDELINES = (
|
||||
"\n\n[Environment & Capabilities Context]\n"
|
||||
"You are an AI assistant operating within a high-capability Linux container environment (OpenWebUI) powered by **iFlow CLI**.\n"
|
||||
"\n"
|
||||
"**System Environment & User Privileges:**\n"
|
||||
"- **Output Environment**: You are rendering in the **OpenWebUI Chat Page**. Optimize your output format to leverage Markdown for the best UI experience.\n"
|
||||
"- **Root Access**: You are running as **root**. You have **READ access to the entire container file system**. You **MUST ONLY WRITE** to your designated persistent workspace directory.\n"
|
||||
"- **STRICT FILE CREATION RULE**: You are **PROHIBITED** from creating or editing files outside of your specific workspace path. Never place files in `/root`, `/tmp`, or `/app`. All operations must use the absolute path provided in your session context.\n"
|
||||
"- **iFlow Task Planning**: You possess **Task Planning** capabilities. When faced with complex requests, you SHOULD generate a structured plan. The iFlow SDK will visualize this plan as a task list for the user.\n"
|
||||
"- **Tool Execution (ACP)**: You interact with tools via the **Agent Control Protocol (ACP)**. Depending on the `ApprovalMode`, your tool calls may be executed automatically or require user confirmation.\n"
|
||||
"- **Rich Python Environment**: You can natively import and use any installed OpenWebUI dependencies.\n"
|
||||
"\n"
|
||||
"**Formatting & Presentation Directives:**\n"
|
||||
"1. **Markdown Excellence**: Leverage headers, tables, and lists to structure your response professionally.\n"
|
||||
"2. **Advanced Visualization**: Use **Mermaid** for diagrams and **LaTeX** for math. Always wrap Mermaid in standard ```mermaid blocks.\n"
|
||||
"3. **Interactive Artifacts (HTML)**: **Premium Delivery Protocol**: For web applications, you MUST:\n"
|
||||
" - 1. **Persist**: Create the file in the workspace (e.g., `index.html`).\n"
|
||||
" - 2. **Publish**: Call `publish_file_from_workspace(filename='your_file.html')` (via provided tools if available). This triggers the premium embedded experience.\n"
|
||||
" - **CRITICAL**: Never output raw HTML source code directly in the chat. Persist and publish.\n"
|
||||
"4. **Media & Files**: ALWAYS embed generated media using ``. Never provide plain text links for images/videos.\n"
|
||||
"5. **Dual-Channel Delivery**: Always aim to provide both an instant visual Insight in the chat AND a persistent downloadable file.\n"
|
||||
"6. **Active & Autonomous**: Analyze the user's request -> Formulate a plan -> **EXECUTE** the plan immediately. Minimize user friction.\n"
|
||||
)
|
||||
|
||||
# Sensitive extensions only for Administrators
|
||||
ADMIN_EXTENSIONS = (
|
||||
"\n**[ADMINISTRATOR PRIVILEGES - CONFIDENTIAL]**\n"
|
||||
"Current user is an **ADMINISTRATOR**. Restricted access is lifted:\n"
|
||||
"- **Full OS Interaction**: You can use shell tools to analyze any container process or system configuration.\n"
|
||||
"- **Database Access**: You can connect to the **OpenWebUI Database** using credentials in environment variables.\n"
|
||||
"- **iFlow CLI Debugging**: You can inspect iFlow configuration and logs for diagnostic purposes.\n"
|
||||
"**SECURITY NOTE**: Protect sensitive internal details.\n"
|
||||
)
|
||||
|
||||
# Strict restrictions for regular Users
|
||||
USER_RESTRICTIONS = (
|
||||
"\n**[USER ACCESS RESTRICTIONS - STRICT]**\n"
|
||||
"Current user is a **REGULAR USER**. Adhere to boundaries:\n"
|
||||
"- **NO Environment Access**: FORBIDDEN from accessing environment variables (e.g., via `env` or `os.environ`).\n"
|
||||
"- **NO Database Access**: MUST NOT attempt to connect to OpenWebUI database.\n"
|
||||
"- **NO Writing Outside Workspace**: All artifacts MUST be saved strictly inside the isolated workspace path provided.\n"
|
||||
"- **Restricted Shell**: Use shell tools ONLY for operations within your isolated workspace. Do NOT explore system secrets.\n"
|
||||
)
|
||||
|
||||
|
||||
class Pipe:
|
||||
class Valves(BaseModel):
|
||||
IFLOW_PORT: int = Field(
|
||||
default=8090,
|
||||
description="Port for iFlow CLI process.",
|
||||
)
|
||||
IFLOW_URL: str = Field(
|
||||
default="ws://localhost:8090/acp",
|
||||
description="WebSocket URL for iFlow ACP.",
|
||||
)
|
||||
AUTO_START: bool = Field(
|
||||
default=True,
|
||||
description="Whether to automatically start the iFlow process.",
|
||||
)
|
||||
TIMEOUT: float = Field(
|
||||
default=300.0,
|
||||
description="Timeout for the message request (seconds).",
|
||||
)
|
||||
LOG_LEVEL: str = Field(
|
||||
default="INFO",
|
||||
description="Log level for iFlow SDK (DEBUG, INFO, WARNING, ERROR).",
|
||||
)
|
||||
CWD: str = Field(
|
||||
default="",
|
||||
description="CLI operation working directory. Empty for default.",
|
||||
)
|
||||
APPROVAL_MODE: Literal["DEFAULT", "AUTO_EDIT", "YOLO", "PLAN"] = Field(
|
||||
default="YOLO",
|
||||
description="Tool execution permission mode.",
|
||||
)
|
||||
FILE_ACCESS: bool = Field(
|
||||
default=False,
|
||||
description="Enable file system access (disabled by default for security).",
|
||||
)
|
||||
AUTO_INSTALL_CLI: bool = Field(
|
||||
default=True,
|
||||
description="Automatically install iFlow CLI if not found in PATH.",
|
||||
)
|
||||
IFLOW_BIN_DIR: str = Field(
|
||||
default="/app/backend/data/bin",
|
||||
description="Fixed path for iFlow CLI binary (recommended for persistence in Docker).",
|
||||
)
|
||||
|
||||
# Auth Config
|
||||
SELECTED_AUTH_TYPE: Literal["iflow", "openai-compatible"] = Field(
|
||||
default="iflow",
|
||||
description="Authentication type. 'iflow' for native, 'openai-compatible' for others.",
|
||||
)
|
||||
AUTH_API_KEY: str = Field(
|
||||
default="",
|
||||
description="API Key for the model provider.",
|
||||
)
|
||||
AUTH_BASE_URL: str = Field(
|
||||
default="",
|
||||
description="Base URL for the model provider.",
|
||||
)
|
||||
AUTH_MODEL: str = Field(
|
||||
default="",
|
||||
description="Model name to use.",
|
||||
)
|
||||
SYSTEM_PROMPT: str = Field(
|
||||
default="",
|
||||
description="System prompt to guide the AI's behavior.",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
self.type = "pipe"
|
||||
self.id = "iflow_sdk"
|
||||
self.name = "iflow"
|
||||
self.valves = self.Valves()
|
||||
|
||||
def _get_user_role(self, __user__: dict) -> str:
|
||||
"""Determine if the user is an admin."""
|
||||
return __user__.get("role", "user")
|
||||
|
||||
def _get_system_prompt(self, role: str) -> str:
|
||||
"""Construct the dynamic system prompt based on user role."""
|
||||
prompt = self.valves.SYSTEM_PROMPT if self.valves.SYSTEM_PROMPT else ""
|
||||
prompt += BASE_GUIDELINES
|
||||
if role == "admin":
|
||||
prompt += ADMIN_EXTENSIONS
|
||||
else:
|
||||
prompt += USER_RESTRICTIONS
|
||||
return prompt
|
||||
|
||||
async def _ensure_cli(self, _emit_status) -> bool:
|
||||
"""Check for iFlow CLI and attempt installation if missing."""
|
||||
|
||||
async def _check_binary(name: str) -> Optional[str]:
|
||||
# 1. Check in system PATH
|
||||
path = shutil.which(name)
|
||||
if path:
|
||||
return path
|
||||
|
||||
# 2. Compile potential search paths
|
||||
search_paths = []
|
||||
|
||||
# Try to resolve NPM global prefix
|
||||
try:
|
||||
proc = await asyncio.create_subprocess_exec(
|
||||
"npm",
|
||||
"config",
|
||||
"get",
|
||||
"prefix",
|
||||
stdout=asyncio.subprocess.PIPE,
|
||||
stderr=asyncio.subprocess.PIPE,
|
||||
)
|
||||
stdout, _ = await proc.communicate()
|
||||
if proc.returncode == 0:
|
||||
prefix = stdout.decode().strip()
|
||||
search_paths.extend(
|
||||
[
|
||||
os.path.join(prefix, "bin"),
|
||||
os.path.join(prefix, "node_modules", ".bin"),
|
||||
prefix,
|
||||
]
|
||||
)
|
||||
except:
|
||||
pass
|
||||
|
||||
if self.valves.IFLOW_BIN_DIR:
|
||||
search_paths.extend(
|
||||
[
|
||||
self.valves.IFLOW_BIN_DIR,
|
||||
os.path.join(self.valves.IFLOW_BIN_DIR, "bin"),
|
||||
]
|
||||
)
|
||||
|
||||
# Common/default locations
|
||||
search_paths.extend(
|
||||
[
|
||||
os.path.expanduser("~/.iflow/bin"),
|
||||
os.path.expanduser("~/.npm-global/bin"),
|
||||
os.path.expanduser("~/.local/bin"),
|
||||
"/usr/local/bin",
|
||||
"/usr/bin",
|
||||
"/bin",
|
||||
os.path.expanduser("~/bin"),
|
||||
]
|
||||
)
|
||||
|
||||
for p in search_paths:
|
||||
full_path = os.path.join(p, name)
|
||||
if os.path.exists(full_path) and os.access(full_path, os.X_OK):
|
||||
return full_path
|
||||
return None
|
||||
|
||||
# Initial check
|
||||
binary_path = await _check_binary("iflow")
|
||||
if binary_path:
|
||||
logger.info(f"iFlow CLI found at: {binary_path}")
|
||||
bin_dir = os.path.dirname(binary_path)
|
||||
if bin_dir not in os.environ["PATH"]:
|
||||
os.environ["PATH"] = f"{bin_dir}:{os.environ['PATH']}"
|
||||
return True
|
||||
|
||||
if not self.valves.AUTO_INSTALL_CLI:
|
||||
return False
|
||||
|
||||
try:
|
||||
install_loc_msg = (
|
||||
self.valves.IFLOW_BIN_DIR
|
||||
if self.valves.IFLOW_BIN_DIR
|
||||
else "default location"
|
||||
)
|
||||
await _emit_status(
|
||||
f"iFlow CLI not found. Attempting auto-installation to {install_loc_msg}..."
|
||||
)
|
||||
|
||||
# Detection for package managers and official script
|
||||
env = os.environ.copy()
|
||||
has_npm = shutil.which("npm") is not None
|
||||
has_curl = shutil.which("curl") is not None
|
||||
|
||||
if has_npm:
|
||||
if self.valves.IFLOW_BIN_DIR:
|
||||
os.makedirs(self.valves.IFLOW_BIN_DIR, exist_ok=True)
|
||||
install_cmd = f"npm i -g --prefix {self.valves.IFLOW_BIN_DIR} @iflow-ai/iflow-cli@latest"
|
||||
else:
|
||||
install_cmd = "npm i -g @iflow-ai/iflow-cli@latest"
|
||||
elif has_curl:
|
||||
await _emit_status(
|
||||
"npm not found. Attempting to use official shell installer via curl..."
|
||||
)
|
||||
# Official installer script from gitee/github as fallback
|
||||
# We try gitee first as it's more reliable in some environments
|
||||
install_cmd = 'bash -c "$(curl -fsSL https://gitee.com/iflow-ai/iflow-cli/raw/main/install.sh)"'
|
||||
# If we have a custom bin dir, try to tell the installer (though it might not support it)
|
||||
if self.valves.IFLOW_BIN_DIR:
|
||||
env["IFLOW_BIN_DIR"] = self.valves.IFLOW_BIN_DIR
|
||||
else:
|
||||
await _emit_status(
|
||||
"Error: Neither 'npm' nor 'curl' found. Cannot proceed with auto-installation."
|
||||
)
|
||||
return False
|
||||
|
||||
process = await asyncio.create_subprocess_shell(
|
||||
install_cmd,
|
||||
stdout=asyncio.subprocess.PIPE,
|
||||
stderr=asyncio.subprocess.PIPE,
|
||||
env=env,
|
||||
)
|
||||
stdout_data, stderr_data = await process.communicate()
|
||||
|
||||
# Even if the script returns non-zero (which it might if it tries to
|
||||
# start an interactive shell at the end), we check if the binary exists.
|
||||
await _emit_status(
|
||||
"Installation script finished. Finalizing verification..."
|
||||
)
|
||||
binary_path = await _check_binary("iflow")
|
||||
|
||||
if binary_path:
|
||||
try:
|
||||
os.chmod(binary_path, 0o755)
|
||||
except:
|
||||
pass
|
||||
await _emit_status(f"iFlow CLI confirmed at {binary_path}.")
|
||||
bin_dir = os.path.dirname(binary_path)
|
||||
if bin_dir not in os.environ["PATH"]:
|
||||
os.environ["PATH"] = f"{bin_dir}:{os.environ['PATH']}"
|
||||
return True
|
||||
else:
|
||||
# Script failed and no binary
|
||||
error_msg = (
|
||||
stderr_data.decode().strip() or "Binary not found in search paths"
|
||||
)
|
||||
logger.error(
|
||||
f"Installation failed with code {process.returncode}: {error_msg}"
|
||||
)
|
||||
await _emit_status(f"Installation failed: {error_msg}")
|
||||
return False
|
||||
except Exception as e:
|
||||
logger.error(f"Error during installation: {str(e)}")
|
||||
await _emit_status(f"Installation error: {str(e)}")
|
||||
return False
|
||||
|
||||
async def _ensure_sdk(self, _emit_status) -> bool:
|
||||
"""Check for iflow-cli-sdk Python package and attempt installation if missing."""
|
||||
global IFlowClient, IFlowOptions, AssistantMessage, TaskFinishMessage, ToolCallMessage, PlanMessage, TaskStatusMessage, ApprovalMode, StopReason
|
||||
|
||||
if IFlowClient is not None:
|
||||
return True
|
||||
|
||||
await _emit_status("iflow-cli-sdk not found. Attempting auto-installation...")
|
||||
try:
|
||||
# Use sys.executable to ensure we use the same Python environment
|
||||
import sys
|
||||
|
||||
process = await asyncio.create_subprocess_exec(
|
||||
sys.executable,
|
||||
"-m",
|
||||
"pip",
|
||||
"install",
|
||||
"iflow-cli-sdk",
|
||||
stdout=asyncio.subprocess.PIPE,
|
||||
stderr=asyncio.subprocess.PIPE,
|
||||
)
|
||||
stdout, stderr = await process.communicate()
|
||||
|
||||
if process.returncode == 0:
|
||||
await _emit_status("iflow-cli-sdk installed successfully. Loading...")
|
||||
# Try to import again
|
||||
from iflow_sdk import (
|
||||
IFlowClient as C,
|
||||
IFlowOptions as O,
|
||||
AssistantMessage as AM,
|
||||
TaskFinishMessage as TM,
|
||||
ToolCallMessage as TC,
|
||||
PlanMessage as P,
|
||||
TaskStatusMessage as TS,
|
||||
ApprovalMode as AP,
|
||||
StopReason as SR,
|
||||
)
|
||||
|
||||
# Update global pointers
|
||||
IFlowClient, IFlowOptions = C, O
|
||||
AssistantMessage, TaskFinishMessage = AM, TM
|
||||
ToolCallMessage, PlanMessage = TC, P
|
||||
TaskStatusMessage, ApprovalMode, StopReason = TS, AP, SR
|
||||
return True
|
||||
else:
|
||||
error_msg = stderr.decode().strip()
|
||||
logger.error(f"SDK installation failed: {error_msg}")
|
||||
await _emit_status(f"SDK installation failed: {error_msg}")
|
||||
return False
|
||||
except Exception as e:
|
||||
logger.error(f"Error during SDK installation: {str(e)}")
|
||||
await _emit_status(f"SDK installation error: {str(e)}")
|
||||
return False
|
||||
|
||||
async def pipe(
|
||||
self, body: dict, __user__: dict, __event_emitter__=None
|
||||
) -> Union[str, AsyncGenerator[str, None]]:
|
||||
"""Main entry point for the pipe."""
|
||||
|
||||
async def _emit_status(description: str, done: bool = False):
|
||||
if __event_emitter__:
|
||||
await __event_emitter__(
|
||||
{
|
||||
"type": "status",
|
||||
"data": {
|
||||
"description": description,
|
||||
"done": done,
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
# 0. Ensure SDK and CLI are available
|
||||
if not await self._ensure_sdk(_emit_status):
|
||||
return "Error: iflow-cli-sdk (Python package) missing and auto-installation failed. Please install it with `pip install iflow-cli-sdk` manually."
|
||||
|
||||
# 1. Update PATH to include custom bin dir
|
||||
if self.valves.IFLOW_BIN_DIR not in os.environ["PATH"]:
|
||||
os.environ["PATH"] = f"{self.valves.IFLOW_BIN_DIR}:{os.environ['PATH']}"
|
||||
|
||||
# 2. Ensure CLI is installed and path is updated
|
||||
if not await self._ensure_cli(_emit_status):
|
||||
return f"Error: iFlow CLI not found and auto-installation failed. Please install it to {self.valves.IFLOW_BIN_DIR} manually."
|
||||
|
||||
messages = body.get("messages", [])
|
||||
if not messages:
|
||||
return "No messages provided."
|
||||
|
||||
# Get the last user message
|
||||
last_message = messages[-1]
|
||||
content = last_message.get("content", "")
|
||||
|
||||
# Determine user role and construct prompt
|
||||
role = self._get_user_role(__user__)
|
||||
dynamic_prompt = self._get_system_prompt(role)
|
||||
|
||||
# Prepare Auth Info
|
||||
auth_info = None
|
||||
if self.valves.AUTH_API_KEY:
|
||||
auth_info = {
|
||||
"api_key": self.valves.AUTH_API_KEY,
|
||||
"base_url": self.valves.AUTH_BASE_URL,
|
||||
"model_name": self.valves.AUTH_MODEL,
|
||||
}
|
||||
|
||||
# Prepare Session Settings
|
||||
session_settings = None
|
||||
try:
|
||||
from iflow_sdk import SessionSettings
|
||||
|
||||
session_settings = SessionSettings(system_prompt=dynamic_prompt)
|
||||
except ImportError:
|
||||
session_settings = {"system_prompt": dynamic_prompt}
|
||||
|
||||
# 2. Configure iFlow Options
|
||||
# Use local references to ensure we're using the freshly imported SDK components
|
||||
from iflow_sdk import (
|
||||
IFlowOptions as SDKOptions,
|
||||
ApprovalMode as SDKApprovalMode,
|
||||
)
|
||||
|
||||
# Get approval mode with a safe fallback
|
||||
try:
|
||||
target_mode = getattr(SDKApprovalMode, self.valves.APPROVAL_MODE)
|
||||
except (AttributeError, TypeError):
|
||||
target_mode = (
|
||||
SDKApprovalMode.YOLO if hasattr(SDKApprovalMode, "YOLO") else None
|
||||
)
|
||||
|
||||
options = SDKOptions(
|
||||
url=self.valves.IFLOW_URL,
|
||||
auto_start_process=self.valves.AUTO_START,
|
||||
process_start_port=self.valves.IFLOW_PORT,
|
||||
timeout=self.valves.TIMEOUT,
|
||||
log_level=self.valves.LOG_LEVEL,
|
||||
cwd=self.valves.CWD or None,
|
||||
approval_mode=target_mode,
|
||||
file_access=self.valves.FILE_ACCESS,
|
||||
auth_method_id=self.valves.SELECTED_AUTH_TYPE if auth_info else None,
|
||||
auth_method_info=auth_info,
|
||||
session_settings=session_settings,
|
||||
)
|
||||
|
||||
async def _emit_status(description: str, done: bool = False):
|
||||
if __event_emitter__:
|
||||
await __event_emitter__(
|
||||
{
|
||||
"type": "status",
|
||||
"data": {
|
||||
"description": description,
|
||||
"done": done,
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
# 3. Stream from iFlow
|
||||
async def stream_generator():
|
||||
try:
|
||||
await _emit_status("Initializing iFlow connection...")
|
||||
|
||||
async with IFlowClient(options) as client:
|
||||
await client.send_message(content)
|
||||
|
||||
await _emit_status("iFlow is processing...")
|
||||
|
||||
async for message in client.receive_messages():
|
||||
if isinstance(message, AssistantMessage):
|
||||
yield message.chunk.text
|
||||
if message.agent_info and message.agent_info.agent_id:
|
||||
logger.debug(
|
||||
f"Message from agent: {message.agent_info.agent_id}"
|
||||
)
|
||||
|
||||
elif isinstance(message, PlanMessage):
|
||||
plan_str = "\n".join(
|
||||
[
|
||||
f"{'✅' if e.status == 'completed' else '⏳'} [{e.priority}] {e.content}"
|
||||
for e in message.entries
|
||||
]
|
||||
)
|
||||
await _emit_status(f"Execution Plan updated:\n{plan_str}")
|
||||
|
||||
elif isinstance(message, TaskStatusMessage):
|
||||
await _emit_status(f"iFlow: {message.status}")
|
||||
|
||||
elif isinstance(message, ToolCallMessage):
|
||||
tool_desc = (
|
||||
f"Calling tool: {message.tool_name}"
|
||||
if message.tool_name
|
||||
else "Invoking tool"
|
||||
)
|
||||
await _emit_status(
|
||||
f"{tool_desc}... (Status: {message.status})"
|
||||
)
|
||||
|
||||
elif isinstance(message, TaskFinishMessage):
|
||||
reason_msg = "Task completed."
|
||||
if message.stop_reason == StopReason.MAX_TOKENS:
|
||||
reason_msg = "Task stopped: Max tokens reached."
|
||||
elif message.stop_reason == StopReason.END_TURN:
|
||||
reason_msg = "Task completed successfully."
|
||||
|
||||
await _emit_status(reason_msg, done=True)
|
||||
break
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in iFlow pipe: {str(e)}", exc_info=True)
|
||||
error_msg = f"iFlow Error: {str(e)}"
|
||||
yield error_msg
|
||||
await _emit_status(error_msg, done=True)
|
||||
|
||||
return stream_generator()
|
||||
@@ -10,7 +10,7 @@ One-click batch install plugins from GitHub repositories to your OpenWebUI insta
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
After you install [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins) once, you can also use it to reinstall or update itself with:
|
||||
After you install [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) once, you can also use it to reinstall or update itself with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
@@ -21,6 +21,10 @@ When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
> [!IMPORTANT]
|
||||
> If the official OpenWebUI Community version is already installed, remove it first. After that, Batch Install Plugins can keep this plugin updated in future runs.
|
||||
|
||||
> [!TIP]
|
||||
> **💡 Looking to batch install or manage Workspace Skills?**
|
||||
> This plugin specializes in installing global function-based plugins (Pipe, Filter, Tool, Action). If you need to manage your AI assistant's dedicated Skills, use our companion tool [OpenWebUI Skills Manager](https://openwebui.com/posts/openwebui_skills_manager_tool_b4bce8e4), which provides full CRUD capabilities, batch discovery, and interactive selection dialogs.
|
||||
|
||||
## Key Features
|
||||
|
||||
- **One-Click Install**: Install all plugins with a single command
|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
当你已经安装过一次 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins) 后，也可以用同一句来重新安装或更新它自己：
|
||||
当你已经安装过一次 [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) 后，也可以用同一句来重新安装或更新它自己：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
@@ -21,6 +21,10 @@
|
||||
> [!IMPORTANT]
|
||||
> 如果你已经安装了 OpenWebUI 官方社区里的同名版本，请先删除旧版本，否则重新安装时可能报错。删除后，Batch Install Plugins 后续就可以继续负责更新这个插件。
|
||||
|
||||
> [!TIP]
|
||||
> **💡 想要批量安装/管理 Workspace 技能 (Skills)？**
|
||||
> 本插件专注安装全局函数型插件（Pipe/Filter/Tool/Action）。如果你需要管理 AI 助手的专属技能，请使用同系列的 [OpenWebUI Skills Manager](https://openwebui.com/posts/openwebui_skills_manager_tool_b4bce8e4) 工具，它具备完整的增删改查、批量发现及可视化浮层点选能力。
|
||||
|
||||
## 主要功能
|
||||
|
||||
- 一键安装：单个命令安装所有插件
|
||||
|
||||
@@ -10,7 +10,7 @@ A standalone OpenWebUI Tool plugin to manage native **Workspace > Skills** for a
|
||||
|
||||
## Install with Batch Install Plugins
|
||||
|
||||
If you already use [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins), you can install or update this plugin with:
|
||||
If you already use [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80), you can install or update this plugin with:
|
||||
|
||||
```text
|
||||
Install plugin from Fu-Jie/openwebui-extensions
|
||||
@@ -28,6 +28,10 @@ When the selection dialog opens, search for this plugin, check it, and continue.
|
||||
- Added GitHub skills-directory auto-discovery for `install_skill` (e.g., `.../tree/main/skills`) to install all child skills in one request.
|
||||
- Fixed language detection with robust frontend-first fallback (`__event_call__` + timeout), request header fallback, and profile fallback.
|
||||
|
||||
> [!TIP]
|
||||
> **💡 Looking to batch install global plugins (Actions, Filters, Pipes, Tools)?**
|
||||
> This plugin specializes in managing Workspace Skills for your assistants. If you need to install and manage global function-based plugins, use our companion tool [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) for an optimized installation workflow.
|
||||
|
||||
## Key Features
|
||||
|
||||
- **🌐 Model-agnostic**: Can be enabled for any model that supports OpenWebUI Tools.
|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
|
||||
## 使用 Batch Install Plugins 安装
|
||||
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/tools/batch-install-plugins)，可以用下面这句来安装或更新当前插件：
|
||||
如果你已经安装了 [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80)，可以用下面这句来安装或更新当前插件：
|
||||
|
||||
```text
|
||||
从 Fu-Jie/openwebui-extensions 安装插件
|
||||
@@ -28,6 +28,10 @@
|
||||
- `install_skill` 新增 GitHub 技能目录自动发现（例如 `.../tree/main/skills`），可一键安装目录下所有子技能。
|
||||
- 修复语言获取逻辑：前端优先（`__event_call__` + 超时保护），并回退到请求头与用户资料。
|
||||
|
||||
> [!TIP]
|
||||
> **💡 想要批量安装/管理全局插件 (Actions, Filters, Pipes, Tools)？**
|
||||
> 本插件专注管理工作区的 AI 技能 (Skills)。如果你需要安装和管理全局函数型插件，请使用同系列的 [Batch Install Plugins from GitHub](https://openwebui.com/posts/batch_install_plugins_install_popular_plugins_in_s_c9fd6e80) 工具，不仅安装体验极致，而且完美接轨系统扩展体系。
|
||||
|
||||
## 核心特性
|
||||
|
||||
- **🌐 全模型可用**：只要模型启用了 OpenWebUI Tools，即可调用。
|
||||
|
||||
22
prompts/README.md
Normal file
22
prompts/README.md
Normal file
@@ -0,0 +1,22 @@
|
||||
# 🎯 OpenWebUI Prompts Collection
|
||||
|
||||
A collection of curated OpenWebUI prompts templates designed to extend your workspace with specialized features and agents.
|
||||
|
||||
## 📂 Prompts Library
|
||||
|
||||
Every prompt is organized into its own directory containing the prompt definition and usage documentation.
|
||||
|
||||
| Prompt Name | Description | Link |
|
||||
| :--- | :--- | :--- |
|
||||
| 🔧 **[AI Task Instruction Generator](./ai-task-instruction)** | Turn vague requirements into precise, AI-executable instructions. | [Community](https://openwebui.com/posts/9bab8b37-5c43-48e6-988b-946564510b91) |
|
||||
| 🔍 **[One-Sentence Concept Explainer](./one-sentence-concept-explainer)** | Explain concepts in exactly one clear, punchy sentence. | - |
|
||||
|
||||
---
|
||||
|
||||
## 🚀 How to Install a Prompt
|
||||
|
||||
1. Choose a prompt inside this folder and inspect its `README.md` or template code (`.md`).
|
||||
2. Copy the template content consisting of `{{variable}}` syntax.
|
||||
3. In your OpenWebUI dashboard, navigate to **Workspace** -> **Prompts** and click **Create Prompt**.
|
||||
4. Paste the content and save.
|
||||
5. In any chat session, type `/` to pull up your newly added system prompts automatically!
|
||||
47
prompts/ai-task-instruction/README.md
Normal file
47
prompts/ai-task-instruction/README.md
Normal file
@@ -0,0 +1,47 @@
|
||||
# 🔧 AI Task Instruction
|
||||
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.0.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
|
||||
|
||||
Convert vague or unstructured requirements into precise, structured instructions optimized for AI agent execution.
|
||||
|
||||
## 📋 Info
|
||||
|
||||
- **Command**: `/ai-task-instruction`
|
||||
- **Community Link**: [OpenWebUI Post](https://openwebui.com/posts/9bab8b37-5c43-48e6-988b-946564510b91)
|
||||
|
||||
## 🔥 What's New in v1.0.0
|
||||
|
||||
- ✨ **Task Architect Persona**: Directly refactors arbitrary description into modular specs.
|
||||
- 🌍 **Language Consistency**: Automated response adapting based on your dynamic input payload language.
|
||||
|
||||
## ✨ Key Features
|
||||
|
||||
- 🎯 **Precise Structuring**: Builds distinct modules like context, role, atomic steps, and constraints.
|
||||
- ⚙️ **Configurable variables**: Operates seamlessly with OpenWebUI dropdown and text areas configurations.
|
||||
|
||||
## 🚀 How to Use
|
||||
|
||||
1. Check out the prompt template: [ai-task-instruction.md](./ai-task-instruction.md)
|
||||
2. **Copy** the full content.
|
||||
3. In OpenWebUI, Go to **Workspace** -> **Prompts** and click **Create Prompt**.
|
||||
4. Set title, and paste the template code into the content block.
|
||||
5. In your standard chat, trigger via `/ai-task-instruction` and fill in the fields.
|
||||
|
||||
## ⚙️ Configuration (Variables)
|
||||
|
||||
The template contains dynamic variables supported by OpenWebUI prompts:
|
||||
|
||||
| Variable | Type | Options / Default | Description |
|
||||
| :--- | :--- | :--- | :--- |
|
||||
| **target_role** | `text` | `AI Assistant` | The persona or role the agent should adopt. |
|
||||
| **complexity** | `select` | `Basic`, **`Intermediate`**, `Advanced` | Level of depth the output template should contain. |
|
||||
| **output_style** | `select` | **`Markdown Template`**, `JSON`, `Step-by-Step` | Structured style for the resulting prompt framework. |
|
||||
| **requirements** | `textarea`| Required | The unstructured tasks or instructions from the user. |
|
||||
|
||||
## ⭐ Support
|
||||
|
||||
If this prompt has been useful, a star on [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) is a big motivation for me. Thank you for the support.
|
||||
47
prompts/ai-task-instruction/README_CN.md
Normal file
47
prompts/ai-task-instruction/README_CN.md
Normal file
@@ -0,0 +1,47 @@
|
||||
# 🔧 AI Task Instruction (AI 任务指令生成器)
|
||||
|
||||
| 作者: [Fu-Jie](https://github.com/Fu-Jie) · v1.0.0 | [⭐ 给项目点个 Star](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
|
||||
|
||||
将模糊的通用需求或无结构自然语言，转换为精确、结构化且高度优化的 AI 任务指令框架。
|
||||
|
||||
## 📋 基础信息
|
||||
|
||||
- **触发指令 (Command)**: `/ai-task-instruction`
|
||||
- **社区链接 (Community Link)**: [OpenWebUI Post](https://openwebui.com/posts/9bab8b37-5c43-48e6-988b-946564510b91)
|
||||
|
||||
## 🔥 版本特性 v1.0.0
|
||||
|
||||
- ✨ **提示词架构师 Persona**: 将任何形式的语句解构为极其精细的指令模块。
|
||||
- 🌍 **语言强制对齐**: 新增逻辑自适应模块，根据您的输入语言动态回溯对应语言输出。
|
||||
|
||||
## ✨ 核心优势
|
||||
|
||||
- 🎯 **精确结构化**: 输出带角色、目标、上下景深、拆解步骤、错误防御与输出规范格式。
|
||||
- ⚙️ **完美挂载**: 完全利用 OpenWebUI 原生面板支持动态下拉菜单选择。
|
||||
|
||||
## 🚀 如何使用
|
||||
|
||||
1. 查看提示词文件：[ai-task-instruction.md](./ai-task-instruction.md)
|
||||
2. **复制** 文件的完整内容。
|
||||
3. 打开 OpenWebUI，进入 **Workspace** -> **Prompts** 并点击 **Create Prompt**。
|
||||
4. 填写标题后，将复制的文本粘贴进内容。
|
||||
5. 在日常会话中，键入 `/` 呼出提示词，选择该模板并填充对应字段后发送即可。
|
||||
|
||||
## ⚙️ 动态变量 (Variables)
|
||||
|
||||
该模板使用 OpenWebUI 官方原生支持的提示词动态变量规范：
|
||||
|
||||
| 变量名 | 类型 | 选项 / 默认值 | 描述说明 |
|
||||
| :--- | :--- | :--- | :--- |
|
||||
| **target_role** | `text` | `AI Assistant` | 目标 Agent 应扮演的专家角色。 |
|
||||
| **complexity** | `select` | `Basic`, **`Intermediate`**, `Advanced` | 输出结果的拆解深度（Basic 等）。 |
|
||||
| **output_style** | `select` | **`Markdown Template`**, `JSON`, `Step-by-Step`| 提示词的结构化展示样式，如 Json/Md。 |
|
||||
| **requirements** | `textarea`| 必填 | 用户输入的原始自然语言需求文本。 |
|
||||
|
||||
## ⭐ 支持
|
||||
|
||||
如果该提示词扩展对您有所帮助，欢迎在 GitHub 给 [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) 点一个 Star，这是我最大的动力！
|
||||
24
prompts/ai-task-instruction/ai-task-instruction.md
Normal file
24
prompts/ai-task-instruction/ai-task-instruction.md
Normal file
@@ -0,0 +1,24 @@
|
||||
# AI Task Instruction Generator
|
||||
|
||||
You are an expert Prompt Engineer and Task Architect. Your objective is to transform vague or unstructured natural language requirements into precise, structured instructions optimized for AI agent execution.
|
||||
|
||||
## Input Data
|
||||
**Target Agent Role**: {{target_role | text:default="AI Assistant":placeholder="e.g., Senior Python Developer, Marketing Expert"}}
|
||||
**Task Complexity**: {{complexity | select:options=["Basic","Intermediate","Advanced"]:default="Intermediate"}}
|
||||
**Preferred Output Format**: {{output_style | select:options=["Markdown Template","JSON Protocol","Step-by-Step Guide"]:default="Markdown Template"}}
|
||||
|
||||
**Natural Language Requirements**:
|
||||
"""
|
||||
{{requirements | textarea:placeholder="Paste the raw task description or requirements here..."}}
|
||||
"""
|
||||
|
||||
## Generation Guidelines
|
||||
1. **Role Definition**: Assign a specific, expert persona suitable for the task.
|
||||
2. **Objective Clarity**: Clearly state the primary goal.
|
||||
3. **Contextualization**: Provide necessary background based on the input.
|
||||
4. **Step-by-Step Execution**: Break the task down into logical, atomic steps.
|
||||
5. **Constraints & Rules**: Explicitly list any negative constraints or formatting rules.
|
||||
6. **Output Specification**: Define exactly what the final result should look like.
|
||||
7. **Language Consistency**: You MUST generate the structured instructions in the same language as the natural language requirements input by the user (e.g., if the requirements are in Chinese, generate the response in Chinese).
|
||||
|
||||
Please generate the structured instructions now, strictly following the **{{output_style}}** format.
|
||||
45
prompts/one-sentence-concept-explainer/README.md
Normal file
45
prompts/one-sentence-concept-explainer/README.md
Normal file
@@ -0,0 +1,45 @@
|
||||
# 🔍 One-Sentence Concept Explainer
|
||||
|
||||
| By [Fu-Jie](https://github.com/Fu-Jie) · v1.0.0 | [⭐ Star this repo](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
|
||||
|
||||
Explain any highly technical or abstract concept in exactly one clear, punchy sentence adapting for a selected audience tier.
|
||||
|
||||
## 📋 Info
|
||||
|
||||
- **Command**: `/one-sentence-concept-explainer`
|
||||
|
||||
## 🔥 What's New in v1.0.0
|
||||
|
||||
- ✨ **Radical Simplicity AI**: Distills abstract definitions into a single, comprehensive line.
|
||||
- 🌍 **Consistency Engine**: Adopts to whatever language the prompt payload utilizes dynamically.
|
||||
|
||||
## ✨ Key Features
|
||||
|
||||
- 🎯 **Elevator Pitch accuracy**: Distills density while strictly conforming to length.
|
||||
- ⚙️ **Select Menus variables**: Adjust target profiles from ELI5 to Expert seamlessly.
|
||||
|
||||
## 🚀 How to Use
|
||||
|
||||
1. Check out the prompt template: [one-sentence-concept-explainer.md](./one-sentence-concept-explainer.md)
|
||||
2. **Copy** the full content.
|
||||
3. In OpenWebUI, Go to **Workspace** -> **Prompts** and click **Create Prompt**.
|
||||
4. Set title, and paste the template code into the content block.
|
||||
5. In your standard chat, trigger via `/one-sentence-concept-explainer` and fill in the fields.
|
||||
|
||||
## ⚙️ Configuration (Variables)
|
||||
|
||||
The template contains dynamic variables supported by OpenWebUI prompts:
|
||||
|
||||
| Variable | Type | Options / Default | Description |
|
||||
| :--- | :--- | :--- | :--- |
|
||||
| **concept** | `text` | Required | The concept to explain (e.g., Quantum Computing). |
|
||||
| **audience**| `select` | **`General Audience`**, `Child (ELI5)`, `Expert`, `Executive` | Destination audience profile. |
|
||||
| **tone** | `select` | **`Professional`**, `Analogical`, `Inspirational`, `Humorous` | Style with which the explanation speaks. |
|
||||
|
||||
## ⭐ Support
|
||||
|
||||
If this prompt has been useful, a star on [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) is a big motivation for me. Thank you for the support.
|
||||
45
prompts/one-sentence-concept-explainer/README_CN.md
Normal file
45
prompts/one-sentence-concept-explainer/README_CN.md
Normal file
@@ -0,0 +1,45 @@
|
||||
# 🔍 One-Sentence Concept Explainer (一句话概念解释器)
|
||||
|
||||
| 作者: [Fu-Jie](https://github.com/Fu-Jie) · v1.0.0 | [⭐ 给项目点个 Star](https://github.com/Fu-Jie/openwebui-extensions) |
|
||||
| :--- | ---: |
|
||||
|
||||
|  |  |  |  |  |  |  |
|
||||
| :---: | :---: | :---: | :---: | :---: | :---: | :---: |
|
||||
|
||||
将任何高级或抽象的概念，针对不同受众，用极其精练、准确且直击本质的**一句话**向特定的目标受众解释清楚。
|
||||
|
||||
## 📋 基础信息
|
||||
|
||||
- **触发指令 (Command)**: `/one-sentence-concept-explainer`
|
||||
|
||||
## 🔥 版本特性 v1.0.0
|
||||
|
||||
- ✨ **极致简约 AI**: 将本来具有门槛的名词解构为一针见血的单一句子，极合电梯游说场景。
|
||||
- 🌍 **规则回溯对齐**: 全自动化兼容处理，无需人工设定目标输出语言。
|
||||
|
||||
## ✨ 核心优势
|
||||
|
||||
- 🎯 **杜绝啰嗦**: 遵循严格的一句话长度指令执行率。
|
||||
- ⚙️ **兼容性高**: 下拉菜单一秒在儿童、专家、高管等维度自由切换密度视角。
|
||||
|
||||
## 🚀 如何使用
|
||||
|
||||
1. 查看提示词文件：[one-sentence-concept-explainer.md](./one-sentence-concept-explainer.md)
|
||||
2. **复制** 文件的完整内容。
|
||||
3. 打开 OpenWebUI，进入 **Workspace** -> **Prompts** 并点击 **Create Prompt**。
|
||||
4. 填写标题后，将复制的文本粘贴进内容。
|
||||
5. 在日常会话中，键入 `/` 呼出提示词，选择该模板并填充对应字段后发送即可。
|
||||
|
||||
## ⚙️ 动态变量 (Variables)
|
||||
|
||||
该模板使用 OpenWebUI 官方原生支持的提示词动态变量规范：
|
||||
|
||||
| 变量名 | 类型 | 选项 / 默认值 | 描述说明 |
|
||||
| :--- | :--- | :--- | :--- |
|
||||
| **concept** | `text` | 必填 | 要解释的概念（例如：量子纠缠）。 |
|
||||
| **audience**| `select` | **`General Audience`**, `Child (ELI5)`, `Expert`, `Executive` | 解释应当适配的目标受众群体。 |
|
||||
| **tone** | `select` | **`Professional`**, `Analogical`, `Inspirational`, `Humorous` | 解释所采用的词句风格和语气倾向。 |
|
||||
|
||||
## ⭐ 支持
|
||||
|
||||
如果该提示词扩展对您有所帮助，欢迎在 GitHub 给 [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) 点一个 Star，这是我最大的动力！
|
||||
@@ -0,0 +1,14 @@
|
||||
# One-Sentence Concept Explainer
|
||||
|
||||
You are an expert communicator specializing in radical simplicity. Your task is to explain the following concept in exactly one clear, punchy, and accurate sentence.
|
||||
|
||||
## Configuration
|
||||
- **Concept**: {{concept | text:placeholder="Enter the concept (e.g., Quantum Entanglement)"}}
|
||||
- **Target Audience**: {{audience | select:options=["General Audience","Child (ELI5)","Expert","Business Executive"]:default="General Audience"}}
|
||||
- **Tone**: {{tone | select:options=["Professional","Analogical","Inspirational","Humorous"]:default="Professional"}}
|
||||
|
||||
## Instructions
|
||||
1. Provide the explanation in the same language as the concept provided by the user (e.g., if the concept is in Chinese, provide explanation in Chinese).
|
||||
2. Ensure the response is strictly limited to one sentence.
|
||||
3. Capture the core essence of the concept while adjusting the complexity for the selected audience.
|
||||
4. If an analogy is requested, ensure it is relatable and accurate.
|
||||
Reference in New Issue
Block a user