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62 Commits

Author SHA1 Message Date
fujie
813b019653 release: GitHub Copilot SDK Pipe v0.1.1 2026-01-26 15:29:26 +08:00
github-actions[bot]
b0b1542939 chore: update community stats - new plugin added (18 -> 19), plugin version updated, points increased (148 -> 152), followers increased (157 -> 158) 2026-01-26 07:14:37 +00:00
github-actions[bot]
15f19d8b8d chore: update community stats - points increased (147 -> 148) 2026-01-26 00:38:32 +00:00
fujie
82253b114c feat(copilot-sdk): release v0.1.1 - remove db dependency, add timeout, fix streaming
- Remove database dependency for session management, use chat_id directly
- Add TIMEOUT valve (default 300s)
- Fix streaming issues by handling full message events
- Improve chat_id extraction and tool detection
- Update docs and bump version to 0.1.1
2026-01-26 07:25:01 +08:00
github-actions[bot]
e0bfbf6dd4 chore: update community stats - points increased (146 -> 147) 2026-01-25 19:07:08 +00:00
github-actions[bot]
4689e80e7a chore: update community stats - points increased (144 -> 146) 2026-01-25 11:07:02 +00:00
github-actions[bot]
556e6c1c67 chore: update community stats - new plugin added (17 -> 18), plugin version updated, points increased (143 -> 144) 2026-01-25 10:08:13 +00:00
github-actions[bot]
3ab84a526d chore: update community stats - followers increased (156 -> 157) 2026-01-25 02:55:55 +00:00
github-actions[bot]
bdce96f912 chore: update community stats - followers increased (155 -> 156) 2026-01-24 17:06:50 +00:00
github-actions[bot]
4811b99a4b chore: update community stats - followers increased (154 -> 155) 2026-01-24 05:08:58 +00:00
github-actions[bot]
fb2a64c07a chore: update community stats - followers increased (153 -> 154) 2026-01-23 20:09:48 +00:00
github-actions[bot]
e023e4f2e2 chore: update community stats - followers increased (152 -> 153) 2026-01-23 07:12:10 +00:00
github-actions[bot]
0b16b1e0f4 chore: update community stats - followers increased (151 -> 152) 2026-01-22 21:09:33 +00:00
github-actions[bot]
59073ad7ac chore: update community stats - points increased (141 -> 143) 2026-01-22 20:10:29 +00:00
github-actions[bot]
8248644c45 chore: update community stats - points increased (140 -> 141) 2026-01-22 16:13:08 +00:00
github-actions[bot]
f38e6394c9 chore: update community stats - points increased (136 -> 140) 2026-01-22 15:13:08 +00:00
github-actions[bot]
0aaa529c6b chore: update community stats - followers increased (150 -> 151) 2026-01-22 13:23:00 +00:00
github-actions[bot]
b81a6562a1 chore: update community stats - points increased (135 -> 136) 2026-01-22 11:10:17 +00:00
github-actions[bot]
c5b10db23a chore: update community stats - followers increased (149 -> 150) 2026-01-22 09:14:48 +00:00
github-actions[bot]
d16e444643 chore: update community stats - followers increased (148 -> 149) 2026-01-22 07:13:25 +00:00
github-actions[bot]
8202468099 chore: update community stats - followers increased (147 -> 148) 2026-01-22 06:13:25 +00:00
github-actions[bot]
766e8bd20f chore: update community stats - followers increased (146 -> 147) 2026-01-22 02:51:30 +00:00
github-actions[bot]
1214ab5a8c chore: update community stats - followers increased (145 -> 146) 2026-01-21 21:13:00 +00:00
github-actions[bot]
ebddbb25f8 chore: update community stats - followers increased (144 -> 145) 2026-01-21 15:13:27 +00:00
github-actions[bot]
59545e1110 chore: update community stats - plugin version updated, followers increased (143 -> 144) 2026-01-21 14:14:42 +00:00
fujie
500e090b11 fix: resolve TypeError and improve Pydantic compatibility in async-context-compression v1.2.2 2026-01-21 21:51:58 +08:00
github-actions[bot]
a75ee555fa chore: update community stats - followers increased (142 -> 143) 2026-01-21 13:22:53 +00:00
github-actions[bot]
6a8c2164cd chore: update community stats - followers increased (141 -> 142) 2026-01-21 12:15:46 +00:00
github-actions[bot]
7f7efa325a chore: update community stats - followers increased (140 -> 141) 2026-01-21 04:25:49 +00:00
github-actions[bot]
9ba6cb08fc chore: update community stats - followers increased (139 -> 140) 2026-01-20 20:27:29 +00:00
github-actions[bot]
1872271a2d chore: update community stats - new plugin added (16 -> 17), plugin version updated, points increased (134 -> 135) 2026-01-20 13:23:26 +00:00
fujie
813b50864a docs(folder-memory): add prerequisites section and enhance release workflow with README links
- Add 'Prerequisites' section to folder-memory README files clarifying that conversations must occur inside a folder
- Update docs/plugins/filters/folder-memory.md and folder-memory.zh.md with same prerequisites
- Enhance extract_plugin_versions.py to auto-generate GitHub README URLs in release notes
- Update plugin-development workflow to document README link requirements for publishing
2026-01-20 20:35:06 +08:00
github-actions[bot]
b18cefe320 chore: update community stats - followers increased (137 -> 139) 2026-01-20 12:15:40 +00:00
fujie
a54c359fcf docs(filters): remove language switchers and legacy references from folder-memory docs 2026-01-20 20:11:00 +08:00
fujie
8d83221a4a docs(filters): add author and project info to folder-memory READMEs and docs 2026-01-20 20:08:52 +08:00
fujie
1879000720 docs(filters): add 'What's New' section to folder-memory READMEs and docs
- Add prominent 'What's New' section to README.md, README_CN.md, and global docs.
- Ensure compliance with plugin development standards.
2026-01-20 20:07:46 +08:00
fujie
ba92649a98 feat(filters): refactor folder-rule-collector to folder-memory
- Rename plugin from `folder-rule-collector` to `folder-memory` for better clarity.
- Refactor code to focus on "Project Rules" collection, removing "Knowledge" collection for V1.
- Add `PRIORITY` valve (default: 20) to ensure execution after context compression.
- Update all parameter names to uppercase for consistency.
- Update documentation (README, global docs) with GitHub raw URL for demo image.
- Remove `STATUS` valve as it's redundant with OpenWebUI's built-in function toggle.
- Add `ROADMAP.md` to track future "Project Knowledge" features.
- Update `.github/copilot-instructions.md` with detailed commit message guidelines.
2026-01-20 20:02:50 +08:00
github-actions[bot]
d2276dcaae chore: update community stats - plugin version updated 2026-01-20 11:10:30 +00:00
fujie
25c9d20f3d feat(async-context-compression): release v1.2.1 with smart config & optimizations
This release introduces significant improvements to configuration flexibility, performance, and stability.

**Key Changes:**

*   **Smart Configuration:**
    *   Added `summary_model_max_context` to allow independent context limits for the summary model (e.g., using `gemini-flash` with 1M context to summarize `gpt-4` history).
    *   Implemented auto-detection of base model settings for custom models, ensuring correct threshold application.
*   **Performance & Refactoring:**
    *   Optimized `model_thresholds` parsing with caching to reduce overhead.
    *   Refactored `inlet` and `outlet` logic to remove redundant code and improve maintainability.
    *   Replaced all `print` statements with proper `logging` calls for better production monitoring.
*   **Bug Fixes & Modernization:**
    *   Fixed `datetime.utcnow()` deprecation warnings by switching to timezone-aware `datetime.now(timezone.utc)`.
    *   Corrected type annotations and improved error handling for `JSONResponse` objects from LLM backends.
    *   Removed hard truncation in summary generation to allow full context usage.

**Files Updated:**
*   Plugin source code (English & Chinese)
*   Documentation and READMEs
*   Version bumped to 1.2.1
2026-01-20 19:09:25 +08:00
github-actions[bot]
0d853577df chore: update community stats - followers increased (136 -> 137) 2026-01-20 09:15:24 +00:00
github-actions[bot]
f91f3d8692 chore: update community stats - followers increased (135 -> 136) 2026-01-20 07:14:01 +00:00
github-actions[bot]
0f7cad8dfa chore: update community stats - followers increased (134 -> 135) 2026-01-19 23:08:06 +00:00
fujie
db1a1e7ef0 fix(async-context-compression): sync CN version with EN version logic
- Add missing imports (contextlib, sessionmaker, Engine)
- Add database engine discovery functions (_discover_owui_engine, _discover_owui_schema)
- Fix ChatSummary table to support schema configuration
- Fix duplicate code in __init__ method
- Add _db_session context manager for robust session handling
- Fix inlet method signature (add __request__, __model__ parameters)
- Fix tool output trimming to check native function calling
- Add chat_id empty check in outlet method
2026-01-19 20:37:37 +08:00
github-actions[bot]
e7de80a059 chore: update community stats - plugin version updated, followers increased (133 -> 134) 2026-01-19 12:15:44 +00:00
fujie
0d8c4e048e release: async-context-compression v1.2.0 and markdown-normalizer v1.2.4 2026-01-19 20:11:55 +08:00
github-actions[bot]
014a5a9d1f chore: update community stats - followers increased (132 -> 133) 2026-01-19 10:11:26 +00:00
github-actions[bot]
a6dd970859 chore: update community stats - followers increased (131 -> 132) 2026-01-19 09:16:08 +00:00
github-actions[bot]
aac730f5b1 chore: update community stats - points increased (133 -> 134), followers increased (130 -> 131) 2026-01-19 07:15:13 +00:00
github-actions[bot]
ff95d9328e chore: update community stats - followers increased (129 -> 130) 2026-01-19 06:15:55 +00:00
github-actions[bot]
afe1d8cf52 chore: update community stats - points increased (118 -> 133) 2026-01-18 19:06:16 +00:00
github-actions[bot]
67b819f3de chore: update community stats - followers increased (128 -> 129) 2026-01-18 15:07:24 +00:00
github-actions[bot]
9b6acb6b95 chore: update community stats - points increased (117 -> 118), followers increased (127 -> 128) 2026-01-18 14:07:18 +00:00
github-actions[bot]
a9a59e1e34 chore: update community stats - followers increased (126 -> 127) 2026-01-18 13:14:54 +00:00
github-actions[bot]
5b05397356 chore: update community stats - followers increased (124 -> 126) 2026-01-18 12:13:26 +00:00
github-actions[bot]
7a7dbc0cfa chore: update community stats - points increased (116 -> 117) 2026-01-18 09:08:33 +00:00
github-actions[bot]
6ac0ba6efe chore: update community stats - followers increased (123 -> 124) 2026-01-18 08:10:15 +00:00
github-actions[bot]
d3d008efb4 chore: update community stats - followers increased (122 -> 123) 2026-01-18 07:08:42 +00:00
github-actions[bot]
4f1528128a chore: update community stats - followers increased (121 -> 122) 2026-01-18 05:10:36 +00:00
github-actions[bot]
93c4326206 chore: update community stats - followers increased (120 -> 121) 2026-01-18 01:37:36 +00:00
github-actions[bot]
0fca7fe524 chore: update community stats - points increased (113 -> 116) 2026-01-18 00:38:45 +00:00
github-actions[bot]
afdcab10c6 chore: update community stats - followers increased (119 -> 120) 2026-01-17 21:06:42 +00:00
github-actions[bot]
f8cc5eabe6 chore: update community stats - plugin version updated 2026-01-17 18:10:56 +00:00
46 changed files with 5298 additions and 461 deletions

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@@ -90,6 +90,9 @@ Reference: `.github/workflows/release.yml`
- Action: Automatically updates the plugin code and metadata on OpenWebUI.com using `scripts/publish_plugin.py`.
- **Auto-Sync**: If a local plugin has no ID but matches an existing published plugin by **Title**, the script will automatically fetch the ID, update the local file, and proceed with the update.
- Requirement: `OPENWEBUI_API_KEY` secret must be set.
- **README Link**: When announcing a release, always include the GitHub README URL for the plugin:
- Format: `https://github.com/Fu-Jie/awesome-openwebui/blob/main/plugins/{type}/{name}/README.md`
- Example: `https://github.com/Fu-Jie/awesome-openwebui/blob/main/plugins/filters/folder-memory/README.md`
### Pull Request Check
- Workflow: `.github/workflows/plugin-version-check.yml`

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@@ -100,13 +100,14 @@ description: 插件功能的简短描述。Brief description of plugin functiona
| `author_url` | 作者主页链接 | `https://github.com/Fu-Jie/awesome-openwebui` |
| `funding_url` | 赞助/项目链接 | `https://github.com/open-webui` |
| `version` | 语义化版本号 | `0.1.0`, `1.2.3` |
| `icon_url` | 图标 (Base64 编码的 SVG) | 见下方图标规范 |
| `icon_url` | 图标 (Base64 编码的 SVG) | 仅 Action 插件**必须**提供。其他类型可选。 |
| `requirements` | 额外依赖 (仅 OpenWebUI 环境未安装的) | `python-docx==1.1.2` |
| `description` | 功能描述 | `将对话导出为 Word 文档` |
#### 图标规范 (Icon Guidelines)
- 图标来源:从 [Lucide Icons](https://lucide.dev/icons/) 获取符合插件功能的图标
- 适用范围Action 插件**必须**提供,其他插件可选
- 格式Base64 编码的 SVG
- 获取方法:从 Lucide 下载 SVG然后使用 Base64 编码
- 示例格式:
@@ -822,6 +823,22 @@ Filter 实例是**单例 (Singleton)**。
#### Commit Message 规范
使用 Conventional Commits 格式 (`feat`, `fix`, `docs`, etc.)。
**必须**在提交标题与正文中清晰描述变更内容,确保在 Release 页面可读且可追踪。
要求:
- 标题必须包含“做了什么”与影响范围(避免含糊词)。
- 正文必须列出关键变更点1-3 条),与实际改动一一对应。
- 若影响用户或插件行为,必须在正文标明影响与迁移说明。
推荐格式:
- `feat(actions): add export settings panel`
- `fix(filters): handle empty metadata to avoid crash`
- `docs(plugins): update bilingual README structure`
正文示例:
- Add valves for export format selection
- Update README/README_CN to include What's New section
- Migration: default TITLE_SOURCE changed to chat_title
### 4. 🤖 Git Operations (Agent Rules)

View File

@@ -10,28 +10,28 @@ A collection of enhancements, plugins, and prompts for [OpenWebUI](https://githu
<!-- STATS_START -->
## 📊 Community Stats
> 🕐 Auto-updated: 2026-01-18 00:08
> 🕐 Auto-updated: 2026-01-26 15:14
| 👤 Author | 👥 Followers | ⭐ Points | 🏆 Contributions |
|:---:|:---:|:---:|:---:|
| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **119** | **113** | **25** |
| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **158** | **152** | **31** |
| 📝 Posts | ⬇️ Downloads | 👁️ Views | 👍 Upvotes | 💾 Saves |
|:---:|:---:|:---:|:---:|:---:|
| **16** | **1659** | **19990** | **99** | **126** |
| **19** | **2388** | **27294** | **138** | **183** |
### 🔥 Top 6 Popular Plugins
> 🕐 Auto-updated: 2026-01-18 00:08
> 🕐 Auto-updated: 2026-01-26 15:14
| Rank | Plugin | Version | Downloads | Views | Updated |
|:---:|------|:---:|:---:|:---:|:---:|
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 0.9.1 | 507 | 4641 | 2026-01-17 |
| 🥈 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 1.4.9 | 228 | 2285 | 2026-01-17 |
| 🥉 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 0.3.7 | 202 | 751 | 2026-01-07 |
| 4⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 1.1.3 | 174 | 1906 | 2026-01-17 |
| 5⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 0.4.3 | 134 | 1255 | 2026-01-17 |
| 6⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 0.2.4 | 132 | 2269 | 2026-01-17 |
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 0.9.1 | 629 | 5600 | 2026-01-17 |
| 🥈 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 1.4.9 | 410 | 3621 | 2026-01-25 |
| 🥉 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 0.3.7 | 255 | 1039 | 2026-01-07 |
| 4⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 0.4.3 | 229 | 1839 | 2026-01-17 |
| 5⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 1.2.2 | 227 | 2461 | 2026-01-21 |
| 6⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 0.2.4 | 165 | 2674 | 2026-01-17 |
*See full stats in [Community Stats Report](./docs/community-stats.md)*
<!-- STATS_END -->
@@ -43,6 +43,7 @@ A collection of enhancements, plugins, and prompts for [OpenWebUI](https://githu
Located in the `plugins/` directory, containing Python-based enhancements:
#### Actions
- **Smart Mind Map** (`smart-mind-map`): Generates interactive mind maps from text.
- **Smart Infographic** (`infographic`): Transforms text into professional infographics using AntV.
- **Flash Card** (`flash-card`): Quickly generates beautiful flashcards for learning.
@@ -51,11 +52,18 @@ Located in the `plugins/` directory, containing Python-based enhancements:
- **Export to Word** (`export_to_docx`): Exports chat history to Word documents.
#### Filters
- **Async Context Compression** (`async-context-compression`): Optimizes token usage via context compression.
- **Context Enhancement** (`context_enhancement_filter`): Enhances chat context.
- **Folder Memory** (`folder-memory`): Automatically extracts project rules from conversations and injects them into the folder's system prompt.
- **Markdown Normalizer** (`markdown_normalizer`): Fixes common Markdown formatting issues in LLM outputs.
#### Pipes
- **GitHub Copilot SDK** (`github-copilot-sdk`): Official GitHub Copilot SDK integration. Supports dynamic models, multi-turn conversation, streaming, multimodal input, and infinite sessions.
#### Pipelines
- **MoE Prompt Refiner** (`moe_prompt_refiner`): Refines prompts for Mixture of Experts (MoE) summary requests to generate high-quality comprehensive reports.
### 🎯 Prompts
@@ -100,6 +108,7 @@ This project is a collection of resources and does not require a Python environm
### Contributing
If you have great prompts or plugins to share:
1. Fork this repository.
2. Add your files to the appropriate `prompts/` or `plugins/` directory.
3. Submit a Pull Request.

View File

@@ -7,28 +7,28 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
<!-- STATS_START -->
## 📊 社区统计
> 🕐 自动更新于 2026-01-18 00:08
> 🕐 自动更新于 2026-01-26 15:14
| 👤 作者 | 👥 粉丝 | ⭐ 积分 | 🏆 贡献 |
|:---:|:---:|:---:|:---:|
| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **119** | **113** | **25** |
| [Fu-Jie](https://openwebui.com/u/Fu-Jie) | **158** | **152** | **31** |
| 📝 发布 | ⬇️ 下载 | 👁️ 浏览 | 👍 点赞 | 💾 收藏 |
|:---:|:---:|:---:|:---:|:---:|
| **16** | **1659** | **19990** | **99** | **126** |
| **19** | **2388** | **27294** | **138** | **183** |
### 🔥 热门插件 Top 6
> 🕐 自动更新于 2026-01-18 00:08
> 🕐 自动更新于 2026-01-26 15:14
| 排名 | 插件 | 版本 | 下载 | 浏览 | 更新日期 |
|:---:|------|:---:|:---:|:---:|:---:|
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 0.9.1 | 507 | 4641 | 2026-01-17 |
| 🥈 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 1.4.9 | 228 | 2285 | 2026-01-17 |
| 🥉 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 0.3.7 | 202 | 751 | 2026-01-07 |
| 4⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 1.1.3 | 174 | 1906 | 2026-01-17 |
| 5⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 0.4.3 | 134 | 1255 | 2026-01-17 |
| 6⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 0.2.4 | 132 | 2269 | 2026-01-17 |
| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | 0.9.1 | 629 | 5600 | 2026-01-17 |
| 🥈 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | 1.4.9 | 410 | 3621 | 2026-01-25 |
| 🥉 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | 0.3.7 | 255 | 1039 | 2026-01-07 |
| 4⃣ | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | 0.4.3 | 229 | 1839 | 2026-01-17 |
| 5⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | 1.2.2 | 227 | 2461 | 2026-01-21 |
| 6⃣ | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | 0.2.4 | 165 | 2674 | 2026-01-17 |
*完整统计请查看 [社区统计报告](./docs/community-stats.zh.md)*
<!-- STATS_END -->
@@ -40,6 +40,7 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
位于 `plugins/` 目录,包含各类 Python 编写的功能增强插件:
#### Actions (交互增强)
- **Smart Mind Map** (`smart-mind-map`): 智能分析文本并生成交互式思维导图。
- **Smart Infographic** (`infographic`): 基于 AntV 的智能信息图生成工具。
- **Flash Card** (`flash-card`): 快速生成精美的学习记忆卡片。
@@ -48,17 +49,22 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
- **Export to Word** (`export_to_docx`): 将对话内容导出为 Word 文档。
#### Filters (消息处理)
- **Async Context Compression** (`async-context-compression`): 异步上下文压缩,优化 Token 使用。
- **Context Enhancement** (`context_enhancement_filter`): 上下文增强过滤器。
- **Folder Memory** (`folder-memory`): 自动从对话中提取项目规则并注入到文件夹系统提示词中。
- **Gemini Manifold Companion** (`gemini_manifold_companion`): Gemini Manifold 配套增强。
- **Gemini Multimodal Filter** (`web_gemini_multimodel_filter`): 为任意模型提供多模态能力PDF、Office、视频等支持智能路由和字幕精修。
- **Markdown Normalizer** (`markdown_normalizer`): 修复 LLM 输出中常见的 Markdown 格式问题。
- **Multi-Model Context Merger** (`multi_model_context_merger`): 自动合并并注入多模型回答的上下文。
#### Pipes (模型管道)
- **GitHub Copilot SDK** (`github-copilot-sdk`): GitHub Copilot SDK 官方集成。支持动态模型、多轮对话、流式输出、图片输入及无限会话。
- **Gemini Manifold** (`gemini_mainfold`): 集成 Gemini 模型的管道。
#### 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。
### 🎯 提示词 (Prompts)
@@ -106,6 +112,7 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
### 贡献代码
如果你有优质的提示词或插件想要分享:
1. Fork 本仓库。
2. 将你的文件添加到对应的 `prompts/``plugins/` 目录。
3. 提交 Pull Request。

View File

@@ -1,7 +1,7 @@
{
"schemaVersion": 1,
"label": "downloads",
"message": "1.7k",
"message": "2.4k",
"color": "blue",
"namedLogo": "openwebui"
}

View File

@@ -1,6 +1,6 @@
{
"schemaVersion": 1,
"label": "followers",
"message": "119",
"message": "158",
"color": "blue"
}

View File

@@ -1,6 +1,6 @@
{
"schemaVersion": 1,
"label": "plugins",
"message": "16",
"message": "19",
"color": "green"
}

View File

@@ -1,6 +1,6 @@
{
"schemaVersion": 1,
"label": "points",
"message": "113",
"message": "152",
"color": "orange"
}

View File

@@ -1,6 +1,6 @@
{
"schemaVersion": 1,
"label": "upvotes",
"message": "99",
"message": "138",
"color": "brightgreen"
}

View File

@@ -1,14 +1,16 @@
{
"total_posts": 16,
"total_downloads": 1659,
"total_views": 19990,
"total_upvotes": 99,
"total_posts": 19,
"total_downloads": 2388,
"total_views": 27294,
"total_upvotes": 138,
"total_downvotes": 2,
"total_saves": 126,
"total_comments": 23,
"total_saves": 183,
"total_comments": 33,
"by_type": {
"pipe": 1,
"action": 14,
"unknown": 2
"unknown": 3,
"filter": 1
},
"posts": [
{
@@ -18,29 +20,29 @@
"version": "0.9.1",
"author": "Fu-Jie",
"description": "Intelligently analyzes text content and generates interactive mind maps to help users structure and visualize knowledge.",
"downloads": 507,
"views": 4641,
"upvotes": 14,
"saves": 28,
"downloads": 629,
"views": 5600,
"upvotes": 16,
"saves": 37,
"comments": 11,
"created_at": "2025-12-30",
"updated_at": "2026-01-17",
"url": "https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a"
},
{
"title": "📊 Smart Infographic (AntV)",
"title": "Smart Infographic",
"slug": "smart_infographic_ad6f0c7f",
"type": "action",
"version": "1.4.9",
"author": "Fu-Jie",
"description": "AI-powered infographic generator based on AntV Infographic. Supports professional templates, auto-icon matching, and SVG/PNG downloads.",
"downloads": 228,
"views": 2285,
"upvotes": 11,
"saves": 16,
"comments": 2,
"downloads": 410,
"views": 3621,
"upvotes": 18,
"saves": 27,
"comments": 7,
"created_at": "2025-12-28",
"updated_at": "2026-01-17",
"updated_at": "2026-01-25",
"url": "https://openwebui.com/posts/smart_infographic_ad6f0c7f"
},
{
@@ -50,31 +52,15 @@
"version": "0.3.7",
"author": "Fu-Jie",
"description": "Extracts tables from chat messages and exports them to Excel (.xlsx) files with smart formatting.",
"downloads": 202,
"views": 751,
"upvotes": 3,
"saves": 5,
"downloads": 255,
"views": 1039,
"upvotes": 4,
"saves": 6,
"comments": 0,
"created_at": "2025-05-30",
"updated_at": "2026-01-07",
"url": "https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d"
},
{
"title": "Async Context Compression",
"slug": "async_context_compression_b1655bc8",
"type": "action",
"version": "1.1.3",
"author": "Fu-Jie",
"description": "Reduces token consumption in long conversations while maintaining coherence through intelligent summarization and message compression.",
"downloads": 174,
"views": 1906,
"upvotes": 7,
"saves": 18,
"comments": 0,
"created_at": "2025-11-08",
"updated_at": "2026-01-17",
"url": "https://openwebui.com/posts/async_context_compression_b1655bc8"
},
{
"title": "Export to Word (Enhanced)",
"slug": "export_to_word_enhanced_formatting_fca6a315",
@@ -82,15 +68,31 @@
"version": "0.4.3",
"author": "Fu-Jie",
"description": "Export current conversation from Markdown to Word (.docx) with Mermaid diagrams rendered client-side (Mermaid.js, SVG+PNG), LaTeX math, real hyperlinks, improved tables, syntax highlighting, and blockquote support.",
"downloads": 134,
"views": 1255,
"upvotes": 6,
"saves": 15,
"downloads": 229,
"views": 1839,
"upvotes": 8,
"saves": 21,
"comments": 0,
"created_at": "2026-01-03",
"updated_at": "2026-01-17",
"url": "https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315"
},
{
"title": "Async Context Compression",
"slug": "async_context_compression_b1655bc8",
"type": "action",
"version": "1.2.2",
"author": "Fu-Jie",
"description": "Reduces token consumption in long conversations while maintaining coherence through intelligent summarization and message compression.",
"downloads": 227,
"views": 2461,
"upvotes": 9,
"saves": 27,
"comments": 0,
"created_at": "2025-11-08",
"updated_at": "2026-01-21",
"url": "https://openwebui.com/posts/async_context_compression_b1655bc8"
},
{
"title": "Flash Card",
"slug": "flash_card_65a2ea8f",
@@ -98,10 +100,10 @@
"version": "0.2.4",
"author": "Fu-Jie",
"description": "Quickly generates beautiful flashcards from text, extracting key points and categories.",
"downloads": 132,
"views": 2269,
"upvotes": 8,
"saves": 10,
"downloads": 165,
"views": 2674,
"upvotes": 11,
"saves": 13,
"comments": 2,
"created_at": "2025-12-30",
"updated_at": "2026-01-17",
@@ -111,34 +113,18 @@
"title": "Markdown Normalizer",
"slug": "markdown_normalizer_baaa8732",
"type": "action",
"version": "1.2.2",
"version": "1.2.4",
"author": "Fu-Jie",
"description": "A content normalizer filter that fixes common Markdown formatting issues in LLM outputs, such as broken code blocks, LaTeX formulas, and list formatting.",
"downloads": 63,
"views": 1746,
"upvotes": 9,
"saves": 15,
"downloads": 148,
"views": 2762,
"upvotes": 10,
"saves": 20,
"comments": 5,
"created_at": "2026-01-12",
"updated_at": "2026-01-17",
"updated_at": "2026-01-19",
"url": "https://openwebui.com/posts/markdown_normalizer_baaa8732"
},
{
"title": "导出为 Word (增强版)",
"slug": "导出为_word_支持公式流程图表格和代码块_8a6306c0",
"type": "action",
"version": "0.4.3",
"author": "Fu-Jie",
"description": "将对话导出为 Word (.docx),支持 Mermaid 图表 (客户端渲染 SVG+PNG)、LaTeX 数学公式、真实超链接、增强表格格式、代码高亮和引用块。",
"downloads": 62,
"views": 1262,
"upvotes": 10,
"saves": 3,
"comments": 1,
"created_at": "2026-01-04",
"updated_at": "2026-01-17",
"url": "https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0"
},
{
"title": "Deep Dive",
"slug": "deep_dive_c0b846e4",
@@ -146,15 +132,31 @@
"version": "1.0.0",
"author": "Fu-Jie",
"description": "A comprehensive thinking lens that dives deep into any content - from context to logic, insights, and action paths.",
"downloads": 58,
"views": 605,
"upvotes": 3,
"saves": 5,
"downloads": 91,
"views": 839,
"upvotes": 4,
"saves": 8,
"comments": 0,
"created_at": "2026-01-08",
"updated_at": "2026-01-08",
"url": "https://openwebui.com/posts/deep_dive_c0b846e4"
},
{
"title": "导出为 Word (增强版)",
"slug": "导出为_word_支持公式流程图表格和代码块_8a6306c0",
"type": "action",
"version": "0.4.3",
"author": "Fu-Jie",
"description": "将对话导出为 Word (.docx),支持 Mermaid 图表 (客户端渲染 SVG+PNG)、LaTeX 数学公式、真实超链接、增强表格格式、代码高亮和引用块。",
"downloads": 87,
"views": 1614,
"upvotes": 11,
"saves": 4,
"comments": 4,
"created_at": "2026-01-04",
"updated_at": "2026-01-17",
"url": "https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0"
},
{
"title": "📊 智能信息图 (AntV Infographic)",
"slug": "智能信息图_e04a48ff",
@@ -162,9 +164,9 @@
"version": "1.4.9",
"author": "Fu-Jie",
"description": "基于 AntV Infographic 的智能信息图生成插件。支持多种专业模板,自动图标匹配,并提供 SVG/PNG 下载功能。",
"downloads": 41,
"views": 654,
"upvotes": 5,
"downloads": 46,
"views": 781,
"upvotes": 6,
"saves": 0,
"comments": 0,
"created_at": "2025-12-28",
@@ -178,15 +180,47 @@
"version": "0.9.1",
"author": "Fu-Jie",
"description": "智能分析文本内容,生成交互式思维导图,帮助用户结构化和可视化知识。",
"downloads": 22,
"views": 392,
"upvotes": 2,
"downloads": 27,
"views": 447,
"upvotes": 4,
"saves": 1,
"comments": 0,
"created_at": "2025-12-31",
"updated_at": "2026-01-17",
"url": "https://openwebui.com/posts/智能生成交互式思维导图帮助用户可视化知识_8d4b097b"
},
{
"title": "📂 Folder Memory Auto-Evolving Project Context",
"slug": "folder_memory_auto_evolving_project_context_4a9875b2",
"type": "filter",
"version": "0.1.0",
"author": "Fu-Jie",
"description": "Automatically extracts project rules from conversations and injects them into the folder's system prompt.",
"downloads": 26,
"views": 725,
"upvotes": 3,
"saves": 4,
"comments": 0,
"created_at": "2026-01-20",
"updated_at": "2026-01-20",
"url": "https://openwebui.com/posts/folder_memory_auto_evolving_project_context_4a9875b2"
},
{
"title": "异步上下文压缩",
"slug": "异步上下文压缩_5c0617cb",
"type": "action",
"version": "1.2.2",
"author": "Fu-Jie",
"description": "通过智能摘要和消息压缩,降低长对话的 token 消耗,同时保持对话连贯性。",
"downloads": 20,
"views": 486,
"upvotes": 5,
"saves": 1,
"comments": 0,
"created_at": "2025-11-08",
"updated_at": "2026-01-21",
"url": "https://openwebui.com/posts/异步上下文压缩_5c0617cb"
},
{
"title": "闪记卡 (Flash Card)",
"slug": "闪记卡生成插件_4a31eac3",
@@ -194,31 +228,15 @@
"version": "0.2.4",
"author": "Fu-Jie",
"description": "快速将文本提炼为精美的学习记忆卡片,支持核心要点提取与分类。",
"downloads": 16,
"views": 430,
"upvotes": 4,
"downloads": 19,
"views": 507,
"upvotes": 6,
"saves": 1,
"comments": 0,
"created_at": "2025-12-30",
"updated_at": "2026-01-17",
"url": "https://openwebui.com/posts/闪记卡生成插件_4a31eac3"
},
{
"title": "异步上下文压缩",
"slug": "异步上下文压缩_5c0617cb",
"type": "action",
"version": "1.1.3",
"author": "Fu-Jie",
"description": "通过智能摘要和消息压缩,降低长对话的 token 消耗,同时保持对话连贯性。",
"downloads": 14,
"views": 340,
"upvotes": 4,
"saves": 1,
"comments": 0,
"created_at": "2025-11-08",
"updated_at": "2026-01-17",
"url": "https://openwebui.com/posts/异步上下文压缩_5c0617cb"
},
{
"title": "精读",
"slug": "精读_99830b0f",
@@ -226,15 +244,47 @@
"version": "1.0.0",
"author": "Fu-Jie",
"description": "全方位的思维透镜 —— 从背景全景到逻辑脉络,从深度洞察到行动路径。",
"downloads": 6,
"views": 254,
"upvotes": 2,
"downloads": 9,
"views": 306,
"upvotes": 3,
"saves": 1,
"comments": 0,
"created_at": "2026-01-08",
"updated_at": "2026-01-08",
"url": "https://openwebui.com/posts/精读_99830b0f"
},
{
"title": "GitHub Copilot Official SDK Pipe",
"slug": "github_copilot_official_sdk_pipe_ce96f7b4",
"type": "pipe",
"version": "0.1.1",
"author": "Fu-Jie",
"description": "Integrate GitHub Copilot SDK. Supports dynamic models, multi-turn conversation, streaming, multimodal input, and infinite sessions (context compaction).",
"downloads": 0,
"views": 8,
"upvotes": 1,
"saves": 0,
"comments": 0,
"created_at": "2026-01-26",
"updated_at": "2026-01-26",
"url": "https://openwebui.com/posts/github_copilot_official_sdk_pipe_ce96f7b4"
},
{
"title": "🚀 Open WebUI Prompt Plus: AI-Powered Prompt Manager",
"slug": "open_webui_prompt_plus_ai_powered_prompt_manager_s_15fa060e",
"type": "unknown",
"version": "",
"author": "",
"description": "",
"downloads": 0,
"views": 222,
"upvotes": 6,
"saves": 4,
"comments": 2,
"created_at": "2026-01-25",
"updated_at": "2026-01-25",
"url": "https://openwebui.com/posts/open_webui_prompt_plus_ai_powered_prompt_manager_s_15fa060e"
},
{
"title": "Review of Claude Haiku 4.5",
"slug": "review_of_claude_haiku_45_41b0db39",
@@ -243,8 +293,8 @@
"author": "",
"description": "",
"downloads": 0,
"views": 46,
"upvotes": 0,
"views": 93,
"upvotes": 1,
"saves": 0,
"comments": 0,
"created_at": "2026-01-14",
@@ -259,9 +309,9 @@
"author": "",
"description": "",
"downloads": 0,
"views": 1154,
"upvotes": 11,
"saves": 7,
"views": 1270,
"upvotes": 12,
"saves": 8,
"comments": 2,
"created_at": "2026-01-10",
"updated_at": "2026-01-10",
@@ -273,11 +323,11 @@
"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": 119,
"following": 2,
"total_points": 113,
"post_points": 97,
"followers": 158,
"following": 3,
"total_points": 152,
"post_points": 136,
"comment_points": 16,
"contributions": 25
"contributions": 31
}
}

View File

@@ -1,40 +1,45 @@
# 📊 OpenWebUI Community Stats Report
> 📅 Updated: 2026-01-18 00:08
> 📅 Updated: 2026-01-26 15:14
## 📈 Overview
| Metric | Value |
|------|------|
| 📝 Total Posts | 16 |
| ⬇️ Total Downloads | 1659 |
| 👁️ Total Views | 19990 |
| 👍 Total Upvotes | 99 |
| 💾 Total Saves | 126 |
| 💬 Total Comments | 23 |
| 📝 Total Posts | 19 |
| ⬇️ Total Downloads | 2388 |
| 👁️ Total Views | 27294 |
| 👍 Total Upvotes | 138 |
| 💾 Total Saves | 183 |
| 💬 Total Comments | 33 |
## 📂 By Type
- **pipe**: 1
- **action**: 14
- **unknown**: 2
- **unknown**: 3
- **filter**: 1
## 📋 Posts List
| Rank | Title | Type | Version | Downloads | Views | Upvotes | Saves | Updated |
|:---:|------|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.9.1 | 507 | 4641 | 14 | 28 | 2026-01-17 |
| 2 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.9 | 228 | 2285 | 11 | 16 | 2026-01-17 |
| 3 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 202 | 751 | 3 | 5 | 2026-01-07 |
| 4 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | action | 1.1.3 | 174 | 1906 | 7 | 18 | 2026-01-17 |
| 5 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 134 | 1255 | 6 | 15 | 2026-01-17 |
| 6 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 132 | 2269 | 8 | 10 | 2026-01-17 |
| 7 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | action | 1.2.2 | 63 | 1746 | 9 | 15 | 2026-01-17 |
| 8 | [导出为 Word (增强版)](https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0) | action | 0.4.3 | 62 | 1262 | 10 | 3 | 2026-01-17 |
| 9 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action | 1.0.0 | 58 | 605 | 3 | 5 | 2026-01-08 |
| 10 | [📊 智能信息图 (AntV Infographic)](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.4.9 | 41 | 654 | 5 | 0 | 2026-01-17 |
| 11 | [思维导图](https://openwebui.com/posts/智能生成交互式思维导图帮助用户可视化知识_8d4b097b) | action | 0.9.1 | 22 | 392 | 2 | 1 | 2026-01-17 |
| 12 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 16 | 430 | 4 | 1 | 2026-01-17 |
| 13 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | action | 1.1.3 | 14 | 340 | 4 | 1 | 2026-01-17 |
| 14 | [精读](https://openwebui.com/posts/精读_99830b0f) | action | 1.0.0 | 6 | 254 | 2 | 1 | 2026-01-08 |
| 15 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | unknown | | 0 | 46 | 0 | 0 | 2026-01-14 |
| 16 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | unknown | | 0 | 1154 | 11 | 7 | 2026-01-10 |
| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.9.1 | 629 | 5600 | 16 | 37 | 2026-01-17 |
| 2 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.9 | 410 | 3621 | 18 | 27 | 2026-01-25 |
| 3 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 255 | 1039 | 4 | 6 | 2026-01-07 |
| 4 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 229 | 1839 | 8 | 21 | 2026-01-17 |
| 5 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | action | 1.2.2 | 227 | 2461 | 9 | 27 | 2026-01-21 |
| 6 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 165 | 2674 | 11 | 13 | 2026-01-17 |
| 7 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | action | 1.2.4 | 148 | 2762 | 10 | 20 | 2026-01-19 |
| 8 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action | 1.0.0 | 91 | 839 | 4 | 8 | 2026-01-08 |
| 9 | [导出为 Word (增强版)](https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0) | action | 0.4.3 | 87 | 1614 | 11 | 4 | 2026-01-17 |
| 10 | [📊 智能信息图 (AntV Infographic)](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.4.9 | 46 | 781 | 6 | 0 | 2026-01-17 |
| 11 | [思维导图](https://openwebui.com/posts/智能生成交互式思维导图帮助用户可视化知识_8d4b097b) | action | 0.9.1 | 27 | 447 | 4 | 1 | 2026-01-17 |
| 12 | [📂 Folder Memory Auto-Evolving Project Context](https://openwebui.com/posts/folder_memory_auto_evolving_project_context_4a9875b2) | filter | 0.1.0 | 26 | 725 | 3 | 4 | 2026-01-20 |
| 13 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | action | 1.2.2 | 20 | 486 | 5 | 1 | 2026-01-21 |
| 14 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 19 | 507 | 6 | 1 | 2026-01-17 |
| 15 | [精读](https://openwebui.com/posts/精读_99830b0f) | action | 1.0.0 | 9 | 306 | 3 | 1 | 2026-01-08 |
| 16 | [GitHub Copilot Official SDK Pipe](https://openwebui.com/posts/github_copilot_official_sdk_pipe_ce96f7b4) | pipe | 0.1.1 | 0 | 8 | 1 | 0 | 2026-01-26 |
| 17 | [🚀 Open WebUI Prompt Plus: AI-Powered Prompt Manager](https://openwebui.com/posts/open_webui_prompt_plus_ai_powered_prompt_manager_s_15fa060e) | unknown | | 0 | 222 | 6 | 4 | 2026-01-25 |
| 18 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | unknown | | 0 | 93 | 1 | 0 | 2026-01-14 |
| 19 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | unknown | | 0 | 1270 | 12 | 8 | 2026-01-10 |

View File

@@ -1,40 +1,45 @@
# 📊 OpenWebUI 社区统计报告
> 📅 更新时间: 2026-01-18 00:08
> 📅 更新时间: 2026-01-26 15:14
## 📈 总览
| 指标 | 数值 |
|------|------|
| 📝 发布数量 | 16 |
| ⬇️ 总下载量 | 1659 |
| 👁️ 总浏览量 | 19990 |
| 👍 总点赞数 | 99 |
| 💾 总收藏数 | 126 |
| 💬 总评论数 | 23 |
| 📝 发布数量 | 19 |
| ⬇️ 总下载量 | 2388 |
| 👁️ 总浏览量 | 27294 |
| 👍 总点赞数 | 138 |
| 💾 总收藏数 | 183 |
| 💬 总评论数 | 33 |
## 📂 按类型分类
- **pipe**: 1
- **action**: 14
- **unknown**: 2
- **unknown**: 3
- **filter**: 1
## 📋 发布列表
| 排名 | 标题 | 类型 | 版本 | 下载 | 浏览 | 点赞 | 收藏 | 更新日期 |
|:---:|------|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.9.1 | 507 | 4641 | 14 | 28 | 2026-01-17 |
| 2 | [📊 Smart Infographic (AntV)](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.9 | 228 | 2285 | 11 | 16 | 2026-01-17 |
| 3 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 202 | 751 | 3 | 5 | 2026-01-07 |
| 4 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | action | 1.1.3 | 174 | 1906 | 7 | 18 | 2026-01-17 |
| 5 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 134 | 1255 | 6 | 15 | 2026-01-17 |
| 6 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 132 | 2269 | 8 | 10 | 2026-01-17 |
| 7 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | action | 1.2.2 | 63 | 1746 | 9 | 15 | 2026-01-17 |
| 8 | [导出为 Word (增强版)](https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0) | action | 0.4.3 | 62 | 1262 | 10 | 3 | 2026-01-17 |
| 9 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action | 1.0.0 | 58 | 605 | 3 | 5 | 2026-01-08 |
| 10 | [📊 智能信息图 (AntV Infographic)](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.4.9 | 41 | 654 | 5 | 0 | 2026-01-17 |
| 11 | [思维导图](https://openwebui.com/posts/智能生成交互式思维导图帮助用户可视化知识_8d4b097b) | action | 0.9.1 | 22 | 392 | 2 | 1 | 2026-01-17 |
| 12 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 16 | 430 | 4 | 1 | 2026-01-17 |
| 13 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | action | 1.1.3 | 14 | 340 | 4 | 1 | 2026-01-17 |
| 14 | [精读](https://openwebui.com/posts/精读_99830b0f) | action | 1.0.0 | 6 | 254 | 2 | 1 | 2026-01-08 |
| 15 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | unknown | | 0 | 46 | 0 | 0 | 2026-01-14 |
| 16 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | unknown | | 0 | 1154 | 11 | 7 | 2026-01-10 |
| 1 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | action | 0.9.1 | 629 | 5600 | 16 | 37 | 2026-01-17 |
| 2 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | action | 1.4.9 | 410 | 3621 | 18 | 27 | 2026-01-25 |
| 3 | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | action | 0.3.7 | 255 | 1039 | 4 | 6 | 2026-01-07 |
| 4 | [Export to Word (Enhanced)](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | action | 0.4.3 | 229 | 1839 | 8 | 21 | 2026-01-17 |
| 5 | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | action | 1.2.2 | 227 | 2461 | 9 | 27 | 2026-01-21 |
| 6 | [Flash Card](https://openwebui.com/posts/flash_card_65a2ea8f) | action | 0.2.4 | 165 | 2674 | 11 | 13 | 2026-01-17 |
| 7 | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | action | 1.2.4 | 148 | 2762 | 10 | 20 | 2026-01-19 |
| 8 | [Deep Dive](https://openwebui.com/posts/deep_dive_c0b846e4) | action | 1.0.0 | 91 | 839 | 4 | 8 | 2026-01-08 |
| 9 | [导出为 Word (增强版)](https://openwebui.com/posts/导出为_word_支持公式流程图表格和代码块_8a6306c0) | action | 0.4.3 | 87 | 1614 | 11 | 4 | 2026-01-17 |
| 10 | [📊 智能信息图 (AntV Infographic)](https://openwebui.com/posts/智能信息图_e04a48ff) | action | 1.4.9 | 46 | 781 | 6 | 0 | 2026-01-17 |
| 11 | [思维导图](https://openwebui.com/posts/智能生成交互式思维导图帮助用户可视化知识_8d4b097b) | action | 0.9.1 | 27 | 447 | 4 | 1 | 2026-01-17 |
| 12 | [📂 Folder Memory Auto-Evolving Project Context](https://openwebui.com/posts/folder_memory_auto_evolving_project_context_4a9875b2) | filter | 0.1.0 | 26 | 725 | 3 | 4 | 2026-01-20 |
| 13 | [异步上下文压缩](https://openwebui.com/posts/异步上下文压缩_5c0617cb) | action | 1.2.2 | 20 | 486 | 5 | 1 | 2026-01-21 |
| 14 | [闪记卡 (Flash Card)](https://openwebui.com/posts/闪记卡生成插件_4a31eac3) | action | 0.2.4 | 19 | 507 | 6 | 1 | 2026-01-17 |
| 15 | [精读](https://openwebui.com/posts/精读_99830b0f) | action | 1.0.0 | 9 | 306 | 3 | 1 | 2026-01-08 |
| 16 | [GitHub Copilot Official SDK Pipe](https://openwebui.com/posts/github_copilot_official_sdk_pipe_ce96f7b4) | pipe | 0.1.1 | 0 | 8 | 1 | 0 | 2026-01-26 |
| 17 | [🚀 Open WebUI Prompt Plus: AI-Powered Prompt Manager](https://openwebui.com/posts/open_webui_prompt_plus_ai_powered_prompt_manager_s_15fa060e) | unknown | | 0 | 222 | 6 | 4 | 2026-01-25 |
| 18 | [Review of Claude Haiku 4.5](https://openwebui.com/posts/review_of_claude_haiku_45_41b0db39) | unknown | | 0 | 93 | 1 | 0 | 2026-01-14 |
| 19 | [ 🛠️ Debug Open WebUI Plugins in Your Browser](https://openwebui.com/posts/debug_open_webui_plugins_in_your_browser_81bf7960) | unknown | | 0 | 1270 | 12 | 8 | 2026-01-10 |

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@@ -1,7 +1,7 @@
# Async Context Compression
<span class="category-badge filter">Filter</span>
<span class="version-badge">v1.1.3</span>
<span class="version-badge">v1.2.2</span>
Reduces token consumption in long conversations through intelligent summarization while maintaining conversational coherence.
@@ -34,6 +34,12 @@ This is especially useful for:
- :material-check-all: **Open WebUI v0.7.x Compatibility**: Dynamic DB session handling
- :material-account-convert: **Improved Compatibility**: Summary role changed to `assistant`
- :material-shield-check: **Enhanced Stability**: Resolved race conditions in state management
- :material-ruler: **Preflight Context Check**: Validates context fit before sending
- :material-format-align-justify: **Structure-Aware Trimming**: Preserves document structure
- :material-content-cut: **Native Tool Output Trimming**: Trims verbose tool outputs (Note: Non-native tool outputs are not fully injected into context)
- :material-chart-bar: **Detailed Token Logging**: Granular token breakdown
- :material-account-search: **Smart Model Matching**: Inherit config from base models
- :material-image-off: **Multimodal Support**: Images are preserved but tokens are **NOT** calculated
---
@@ -64,10 +70,14 @@ graph TD
| Option | Type | Default | Description |
|--------|------|---------|-------------|
| `token_threshold` | integer | `4000` | Trigger compression above this token count |
| `preserve_recent` | integer | `5` | Number of recent messages to keep uncompressed |
| `summary_model` | string | `"auto"` | Model to use for summarization |
| `compression_ratio` | float | `0.3` | Target compression ratio |
| `compression_threshold_tokens` | integer | `64000` | Trigger compression above this token count |
| `max_context_tokens` | integer | `128000` | Hard limit for context |
| `keep_first` | integer | `1` | Always keep the first N messages |
| `keep_last` | integer | `6` | Always keep the last N messages |
| `summary_model` | string | `None` | Model to use for summarization |
| `summary_model_max_context` | integer | `0` | Max context tokens for summary model |
| `max_summary_tokens` | integer | `16384` | Maximum tokens for the summary |
| `enable_tool_output_trimming` | boolean | `false` | Enable trimming of large tool outputs |
---

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@@ -1,7 +1,7 @@
# Async Context Compression异步上下文压缩
<span class="category-badge filter">Filter</span>
<span class="version-badge">v1.1.3</span>
<span class="version-badge">v1.2.2</span>
通过智能摘要减少长对话的 token 消耗,同时保持对话连贯。
@@ -34,6 +34,12 @@ Async Context Compression 过滤器通过以下方式帮助管理长对话的 to
- :material-check-all: **Open WebUI v0.7.x 兼容性**:动态数据库会话处理
- :material-account-convert: **兼容性提升**:摘要角色改为 `assistant`
- :material-shield-check: **稳定性增强**:解决状态管理竞态条件
- :material-ruler: **预检上下文检查**:发送前验证上下文是否超限
- :material-format-align-justify: **结构感知裁剪**:保留文档结构的智能裁剪
- :material-content-cut: **原生工具输出裁剪**:自动裁剪冗长的工具输出(注意:非原生工具调用输出不会完整注入上下文)
- :material-chart-bar: **详细 Token 日志**:提供细粒度的 Token 统计
- :material-account-search: **智能模型匹配**:自定义模型自动继承基础模型配置
- :material-image-off: **多模态支持**:图片内容保留但 Token **不参与计算**
---
@@ -64,10 +70,14 @@ graph TD
| 选项 | 类型 | 默认值 | 说明 |
|--------|------|---------|-------------|
| `token_threshold` | integer | `4000` | 超过该 token 数触发压缩 |
| `preserve_recent` | integer | `5` | 保留不压缩的最近消息数量 |
| `summary_model` | string | `"auto"` | 用于摘要的模型 |
| `compression_ratio` | float | `0.3` | 目标压缩比例 |
| `compression_threshold_tokens` | integer | `64000` | 超过该 token 数触发压缩 |
| `max_context_tokens` | integer | `128000` | 上下文硬性上限 |
| `keep_first` | integer | `1` | 始终保留的前 N 条消息 |
| `keep_last` | integer | `6` | 始终保留的后 N 条消息 |
| `summary_model` | string | `None` | 用于摘要的模型 |
| `summary_model_max_context` | integer | `0` | 摘要模型的最大上下文 Token 数 |
| `max_summary_tokens` | integer | `16384` | 摘要的最大 token 数 |
| `enable_tool_output_trimming` | boolean | `false` | 启用长工具输出裁剪 |
---

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@@ -0,0 +1,57 @@
# Folder Memory
**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 0.1.0 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
---
### 📌 What's new in 0.1.0
- **Initial Release**: Automated "Project Rules" management for OpenWebUI folders.
- **Folder-Level Persistence**: Automatically updates folder system prompts with extracted rules.
- **Optimized Performance**: Runs asynchronously and supports `PRIORITY` configuration for seamless integration with other filters.
---
**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.
This ensures that all future conversations within that folder share the same evolved context and rules, without manual updates.
## Features
- **Automatic Extraction**: Analyzes chat history every N messages to extract project rules.
- **Non-destructive Injection**: Updates only the specific "Project Rules" block in the system prompt, preserving other instructions.
- **Async Processing**: Runs in the background without blocking the user's chat experience.
- **ORM Integration**: Directly updates folder data using OpenWebUI's internal models for reliability.
## Prerequisites
- **Conversations must occur inside a folder.** This plugin only triggers when a chat belongs to a folder (i.e., you need to create a folder in OpenWebUI and start a conversation within it).
## Installation
1. Copy `folder_memory.py` to your OpenWebUI `plugins/filters/` directory (or upload via Admin UI).
2. Enable the filter in your **Settings** -> **Filters**.
3. (Optional) Configure the triggering threshold (default: every 10 messages).
## Configuration (Valves)
| Valve | Default | Description |
| :--- | :--- | :--- |
| `PRIORITY` | `20` | Priority level for the filter operations. |
| `MESSAGE_TRIGGER_COUNT` | `10` | The number of messages required to trigger a rule analysis. |
| `MODEL_ID` | `""` | The model used to generate rules. If empty, uses the current chat model. |
| `RULES_BLOCK_TITLE` | `## 📂 Project Rules` | The title displayed above the injected rules block. |
| `SHOW_DEBUG_LOG` | `False` | Show detailed debug logs in the browser console. |
| `UPDATE_ROOT_FOLDER` | `False` | If enabled, finds and updates the root folder rules instead of the current subfolder. |
## How It Works
![Folder Memory Demo](https://raw.githubusercontent.com/Fu-Jie/awesome-openwebui/main/plugins/filters/folder-memory/folder-memory-demo.png)
1. **Trigger**: When a conversation reaches `MESSAGE_TRIGGER_COUNT` (e.g., 10, 20 messages).
2. **Analysis**: The plugin sends the recent conversation + existing rules to the LLM.
3. **Synthesis**: The LLM merges new insights with old rules, removing obsolete ones.
4. **Update**: The new rule set replaces the `<!-- OWUI_PROJECT_RULES_START -->` block in the folder's system prompt.
## Roadmap
See [ROADMAP](https://github.com/Fu-Jie/awesome-openwebui/blob/main/plugins/filters/folder-memory/ROADMAP.md) for future plans, including "Project Knowledge" collection.

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@@ -0,0 +1,57 @@
# 文件夹记忆 (Folder Memory)
**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 0.1.0 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
---
### 📌 0.1.0 版本特性
- **首个版本发布**:专注于自动化的“项目规则”管理。
- **文件夹级持久化**:自动将提取的规则回写到文件夹系统提示词中。
- **性能优化**:采用异步处理机制,并支持 `PRIORITY` 配置,确保与其他过滤器(如上下文压缩)完美协作。
---
**文件夹记忆 (Folder Memory)** 是一个 OpenWebUI 的智能上下文过滤器插件。它能自动从文件夹内的对话中提取一致性的“项目规则”,并将其回写到文件夹的系统提示词中。
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。
## 功能特性
- **自动提取**:每隔 N 条消息分析一次聊天记录,提取项目规则。
- **无损注入**:仅更新系统提示词中的特定“项目规则”块,保留其他指令。
- **异步处理**:在后台运行,不阻塞用户的聊天体验。
- **ORM 集成**:直接使用 OpenWebUI 的内部模型更新文件夹数据,确保可靠性。
## 前置条件
- **对话必须在文件夹内进行。** 此插件仅在聊天属于某个文件夹时触发(即您需要先在 OpenWebUI 中创建一个文件夹,并在其内部开始对话)。
## 安装指南
1.`folder_memory.py` (或中文版 `folder_memory_cn.py`) 复制到 OpenWebUI 的 `plugins/filters/` 目录(或通过管理员 UI 上传)。
2.**设置** -> **过滤器** 中启用该插件。
3. (可选)配置触发阈值(默认:每 10 条消息)。
## 配置 (Valves)
| 参数 | 默认值 | 说明 |
| :--- | :--- | :--- |
| `PRIORITY` | `20` | 过滤器操作的优先级。 |
| `MESSAGE_TRIGGER_COUNT` | `10` | 触发规则分析的消息数量阈值。 |
| `MODEL_ID` | `""` | 用于生成规则的模型 ID。若为空则使用当前对话模型。 |
| `RULES_BLOCK_TITLE` | `## 📂 项目规则` | 显示在注入规则块上方的标题。 |
| `SHOW_DEBUG_LOG` | `False` | 在浏览器控制台显示详细调试日志。 |
| `UPDATE_ROOT_FOLDER` | `False` | 如果启用,将向上查找并更新根文件夹的规则,而不是当前子文件夹。 |
## 工作原理
![Folder Memory Demo](https://raw.githubusercontent.com/Fu-Jie/awesome-openwebui/main/plugins/filters/folder-memory/folder-memory-demo.png)
1. **触发**:当对话达到 `MESSAGE_TRIGGER_COUNT`(例如 10、20 条消息)时。
2. **分析**:插件将最近的对话 + 现有规则发送给 LLM。
3. **综合**LLM 将新见解与旧规则合并,移除过时的规则。
4. **更新**:新的规则集替换文件夹系统提示词中的 `<!-- OWUI_PROJECT_RULES_START -->` 块。
## 路线图
查看 [ROADMAP](https://github.com/Fu-Jie/awesome-openwebui/blob/main/plugins/filters/folder-memory/ROADMAP.md) 了解未来计划,包括“项目知识”收集功能。

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@@ -22,7 +22,7 @@ Filters act as middleware in the message pipeline:
Reduces token consumption in long conversations through intelligent summarization while maintaining coherence.
**Version:** 1.1.3
**Version:** 1.2.2
[:octicons-arrow-right-24: Documentation](async-context-compression.md)
@@ -36,7 +36,15 @@ Filters act as middleware in the message pipeline:
[:octicons-arrow-right-24: Documentation](context-enhancement.md)
- :material-folder-refresh:{ .lg .middle } **Folder Memory**
---
Automatically extracts consistent "Project Rules" from ongoing conversations within a folder and injects them back into the folder's system prompt.
**Version:** 0.1.0
[:octicons-arrow-right-24: Documentation](folder-memory.md)
- :material-format-paint:{ .lg .middle } **Markdown Normalizer**
@@ -44,7 +52,7 @@ Filters act as middleware in the message pipeline:
Fixes common Markdown formatting issues in LLM outputs, including Mermaid syntax, code blocks, and LaTeX formulas.
**Version:** 1.2.3
**Version:** 1.2.4
[:octicons-arrow-right-24: Documentation](markdown_normalizer.md)

View File

@@ -22,7 +22,7 @@ Filter 充当消息管线中的中间件:
通过智能总结减少长对话的 token 消耗,同时保持连贯性。
**版本:** 1.1.3
**版本:** 1.2.2
[:octicons-arrow-right-24: 查看文档](async-context-compression.md)
@@ -36,7 +36,15 @@ Filter 充当消息管线中的中间件:
[:octicons-arrow-right-24: 查看文档](context-enhancement.md)
- :material-folder-refresh:{ .lg .middle } **Folder Memory**
---
自动从文件夹内的对话中提取一致性的“项目规则”,并将其回写到文件夹的系统提示词中。
**版本:** 0.1.0
[:octicons-arrow-right-24: 查看文档](folder-memory.zh.md)
- :material-format-paint:{ .lg .middle } **Markdown Normalizer**
@@ -44,7 +52,7 @@ Filter 充当消息管线中的中间件:
修复 LLM 输出中常见的 Markdown 格式问题,包括 Mermaid 语法、代码块和 LaTeX 公式。
**版本:** 1.2.3
**版本:** 1.2.4
[:octicons-arrow-right-24: 查看文档](markdown_normalizer.zh.md)

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@@ -51,6 +51,10 @@ A content normalizer filter for Open WebUI that fixes common Markdown formatting
## Changelog
### v1.2.4
* **Documentation Updates**: Synchronized version numbers across all documentation and code files.
### v1.2.3
* **List Marker Protection Enhancement**: Fixed a bug where list markers (`*`) followed by plain text and emphasis were having their spaces incorrectly stripped (e.g., `* U16 forward` became `*U16 forward`).

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@@ -51,6 +51,10 @@
## 更新日志
### v1.2.4
* **文档更新**: 同步了所有文档和代码文件的版本号。
### v1.2.3
* **列表标记保护增强**: 修复了列表标记 (`*`) 后跟普通文本和强调标记时,空格被错误剥离的问题(例如 `* U16 前锋` 变成 `*U16 前锋`)。

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@@ -0,0 +1,84 @@
# GitHub Copilot SDK Pipe for OpenWebUI
**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 0.1.0 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
This is an advanced Pipe function for [OpenWebUI](https://github.com/open-webui/open-webui) that allows you to use GitHub Copilot models (such as `gpt-5`, `gpt-5-mini`, `claude-sonnet-4.5`) directly within OpenWebUI. It is built upon the official [GitHub Copilot SDK for Python](https://github.com/github/copilot-sdk), providing a native integration experience.
## 🚀 What's New (v0.1.0)
* **♾️ Infinite Sessions**: Automatic context compaction for long-running conversations. No more context limit errors!
* **🧠 Thinking Process**: Real-time display of model reasoning/thinking process (for supported models).
* **📂 Workspace Control**: Restricted workspace directory for secure file operations.
* **🔍 Model Filtering**: Exclude specific models using keywords (e.g., `codex`, `haiku`).
* **💾 Session Persistence**: Improved session resume logic using OpenWebUI chat ID mapping.
## ✨ Core Features
* **🚀 Official SDK Integration**: Built on the official SDK for stability and reliability.
* **💬 Multi-turn Conversation**: Automatically concatenates history context so Copilot understands your previous messages.
* **🌊 Streaming Output**: Supports typewriter effect for fast responses.
* **🖼️ Multimodal Support**: Supports image uploads, automatically converting them to attachments for Copilot (requires model support).
* **🛠️ Zero-config Installation**: Automatically detects and downloads the GitHub Copilot CLI, ready to use out of the box.
* **🔑 Secure Authentication**: Supports Fine-grained Personal Access Tokens for minimized permissions.
* **🐛 Debug Mode**: Built-in detailed log output for easy connection troubleshooting.
## 📦 Installation & Usage
### 1. Import Function
1. Open OpenWebUI.
2. Go to **Workspace** -> **Functions**.
3. Click **+** (Create Function).
4. Paste the content of `github_copilot_sdk.py` (or `github_copilot_sdk_cn.py` for Chinese) completely.
5. Save.
### 2. Configure Valves (Settings)
Find "GitHub Copilot" in the function list and click the **⚙️ (Valves)** icon to configure:
| Parameter | Description | Default |
| :--- | :--- | :--- |
| **GH_TOKEN** | **(Required)** Your GitHub Token. | - |
| **MODEL_ID** | The model name to use. Recommended `gpt-5-mini` or `gpt-5`. | `gpt-5-mini` |
| **CLI_PATH** | Path to the Copilot CLI. Will download automatically if not found. | `/usr/local/bin/copilot` |
| **DEBUG** | Whether to enable debug logs (output to chat). | `True` |
| **SHOW_THINKING** | Show model reasoning/thinking process. | `True` |
| **EXCLUDE_KEYWORDS** | Exclude models containing these keywords (comma separated). | - |
| **WORKSPACE_DIR** | Restricted workspace directory for file operations. | - |
| **INFINITE_SESSION** | Enable Infinite Sessions (automatic context compaction). | `True` |
| **COMPACTION_THRESHOLD** | Background compaction threshold (0.0-1.0). | `0.8` |
| **BUFFER_THRESHOLD** | Buffer exhaustion threshold (0.0-1.0). | `0.95` |
### 3. Get GH_TOKEN
For security, it is recommended to use a **Fine-grained Personal Access Token**:
1. Visit [GitHub Token Settings](https://github.com/settings/tokens?type=beta).
2. Click **Generate new token**.
3. **Repository access**: Select `All repositories` or `Public Repositories`.
4. **Permissions**:
* Click **Account permissions**.
* Find **Copilot Requests**, select **Read and write** (or Access).
5. Generate and copy the Token.
## 📋 Dependencies
This Pipe will automatically attempt to install the following dependencies:
* `github-copilot-sdk` (Python package)
* `github-copilot-cli` (Binary file, installed via official script)
## ⚠️ FAQ
* **Stuck on "Waiting..."**:
* Check if `GH_TOKEN` is correct and has `Copilot Requests` permission.
* Try changing `MODEL_ID` to `gpt-4o` or `copilot-chat`.
* **Images not recognized**:
* Ensure `MODEL_ID` is a model that supports multimodal input.
* **CLI Installation Failed**:
* Ensure the OpenWebUI container has internet access.
* You can manually download the CLI and specify `CLI_PATH` in Valves.
## 📄 License
MIT

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@@ -0,0 +1,84 @@
# GitHub Copilot SDK 官方管道
**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 0.1.0 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
这是一个用于 [OpenWebUI](https://github.com/open-webui/open-webui) 的高级 Pipe 函数,允许你直接在 OpenWebUI 中使用 GitHub Copilot 模型(如 `gpt-5`, `gpt-5-mini`, `claude-sonnet-4.5`)。它基于官方 [GitHub Copilot SDK for Python](https://github.com/github/copilot-sdk) 构建,提供了原生级的集成体验。
## 🚀 最新特性 (v0.1.0)
* **♾️ 无限会话 (Infinite Sessions)**:支持长对话的自动上下文压缩,告别上下文超限错误!
* **🧠 思考过程展示**:实时显示模型的推理/思考过程(需模型支持)。
* **📂 工作目录控制**:支持设置受限工作目录,确保文件操作安全。
* **🔍 模型过滤**:支持通过关键词排除特定模型(如 `codex`, `haiku`)。
* **💾 会话持久化**: 改进的会话恢复逻辑,直接关联 OpenWebUI 聊天 ID连接更稳定。
## ✨ 核心特性
* **🚀 官方 SDK 集成**:基于官方 SDK稳定可靠。
* **💬 多轮对话支持**自动拼接历史上下文Copilot 能理解你的前文。
* **🌊 流式输出 (Streaming)**:支持打字机效果,响应迅速。
* **🖼️ 多模态支持**:支持上传图片,自动转换为附件发送给 Copilot需模型支持
* **🛠️ 零配置安装**:自动检测并下载 GitHub Copilot CLI开箱即用。
* **🔑 安全认证**:支持 Fine-grained Personal Access Tokens权限最小化。
* **🐛 调试模式**:内置详细的日志输出,方便排查连接问题。
## 📦 安装与使用
### 1. 导入函数
1. 打开 OpenWebUI。
2. 进入 **Workspace** -> **Functions**
3. 点击 **+** (创建函数)。
4.`github_copilot_sdk_cn.py` 的内容完整粘贴进去。
5. 保存。
### 2. 配置 Valves (设置)
在函数列表中找到 "GitHub Copilot",点击 **⚙️ (Valves)** 图标进行配置:
| 参数 | 说明 | 默认值 |
| :--- | :--- | :--- |
| **GH_TOKEN** | **(必填)** 你的 GitHub Token。 | - |
| **MODEL_ID** | 使用的模型名称。推荐 `gpt-5-mini``gpt-5`。 | `gpt-5-mini` |
| **CLI_PATH** | Copilot CLI 的路径。如果未找到会自动下载。 | `/usr/local/bin/copilot` |
| **DEBUG** | 是否开启调试日志(输出到对话框)。 | `True` |
| **SHOW_THINKING** | 是否显示模型推理/思考过程。 | `True` |
| **EXCLUDE_KEYWORDS** | 排除包含这些关键词的模型 (逗号分隔)。 | - |
| **WORKSPACE_DIR** | 文件操作的受限工作目录。 | - |
| **INFINITE_SESSION** | 启用无限会话 (自动上下文压缩)。 | `True` |
| **COMPACTION_THRESHOLD** | 后台压缩阈值 (0.0-1.0)。 | `0.8` |
| **BUFFER_THRESHOLD** | 缓冲耗尽阈值 (0.0-1.0)。 | `0.95` |
### 3. 获取 GH_TOKEN
为了安全起见,推荐使用 **Fine-grained Personal Access Token**
1. 访问 [GitHub Token Settings](https://github.com/settings/tokens?type=beta)。
2. 点击 **Generate new token**
3. **Repository access**: 选择 `All repositories``Public Repositories`
4. **Permissions**:
* 点击 **Account permissions**
* 找到 **Copilot Requests**,选择 **Read and write** (或 Access)。
5. 生成并复制 Token。
## 📋 依赖说明
该 Pipe 会自动尝试安装以下依赖(如果环境中缺失):
* `github-copilot-sdk` (Python 包)
* `github-copilot-cli` (二进制文件,通过官方脚本安装)
## ⚠️ 常见问题
* **一直显示 "Waiting..."**
* 检查 `GH_TOKEN` 是否正确且拥有 `Copilot Requests` 权限。
* 尝试将 `MODEL_ID` 改为 `gpt-4o``copilot-chat`
* **图片无法识别**
* 确保 `MODEL_ID` 是支持多模态的模型。
* **CLI 安装失败**
* 确保 OpenWebUI 容器有外网访问权限。
* 你可以手动下载 CLI 并挂载到容器中,然后在 Valves 中指定 `CLI_PATH`
## 📄 许可证
MIT

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@@ -15,7 +15,7 @@ Pipes allow you to:
## Available Pipe Plugins
- [GitHub Copilot SDK](github-copilot-sdk.md) (v0.1.1) - Official GitHub Copilot SDK integration. Supports dynamic models, multi-turn conversation, streaming, multimodal input, and infinite sessions.
---

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@@ -15,7 +15,7 @@ Pipes 可以用于:
## 可用的 Pipe 插件
- [GitHub Copilot SDK](github-copilot-sdk.zh.md) (v0.1.1) - GitHub Copilot SDK 官方集成。支持动态模型、多轮对话、流式输出、图片输入及无限会话。
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# Async Context Compression Filter
**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 1.1.3 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 1.2.2 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
This filter reduces token consumption in long conversations through intelligent summarization and message compression while keeping conversations coherent.
## What's new in 1.2.2
- **Critical Fix**: Resolved `TypeError: 'str' object is not callable` caused by variable name conflict in logging function.
- **Compatibility**: Enhanced `params` handling to support Pydantic objects, improving compatibility with different OpenWebUI versions.
## What's new in 1.2.1
- **Smart Configuration**: Automatically detects base model settings for custom models and adds `summary_model_max_context` for independent summary limits.
- **Performance & Refactoring**: Optimized threshold parsing with caching, removed redundant code, and improved LLM response handling (JSONResponse support).
- **Bug Fixes & Modernization**: Fixed `datetime` deprecation warnings, corrected type annotations, and replaced print statements with proper logging.
## What's new in 1.2.0
- **Preflight Context Check**: Before sending to the model, validates that total tokens fit within the context window. Automatically trims or drops oldest messages if exceeded.
- **Structure-Aware Assistant Trimming**: When context exceeds the limit, long AI responses are intelligently collapsed while preserving their structure (headers H1-H6, first line, last line).
- **Native Tool Output Trimming**: Detects and trims native tool outputs (`function_calling: "native"`), extracting only the final answer. Enable via `enable_tool_output_trimming`. **Note**: Non-native tool outputs are not fully injected into context.
- **Consolidated Status Notifications**: Unified "Context Usage" and "Context Summary Updated" notifications with appended warnings (e.g., `| ⚠️ High Usage`) for clearer feedback.
- **Context Usage Warning**: Emits a warning notification when context usage exceeds 90%.
- **Enhanced Header Detection**: Optimized regex (`^#{1,6}\s+`) to avoid false positives like `#hashtag`.
- **Detailed Token Logging**: Logs now show token breakdown for System, Head, Summary, and Tail sections with total.
## What's new in 1.1.3
- **Improved Compatibility**: Changed summary injection role from `user` to `assistant` for better compatibility across different LLMs.
- **Enhanced Stability**: Fixed a race condition in state management that could cause "inlet state not found" warnings in high-concurrency scenarios.
- **Bug Fixes**: Corrected default model handling to prevent misleading logs when no model is specified.
## What's new in 1.1.2
- **Open WebUI v0.7.x Compatibility**: Resolved a critical database session binding error affecting Open WebUI v0.7.x users. The plugin now dynamically discovers the database engine and session context, ensuring compatibility across versions.
- **Enhanced Error Reporting**: Errors during background summary generation are now reported via both the status bar and browser console.
- **Robust Model Handling**: Improved handling of missing or invalid model IDs to prevent crashes.
## What's new in 1.1.1
- **Frontend Debugging**: Added `show_debug_log` option to print debug info to the browser console (F12).
- **Optimized Compression**: Improved token calculation logic to prevent aggressive truncation of history, ensuring more context is retained.
---
@@ -31,6 +39,12 @@ This filter reduces token consumption in long conversations through intelligent
- ✅ Persistent storage via Open WebUI's shared database connection (PostgreSQL, SQLite, etc.).
- ✅ Flexible retention policy to keep the first and last N messages.
- ✅ Smart injection of historical summaries back into the context.
- ✅ Structure-aware trimming that preserves document structure (headers, intro, conclusion).
- ✅ Native tool output trimming for cleaner context when using function calling.
- ✅ Real-time context usage monitoring with warning notifications (>90%).
- ✅ Detailed token logging for precise debugging and optimization.
-**Smart Model Matching**: Automatically inherits configuration from base models for custom presets.
-**Multimodal Support**: Images are preserved but their tokens are **NOT** calculated. Please adjust thresholds accordingly.
---
@@ -61,9 +75,11 @@ It is recommended to keep this filter early in the chain so it runs before filte
| `keep_first` | `1` | Always keep the first N messages (protects 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. |
| `max_summary_tokens` | `4000` | Maximum tokens for the generated summary. |
| `summary_model_max_context` | `0` | Max context tokens for the summary model. If 0, falls back to `model_thresholds` or global `max_context_tokens`. |
| `max_summary_tokens` | `16384` | Maximum tokens for the generated summary. |
| `summary_temperature` | `0.3` | Randomness for summary generation. Lower is more deterministic. |
| `model_thresholds` | `{}` | Per-model overrides for `compression_threshold_tokens` and `max_context_tokens` (useful for mixed models). |
| `enable_tool_output_trimming` | `false` | When enabled and `function_calling: "native"` is active, trims verbose tool outputs to extract only the final answer. |
| `debug_mode` | `true` | Log verbose debug info. Set to `false` in production. |
| `show_debug_log` | `false` | Print debug logs to browser console (F12). Useful for frontend debugging. |

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@@ -1,28 +1,36 @@
# 异步上下文压缩过滤器
**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 1.1.3 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 1.2.2 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
> **重要提示**:为了确保所有过滤器的可维护性和易用性,每个过滤器都应附带清晰、完整的文档,以确保其功能、配置和使用方法得到充分说明。
本过滤器通过智能摘要和消息压缩技术,在保持对话连贯性的同时,显著降低长对话的 Token 消耗。
## 1.2.2 版本更新
- **严重错误修复**: 解决了因日志函数变量名冲突导致的 `TypeError: 'str' object is not callable` 错误。
- **兼容性增强**: 改进了 `params` 处理逻辑以支持 Pydantic 对象,提高了对不同 OpenWebUI 版本的兼容性。
## 1.2.1 版本更新
- **智能配置增强**: 自动检测自定义模型的基础模型配置,并新增 `summary_model_max_context` 参数以独立控制摘要模型的上下文限制。
- **性能优化与重构**: 重构了阈值解析逻辑并增加缓存,移除了冗余的处理代码,并增强了 LLM 响应处理(支持 JSONResponse
- **稳定性改进**: 修复了 `datetime` 弃用警告,修正了类型注解,并将 print 语句替换为标准日志记录。
## 1.2.0 版本更新
- **预检上下文检查 (Preflight Context Check)**: 在发送给模型之前,验证总 Token 是否符合上下文窗口。如果超出,自动裁剪或丢弃最旧的消息。
- **结构感知助手裁剪 (Structure-Aware Assistant Trimming)**: 当上下文超出限制时,智能折叠过长的 AI 回复,同时保留其结构(标题 H1-H6、首行、尾行
- **原生工具输出裁剪 (Native Tool Output Trimming)**: 检测并裁剪原生工具输出 (`function_calling: "native"`),仅提取最终答案。通过 `enable_tool_output_trimming` 启用。**注意**:非原生工具调用输出不会完整注入上下文。
- **统一状态通知**: 统一了“上下文使用情况”和“上下文摘要更新”的通知,并附加警告(例如 `| ⚠️ 高负载`),反馈更清晰。
- **上下文使用警告**: 当上下文使用率超过 90% 时发出警告通知。
- **增强的标题检测**: 优化了正则表达式 (`^#{1,6}\s+`) 以避免误判(如 `#hashtag`)。
- **详细 Token 日志**: 日志现在显示 System、Head、Summary 和 Tail 部分的 Token 细分及总计。
## 1.1.3 版本更新
- **兼容性提升**: 将摘要注入角色从 `user` 改为 `assistant`,以提高在不同 LLM 之间的兼容性。
- **稳定性增强**: 修复了状态管理中的竞态条件,解决了高并发场景下可能出现的“无法获取 inlet 状态”警告。
- **Bug 修复**: 修正了默认模型处理逻辑,防止在未指定模型时产生误导性日志。
## 1.1.2 版本更新
- **Open WebUI v0.7.x 兼容性**: 修复了影响 Open WebUI v0.7.x 用户的严重数据库会话绑定错误。插件现在动态发现数据库引擎和会话上下文,确保跨版本兼容性。
- **增强错误报告**: 后台摘要生成过程中的错误现在会通过状态栏和浏览器控制台同时报告。
- **健壮的模型处理**: 改进了对缺失或无效模型 ID 的处理,防止程序崩溃。
## 1.1.1 版本更新
- **前端调试**: 新增 `show_debug_log` 选项,支持在浏览器控制台 (F12) 打印调试信息。
- **压缩优化**: 优化 Token 计算逻辑,防止历史记录被过度截断,保留更多上下文。
---
@@ -33,6 +41,12 @@
-**持久化存储**: 复用 Open WebUI 共享数据库连接,自动支持 PostgreSQL/SQLite 等。
-**灵活保留策略**: 可配置保留对话头部和尾部消息,确保关键信息连贯。
-**智能注入**: 将历史摘要智能注入到新上下文中。
-**结构感知裁剪**: 智能折叠过长消息,保留文档骨架(标题、首尾)。
-**原生工具输出裁剪**: 支持裁剪冗长的工具调用输出。
-**实时监控**: 实时监控上下文使用情况,超过 90% 发出警告。
-**详细日志**: 提供精确的 Token 统计日志,便于调试。
-**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。
详细的工作原理和流程请参考 [工作流程指南](WORKFLOW_GUIDE_CN.md)。
@@ -74,6 +88,7 @@
| 参数 | 默认值 | 描述 |
| :-------------------- | :------ | :------------------------------------------------------------------------------------------------------------------------------------------ |
| `summary_model` | `None` | 用于生成摘要的模型 ID。**强烈建议**配置快速、经济、上下文窗口大的模型(如 `gemini-2.5-flash``deepseek-v3`)。留空则尝试复用当前对话模型。 |
| `summary_model_max_context` | `0` | 摘要模型的最大上下文 Token 数。如果为 0则回退到 `model_thresholds` 或全局 `max_context_tokens`。 |
| `max_summary_tokens` | `16384` | 生成摘要时允许的最大 Token 数。 |
| `summary_temperature` | `0.1` | 控制摘要生成的随机性,较低的值结果更稳定。 |
@@ -100,15 +115,12 @@
}
```
#### `debug_mode`
- **默认值**: `true`
- **描述**: 是否在 Open WebUI 的控制台日志中打印详细的调试信息(如 Token 计数、压缩进度、数据库操作等)。生产环境建议设为 `false`
#### `show_debug_log`
- **默认值**: `false`
- **描述**: 是否在浏览器控制台 (F12) 打印调试日志。便于前端调试。
| 参数 | 默认值 | 描述 |
| :----------------------------- | :------- | :-------------------------------------------------------------------------------------------------------------------------------------- |
| `enable_tool_output_trimming` | `false` | 启用时,若 `function_calling: "native"` 激活,将裁剪冗长的工具输出以仅提取最终答案。 |
| `debug_mode` | `true` | 是否在 Open WebUI 的控制台日志中打印详细的调试信息(如 Token 计数、压缩进度、数据库操作等)。生产环境建议设为 `false` |
| `show_debug_log` | `false` | 是否在浏览器控制台 (F12) 打印调试日志。便于前端调试。 |
| `show_token_usage_status` | `true` | 是否在对话结束时显示 Token 使用情况的状态通知。 |
---

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# Folder Memory
**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 0.1.0 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
---
### 📌 What's new in 0.1.0
- **Initial Release**: Automated "Project Rules" management for OpenWebUI folders.
- **Folder-Level Persistence**: Automatically updates folder system prompts with extracted rules.
- **Optimized Performance**: Runs asynchronously and supports `PRIORITY` configuration for seamless integration with other filters.
---
**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.
## ✨ Features
- **Automatic Extraction**: Analyzes chat history every N messages to extract project rules.
- **Non-destructive Injection**: Updates only the specific "Project Rules" block in the system prompt, preserving other instructions.
- **Async Processing**: Runs in the background without blocking the user's chat experience.
- **ORM Integration**: Directly updates folder data using OpenWebUI's internal models for reliability.
## ⚠️ Prerequisites
- **Conversations must occur inside a folder.** This plugin only triggers when a chat belongs to a folder (i.e., you need to create a folder in OpenWebUI and start a conversation within it).
## 📦 Installation
1. Copy `folder_memory.py` to your OpenWebUI `plugins/filters/` directory (or upload via Admin UI).
2. Enable the filter in your **Settings** -> **Filters**.
3. (Optional) Configure the triggering threshold (default: every 10 messages).
## ⚙️ Configuration (Valves)
| Valve | Default | Description |
| :--- | :--- | :--- |
| `PRIORITY` | `20` | Priority level for the filter operations. |
| `MESSAGE_TRIGGER_COUNT` | `10` | The number of messages required to trigger a rule analysis. |
| `MODEL_ID` | `""` | The model used to generate rules. If empty, uses the current chat model. |
| `RULES_BLOCK_TITLE` | `## 📂 Project Rules` | The title displayed above the injected rules block. |
| `SHOW_DEBUG_LOG` | `False` | Show detailed debug logs in the browser console. |
| `UPDATE_ROOT_FOLDER` | `False` | If enabled, finds and updates the root folder rules instead of the current subfolder. |
## 🛠️ How It Works
![Folder Memory Demo](https://raw.githubusercontent.com/Fu-Jie/awesome-openwebui/main/plugins/filters/folder-memory/folder-memory-demo.png)
1. **Trigger**: When a conversation reaches `MESSAGE_TRIGGER_COUNT` (e.g., 10, 20 messages).
2. **Analysis**: The plugin sends the recent conversation + existing rules to the LLM.
3. **Synthesis**: The LLM merges new insights with old rules, removing obsolete ones.
4. **Update**: The new rule set replaces the `<!-- OWUI_PROJECT_RULES_START -->` block in the folder's system prompt.
## ⚠️ Notes
- This plugin modifies the `system_prompt` of your folders.
- It uses a specific marker `<!-- OWUI_PROJECT_RULES_START -->` to locate its content. Do not manually remove these markers if you want the plugin to continue managing that section.
## 🗺️ Roadmap
See [ROADMAP.md](./ROADMAP.md) for future plans, including "Project Knowledge" collection.

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# 文件夹记忆 (Folder Memory)
**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 0.1.0 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
---
### 📌 0.1.0 版本特性
- **首个版本发布**:专注于自动化的“项目规则”管理。
- **文件夹级持久化**:自动将提取的规则回写到文件夹系统提示词中。
- **性能优化**:采用异步处理机制,并支持 `PRIORITY` 配置,确保与其他过滤器(如上下文压缩)完美协作。
---
**文件夹记忆 (Folder Memory)** 是一个 OpenWebUI 的智能上下文过滤器插件。它能自动从文件夹内的对话中提取一致性的“项目规则”,并将其回写到文件夹的系统提示词中。
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。
## ✨ 功能特性
- **自动提取**:每隔 N 条消息分析一次聊天记录,提取项目规则。
- **无损注入**:仅更新系统提示词中的特定“项目规则”块,保留其他指令。
- **异步处理**:在后台运行,不阻塞用户的聊天体验。
- **ORM 集成**:直接使用 OpenWebUI 的内部模型更新文件夹数据,确保可靠性。
## ⚠️ 前置条件
- **对话必须在文件夹内进行。** 此插件仅在聊天属于某个文件夹时触发(即您需要先在 OpenWebUI 中创建一个文件夹,并在其内部开始对话)。
## 📦 安装指南
1.`folder_memory.py` (或中文版 `folder_memory_cn.py`) 复制到 OpenWebUI 的 `plugins/filters/` 目录(或通过管理员 UI 上传)。
2.**设置** -> **过滤器** 中启用该插件。
3. (可选)配置触发阈值(默认:每 10 条消息)。
## ⚙️ 配置 (Valves)
| 参数 | 默认值 | 说明 |
| :--- | :--- | :--- |
| `PRIORITY` | `20` | 过滤器操作的优先级。 |
| `MESSAGE_TRIGGER_COUNT` | `10` | 触发规则分析的消息数量阈值。 |
| `MODEL_ID` | `""` | 用于生成规则的模型 ID。若为空则使用当前对话模型。 |
| `RULES_BLOCK_TITLE` | `## 📂 项目规则` | 显示在注入规则块上方的标题。 |
| `SHOW_DEBUG_LOG` | `False` | 在浏览器控制台显示详细调试日志。 |
| `UPDATE_ROOT_FOLDER` | `False` | 如果启用,将向上查找并更新根文件夹的规则,而不是当前子文件夹。 |
## 🛠️ 工作原理
![Folder Memory Demo](https://raw.githubusercontent.com/Fu-Jie/awesome-openwebui/main/plugins/filters/folder-memory/folder-memory-demo.png)
1. **触发**:当对话达到 `MESSAGE_TRIGGER_COUNT`(例如 10、20 条消息)时。
2. **分析**:插件将最近的对话 + 现有规则发送给 LLM。
3. **综合**LLM 将新见解与旧规则合并,移除过时的规则。
4. **更新**:新的规则集替换文件夹系统提示词中的 `<!-- OWUI_PROJECT_RULES_START -->` 块。
## ⚠️ 注意事项
- 此插件会修改文件夹的 `system_prompt`
- 它使用特定标记 `<!-- OWUI_PROJECT_RULES_START -->` 来定位内容。如果您希望插件继续管理该部分,请勿手动删除这些标记。
## 🗺️ 路线图
查看 [ROADMAP.md](./ROADMAP.md) 了解未来计划,包括“项目知识”收集功能。

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# Roadmap
## Future Features
### 🧠 Project Knowledge (Planned)
In future versions, we plan to introduce "Project Knowledge" collection. Unlike "Rules" which are strict instructions, "Knowledge" will capture reusable information, consensus, and context that helps the LLM understand the project better.
- **Knowledge Extraction**: Automatically extract reusable knowledge (terminology, style guides, business logic) from conversations.
- **Long-term Memory**: Use the entire folder's chat history as a corpus for knowledge generation.
- **Context Injection**: Inject summarized knowledge into the system prompt alongside rules.

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"""
title: 📂 Folder Memory
author: Fu-Jie
author_url: https://github.com/Fu-Jie/awesome-openwebui
funding_url: https://github.com/open-webui
version: 0.1.0
description: Automatically extracts project rules from conversations and injects them into the folder's system prompt.
requirements:
"""
from pydantic import BaseModel, Field
from typing import Optional, Dict, List
from fastapi import Request
import logging
import json
import re
import asyncio
from datetime import datetime
from open_webui.utils.chat import generate_chat_completion
from open_webui.models.users import Users
from open_webui.models.folders import Folders, FolderUpdateForm
from open_webui.models.chats import Chats
logging.basicConfig(
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)
# Markers for rule injection
RULES_BLOCK_START = "<!-- OWUI_PROJECT_RULES_START -->"
RULES_BLOCK_END = "<!-- OWUI_PROJECT_RULES_END -->"
# System Prompt for Rule Generation
SYSTEM_PROMPT_RULE_GENERATOR = """
You are a project rule extractor. Your task is to extract "Project Rules" from the conversation and merge them with existing rules.
### Input
1. **Existing Rules**: Current rules in the folder system prompt.
2. **Conversation**: Recent chat history.
### Goal
Synthesize a concise list of rules that apply to this project/folder.
- **Remove** rules that are no longer relevant or were one-off instructions.
- **Add** new consistent requirements found in the conversation.
- **Merge** similar rules.
- **Format**: Concise bullet points (Markdown).
### Output Format
ONLY output the rules list as Markdown bullet points. Do not include any intro/outro text.
Example:
- Always use Python 3.11 for type hinting.
- Docstrings must follow Google style.
- Commit messages should be in English.
"""
class Filter:
class Valves(BaseModel):
PRIORITY: int = Field(
default=20, description="Priority level for the filter operations."
)
SHOW_DEBUG_LOG: bool = Field(
default=False, description="Show debug logs in console."
)
MESSAGE_TRIGGER_COUNT: int = Field(
default=10, description="Analyze rules after every N messages in a chat."
)
MODEL_ID: str = Field(
default="",
description="Model used for rule extraction. If empty, uses the current chat model.",
)
RULES_BLOCK_TITLE: str = Field(
default="## 📂 Project Rules",
description="Title displayed above the rules block.",
)
UPDATE_ROOT_FOLDER: bool = Field(
default=False,
description="If enabled, finds and updates the root folder rules instead of the current subfolder.",
)
def __init__(self):
self.valves = self.Valves()
# ==================== Helper Methods ====================
def _get_user_context(self, __user__: Optional[dict]) -> Dict[str, str]:
"""Safely extracts user context information."""
if isinstance(__user__, (list, tuple)):
user_data = __user__[0] if __user__ else {}
elif isinstance(__user__, dict):
user_data = __user__
else:
user_data = {}
return {
"user_id": user_data.get("id", ""),
"user_name": user_data.get("name", "User"),
"user_language": user_data.get("language", "en-US"),
}
def _get_chat_context(
self, body: dict, __metadata__: Optional[dict] = None
) -> Dict[str, str]:
"""Unified extraction of chat context information (chat_id, message_id)."""
chat_id = ""
message_id = ""
if isinstance(body, dict):
chat_id = body.get("chat_id", "")
message_id = body.get("id", "")
if not chat_id or not message_id:
body_metadata = body.get("metadata", {})
if isinstance(body_metadata, dict):
if not chat_id:
chat_id = body_metadata.get("chat_id", "")
if not message_id:
message_id = body_metadata.get("message_id", "")
if __metadata__ and isinstance(__metadata__, dict):
if not chat_id:
chat_id = __metadata__.get("chat_id", "")
if not message_id:
message_id = __metadata__.get("message_id", "")
return {
"chat_id": str(chat_id).strip(),
"message_id": str(message_id).strip(),
}
async def _emit_debug_log(self, __event_emitter__, title: str, data: dict):
if self.valves.SHOW_DEBUG_LOG and __event_emitter__:
try:
# Flat log format as requested
js_code = f"""
console.log("[Folder Memory] {title}", {json.dumps(data, ensure_ascii=False)});
"""
await __event_emitter__({"type": "execute", "data": {"code": js_code}})
except Exception as e:
logger.error(f"Error emitting log: {e}")
async def _emit_status(
self, __event_emitter__, description: str, done: bool = False
):
if __event_emitter__:
await __event_emitter__(
{"type": "status", "data": {"description": description, "done": done}}
)
def _get_folder_id(self, body: dict) -> Optional[str]:
# 1. Try retrieving folder_id specifically from metadata
if "metadata" in body and isinstance(body["metadata"], dict):
if "folder_id" in body["metadata"]:
return body["metadata"]["folder_id"]
# 2. Check regular body chat object if available
if "chat" in body and isinstance(body["chat"], dict):
if "folder_id" in body["chat"]:
return body["chat"]["folder_id"]
# 3. Try fallback via Chat ID (Most reliable)
chat_id = body.get("chat_id")
if not chat_id:
if "metadata" in body and isinstance(body["metadata"], dict):
chat_id = body["metadata"].get("chat_id")
if chat_id:
try:
chat = Chats.get_chat_by_id(chat_id)
if chat and chat.folder_id:
return chat.folder_id
except Exception as e:
logger.error(f"Failed to fetch chat {chat_id}: {e}")
return None
def _extract_existing_rules(self, system_prompt: str) -> str:
pattern = re.compile(
re.escape(RULES_BLOCK_START) + r"([\s\S]*?)" + re.escape(RULES_BLOCK_END)
)
match = pattern.search(system_prompt)
if match:
# Remove title if it's inside the block
content = match.group(1).strip()
# Simple cleanup of the title if user formatted it inside
title_pat = re.compile(r"^#+\s+.*$", re.MULTILINE)
return title_pat.sub("", content).strip()
return ""
def _inject_rules(self, system_prompt: str, new_rules: str, title: str) -> str:
new_block_content = f"\n{title}\n\n{new_rules}\n"
new_block = f"{RULES_BLOCK_START}{new_block_content}{RULES_BLOCK_END}"
system_prompt = system_prompt or ""
pattern = re.compile(
re.escape(RULES_BLOCK_START) + r"[\s\S]*?" + re.escape(RULES_BLOCK_END)
)
if pattern.search(system_prompt):
return pattern.sub(new_block, system_prompt).strip()
else:
# Append if not found
if system_prompt:
return f"{system_prompt}\n\n{new_block}"
else:
return new_block
async def _generate_new_rules(
self,
current_rules: str,
messages: List[Dict],
user_id: str,
__request__: Request,
) -> str:
# Prepare context
conversation_text = "\n".join(
[
f"{msg['role'].upper()}: {msg['content']}"
for msg in messages[-20:] # Analyze last 20 messages context
]
)
prompt = f"""
Existing Rules:
{current_rules if current_rules else "None"}
Conversation Excerpt:
{conversation_text}
Please output the updated Project Rules:
"""
payload = {
"model": self.valves.MODEL_ID,
"messages": [
{"role": "system", "content": SYSTEM_PROMPT_RULE_GENERATOR},
{"role": "user", "content": prompt},
],
"stream": False,
}
try:
# We need a user object for permission checks in generate_chat_completion
user = Users.get_user_by_id(user_id)
if not user:
return current_rules
completion = await generate_chat_completion(__request__, payload, user)
if "choices" in completion and len(completion["choices"]) > 0:
content = completion["choices"][0]["message"]["content"].strip()
# Basic validation: ensure it looks like a list
if (
content.startswith("-")
or content.startswith("*")
or content.startswith("1.")
):
return content
except Exception as e:
logger.error(f"Rule generation failed: {e}")
return current_rules
async def _process_rules_update(
self,
folder_id: str,
body: dict,
user_id: str,
__request__: Request,
__event_emitter__,
):
try:
await self._emit_debug_log(
__event_emitter__,
"Start Processing",
{"step": "start", "initial_folder_id": folder_id, "user_id": user_id},
)
# 1. Fetch Folder Data (ORM)
initial_folder = Folders.get_folder_by_id_and_user_id(folder_id, user_id)
if not initial_folder:
await self._emit_debug_log(
__event_emitter__,
"Error: Initial folder not found",
{
"step": "fetch_initial_folder",
"initial_folder_id": folder_id,
"user_id": user_id,
},
)
return
# Subfolder handling logic
target_folder = initial_folder
if self.valves.UPDATE_ROOT_FOLDER:
# Traverse up until a folder with no parent_id is found
while target_folder and getattr(target_folder, "parent_id", None):
try:
parent = Folders.get_folder_by_id_and_user_id(
target_folder.parent_id, user_id
)
if parent:
target_folder = parent
else:
break
except Exception as e:
await self._emit_debug_log(
__event_emitter__,
"Warning: Failed to traverse parent folder",
{"step": "traverse_root", "error": str(e)},
)
break
target_folder_id = target_folder.id
await self._emit_debug_log(
__event_emitter__,
"Target Folder Resolved",
{
"step": "target_resolved",
"target_folder_id": target_folder_id,
"target_folder_name": target_folder.name,
"is_root_update": target_folder_id != folder_id,
},
)
existing_data = target_folder.data if target_folder.data else {}
existing_sys_prompt = existing_data.get("system_prompt", "")
# 2. Extract Existing Rules
current_rules_content = self._extract_existing_rules(existing_sys_prompt)
# 3. Generate New Rules
await self._emit_status(
__event_emitter__, "Analyzing project rules...", done=False
)
messages = body.get("messages", [])
new_rules_content = await self._generate_new_rules(
current_rules_content, messages, user_id, __request__
)
rules_changed = new_rules_content != current_rules_content
# 4. If no change, skip
if not rules_changed:
await self._emit_debug_log(
__event_emitter__,
"No Changes",
{
"step": "check_changes",
"reason": "content_identical_or_generation_failed",
},
)
await self._emit_status(
__event_emitter__,
"Rule analysis complete: No new content.",
done=True,
)
return
# 5. Inject Rules into System Prompt
updated_sys_prompt = existing_sys_prompt
if rules_changed:
updated_sys_prompt = self._inject_rules(
updated_sys_prompt,
new_rules_content,
self.valves.RULES_BLOCK_TITLE,
)
await self._emit_debug_log(
__event_emitter__,
"Ready to Update DB",
{"step": "pre_db_update", "target_folder_id": target_folder_id},
)
# 6. Update Folder (ORM) - Only update 'data' field
existing_data["system_prompt"] = updated_sys_prompt
updated_folder = Folders.update_folder_by_id_and_user_id(
target_folder_id,
user_id,
FolderUpdateForm(data=existing_data),
)
if not updated_folder:
raise Exception("Update folder failed (ORM returned None)")
await self._emit_status(
__event_emitter__, "Rule analysis complete: Rules updated.", done=True
)
await self._emit_debug_log(
__event_emitter__,
"Rule Generation Process & Change Details",
{
"step": "success",
"folder_id": target_folder_id,
"target_is_root": target_folder_id != folder_id,
"model_used": self.valves.MODEL_ID,
"analyzed_messages_count": len(messages),
"old_rules_length": len(current_rules_content),
"new_rules_length": len(new_rules_content),
"changes_digest": {
"old_rules_preview": (
current_rules_content[:100] + "..."
if current_rules_content
else "None"
),
"new_rules_preview": (
new_rules_content[:100] + "..."
if new_rules_content
else "None"
),
},
"timestamp": datetime.now().isoformat(),
},
)
except Exception as e:
logger.error(f"Async rule processing error: {e}")
await self._emit_status(
__event_emitter__, "Failed to update rules.", done=True
)
# Emit error to console for debugging
await self._emit_debug_log(
__event_emitter__,
"Execution Error",
{"error": str(e), "folder_id": folder_id},
)
# ==================== Filter Hooks ====================
async def inlet(
self, body: dict, __user__: Optional[dict] = None, __event_emitter__=None
) -> dict:
return body
async def outlet(
self,
body: dict,
__user__: Optional[dict] = None,
__event_emitter__=None,
__request__: Optional[Request] = None,
) -> dict:
user_ctx = self._get_user_context(__user__)
chat_ctx = self._get_chat_context(body)
messages = body.get("messages", [])
if not messages:
return body
# Trigger logic: Message Count threshold
if len(messages) % self.valves.MESSAGE_TRIGGER_COUNT != 0:
return body
folder_id = self._get_folder_id(body)
if not folder_id:
await self._emit_debug_log(
__event_emitter__,
"Skipping Analysis",
{
"reason": "Chat does not belong to any folder",
"chat_id": chat_ctx.get("chat_id"),
},
)
return body
# User Info
user_id = user_ctx.get("user_id")
if not user_id:
return body
# Async Task
if self.valves.MODEL_ID == "":
self.valves.MODEL_ID = body.get("model", "")
asyncio.create_task(
self._process_rules_update(
folder_id, body, user_id, __request__, __event_emitter__
)
)
return body

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"""
title: 📂 文件夹记忆 (Folder Memory)
author: Fu-Jie
author_url: https://github.com/Fu-Jie/awesome-openwebui
funding_url: https://github.com/open-webui
version: 0.1.0
description: 自动从对话中提取项目规则,并将其注入到文件夹的系统提示词中。
requirements:
"""
from pydantic import BaseModel, Field
from typing import Optional, Dict, List
from fastapi import Request
import logging
import json
import re
import asyncio
from datetime import datetime
from open_webui.utils.chat import generate_chat_completion
from open_webui.models.users import Users
from open_webui.models.folders import Folders, FolderUpdateForm
from open_webui.models.chats import Chats
logging.basicConfig(
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)
# 规则注入标记
RULES_BLOCK_START = "<!-- OWUI_PROJECT_RULES_START -->"
RULES_BLOCK_END = "<!-- OWUI_PROJECT_RULES_END -->"
# 规则生成系统提示词
SYSTEM_PROMPT_RULE_GENERATOR = """
你是一个项目规则提取器。你的任务是从对话中提取“项目规则”,并与现有规则合并。
### 输入
1. **现有规则 (Existing Rules)**:当前文件夹系统提示词中的规则。
2. **对话片段 (Conversation)**:最近的聊天记录。
### 目标
综合生成一份适用于当前项目/文件夹的简洁规则列表。
- **移除** 不再相关或仅是一次性指令的规则。
- **添加** 对话中发现的新的、一致性的要求。
- **合并** 相似的规则。
- **格式**:简洁的 Markdown 项目符号列表。
### 输出格式
仅输出 Markdown 项目符号列表形式的规则。不要包含任何开头或结尾的说明文字。
示例:
- 始终使用 Python 3.11 进行类型提示。
- 文档字符串必须遵循 Google 风格。
- 提交信息必须使用英文。
"""
class Filter:
class Valves(BaseModel):
PRIORITY: int = Field(default=20, description="过滤器操作的优先级。")
SHOW_DEBUG_LOG: bool = Field(
default=False, description="在控制台显示调试日志。"
)
MESSAGE_TRIGGER_COUNT: int = Field(
default=10, description="每隔 N 条消息分析一次规则。"
)
MODEL_ID: str = Field(
default="", description="用于提取规则的模型 ID。为空则使用当前对话模型。"
)
RULES_BLOCK_TITLE: str = Field(
default="## 📂 项目规则", description="显示在规则块上方的标题。"
)
UPDATE_ROOT_FOLDER: bool = Field(
default=False,
description="如果启用,将向上查找并更新根文件夹的规则,而不是当前子文件夹。",
)
def __init__(self):
self.valves = self.Valves()
# ==================== 辅助方法 ====================
def _get_user_context(self, __user__: Optional[dict]) -> Dict[str, str]:
"""安全提取用户上下文信息。"""
if isinstance(__user__, (list, tuple)):
user_data = __user__[0] if __user__ else {}
elif isinstance(__user__, dict):
user_data = __user__
else:
user_data = {}
return {
"user_id": user_data.get("id", ""),
"user_name": user_data.get("name", "User"),
"user_language": user_data.get("language", "zh-CN"),
}
def _get_chat_context(
self, body: dict, __metadata__: Optional[dict] = None
) -> Dict[str, str]:
"""统一提取聊天上下文信息 (chat_id, message_id)。"""
chat_id = ""
message_id = ""
if isinstance(body, dict):
chat_id = body.get("chat_id", "")
message_id = body.get("id", "")
if not chat_id or not message_id:
body_metadata = body.get("metadata", {})
if isinstance(body_metadata, dict):
if not chat_id:
chat_id = body_metadata.get("chat_id", "")
if not message_id:
message_id = body_metadata.get("message_id", "")
if __metadata__ and isinstance(__metadata__, dict):
if not chat_id:
chat_id = __metadata__.get("chat_id", "")
if not message_id:
message_id = __metadata__.get("message_id", "")
return {
"chat_id": str(chat_id).strip(),
"message_id": str(message_id).strip(),
}
async def _emit_debug_log(self, __event_emitter__, title: str, data: dict):
if self.valves.SHOW_DEBUG_LOG and __event_emitter__:
try:
# 按照用户要求的格式输出展平的日志
js_code = f"""
console.log("[Folder Memory] {title}", {json.dumps(data, ensure_ascii=False)});
"""
await __event_emitter__({"type": "execute", "data": {"code": js_code}})
except Exception as e:
logger.error(f"发出日志错误: {e}")
async def _emit_status(
self, __event_emitter__, description: str, done: bool = False
):
if __event_emitter__:
await __event_emitter__(
{"type": "status", "data": {"description": description, "done": done}}
)
def _get_folder_id(self, body: dict) -> Optional[str]:
# 1. 尝试从 metadata 获取 folder_id
if "metadata" in body and isinstance(body["metadata"], dict):
if "folder_id" in body["metadata"]:
return body["metadata"]["folder_id"]
# 2. 检查 chat 对象
if "chat" in body and isinstance(body["chat"], dict):
if "folder_id" in body["chat"]:
return body["chat"]["folder_id"]
# 3. 尝试通过 Chat ID 查找 (最可靠的方法)
chat_id = body.get("chat_id")
if not chat_id:
if "metadata" in body and isinstance(body["metadata"], dict):
chat_id = body["metadata"].get("chat_id")
if chat_id:
try:
chat = Chats.get_chat_by_id(chat_id)
if chat and chat.folder_id:
return chat.folder_id
except Exception as e:
logger.error(f"获取聊天信息失败 chat_id={chat_id}: {e}")
return None
def _extract_existing_rules(self, system_prompt: str) -> str:
pattern = re.compile(
re.escape(RULES_BLOCK_START) + r"([\s\S]*?)" + re.escape(RULES_BLOCK_END)
)
match = pattern.search(system_prompt)
if match:
# 如果标题在块内,将其移除以便纯净合并
content = match.group(1).strip()
title_pat = re.compile(r"^#+\s+.*$", re.MULTILINE)
return title_pat.sub("", content).strip()
return ""
def _inject_rules(self, system_prompt: str, new_rules: str, title: str) -> str:
new_block_content = f"\n{title}\n\n{new_rules}\n"
new_block = f"{RULES_BLOCK_START}{new_block_content}{RULES_BLOCK_END}"
system_prompt = system_prompt or ""
pattern = re.compile(
re.escape(RULES_BLOCK_START) + r"[\s\S]*?" + re.escape(RULES_BLOCK_END)
)
if pattern.search(system_prompt):
# 替换现有块
return pattern.sub(new_block, system_prompt).strip()
else:
# 追加到末尾
if system_prompt:
return f"{system_prompt}\n\n{new_block}"
else:
return new_block
async def _generate_new_rules(
self,
current_rules: str,
messages: List[Dict],
user_id: str,
__request__: Request,
) -> str:
# 准备上下文
conversation_text = "\n".join(
[
f"{msg['role'].upper()}: {msg['content']}"
for msg in messages[-20:] # 分析最近 20 条消息上下文
]
)
prompt = f"""
Existing Rules (现有规则):
{current_rules if current_rules else ""}
Conversation Excerpt (对话片段):
{conversation_text}
Please output the updated Project Rules (请输出更新后的项目规则):
"""
payload = {
"model": self.valves.MODEL_ID,
"messages": [
{"role": "system", "content": SYSTEM_PROMPT_RULE_GENERATOR},
{"role": "user", "content": prompt},
],
"stream": False,
}
try:
# 需要用户对象进行权限检查
user = Users.get_user_by_id(user_id)
if not user:
return current_rules
completion = await generate_chat_completion(__request__, payload, user)
if "choices" in completion and len(completion["choices"]) > 0:
content = completion["choices"][0]["message"]["content"].strip()
# 简单验证:确保看起来像个列表
if (
content.startswith("-")
or content.startswith("*")
or content.startswith("1.")
):
return content
except Exception as e:
logger.error(f"规则生成失败: {e}")
return current_rules
async def _process_rules_update(
self,
folder_id: str,
body: dict,
user_id: str,
__request__: Request,
__event_emitter__,
):
try:
await self._emit_debug_log(
__event_emitter__,
"开始处理",
{"step": "start", "initial_folder_id": folder_id, "user_id": user_id},
)
# 1. 获取文件夹数据 (ORM)
initial_folder = Folders.get_folder_by_id_and_user_id(folder_id, user_id)
if not initial_folder:
await self._emit_debug_log(
__event_emitter__,
"错误:未找到初始文件夹",
{
"step": "fetch_initial_folder",
"initial_folder_id": folder_id,
"user_id": user_id,
},
)
return
# 处理子文件夹逻辑:决定是更新当前文件夹还是根文件夹
target_folder = initial_folder
if self.valves.UPDATE_ROOT_FOLDER:
# 向上遍历直到找到没有 parent_id 的根文件夹
while target_folder and getattr(target_folder, "parent_id", None):
try:
parent = Folders.get_folder_by_id_and_user_id(
target_folder.parent_id, user_id
)
if parent:
target_folder = parent
else:
break
except Exception as e:
await self._emit_debug_log(
__event_emitter__,
"警告:向上查找父文件夹失败",
{"step": "traverse_root", "error": str(e)},
)
break
target_folder_id = target_folder.id
await self._emit_debug_log(
__event_emitter__,
"定目标文件夹",
{
"step": "target_resolved",
"target_folder_id": target_folder_id,
"target_folder_name": target_folder.name,
"is_root_update": target_folder_id != folder_id,
},
)
existing_data = target_folder.data if target_folder.data else {}
existing_sys_prompt = existing_data.get("system_prompt", "")
# 2. 提取现有规则
current_rules_content = self._extract_existing_rules(existing_sys_prompt)
# 3. 生成新规则
await self._emit_status(
__event_emitter__, "正在分析项目规则...", done=False
)
messages = body.get("messages", [])
new_rules_content = await self._generate_new_rules(
current_rules_content, messages, user_id, __request__
)
rules_changed = new_rules_content != current_rules_content
# 如果生成结果无变更
if not rules_changed:
await self._emit_debug_log(
__event_emitter__,
"无变更",
{
"step": "check_changes",
"reason": "content_identical_or_generation_failed",
},
)
await self._emit_status(
__event_emitter__, "规则分析完成:无新增内容。", done=True
)
return
# 5. 注入规则到 System Prompt
updated_sys_prompt = existing_sys_prompt
if rules_changed:
updated_sys_prompt = self._inject_rules(
updated_sys_prompt,
new_rules_content,
self.valves.RULES_BLOCK_TITLE,
)
await self._emit_debug_log(
__event_emitter__,
"准备更新数据库",
{"step": "pre_db_update", "target_folder_id": target_folder_id},
)
# 6. 更新文件夹 (ORM) - 仅更新 'data' 字段
existing_data["system_prompt"] = updated_sys_prompt
updated_folder = Folders.update_folder_by_id_and_user_id(
target_folder_id,
user_id,
FolderUpdateForm(data=existing_data),
)
if not updated_folder:
raise Exception("Update folder failed (ORM returned None)")
await self._emit_status(
__event_emitter__, "规则分析完成:规则已更新。", done=True
)
await self._emit_debug_log(
__event_emitter__,
"规则生成过程和变更详情",
{
"step": "success",
"folder_id": target_folder_id,
"target_is_root": target_folder_id != folder_id,
"model_used": self.valves.MODEL_ID,
"analyzed_messages_count": len(messages),
"old_rules_length": len(current_rules_content),
"new_rules_length": len(new_rules_content),
"changes_digest": {
"old_rules_preview": (
current_rules_content[:100] + "..."
if current_rules_content
else "None"
),
"new_rules_preview": (
new_rules_content[:100] + "..."
if new_rules_content
else "None"
),
},
"timestamp": datetime.now().isoformat(),
},
)
except Exception as e:
logger.error(f"异步规则处理错误: {e}")
await self._emit_status(__event_emitter__, "更新规则失败。", done=True)
# 在控制台也输出错误信息,方便调试
await self._emit_debug_log(
__event_emitter__, "执行出错", {"error": str(e), "folder_id": folder_id}
)
# ==================== Filter Hooks ====================
async def inlet(
self, body: dict, __user__: Optional[dict] = None, __event_emitter__=None
) -> dict:
return body
async def outlet(
self,
body: dict,
__user__: Optional[dict] = None,
__event_emitter__=None,
__request__: Optional[Request] = None,
) -> dict:
user_ctx = self._get_user_context(__user__)
chat_ctx = self._get_chat_context(body)
messages = body.get("messages", [])
if not messages:
return body
# 触发逻辑:消息计数阈值
if len(messages) % self.valves.MESSAGE_TRIGGER_COUNT != 0:
return body
folder_id = self._get_folder_id(body)
if not folder_id:
await self._emit_debug_log(
__event_emitter__,
"跳过分析",
{"reason": "对话不属于任何文件夹", "chat_id": chat_ctx.get("chat_id")},
)
return body
# 用户信息
user_id = user_ctx.get("user_id")
if not user_id:
return body
# 异步任务
if self.valves.MODEL_ID == "":
self.valves.MODEL_ID = body.get("model", "")
asyncio.create_task(
self._process_rules_update(
folder_id, body, user_id, __request__, __event_emitter__
)
)
return body

View File

@@ -1,6 +1,6 @@
# Markdown Normalizer Filter
**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 1.2.2 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 1.2.4 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
A content normalizer filter for Open WebUI that fixes common Markdown formatting issues in LLM outputs. It ensures that code blocks, LaTeX formulas, Mermaid diagrams, and other Markdown elements are rendered correctly.
@@ -43,7 +43,7 @@ A content normalizer filter for Open WebUI that fixes common Markdown formatting
* `enable_heading_fix`: Fix missing space in headings.
* `enable_table_fix`: Fix missing closing pipe in tables.
* `enable_xml_tag_cleanup`: Cleanup leftover XML tags.
* `enable_emphasis_spacing_fix`: Fix extra spaces in emphasis (default: True).
* `enable_emphasis_spacing_fix`: Fix extra spaces in emphasis (default: False).
* `show_status`: Show status notification when fixes are applied.
* `show_debug_log`: Print debug logs to browser console.
@@ -53,6 +53,10 @@ A content normalizer filter for Open WebUI that fixes common Markdown formatting
## Changelog
### v1.2.4
* **Documentation Updates**: Synchronized version numbers across all documentation and code files.
### v1.2.3
* **List Marker Protection Enhancement**: Fixed a bug where list markers (`*`) followed by plain text and emphasis were having their spaces incorrectly stripped (e.g., `* U16 forward` became `*U16 forward`).

View File

@@ -1,6 +1,6 @@
# Markdown 格式化过滤器 (Markdown Normalizer)
**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 1.2.2 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 1.2.4 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
这是一个用于 Open WebUI 的内容格式化过滤器,旨在修复 LLM 输出中常见的 Markdown 格式问题。它能确保代码块、LaTeX 公式、Mermaid 图表和其他 Markdown 元素被正确渲染。
@@ -53,6 +53,10 @@
## 更新日志
### v1.2.4
* **文档更新**: 同步了所有文档和代码文件的版本号。
### v1.2.3
* **列表标记保护增强**: 修复了列表标记 (`*`) 后跟普通文本和强调标记时,空格被错误剥离的问题(例如 `* U16 前锋` 变成 `*U16 前锋`)。

View File

@@ -3,7 +3,7 @@ title: Markdown Normalizer
author: Fu-Jie
author_url: https://github.com/Fu-Jie/awesome-openwebui
funding_url: https://github.com/open-webui
version: 1.2.3
version: 1.2.4
openwebui_id: baaa8732-9348-40b7-8359-7e009660e23c
description: A content normalizer filter that fixes common Markdown formatting issues in LLM outputs, such as broken code blocks, LaTeX formulas, and list formatting.
"""
@@ -43,7 +43,7 @@ class NormalizerConfig:
)
enable_table_fix: bool = True # Fix missing closing pipe in tables
enable_xml_tag_cleanup: bool = True # Cleanup leftover XML tags
enable_emphasis_spacing_fix: bool = True # Fix spaces inside **emphasis**
enable_emphasis_spacing_fix: bool = False # Fix spaces inside **emphasis**
# Custom cleaner functions (for advanced extension)
custom_cleaners: List[Callable[[str], str]] = field(default_factory=list)
@@ -564,7 +564,7 @@ class Filter:
default=True, description="Cleanup leftover XML tags"
)
enable_emphasis_spacing_fix: bool = Field(
default=True,
default=False,
description="Fix spaces inside **emphasis** (e.g. ** text ** -> **text**)",
)
show_status: bool = Field(
@@ -695,6 +695,15 @@ class Filter:
if self._contains_html(content):
return body
# Skip if content contains tool output markers (native function calling)
# Pattern: ""&quot;...&quot;"" or tool_call_id or <details type="tool_calls"...>
if (
'""&quot;' in content
or "tool_call_id" in content
or '<details type="tool_calls"' in content
):
return body
# Configure normalizer based on valves
config = NormalizerConfig(
enable_escape_fix=self.valves.enable_escape_fix,

View File

@@ -3,7 +3,7 @@ title: Markdown 格式修复器 (Markdown Normalizer)
author: Fu-Jie
author_url: https://github.com/Fu-Jie/awesome-openwebui
funding_url: https://github.com/open-webui
version: 1.2.3
version: 1.2.4
description: 内容规范化过滤器,修复 LLM 输出中常见的 Markdown 格式问题如损坏的代码块、LaTeX 公式、Mermaid 图表和列表格式。
"""
@@ -24,6 +24,9 @@ class NormalizerConfig:
"""配置类,用于启用/禁用特定的规范化规则"""
enable_escape_fix: bool = True # 修复过度的转义字符
enable_escape_fix_in_code_blocks: bool = (
False # 在代码块内部应用转义修复 (默认:关闭,以确保安全)
)
enable_thought_tag_fix: bool = True # 规范化思维链标签
enable_details_tag_fix: bool = True # 规范化 <details> 标签(类似思维链标签)
enable_code_block_fix: bool = True # 修复代码块格式
@@ -35,7 +38,7 @@ class NormalizerConfig:
enable_heading_fix: bool = True # 修复标题中缺失的空格 (#Header -> # Header)
enable_table_fix: bool = True # 修复表格中缺失的闭合管道符
enable_xml_tag_cleanup: bool = True # 清理残留的 XML 标签
enable_emphasis_spacing_fix: bool = True # 修复 **强调内容** 中的多余空格
enable_emphasis_spacing_fix: bool = False # 修复 **强调内容** 中的多余空格
# 自定义清理函数 (用于高级扩展)
custom_cleaners: List[Callable[[str], str]] = field(default_factory=list)
@@ -239,12 +242,27 @@ class ContentNormalizer:
return content
def _fix_escape_characters(self, content: str) -> str:
"""Fix excessive escape characters"""
content = content.replace("\\r\\n", "\n")
content = content.replace("\\n", "\n")
content = content.replace("\\t", "\t")
content = content.replace("\\\\", "\\")
return content
"""修复过度的转义字符
如果 enable_escape_fix_in_code_blocks 为 False (默认),此方法将仅修复代码块外部的转义字符,
以避免破坏有效的代码示例 (例如,带有 \\n 的 JSON 字符串、正则表达式模式等)。
"""
if self.config.enable_escape_fix_in_code_blocks:
# 全局应用 (原始行为)
content = content.replace("\\r\\n", "\n")
content = content.replace("\\n", "\n")
content = content.replace("\\t", "\t")
content = content.replace("\\\\", "\\")
return content
else:
# 仅在代码块外部应用 (安全模式)
parts = content.split("```")
for i in range(0, len(parts), 2): # 偶数索引是 Markdown 文本 (非代码)
parts[i] = parts[i].replace("\\r\\n", "\n")
parts[i] = parts[i].replace("\\n", "\n")
parts[i] = parts[i].replace("\\t", "\t")
parts[i] = parts[i].replace("\\\\", "\\")
return "```".join(parts)
def _fix_thought_tags(self, content: str) -> str:
"""Normalize thought tags: unify naming and fix spacing"""
@@ -501,6 +519,10 @@ class Filter:
enable_escape_fix: bool = Field(
default=True, description="修复过度的转义字符 (\\n, \\t 等)"
)
enable_escape_fix_in_code_blocks: bool = Field(
default=False,
description="在代码块内部应用转义修复 (⚠️ 警告:可能会破坏有效的代码,如 JSON 字符串或正则模式。默认:关闭,以确保安全)",
)
enable_thought_tag_fix: bool = Field(
default=True, description="规范化思维链标签 (<think> -> <thought>)"
)
@@ -539,7 +561,7 @@ class Filter:
default=True, description="清理残留的 XML 标签"
)
enable_emphasis_spacing_fix: bool = Field(
default=True,
default=False,
description="修复强调语法中的多余空格 (例如 ** 文本 ** -> **文本**)",
)
show_status: bool = Field(default=True, description="应用修复时显示状态通知")
@@ -682,13 +704,23 @@ class Filter:
content = last.get("content", "") or ""
if last.get("role") == "assistant" and isinstance(content, str):
# Skip if content looks like HTML to avoid breaking it
# 如果内容看起来像 HTML则跳过以避免破坏它
if self._contains_html(content):
return body
# Configure normalizer based on valves
# 如果内容包含工具输出标记 (原生函数调用),则跳过
# 模式:""&quot;...&quot;"" 或 tool_call_id 或 <details type="tool_calls"...>
if (
'""&quot;' in content
or "tool_call_id" in content
or '<details type="tool_calls"' in content
):
return body
# 根据 Valves 配置 Normalizer
config = NormalizerConfig(
enable_escape_fix=self.valves.enable_escape_fix,
enable_escape_fix_in_code_blocks=self.valves.enable_escape_fix_in_code_blocks,
enable_thought_tag_fix=self.valves.enable_thought_tag_fix,
enable_details_tag_fix=self.valves.enable_details_tag_fix,
enable_code_block_fix=self.valves.enable_code_block_fix,

View File

@@ -0,0 +1,81 @@
# GitHub Copilot SDK Pipe for OpenWebUI
**Author:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **Version:** 0.1.1 | **Project:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **License:** MIT
This is an advanced Pipe function for [OpenWebUI](https://github.com/open-webui/open-webui) that allows you to use GitHub Copilot models (such as `gpt-5`, `gpt-5-mini`, `claude-sonnet-4.5`) directly within OpenWebUI. It is built upon the official [GitHub Copilot SDK for Python](https://github.com/github/copilot-sdk), providing a native integration experience.
## 🚀 What's New (v0.1.1)
* **♾️ Infinite Sessions**: Automatic context compaction for long-running conversations. No more context limit errors!
* **🧠 Thinking Process**: Real-time display of model reasoning/thinking process (for supported models).
* **📂 Workspace Control**: Restricted workspace directory for secure file operations.
* **🔍 Model Filtering**: Exclude specific models using keywords (e.g., `codex`, `haiku`).
* **💾 Session Persistence**: Improved session resume logic using OpenWebUI chat ID mapping.
## ✨ Core Features
* **🚀 Official SDK Integration**: Built on the official SDK for stability and reliability.
* **💬 Multi-turn Conversation**: Automatically concatenates history context so Copilot understands your previous messages.
* **🌊 Streaming Output**: Supports typewriter effect for fast responses.
* **🖼️ Multimodal Support**: Supports image uploads, automatically converting them to attachments for Copilot (requires model support).
* **🛠️ Zero-config Installation**: Automatically detects and downloads the GitHub Copilot CLI, ready to use out of the box.
* **🔑 Secure Authentication**: Supports Fine-grained Personal Access Tokens for minimized permissions.
* **🐛 Debug Mode**: Built-in detailed log output for easy connection troubleshooting.
* **⚠️ Single Node Only**: Due to local session storage, this plugin currently supports single-node OpenWebUI deployment or multi-node with sticky sessions enabled.
## 📦 Installation & Usage
### 1. Import Function
1. Open OpenWebUI.
2. Go to **Workspace** -> **Functions**.
3. Click **+** (Create Function).
4. Paste the content of `github_copilot_sdk.py` (or `github_copilot_sdk_cn.py` for Chinese) completely.
5. Save.
### 2. Configure Valves (Settings)
Find "GitHub Copilot" in the function list and click the **⚙️ (Valves)** icon to configure:
| Parameter | Description | Default |
| :--- | :--- | :--- |
| **GH_TOKEN** | **(Required)** Your GitHub Token. | - |
| **MODEL_ID** | The model name to use. | `gpt-5-mini` |
| **CLI_PATH** | Path to the Copilot CLI. Will download automatically if not found. | `/usr/local/bin/copilot` |
| **DEBUG** | Whether to enable debug logs (output to chat). | `True` |
| **SHOW_THINKING** | Show model reasoning/thinking process. | `True` |
| **EXCLUDE_KEYWORDS** | Exclude models containing these keywords (comma separated). | - |
| **WORKSPACE_DIR** | Restricted workspace directory for file operations. | - |
| **INFINITE_SESSION** | Enable Infinite Sessions (automatic context compaction). | `True` |
| **COMPACTION_THRESHOLD** | Background compaction threshold (0.0-1.0). | `0.8` |
| **BUFFER_THRESHOLD** | Buffer exhaustion threshold (0.0-1.0). | `0.95` |
| **TIMEOUT** | Timeout for each stream chunk (seconds). | `300` |
### 3. Get GH_TOKEN
For security, it is recommended to use a **Fine-grained Personal Access Token**:
1. Visit [GitHub Token Settings](https://github.com/settings/tokens?type=beta).
2. Click **Generate new token**.
3. **Repository access**: Select **Public repositories** (Required to access Copilot permissions).
4. **Permissions**:
* Click **Account permissions**.
* Find **Copilot Requests** (It defaults to **Read-only**, no selection needed).
5. Generate and copy the Token.
## 📋 Dependencies
This Pipe will automatically attempt to install the following dependencies:
* `github-copilot-sdk` (Python package)
* `github-copilot-cli` (Binary file, installed via official script)
## ⚠️ FAQ
* **Stuck on "Waiting..."**:
* Check if `GH_TOKEN` is correct and has `Copilot Requests` permission.
* **Images not recognized**:
* Ensure `MODEL_ID` is a model that supports multimodal input.
* **CLI Installation Failed**:
* Ensure the OpenWebUI container has internet access.
* You can manually download the CLI and specify `CLI_PATH` in Valves.

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# GitHub Copilot SDK 官方管道
**作者:** [Fu-Jie](https://github.com/Fu-Jie/awesome-openwebui) | **版本:** 0.1.1 | **项目:** [Awesome OpenWebUI](https://github.com/Fu-Jie/awesome-openwebui) | **许可证:** MIT
这是一个用于 [OpenWebUI](https://github.com/open-webui/open-webui) 的高级 Pipe 函数,允许你直接在 OpenWebUI 中使用 GitHub Copilot 模型(如 `gpt-5`, `gpt-5-mini`, `claude-sonnet-4.5`)。它基于官方 [GitHub Copilot SDK for Python](https://github.com/github/copilot-sdk) 构建,提供了原生级的集成体验。
## 🚀 最新特性 (v0.1.1)
* **♾️ 无限会话 (Infinite Sessions)**:支持长对话的自动上下文压缩,告别上下文超限错误!
* **🧠 思考过程展示**:实时显示模型的推理/思考过程(需模型支持)。
* **📂 工作目录控制**:支持设置受限工作目录,确保文件操作安全。
* **🔍 模型过滤**:支持通过关键词排除特定模型(如 `codex`, `haiku`)。
* **💾 会话持久化**: 改进的会话恢复逻辑,直接关联 OpenWebUI 聊天 ID连接更稳定。
## ✨ 核心特性
* **🚀 官方 SDK 集成**:基于官方 SDK稳定可靠。
* **💬 多轮对话支持**自动拼接历史上下文Copilot 能理解你的前文。
* **🌊 流式输出 (Streaming)**:支持打字机效果,响应迅速。
* **🖼️ 多模态支持**:支持上传图片,自动转换为附件发送给 Copilot需模型支持
* **🛠️ 零配置安装**:自动检测并下载 GitHub Copilot CLI开箱即用。
* **🔑 安全认证**:支持 Fine-grained Personal Access Tokens权限最小化。
* **🐛 调试模式**:内置详细的日志输出,方便排查连接问题。
* **⚠️ 仅支持单节点**:由于会话状态存储在本地,本插件目前仅支持 OpenWebUI 单节点部署,或开启了会话粘性 (Sticky Session) 的多节点集群。
## 📦 安装与使用
### 1. 导入函数
1. 打开 OpenWebUI。
2. 进入 **Workspace** -> **Functions**
3. 点击 **+** (创建函数)。
4.`github_copilot_sdk_cn.py` 的内容完整粘贴进去。
5. 保存。
### 2. 配置 Valves (设置)
在函数列表中找到 "GitHub Copilot",点击 **⚙️ (Valves)** 图标进行配置:
| 参数 | 说明 | 默认值 |
| :--- | :--- | :--- |
| **GH_TOKEN** | **(必填)** 你的 GitHub Token。 | - |
| **MODEL_ID** | 使用的模型名称。 | `gpt-5-mini` |
| **CLI_PATH** | Copilot CLI 的路径。如果未找到会自动下载。 | `/usr/local/bin/copilot` |
| **DEBUG** | 是否开启调试日志(输出到对话框)。 | `True` |
| **SHOW_THINKING** | 是否显示模型推理/思考过程。 | `True` |
| **EXCLUDE_KEYWORDS** | 排除包含这些关键词的模型 (逗号分隔)。 | - |
| **WORKSPACE_DIR** | 文件操作的受限工作目录。 | - |
| **INFINITE_SESSION** | 启用无限会话 (自动上下文压缩)。 | `True` |
| **COMPACTION_THRESHOLD** | 后台压缩阈值 (0.0-1.0)。 | `0.8` |
| **BUFFER_THRESHOLD** | 缓冲耗尽阈值 (0.0-1.0)。 | `0.95` |
| **TIMEOUT** | 流式数据块超时时间 (秒)。 | `300` |
### 3. 获取 GH_TOKEN
为了安全起见,推荐使用 **Fine-grained Personal Access Token**
1. 访问 [GitHub Token Settings](https://github.com/settings/tokens?type=beta)。
2. 点击 **Generate new token**
3. **Repository access**: 选择 **Public repositories** (必须选择此项才能看到 Copilot 权限)。
4. **Permissions**:
* 点击 **Account permissions**
* 找到 **Copilot Requests** (默认即为 **Read-only**,无需手动修改)。
5. 生成并复制 Token。
## 📋 依赖说明
该 Pipe 会自动尝试安装以下依赖(如果环境中缺失):
* `github-copilot-sdk` (Python 包)
* `github-copilot-cli` (二进制文件,通过官方脚本安装)
## ⚠️ 常见问题
* **一直显示 "Waiting..."**
* 检查 `GH_TOKEN` 是否正确且拥有 `Copilot Requests` 权限。
* **图片无法识别**
* 确保 `MODEL_ID` 是支持多模态的模型。
* **CLI 安装失败**
* 确保 OpenWebUI 容器有外网访问权限。
* 你可以手动下载 CLI 并挂载到容器中,然后在 Valves 中指定 `CLI_PATH`

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"""
title: GitHub Copilot Official SDK Pipe
author: Fu-Jie
author_url: https://github.com/Fu-Jie/awesome-openwebui
funding_url: https://github.com/open-webui
openwebui_id: ce96f7b4-12fc-4ac3-9a01-875713e69359
description: Integrate GitHub Copilot SDK. Supports dynamic models, multi-turn conversation, streaming, multimodal input, and infinite sessions (context compaction).
version: 0.1.1
requirements: github-copilot-sdk
"""
import os
import time
import json
import base64
import tempfile
import asyncio
import logging
import shutil
import subprocess
import sys
from typing import Optional, Union, AsyncGenerator, List, Any, Dict
from pydantic import BaseModel, Field
from datetime import datetime, timezone
import contextlib
# Setup logger
logger = logging.getLogger(__name__)
# Global client storage
_SHARED_CLIENT = None
_SHARED_TOKEN = ""
_CLIENT_LOCK = asyncio.Lock()
class Pipe:
class Valves(BaseModel):
GH_TOKEN: str = Field(
default="",
description="GitHub Fine-grained Token (Requires 'Copilot Requests' permission)",
)
MODEL_ID: str = Field(
default="claude-sonnet-4.5",
description="Default Copilot model name (used when dynamic fetching fails)",
)
CLI_PATH: str = Field(
default="/usr/local/bin/copilot",
description="Path to Copilot CLI",
)
DEBUG: bool = Field(
default=False,
description="Enable technical debug logs (connection info, etc.)",
)
SHOW_THINKING: bool = Field(
default=True,
description="Show model reasoning/thinking process",
)
EXCLUDE_KEYWORDS: str = Field(
default="",
description="Exclude models containing these keywords (comma separated, e.g.: codex, haiku)",
)
WORKSPACE_DIR: str = Field(
default="",
description="Restricted workspace directory for file operations. If empty, allows access to the current process directory.",
)
INFINITE_SESSION: bool = Field(
default=True,
description="Enable Infinite Sessions (automatic context compaction)",
)
COMPACTION_THRESHOLD: float = Field(
default=0.8,
description="Background compaction threshold (0.0-1.0)",
)
BUFFER_THRESHOLD: float = Field(
default=0.95,
description="Buffer exhaustion threshold (0.0-1.0)",
)
TIMEOUT: int = Field(
default=300,
description="Timeout for each stream chunk (seconds)",
)
def __init__(self):
self.type = "pipe"
self.id = "copilotsdk"
self.name = "copilotsdk"
self.valves = self.Valves()
self.temp_dir = tempfile.mkdtemp(prefix="copilot_images_")
self.thinking_started = False
self._model_cache = [] # Model list cache
def __del__(self):
try:
shutil.rmtree(self.temp_dir)
except:
pass
def _emit_debug_log(self, message: str):
"""Emit debug log to frontend if DEBUG valve is enabled."""
if self.valves.DEBUG:
print(f"[Copilot Pipe] {message}")
def _get_user_context(self):
"""Helper to get user context (placeholder for future use)."""
return {}
def _get_chat_context(
self, body: dict, __metadata__: Optional[dict] = None
) -> Dict[str, str]:
"""
Highly reliable chat context extraction logic.
Priority: __metadata__ > body['chat_id'] > body['metadata']['chat_id']
"""
chat_id = ""
source = "none"
# 1. Prioritize __metadata__ (most reliable source injected by OpenWebUI)
if __metadata__ and isinstance(__metadata__, dict):
chat_id = __metadata__.get("chat_id", "")
if chat_id:
source = "__metadata__"
# 2. Then try body root
if not chat_id and isinstance(body, dict):
chat_id = body.get("chat_id", "")
if chat_id:
source = "body_root"
# 3. Finally try body.metadata
if not chat_id and isinstance(body, dict):
body_metadata = body.get("metadata", {})
if isinstance(body_metadata, dict):
chat_id = body_metadata.get("chat_id", "")
if chat_id:
source = "body_metadata"
# Debug: Log ID source
if chat_id:
self._emit_debug_log(f"Extracted ChatID: {chat_id} (Source: {source})")
else:
# If still not found, log body keys for troubleshooting
keys = list(body.keys()) if isinstance(body, dict) else "not a dict"
self._emit_debug_log(
f"Warning: Failed to extract ChatID. Body keys: {keys}"
)
return {
"chat_id": str(chat_id).strip(),
}
async def pipes(self) -> List[dict]:
"""Dynamically fetch model list"""
# Return cache if available
if self._model_cache:
return self._model_cache
self._emit_debug_log("Fetching model list dynamically...")
try:
self._setup_env()
if not self.valves.GH_TOKEN:
return [{"id": f"{self.id}-error", "name": "Error: GH_TOKEN not set"}]
from copilot import CopilotClient
client_config = {}
if os.environ.get("COPILOT_CLI_PATH"):
client_config["cli_path"] = os.environ["COPILOT_CLI_PATH"]
client = CopilotClient(client_config)
try:
await client.start()
models = await client.list_models()
# Update cache
self._model_cache = []
exclude_list = [
k.strip().lower()
for k in self.valves.EXCLUDE_KEYWORDS.split(",")
if k.strip()
]
models_with_info = []
for m in models:
# Compatible with dict and object access
m_id = (
m.get("id") if isinstance(m, dict) else getattr(m, "id", str(m))
)
m_name = (
m.get("name")
if isinstance(m, dict)
else getattr(m, "name", m_id)
)
m_policy = (
m.get("policy")
if isinstance(m, dict)
else getattr(m, "policy", {})
)
m_billing = (
m.get("billing")
if isinstance(m, dict)
else getattr(m, "billing", {})
)
# Check policy state
state = (
m_policy.get("state")
if isinstance(m_policy, dict)
else getattr(m_policy, "state", "enabled")
)
if state == "disabled":
continue
# Filtering logic
if any(kw in m_id.lower() for kw in exclude_list):
continue
# Get multiplier
multiplier = (
m_billing.get("multiplier", 1)
if isinstance(m_billing, dict)
else getattr(m_billing, "multiplier", 1)
)
# Format display name
if multiplier == 0:
display_name = f"-🔥 {m_id} (unlimited)"
else:
display_name = f"-{m_id} ({multiplier}x)"
models_with_info.append(
{
"id": f"{self.id}-{m_id}",
"name": display_name,
"multiplier": multiplier,
"raw_id": m_id,
}
)
# Sort: multiplier ascending, then raw_id ascending
models_with_info.sort(key=lambda x: (x["multiplier"], x["raw_id"]))
self._model_cache = [
{"id": m["id"], "name": m["name"]} for m in models_with_info
]
self._emit_debug_log(
f"Successfully fetched {len(self._model_cache)} models (filtered)"
)
return self._model_cache
except Exception as e:
self._emit_debug_log(f"Failed to fetch model list: {e}")
# Return default model on failure
return [
{
"id": f"{self.id}-{self.valves.MODEL_ID}",
"name": f"GitHub Copilot ({self.valves.MODEL_ID})",
}
]
finally:
await client.stop()
except Exception as e:
self._emit_debug_log(f"Pipes Error: {e}")
return [
{
"id": f"{self.id}-{self.valves.MODEL_ID}",
"name": f"GitHub Copilot ({self.valves.MODEL_ID})",
}
]
async def _get_client(self):
"""Helper to get or create a CopilotClient instance."""
from copilot import CopilotClient
client_config = {}
if os.environ.get("COPILOT_CLI_PATH"):
client_config["cli_path"] = os.environ["COPILOT_CLI_PATH"]
client = CopilotClient(client_config)
await client.start()
return client
def _setup_env(self):
cli_path = self.valves.CLI_PATH
found = False
if os.path.exists(cli_path):
found = True
if not found:
sys_path = shutil.which("copilot")
if sys_path:
cli_path = sys_path
found = True
if not found:
try:
subprocess.run(
"curl -fsSL https://gh.io/copilot-install | bash",
shell=True,
check=True,
)
if os.path.exists(self.valves.CLI_PATH):
cli_path = self.valves.CLI_PATH
found = True
except:
pass
if found:
os.environ["COPILOT_CLI_PATH"] = cli_path
cli_dir = os.path.dirname(cli_path)
if cli_dir not in os.environ["PATH"]:
os.environ["PATH"] = f"{cli_dir}:{os.environ['PATH']}"
if self.valves.GH_TOKEN:
os.environ["GH_TOKEN"] = self.valves.GH_TOKEN
os.environ["GITHUB_TOKEN"] = self.valves.GH_TOKEN
def _process_images(self, messages):
attachments = []
text_content = ""
if not messages:
return "", []
last_msg = messages[-1]
content = last_msg.get("content", "")
if isinstance(content, list):
for item in content:
if item.get("type") == "text":
text_content += item.get("text", "")
elif item.get("type") == "image_url":
image_url = item.get("image_url", {}).get("url", "")
if image_url.startswith("data:image"):
try:
header, encoded = image_url.split(",", 1)
ext = header.split(";")[0].split("/")[-1]
file_name = f"image_{len(attachments)}.{ext}"
file_path = os.path.join(self.temp_dir, file_name)
with open(file_path, "wb") as f:
f.write(base64.b64decode(encoded))
attachments.append(
{
"type": "file",
"path": file_path,
"display_name": file_name,
}
)
self._emit_debug_log(f"Image processed: {file_path}")
except Exception as e:
self._emit_debug_log(f"Image error: {e}")
else:
text_content = str(content)
return text_content, attachments
async def pipe(
self, body: dict, __metadata__: Optional[dict] = None
) -> Union[str, AsyncGenerator]:
self._setup_env()
if not self.valves.GH_TOKEN:
return "Error: Please configure GH_TOKEN in Valves."
# Parse user selected model
request_model = body.get("model", "")
real_model_id = self.valves.MODEL_ID # Default value
if request_model.startswith(f"{self.id}-"):
real_model_id = request_model[len(f"{self.id}-") :]
self._emit_debug_log(f"Using selected model: {real_model_id}")
messages = body.get("messages", [])
if not messages:
return "No messages."
# Get Chat ID using improved helper
chat_ctx = self._get_chat_context(body, __metadata__)
chat_id = chat_ctx.get("chat_id")
is_streaming = body.get("stream", False)
self._emit_debug_log(f"Request Streaming: {is_streaming}")
last_text, attachments = self._process_images(messages)
# Determine prompt strategy
# If we have a chat_id, we try to resume session.
# If resumed, we assume the session has history, so we only send the last message.
# If new session, we send full history (or at least the last few turns if we want to be safe, but let's send full for now).
# However, to be robust against history edits in OpenWebUI, we might want to always send full history?
# Copilot SDK `create_session` doesn't take history. `session.send` appends.
# If we resume, we append.
# If user edited history, the session state is stale.
# For now, we implement "Resume if possible, else Create".
prompt = ""
is_new_session = True
try:
client = await self._get_client()
session = None
if chat_id:
try:
# Try to resume session using chat_id as session_id
session = await client.resume_session(chat_id)
self._emit_debug_log(f"Resumed session using ChatID: {chat_id}")
is_new_session = False
except Exception:
# Resume failed, session might not exist on disk
self._emit_debug_log(
f"Session {chat_id} not found or expired, creating new."
)
session = None
if session is None:
# Create new session
from copilot.types import SessionConfig, InfiniteSessionConfig
# Infinite Session Config
infinite_session_config = None
if self.valves.INFINITE_SESSION:
infinite_session_config = InfiniteSessionConfig(
enabled=True,
background_compaction_threshold=self.valves.COMPACTION_THRESHOLD,
buffer_exhaustion_threshold=self.valves.BUFFER_THRESHOLD,
)
session_config = SessionConfig(
session_id=(
chat_id if chat_id else None
), # Use chat_id as session_id
model=real_model_id,
streaming=body.get("stream", False),
infinite_sessions=infinite_session_config,
)
session = await client.create_session(config=session_config)
new_sid = getattr(session, "session_id", getattr(session, "id", None))
self._emit_debug_log(f"Created new session: {new_sid}")
# Construct prompt
if is_new_session:
# For new session, send full conversation history
full_conversation = []
for msg in messages[:-1]:
role = msg.get("role", "user").upper()
content = msg.get("content", "")
if isinstance(content, list):
content = " ".join(
[
c.get("text", "")
for c in content
if c.get("type") == "text"
]
)
full_conversation.append(f"{role}: {content}")
full_conversation.append(f"User: {last_text}")
prompt = "\n\n".join(full_conversation)
else:
# For resumed session, only send the last message
prompt = last_text
send_payload = {"prompt": prompt, "mode": "immediate"}
if attachments:
send_payload["attachments"] = attachments
if body.get("stream", False):
# Determine session status message for UI
init_msg = ""
if self.valves.DEBUG:
if is_new_session:
new_sid = getattr(
session, "session_id", getattr(session, "id", "unknown")
)
init_msg = f"> [Debug] Created new session: {new_sid}\n"
else:
init_msg = (
f"> [Debug] Resumed session using ChatID: {chat_id}\n"
)
return self.stream_response(client, session, send_payload, init_msg)
else:
try:
response = await session.send_and_wait(send_payload)
return response.data.content if response else "Empty response."
finally:
# Destroy session object to free memory, but KEEP data on disk
await session.destroy()
except Exception as e:
self._emit_debug_log(f"Request Error: {e}")
return f"Error: {str(e)}"
async def stream_response(
self, client, session, send_payload, init_message: str = ""
) -> AsyncGenerator:
queue = asyncio.Queue()
done = asyncio.Event()
self.thinking_started = False
has_content = False # Track if any content has been yielded
def get_event_data(event, attr, default=""):
if hasattr(event, "data"):
data = event.data
if data is None:
return default
if isinstance(data, (str, int, float, bool)):
return str(data) if attr == "value" else default
if isinstance(data, dict):
val = data.get(attr)
if val is None:
alt_attr = attr.replace("_", "") if "_" in attr else attr
val = data.get(alt_attr)
if val is None and "_" not in attr:
# Try snake_case if camelCase failed
import re
snake_attr = re.sub(r"(?<!^)(?=[A-Z])", "_", attr).lower()
val = data.get(snake_attr)
else:
val = getattr(data, attr, None)
if val is None:
alt_attr = attr.replace("_", "") if "_" in attr else attr
val = getattr(data, alt_attr, None)
if val is None and "_" not in attr:
import re
snake_attr = re.sub(r"(?<!^)(?=[A-Z])", "_", attr).lower()
val = getattr(data, snake_attr, None)
return val if val is not None else default
return default
def handler(event):
event_type = (
getattr(event.type, "value", None)
if hasattr(event, "type")
else str(event.type)
)
# Log full event data for tool events to help debugging
if "tool" in event_type:
try:
data_str = str(event.data) if hasattr(event, "data") else "no data"
self._emit_debug_log(f"Tool Event [{event_type}]: {data_str}")
except:
pass
self._emit_debug_log(f"Event: {event_type}")
# Handle message content (delta or full)
if event_type in [
"assistant.message_delta",
"assistant.message.delta",
"assistant.message",
]:
# Log full message event for troubleshooting why there's no delta
if event_type == "assistant.message":
self._emit_debug_log(
f"Received full message event (non-Delta): {get_event_data(event, 'content')[:50]}..."
)
delta = (
get_event_data(event, "delta_content")
or get_event_data(event, "deltaContent")
or get_event_data(event, "content")
or get_event_data(event, "text")
)
if delta:
if self.thinking_started:
queue.put_nowait("\n</think>\n")
self.thinking_started = False
queue.put_nowait(delta)
elif event_type in [
"assistant.reasoning_delta",
"assistant.reasoning.delta",
"assistant.reasoning",
]:
delta = (
get_event_data(event, "delta_content")
or get_event_data(event, "deltaContent")
or get_event_data(event, "content")
or get_event_data(event, "text")
)
if delta:
if not self.thinking_started and self.valves.SHOW_THINKING:
queue.put_nowait("<think>\n")
self.thinking_started = True
if self.thinking_started:
queue.put_nowait(delta)
elif event_type == "tool.execution_start":
# Try multiple possible fields for tool name/description
tool_name = (
get_event_data(event, "toolName")
or get_event_data(event, "name")
or get_event_data(event, "description")
or get_event_data(event, "tool_name")
or "Unknown Tool"
)
if not self.thinking_started and self.valves.SHOW_THINKING:
queue.put_nowait("<think>\n")
self.thinking_started = True
if self.thinking_started:
queue.put_nowait(f"\nRunning Tool: {tool_name}...\n")
self._emit_debug_log(f"Tool Start: {tool_name}")
elif event_type == "tool.execution_complete":
if self.thinking_started:
queue.put_nowait("Tool Completed.\n")
self._emit_debug_log("Tool Complete")
elif event_type == "session.compaction_start":
self._emit_debug_log("Session Compaction Started")
elif event_type == "session.compaction_complete":
self._emit_debug_log("Session Compaction Completed")
elif event_type == "session.idle":
done.set()
elif event_type == "session.error":
msg = get_event_data(event, "message", "Unknown Error")
queue.put_nowait(f"\n[Error: {msg}]")
done.set()
unsubscribe = session.on(handler)
await session.send(send_payload)
if self.valves.DEBUG:
yield "<think>\n"
if init_message:
yield init_message
yield "> [Debug] Connection established, waiting for response...\n"
self.thinking_started = True
try:
while not done.is_set():
try:
chunk = await asyncio.wait_for(
queue.get(), timeout=float(self.valves.TIMEOUT)
)
if chunk:
has_content = True
yield chunk
except asyncio.TimeoutError:
if done.is_set():
break
if self.thinking_started:
yield f"> [Debug] Waiting for response ({self.valves.TIMEOUT}s exceeded)...\n"
continue
while not queue.empty():
chunk = queue.get_nowait()
if chunk:
has_content = True
yield chunk
if self.thinking_started:
yield "\n</think>\n"
has_content = True
# Core fix: If no content was yielded, return a fallback message to prevent OpenWebUI error
if not has_content:
yield "⚠️ Copilot returned no content. Please check if the Model ID is correct or enable DEBUG mode in Valves for details."
except Exception as e:
yield f"\n[Stream Error: {str(e)}]"
finally:
unsubscribe()
# Only destroy session if it's not cached
# We can't easily check chat_id here without passing it,
# but stream_response is called within the scope where we decide persistence.
# Wait, stream_response takes session as arg.
# We need to know if we should destroy it.
# Let's assume if it's in _SESSIONS, we don't destroy it.
# But checking _SESSIONS here is race-prone or complex.
# Simplified: The caller (pipe) handles destruction logic?
# No, stream_response is a generator, pipe returns it.
# So pipe function exits before stream finishes.
# We need to handle destruction here.
pass
# TODO: Proper session cleanup for streaming
# For now, we rely on the fact that if we mapped it, we keep it.
# If we didn't map it (no chat_id), we should destroy it.
# But we don't have chat_id here.
# Let's modify stream_response signature or just leave it open for GC?
# CopilotSession doesn't auto-close.
# Let's add a flag to stream_response.
pass

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"""
title: GitHub Copilot Official SDK Pipe
author: Fu-Jie
author_url: https://github.com/Fu-Jie/awesome-openwebui
funding_url: https://github.com/open-webui
description: 集成 GitHub Copilot SDK。支持动态模型、多轮对话、流式输出、多模态输入及无限会话上下文自动压缩
version: 0.1.1
requirements: github-copilot-sdk
"""
import os
import time
import json
import base64
import tempfile
import asyncio
import logging
import shutil
import subprocess
import sys
from typing import Optional, Union, AsyncGenerator, List, Any, Dict
from pydantic import BaseModel, Field
from datetime import datetime, timezone
import contextlib
# Setup logger
logger = logging.getLogger(__name__)
# Open WebUI internal database (re-use shared connection)
try:
from open_webui.internal import db as owui_db
except ModuleNotFoundError:
owui_db = None
def _discover_owui_engine(db_module: Any) -> Optional[Engine]:
"""Discover the Open WebUI SQLAlchemy engine via provided db module helpers."""
if db_module is None:
return None
db_context = getattr(db_module, "get_db_context", None) or getattr(
db_module, "get_db", None
)
if callable(db_context):
try:
with db_context() as session:
try:
return session.get_bind()
except AttributeError:
return getattr(session, "bind", None) or getattr(
session, "engine", None
)
except Exception as exc:
logger.error(f"[DB Discover] get_db_context failed: {exc}")
for attr in ("engine", "ENGINE", "bind", "BIND"):
candidate = getattr(db_module, attr, None)
if candidate is not None:
return candidate
return None
def _discover_owui_schema(db_module: Any) -> Optional[str]:
"""Discover the Open WebUI database schema name if configured."""
if db_module is None:
return None
try:
base = getattr(db_module, "Base", None)
metadata = getattr(base, "metadata", None) if base is not None else None
candidate = getattr(metadata, "schema", None) if metadata is not None else None
if isinstance(candidate, str) and candidate.strip():
return candidate.strip()
except Exception as exc:
logger.error(f"[DB Discover] Base metadata schema lookup failed: {exc}")
try:
metadata_obj = getattr(db_module, "metadata_obj", None)
candidate = (
getattr(metadata_obj, "schema", None) if metadata_obj is not None else None
)
if isinstance(candidate, str) and candidate.strip():
return candidate.strip()
except Exception as exc:
logger.error(f"[DB Discover] metadata_obj schema lookup failed: {exc}")
try:
from open_webui import env as owui_env
candidate = getattr(owui_env, "DATABASE_SCHEMA", None)
if isinstance(candidate, str) and candidate.strip():
return candidate.strip()
except Exception as exc:
logger.error(f"[DB Discover] env schema lookup failed: {exc}")
return None
owui_engine = _discover_owui_engine(owui_db)
owui_schema = _discover_owui_schema(owui_db)
owui_Base = getattr(owui_db, "Base", None) if owui_db is not None else None
if owui_Base is None:
owui_Base = declarative_base()
class CopilotSessionMap(owui_Base):
"""Copilot Session Mapping Table"""
__tablename__ = "copilot_session_map"
__table_args__ = (
{"extend_existing": True, "schema": owui_schema}
if owui_schema
else {"extend_existing": True}
)
id = Column(Integer, primary_key=True, autoincrement=True)
chat_id = Column(String(255), unique=True, nullable=False, index=True)
copilot_session_id = Column(String(255), nullable=False)
updated_at = Column(
DateTime,
default=lambda: datetime.now(timezone.utc),
onupdate=lambda: datetime.now(timezone.utc),
)
# 全局客户端存储
_SHARED_CLIENT = None
_SHARED_TOKEN = ""
_CLIENT_LOCK = asyncio.Lock()
class Pipe:
class Valves(BaseModel):
GH_TOKEN: str = Field(
default="", description="GitHub 细粒度令牌 (需开启 'Copilot Requests' 权限)"
)
MODEL_ID: str = Field(
default="claude-sonnet-4.5",
description="默认使用的 Copilot 模型名称 (当无法动态获取时使用)",
)
CLI_PATH: str = Field(
default="/usr/local/bin/copilot",
description="Copilot CLI 路径",
)
DEBUG: bool = Field(
default=False,
description="开启技术调试日志 (连接信息等)",
)
SHOW_THINKING: bool = Field(
default=True,
description="显示模型推理/思考过程",
)
EXCLUDE_KEYWORDS: str = Field(
default="",
description="排除包含这些关键词的模型 (逗号分隔,例如: codex, haiku)",
)
WORKSPACE_DIR: str = Field(
default="",
description="文件操作的受限工作目录。如果为空,允许访问当前进程目录。",
)
INFINITE_SESSION: bool = Field(
default=True,
description="启用无限会话 (自动上下文压缩)",
)
COMPACTION_THRESHOLD: float = Field(
default=0.8,
description="后台压缩阈值 (0.0-1.0)",
)
BUFFER_THRESHOLD: float = Field(
default=0.95,
description="背景压缩缓冲区阈值 (0.0-1.0)",
)
TIMEOUT: int = Field(
default=300,
description="流式数据块超时时间 (秒)",
)
def __init__(self):
self.type = "pipe"
self.name = "copilotsdk"
self.valves = self.Valves()
self.temp_dir = tempfile.mkdtemp(prefix="copilot_images_")
self.thinking_started = False
self._model_cache = [] # 模型列表缓存
def __del__(self):
try:
shutil.rmtree(self.temp_dir)
except:
pass
def _emit_debug_log(self, message: str):
"""Emit debug log to frontend if DEBUG valve is enabled."""
if self.valves.DEBUG:
print(f"[Copilot Pipe] {message}")
def _get_user_context(self):
"""Helper to get user context (placeholder for future use)."""
return {}
def _get_chat_context(
self, body: dict, __metadata__: Optional[dict] = None
) -> Dict[str, str]:
"""
高度可靠的聊天上下文提取逻辑。
优先级__metadata__ > body['chat_id'] > body['metadata']['chat_id']
"""
chat_id = ""
source = "none"
# 1. 优先从 __metadata__ 获取 (OpenWebUI 注入的最可靠来源)
if __metadata__ and isinstance(__metadata__, dict):
chat_id = __metadata__.get("chat_id", "")
if chat_id:
source = "__metadata__"
# 2. 其次从 body 顶层获取
if not chat_id and isinstance(body, dict):
chat_id = body.get("chat_id", "")
if chat_id:
source = "body_root"
# 3. 最后从 body.metadata 获取
if not chat_id and isinstance(body, dict):
body_metadata = body.get("metadata", {})
if isinstance(body_metadata, dict):
chat_id = body_metadata.get("chat_id", "")
if chat_id:
source = "body_metadata"
# 调试:记录 ID 来源
if chat_id:
self._emit_debug_log(f"提取到 ChatID: {chat_id} (来源: {source})")
else:
# 如果还是没找到,记录一下 body 的键,方便排查
keys = list(body.keys()) if isinstance(body, dict) else "not a dict"
self._emit_debug_log(f"警告: 未能提取到 ChatID。Body 键: {keys}")
return {
"chat_id": str(chat_id).strip(),
}
async def pipes(self) -> List[dict]:
"""动态获取模型列表"""
# 如果有缓存,直接返回
if self._model_cache:
return self._model_cache
self._emit_debug_log("正在动态获取模型列表...")
try:
self._setup_env()
if not self.valves.GH_TOKEN:
return [{"id": f"{self.id}-error", "name": "Error: GH_TOKEN not set"}]
from copilot import CopilotClient
client_config = {}
if os.environ.get("COPILOT_CLI_PATH"):
client_config["cli_path"] = os.environ["COPILOT_CLI_PATH"]
client = CopilotClient(client_config)
try:
await client.start()
models = await client.list_models()
# 更新缓存
self._model_cache = []
exclude_list = [
k.strip().lower()
for k in self.valves.EXCLUDE_KEYWORDS.split(",")
if k.strip()
]
models_with_info = []
for m in models:
# 兼容字典和对象访问方式
m_id = (
m.get("id") if isinstance(m, dict) else getattr(m, "id", str(m))
)
m_name = (
m.get("name")
if isinstance(m, dict)
else getattr(m, "name", m_id)
)
m_policy = (
m.get("policy")
if isinstance(m, dict)
else getattr(m, "policy", {})
)
m_billing = (
m.get("billing")
if isinstance(m, dict)
else getattr(m, "billing", {})
)
# 检查策略状态
state = (
m_policy.get("state")
if isinstance(m_policy, dict)
else getattr(m_policy, "state", "enabled")
)
if state == "disabled":
continue
# 过滤逻辑
if any(kw in m_id.lower() for kw in exclude_list):
continue
# 获取倍率
multiplier = (
m_billing.get("multiplier", 1)
if isinstance(m_billing, dict)
else getattr(m_billing, "multiplier", 1)
)
# 格式化显示名称
if multiplier == 0:
display_name = f"-🔥 {m_id} (unlimited)"
else:
display_name = f"-{m_id} ({multiplier}x)"
models_with_info.append(
{
"id": f"{self.id}-{m_id}",
"name": display_name,
"multiplier": multiplier,
"raw_id": m_id,
}
)
# 排序倍率升序然后是原始ID升序
models_with_info.sort(key=lambda x: (x["multiplier"], x["raw_id"]))
self._model_cache = [
{"id": m["id"], "name": m["name"]} for m in models_with_info
]
self._emit_debug_log(
f"成功获取 {len(self._model_cache)} 个模型 (已过滤)"
)
return self._model_cache
except Exception as e:
self._emit_debug_log(f"获取模型列表失败: {e}")
# 失败时返回默认模型
return [
{
"id": f"{self.id}-{self.valves.MODEL_ID}",
"name": f"GitHub Copilot ({self.valves.MODEL_ID})",
}
]
finally:
await client.stop()
except Exception as e:
self._emit_debug_log(f"Pipes Error: {e}")
return [
{
"id": f"{self.id}-{self.valves.MODEL_ID}",
"name": f"GitHub Copilot ({self.valves.MODEL_ID})",
}
]
async def _get_client(self):
"""Helper to get or create a CopilotClient instance."""
from copilot import CopilotClient
client_config = {}
if os.environ.get("COPILOT_CLI_PATH"):
client_config["cli_path"] = os.environ["COPILOT_CLI_PATH"]
client = CopilotClient(client_config)
await client.start()
return client
def _setup_env(self):
cli_path = self.valves.CLI_PATH
found = False
if os.path.exists(cli_path):
found = True
if not found:
sys_path = shutil.which("copilot")
if sys_path:
cli_path = sys_path
found = True
if not found:
try:
subprocess.run(
"curl -fsSL https://gh.io/copilot-install | bash",
shell=True,
check=True,
)
if os.path.exists(self.valves.CLI_PATH):
cli_path = self.valves.CLI_PATH
found = True
except:
pass
if found:
os.environ["COPILOT_CLI_PATH"] = cli_path
cli_dir = os.path.dirname(cli_path)
if cli_dir not in os.environ["PATH"]:
os.environ["PATH"] = f"{cli_dir}:{os.environ['PATH']}"
if self.valves.GH_TOKEN:
os.environ["GH_TOKEN"] = self.valves.GH_TOKEN
os.environ["GITHUB_TOKEN"] = self.valves.GH_TOKEN
def _process_images(self, messages):
attachments = []
text_content = ""
if not messages:
return "", []
last_msg = messages[-1]
content = last_msg.get("content", "")
if isinstance(content, list):
for item in content:
if item.get("type") == "text":
text_content += item.get("text", "")
elif item.get("type") == "image_url":
image_url = item.get("image_url", {}).get("url", "")
if image_url.startswith("data:image"):
try:
header, encoded = image_url.split(",", 1)
ext = header.split(";")[0].split("/")[-1]
file_name = f"image_{len(attachments)}.{ext}"
file_path = os.path.join(self.temp_dir, file_name)
with open(file_path, "wb") as f:
f.write(base64.b64decode(encoded))
attachments.append(
{
"type": "file",
"path": file_path,
"display_name": file_name,
}
)
self._emit_debug_log(f"Image processed: {file_path}")
except Exception as e:
self._emit_debug_log(f"Image error: {e}")
else:
text_content = str(content)
return text_content, attachments
async def pipe(
self, body: dict, __metadata__: Optional[dict] = None
) -> Union[str, AsyncGenerator]:
self._setup_env()
if not self.valves.GH_TOKEN:
return "Error: 请在 Valves 中配置 GH_TOKEN。"
# 解析用户选择的模型
request_model = body.get("model", "")
real_model_id = self.valves.MODEL_ID # 默认值
if request_model.startswith(f"{self.id}-"):
real_model_id = request_model[len(f"{self.id}-") :]
self._emit_debug_log(f"使用选择的模型: {real_model_id}")
messages = body.get("messages", [])
if not messages:
return "No messages."
# 使用改进的助手获取 Chat ID
chat_ctx = self._get_chat_context(body, __metadata__)
chat_id = chat_ctx.get("chat_id")
is_streaming = body.get("stream", False)
self._emit_debug_log(f"请求流式传输: {is_streaming}")
last_text, attachments = self._process_images(messages)
# 确定 Prompt 策略
# 如果有 chat_id尝试恢复会话。
# 如果恢复成功,假设会话已有历史,只发送最后一条消息。
# 如果是新会话,发送完整历史。
prompt = ""
is_new_session = True
try:
client = await self._get_client()
session = None
if chat_id:
try:
# 尝试直接使用 chat_id 作为 session_id 恢复会话
session = await client.resume_session(chat_id)
self._emit_debug_log(f"已通过 ChatID 恢复会话: {chat_id}")
is_new_session = False
except Exception:
# 恢复失败,磁盘上可能不存在该会话
self._emit_debug_log(
f"会话 {chat_id} 不存在或已过期,将创建新会话。"
)
session = None
if session is None:
# 创建新会话
from copilot.types import SessionConfig, InfiniteSessionConfig
# 无限会话配置
infinite_session_config = None
if self.valves.INFINITE_SESSION:
infinite_session_config = InfiniteSessionConfig(
enabled=True,
background_compaction_threshold=self.valves.COMPACTION_THRESHOLD,
buffer_exhaustion_threshold=self.valves.BUFFER_THRESHOLD,
)
session_config = SessionConfig(
session_id=(
chat_id if chat_id else None
), # 使用 chat_id 作为 session_id
model=real_model_id,
streaming=body.get("stream", False),
infinite_sessions=infinite_session_config,
)
session = await client.create_session(config=session_config)
# 获取新会话 ID
new_sid = getattr(session, "session_id", getattr(session, "id", None))
self._emit_debug_log(f"创建了新会话: {new_sid}")
# 构建 Prompt
if is_new_session:
# 新会话,发送完整历史
full_conversation = []
for msg in messages[:-1]:
role = msg.get("role", "user").upper()
content = msg.get("content", "")
if isinstance(content, list):
content = " ".join(
[
c.get("text", "")
for c in content
if c.get("type") == "text"
]
)
full_conversation.append(f"{role}: {content}")
full_conversation.append(f"User: {last_text}")
prompt = "\n\n".join(full_conversation)
else:
# 恢复的会话,只发送最后一条消息
prompt = last_text
send_payload = {"prompt": prompt, "mode": "immediate"}
if attachments:
send_payload["attachments"] = attachments
if body.get("stream", False):
# 确定 UI 显示的会话状态消息
init_msg = ""
if self.valves.DEBUG:
if is_new_session:
new_sid = getattr(
session, "session_id", getattr(session, "id", "unknown")
)
init_msg = f"> [Debug] 创建了新会话: {new_sid}\n"
else:
init_msg = f"> [Debug] 已通过 ChatID 恢复会话: {chat_id}\n"
return self.stream_response(client, session, send_payload, init_msg)
else:
try:
response = await session.send_and_wait(send_payload)
return response.data.content if response else "Empty response."
finally:
# 销毁会话对象以释放内存,但保留磁盘数据
await session.destroy()
except Exception as e:
self._emit_debug_log(f"请求错误: {e}")
return f"Error: {str(e)}"
async def stream_response(
self, client, session, send_payload, init_message: str = ""
) -> AsyncGenerator:
queue = asyncio.Queue()
done = asyncio.Event()
self.thinking_started = False
has_content = False # 追踪是否已经输出了内容
def get_event_data(event, attr, default=""):
if hasattr(event, "data"):
data = event.data
if data is None:
return default
if isinstance(data, (str, int, float, bool)):
return str(data) if attr == "value" else default
if isinstance(data, dict):
val = data.get(attr)
if val is None:
alt_attr = attr.replace("_", "") if "_" in attr else attr
val = data.get(alt_attr)
if val is None and "_" not in attr:
# 尝试将 camelCase 转换为 snake_case
import re
snake_attr = re.sub(r"(?<!^)(?=[A-Z])", "_", attr).lower()
val = data.get(snake_attr)
else:
val = getattr(data, attr, None)
if val is None:
alt_attr = attr.replace("_", "") if "_" in attr else attr
val = getattr(data, alt_attr, None)
if val is None and "_" not in attr:
import re
snake_attr = re.sub(r"(?<!^)(?=[A-Z])", "_", attr).lower()
val = getattr(data, snake_attr, None)
return val if val is not None else default
return default
def handler(event):
event_type = (
getattr(event.type, "value", None)
if hasattr(event, "type")
else str(event.type)
)
# 记录工具事件的完整数据以辅助调试
if "tool" in event_type:
try:
data_str = str(event.data) if hasattr(event, "data") else "no data"
self._emit_debug_log(f"Tool Event [{event_type}]: {data_str}")
except:
pass
self._emit_debug_log(f"Event: {event_type}")
# 处理消息内容 (增量或全量)
if event_type in [
"assistant.message_delta",
"assistant.message.delta",
"assistant.message",
]:
# 记录全量消息事件的特殊日志,帮助排查为什么没有 delta
if event_type == "assistant.message":
self._emit_debug_log(
f"收到全量消息事件 (非 Delta): {get_event_data(event, 'content')[:50]}..."
)
delta = (
get_event_data(event, "delta_content")
or get_event_data(event, "deltaContent")
or get_event_data(event, "content")
or get_event_data(event, "text")
)
if delta:
if self.thinking_started:
queue.put_nowait("\n</think>\n")
self.thinking_started = False
queue.put_nowait(delta)
elif event_type in [
"assistant.reasoning_delta",
"assistant.reasoning.delta",
"assistant.reasoning",
]:
delta = (
get_event_data(event, "delta_content")
or get_event_data(event, "deltaContent")
or get_event_data(event, "content")
or get_event_data(event, "text")
)
if delta:
if not self.thinking_started and self.valves.SHOW_THINKING:
queue.put_nowait("<think>\n")
self.thinking_started = True
if self.thinking_started:
queue.put_nowait(delta)
elif event_type == "tool.execution_start":
# 尝试多个可能的字段来获取工具名称或描述
tool_name = (
get_event_data(event, "toolName")
or get_event_data(event, "name")
or get_event_data(event, "description")
or get_event_data(event, "tool_name")
or "Unknown Tool"
)
if not self.thinking_started and self.valves.SHOW_THINKING:
queue.put_nowait("<think>\n")
self.thinking_started = True
if self.thinking_started:
queue.put_nowait(f"\n正在运行工具: {tool_name}...\n")
self._emit_debug_log(f"Tool Start: {tool_name}")
elif event_type == "tool.execution_complete":
if self.thinking_started:
queue.put_nowait("工具运行完成。\n")
self._emit_debug_log("Tool Complete")
elif event_type == "session.compaction_start":
self._emit_debug_log("会话压缩开始")
elif event_type == "session.compaction_complete":
self._emit_debug_log("会话压缩完成")
elif event_type == "session.idle":
done.set()
elif event_type == "session.error":
msg = get_event_data(event, "message", "Unknown Error")
queue.put_nowait(f"\n[Error: {msg}]")
done.set()
unsubscribe = session.on(handler)
await session.send(send_payload)
if self.valves.DEBUG:
yield "<think>\n"
if init_message:
yield init_message
yield "> [Debug] 连接已建立,等待响应...\n"
self.thinking_started = True
try:
while not done.is_set():
try:
chunk = await asyncio.wait_for(
queue.get(), timeout=float(self.valves.TIMEOUT)
)
if chunk:
has_content = True
yield chunk
except asyncio.TimeoutError:
if done.is_set():
break
if self.thinking_started:
yield f"> [Debug] 等待响应中 (已超过 {self.valves.TIMEOUT} 秒)...\n"
continue
while not queue.empty():
chunk = queue.get_nowait()
if chunk:
has_content = True
yield chunk
if self.thinking_started:
yield "\n</think>\n"
has_content = True
# 核心修复:如果整个过程没有任何输出,返回一个提示,防止 OpenWebUI 报错
if not has_content:
yield "⚠️ Copilot 未返回任何内容。请检查模型 ID 是否正确,或尝试在 Valves 中开启 DEBUG 模式查看详细日志。"
except Exception as e:
yield f"\n[Stream Error: {str(e)}]"
finally:
unsubscribe()
# 销毁会话对象以释放内存,但保留磁盘数据
await session.destroy()

View File

@@ -217,6 +217,23 @@ def format_markdown_table(plugins: list[dict]) -> str:
return "\n".join(lines)
def _get_readme_url(file_path: str) -> str:
"""
Generate GitHub README URL from plugin file path.
从插件文件路径生成 GitHub README 链接。
"""
if not file_path:
return ""
# Extract plugin directory (e.g., plugins/filters/folder-memory/folder_memory.py -> plugins/filters/folder-memory)
from pathlib import Path
plugin_dir = Path(file_path).parent
# Convert to GitHub URL
return (
f"https://github.com/Fu-Jie/awesome-openwebui/blob/main/{plugin_dir}/README.md"
)
def format_release_notes(
comparison: dict[str, list], ignore_removed: bool = False
) -> str:
@@ -229,9 +246,12 @@ def format_release_notes(
if comparison["added"]:
lines.append("### 新增插件 / New Plugins")
for plugin in comparison["added"]:
readme_url = _get_readme_url(plugin.get("file_path", ""))
lines.append(f"- **{plugin['title']}** v{plugin['version']}")
if plugin.get("description"):
lines.append(f" - {plugin['description']}")
if readme_url:
lines.append(f" - 📖 [README / 文档]({readme_url})")
lines.append("")
if comparison["updated"]:
@@ -258,7 +278,10 @@ def format_release_notes(
)
prev_ver = prev_manifest.get("version") or prev.get("version")
readme_url = _get_readme_url(curr.get("file_path", ""))
lines.append(f"- **{curr_title}**: v{prev_ver} → v{curr_ver}")
if readme_url:
lines.append(f" - 📖 [README / 文档]({readme_url})")
lines.append("")
if comparison["removed"] and not ignore_removed: