feat(pipes): v0.7.0 final release with native tool UI and CLI integration

- Core: Adapt to OpenWebUI native tool call UI and thinking process visualization
- Infra: Bundle Copilot CLI via pip package (no more background curl installation)
- Fix: Resolve "Error getting file content" on OpenWebUI v0.8.0+ via absolute paths
- i18n: Add native localization for status messages in 11 languages
- UX: Optimize reasoning status display logic and cleanup legacy code

.agent/workflows/plugin-development.md

@@ -12,11 +12,11 @@ Reference: `.github/copilot-instructions.md`
 
 ### Bilingual Requirement
 
-Every plugin **MUST** have bilingual versions for both code and documentation:
+Every plugin **MUST** have a single internationalized code file and bilingual documentation:
 
-- **Code**:
+- **Code (i18n)**:
-  - English: `plugins/{type}/{name}/{name}.py`
+  - `plugins/{type}/{name}/{name}.py`
-  - Chinese: `plugins/{type}/{name}/{name_cn}.py` (or `中文名.py`)
+  - The single `.py` file must implement internal i18n (e.g., using `navigator.language` or backend headers) to support multiple languages natively, rather than splitting into separate files.
 - **README**:
   - English: `plugins/{type}/{name}/README.md`
   - Chinese: `plugins/{type}/{name}/README_CN.md`
@@ -81,14 +81,13 @@ Reference: `.github/workflows/release.yml`
 - **Release Information Compliance**: When a release is requested, the agent must generate a standard release summary (English commit title + bilingual bullet points) as defined in Section 3 & 5.
 - **Default Action (Prepare Only)**: When performing a version bump or update, the agent should update all files locally but **STOP** before committing. Present the changes and the **proposed Release/Commit Message** to the user and wait for explicit confirmation to commit/push.
 - **Consistency**: When bumping, update version in **ALL** locations:
-  1. English Code (`.py`)
+  1. Code (`.py`)
-  2. Chinese Code (`.py`)
+  2. English README (`README.md`)
-  3. English README (`README.md`)
+  3. Chinese README (`README_CN.md`)
-  4. Chinese README (`README_CN.md`)
+  4. Docs Index (`docs/.../index.md`)
-  5. Docs Index (`docs/.../index.md`)
+  5. Docs Index CN (`docs/.../index.zh.md`)
-  6. Docs Index CN (`docs/.../index.zh.md`)
+  6. Docs Detail (`docs/.../{name}.md`)
-  7. Docs Detail (`docs/.../{name}.md`)
+  7. Docs Detail CN (`docs/.../{name}.zh.md`)
-  8. Docs Detail CN (`docs/.../{name}.zh.md`)
 
 ### Automated Release Process
 
@@ -120,7 +119,7 @@ When the user confirms a release, the agent **MUST** follow these content standa
    - Before committing, present a "Release Draft" containing:
      - **Title**: e.g., `Release v0.1.1: [Plugin Name] - [Brief Summary]`
      - **Changelog**: English-only list of commits since the last release, including hashes (e.g., `896de02 docs(config): reorder antigravity model alias example`).
-     - **Verification Status**: Confirm all 8+ files have been updated and synced.
+     - **Verification Status**: Confirm all 7+ files have been updated and synced.
 3. **Internal Documentation**: Ensure "What's New" sections in READMEs and `docs/` match exactly the changes being released.
 
 ### Pull Request Check
@@ -134,7 +133,7 @@ When the user confirms a release, the agent **MUST** follow these content standa
 
 Before committing:
 
-- [ ] Code is bilingual and functional?
+- [ ] Code is internal i18n supported (`.py`) and fully functional?
 - [ ] Docstrings have updated version?
 - [ ] READMEs are updated and bilingual?
 - [ ] **Key Capabilities** in READMEs still cover all legacy core features + new features?

.github/copilot-instructions.md

@@ -8,27 +8,26 @@ This document defines the standard conventions and best practices for OpenWebUI
 
 ## 🏗️ 项目结构与命名 (Project Structure & Naming)
 
-### 1. 双语版本要求 (Bilingual Version Requirements)
+### 1. 语言与代码规范 (Language & Code Requirements)
 
 #### 插件代码 (Plugin Code)
 
-每个插件必须提供两个版本：
+每个插件**必须**采用单文件国际化 (i18n) 设计。严禁为不同语言创建独立的源代码文件（如 `_cn.py`）。
 
-1. **英文版本**: `plugin_name.py` - 英文界面、提示词和注释
+1.  **单代码文件**: `plugins/{type}/{name}/{name}.py`
-2. **中文版本**: `plugin_name_cn.py` - 中文界面、提示词和注释
+2.  **内置 i18n**: 必须在代码中根据前端传来的用户语言（如 `__user__` 中的 `language` 或通过 `get_user_language` 脚本读取）动态切换界面显示、提示词和状态日志。
 
-示例：
+示例目录结构：
 ```
 plugins/actions/export_to_docx/
-├── export_to_word.py      # English version
+├── export_to_word.py      # 单个代码文件，内置多语言支持
-├── export_to_word_cn.py    # Chinese version
+├── README.md               # 英文文档 (English documentation)
-├── README.md               # English documentation
+└── README_CN.md            # 中文文档
-└── README_CN.md            # Chinese documentation
 ```
 
 #### 文档 (Documentation)
 
-每个插件目录必须包含双语 README 文件：
+尽管代码是合一的，但为了市场展示和 SEO，每个插件目录仍**必须**包含双语 README 文件：
 
 - `README.md` - English documentation
 - `README_CN.md` - 中文文档
@@ -58,12 +57,10 @@ plugins/actions/export_to_docx/
 plugins/
 ├── actions/           # Action 插件 (用户触发的功能)
 │   ├── my_action/
-│   │   ├── my_action.py          # English version
+│   │   ├── my_action.py          # 单文件，内置 i18n
-│   │   ├── 我的动作.py            # Chinese version
 │   │   ├── README.md              # English documentation
 │   │   └── README_CN.md           # Chinese documentation
-│   ├── ACTION_PLUGIN_TEMPLATE.py      # English template
+│   ├── ACTION_PLUGIN_TEMPLATE.py      # 通用 i18n 模板
-│   ├── ACTION_PLUGIN_TEMPLATE_CN.py   # Chinese template
 │   └── README.md
 ├── filters/           # Filter 插件 (输入处理)
 │   └── ...
@@ -474,14 +471,124 @@ async def get_user_language(self):
 
 #### 适用场景与引导 (Usage Guidelines)
 
-- **语言适配**: 动态获取界面语言 (`ru-RU`, `zh-CN`) 自动切换输出语言。
+- **语言适配**: 动态获取界面语言 (`ru-RU`, `zh-CN`) 自动切换输出语言和 UI 翻译。这对于单文件 i18n 插件至关重要。
 - **时区处理**: 获取 `Intl.DateTimeFormat().resolvedOptions().timeZone` 处理时间。
 - **客户端存储**: 读取 `localStorage` 中的用户偏好设置。
 - **硬件能力**: 获取 `navigator.clipboard` 或 `navigator.geolocation` (需授权)。
 
 **注意**: 即使插件有 `Valves` 配置，也应优先尝试自动探测，提升用户体验。
 
-### 8. 智能代理文件交付规范 (Agent File Delivery Standards)
+### 8. 国际化 (i18n) 适配规范 (Internationalization Standards)
+
+开发供全球用户使用的插件时，必须预置多语言支持（如中文、英文等）。
+
+#### i18n 字典定义
+
+在文件顶部定义 `TRANSLATIONS` 字典存储多语言字符串：
+
+```python
+TRANSLATIONS = {
+    "en-US": {
+        "status_starting": "Smart Mind Map is starting...",
+    },
+    "zh-CN": {
+        "status_starting": "智能思维导图正在启动...",
+    },
+    # ... 其他语言
+}
+
+# 语言回退映射 (Fallback Map)
+FALLBACK_MAP = {
+    "zh": "zh-CN",
+    "zh-TW": "zh-CN",
+    "zh-HK": "zh-CN",
+    "en": "en-US",
+    "en-GB": "en-US"
+}
+```
+
+#### 获取当前用户真实语言 (Robust Language Detection)
+
+Open WebUI 的前端（localStorage）并未自动同步语言设置到后端数据库或通过标准 API 参数传递。为了获取精准的用户偏好语言，**必须**使用多层级回退机制（Multi-level Fallback）：
+`JS 动态探测 (localStorage)` > `HTTP 浏览器头 (Accept-Language)` > `用户 Profile 默认设置` > `en-US`
+
+> **注意！防卡死指南 (Anti-Deadlock Guide)**
+> 在通过 `__event_call__` 执行前端 JS 脚本时，如果前端脚本不慎抛出异常 (`Exception`) 会导致回调函数 `cb()` 永不执行，这会让后端的 `asyncio` 永远阻塞并卡死整个请求队列！
+> **必须**做两重防护：
+> 1. JS 内部包裹 `try...catch` 保证必须有 `return`。
+> 2. 后端使用 `asyncio.wait_for` 设置强制超时（建议 2 秒）。
+
+```python
+import asyncio
+from fastapi import Request
+
+async def _get_user_context(
+    self,
+    __user__: Optional[dict],
+    __event_call__: Optional[callable] = None,
+    __request__: Optional[Request] = None,
+) -> dict:
+    user_language = __user__.get("language", "en-US") if __user__ else "en-US"
+    
+    # 1st Fallback: HTTP Accept-Language header
+    if __request__ and hasattr(__request__, "headers") and "accept-language" in __request__.headers:
+        raw_lang = __request__.headers.get("accept-language", "")
+        if raw_lang:
+            user_language = raw_lang.split(",")[0].split(";")[0]
+
+    # 2nd Fallback (Best): Execute JS in frontend to read localStorage
+    if __event_call__:
+        try:
+            js_code = """
+                try {
+                    return (
+                        document.documentElement.lang ||
+                        localStorage.getItem('locale') || 
+                        navigator.language || 
+                        'en-US'
+                    );
+                } catch (e) {
+                    return 'en-US';
+                }
+            """
+            # 【致命！】必须设置 wait_for 防止前端无响应卡死后端
+            frontend_lang = await asyncio.wait_for(
+                __event_call__({"type": "execute", "data": {"code": js_code}}),
+                timeout=2.0
+            )
+            if frontend_lang and isinstance(frontend_lang, str):
+                user_language = frontend_lang
+        except Exception as e:
+            pass # fallback to accept-language or en-US
+
+    return {
+        "user_language": user_language,
+        # ... user_name, user_id etc.
+    }
+```
+
+#### 实际使用 (Usage in Action/Filter)
+
+在 Action 或者 Filter 执行时引用这套上下文获取机制，然后传入映射器获取最终翻译：
+
+```python
+async def action(
+    self, 
+    body: dict, 
+    __user__: Optional[dict] = None,
+    __event_call__: Optional[callable] = None, 
+    __request__: Optional[Request] = None,
+    **kwargs
+) -> Optional[dict]:
+    
+    user_ctx = await self._get_user_context(__user__, __event_call__, __request__)
+    user_lang = user_ctx["user_language"]
+    
+    # 获取多语言文本 (通过你的 translation.get() 扩展)
+    # start_msg = self._get_translation(user_lang, "status_starting")
+```
+
+### 9. 智能代理文件交付规范 (Agent File Delivery Standards)
 
 在开发具备文件生成能力的智能代理插件（如 GitHub Copilot SDK 集成）时，必须遵循以下标准流程，以确保文件在不同存储后端（本地/S3）下的可用性并绕过不必要的 RAG 处理。
 
@@ -501,7 +608,7 @@ async def get_user_language(self):
 - 代理应始终将“当前目录”视为其受保护所在的私有工作空间。
 - `publish_file_from_workspace` 的参数 `filename` 仅需传入相对于当前目录的文件名。
 
-### 9. Copilot SDK 插件工具定义规范 (Copilot SDK Tool Definition Standards)
+### 10. Copilot SDK 插件工具定义规范 (Copilot SDK Tool Definition Standards)
 
 在为 GitHub Copilot SDK 开发自定义工具时，为了确保大模型能正确识别参数（避免生成空的 `properties` Schema），必须遵循以下定义模式：
 
@@ -535,6 +642,63 @@ my_tool = define_tool(
 2.  **Field 描述**: 在 `BaseModel` 中使用 `Field(..., description="...")` 为每个参数提供详细的描述信息。
 3.  **Required vs Optional**: 明确标注必填项（无默认值）和可选项（带 `default`）。
 
+### 11. Copilot SDK 流式渲染与工具卡片规范 (Streaming & Tool Card Standards)
+
+在处理大模型的思维链（Reasoning）输出和工具调用（Tool Calls）时，为了确保能完美兼容 OpenWebUI 0.8.x 前端的 Markdown 解析器及原生折叠 UI 组件，必须遵循以下极度严格的输出格式规范。
+
+#### 思维链流式渲染 (Reasoning Streaming)
+
+为了让前端能够正确显示“Thinking...”的折叠框和 Spinner 动画，**必须**使用原生的 `<think>` 标签。
+
+- **正确的标签包裹**:
+  ```html
+  <think>
+  这里是思考过程...
+  </think>
+  ```
+- **关键细节**:
+  - **标签闭合检测**: 必须在代码内部维护状态（如 `state["thinking_started"]`）。当（1）正文内容即将开始输出，或（2）工具调用触发 (`tool.execution_start`) 时，**必须优先输出 `\n</think>\n` 强制闭合标签**。如果不闭合，后续的正文或工具面板会被全部吞进思考框内，导致页面完全崩坏！
+  - **不要手动拼装**: 严禁通过手动输出 `<details type="reasoning">` 等大段 HTML 来模拟思考过程，这种方式极易在流式片段发送中破坏前端 DOM 树并导致错位。
+
+#### 工具调用原生卡片 (Native Tool Calls Block)
+
+为了在对话界面中生成标准、原生的下拉折叠“工具调用”卡片，当 `event_type == "tool.execution_complete"` 时，必须向队列输出如下严格格式的 HTML：
+
+```python
+# 必须转义属性中的双引号为 &quot;
+args_for_attr = args_json_str.replace('"', "&quot;")
+result_for_attr = result_content.replace('"', "&quot;")
+
+tool_block = (
+    f'\\n<details type="tool_calls"'
+    f' id="{tool_call_id}"'
+    f' name="{tool_name}"'
+    f' arguments="{args_for_attr}"'
+    f' result="{result_for_attr}"'
+    f' done="true">\\n'
+    f"<summary>Tool Executed</summary>\\n"
+    f"</details>\\n\\n"
+)
+queue.put_nowait(tool_block)
+```
+
+- **致命避坑点 (Critical Pitfalls)**:
+  1. **属性转义 (Extremely Important)**: `<details>` 内的 `arguments` 和 `result` 属性**必须**将内部的所有双引号 `"` 替换为 `&quot;`。因为 OpenWebUI 前端提取这些数据的 Regex 是严格的 `="([^"]*)"`，一旦内容中出现原生双引号，就会被瞬间截断，导致参数被渲染为空并引发解析错误！
+  2. **换行符要求**: `<details ...>` 尖括号闭合后紧接着的内容**必须换行**（即 `>\\n`），否则 Markdown 扩展引擎无法将其识别为独立的 UI Block。
+  3. **去除冗余通知**: 不要在 `tool.execution_start` 事件中提前向对话流输出普通的 `🔧 Executing...` 纯文本块，这会导致最终页面上同时出现两块工具提示（一个文本，一个折叠卡片）。
+
+#### Debug 信息的解耦 (Decoupling Debug Logs)
+
+对于连接建立、运行环境、缓存加载等属于 *脚本自身运行状态* 的 Debug 信息：
+- **禁止**: 不要将这些内容 yield 到最终的回答数据流（或塞进 `<think>` 标签内），这会污染回答的纯粹性。
+- **推荐**: 统一使用 OpenWebUI 顶部的原生状态反馈气泡（Status Events）：
+  ```python
+  await __event_emitter__({
+      "type": "status",
+      "data": {"description": "连接建立，正在等待响应...", "done": True}
+  })
+  ```
+
 ---
 
 ## ⚡ Action 插件规范 (Action Plugin Standards)
@@ -932,8 +1096,7 @@ Filter 实例是**单例 (Singleton)**。
 
 ### 1. ✅ 开发检查清单 (Development Checklist)
 
-- [ ] 创建英文版插件代码 (`plugin_name.py`)
+- [ ] 代码实现了内置 i18n 逻辑 (`.py`)
-- [ ] 创建中文版插件代码 (`plugin_name_cn.py`)
 - [ ] 编写英文 README (`README.md`)
 - [ ] 编写中文 README (`README_CN.md`)
 - [ ] 包含标准化文档字符串
@@ -941,7 +1104,7 @@ Filter 实例是**单例 (Singleton)**。
 - [ ] 使用 Lucide 图标
 - [ ] 实现 Valves 配置
 - [ ] 使用 logging 而非 print
-- [ ] 测试双语界面
+- [ ] 测试 i18n 界面适配
 - [ ] **一致性检查**: 确保文档、代码、README 同步
 - [ ] **README 结构**: 
     - **Key Capabilities** (英文) / **核心功能** (中文): 必须包含所有核心功能
@@ -951,8 +1114,10 @@ Filter 实例是**单例 (Singleton)**。
 
 任何插件的**新增、修改或移除**，必须同时更新：
 1. **插件代码** (version)
-2. **项目文档** (`docs/`)
+2. **插件自述文件** (`plugins/{type}/{name}/README.md` & `README_CN.md`)
-3. **自述文件** (`README.md`)
+3. **项目文档** (`docs/plugins/{type}/{name}.md` & `.zh.md`)
+4. **项目文档索引** (`docs/plugins/{type}/index.md` & `index.zh.md` — 版本号)
+5. **项目根 README** (`README.md` & `README_CN.md` — 更新日期徽章 `![updated](https://img.shields.io/badge/YYYY--MM--DD-gray?style=flat)` 必须同步为发布当天日期)
 
 ### 3.  发布工作流 (Release Workflow)
 
@@ -988,13 +1153,14 @@ Filter 实例是**单例 (Singleton)**。
 2. **变更列表 (Bilingual Changes)**: 
    - 英文: Clear descriptions of technical/functional changes.
    - 中文: 清晰描述用户可见的功能改进或修复。
-3. **核查状态 (Verification)**: 确认版本号已在相关 8+ 处位置同步更新。
+3. **核查状态 (Verification)**: 确认版本号已在相关 7+ 处位置同步更新（1 个代码文件 + 2 个 README + 4 个 Docs 文件）。
 
 ### 4. 🤖 Git 提交与推送规范 (Git Operations & Push Rules)
 
 - **核心原则**: 默认仅进行**本地文件准备**（更新代码、READMEs、Docs、版本号），**严禁**在未获用户明确许可的情况下自动执行 `git commit` 或 `git push`。
 - **允许 (需确认)**: 只有在用户明确表示“发布”、“Commit it”、“Release”或“提交”后，才允许直接推送到 `main` 分支或创建 PR。
 - **功能分支**: 推荐在进行大规模重构或实验性功能开发时，创建功能分支 (`feature/xxx`) 进行隔离。
+- **PR 提交**: 必须使用 GitHub CLI (`gh`) 创建 Pull Request。示例：`gh pr create --title "feat: ..." --body "..."`。
 
 ### 5. 🤝 贡献者认可规范 (Contributor Recognition)
 
@@ -1004,8 +1170,7 @@ Filter 实例是**单例 (Singleton)**。
 
 ## 📚 参考资源 (Reference Resources)
 
-- [Action 插件模板 (英文)](plugins/actions/ACTION_PLUGIN_TEMPLATE.py)
+- [Action 插件模板](plugins/actions/ACTION_PLUGIN_TEMPLATE.py)
-- [Action 插件模板 (中文)](plugins/actions/ACTION_PLUGIN_TEMPLATE_CN.py)
 - [插件开发指南](plugins/actions/PLUGIN_DEVELOPMENT_GUIDE.md)
 - [Lucide Icons](https://lucide.dev/icons/)
 - [OpenWebUI 文档](https://docs.openwebui.com/)

.github/workflows/release.yml

@@ -329,8 +329,7 @@ jobs:
           DETECTED_CHANGES: ${{ needs.check-changes.outputs.release_notes }}
           COMMITS: ${{ steps.commits.outputs.commits }}
         run: |
-          echo "# ${VERSION} Release" > release_notes.md
+          > release_notes.md
-          echo "" >> release_notes.md
           
           if [ -n "$TITLE" ]; then
             echo "## $TITLE" >> release_notes.md

.gitignore

@@ -139,3 +139,4 @@ logs/
 
 # OpenWebUI specific
 # Add any specific ignores for OpenWebUI plugins if needed
+.git-worktrees/

README.md

@@ -24,12 +24,12 @@ A collection of enhancements, plugins, and prompts for [OpenWebUI](https://githu
 
 | Rank | Plugin | Version | Downloads | Views | 📅 Updated |
 | :---: | :--- | :---: | :---: | :---: | :---: |
-| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | ![p1_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_version.json&style=flat) | ![p1_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_dl.json&style=flat) | ![p1_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
+| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | ![p1_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_version.json&style=flat) | ![p1_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_dl.json&style=flat) | ![p1_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--02--22-gray?style=flat) |
 | 🥈 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | ![p2_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p2_version.json&style=flat) | ![p2_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p2_dl.json&style=flat) | ![p2_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p2_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--31-gray?style=flat) |
 | 🥉 | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | ![p3_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p3_version.json&style=flat) | ![p3_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p3_dl.json&style=flat) | ![p3_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p3_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--02--07-gray?style=flat) |
-| 4️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | ![p4_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_version.json&style=flat) | ![p4_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_dl.json&style=flat) | ![p4_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
+| 4️⃣ | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | ![p4_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_version.json&style=flat) | ![p4_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_dl.json&style=flat) | ![p4_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
-| 5️⃣ | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | ![p5_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_version.json&style=flat) | ![p5_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_dl.json&style=flat) | ![p5_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--02--10-gray?style=flat) |
+| 5️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | ![p5_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_version.json&style=flat) | ![p5_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_dl.json&style=flat) | ![p5_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
-| 6️⃣ | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | ![p6_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_version.json&style=flat) | ![p6_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_dl.json&style=flat) | ![p6_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
+| 6️⃣ | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | ![p6_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_version.json&style=flat) | ![p6_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_dl.json&style=flat) | ![p6_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--02--10-gray?style=flat) |
 
 ### 📈 Total Downloads Trend
 

README_CN.md

@@ -21,12 +21,12 @@ OpenWebUI 增强功能集合。包含个人开发与收集的插件、提示词
 
 | 排名 | 插件 | 版本 | 下载 | 浏览 | 📅 更新 |
 | :---: | :--- | :---: | :---: | :---: | :---: |
-| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | ![p1_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_version.json&style=flat) | ![p1_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_dl.json&style=flat) | ![p1_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
+| 🥇 | [Smart Mind Map](https://openwebui.com/posts/turn_any_text_into_beautiful_mind_maps_3094c59a) | ![p1_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_version.json&style=flat) | ![p1_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_dl.json&style=flat) | ![p1_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p1_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--02--22-gray?style=flat) |
 | 🥈 | [Smart Infographic](https://openwebui.com/posts/smart_infographic_ad6f0c7f) | ![p2_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p2_version.json&style=flat) | ![p2_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p2_dl.json&style=flat) | ![p2_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p2_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--31-gray?style=flat) |
 | 🥉 | [Export to Word Enhanced](https://openwebui.com/posts/export_to_word_enhanced_formatting_fca6a315) | ![p3_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p3_version.json&style=flat) | ![p3_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p3_dl.json&style=flat) | ![p3_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p3_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--02--07-gray?style=flat) |
-| 4️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | ![p4_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_version.json&style=flat) | ![p4_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_dl.json&style=flat) | ![p4_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
+| 4️⃣ | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | ![p4_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_version.json&style=flat) | ![p4_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_dl.json&style=flat) | ![p4_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p4_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
-| 5️⃣ | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | ![p5_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_version.json&style=flat) | ![p5_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_dl.json&style=flat) | ![p5_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--02--10-gray?style=flat) |
+| 5️⃣ | [Async Context Compression](https://openwebui.com/posts/async_context_compression_b1655bc8) | ![p5_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_version.json&style=flat) | ![p5_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_dl.json&style=flat) | ![p5_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p5_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
-| 6️⃣ | [Markdown Normalizer](https://openwebui.com/posts/markdown_normalizer_baaa8732) | ![p6_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_version.json&style=flat) | ![p6_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_dl.json&style=flat) | ![p6_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--01--29-gray?style=flat) |
+| 6️⃣ | [Export to Excel](https://openwebui.com/posts/export_mulit_table_to_excel_244b8f9d) | ![p6_version](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_version.json&style=flat) | ![p6_dl](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_dl.json&style=flat) | ![p6_vw](https://img.shields.io/endpoint?url=https%3A%2F%2Fgist.githubusercontent.com%2FFu-Jie%2Fdb3d95687075a880af6f1fba76d679c6%2Fraw%2Fbadge_p6_vw.json&style=flat) | ![updated](https://img.shields.io/badge/2026--02--10-gray?style=flat) |
 
 ### 📈 总下载量累计趋势
 

docs/plugins/actions/index.md

@@ -23,7 +23,7 @@ Actions are interactive plugins that:
 
     Intelligently analyzes text content and generates interactive mind maps with beautiful visualizations.
 
-    **Version:** 0.9.2
+    **Version:** 1.0.0
 
     [:octicons-arrow-right-24: Documentation](smart-mind-map.md)
 

docs/plugins/actions/index.zh.md

@@ -23,7 +23,7 @@ Actions 是交互式插件，能够：
 
     智能分析文本并生成交互式、精美的思维导图。
 
-    **版本：** 0.8.0
+    **版本：** 1.0.0
 
     [:octicons-arrow-right-24: 查看文档](smart-mind-map.md)
 

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

@@ -1,7 +1,7 @@
 # Smart Mind Map
 
 <span class="category-badge action">Action</span>
-<span class="version-badge">v0.9.2</span>
+<span class="version-badge">v1.0.0</span>
 
 Intelligently analyzes text content and generates interactive mind maps for better visualization and understanding.
 
@@ -17,7 +17,8 @@ The Smart Mind Map plugin transforms text content into beautiful, interactive mi
 - :material-gesture-swipe: **Rich Controls**: Zoom, reset view, expand level selector (All/2/3) and fullscreen
 - :material-palette: **Theme Aware**: Auto-detects OpenWebUI light/dark theme with manual toggle
 - :material-download: **One-Click Export**: Download high-res PNG, copy SVG, or copy Markdown source
-- :material-translate: **Multi-language**: Matches output language to the input text
+- :material-translate: **i18n Embedded**: One code file smartly detects frontend languages and translates the output.
+- :material-arrow-all: **Auto-Sizing & Direct Embed**: Seamlessly scales to display massive canvas inline (requires setting toggle).
 
 ---
 
@@ -50,6 +51,7 @@ The Smart Mind Map plugin transforms text content into beautiful, interactive mi
 | `MIN_TEXT_LENGTH` | integer | `100` | Minimum characters required before analysis runs |
 | `CLEAR_PREVIOUS_HTML` | boolean | `false` | Clear previous plugin HTML instead of merging |
 | `MESSAGE_COUNT` | integer | `1` | Number of recent messages to include (1–5) |
+| `ENABLE_DIRECT_EMBED_MODE` | boolean | `false` | Enable inline full-width UI for OpenWebUI 0.8.0+ |
 
 ---
 

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

@@ -1,7 +1,7 @@
 # Smart Mind Map（智能思维导图）
 
 <span class="category-badge action">Action</span>
-<span class="version-badge">v0.9.2</span>
+<span class="version-badge">v1.0.0</span>
 
 智能分析文本内容，生成交互式思维导图，帮助你更直观地理解信息结构。
 
@@ -17,7 +17,8 @@ Smart Mind Map 会将文本转换成漂亮的交互式思维导图。插件会
 - :material-gesture-swipe: **丰富控制**：缩放/重置、展开层级（全部/2/3 级）与全屏
 - :material-palette: **主题感知**：自动检测 OpenWebUI 亮/暗色主题并支持手动切换
 - :material-download: **一键导出**：下载高分辨率 PNG、复制 SVG 或 Markdown
-- :material-translate: **多语言**：输出语言与输入文本一致
+- :material-translate: **内置 i18n 语言识别**：单个文件自动检测控制台前端语言，无需繁杂的各种语言包版本。
+- :material-arrow-all: **直出全屏版体验 (需配置开启)**：新版直出渲染抛开沙盒限制，纵情铺满屏幕，享受原生的图表体验。
 
 ---
 
@@ -50,6 +51,7 @@ Smart Mind Map 会将文本转换成漂亮的交互式思维导图。插件会
 | `MIN_TEXT_LENGTH` | integer | `100` | 开始分析所需的最少字符数 |
 | `CLEAR_PREVIOUS_HTML` | boolean | `false` | 生成新导图时是否清除之前的插件 HTML |
 | `MESSAGE_COUNT` | integer | `1` | 用于生成的最近消息数量（1–5） |
+| `ENABLE_DIRECT_EMBED_MODE` | boolean | `false` | 是否开启沉浸式直出模式 (需要 Open WebUI 0.8.0+ ) |
 
 ---
 

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

@@ -1,137 +1,81 @@
-# Async Context Compression
+# Async Context Compression Filter
 
-<span class="category-badge filter">Filter</span>
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **Version:** 1.3.0 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **License:** MIT
-<span class="version-badge">v1.2.2</span>
 
-Reduces token consumption in long conversations through intelligent summarization while maintaining conversational coherence.
+This filter reduces token consumption in long conversations through intelligent summarization and message compression while keeping conversations coherent.
+
+## What's new in 1.3.0
+
+- **Internationalization (i18n)**: Complete localization of user-facing messages across 9 languages (English, Chinese, Japanese, Korean, French, German, Spanish, Italian).
+- **Smart Status Display**: Added `token_usage_status_threshold` valve (default 80%) to intelligently control when token usage status is shown.
+- **Improved Performance**: Frontend language detection and logging are optimized to be completely non-blocking, maintaining lightning-fast TTFB.
+- **Copilot SDK Integration**: Automatically detects and skips compression for copilot_sdk based models to prevent conflicts.
+- **Configuration**: `debug_mode` is now set to `false` by default for a quieter production experience.
 
 ---
 
-## Overview
+## Core Features
 
-The Async Context Compression filter helps manage token usage in long conversations by:
+- ✅ **Full i18n Support**: Native localization across 9 languages.
-
+- ✅ Automatic compression triggered by token thresholds.
-- Intelligently summarizing older messages
+- ✅ Asynchronous summarization that does not block chat responses.
-- Preserving important context
+- ✅ Persistent storage via Open WebUI's shared database connection (PostgreSQL, SQLite, etc.).
-- Reducing API costs
+- ✅ Flexible retention policy to keep the first and last N messages.
-- Maintaining conversation coherence
+- ✅ Smart injection of historical summaries back into the context.
-
+- ✅ Structure-aware trimming that preserves document structure (headers, intro, conclusion).
-This is especially useful for:
+- ✅ Native tool output trimming for cleaner context when using function calling.
-
+- ✅ Real-time context usage monitoring with warning notifications (>90%).
-- Long-running conversations
+- ✅ Detailed token logging for precise debugging and optimization.
-- Complex multi-turn discussions
+- ✅ **Smart Model Matching**: Automatically inherits configuration from base models for custom presets.
-- Cost optimization
+- ⚠ **Multimodal Support**: Images are preserved but their tokens are **NOT** calculated. Please adjust thresholds accordingly.
-- Token limit management
-
-## Features
-
-- :material-arrow-collapse-vertical: **Smart Compression**: AI-powered context summarization
-- :material-clock-fast: **Async Processing**: Non-blocking background compression
-- :material-memory: **Context Preservation**: Keeps important information
-- :material-currency-usd-off: **Cost Reduction**: Minimize token usage
-- :material-console: **Frontend Debugging**: Debug logs in browser console
-- :material-alert-circle-check: **Enhanced Error Reporting**: Clear error status notifications
-- :material-check-all: **Open WebUI v0.7.x Compatibility**: Dynamic DB session handling
-- :material-account-convert: **Improved Compatibility**: Summary role changed to `assistant`
-- :material-shield-check: **Enhanced Stability**: Resolved race conditions in state management
-- :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
 
 ---
 
-## Installation
+## Installation & Configuration
 
-1. Download the plugin file: [`async_context_compression.py`](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/filters/async-context-compression)
+### 1) Database (automatic)
-2. Upload to OpenWebUI: **Admin Panel** → **Settings** → **Functions**
+
-3. Configure compression settings
+- Uses Open WebUI's shared database connection; no extra configuration needed.
-4. Enable the filter
+- The `chat_summary` table is created on first run.
+
+### 2) Filter order
+
+- Recommended order: pre-filters (<10) → this filter (10) → post-filters (>10).
 
 ---
 
-## How It Works
+## Configuration Parameters
 
-```mermaid
+| Parameter                      | Default  | Description                                                                                                                                                           |
-graph TD
+| :----------------------------- | :------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-    A[Incoming Messages] --> B{Token Count > Threshold?}
+| `priority`                     | `10`     | Execution order; lower runs earlier.                                                                                                                                  |
-    B -->|No| C[Pass Through]
+| `compression_threshold_tokens` | `64000`  | Trigger asynchronous summary when total tokens exceed this value. Set to 50%-70% of your model's context window.                                                      |
-    B -->|Yes| D[Summarize Older Messages]
+| `max_context_tokens`           | `128000` | Hard cap for context; older messages (except protected ones) are dropped if exceeded.                                                                                 |
-    D --> E[Preserve Recent Messages]
+| `keep_first`                   | `1`      | Always keep the first N messages (protects system prompts).                                                                                                           |
-    E --> F[Combine Summary + Recent]
+| `keep_last`                    | `6`      | Always keep the last N messages to preserve recent context.                                                                                                           |
-    F --> G[Send to LLM]
+| `summary_model`                | `None`   | Model for summaries. Strongly recommended to set a fast, economical model (e.g., `gemini-2.5-flash`, `deepseek-v3`). Falls back to the current chat model when empty. |
-```
+| `summary_model_max_context`    | `0`      | 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`                   | `false`  | Log verbose debug info. Set to `false` in production.                                                                                                                 |
+| `show_debug_log`               | `false`  | Print debug logs to browser console (F12). Useful for frontend debugging.                                                                                             |
+| `show_token_usage_status`      | `true`   | Show token usage status notification in the chat interface.                                                                                                           |
+| `token_usage_status_threshold` | `80`     | The minimum usage percentage (0-100) required to show a context usage status notification.                                                                            |
 
 ---
 
-## Configuration
+## ⭐ Support
 
-| Option | Type | Default | Description |
+If this plugin has been useful, a star on [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) is a big motivation for me. Thank you for the support.
-|--------|------|---------|-------------|
-| `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 |
 
----
+## Troubleshooting ❓
 
-## Example
+- **Initial system prompt is lost**: Keep `keep_first` greater than 0 to protect the initial message.
+- **Compression effect is weak**: Raise `compression_threshold_tokens` or lower `keep_first` / `keep_last` to allow more aggressive compression.
+- **Submit an Issue**: If you encounter any problems, please submit an issue on GitHub: [OpenWebUI Extensions Issues](https://github.com/Fu-Jie/openwebui-extensions/issues)
 
-### Before Compression
+## Changelog
 
-```
+See the full history on GitHub: [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions)
-[Message 1] User: Tell me about Python...
-[Message 2] AI: Python is a programming language...
-[Message 3] User: What about its history?
-[Message 4] AI: Python was created by Guido...
-[Message 5] User: And its features?
-[Message 6] AI: Python has many features...
-... (many more messages)
-[Message 20] User: Current question
-```
-
-### After Compression
-
-```
-[Summary] Previous conversation covered Python basics,
-history, features, and common use cases...
-
-[Message 18] User: Recent question about decorators
-[Message 19] AI: Decorators in Python are...
-[Message 20] User: Current question
-```
-
----
-
-## Requirements
-
-!!! note "Prerequisites"
-    - OpenWebUI v0.3.0 or later
-    - Access to an LLM for summarization
-
-!!! tip "Best Practices"
-    - Set appropriate token thresholds based on your model's context window
-    - Preserve more recent messages for technical discussions
-    - Test compression settings in non-critical conversations first
-
----
-
-## Troubleshooting
-
-??? question "Compression not triggering?"
-    Check if the token count exceeds your configured threshold. Enable debug logging for more details.
-
-??? question "Important context being lost?"
-    Increase the `preserve_recent` setting or lower the compression ratio.
-
----
-
-## Source Code
-
-[:fontawesome-brands-github: View on GitHub](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/filters/async-context-compression){ .md-button }

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

@@ -1,137 +1,119 @@
-# Async Context Compression（异步上下文压缩）
+# 异步上下文压缩过滤器
 
-<span class="category-badge filter">Filter</span>
+**作者:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **版本:** 1.3.0 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **许可证:** MIT
-<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。
+> **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。
+
+## 1.3.0 版本更新
+
+- **国际化 (i18n) 支持**: 完成了所有用户可见消息的本地化，现已原生支持 9 种语言（含中、英、日、韩及欧洲主要语言）。
+- **智能状态显示**: 新增 `token_usage_status_threshold` 阀门（默认 80%），可以智能控制何时显示 Token 用量状态，减少不必要的打扰。
+- **性能大幅优化**: 对前端语言检测和日志处理流程进行了非阻塞重构，完全不影响首字节响应时间（TTFB），保持毫秒级极速推流。
+- **Copilot SDK 兼容**: 自动检测并跳过基于 `copilot_sdk` 模型的上下文压缩，避免冲突。
+- **配置项调整**: 为了提供更安静的生产环境体验，`debug_mode` 现已默认设置为 `false`。
 
 ---
 
-## 概览
+## 核心特性
 
-Async Context Compression 过滤器通过以下方式帮助管理长对话的 token 使用：
+- ✅ **全方位国际化**: 原生支持 9 种界面语言。
+- ✅ **自动压缩**: 基于 Token 阈值自动触发上下文压缩。
+- ✅ **异步摘要**: 后台生成摘要，不阻塞当前对话响应。
+- ✅ **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。
 
-- 智能总结较早的消息
+详细的工作原理和流程请参考 [工作流程指南](https://github.com/Fu-Jie/openwebui-extensions/blob/main/plugins/filters/async-context-compression/WORKFLOW_GUIDE_CN.md)。
-- 保留关键信息
-- 降低 API 成本
-- 保持对话一致性
-
-特别适用于：
-
-- 长时间会话
-- 多轮复杂讨论
-- 成本优化
-- 上下文长度控制
-
-## 功能特性
-
-- :material-arrow-collapse-vertical: **智能压缩**：AI 驱动的上下文摘要
-- :material-clock-fast: **异步处理**：后台非阻塞压缩
-- :material-memory: **保留上下文**：尽量保留重要信息
-- :material-currency-usd-off: **降低成本**：减少 token 使用
-- :material-console: **前端调试**：支持浏览器控制台日志
-- :material-alert-circle-check: **增强错误报告**：清晰的错误状态通知
-- :material-check-all: **Open WebUI v0.7.x 兼容性**：动态数据库会话处理
-- :material-account-convert: **兼容性提升**：摘要角色改为 `assistant`
-- :material-shield-check: **稳定性增强**：解决状态管理竞态条件
-- :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**
 
 ---
 
-## 安装
+## 安装与配置
 
-1. 下载插件文件：[`async_context_compression.py`](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/filters/async-context-compression)
+### 1. 数据库（自动）
-2. 上传到 OpenWebUI：**Admin Panel** → **Settings** → **Functions**
+
-3. 配置压缩参数
+- 自动使用 Open WebUI 的共享数据库连接，**无需额外配置**。
-4. 启用过滤器
+- 首次运行自动创建 `chat_summary` 表。
+
+### 2. 过滤器顺序
+
+- 建议顺序：前置过滤器（<10）→ 本过滤器（10）→ 后置过滤器（>10）。
 
 ---
 
-## 工作原理
+## 配置参数
 
-```mermaid
+您可以在过滤器的设置中调整以下参数：
-graph TD
+
-    A[Incoming Messages] --> B{Token Count > Threshold?}
+### 核心参数
-    B -->|No| C[Pass Through]
+
-    B -->|Yes| D[Summarize Older Messages]
+| 参数                           | 默认值   | 描述                                                                                  |
-    D --> E[Preserve Recent Messages]
+| :----------------------------- | :------- | :------------------------------------------------------------------------------------ |
-    E --> F[Combine Summary + Recent]
+| `priority`                     | `10`     | 过滤器执行顺序，数值越小越先执行。                                                    |
-    F --> G[Send to LLM]
+| `compression_threshold_tokens` | `64000`  | **重要**: 当上下文总 Token 超过此值时后台生成摘要，建议设为模型上下文窗口的 50%-70%。 |
+| `max_context_tokens`           | `128000` | **重要**: 上下文硬上限，超过即移除最早消息（保留受保护消息）。                        |
+| `keep_first`                   | `1`      | 始终保留对话开始的 N 条消息，保护系统提示或环境变量。                                 |
+| `keep_last`                    | `6`      | 始终保留对话末尾的 N 条消息，确保最近上下文连贯。                                     |
+
+### 摘要生成配置
+
+| 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。                                                                                                  |
+
+### 高级配置
+
+#### `model_thresholds` (模型特定阈值)
+
+这是一个字典配置，可为特定模型 ID 覆盖全局 `compression_threshold_tokens` 与 `max_context_tokens`，适用于混合不同上下文窗口的模型。
+
+**默认包含 GPT-4、Claude 3.5、Gemini 1.5/2.0、Qwen 2.5/3、DeepSeek V3 等推荐阈值。**
+
+**配置示例：**
+
+```json
+{
+  "gpt-4": {
+    "compression_threshold_tokens": 8000,
+    "max_context_tokens": 32000
+  },
+  "gemini-2.5-flash": {
+    "compression_threshold_tokens": 734000,
+    "max_context_tokens": 1048576
+  }
+}
 ```
 
----
+| 参数                           | 默认值   | 描述                                                                                                                                    |
-
+| :----------------------------- | :------- | :-------------------------------------------------------------------------------------------------------------------------------------- |
-## 配置项
+| `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`                   | `false`   | 是否在 Open WebUI 的控制台日志中打印详细的调试信息。生产环境默认且建议设为 `false`。 |
-| 选项 | 类型 | 默认值 | 说明 |
+| `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。                                                                         |
-| `compression_threshold_tokens` | integer | `64000` | 超过该 token 数触发压缩 |
+| `token_usage_status_threshold` | `80`     | 触发显示上下文用量状态通知的最低百分比阈值 (0-100)。                                                                    |
-| `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 |
 
 ---
 
-## 示例
+## ⭐ 支持
 
-### 压缩前
+如果这个插件对你有帮助，欢迎到 [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) 点个 Star，这将是我持续改进的动力，感谢支持。
 
-```
+## 故障排除 (Troubleshooting) ❓
-[Message 1] User: Tell me about Python...
-[Message 2] AI: Python is a programming language...
-[Message 3] User: What about its history?
-[Message 4] AI: Python was created by Guido...
-[Message 5] User: And its features?
-[Message 6] AI: Python has many features...
-... (many more messages)
-[Message 20] User: Current question
-```
 
-### 压缩后
+- **初始系统提示丢失**：将 `keep_first` 设置为大于 0。
+- **压缩效果不明显**：提高 `compression_threshold_tokens`，或降低 `keep_first` / `keep_last` 以增强压缩力度。
+- **提交 Issue**: 如果遇到任何问题，请在 GitHub 上提交 Issue：[OpenWebUI Extensions Issues](https://github.com/Fu-Jie/openwebui-extensions/issues)
 
-```
+## 更新日志
-[Summary] Previous conversation covered Python basics,
-history, features, and common use cases...
 
-[Message 18] User: Recent question about decorators
+完整历史请查看 GitHub 项目： [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions)
-[Message 19] AI: Decorators in Python are...
-[Message 20] User: Current question
-```
-
----
-
-## 运行要求
-
-!!! note "前置条件"
-    - OpenWebUI v0.3.0 及以上
-    - 需要可用的 LLM 用于摘要
-
-!!! tip "最佳实践"
-    - 根据模型上下文窗口设置合适的 token 阈值
-    - 技术讨论可适当提高 `preserve_recent`
-    - 先在非关键对话中测试压缩效果
-
----
-
-## 常见问题
-
-??? question "没有触发压缩？"
-    检查 token 数是否超过配置的阈值，并开启调试日志了解细节。
-
-??? question "重要上下文丢失？"
-    提高 `preserve_recent` 或降低压缩比例。
-
----
-
-## 源码
-
-[:fontawesome-brands-github: 在 GitHub 查看](https://github.com/Fu-Jie/openwebui-extensions/tree/main/plugins/filters/async-context-compression){ .md-button }

docs/plugins/filters/index.md

@@ -22,7 +22,7 @@ Filters act as middleware in the message pipeline:
 
     Reduces token consumption in long conversations through intelligent summarization while maintaining coherence.
 
-    **Version:** 1.2.2
+    **Version:** 1.3.0
 
     [:octicons-arrow-right-24: Documentation](async-context-compression.md)
 

docs/plugins/filters/index.zh.md

@@ -22,7 +22,7 @@ Filter 充当消息管线中的中间件：
 
     通过智能总结减少长对话的 token 消耗，同时保持连贯性。
 
-    **版本：** 1.2.2
+    **版本：** 1.3.0
 
     [:octicons-arrow-right-24: 查看文档](async-context-compression.md)
 

docs/plugins/pipes/github-copilot-sdk.md

@@ -1,6 +1,6 @@
 # GitHub Copilot SDK Pipe for OpenWebUI
 
-**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.6.2 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **License:** MIT
+**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.7.0 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **License:** MIT
 
 This is an advanced Pipe function for [OpenWebUI](https://github.com/open-webui/open-webui) that integrates the official [GitHub Copilot SDK](https://github.com/github/copilot-sdk). It enables you to use **GitHub Copilot models** (e.g., `gpt-5.2-codex`, `claude-sonnet-4.5`,`gemini-3-pro`, `gpt-5-mini`) **AND** your own models via **BYOK** (OpenAI, Anthropic) directly within OpenWebUI, providing a unified agentic experience with **strict User & Chat-level Workspace Isolation**.
 
@@ -14,12 +14,13 @@ This is an advanced Pipe function for [OpenWebUI](https://github.com/open-webui/
 
 ---
 
-## ✨ v0.6.2 Updates (What's New)
+## ✨ v0.7.0 Updates (What's New)
 
-- **🛠️ New Workspace Artifacts Tool**: Introduced `publish_file_from_workspace`. Agents can now generate files (e.g., Python-generated Excel/CSV) and provide direct download links for the user to click and save.
+- **🚀 Integrated CLI Management**: The Copilot CLI is now automatically managed and bundled via the `github-copilot-sdk` pip package. (v0.7.0)
-- **⚙️ Workflow Optimization**: Improved reliability of the internal agentic workspace management.
+- **🧠 Native Tool Call UI**: Full adaptation to **OpenWebUI's native tool call UI** and thinking process visualization. (v0.7.0)
-- **🛡️ Enhanced Security**: Refined access control for system resources within the isolated environment.
+- **🏠 OpenWebUI v0.8.0+ Fix**: Resolved "Error getting file content" download failure by switching to absolute path registration for published files. (v0.7.0)
-- **🔧 Performance Tuning**: Optimized stream processing for larger context windows.
+- **🌐 Comprehensive Multi-language Support**: Native localization for status messages in 11 languages (EN, ZH, JA, KO, FR, DE, ES, IT, RU, VI, ID). (v0.7.0)
+- **🧹 Architecture Cleanup**: Refactored core setup and optimized reasoning status display for a leaner experience. (v0.7.0)
 
 ---
 
@@ -31,8 +32,8 @@ This is an advanced Pipe function for [OpenWebUI](https://github.com/open-webui/
 - **♾️ Infinite Session Management**: Smart context window management with automatic compaction for indefinite conversation capability.
 - **🧠 Deep Database Integration**: Real-time persistence of TOD·O lists for long-running workflows.
 - **🌊 Advanced Streaming**: Full support for thinking process/Chain of Thought visualization.
-- **🖼️ Intelligent Multimodal**: Vision capabilities and raw file analysis support.
+- **🖼️ Intelligent Multimodal**: Vision capabilities and raw file analysis support (bypasses RAG for direct binary access).
-- **⚡ Full-Lifecycle File Agent**: Supports receiving uploaded files for raw bypass analysis and publishing results (Excel/reports) as downloadable links.
+- **📤 Workspace Artifacts (`publish_file_from_workspace`)**: Agents can generate files (Excel, CSV, HTML reports, etc.) and provide **persistent download links** directly in the chat.
 - **🖼️ Interactive Artifacts**: Automatically renders HTML/JS apps generated by the agent directly in the chat interface.
 
 ---
@@ -110,7 +111,7 @@ If this plugin has been useful, a **Star** on [OpenWebUI Extensions](https://git
 
 - **Agent ignores files?**: Ensure the Files Filter is enabled, otherwise RAG will interfere with raw binaries.
 - **No progress bar?**: The bar only appears when the Agent uses the `update_todo` tool.
-- **Dependencies**: This Pipe automatically installs `github-copilot-sdk` (Python) and `github-copilot-cli` (Binary).
+- **Dependencies**: This Pipe automatically manages `github-copilot-sdk` (Python) and utilizes the bundled binary CLI. No manual install required.
 
 ---
 

docs/plugins/pipes/github-copilot-sdk.zh.md

@@ -1,6 +1,6 @@
 # GitHub Copilot SDK 官方管道
 
-**作者:** [Fu-Jie](https://github.com/Fu-Jie) | **版本:** 0.6.2 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **许可证:** MIT
+**作者:** [Fu-Jie](https://github.com/Fu-Jie) | **版本:** 0.7.0 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **许可证:** MIT
 
 这是一个用于 [OpenWebUI](https://github.com/open-webui/open-webui) 的高级 Pipe 函数，深度集成了 **GitHub Copilot SDK**。它不仅支持 **GitHub Copilot 官方模型**（如 `gpt-5.2-codex`, `claude-sonnet-4.5`, `gemini-3-pro`, `gpt-5-mini`），还支持 **BYOK (自带 Key)** 模式对接自定义服务商（OpenAI, Anthropic），并具备**严格的用户与会话级工作区隔离**能力，提供统一且安全的 Agent 交互体验。
 
@@ -14,12 +14,13 @@
 
 ---
 
-## ✨ 0.6.2 更新内容 (What's New)
+## ✨ 0.7.0 更新内容 (What's New)
 
-- **🛠️ 新增工作区产物工具**: 引入 `publish_file_from_workspace`。Agent 现在可以生成物理文件（如使用 Python 生成的 Excel/CSV 报表），并直接在聊天界面提供点击下载链接。
+- **🚀 CLI 免维护集成**: Copilot CLI 现在通过 `github-copilot-sdk` pip 包自动同步管理，彻底告别手动 `curl | bash` 安装问题。(v0.7.0)
-- **⚙️ 工作流优化**: 提升了内部 Agent 物理工作区管理的可靠性与原子性。
+- **🧠 原生工具调用 UI**: 全面适配 **OpenWebUI 原生工具调用 UI** 与模型思考过程（思维链）展示。(v0.7.0)
-- **🛡️ 安全增强**: 精细化了隔离环境下系统资源的访问控制策略。
+- **🏠 OpenWebUI v0.8.0+ 兼容性修复**: 通过切换为绝对路径注册发布文件，彻底解决了“Error getting file content”无法下载到本地的问题。(v0.7.0)
-- **🔧 性能微调**: 针对大上下文窗口优化了流式数据处理性能。
+- **🌐 全面的多语言支持**: 针对状态消息进行了 11 国语言的原生本地化 (中/英/日/韩/法/德/西/意/俄/越/印尼)。(v0.7.0)
+- **🧹 架构精简**: 重构了初始化逻辑并优化了推理状态显示，提供更轻量稳健的体验。(v0.7.0)
 
 ---
 
@@ -31,8 +32,8 @@
 - **♾️ 无限会话管理**: 智能上下文窗口管理与自动压缩算法，支持无限时长的对话交互。
 - **🧠 深度数据库集成**: 实时持久化 TOD·O 列表到 UI 进度条。
 - **🌊 深度推理展示**: 完整支持模型思考过程 (Thinking Process) 的流式渲染。
-- **🖼️ 智能多模态**: 完整支持图像识别与附件上传分析。
+- **🖼️ 智能多模态**: 完整支持图像识别与附件上传分析（绕过 RAG 直接访问原始二进制内容）。
-- **⚡ 全生命周期文件 Agent**: 支持接收上传文件进行绕过 RAG 的深度分析，并将处理结果（如 Excel/报告）发布为下载链接实现闭环。
+- **📤 工作区产物工具 (`publish_file_from_workspace`)**: Agent 可生成文件（Excel、CSV、HTML 报告等）并直接提供**持久化下载链接**。管理员还可额外获得通过 `/content/html` 接口的**聊天内 HTML 预览**链接。
 - **🖼️ 交互式伪影 (Artifacts)**: 自动渲染 Agent 生成的 HTML/JS 应用程序，直接在聊天界面交互。
 
 ---
@@ -95,7 +96,7 @@
 ### 1) 导入函数
 
 1. 打开 OpenWebUI，前往 **工作区** -> **函数**。
-2. 点击 **+** (创建函数)，完整粘贴 `github_copilot_sdk_cn.py` 的内容。
+2. 点击 **+** (创建函数)，完整粘贴 `github_copilot_sdk.py` 的内容。
 3. 点击保存并确保已启用。
 
 ### 2) 获取 Token (Get Token)
@@ -110,7 +111,7 @@
 
 - **Agent 无法识别文件？**: 请确保已安装并启用了 Files Filter 插件，否则原始文件会被 RAG 干扰。
 - **看不到 TODO 进度条？**: 进度条仅在 Agent 使用 `update_todo` 工具（通常是处理复杂任务）时出现。
-- **依赖安装**: 本管道会自动尝试安装 `github-copilot-sdk` (Python 包) 和 `github-copilot-cli` (官方二进制)。
+- **依赖安装**: 本管道会自动管理 `github-copilot-sdk` (Python 包) 并优先直接使用内置的二进制 CLI，无需手动干预。
 
 ---
 

docs/plugins/pipes/index.md

@@ -15,7 +15,7 @@ Pipes allow you to:
 
 ## Available Pipe Plugins
 
-- [GitHub Copilot SDK](github-copilot-sdk.md) (v0.6.2) - Official GitHub Copilot SDK integration. Features **Workspace Isolation**, **Database Persistence**, **Zero-config OpenWebUI Tool Bridge**, **BYOK** support, and **dynamic MCP discovery**. Supports streaming, multimodal, and infinite sessions. [View Deep Dive](github-copilot-sdk-deep-dive.md) | [**View Advanced Tutorial**](github-copilot-sdk-tutorial.md).
+- [GitHub Copilot SDK](github-copilot-sdk.md) (v0.7.0) - Official GitHub Copilot SDK integration. Features **Workspace Isolation**, **Database Persistence**, **Zero-config OpenWebUI Tool Bridge**, **BYOK** support, and **dynamic MCP discovery**. Supports streaming, multimodal, and infinite sessions. [View Deep Dive](github-copilot-sdk-deep-dive.md) | [**View Advanced Tutorial**](github-copilot-sdk-tutorial.md).
 - **[Case Study: GitHub 100 Star Growth Analysis](star-prediction-example.md)** - Learn how to use the GitHub Copilot SDK Pipe with Minimax 2.1 to automatically analyze CSV data and generate project growth reports.
 - **[Case Study: High-Quality Video to GIF Conversion](video-processing-example.md)** - See how the model uses system-level FFmpeg to accelerate, scale, and optimize colors for screen recordings.
 

docs/plugins/pipes/index.zh.md

@@ -15,7 +15,7 @@ Pipes 可以用于：
 
 ## 可用的 Pipe 插件
 
-- [GitHub Copilot SDK](github-copilot-sdk.zh.md) (v0.6.2) - GitHub Copilot SDK 官方集成。具备**工作区安全隔离**、**数据库持久化**、**零配置工具桥接**与**BYOK (自带 Key) 支持**。支持流式输出、打字机思考过程及无限会话。[查看深度架构解析](github-copilot-sdk-deep-dive.zh.md) | [**查看进阶实战教程**](github-copilot-sdk-tutorial.zh.md)。
+- [GitHub Copilot SDK](github-copilot-sdk.zh.md) (v0.7.0) - GitHub Copilot SDK 官方集成。具备**工作区安全隔离**、**数据库持久化**、**零配置工具桥接**与**BYOK (自带 Key) 支持**。支持流式输出、打字机思考过程及无限会话。[查看深度架构解析](github-copilot-sdk-deep-dive.zh.md) | [**查看进阶实战教程**](github-copilot-sdk-tutorial.zh.md)。
 - **[实战案例：GitHub 100 Star 增长预测](star-prediction-example.zh.md)** - 展示如何使用 GitHub Copilot SDK Pipe 结合 Minimax 2.1 模型，自动编写脚本分析 CSV 数据并生成详细的项目增长报告。
 - **[实战案例：视频高质量 GIF 转换与加速](video-processing-example.zh.md)** - 演示模型如何通过底层 FFmpeg 工具对录屏进行加速、缩放及双阶段色彩优化处理。
 

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

@@ -2,21 +2,26 @@
 
 Smart Mind Map is a powerful OpenWebUI action plugin that intelligently analyzes long-form text content and automatically generates interactive mind maps, helping users structure and visualize knowledge.
 
-**Author:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **Version:** 0.9.2 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **License:** MIT
+**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 1.0.0 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **License:** MIT
 
-## What's New in v0.9.2
+## What's New in v1.0.0
 
-**Language Rule Alignment**
+### Direct Embed & UI Refinements
 
-- **Input Language First**: Mind map output now strictly matches the input text language.
+- **Native Multi-language UI (i18n)**: The plugin interface (buttons, settings, status) now automatically adapts to your browser's language setting for a seamless global experience.
-- **Consistent Behavior**: Matches the infographic language rule for predictable multilingual output.
+- **Direct Embed Mode**: Introduced a native-like inline display mode for Open WebUI 0.8.0+, enabling a seamless full-width canvas.
+- **Adaptive Auto-Sizing**: Mind map now dynamically scales its height and perfectly refits to the window to eliminate scrollbar artifacts.
+- **Subdued & Compact UI**: Completely redesigned the header tooling bar to a slender, single-line configuration to maximize visual rendering space.
+- **Configurable Experience**: Added `ENABLE_DIRECT_EMBED_MODE` valve to explicitly toggle the new inline rendering behavior.
 
 ## Key Features 🔑
 
 - ✅ **Intelligent Text Analysis**: Automatically identifies core themes, key concepts, and hierarchical structures.
+- ✅ **Native Multi-language UI**: Automatic interface translation (i18n) based on system language for a native feel.
 - ✅ **Interactive Visualization**: Generates beautiful interactive mind maps based on Markmap.js.
+- ✅ **Direct Embed Mode**: (Optional) For Open WebUI 0.8.0+, render natively inline to fill entire UI width.
 - ✅ **High-Resolution PNG Export**: Export mind maps as high-quality PNG images (9x scale).
-- ✅ **Complete Control Panel**: Zoom controls, expand level selection, and fullscreen mode.
+- ✅ **Complete Control Panel**: Zoom controls, expand level selection, and fullscreen mode within a compact toolbar.
 - ✅ **Theme Switching**: Manual theme toggle button with automatic theme detection.
 - ✅ **Image Output Mode**: Generate static SVG images embedded directly in Markdown for cleaner history.
 
@@ -37,6 +42,7 @@ Smart Mind Map is a powerful OpenWebUI action plugin that intelligently analyzes
 | `CLEAR_PREVIOUS_HTML` | `false` | Whether to clear previous plugin-generated HTML content. |
 | `MESSAGE_COUNT` | `1` | Number of recent messages to use for generation (1-5). |
 | `OUTPUT_MODE` | `html` | Output mode: `html` (interactive) or `image` (static). |
+| `ENABLE_DIRECT_EMBED_MODE` | `false` | Enable Direct Embed Mode (Open WebUI 0.8.0+ native layout) instead of Legacy Mode. |
 
 ## ⭐ Support
 

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

@@ -2,21 +2,26 @@
 
 思维导图是一个强大的 OpenWebUI 动作插件，能够智能分析长篇文本内容，自动生成交互式思维导图，帮助用户结构化和可视化知识。
 
-**作者:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **版本:** 0.9.2 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **许可证:** MIT
+**作者:** [Fu-Jie](https://github.com/Fu-Jie) | **版本:** 1.0.0 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **许可证:** MIT
 
-## v0.9.2 更新亮点
+## v1.0.0 最新更新
 
-**语言规则对齐**
+### 嵌入式直出与 UI 细节全线重构
 
-- **输入语言优先**：导图输出严格与输入文本语言一致。
+- **原生多语言界面 (Native i18n)**：插件界面（按钮、设置说明、状态提示）现在会根据您浏览器的语言设置自动适配系统语言。
-- **一致性提升**：与信息图语言规则保持一致，多语言输出更可预期。
+- **原生态嵌入模式 (Direct Embed)**：针对 Open WebUI 0.8.0+ 的前端架构支持了纯正的内容内联（Inline）直出模式，不再受气泡和 Markdown 隔离，真正撑满屏幕宽度。
+- **自动响应边界 (Auto-Sizing)**：突破以前高度僵死的问题。思维导图现在可以根据您的当前屏幕大小弹性伸缩（动态 `clamp()` 高度），彻底消灭丑陋的局部滚动条与白边。
+- **极简专业 UI (Compact UI)**：推倒重做了头部的菜单栏，统一使用了一套干净、单行的极简全透明微拟物 Toolbar 设计，为导图画布省下极大的垂直空间。
+- **模式配置自由**：为了照顾阅读流连贯的习惯，新增了 `ENABLE_DIRECT_EMBED_MODE` 配置开关。您必须在设置中显式开启才能体验宽广内联全屏模式。
 
 ## 核心特性 🔑
 
 - ✅ **智能文本分析**：自动识别文本的核心主题、关键概念和层次结构。
+- ✅ **原生多语言界面**：根据系统语言自动切换界面语言 (i18n)，提供原生交互体验。
 - ✅ **交互式可视化**：基于 Markmap.js 生成美观的交互式思维导图。
+- ✅ **直出全景内嵌 (Direct Embed)**：(可选开关) 对于 Open WebUI 0.8.0+，直接填补整个前端宽度，去除气泡剥离感。
 - ✅ **高分辨率 PNG 导出**：导出高质量的 PNG 图片（9 倍分辨率）。
-- ✅ **完整控制面板**：缩放控制、展开层级选择、全屏模式。
+- ✅ **完整控制面板**：极简清爽的单行大屏缩放控制、展开层级选择、全局全屏等核心操作。
 - ✅ **主题切换**：手动主题切换按钮与自动主题检测。
 - ✅ **图片输出模式**：生成静态 SVG 图片直接嵌入 Markdown，聊天记录更简洁。
 
@@ -37,6 +42,7 @@
 | `CLEAR_PREVIOUS_HTML` | `false` | 在生成新的思维导图时，是否清除之前的 HTML 内容。 |
 | `MESSAGE_COUNT` | `1` | 用于生成思维导图的最近消息数量（1-5）。 |
 | `OUTPUT_MODE` | `html` | 输出模式：`html`（交互式）或 `image`（静态图片）。 |
+| `ENABLE_DIRECT_EMBED_MODE` | `false` | 是否开启沉浸式直出嵌入模式（需要 Open WebUI v0.8.0+ 环境）。如果保持 `false` 将会维持旧版的对话流 Markdown 渲染模式。 |
 
 ## ⭐ 支持
 

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

@@ -1,18 +1,22 @@
 # Async Context Compression Filter
 
-**Author:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **Version:** 1.2.2 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **License:** MIT
+**Author:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **Version:** 1.3.0 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **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
+## What's new in 1.3.0
 
-- **Critical Fix**: Resolved `TypeError: 'str' object is not callable` caused by variable name conflict in logging function.
+- **Internationalization (i18n)**: Complete localization of user-facing messages across 9 languages (English, Chinese, Japanese, Korean, French, German, Spanish, Italian).
-- **Compatibility**: Enhanced `params` handling to support Pydantic objects, improving compatibility with different OpenWebUI versions.
+- **Smart Status Display**: Added `token_usage_status_threshold` valve (default 80%) to intelligently control when token usage status is shown.
+- **Improved Performance**: Frontend language detection and logging are optimized to be completely non-blocking, maintaining lightning-fast TTFB.
+- **Copilot SDK Integration**: Automatically detects and skips compression for copilot_sdk based models to prevent conflicts.
+- **Configuration**: `debug_mode` is now set to `false` by default for a quieter production experience.
 
 ---
 
 ## Core Features
 
+- ✅ **Full i18n Support**: Native localization across 9 languages.
 - ✅ Automatic compression triggered by token thresholds.
 - ✅ Asynchronous summarization that does not block chat responses.
 - ✅ Persistent storage via Open WebUI's shared database connection (PostgreSQL, SQLite, etc.).
@@ -55,8 +59,10 @@ This filter reduces token consumption in long conversations through intelligent
 | `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.                                                                                                                 |
+| `debug_mode`                   | `false`  | Log verbose debug info. Set to `false` in production.                                                                                                                 |
 | `show_debug_log`               | `false`  | Print debug logs to browser console (F12). Useful for frontend debugging.                                                                                             |
+| `show_token_usage_status`      | `true`   | Show token usage status notification in the chat interface.                                                                                                           |
+| `token_usage_status_threshold` | `80`     | The minimum usage percentage (0-100) required to show a context usage status notification.                                                                            |
 
 ---
 

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

@@ -1,20 +1,24 @@
 # 异步上下文压缩过滤器
 
-**作者:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **版本:** 1.2.2 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **许可证:** MIT
+**作者:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **版本:** 1.3.0 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **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
+## 1.3.0 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。
+- **国际化 (i18n) 支持**: 完成了所有用户可见消息的本地化，现已原生支持 9 种语言（含中、英、日、韩及欧洲主要语言）。
-- **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。
+- **智能状态显示**: 新增 `token_usage_status_threshold` 阀门（默认 80%），可以智能控制何时显示 Token 用量状态，减少不必要的打扰。
+- **性能大幅优化**: 对前端语言检测和日志处理流程进行了非阻塞重构，完全不影响首字节响应时间（TTFB），保持毫秒级极速推流。
+- **Copilot SDK 兼容**: 自动检测并跳过基于 `copilot_sdk` 模型的上下文压缩，避免冲突。
+- **配置项调整**: 为了提供更安静的生产环境体验，`debug_mode` 现已默认设置为 `false`。
 
 ---
 
 ## 核心特性
 
+- ✅ **全方位国际化**: 原生支持 9 种界面语言。
 - ✅ **自动压缩**: 基于 Token 阈值自动触发上下文压缩。
 - ✅ **异步摘要**: 后台生成摘要，不阻塞当前对话响应。
 - ✅ **持久化存储**: 复用 Open WebUI 共享数据库连接，自动支持 PostgreSQL/SQLite 等。
@@ -27,7 +31,7 @@
 - ✅ **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)。
+详细的工作原理和流程请参考 [工作流程指南](https://github.com/Fu-Jie/openwebui-extensions/blob/main/plugins/filters/async-context-compression/WORKFLOW_GUIDE_CN.md)。
 
 ---
 
@@ -93,9 +97,10 @@
 | 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`。 |
+| `debug_mode`                   | `false`   | 是否在 Open WebUI 的控制台日志中打印详细的调试信息。生产环境默认且建议设为 `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。                                                                         |
+| `token_usage_status_threshold` | `80`     | 触发显示上下文用量状态通知的最低百分比阈值 (0-100)。                                                                    |
 
 ---
 

plugins/filters/async-context-compression/async_context_compression.py

@@ -5,17 +5,17 @@ author: Fu-Jie
 author_url: https://github.com/Fu-Jie/openwebui-extensions
 funding_url: https://github.com/open-webui
 description: Reduces token consumption in long conversations while maintaining coherence through intelligent summarization and message compression.
-version: 1.2.2
+version: 1.3.0
 openwebui_id: b1655bc8-6de9-4cad-8cb5-a6f7829a02ce
 license: MIT
 
 ═══════════════════════════════════════════════════════════════════════════════
-📌 What's new in 1.2.1
+📌 What's new in 1.3.0
 ═══════════════════════════════════════════════════════════════════════════════
 
-  ✅ Smart Configuration: Automatically detects base model settings for custom models and adds `summary_model_max_context` for independent summary limits.
+  ✅ Smart Status Display: Added `token_usage_status_threshold` valve (default 80%) to control when token usage status is shown, reducing unnecessary notifications.
-  ✅ Performance & Refactoring: Optimized threshold parsing with caching and removed redundant code for better efficiency.
+  ✅ Copilot SDK Integration: Automatically detects and skips compression for copilot_sdk based models to prevent conflicts.
-  ✅ Bug Fixes & Modernization: Fixed `datetime` deprecation warnings and corrected type annotations.
+  ✅ Improved User Experience: Status messages now only appear when token usage exceeds the configured threshold, keeping the interface cleaner.
 
 ═══════════════════════════════════════════════════════════════════════════════
 📌 Overview
@@ -150,7 +150,7 @@ summary_temperature
   Description: Controls the randomness of the summary generation. Lower values produce more deterministic output.
 
 debug_mode
-  Default: true
+  Default: false
   Description: Prints detailed debug information to the log. Recommended to set to `false` in production.
 
 show_debug_log
@@ -268,6 +268,7 @@ import hashlib
 import time
 import contextlib
 import logging
+from functools import lru_cache
 
 # Setup logger
 logger = logging.getLogger(__name__)
@@ -391,6 +392,130 @@ class ChatSummary(owui_Base):
     )
 
 
+TRANSLATIONS = {
+    "en-US": {
+        "status_context_usage": "Context Usage (Estimated): {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_high_usage": " | ⚠️ High Usage",
+        "status_loaded_summary": "Loaded historical summary (Hidden {count} historical messages)",
+        "status_context_summary_updated": "Context Summary Updated: {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_generating_summary": "Generating context summary in background...",
+        "status_summary_error": "Summary Error: {error}",
+        "summary_prompt_prefix": "【Previous Summary: The following is a summary of the historical conversation, provided for context only. Do not reply to the summary content itself; answer the subsequent latest questions directly.】\n\n",
+        "summary_prompt_suffix": "\n\n---\nBelow is the recent conversation:",
+        "tool_trimmed": "... [Tool outputs trimmed]\n{content}",
+        "content_collapsed": "\n... [Content collapsed] ...\n",
+    },
+    "zh-CN": {
+        "status_context_usage": "上下文用量 (预估): {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_high_usage": " | ⚠️ 用量较高",
+        "status_loaded_summary": "已加载历史总结 (隐藏了 {count} 条历史消息)",
+        "status_context_summary_updated": "上下文总结已更新: {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_generating_summary": "正在后台生成上下文总结...",
+        "status_summary_error": "总结生成错误: {error}",
+        "summary_prompt_prefix": "【前情提要：以下是历史对话的总结，仅供上下文参考。请不要回复总结内容本身，直接回答之后最新的问题。】\n\n",
+        "summary_prompt_suffix": "\n\n---\n以下是最近的对话：",
+        "tool_trimmed": "... [工具输出已裁剪]\n{content}",
+        "content_collapsed": "\n... [内容已折叠] ...\n",
+    },
+    "zh-HK": {
+        "status_context_usage": "上下文用量 (預估): {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_high_usage": " | ⚠️ 用量較高",
+        "status_loaded_summary": "已載入歷史總結 (隱藏了 {count} 條歷史訊息)",
+        "status_context_summary_updated": "上下文總結已更新: {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_generating_summary": "正在後台生成上下文總結...",
+        "status_summary_error": "總結生成錯誤: {error}",
+        "summary_prompt_prefix": "【前情提要：以下是歷史對話的總結，僅供上下文參考。請不要回覆總結內容本身，直接回答之後最新的問題。】\n\n",
+        "summary_prompt_suffix": "\n\n---\n以下是最近的對話：",
+        "tool_trimmed": "... [工具輸出已裁剪]\n{content}",
+        "content_collapsed": "\n... [內容已折疊] ...\n",
+    },
+    "zh-TW": {
+        "status_context_usage": "上下文用量 (預估): {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_high_usage": " | ⚠️ 用量較高",
+        "status_loaded_summary": "已載入歷史總結 (隱藏了 {count} 條歷史訊息)",
+        "status_context_summary_updated": "上下文總結已更新: {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_generating_summary": "正在後台生成上下文總結...",
+        "status_summary_error": "總結生成錯誤: {error}",
+        "summary_prompt_prefix": "【前情提要：以下是歷史對話的總結，僅供上下文参考。請不要回覆總結內容本身，直接回答之後最新的問題。】\n\n",
+        "summary_prompt_suffix": "\n\n---\n以下是最近的對話：",
+        "tool_trimmed": "... [工具輸出已裁剪]\n{content}",
+        "content_collapsed": "\n... [內容已折疊] ...\n",
+    },
+    "ja-JP": {
+        "status_context_usage": "コンテキスト使用量 (推定): {tokens} / {max_tokens} トークン ({ratio}%)",
+        "status_high_usage": " | ⚠️ 使用量高",
+        "status_loaded_summary": "履歴の要約を読み込みました ({count} 件の履歴メッセージを非表示)",
+        "status_context_summary_updated": "コンテキストの要約が更新されました: {tokens} / {max_tokens} トークン ({ratio}%)",
+        "status_generating_summary": "バックグラウンドでコンテキスト要約を生成しています...",
+        "status_summary_error": "要約エラー: {error}",
+        "summary_prompt_prefix": "【これまでのあらすじ：以下は過去の会話の要約であり、コンテキストの参考としてのみ提供されます。要約の内容自体には返答せず、その後の最新の質問に直接答えてください。】\n\n",
+        "summary_prompt_suffix": "\n\n---\n以下は最近の会話です：",
+        "tool_trimmed": "... [ツールの出力をトリミングしました]\n{content}",
+        "content_collapsed": "\n... [コンテンツが折りたたまれました] ...\n",
+    },
+    "ko-KR": {
+        "status_context_usage": "컨텍스트 사용량 (예상): {tokens} / {max_tokens} 토큰 ({ratio}%)",
+        "status_high_usage": " | ⚠️ 사용량 높음",
+        "status_loaded_summary": "이전 요약 불러옴 ({count}개의 이전 메시지 숨김)",
+        "status_context_summary_updated": "컨텍스트 요약 업데이트됨: {tokens} / {max_tokens} 토큰 ({ratio}%)",
+        "status_generating_summary": "백그라운드에서 컨텍스트 요약 생성 중...",
+        "status_summary_error": "요약 오류: {error}",
+        "summary_prompt_prefix": "【이전 요약: 다음은 이전 대화의 요약이며 문맥 참고용으로만 제공됩니다. 요약 내용 자체에 답하지 말고 последу의 최신 질문에 직접 답하세요.】\n\n",
+        "summary_prompt_suffix": "\n\n---\n다음은 최근 대화입니다:",
+        "tool_trimmed": "... [도구 출력 잘림]\n{content}",
+        "content_collapsed": "\n... [내용 접힘] ...\n",
+    },
+    "fr-FR": {
+        "status_context_usage": "Utilisation du contexte (estimée) : {tokens} / {max_tokens} jetons ({ratio}%)",
+        "status_high_usage": " | ⚠️ Utilisation élevée",
+        "status_loaded_summary": "Résumé historique chargé ({count} messages d'historique masqués)",
+        "status_context_summary_updated": "Résumé du contexte mis à jour : {tokens} / {max_tokens} jetons ({ratio}%)",
+        "status_generating_summary": "Génération du résumé du contexte en arrière-plan...",
+        "status_summary_error": "Erreur de résumé : {error}",
+        "summary_prompt_prefix": "【Résumé précédent : Ce qui suit est un résumé de la conversation historique, fourni uniquement pour le contexte. Ne répondez pas au contenu du résumé lui-même ; répondez directement aux dernières questions.】\n\n",
+        "summary_prompt_suffix": "\n\n---\nVoici la conversation récente :",
+        "tool_trimmed": "... [Sorties d'outils coupées]\n{content}",
+        "content_collapsed": "\n... [Contenu réduit] ...\n",
+    },
+    "de-DE": {
+        "status_context_usage": "Kontextnutzung (geschätzt): {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_high_usage": " | ⚠️ Hohe Nutzung",
+        "status_loaded_summary": "Historische Zusammenfassung geladen ({count} historische Nachrichten ausgeblendet)",
+        "status_context_summary_updated": "Kontextzusammenfassung aktualisiert: {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_generating_summary": "Kontextzusammenfassung wird im Hintergrund generiert...",
+        "status_summary_error": "Zusammenfassungsfehler: {error}",
+        "summary_prompt_prefix": "【Vorherige Zusammenfassung: Das Folgende ist eine Zusammenfassung der historischen Konversation, die nur als Kontext dient. Antworten Sie nicht auf den Inhalt der Zusammenfassung selbst, sondern direkt auf die nachfolgenden neuesten Fragen.】\n\n",
+        "summary_prompt_suffix": "\n\n---\nHier ist die jüngste Konversation:",
+        "tool_trimmed": "... [Werkzeugausgaben gekürzt]\n{content}",
+        "content_collapsed": "\n... [Inhalt ausgeblendet] ...\n",
+    },
+    "es-ES": {
+        "status_context_usage": "Uso del contexto (estimado): {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_high_usage": " | ⚠️ Uso elevado",
+        "status_loaded_summary": "Resumen histórico cargado ({count} mensajes históricos ocultos)",
+        "status_context_summary_updated": "Resumen del contexto actualizado: {tokens} / {max_tokens} Tokens ({ratio}%)",
+        "status_generating_summary": "Generando resumen del contexto en segundo plano...",
+        "status_summary_error": "Error de resumen: {error}",
+        "summary_prompt_prefix": "【Resumen anterior: El siguiente es un resumen de la conversación histórica, proporcionado solo como contexto. No responda al contenido del resumen en sí; responda directamente a las preguntas más recientes.】\n\n",
+        "summary_prompt_suffix": "\n\n---\nA continuación se muestra la conversación reciente:",
+        "tool_trimmed": "... [Salidas de herramientas recortadas]\n{content}",
+        "content_collapsed": "\n... [Contenido contraído] ...\n",
+    },
+    "it-IT": {
+        "status_context_usage": "Utilizzo contesto (stimato): {tokens} / {max_tokens} Token ({ratio}%)",
+        "status_high_usage": " | ⚠️ Utilizzo elevato",
+        "status_loaded_summary": "Riepilogo storico caricato ({count} messaggi storici nascosti)",
+        "status_context_summary_updated": "Riepilogo contesto aggiornato: {tokens} / {max_tokens} Token ({ratio}%)",
+        "status_generating_summary": "Generazione riepilogo contesto in background...",
+        "status_summary_error": "Errore riepilogo: {error}",
+        "summary_prompt_prefix": "【Riepilogo precedente: Il seguente è un riepilogo della conversazione storica, fornito solo per contesto. Non rispondere al contenuto del riepilogo stesso; rispondi direttamente alle domande più recenti.】\n\n",
+        "summary_prompt_suffix": "\n\n---\nDi seguito è riportata la conversazione recente:",
+        "tool_trimmed": "... [Output degli strumenti tagliati]\n{content}",
+        "content_collapsed": "\n... [Contenuto compresso] ...\n",
+    },
+}
+
+
 # Global cache for tiktoken encoding
 TIKTOKEN_ENCODING = None
 if tiktoken:
@@ -400,6 +525,26 @@ if tiktoken:
         logger.error(f"[Init] Failed to load tiktoken encoding: {e}")
 
 
+@lru_cache(maxsize=1024)
+def _get_cached_tokens(text: str) -> int:
+    """Calculates tokens with LRU caching for exact string matches."""
+    if not text:
+        return 0
+    if TIKTOKEN_ENCODING:
+        try:
+            # tiktoken logic is relatively fast, but caching it based on exact string match
+            # turns O(N) encoding time to O(1) dictionary lookup for historical messages.
+            return len(TIKTOKEN_ENCODING.encode(text))
+        except Exception as e:
+            logger.warning(
+                f"[Token Count] tiktoken error: {e}, falling back to character estimation"
+            )
+            pass
+
+    # Fallback strategy: Rough estimation (1 token ≈ 4 chars)
+    return len(text) // 4
+
+
 class Filter:
     def __init__(self):
         self.valves = self.Valves()
@@ -409,8 +554,105 @@ class Filter:
             sessionmaker(bind=self._db_engine) if self._db_engine else None
         )
         self._model_thresholds_cache: Optional[Dict[str, Any]] = None
+
+        # Fallback mapping for variants not in TRANSLATIONS keys
+        self.fallback_map = {
+            "es-AR": "es-ES",
+            "es-MX": "es-ES",
+            "fr-CA": "fr-FR",
+            "en-CA": "en-US",
+            "en-GB": "en-US",
+            "en-AU": "en-US",
+            "de-AT": "de-DE",
+        }
+
         self._init_database()
 
+    def _resolve_language(self, lang: str) -> str:
+        """Resolve the best matching language code from the TRANSLATIONS dict."""
+        target_lang = lang
+
+        # 1. Direct match
+        if target_lang in TRANSLATIONS:
+            return target_lang
+
+        # 2. Variant fallback (explicit mapping)
+        if target_lang in self.fallback_map:
+            target_lang = self.fallback_map[target_lang]
+            if target_lang in TRANSLATIONS:
+                return target_lang
+
+        # 3. Base language fallback (e.g. fr-BE -> fr-FR)
+        if "-" in lang:
+            base_lang = lang.split("-")[0]
+            for supported_lang in TRANSLATIONS:
+                if supported_lang.startswith(base_lang + "-"):
+                    return supported_lang
+
+        # 4. Final Fallback to en-US
+        return "en-US"
+
+    def _get_translation(self, lang: str, key: str, **kwargs) -> str:
+        """Get translated string for the given language and key."""
+        target_lang = self._resolve_language(lang)
+        lang_dict = TRANSLATIONS.get(target_lang, TRANSLATIONS["en-US"])
+        text = lang_dict.get(key, TRANSLATIONS["en-US"].get(key, key))
+        if kwargs:
+            try:
+                text = text.format(**kwargs)
+            except Exception as e:
+                logger.warning(f"Translation formatting failed for {key}: {e}")
+        return text
+
+    async def _get_user_context(
+        self,
+        __user__: Optional[Dict[str, Any]],
+        __event_call__: Optional[Callable[[Any], Awaitable[None]]] = None,
+    ) -> Dict[str, str]:
+        """Extract basic user context with safe fallbacks."""
+        if isinstance(__user__, (list, tuple)):
+            user_data = __user__[0] if __user__ else {}
+        elif isinstance(__user__, dict):
+            user_data = __user__
+        else:
+            user_data = {}
+
+        user_id = user_data.get("id", "unknown_user")
+        user_name = user_data.get("name", "User")
+        user_language = user_data.get("language", "en-US")
+
+        if __event_call__:
+            try:
+                js_code = """
+                    return (
+                        document.documentElement.lang ||
+                        localStorage.getItem('locale') || 
+                        localStorage.getItem('language') || 
+                        navigator.language || 
+                        'en-US'
+                    );
+                """
+                frontend_lang = await asyncio.wait_for(
+                    __event_call__({"type": "execute", "data": {"code": js_code}}),
+                    timeout=1.0,
+                )
+                if frontend_lang and isinstance(frontend_lang, str):
+                    user_language = frontend_lang
+            except asyncio.TimeoutError:
+                logger.warning(
+                    "Failed to retrieve frontend language: Timeout (using fallback)"
+                )
+            except Exception as e:
+                logger.warning(
+                    f"Failed to retrieve frontend language: {type(e).__name__}: {e}"
+                )
+
+        return {
+            "user_id": user_id,
+            "user_name": user_name,
+            "user_language": user_language,
+        }
+
     def _parse_model_thresholds(self) -> Dict[str, Any]:
         """Parse model_thresholds string into a dictionary.
 
@@ -574,7 +816,7 @@ class Filter:
             description="The temperature for summary generation.",
         )
         debug_mode: bool = Field(
-            default=True, description="Enable detailed logging for debugging."
+            default=False, description="Enable detailed logging for debugging."
         )
         show_debug_log: bool = Field(
             default=False, description="Show debug logs in the frontend console"
@@ -582,6 +824,12 @@ class Filter:
         show_token_usage_status: bool = Field(
             default=True, description="Show token usage status notification"
         )
+        token_usage_status_threshold: int = Field(
+            default=80,
+            ge=0,
+            le=100,
+            description="Only show token usage status when usage exceeds this percentage (0-100). Set to 0 to always show.",
+        )
         enable_tool_output_trimming: bool = Field(
             default=False,
             description="Enable trimming of large tool outputs (only works with native function calling).",
@@ -654,20 +902,7 @@ class Filter:
 
     def _count_tokens(self, text: str) -> int:
         """Counts the number of tokens in the text."""
-        if not text:
+        return _get_cached_tokens(text)
-            return 0
-
-        if TIKTOKEN_ENCODING:
-            try:
-                return len(TIKTOKEN_ENCODING.encode(text))
-            except Exception as e:
-                if self.valves.debug_mode:
-                    logger.warning(
-                        f"[Token Count] tiktoken error: {e}, falling back to character estimation"
-                    )
-
-        # Fallback strategy: Rough estimation (1 token ≈ 4 chars)
-        return len(text) // 4
 
     def _calculate_messages_tokens(self, messages: List[Dict]) -> int:
         """Calculates the total tokens for a list of messages."""
@@ -693,6 +928,20 @@ class Filter:
 
         return total_tokens
 
+    def _estimate_messages_tokens(self, messages: List[Dict]) -> int:
+        """Fast estimation of tokens based on character count (1/4 ratio)."""
+        total_chars = 0
+        for msg in messages:
+            content = msg.get("content", "")
+            if isinstance(content, list):
+                for part in content:
+                    if isinstance(part, dict) and part.get("type") == "text":
+                        total_chars += len(part.get("text", ""))
+            else:
+                total_chars += len(str(content))
+
+        return total_chars // 4
+
     def _get_model_thresholds(self, model_id: str) -> Dict[str, int]:
         """Gets threshold configuration for a specific model.
 
@@ -830,12 +1079,14 @@ class Filter:
                 }})();
             """
 
-            await __event_call__(
+            asyncio.create_task(
+                __event_call__(
                     {
                         "type": "execute",
                         "data": {"code": js_code},
                     }
                 )
+            )
         except Exception as e:
             logger.error(f"Error emitting debug log: {e}")
 
@@ -876,17 +1127,55 @@ class Filter:
                 js_code = f"""
                     console.log("%c[Compression] {safe_message}", "{css}");
                 """
-                # Add timeout to prevent blocking if frontend connection is broken
+                asyncio.create_task(
-                await asyncio.wait_for(
+                    event_call({"type": "execute", "data": {"code": js_code}})
-                    event_call({"type": "execute", "data": {"code": js_code}}),
-                    timeout=2.0,
-                )
-            except asyncio.TimeoutError:
-                logger.warning(
-                    f"Failed to emit log to frontend: Timeout (connection may be broken)"
                 )
             except Exception as e:
-                logger.error(f"Failed to emit log to frontend: {type(e).__name__}: {e}")
+                logger.error(
+                    f"Failed to process log to frontend: {type(e).__name__}: {e}"
+                )
+
+    def _should_show_status(self, usage_ratio: float) -> bool:
+        """
+        Check if token usage status should be shown based on threshold.
+
+        Args:
+            usage_ratio: Current usage ratio (0.0 to 1.0)
+
+        Returns:
+            True if status should be shown, False otherwise
+        """
+        if not self.valves.show_token_usage_status:
+            return False
+
+        # If threshold is 0, always show
+        if self.valves.token_usage_status_threshold == 0:
+            return True
+
+        # Check if usage exceeds threshold
+        threshold_ratio = self.valves.token_usage_status_threshold / 100.0
+        return usage_ratio >= threshold_ratio
+
+    def _should_skip_compression(
+        self, body: dict, __model__: Optional[dict] = None
+    ) -> bool:
+        """
+        Check if compression should be skipped.
+        Returns True if:
+        1. The base model includes 'copilot_sdk'
+        """
+        # Check if base model includes copilot_sdk
+        if __model__:
+            base_model_id = __model__.get("base_model_id", "")
+            if "copilot_sdk" in base_model_id.lower():
+                return True
+
+        # Also check model in body
+        model_id = body.get("model", "")
+        if "copilot_sdk" in model_id.lower():
+            return True
+
+        return False
 
     async def inlet(
         self,
@@ -903,6 +1192,19 @@ class Filter:
         Compression Strategy: Only responsible for injecting existing summaries, no Token calculation.
         """
 
+        # Check if compression should be skipped (e.g., for copilot_sdk)
+        if self._should_skip_compression(body, __model__):
+            if self.valves.debug_mode:
+                logger.info(
+                    "[Inlet] Skipping compression: copilot_sdk detected in base model"
+                )
+            if self.valves.show_debug_log and __event_call__:
+                await self._log(
+                    "[Inlet] ⏭️ Skipping compression: copilot_sdk detected",
+                    event_call=__event_call__,
+                )
+            return body
+
         messages = body.get("messages", [])
 
         # --- Native Tool Output Trimming (Opt-in, only for native function calling) ---
@@ -966,8 +1268,14 @@ class Filter:
                                 final_answer = content[last_match_end:].strip()
 
                                 if final_answer:
-                                    msg["content"] = (
+                                    msg["content"] = self._get_translation(
-                                        f"... [Tool outputs trimmed]\n{final_answer}"
+                                        (
+                                            __user__.get("language", "en-US")
+                                            if __user__
+                                            else "en-US"
+                                        ),
+                                        "tool_trimmed",
+                                        content=final_answer,
                                     )
                                     trimmed_count += 1
                             else:
@@ -980,8 +1288,14 @@ class Filter:
                                 if len(parts) > 1:
                                     final_answer = parts[-1].strip()
                                     if final_answer:
-                                        msg["content"] = (
+                                        msg["content"] = self._get_translation(
-                                            f"... [Tool outputs trimmed]\n{final_answer}"
+                                            (
+                                                __user__.get("language", "en-US")
+                                                if __user__
+                                                else "en-US"
+                                            ),
+                                            "tool_trimmed",
+                                            content=final_answer,
                                         )
                                         trimmed_count += 1
 
@@ -1173,6 +1487,10 @@ class Filter:
         # Target is to compress up to the (total - keep_last) message
         target_compressed_count = max(0, len(messages) - self.valves.keep_last)
 
+        # Get user context for i18n
+        user_ctx = await self._get_user_context(__user__, __event_call__)
+        lang = user_ctx["user_language"]
+
         await self._log(
             f"[Inlet] Recorded target compression progress: {target_compressed_count}",
             event_call=__event_call__,
@@ -1207,10 +1525,9 @@ class Filter:
 
             # 2. Summary message (Inserted as Assistant message)
             summary_content = (
-                f"【Previous Summary: The following is a summary of the historical conversation, provided for context only. Do not reply to the summary content itself; answer the subsequent latest questions directly.】\n\n"
+                self._get_translation(lang, "summary_prompt_prefix")
-                f"{summary_record.summary}\n\n"
+                + f"{summary_record.summary}"
-                f"---\n"
+                + self._get_translation(lang, "summary_prompt_suffix")
-                f"Below is the recent conversation:"
             )
             summary_msg = {"role": "assistant", "content": summary_content}
 
@@ -1249,14 +1566,25 @@ class Filter:
                 "max_context_tokens", self.valves.max_context_tokens
             )
 
-            # Calculate total tokens
+            # --- Fast Estimation Check ---
+            estimated_tokens = self._estimate_messages_tokens(calc_messages)
+
+            # Since this is a hard limit check, only skip precise calculation if we are far below it (margin of 15%)
+            if estimated_tokens < max_context_tokens * 0.85:
+                total_tokens = estimated_tokens
+                await self._log(
+                    f"[Inlet] 🔎 Fast Preflight Check (Est): {total_tokens}t / {max_context_tokens}t (Well within limit)",
+                    event_call=__event_call__,
+                )
+            else:
+                # Calculate exact total tokens via tiktoken
                 total_tokens = await asyncio.to_thread(
                     self._calculate_messages_tokens, calc_messages
                 )
 
                 # Preflight Check Log
                 await self._log(
-                f"[Inlet] 🔎 Preflight Check: {total_tokens}t / {max_context_tokens}t ({(total_tokens/max_context_tokens*100):.1f}%)",
+                    f"[Inlet] 🔎 Precise Preflight Check: {total_tokens}t / {max_context_tokens}t ({(total_tokens/max_context_tokens*100):.1f}%)",
                     event_call=__event_call__,
                 )
 
@@ -1325,7 +1653,9 @@ class Filter:
                                 first_line_found = True
                                 # Add placeholder if there's more content coming
                                 if idx < last_line_idx:
-                                    kept_lines.append("\n... [Content collapsed] ...\n")
+                                    kept_lines.append(
+                                        self._get_translation(lang, "content_collapsed")
+                                    )
                                 continue
 
                             # Keep last non-empty line
@@ -1347,6 +1677,11 @@ class Filter:
                             target_msg["metadata"]["is_trimmed"] = True
 
                             # Calculate token reduction
+                            # Use current token strategy
+                            if total_tokens == estimated_tokens:
+                                old_tokens = len(content) // 4
+                                new_tokens = len(target_msg["content"]) // 4
+                            else:
                                 old_tokens = self._count_tokens(content)
                                 new_tokens = self._count_tokens(target_msg["content"])
                             diff = old_tokens - new_tokens
@@ -1362,7 +1697,12 @@ class Filter:
                     # Strategy 2: Fallback - Drop Oldest Message Entirely (FIFO)
                     # (User requested to remove progressive trimming for other cases)
                     dropped = tail_messages.pop(0)
-                    dropped_tokens = self._count_tokens(str(dropped.get("content", "")))
+                    if total_tokens == estimated_tokens:
+                        dropped_tokens = len(str(dropped.get("content", ""))) // 4
+                    else:
+                        dropped_tokens = self._count_tokens(
+                            str(dropped.get("content", ""))
+                        )
                     total_tokens -= dropped_tokens
 
                     if self.valves.show_debug_log and __event_call__:
@@ -1382,6 +1722,16 @@ class Filter:
             final_messages = candidate_messages
 
             # Calculate detailed token stats for logging
+            if total_tokens == estimated_tokens:
+                system_tokens = (
+                    len(system_prompt_msg.get("content", "")) // 4
+                    if system_prompt_msg
+                    else 0
+                )
+                head_tokens = self._estimate_messages_tokens(head_messages)
+                summary_tokens = len(summary_content) // 4
+                tail_tokens = self._estimate_messages_tokens(tail_messages)
+            else:
                 system_tokens = (
                     self._count_tokens(system_prompt_msg.get("content", ""))
                     if system_prompt_msg
@@ -1408,11 +1758,17 @@ class Filter:
             # Prepare status message (Context Usage format)
             if max_context_tokens > 0:
                 usage_ratio = total_section_tokens / max_context_tokens
-                status_msg = f"Context Usage (Estimated): {total_section_tokens} / {max_context_tokens} Tokens ({usage_ratio*100:.1f}%)"
+                # Only show status if threshold is met
+                if self._should_show_status(usage_ratio):
+                    status_msg = self._get_translation(
+                        lang,
+                        "status_context_usage",
+                        tokens=total_section_tokens,
+                        max_tokens=max_context_tokens,
+                        ratio=f"{usage_ratio*100:.1f}",
+                    )
                     if usage_ratio > 0.9:
-                    status_msg += " | ⚠️ High Usage"
+                        status_msg += self._get_translation(lang, "status_high_usage")
-            else:
-                status_msg = f"Loaded historical summary (Hidden {compressed_count} historical messages)"
 
                     if __event_emitter__:
                         await __event_emitter__(
@@ -1424,6 +1780,21 @@ class Filter:
                                 },
                             }
                         )
+            else:
+                # For the case where max_context_tokens is 0, show summary info without threshold check
+                if self.valves.show_token_usage_status and __event_emitter__:
+                    status_msg = self._get_translation(
+                        lang, "status_loaded_summary", count=compressed_count
+                    )
+                    await __event_emitter__(
+                        {
+                            "type": "status",
+                            "data": {
+                                "description": status_msg,
+                                "done": True,
+                            },
+                        }
+                    )
 
             # Emit debug log to frontend (Keep the structured log as well)
             await self._emit_debug_log(
@@ -1454,6 +1825,17 @@ class Filter:
                 "max_context_tokens", self.valves.max_context_tokens
             )
 
+            # --- Fast Estimation Check ---
+            estimated_tokens = self._estimate_messages_tokens(calc_messages)
+
+            # Only skip precise calculation if we are clearly below the limit
+            if estimated_tokens < max_context_tokens * 0.85:
+                total_tokens = estimated_tokens
+                await self._log(
+                    f"[Inlet] 🔎 Fast limit check (Est): {total_tokens}t / {max_context_tokens}t",
+                    event_call=__event_call__,
+                )
+            else:
                 total_tokens = await asyncio.to_thread(
                     self._calculate_messages_tokens, calc_messages
                 )
@@ -1476,7 +1858,12 @@ class Filter:
                     > start_trim_index + 1  # Keep at least 1 message after keep_first
                 ):
                     dropped = final_messages.pop(start_trim_index)
-                    dropped_tokens = self._count_tokens(str(dropped.get("content", "")))
+                    if total_tokens == estimated_tokens:
+                        dropped_tokens = len(str(dropped.get("content", ""))) // 4
+                    else:
+                        dropped_tokens = self._count_tokens(
+                            str(dropped.get("content", ""))
+                        )
                     total_tokens -= dropped_tokens
 
                 await self._log(
@@ -1485,14 +1872,21 @@ class Filter:
                 )
 
             # Send status notification (Context Usage format)
-            if __event_emitter__:
-                status_msg = f"Context Usage (Estimated): {total_tokens} / {max_context_tokens} Tokens"
             if max_context_tokens > 0:
                 usage_ratio = total_tokens / max_context_tokens
-                    status_msg += f" ({usage_ratio*100:.1f}%)"
+                # Only show status if threshold is met
+                if self._should_show_status(usage_ratio):
+                    status_msg = self._get_translation(
+                        lang,
+                        "status_context_usage",
+                        tokens=total_tokens,
+                        max_tokens=max_context_tokens,
+                        ratio=f"{usage_ratio*100:.1f}",
+                    )
                     if usage_ratio > 0.9:
-                        status_msg += " | ⚠️ High Usage"
+                        status_msg += self._get_translation(lang, "status_high_usage")
 
+                    if __event_emitter__:
                         await __event_emitter__(
                             {
                                 "type": "status",
@@ -1517,6 +1911,7 @@ class Filter:
         body: dict,
         __user__: Optional[dict] = None,
         __metadata__: dict = None,
+        __model__: dict = None,
         __event_emitter__: Callable[[Any], Awaitable[None]] = None,
         __event_call__: Callable[[Any], Awaitable[None]] = None,
     ) -> dict:
@@ -1524,6 +1919,23 @@ class Filter:
         Executed after the LLM response is complete.
         Calculates Token count in the background and triggers summary generation (does not block current response, does not affect content output).
         """
+        # Check if compression should be skipped (e.g., for copilot_sdk)
+        if self._should_skip_compression(body, __model__):
+            if self.valves.debug_mode:
+                logger.info(
+                    "[Outlet] Skipping compression: copilot_sdk detected in base model"
+                )
+            if self.valves.show_debug_log and __event_call__:
+                await self._log(
+                    "[Outlet] ⏭️ Skipping compression: copilot_sdk detected",
+                    event_call=__event_call__,
+                )
+            return body
+
+        # Get user context for i18n
+        user_ctx = await self._get_user_context(__user__, __event_call__)
+        lang = user_ctx["user_language"]
+
         chat_ctx = self._get_chat_context(body, __metadata__)
         chat_id = chat_ctx["chat_id"]
         if not chat_id:
@@ -1547,6 +1959,7 @@ class Filter:
                 body,
                 __user__,
                 target_compressed_count,
+                lang,
                 __event_emitter__,
                 __event_call__,
             )
@@ -1561,6 +1974,7 @@ class Filter:
         body: dict,
         user_data: Optional[dict],
         target_compressed_count: Optional[int],
+        lang: str = "en-US",
         __event_emitter__: Callable[[Any], Awaitable[None]] = None,
         __event_call__: Callable[[Any], Awaitable[None]] = None,
     ):
@@ -1595,27 +2009,48 @@ class Filter:
                 event_call=__event_call__,
             )
 
-            # Calculate Token count in a background thread
+            # --- Fast Estimation Check ---
+            estimated_tokens = self._estimate_messages_tokens(messages)
+
+            # For triggering summary generation, we need to be more precise if we are in the grey zone
+            # Margin is 15% (skip tiktoken if estimated is < 85% of threshold)
+            # Note: We still use tiktoken if we exceed threshold, because we want an accurate usage status report
+            if estimated_tokens < compression_threshold_tokens * 0.85:
+                current_tokens = estimated_tokens
+                await self._log(
+                    f"[🔍 Background Calculation] Fast estimate ({current_tokens}) is well below threshold ({compression_threshold_tokens}). Skipping tiktoken.",
+                    event_call=__event_call__,
+                )
+            else:
+                # Calculate Token count precisely in a background thread
                 current_tokens = await asyncio.to_thread(
                     self._calculate_messages_tokens, messages
                 )
-
                 await self._log(
-                f"[🔍 Background Calculation] Token count: {current_tokens}",
+                    f"[🔍 Background Calculation] Precise token count: {current_tokens}",
                     event_call=__event_call__,
                 )
 
             # Send status notification (Context Usage format)
-            if __event_emitter__ and self.valves.show_token_usage_status:
+            if __event_emitter__:
                 max_context_tokens = thresholds.get(
                     "max_context_tokens", self.valves.max_context_tokens
                 )
-                status_msg = f"Context Usage (Estimated): {current_tokens} / {max_context_tokens} Tokens"
                 if max_context_tokens > 0:
                     usage_ratio = current_tokens / max_context_tokens
-                    status_msg += f" ({usage_ratio*100:.1f}%)"
+                    # Only show status if threshold is met
+                    if self._should_show_status(usage_ratio):
+                        status_msg = self._get_translation(
+                            lang,
+                            "status_context_usage",
+                            tokens=current_tokens,
+                            max_tokens=max_context_tokens,
+                            ratio=f"{usage_ratio*100:.1f}",
+                        )
                         if usage_ratio > 0.9:
-                        status_msg += " | ⚠️ High Usage"
+                            status_msg += self._get_translation(
+                                lang, "status_high_usage"
+                            )
 
                         await __event_emitter__(
                             {
@@ -1642,6 +2077,7 @@ class Filter:
                     body,
                     user_data,
                     target_compressed_count,
+                    lang,
                     __event_emitter__,
                     __event_call__,
                 )
@@ -1672,6 +2108,7 @@ class Filter:
         body: dict,
         user_data: Optional[dict],
         target_compressed_count: Optional[int],
+        lang: str = "en-US",
         __event_emitter__: Callable[[Any], Awaitable[None]] = None,
         __event_call__: Callable[[Any], Awaitable[None]] = None,
     ):
@@ -1811,7 +2248,9 @@ class Filter:
                     {
                         "type": "status",
                         "data": {
-                            "description": "Generating context summary in background...",
+                            "description": self._get_translation(
+                                lang, "status_generating_summary"
+                            ),
                             "done": False,
                         },
                     }
@@ -1849,7 +2288,11 @@ class Filter:
                     {
                         "type": "status",
                         "data": {
-                            "description": f"Context summary updated (Compressed {len(middle_messages)} messages)",
+                            "description": self._get_translation(
+                                lang,
+                                "status_loaded_summary",
+                                count=len(middle_messages),
+                            ),
                             "done": True,
                         },
                     }
@@ -1910,10 +2353,9 @@ class Filter:
 
                     # Summary
                     summary_content = (
-                        f"【System Prompt: The following is a summary of the historical conversation, provided for context only. Do not reply to the summary content itself; answer the subsequent latest questions directly.】\n\n"
+                        self._get_translation(lang, "summary_prompt_prefix")
-                        f"{new_summary}\n\n"
+                        + f"{new_summary}"
-                        f"---\n"
+                        + self._get_translation(lang, "summary_prompt_suffix")
-                        f"Below is the recent conversation:"
                     )
                     summary_msg = {"role": "assistant", "content": summary_content}
 
@@ -1943,13 +2385,22 @@ class Filter:
                     max_context_tokens = thresholds.get(
                         "max_context_tokens", self.valves.max_context_tokens
                     )
-                    # 6. Emit Status
+                    # 6. Emit Status (only if threshold is met)
-                    status_msg = f"Context Summary Updated: {token_count} / {max_context_tokens} Tokens"
                     if max_context_tokens > 0:
-                        ratio = (token_count / max_context_tokens) * 100
+                        usage_ratio = token_count / max_context_tokens
-                        status_msg += f" ({ratio:.1f}%)"
+                        # Only show status if threshold is met
-                        if ratio > 90.0:
+                        if self._should_show_status(usage_ratio):
-                            status_msg += " | ⚠️ High Usage"
+                            status_msg = self._get_translation(
+                                lang,
+                                "status_context_summary_updated",
+                                tokens=token_count,
+                                max_tokens=max_context_tokens,
+                                ratio=f"{usage_ratio*100:.1f}",
+                            )
+                            if usage_ratio > 0.9:
+                                status_msg += self._get_translation(
+                                    lang, "status_high_usage"
+                                )
 
                             await __event_emitter__(
                                 {
@@ -1979,7 +2430,9 @@ class Filter:
                     {
                         "type": "status",
                         "data": {
-                            "description": f"Summary Error: {str(e)[:100]}...",
+                            "description": self._get_translation(
+                                lang, "status_summary_error", error=str(e)[:100]
+                            ),
                             "done": True,
                         },
                     }

plugins/pipes/github-copilot-sdk/README.md

@@ -1,6 +1,6 @@
 # GitHub Copilot SDK Pipe for OpenWebUI
 
-**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.6.2 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **License:** MIT
+**Author:** [Fu-Jie](https://github.com/Fu-Jie) | **Version:** 0.7.0 | **Project:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **License:** MIT
 
 This is an advanced Pipe function for [OpenWebUI](https://github.com/open-webui/open-webui) that integrates the official [GitHub Copilot SDK](https://github.com/github/copilot-sdk). It enables you to use **GitHub Copilot models** (e.g., `gpt-5.2-codex`, `claude-sonnet-4.5`,`gemini-3-pro`, `gpt-5-mini`) **AND** your own models via **BYOK** (OpenAI, Anthropic) directly within OpenWebUI, providing a unified agentic experience with **strict User & Chat-level Workspace Isolation**.
 
@@ -14,12 +14,13 @@ This is an advanced Pipe function for [OpenWebUI](https://github.com/open-webui/
 
 ---
 
-## ✨ v0.6.2 Updates (What's New)
+## ✨ v0.7.0 Updates (What's New)
 
-- **🛠️ New Workspace Artifacts Tool**: Introduced `publish_file_from_workspace`. Agents can now generate files (e.g., Python-generated Excel/CSV) and provide direct download links for the user to click and save.
+- **🚀 Integrated CLI Management**: The Copilot CLI is now automatically managed and bundled via the `github-copilot-sdk` pip package. No more manual `curl | bash` installation or version mismatches. (v0.7.0)
-- **⚙️ Workflow Optimization**: Improved reliability of the internal agentic workspace management.
+- **🧠 Native Tool Call UI**: Full adaptation to **OpenWebUI's native tool call UI** and thinking process visualization. (v0.7.0)
-- **🛡️ Enhanced Security**: Refined access control for system resources within the isolated environment.
+- **🏠 OpenWebUI v0.8.0+ Fix**: Resolved "Error getting file content" download failure by switching to absolute path registration for published files. (v0.7.0)
-- **🔧 Performance Tuning**: Optimized stream processing for larger context windows.
+- **🌐 Comprehensive Multi-language Support**: Native localization for status messages in 11 languages (EN, ZH, JA, KO, FR, DE, ES, IT, RU, VI, ID). (v0.7.0)
+- **🧹 Architecture Cleanup**: Refactored core setup and optimized reasoning status display for a leaner experience. (v0.7.0)
 
 ---
 
@@ -31,8 +32,8 @@ This is an advanced Pipe function for [OpenWebUI](https://github.com/open-webui/
 - **♾️ Infinite Session Management**: Smart context window management with automatic compaction for indefinite conversation capability.
 - **🧠 Deep Database Integration**: Real-time persistence of TOD·O lists for long-running workflows.
 - **🌊 Advanced Streaming**: Full support for thinking process/Chain of Thought visualization.
-- **🖼️ Intelligent Multimodal**: Vision capabilities and raw file analysis support.
+- **🖼️ Intelligent Multimodal**: Vision capabilities and raw file analysis support (bypasses RAG for direct binary access).
-- **⚡ Full-Lifecycle File Agent**: Supports receiving uploaded files for raw bypass analysis and publishing results (Excel/reports) as downloadable links.
+- **📤 Workspace Artifacts (`publish_file_from_workspace`)**: Agents can generate files (Excel, CSV, HTML reports, etc.) and provide **persistent download links** directly in the chat.
 - **🖼️ Interactive Artifacts**: Automatically renders HTML/JS apps generated by the agent directly in the chat interface.
 
 ---
@@ -110,7 +111,7 @@ If this plugin has been useful, a **Star** on [OpenWebUI Extensions](https://git
 
 - **Agent ignores files?**: Ensure the Files Filter is enabled, otherwise RAG will interfere with raw binaries.
 - **No progress bar?**: The bar only appears when the Agent uses the `update_todo` tool.
-- **Dependencies**: This Pipe automatically installs `github-copilot-sdk` (Python) and `github-copilot-cli` (Binary).
+- **Dependencies**: This Pipe automatically manages `github-copilot-sdk` (Python) and utilizes the bundled binary CLI. No manual install required.
 
 ---
 

plugins/pipes/github-copilot-sdk/README_CN.md

@@ -1,6 +1,6 @@
 # GitHub Copilot SDK 官方管道
 
-**作者:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **版本:** 0.6.2 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **许可证:** MIT
+**作者:** [Fu-Jie](https://github.com/Fu-Jie/openwebui-extensions) | **版本:** 0.7.0 | **项目:** [OpenWebUI Extensions](https://github.com/Fu-Jie/openwebui-extensions) | **许可证:** MIT
 
 这是一个用于 [OpenWebUI](https://github.com/open-webui/open-webui) 的高级 Pipe 函数，深度集成了 **GitHub Copilot SDK**。它不仅支持 **GitHub Copilot 官方模型**（如 `gpt-5.2-codex`, `claude-sonnet-4.5`, `gemini-3-pro`, `gpt-5-mini`），还支持 **BYOK (自带 Key)** 模式对接自定义服务商（OpenAI, Anthropic），并具备**严格的用户与会话级工作区隔离**能力，提供统一且安全的 Agent 交互体验。
 
@@ -14,12 +14,13 @@
 
 ---
 
-## ✨ 0.6.2 更新内容 (What's New)
+## ✨ 0.7.0 更新内容 (What's New)
 
-- **🛠️ 新增工作区产物工具**: 引入 `publish_file_from_workspace`。Agent 现在可以生成物理文件（如使用 Python 生成的 Excel/CSV 报表），并直接在聊天界面提供点击下载链接。
+- **🚀 CLI 免维护集成**: Copilot CLI 现在通过 `github-copilot-sdk` pip 包自动同步管理，彻底告别手动 `curl | bash` 安装及版本不匹配问题。(v0.7.0)
-- **⚙️ 工作流优化**: 提升了内部 Agent 物理工作区管理的可靠性与原子性。
+- **🧠 原生工具调用 UI**: 全面适配 **OpenWebUI 原生工具调用 UI** 与模型思考过程（思维链）展示。(v0.7.0)
-- **🛡️ 安全增强**: 精细化了隔离环境下系统资源的访问控制策略。
+- **🏠 OpenWebUI v0.8.0+ 兼容性修复**: 通过切换为绝对路径注册发布文件，彻底解决了“Error getting file content”无法下载到本地的问题。(v0.7.0)
-- **🔧 性能微调**: 针对大上下文窗口优化了流式数据处理性能。
+- **🌐 全面的多语言支持**: 针对状态消息进行了 11 国语言的原生本地化 (中/英/日/韩/法/德/西/意/俄/越/印尼)。(v0.7.0)
+- **🧹 架构精简**: 重构了初始化逻辑并优化了推理状态显示，提供更轻量稳健的体验。(v0.7.0)
 
 ---
 
@@ -31,8 +32,8 @@
 - **♾️ 无限会话管理**: 智能上下文窗口管理与自动压缩算法，支持无限时长的对话交互。
 - **🧠 深度数据库集成**: 实时持久化 TOD·O 列表到 UI 进度条。
 - **🌊 深度推理展示**: 完整支持模型思考过程 (Thinking Process) 的流式渲染。
-- **🖼️ 智能多模态**: 完整支持图像识别与附件上传分析。
+- **🖼️ 智能多模态**: 完整支持图像识别与附件上传分析（绕过 RAG 直接访问原始二进制内容）。
-- **⚡ 全生命周期文件 Agent**: 支持接收上传文件进行绕过 RAG 的深度分析，并将处理结果（如 Excel/报告）发布为下载链接。
+- **📤 工作区产物工具 (`publish_file_from_workspace`)**: Agent 可生成文件（Excel、CSV、HTML 报告等）并直接在聊天中提供**持久化下载链接**。
 - **🖼️ 交互式伪影 (Artifacts)**: 自动渲染 Agent 生成的 HTML/JS 应用程序，直接在聊天界面交互。
 
 ---
@@ -95,7 +96,7 @@
 ### 1) 导入函数
 
 1. 打开 OpenWebUI，前往 **工作区** -> **函数**。
-2. 点击 **+** (创建函数)，完整粘贴 `github_copilot_sdk_cn.py` 的内容。
+2. 点击 **+** (创建函数)，完整粘贴 `github_copilot_sdk.py` 的内容。
 3. 点击保存并确保已启用。
 
 ### 2) 获取 Token (Get Token)
@@ -114,7 +115,7 @@
 
 - **Agent 无法识别文件？**: 请确保已安装并启用了 Files Filter 插件，否则原始文件会被 RAG 干扰。
 - **看不到 TODO 进度条？**: 进度条仅在 Agent 使用 `update_todo` 工具（通常是处理复杂任务）时出现。
-- **依赖安装**: 本管道会自动尝试安装 `github-copilot-sdk` (Python 包) 和 `github-copilot-cli` (官方二进制)。
+- **依赖安装**: 本管道会自动管理 `github-copilot-sdk` (Python 包) 并优先直接使用内置的二进制 CLI，无需手动干预。
 
 ---
 

plugins/pipes/github-copilot-sdk/github_copilot_sdk.py

@@ -1,12 +1,12 @@
 """
 title: GitHub Copilot Official SDK Pipe
 author: Fu-Jie
-author_url: https://github.com/Fu-Jie/awesome-openwebui
+author_url: https://github.com/Fu-Jie/openwebui-extensions
 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, infinite sessions, and frontend debug logging.
-version: 0.6.2
+version: 0.7.0
-requirements: github-copilot-sdk==0.1.23
+requirements: github-copilot-sdk==0.1.25
 """
 
 import os
@@ -226,10 +226,7 @@ class Pipe:
             default=300,
             description="Timeout for each stream chunk (seconds)",
         )
-        COPILOT_CLI_VERSION: str = Field(
+
-            default="0.0.406",
-            description="Specific Copilot CLI version to install/enforce (e.g. '0.0.406'). Leave empty for latest.",
-        )
         EXCLUDE_KEYWORDS: str = Field(
             default="",
             description="Exclude models containing these keywords (comma separated, e.g.: codex, haiku)",
@@ -360,6 +357,116 @@ class Pipe:
     _env_setup_done = False  # Track if env setup has been completed
     _last_update_check = 0  # Timestamp of last CLI update check
 
+    TRANSLATIONS = {
+        "en-US": {
+            "status_conn_est": "Connection established, waiting for response...",
+            "status_reasoning_inj": "Reasoning Effort injected: {effort}",
+            "debug_agent_working_in": "Agent working in: {path}",
+            "debug_mcp_servers": "🔌 Connected MCP Servers: {servers}",
+            "publish_success": "File published successfully.",
+            "publish_hint_html": "Link: [View {filename}]({view_url}) | [Download]({download_url})",
+            "publish_hint_default": "Link: [Download {filename}]({download_url})",
+        },
+        "zh-CN": {
+            "status_conn_est": "已建立连接，等待响应...",
+            "status_reasoning_inj": "已注入推理级别：{effort}",
+            "debug_agent_working_in": "Agent 工作目录: {path}",
+            "debug_mcp_servers": "🔌 已连接 MCP 服务器: {servers}",
+            "publish_success": "文件发布成功。",
+            "publish_hint_html": "链接: [查看 {filename}]({view_url}) | [下载]({download_url})",
+            "publish_hint_default": "链接: [下载 {filename}]({download_url})",
+        },
+        "zh-HK": {
+            "status_conn_est": "已建立連接，等待響應...",
+            "status_reasoning_inj": "已注入推理級別：{effort}",
+            "debug_agent_working_in": "Agent 工作目錄: {path}",
+            "debug_mcp_servers": "🔌 已連接 MCP 伺服器: {servers}",
+            "publish_success": "文件發布成功。",
+            "publish_hint_html": "連結: [查看 {filename}]({view_url}) | [下載]({download_url})",
+            "publish_hint_default": "連結: [下載 {filename}]({download_url})",
+        },
+        "zh-TW": {
+            "status_conn_est": "已建立連接，等待響應...",
+            "status_reasoning_inj": "已注入推理級別：{effort}",
+            "debug_agent_working_in": "Agent 工作目錄: {path}",
+            "debug_mcp_servers": "🔌 已連接 MCP 伺服器: {servers}",
+            "publish_success": "文件發布成功。",
+            "publish_hint_html": "連結: [查看 {filename}]({view_url}) | [下載]({download_url})",
+            "publish_hint_default": "連結: [下載 {filename}]({download_url})",
+        },
+        "ja-JP": {
+            "status_conn_est": "接続が確立されました。応答を待っています...",
+            "status_reasoning_inj": "推論レベルが注入されました：{effort}",
+            "debug_agent_working_in": "Agent 作業ディレクトリ: {path}",
+            "debug_mcp_servers": "🔌 接続済み MCP サーバー: {servers}",
+        },
+        "ko-KR": {
+            "status_conn_est": "연결이 설정되었습니다. 응답을 기다리는 중...",
+            "status_reasoning_inj": "추론 수준 설정됨: {effort}",
+            "debug_agent_working_in": "Agent 작업 디렉토리: {path}",
+            "debug_mcp_servers": "🔌 연결된 MCP 서버: {servers}",
+        },
+        "fr-FR": {
+            "status_conn_est": "Connexion établie, en attente de réponse...",
+            "status_reasoning_inj": "Effort de raisonnement injecté : {effort}",
+            "debug_agent_working_in": "Répertoire de travail de l'Agent : {path}",
+            "debug_mcp_servers": "🔌 Serveurs MCP connectés : {servers}",
+        },
+        "de-DE": {
+            "status_conn_est": "Verbindung hergestellt, warte auf Antwort...",
+            "status_reasoning_inj": "Argumentationsaufwand injiziert: {effort}",
+            "debug_agent_working_in": "Agent-Arbeitsverzeichnis: {path}",
+            "debug_mcp_servers": "🔌 Verbundene MCP-Server: {servers}",
+        },
+        "es-ES": {
+            "status_conn_est": "Conexión establecida, esperando respuesta...",
+            "status_reasoning_inj": "Nivel de razonamiento inyectado: {effort}",
+            "debug_agent_working_in": "Directorio de trabajo del Agente: {path}",
+            "debug_mcp_servers": "🔌 Servidores MCP conectados: {servers}",
+        },
+        "it-IT": {
+            "status_conn_est": "Connessione stabilita, in attesa di risposta...",
+            "status_reasoning_inj": "Livello di ragionamento iniettato: {effort}",
+            "debug_agent_working_in": "Directory di lavoro dell'Agente: {path}",
+            "debug_mcp_servers": "🔌 Server MCP connessi: {servers}",
+        },
+        "ru-RU": {
+            "status_conn_est": "Соединение установлено, ожидание ответа...",
+            "status_reasoning_inj": "Уровень рассуждения внедрен: {effort}",
+            "debug_agent_working_in": "Рабочий каталог Агента: {path}",
+            "debug_mcp_servers": "🔌 Подключенные серверы MCP: {servers}",
+        },
+        "vi-VN": {
+            "status_conn_est": "Đã thiết lập kết nối, đang chờ phản hồi...",
+            "status_reasoning_inj": "Cấp độ suy luận đã được áp dụng: {effort}",
+            "debug_agent_working_in": "Thư mục làm việc của Agent: {path}",
+            "debug_mcp_servers": "🔌 Các máy chủ MCP đã kết nối: {servers}",
+        },
+        "id-ID": {
+            "status_conn_est": "Koneksi terjalin, menunggu respons...",
+            "status_reasoning_inj": "Tingkat penalaran diterapkan: {effort}",
+            "debug_agent_working_in": "Direktori kerja Agent: {path}",
+            "debug_mcp_servers": "🔌 Server MCP yang terhubung: {servers}",
+        },
+    }
+
+    FALLBACK_MAP = {
+        "zh": "zh-CN",
+        "zh-TW": "zh-TW",
+        "zh-HK": "zh-HK",
+        "en": "en-US",
+        "en-GB": "en-US",
+        "ja": "ja-JP",
+        "ko": "ko-KR",
+        "fr": "fr-FR",
+        "de": "de-DE",
+        "es": "es-ES",
+        "it": "it-IT",
+        "ru": "ru-RU",
+        "vi": "vi-VN",
+        "id": "id-ID",
+    }
+
     def __init__(self):
         self.type = "pipe"
         self.id = "github_copilot_sdk"
@@ -390,6 +497,83 @@ class Pipe:
         except Exception as e:
             logger.error(f"[Database] ❌ Initialization failed: {str(e)}")
 
+    def _resolve_language(self, user_language: str) -> str:
+        """Normalize user language code to a supported translation key."""
+        if not user_language:
+            return "en-US"
+        if user_language in self.TRANSLATIONS:
+            return user_language
+        lang_base = user_language.split("-")[0]
+        if user_language in self.FALLBACK_MAP:
+            return self.FALLBACK_MAP[user_language]
+        if lang_base in self.FALLBACK_MAP:
+            return self.FALLBACK_MAP[lang_base]
+        return "en-US"
+
+    def _get_translation(self, lang: str, key: str, **kwargs) -> str:
+        """Helper function to get translated string for a key."""
+        lang_key = self._resolve_language(lang)
+        trans_map = self.TRANSLATIONS.get(lang_key, self.TRANSLATIONS["en-US"])
+        text = trans_map.get(key, self.TRANSLATIONS["en-US"].get(key, key))
+        if kwargs:
+            try:
+                text = text.format(**kwargs)
+            except Exception as e:
+                logger.warning(f"Translation formatting failed for {key}: {e}")
+        return text
+
+    async def _get_user_context(self, __user__, __event_call__=None, __request__=None):
+        """Extract basic user context with safe fallbacks including JS localStorage."""
+        if isinstance(__user__, (list, tuple)):
+            user_data = __user__[0] if __user__ else {}
+        elif isinstance(__user__, dict):
+            user_data = __user__
+        else:
+            user_data = {}
+
+        user_id = user_data.get("id", "unknown_user")
+        user_name = user_data.get("name", "User")
+        user_language = user_data.get("language", "en-US")
+
+        if (
+            __request__
+            and hasattr(__request__, "headers")
+            and "accept-language" in __request__.headers
+        ):
+            raw_lang = __request__.headers.get("accept-language", "")
+            if raw_lang:
+                user_language = raw_lang.split(",")[0].split(";")[0]
+
+        if __event_call__:
+            try:
+                js_code = """
+                    try {
+                        return (
+                            document.documentElement.lang ||
+                            localStorage.getItem('locale') || 
+                            localStorage.getItem('language') || 
+                            navigator.language || 
+                            'en-US'
+                        );
+                    } catch (e) {
+                        return 'en-US';
+                    }
+                """
+                frontend_lang = await asyncio.wait_for(
+                    __event_call__({"type": "execute", "data": {"code": js_code}}),
+                    timeout=2.0,
+                )
+                if frontend_lang and isinstance(frontend_lang, str):
+                    user_language = frontend_lang
+            except Exception as e:
+                pass
+
+        return {
+            "user_id": user_id,
+            "user_name": user_name,
+            "user_language": user_language,
+        }
+
     @contextlib.contextmanager
     def _db_session(self):
         """Yield a database session using Open WebUI helpers with graceful fallbacks."""
@@ -611,6 +795,8 @@ class Pipe:
             user_data = {}
 
         user_id = user_data.get("id") or user_data.get("user_id")
+        user_lang = user_data.get("language") or "en-US"
+        is_admin = user_data.get("role") == "admin"
         if not user_id:
             return None
 
@@ -746,9 +932,6 @@ class Pipe:
                     dest_path = Path(UPLOAD_DIR) / f"{file_id}_{safe_filename}"
                     await asyncio.to_thread(shutil.copy2, target_path, dest_path)
 
-                    try:
-                        db_path = str(os.path.relpath(dest_path, DATA_DIR))
-                    except:
                     db_path = str(dest_path)
 
                     file_form = FileForm(
@@ -769,12 +952,37 @@ class Pipe:
 
                 # 5. Result
                 download_url = f"/api/v1/files/{file_id}/content"
+                view_url = download_url
+                is_html = safe_filename.lower().endswith(".html")
+
+                # For HTML files, if user is admin, provide a direct view link (/content/html)
+                if is_html and is_admin:
+                    view_url = f"{download_url}/html"
+
+                # Localized output
+                msg = self._get_translation(user_lang, "publish_success")
+                if is_html and is_admin:
+                    hint = self._get_translation(
+                        user_lang,
+                        "publish_hint_html",
+                        filename=safe_filename,
+                        view_url=view_url,
+                        download_url=download_url,
+                    )
+                else:
+                    hint = self._get_translation(
+                        user_lang,
+                        "publish_hint_default",
+                        filename=safe_filename,
+                        download_url=download_url,
+                    )
+
                 return {
                     "file_id": file_id,
                     "filename": safe_filename,
                     "download_url": download_url,
-                    "message": "File published successfully.",
+                    "message": msg,
-                    "hint": f"Link: [Download {safe_filename}]({download_url})",
+                    "hint": hint,
                 }
             except Exception as e:
                 return {"error": str(e)}
@@ -1921,10 +2129,6 @@ class Pipe:
             "on_post_tool_use": on_post_tool_use,
         }
 
-    def _get_user_context(self):
-        """Helper to get user context (placeholder for future use)."""
-        return {}
-
     def _get_chat_context(
         self,
         body: dict,
@@ -2327,25 +2531,11 @@ class Pipe:
         token: str = None,
         enable_mcp: bool = True,
         enable_cache: bool = True,
-        skip_cli_install: bool = False,
+        skip_cli_install: bool = False,  # Kept for call-site compatibility, no longer used
         __event_emitter__=None,
+        user_lang: str = "en-US",
     ):
-        """Setup environment variables and verify Copilot CLI. Dynamic Token Injection."""
+        """Setup environment variables and resolve Copilot CLI path from SDK bundle."""
-        def emit_status_sync(description: str, done: bool = False):
-            if not __event_emitter__:
-                return
-            try:
-                loop = asyncio.get_running_loop()
-                loop.create_task(
-                    __event_emitter__(
-                        {
-                            "type": "status",
-                            "data": {"description": description, "done": done},
-                        }
-                    )
-                )
-            except Exception:
-                pass
 
         # 1. Real-time Token Injection (Always updates on each call)
         effective_token = token or self.valves.GH_TOKEN
@@ -2353,8 +2543,6 @@ class Pipe:
             os.environ["GH_TOKEN"] = os.environ["GITHUB_TOKEN"] = effective_token
 
         if self._env_setup_done:
-            # If done, we only sync MCP if called explicitly or in debug mode
-            # To improve speed, we avoid redundant file I/O here for regular requests
             if debug_enabled:
                 self._sync_mcp_config(
                     __event_call__,
@@ -2365,186 +2553,46 @@ class Pipe:
             return
 
         os.environ["COPILOT_AUTO_UPDATE"] = "false"
-        self._emit_debug_log_sync(
-            "Disabled CLI auto-update (COPILOT_AUTO_UPDATE=false)",
-            __event_call__,
-            debug_enabled=debug_enabled,
-        )
 
-        # 2. CLI Path Discovery
+        # 2. CLI Path Discovery (priority: env var > PATH > SDK bundle)
-        cli_path = "/usr/local/bin/copilot"
+        cli_path = os.environ.get("COPILOT_CLI_PATH", "")
-        if os.environ.get("COPILOT_CLI_PATH"):
+        found = bool(cli_path and os.path.exists(cli_path))
-            cli_path = os.environ["COPILOT_CLI_PATH"]
-
-        target_version = self.valves.COPILOT_CLI_VERSION.strip()
-        found = False
-        current_version = None
-
-        def get_cli_version(path):
-            try:
-                output = (
-                    subprocess.check_output(
-                        [path, "--version"], stderr=subprocess.STDOUT
-                    )
-                    .decode()
-                    .strip()
-                )
-                import re
-
-                match = re.search(r"(\d+\.\d+\.\d+)", output)
-                return match.group(1) if match else output
-            except Exception:
-                return None
-
-        # Check existing version
-        if os.path.exists(cli_path):
-            found = True
-            current_version = get_cli_version(cli_path)
 
         if not found:
             sys_path = shutil.which("copilot")
             if sys_path:
                 cli_path = sys_path
                 found = True
-                current_version = get_cli_version(cli_path)
 
         if not found:
-            pkg_path = os.path.join(os.path.dirname(__file__), "bin", "copilot")
+            try:
-            if os.path.exists(pkg_path):
+                from copilot.client import _get_bundled_cli_path
-                cli_path = pkg_path
+
+                bundled_path = _get_bundled_cli_path()
+                if bundled_path and os.path.exists(bundled_path):
+                    cli_path = bundled_path
                     found = True
-                current_version = get_cli_version(cli_path)
+            except ImportError:
-
-        # 3. Installation/Update Logic
-        should_install = not found
-        install_reason = "CLI not found"
-        if found and target_version:
-            norm_target = target_version.lstrip("v")
-            norm_current = current_version.lstrip("v") if current_version else ""
-
-            # Only install if target version is GREATER than current version
-            try:
-                from packaging.version import parse as parse_version
-
-                if parse_version(norm_target) > parse_version(norm_current):
-                    should_install = True
-                    install_reason = (
-                        f"Upgrade needed ({current_version} -> {target_version})"
-                    )
-                elif parse_version(norm_target) < parse_version(norm_current):
-                    self._emit_debug_log_sync(
-                        f"Current version ({current_version}) is newer than specified ({target_version}). Skipping downgrade.",
-                        __event_call__,
-                        debug_enabled=debug_enabled,
-                    )
-            except Exception as e:
-                # Fallback to string comparison if packaging is not available
-                if norm_target != norm_current:
-                    should_install = True
-                    install_reason = (
-                        f"Version mismatch ({current_version} != {target_version})"
-                    )
-
-        if should_install and not skip_cli_install:
-            self._emit_debug_log_sync(
-                f"Installing/Updating Copilot CLI: {install_reason}...",
-                __event_call__,
-                debug_enabled=debug_enabled,
-            )
-            emit_status_sync(
-                "🔧 正在安装/更新 Copilot CLI（首次可能需要 1-3 分钟）...",
-                done=False,
-            )
-            try:
-                env = os.environ.copy()
-                if target_version:
-                    env["VERSION"] = target_version
-                proc = subprocess.Popen(
-                    "curl -fsSL https://gh.io/copilot-install | bash",
-                    shell=True,
-                    stdout=subprocess.PIPE,
-                    stderr=subprocess.STDOUT,
-                    text=True,
-                    bufsize=1,
-                    env=env,
-                )
-
-                progress_percent = -1
-                line_count = 0
-                while True:
-                    raw_line = proc.stdout.readline() if proc.stdout else ""
-                    if raw_line == "" and proc.poll() is not None:
-                        break
-
-                    line = (raw_line or "").strip()
-                    if not line:
-                        continue
-
-                    line_count += 1
-                    percent_match = re.search(r"(\d{1,3})%", line)
-                    if percent_match:
-                        try:
-                            pct = int(percent_match.group(1))
-                            if pct >= progress_percent + 5:
-                                progress_percent = pct
-                                emit_status_sync(
-                                    f"📦 Copilot CLI 安装中：{pct}%", done=False
-                                )
-                        except Exception:
                 pass
-                    elif line_count % 20 == 0:
-                        emit_status_sync(
-                            f"📦 Copilot CLI 安装中：{line[:120]}", done=False
-                        )
 
-                return_code = proc.wait()
+        # 3. Finalize
-                if return_code != 0:
+        cli_ready = found
-                    raise subprocess.CalledProcessError(
-                        return_code,
-                        "curl -fsSL https://gh.io/copilot-install | bash",
-                    )
-
-                # Re-verify
-                current_version = get_cli_version(cli_path)
-                emit_status_sync(
-                    f"✅ Copilot CLI 安装完成（v{current_version or target_version or 'latest'}）",
-                    done=False,
-                )
-            except Exception as e:
-                self._emit_debug_log_sync(
-                    f"CLI installation failed: {e}",
-                    __event_call__,
-                    debug_enabled=debug_enabled,
-                )
-                emit_status_sync(
-                    f"❌ Copilot CLI 安装失败：{str(e)[:120]}",
-                    done=True,
-                )
-        elif should_install and skip_cli_install:
-            self._emit_debug_log_sync(
-                f"Skipping CLI install during model listing: {install_reason}",
-                __event_call__,
-                debug_enabled=debug_enabled,
-            )
-
-        # 4. Finalize
-        cli_ready = bool(cli_path and os.path.exists(cli_path))
         if cli_ready:
             os.environ["COPILOT_CLI_PATH"] = cli_path
+            # Add the CLI's parent directory to PATH so subprocesses can invoke `copilot` directly
+            cli_bin_dir = os.path.dirname(cli_path)
+            current_path = os.environ.get("PATH", "")
+            if cli_bin_dir and cli_bin_dir not in current_path.split(os.pathsep):
+                os.environ["PATH"] = cli_bin_dir + os.pathsep + current_path
 
         self.__class__._env_setup_done = cli_ready
         self.__class__._last_update_check = datetime.now().timestamp()
 
         self._emit_debug_log_sync(
-            f"Environment setup complete. CLI ready={cli_ready}. Path: {cli_path} (v{current_version})",
+            f"Environment setup complete. CLI ready={cli_ready}. Path: {cli_path}",
             __event_call__,
             debug_enabled=debug_enabled,
         )
-        if not skip_cli_install:
-            if cli_ready:
-                emit_status_sync("✅ Copilot CLI 已就绪", done=True)
-            else:
-                emit_status_sync("⚠️ Copilot CLI 尚未就绪，请稍后重试。", done=True)
 
     def _process_attachments(
         self,
@@ -2822,6 +2870,9 @@ class Pipe:
         effective_mcp = user_valves.ENABLE_MCP_SERVER
         effective_cache = user_valves.ENABLE_TOOL_CACHE
 
+        user_ctx = await self._get_user_context(__user__, __event_call__, __request__)
+        user_lang = user_ctx["user_language"]
+
         # 2. Setup environment with effective settings
         self._setup_env(
             __event_call__,
@@ -2830,11 +2881,12 @@ class Pipe:
             enable_mcp=effective_mcp,
             enable_cache=effective_cache,
             __event_emitter__=__event_emitter__,
+            user_lang=user_lang,
         )
 
         cwd = self._get_workspace_dir(user_id=user_id, chat_id=chat_id)
         await self._emit_debug_log(
-            f"Agent working in: {cwd} (Admin: {is_admin}, MCP: {effective_mcp})",
+            f"{self._get_translation(user_lang, 'debug_agent_working_in', path=cwd)} (Admin: {is_admin}, MCP: {effective_mcp})",
             __event_call__,
             debug_enabled=effective_debug,
         )
@@ -3269,9 +3321,9 @@ class Pipe:
             if body.get("stream", False):
                 init_msg = ""
                 if effective_debug:
-                    init_msg = f"> [Debug] Agent working in: {self._get_workspace_dir(user_id=user_id, chat_id=chat_id)}\n"
+                    init_msg = f"> [Debug] {self._get_translation(user_lang, 'debug_agent_working_in', path=self._get_workspace_dir(user_id=user_id, chat_id=chat_id))}\n"
                     if mcp_server_names:
-                        init_msg += f"> [Debug] 🔌 Connected MCP Servers: {', '.join(mcp_server_names)}\n"
+                        init_msg += f"> [Debug] {self._get_translation(user_lang, 'debug_mcp_servers', servers=', '.join(mcp_server_names))}\n"
 
                 # Transfer client ownership to stream_response
                 should_stop_client = False
@@ -3284,9 +3336,14 @@ class Pipe:
                     init_message=init_msg,
                     __event_call__=__event_call__,
                     __event_emitter__=__event_emitter__,
-                    reasoning_effort=effective_reasoning_effort,
+                    reasoning_effort=(
+                        effective_reasoning_effort
+                        if (is_reasoning and not is_byok_model)
+                        else "off"
+                    ),
                     show_thinking=show_thinking,
                     debug_enabled=effective_debug,
+                    user_lang=user_lang,
                 )
             else:
                 try:
@@ -3332,6 +3389,7 @@ class Pipe:
         reasoning_effort: str = "",
         show_thinking: bool = True,
         debug_enabled: bool = False,
+        user_lang: str = "en-US",
     ) -> AsyncGenerator:
         """
         Stream response from Copilot SDK, handling various event types.
@@ -3476,14 +3534,8 @@ class Pipe:
                     queue.put_nowait("\n</think>\n")
                     state["thinking_started"] = False
 
-                # Display tool call with improved formatting
+                # Note: We do NOT emit a done="false" card here to avoid card duplication
-                if tool_args:
+                # (unless we have a way to update text which SSE content stream doesn't)
-                    tool_args_json = json.dumps(tool_args, indent=2, ensure_ascii=False)
-                    tool_display = f"\n\n<details>\n<summary>🔧 Executing Tool: {tool_name}</summary>\n\n**Parameters:**\n\n```json\n{tool_args_json}\n```\n\n</details>\n\n"
-                else:
-                    tool_display = f"\n\n<details>\n<summary>🔧 Executing Tool: {tool_name}</summary>\n\n*No parameters*\n\n</details>\n\n"
-
-                queue.put_nowait(tool_display)
 
                 self._emit_debug_log_sync(
                     f"Tool Start: {tool_name}",
@@ -3600,31 +3652,55 @@ class Pipe:
                             )
                     # ------------------------
 
-                    # Try to detect content type for better formatting
+                    # --- Build native OpenWebUI 0.8.3 tool_calls block ---
-                    is_json = False
+                    # Serialize input args (from execution_start)
+                    tool_args_for_block = {}
+                    if tool_call_id and tool_call_id in active_tools:
+                        tool_args_for_block = active_tools[tool_call_id].get(
+                            "arguments", {}
+                        )
+
                     try:
-                        json_obj = (
+                        args_json_str = json.dumps(
-                            json.loads(result_content)
+                            tool_args_for_block, ensure_ascii=False
-                            if isinstance(result_content, str)
-                            else result_content
                         )
-                        if isinstance(json_obj, (dict, list)):
+                    except Exception:
-                            result_content = json.dumps(
+                        args_json_str = "{}"
-                                json_obj, indent=2, ensure_ascii=False
+
+                    def escape_html_attr(s: str) -> str:
+                        if not isinstance(s, str):
+                            return ""
+                        return (
+                            str(s)
+                            .replace("&", "&amp;")
+                            .replace("<", "&lt;")
+                            .replace(">", "&gt;")
+                            .replace('"', "&quot;")
+                            .replace("\n", "&#10;")
+                            .replace("\r", "&#13;")
                         )
-                            is_json = True
-                    except:
-                        pass
 
-                    # Format based on content type
+                    # MUST escape both arguments and result with &quot; and &#10; to satisfy OpenWebUI's strict regex /="([^"]*)"/
-                    if is_json:
+                    # OpenWebUI `marked` extension does not match multiline attributes properly without &#10;
-                        # JSON content: use code block with syntax highlighting
+                    args_for_attr = (
-                        result_display = f"\n<details>\n<summary>{status_icon} Tool Result: {tool_name}</summary>\n\n```json\n{result_content}\n```\n\n</details>\n\n"
+                        escape_html_attr(args_json_str) if args_json_str else "{}"
-                    else:
+                    )
-                        # Plain text: use text code block to preserve formatting and add line breaks
+                    result_for_attr = escape_html_attr(result_content)
-                        result_display = f"\n<details>\n<summary>{status_icon} Tool Result: {tool_name}</summary>\n\n```text\n{result_content}\n```\n\n</details>\n\n"
 
-                    queue.put_nowait(result_display)
+                    # Emit the unified native tool_calls block:
+                    # OpenWebUI 0.8.3 frontend regex explicitly expects: name="xxx" arguments="..." result="..." done="true"
+                    # CRITICAL: <details> tag MUST be followed immediately by \n for the frontend Markdown extension to parse it!
+                    tool_block = (
+                        f'\n<details type="tool_calls"'
+                        f' id="{tool_call_id}"'
+                        f' name="{tool_name}"'
+                        f' arguments="{args_for_attr}"'
+                        f' result="{result_for_attr}"'
+                        f' done="true">\n'
+                        f"<summary>Tool Executed</summary>\n"
+                        f"</details>\n\n"
+                    )
+                    queue.put_nowait(tool_block)
 
             elif event_type == "tool.execution_progress":
                 # Tool execution progress update (for long-running tools)
@@ -3725,20 +3801,42 @@ class Pipe:
 
         # Safe initial yield with error handling
         try:
-            if debug_enabled and show_thinking:
+            if debug_enabled and __event_emitter__:
-                yield "<think>\n"
+                # Emit debug info as UI status rather than reasoning block
+                async def _emit_status(key: str, desc: str = None, **kwargs):
+                    try:
+                        final_desc = (
+                            desc
+                            if desc
+                            else self._get_translation(user_lang, key, **kwargs)
+                        )
+                        await __event_emitter__(
+                            {
+                                "type": "status",
+                                "data": {"description": final_desc, "done": True},
+                            }
+                        )
+                    except:
+                        pass
+
                 if init_message:
-                    yield init_message
+                    for line in init_message.split("\n"):
+                        if line.strip():
+                            clean_msg = line.replace("> [Debug] ", "").strip()
+                            asyncio.create_task(_emit_status("custom", desc=clean_msg))
 
                 if reasoning_effort and reasoning_effort != "off":
-                    yield f"> [Debug] Reasoning Effort injected: {reasoning_effort.upper()}\n"
+                    asyncio.create_task(
+                        _emit_status(
+                            "status_reasoning_inj", effort=reasoning_effort.upper()
+                        )
+                    )
 
-                yield "> [Debug] Connection established, waiting for response...\n"
+                asyncio.create_task(_emit_status("status_conn_est"))
-                state["thinking_started"] = True
         except Exception as e:
             # If initial yield fails, log but continue processing
             self._emit_debug_log_sync(
-                f"Initial yield warning: {e}",
+                f"Initial status warning: {e}",
                 __event_call__,
                 debug_enabled=debug_enabled,
             )
@@ -3766,12 +3864,21 @@ class Pipe:
                 except asyncio.TimeoutError:
                     if done.is_set():
                         break
-                    if state["thinking_started"]:
+                    if __event_emitter__ and debug_enabled:
                         try:
-                            yield f"> [Debug] Waiting for response ({self.valves.TIMEOUT}s exceeded)...\n"
+                            asyncio.create_task(
+                                __event_emitter__(
+                                    {
+                                        "type": "status",
+                                        "data": {
+                                            "description": f"Waiting for response ({self.valves.TIMEOUT}s exceeded)...",
+                                            "done": True,
+                                        },
+                                    }
+                                )
+                            )
                         except:
-                            # If yield fails during timeout, connection is gone
+                            pass
-                            break
                     continue
 
             while not queue.empty():

plugins/pipes/github-copilot-sdk/v0.7.0.md

@@ -0,0 +1,82 @@
+# GitHub Copilot SDK Pipe v0.7.0
+
+**GitHub Copilot SDK Pipe v0.7.0** — A major infrastructure and UX upgrade. This release eliminates manual CLI management, fully embraces OpenWebUI's native tool calling interface, and ensures seamless compatibility with the latest OpenWebUI versions.
+
+---
+
+## 📦 Quick Installation
+
+- **GitHub Copilot SDK (Pipe)**: [Install v0.7.0](https://openwebui.com/posts/ce96f7b4-12fc-4ac3-9a01-875713e69359)
+- **GitHub Copilot SDK (Filter)**: [Install v0.1.2](https://openwebui.com/posts/403a62ee-a596-45e7-be65-fab9cc249dd6)
+
+---
+
+## 🚀 What's New in v0.7.0
+
+### 1. Zero-Maintenance CLI Integration
+
+The most significant infrastructure change: you no longer need to worry about CLI versions or background downloads.
+
+| Before (v0.6.x) | After (v0.7.0) |
+| :--- | :--- |
+| CLI installed via background `curl \| bash` | CLI bundled inside the `github-copilot-sdk` pip package |
+| Version mismatches between SDK and CLI | Versions are always in sync automatically |
+| Fails in restricted networks | Works everywhere `pip install` works |
+
+**How it works**: When you install `github-copilot-sdk==0.1.25`, the matching `copilot-cli v0.0.411` is included. The plugin auto-discovers the path and injects it into the environment—zero configuration required.
+
+### 2. Native OpenWebUI Tool Call UI
+
+Tool calls from Copilot agents now render using **OpenWebUI's built-in tool call UI**.
+
+- Tool execution status is displayed natively in the chat interface.
+- Thinking processes (Chain of Thought) are visualized with the standard collapsible UI.
+- Improved visual consistency and integration with the main OpenWebUI interface.
+
+### 3. OpenWebUI v0.8.0+ Compatibility Fix (Bug Fix)
+
+Resolved the **"Error getting file content"** failure that affected users on OpenWebUI v0.8.0 and later.
+
+- **The Issue**: Relative path registration for published files was rejected by the latest OpenWebUI versions.
+- **The Fix**: Switched to **absolute path registration**, restoring the ability to download generated artifacts to your local machine.
+
+### 4. Comprehensive Multi-language Support (i18n)
+
+Native localization for status messages and UI hints in **11 languages**:
+*English, Chinese (Simp/Trad/HK/TW), Japanese, Korean, French, German, Spanish, Italian, Russian, Vietnamese, and Indonesian.*
+
+### 5. Reasoning Status & UX Optimizations
+
+- **Intelligent Status Display**: `Reasoning Effort injected` status is now only shown for native Copilot reasoning models.
+- **Clean UI**: Removed redundant debug/status noise for BYOK and standard models.
+- **Architecture Cleanup**: Refactored core setup and removed legacy installation code for a robust "one-click" experience.
+
+---
+
+## 🛠️ Key Capabilities
+
+| Feature | Description |
+| :--- | :--- |
+| **Universal Tool Protocol** | Native support for **MCP**, **OpenAPI**, and **OpenWebUI built-in tools**. |
+| **Native Tool Call UI** | Adapted to OpenWebUI's built-in tool call rendering. |
+| **Workspace Isolation** | Strict sandboxing for per-session data privacy and security. |
+| **Workspace Artifacts** | Agents generate files (Excel/CSV/HTML) with persistent download links via `publish_file_from_workspace`. |
+| **Tool Execution** | Direct access to system binaries (Python, FFmpeg, Git, etc.). |
+| **11-Language Localization** | Auto-detected, native status messages for global users. |
+| **OpenWebUI v0.8.0+ Support** | Robust file handling for the latest OpenWebUI platform versions. |
+
+---
+
+## 📥 Import Chat Templates
+
+- [📥 Star Prediction Chat log](https://fu-jie.github.io/awesome-openwebui/plugins/pipes/star-prediction-chat.json)
+- [📥 Video Processing Chat log](https://fu-jie.github.io/awesome-openwebui/plugins/pipes/video-processing-chat.json)
+
+*Settings -> Data -> Import Chats.*
+
+---
+
+## 🔗 Resources
+
+- **GitHub Repository**: [openwebui-extensions](https://github.com/Fu-Jie/openwebui-extensions)
+- **Full Changelog**: [README.md](https://github.com/Fu-Jie/openwebui-extensions/blob/main/plugins/pipes/github-copilot-sdk/README.md)